- 1 Value flows in energy system and in smart meter roll-out – scaled to ‘Bristol scale’
- 2 Understanding markets where value is traded (capacity, balancing etc)
- 2.1 The Capacity Market
- 2.2 Balancing and Settlement
- 2.3 Electricity Network Charges
- 2.4 Gas Network Charges
- 3 Understanding value created by smart energy response and management of system at city scale (and how that will change over time)
- 3.1 The value of smart meters
- 3.2 Demand Side Measures
- 3.3 Distributed Energy Resources (DER)
- 3.4 Storage
- 3.5 Realising the DSR potential at the customer level
- 3.6 Realising the DSR potential at the grid level
- 3.7 How value of smart energy response and smart grids will change over time
- 3.8 The Local Scale
- 4 Understanding potential financial value of using smart energy data in other services (e.g. health improvement – thermal safeguarding etc)
- 5 Energy supplier smart meter roll-out plans and potential for securing integrated city-wide approach
- 6 Potential business models for city-wide approach
- 6.1 Project SoLa BRISTOL (Buildings, Renewables and Integrated Storage with Tariffs to Overcome network Limitations)
- 6.2 Project FALCON (Flexible Approaches for Low Carbon Optimised Networks)
- 6.3 LEMMA (Local Energy Markets Modelling and Analysis)
- 6.4 Wadebridge Renewable Energy Network (WREN)
- 6.5 EcoGrid EU (Bonholm, Denmark)
- 6.6 NOBEL (Neighbourhood Oriented Brokerage Electricity and Monitoring System)
- 6.7 Power Matching City - Hoogkerk, Netherlands
- 6.8 Mulheim's Into Metering
- 6.9 ADDRESS (Active Distribution networks with full integration of Demand and distributed Energy Resources)
- 7 Innovation and research activities and funding sources for smart energy data/city development
Value flows in energy system and in smart meter roll-out – scaled to ‘Bristol scale’
The energy industry directly contributed £25 billion to the UK economy in 2013 (measured as Gross Value Added). This includes all fuels. The sector’s direct activities resulted in around £71 billion of value elsewhere in the economy (goods and services bought for energy companies' activities). In 2013, direct activities in the energy sector were the source of around £5.7 billion of tax revenue.
Bristol's electricity and gas consumption as a proportion of UK consumption was around 0.45% in 2013. Assuming this proportion applies to other fuels as well, the GVA directly contributed by the energy consumed in Bristol would be approximately £113 million annually. Gross Value Added is revenue less inputs bought from other firms, and so is equal to profit plus employee pay plus taxes paid - essentially, the value added to the final product by the work of all the organisations along the value chain.
The Energy Value Chain
The energy value chain consists of fuel production, generation, transmission, distribution, and supply. I have not found any research describing the value added at each stage of the value chain. A partial view of this could be obtained by looking at Ofgem's Consolidated Financial Statements for the Big Six energy suppliers, which would cover supply and part of the generation market, and the financial statements of the distribution and transmission businesses.
Profits made at different points in the supply chain
The table below shows GB profits from the big six for 2013 (note the figures in the first section related to UK, not GB). Bristol's consumption of electricity and gas was around 0.58% of the GB total in 2013, and this proportion is applied to the total profits to get a proportion for Bristol in the third column of the table. Total generation and supply profits for the big six, scaled to Bristol, are around £16.3 million per year.
|GB, £ millions||Bristol, £ millions|
|Domestic supply profit of big six, 2013||1,133||6.61|
|Non-domestic supply profit, big six, 2013||423||2.47|
|Total supply profit of big six, 2013||1,556||9.08|
|Generation profits of big six, 2013||1,240||7.23|
Similar data does not appear to be gathered for distribution or transmission.
Bristol's Energy Bill
Using average price statistics for 2014 (for domestic prices, the South West, and for non-domestic prices, a UK average including the costs of the Climate Change Levy) and statistics on Bristol's 2013 electricity and gas consumption, estimated energy bills are as follows:
|Estimated bill, £ millions (excl. VAT)|
Value flows in the smart meter roll out
According to DECC's May 2012 Impact Assessment, the costs and benefits of the smart meter roll out will be as follows:
|Metering equipment and installation||6,100|
|Industry set up, marketing, disposal, energy and pavement reading inefficiency||1,230|
|Consumer savings: reduced consumption||4,390|
|Consumer savings: other||40|
|Supplier savings: avoided site visits||3,080|
|Supplier savings: reduced enquiries and customer overheads||1,040|
|Supplier savings: other||4,350|
|Carbon related benefits||1,200|
|Total benefits||15,689 (Difference due to rounding in figures above)|
The net present value ('present' meaning 2012 as that's when the analysis was done) was calculated to be £4,840 million.
Value of smart grid at difference stages of the value chain
The table below provides a useful summary of the value of the smart grid to different elements of the value chain.
Understanding markets where value is traded (capacity, balancing etc)
The energy market is composed of three main sectors: generation, transmission and sale. Traditionally, most European energy markets worked on the basis of payments being made to generators for the value of the energy they had produced and sold.
The Capacity Market
In 2014 the Capacity Market was introduced as part of the Electricity Market Reform which was legislated in the Energy Act of 2013. From this time, the market works slightly differently; suppliers are now paid not only for the electricity that they produce, but also for the capacity that they have promised they can produce during times of system stress. The Capacity Market is intended to ensure that there will always be sufficient supply to match demand. This is of particular concern currently as at the same time as demand for electricity is projected to rise, due to increased electrification of heating and transport systems, supply is set to become more unstable with an increased share of renewable technologies in the generation mix and many older, fossil fueled plants going offline. It is hoped that the certainty of revenue provided by the capacity market will remove some of the risk for investors and ensure increased capacity moving into the future. Capacity can be provided in either the form of power supply or in demand reduction, with a MW of power produced from a plant functionally equivalent to a MW of reduced power from demand reduction.
Decisions about the level at which capacity payments are set are made in capacity auctions, the first of which took place in 2014 for delivery of capacity from winter 2018/19. There are a number of stages in the process of acquiring capacity:
- Capacity forecasting - the amount of capacity required for a certain period is estimated by the government using a forecasted future peak demand
- Capacity contracting - the capacity is contracted for through a competitive auction process. This takes place 4 years in advance of its need.
- Capacity agreements - those successful in the auction enter into an agreement whereby they commit to providing a certain amount of electricity when they are called upon in times of system stress.
- Capacity payments - suppliers are paid for providing this service and if they fail to provide what they said they would they will incur a fine (capped at 200% of their monthly income and 100% of their annual income)
- Capacity trading - capacity providers are then able to trade capacity freely in the private market.
The auction process
The capacity auctions are carried out in a descending clock format with the following structure:
- A price is set for the amount wishing to be paid for capacity– bidders are given the choice as to whether they want to bid for capacity at this price.
- Initially, this means there are more bidders of capacity, than there is capacity required.
- The price is lowered – and capacity providers are asked to bid again (declaring how much capacity they are willing to provide at that price).
- Process continues, with some bidders dropping out, or lowering the amount of capacity they are offering, as the price being offered decreases.
- Eventually, the amount of capacity required matches the amount being offered by bidders.
The final payments are made on a 'pay-as-you-clear' basis, meaning that everyone is paid the marginal price (the price of the most expensive offer accepted).
Criticisms of the capacity market
In the first capacity market auction the UK secured 49 gigawatts of generating capacity at a price of £19.40 per kilowatt. This amounts to a total cost of almost £1 billion which will be footed by energy consumers with an increase of £11 on an average bill.
Of particular concern to critics is that the capacity market will only act to provide support to pre-existing fossil fuel powered stations. The results of the 2014 auction show the majority of contracts were given to existing power stations, with only one new power station winning a contract. Demand Side Response (DSR) providers won less than 1% of the capacity, which will ensure that it continues to play a small part in the market (currently DSR contracts only 1-1.5 gigawatts in the market, compared to a generating capacity of 80 gigawatts).. This is of particular concern as energy reduction has been found to be three and a half times cheaper per MWh than generation and transmission of energy from conventional fuel sources.
Catherine Mitchell has suggested that a flaw in the capacity market is its assumption that fossil fueled generation is required to provide back up for renewables on a GW-for GW basis. This has been proven to be unnecessary, and can be solved largely through the increased use of DSR, which will be facilitated by the introduction of smart meters and half-hourly settlement (see below).
Balancing and Settlement
There are three main market participants in the electricity market: generators (who produce energy), suppliers (who buy energy from generators and sell it to customers) and non-physical traders (who buy and sell electricity to make profit, but don't actually use it).
Electricity is fundamentally different to most commodities that are bought and sold: it is being generated continuously and must be used immediately as it cannot be stored in large quantities. Calculating payments for the use of this electricity on a continuous basis would be impractical and so for the purpose of the electricity market electricity use is broken down into half hour chunks known as settlement periods. For each settlement period in a day generators and suppliers must submit predictions of how much electricity they project that they are going to either produce or require. These predictions are generally submitted far in advance of the settlement period taking place and long term contracts are formed. However, there is also the option for day-ahead trading and contracts are allowed to be negotiated right up until an hour before the settlement period begins. This cut off is known as the Gate Closure, and occurs every half hour. When the gate closes, the market participants will inform the National Grid of how much they intend to produce/consume in a particular settlement period and during the half hour period they will aim to produce/consume as close to this amount as possible.
In reality, errors in forecasting, problems with production and transportation or the occurrence of unforeseen events mean that imbalances do generally exist between the expected and actual consumption of electricity. Balancing and settlement are two processes that deal with this imbalance. The process through which balancing and settlement occur is laid out in the Balancing and Settlement Code (BSC) which was introduced in England and Wales in 2001 and in Scotland in 2005. The process is administered by ELEXON.
Balancing deals with these imbalances in the real time, ensuring that lights stay on and power surges are avoided. Balancing can be further divided into two categories:
Energy imbalance actions - Deal with imbalance on the system overall, occurring due to:
- Errors in forecasting by suppliers
- Generator plant failures
- Intermittent energy sources (e.g. renewables) produce more or less than was expected.
System imbalance actions - Deal with localised issues, occurring due to:
- Grid asset issues prevent electricity being transported to where it is needed i.e. constraints in the capacity of the transmission network preventing electricity reaching the areas it needs to.
- Variations in demand and supply on a second by second basis (i.e. supply might meet demand during the course of a half hour period when viewed as a whole, but in the moment there might be imbalances in certain places).
The National Grid deals with these imbalances my making deals to alter levels of demand and generation at a local scale, in particular regions, for short, distinct periods within the settlement period.
In all, there are 22 different balancing service which National Grid uses. A number of these serves are classed as ancillary services and are listed in figure x.
STOR (Short Term Operating Reserve)
STOR is designed to ensure that the National Grid is able to balance the grid minute by minute. A STOR provider offers availability of their services (in generation or DSR) between pre-determined windows (e.g. 7am to 10pm). There are up to three windows a day, and a provider can choose which of these they want to provide in. Within this window they then must be able to provide generation/DSR within 4 hours of request. Payments are divided into availability (paid just for being available in case of use) and utilisation (payment per MWhr delivered). The National Grid has 1.8- 2.3 GW of STOR capacity on operational standby available for use at short notice. It is expected that this will increase to a requirement for 8GW of STOR by 2025.
STOR prices are not sufficient to encourage much participation (reference needed).
Settlement occurs after the end of the settlement periods and redresses financial imbalances that may have occurred during that time. At the end of the period the amount of electricity that has been used by suppliers and produced by generators is measured, and compared to the amount of electricity they said they would use/produce. The calculations for the value of settlement payments are repeated several times over a 14 month period, generally becoming more accurate each time as more data and details are received. This is necessary as half hourly meter readings are only mandatory for those with consumption over 100kWh and so there is a time delay before data is received.
There are currently 29 million customers for whom HH (half hourly) settlement is impossible that are instead settled on a NHH (non half-hourly) basis. In order for the settlement process to take place, however, it is necessary to be able to generate a value for each HH period. This estimation is done by assigning each customer to one of 8 profile classes. A small subsection of those in each profile class is randomly selected to be monitored on a HH basis and this data is used to generate average load profiles detailing the times of day at which electricity is generally used. The load profile is then used to allocate an individual's annual consumption to HH periods. Thus, the settlement over a longer period will be accurate, but the timing of the day when electricity consumed will only be estimated in line with the load profile. Customers are settled for any differences between their estimated and actual energy usage every quarter, or in some cases even less frequently, as it relies on the energy company to manually check the meter reading.
Electricity Network Charges
TNUoS (Transmission Network Use of System) charges
Transmission Network Use of System Charges (TNUoS) are paid by generators and users to reflect the amount of investment in the network that is required to meet the energy they produce and use. 73% of the transmission costs are recouped through charges paid by homes and businesses and 27% through generators. For homes and business, the demand side, charges vary depending on whether you are a half-hourly or non half-hourly settled customer:
- HH meter customers: The charge is based upon average demand during triad periods multiplied by the tariff set for their region
- Non HH meter customers: The charge is based upon profiled annual electricity use between 4pm and 7pm multiplied by the tariff set for their region.
The regional tariffs are lower in the North to reflect the lower demand in these regions.
On the supply side, the charges are dependent on a number of smaller parts: a wider zonal tariff (dependent on location); a local substation tariff (dependent on the capacity of the substation); a local circuit tariff (dependent on the cost of connecting the generator to the National Grid).  The regional tariffs are higher in the North, to reflect the increased transmission capacity needed to move power from the rural areas to the densely populated south, where the demand is concentrated.
A full list of zonal tariffs for both the supply and demand sides can be found on the National Grid's website.
TNUoS charges make up 4% of an average household bill.
A triad is one of the three HH periods of highest demand during the triad season, which runs between November and February every year. At the end of the season, once the half hourly meters have been read, the triads are identified, with 10 days required between each triad. At these times the price of electricity is higher than usual, as inefficient and expensive generators must be switched on to meet demand. As a result, triad warning services exist which forecast when triads will occur, around 24 hours in advance, and allow companies to attempt to reduce demand in this period. If they manage to do this they will save considerably on the amount they pay in TNUoS charges. In this way, the TNUoS system also acts as a peak load shifting mechanism. In recent times, however, more companies have participated in triad avoidance and so it has become more difficult to predict triads as a result.
Specific triad management services, whereby a third party controls demand side measures in order to avoid triads, are currently only offered by one company in the UK, Flexitricity. With the establishment of the smart grid it is possible that substantial worth may be derived from the provision of triad avoidance services. However, as many businesses currently attempt to avoid triads, the triads are being somewhat flattened, and as this happens the value of triad avoidance could be reduced.
DUoS (Distribution Use of System) charges
These payments go to the regional DNO to maintain the local infrastructure. They cover the cost of receiving power from the National Grid and distributing it on a local scale. The charge is made up of several components: a fixed rate (independent of energy usage); capacity charge (dependent on how much electricity is being imported); reactive power charges; unit charges. These currently make up 18% of an average bill.
Since 2010 DUoS charges have been applied according to a red, amber, green traffic light system. Red periods will cover peak times such as the afternoon, amber the daytime period and green the nighttime and weekend, with higher payments in red and amber times. This is to encourage decreased usage in these time periods.
A site classified as a Designated EHV Property is subject to a locational based charging methodology. These charges are site-specific, reflecting the degree to which the local and higher voltage networks have the capacity to serve more demand or generation without the need to upgrade the electricity infrastructure. The charge is composed of a fixed charge to cover the cost of assets used solely by the customer, and a capacity charge which recovers the relevant Long Run Incremental Cost Pricing cost, the National Grid Electricity Transmission (NGET) cost and other regulated costs, and a super-red unit charge, charged on consumption at specific times. 
GDUoS (Generation Distribution Use of Systems) charges
This is a charge that is payable to the DNO for exporting electricity to their network.
BSUoS (Balancing Services Use of System) charges
These payments are paid for equally by generators and consumers and go towards the balancing services provided by the National Grid that help to keep the system balanced. The costs generally consist of payments made to providers for supply a balancing service such as STOR or frequency response and constraint costs paid to suppliers to not producing.
They do not vary by location.
Gas Network Charges
The gas network can be understood in terms of transmission and distribution:
- The National Transmission Service (NTS) is the high pressure network that transports gas from its entry points to the market to gas distribution networks or occasionally directly to large industrial users. It is operated by the National Grid
- The Gas Distribution Networks (GDN) transports gas to homes on a local scale. There are 8 local GDNs owned by 4 companies.
80% of gas network charges are made up of payments made to the Gas Distribution Networks (GDN) in the form of Local Distribution Zone (LDZ) charges.
Understanding value created by smart energy response and management of system at city scale (and how that will change over time)
The value of smart meters
Implementation of a smarter grid and smart energy response will impact all of the market players in the energy value chain.
The cost of installing 53 million smart meters in British households will be paid for by consumers and has been estimated to be £215 per home. Overall, latest estimates by DECC suggest that the roll-out will cost £10.9 billion and bring in benefits of £17.1 billion between 2013 and 2030. This equates to benefits of £1.60 for every £1 spent. 
Demand Side Measures
In 2014 the total annual electricity consumption of the UK was 318TWh. This electricity use, however, is not split evenly over the duration of a year, or even over the course of a day. Electricity use peaks at certain points, namely in the early evening and morning and in the winter months. The demand at peak times in the UK is currently just under 60GW. This is problematic as although capacity for generation and transportation may be sufficient to meet the demand the majority of the time, it may be unable to deliver demand during these peak demands. One measure of our ability to absorb this variation is the capacity margin - the difference between the available generation capacity and the expected demand. The capacity margin was 14% in 2012, but in 2015/16 is expected to fluctuate between 2% and 8%. This presents a significant drop in the security of supply for peak times. One way to deal with this is through Demand Side Measures which seek to reduce demand for energy at peak times. They can be grouped into two categories:
- Demand Reduction (DR) - reducing annual consumption of energy
- Demand Side Response (DSR) - shifting consumption from peak to non-peak times
Demand Reduction and Demand Side Response are complementary measures that both serve the basic purpose of reducing demand on the energy system, but they operate at different scales. Demand Reduction is likely to occur over a longer time frame and generally happens as the result of efficiency measures decreasing the amount of energy required to heat our homes and power our appliances. The result of demand reduction will be a fall in the annual load of the UK. Indeed, the introduction of smart meters is expected to lower electricity demand by 2% per household and a report by McKinsey, on behalf of DECC, has concluded that there is capacity for overall demand to be reduced by 36% by 2030.
Demand Side Response, by contrast, occurs in the moment, generally as a response to a message signalling the grid is experiencing a stress period of high demand. This is particularly valuable as, unlike Demand Reduction, it can be used to balance supply and demand in the market in real time. It is achieved by postponing or shifting the use of appliances to times when demand is not so high. Demand Side Response has no impact on the annual energy usage of the UK. Rather, it is likely to result in creating a more level profile for energy consumption over the course of a day. A smarter grid offers most potential in its ability to unlock greater use of DSR measures; the National Grid's 2013 report, 'Gone Green,' predicted that domestic DSR will play a far larger role in 2018/19 at 0.4GW, compared to today.
Technical potential and financial value of DSR throughout the energy supply chain
Overall, the NPV of DSR measures between 2017 and 2034 has been estimated to be £0.7 billion.
Analysis carried out by Redpoint and Element on behalf of DECC found the value of DSR from domestic households to be between £60 and £500 million.
The DECC and Ofgem estimates are of annual savings of £286 million from DR benefits from the introduction of smart meters (from shifting of 2.8% of overall electricity use and 1.3% of peak demand).Demand Side Response is valuable throughout the energy supply chain, as seen in the figure below.
The National Grid is responsible for balancing the market in real-time to ensure levels of supply and demand remain equal, as described above. An average household in the UK uses 3,800 kWh of electricity per annum,this domestic load makes up one third of the annual energy consumption of the UK as a whole. However, during peak periods the share of domestic energy consumption increases to a half. This means that DSR of domestic loads presents a valuable balancing resource in times of peak use.
Various studies have attempted to quantify how much of this demand is technically feasible to shift:
- Sustainability First use the Brattle Electricity Demand Side Model and conclude around a third of domestic evening load is shiftable (with a smaller shiftable amount in summer, in proportion to a smaller peak load).
- The Redpoint and Element Energy report suggested DSR could reduce peak demand by 2.5GW. 
- A DECC report which reviewed 30 trials in DSR found an average shifted demand of 5-7%.
Despite this, it remains that only 1-1.5GW of Demand Side Response capacity is currently contracted for by National Grid for use in balancing. Of this, 1.1GW comes from industry and commerce and 0.25GW comes from householders, mostly through the use of night storage heaters.
Balancing costs have been rising, and stood at just over £1,002 million in 2013-14, compared to £642 million in 2005-06.
Potential of DSR in ancillary balancing services
Current contribution of DSR to ancillary balancing services:
- Fast Reserve = 50-300MW
- Frequency Response = 80-90MW
- STOR = 200MW.
Payments made for these services in recent years:
- Fast Reserve = availability: £44,000/MW/pa, usage: £6,000/MW/pa (2009)
- Frequency Response = £50-60,000/kW/pa (2011-2012)
- STOR = availability: £10/MWh, usage: £224/MWh (2012)
The fact that lots of people are bidding to provide STOR is pushing down the price, particularly the availability payments. A limit has been set for the period between 2015/2016 that at least 200MW of STOR capacity must be provided by DSR, with a limit of 30MW per provider to prevent monopolisation. It is thought that the greatest earnings from DSR are likely to come from Fast Reserve and Frequency Response.
An overall figure of £383 million has been suggested for the value of the balancing services in which DSR can participate in the UK.
Particular worth can be derived from customer demand response if it can be achieved during triad periods, leading to high transmission costs being avoided. A study by the IEA looked at the financial value of shifting demand during triads. They noted that in 2006, at the point when demand peaked, the peak hour of load was adding 1,492 MW to the total system load and the top ten highest hours were adding 6,737 MW. In order to meet the higher demand of this ten hour period, 7GW of installed capacity would be needed. If Open Cycle Gas Turbines (the cheapest source to meet this demand) were used for 9 hours, then this would come at a cost of $10,000 per MWh. Thus, triad management through demand response would be financially viable if offered at any price lower than this.
Currently, the National Grid estimated that every year 0.5-1GW is shaved off the peak during predicted triad periods, and triad avoidance represents one of the largest forms of demand side response currently occurring in the UK. If triad response grows any further it does have the potential to complicate the triad system; shifting of loads occurring on a mass scale in order to avoid these peaks, will simply shift them to other times and make them harder to predict.
A reduction in overall demand (due to demand reduction) or an overall smoothing of the demand curve (due to demand shifting) would result in reduced requirement for generation capacity. Sustainability First's GB Electricity Demand Project concluded that if a 9% reduction in demand was realised by 2030 then this would also equate to the requirement for 4 less power stations. Green Alliance have suggested that the government is factoring demand response of 9% by 2025 (compared to a baseline scenario) into its planning for the future; this equates to avoidance of building 6 CCS coal or nuclear plants and a saving of £70 billion from 2010 to 2025. If demand reduction is increased to 16% in line with EU targets this avoided spending would rise to £125 billion. Ofgem have performed similar calculations and came up with saving estimates from avoided capacity at £129m - £536m annually.
The avoided investment in 'peaking plants,' plants that are generally gas fueled, rarely used and inefficient but currently critical to meeting demand at peak times, is particularly important. A report by Redpoint and Element Energy finds that reduced investment will be needed in OCGT peaking plants, which are generally the power sources used to meet the peak portion of demand Under the most favourable scenario they modelled this equated to savings of £266m from 3.2GW less required OCGT power output. A limiting factor here is that the DSR savings in 2025 are not as great as in 2030 and so OCGT plants may still have to be built to meet the 2025 demand. It is also important to ensure that DSR is provided by true demand response, and not by distributed energy resources, such as back-up diesel generators.
DSR also has benefits in reducing the ongoing operating costs of generation, as plants should be able to meet their load more efficiently. In the UK's electricity market plants are switched online to meet demand in order of their cost effectiveness, meaning by the time it comes to meeting peak demands only the most inefficient and expensive are left. If the need to switch these costly plants on and off can be avoided then money will be saved. The value of these reduced operating costs have been estimated by Ofgem to be between £129m - £536m and by Redpoint and Element Enegy at up to £170m a year. The most beneficial scenario modeled for DECC found reduced need for 3.2GW of CCGt and annual savings of £266m.
A reduced demand for electricity has knock-on impacts for the requirements of the infrastructure to transport this electricity to the areas of need. DECC and OFGEM have calculated a present value saving of £29 million for the domestic sector and £1 million for the small and medium non domestic sector over 20 years. om savings for distribution and transmission networks as a result of uptake of ToU tariffs.
The distribution network moves electricity from the transmission network to end use customers (households and small businesses). It has been projected that £110 billion would be needed to upgrade the UK's distribution network infrastructure over the coming decade; much of the network is outdated, a legacy of investment in the 1960s, and as early as the turn of the millennium 70% of the network was already deemed to be reaching the end of its design life. Avoidance, or at least delay, of the cost to the DNOs of reinforcing these networks was cited by Redpoint Energy as the second most important benefit of DSR.
To calculate the financial value of DSR to DNOs you would need to know the expected cost of reinforcing the network to meet the need. One estimate of the annual value of avoiding distribution network capital expenditure through DSR has been given at £40-£60/kW/pa. Ofgem's modelling suggests that the avoided capital cost of this network investment is worth £14m-£28m (shifting of 5% or 10% of demand respectively). Reduced investment in the network will pass through to mean reduced DUoS charges. These currently represent 18% of an average electricity bill; a 10% reduction in costs avoided by DSR could pass through a benefit of 2% off of an average bill.
In addition to reduced capital costs from DSR, the widespread adoption of smart meters will also mean reduced network management costs for DNOs. Most households and small businesses are served by the low voltage network, and currently DNOs have no means by which to monitor this network automatically. Although, historically, this has not presented a problem as load profiles of customers have been fairly easy to predict, an increased prevalence of EV's, heat pumps and CHP in the future might make this more complicated. With smart meters in place, if DNOS invest in the necessary capacity and upgrades this data will be very useful to them. Smart meters will also allow for more easy detection of faults on these low voltage networks.
In 2013-14 DNOs spent £340 million on constraint management costs, which is an increase from levels around the £100 million mark in 2005-2008. Constraints represent bottlenecks in the network where there is too much production or demand in certain localised areas, and so the network must be balanced; DSR in certain region areas would be a more cost effective way of dealing with this.
The transmission networks move large amounts of electricity at high voltage (275kV or 400kV) from producers to areas of need and are already 'smarter' than distribution networks
Looking to the future, an increasing prevalence of heat pumps and electric cars is likely to mean a greater overall electricity load and thus increased transmission capacity requirement. However, it will also increase potential for integration of local DSR and DER and this may provide opportunity to balance supply and demand on a local scale, thus reducing the need for inputs from the transmission networks.
Mott MacDonald have calculated that decreases in the size of peak loads will have knock on transmission savings between £50-80/kW. The average cost of transmission network reinforcement in the UK is £300/MW km. Studies suggest that DSR could lead to £800 million per year avoided costs.
Transmission constraints currently cost the National Grid £300m a year to manage, which is a massive increase on costs a decade ago The National Grid has a threshold for the amount of electricity it can transport from producer to consumer and thus constraints arise when it is unable to transport the electricity produced at one location in order to meet demand at another location. There are a number of reasons for this, including: heating ratings on lines being exceeded or inability to maintain supply within specified voltage ratings. To deal with this, the National Grid will use balancing services to increase production in certain location and will make 'constraint payments' to producers to tell them to produce less than they contracted for. These constraint charges come under BSUoS (Balancing Services Use of System charges) and are an important signal for transmission investment being required.
|Customers|| If savings are passed through to customers then they will see reduced bills. The level of saving depends on whether they are socialised amongst all customers or just with those who have participated in DSR on the domestic level.Cite error: Invalid |
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|Suppliers||Suppliers will benefit if they use make use of DSR in real time as a means to ensure their forecasted supply matches demand and that they avoid paying imbalance charges.|
|Network operators||Transmission and distribution network operators will benefit if they avoid the need to reinforce the network and if they can better monitor and manage network constraints, faults, leakage and theft.|
|System operator||The system operator can make use of DSR in its balancing services. It is likely to be cheaper than other balancing services available.|
|Aggregators||Third party aggregators will be able to turn a profit through aggregating DSR services from customers and then supplying it as one power source to the Naitonal Grid.|
It is important to remember that a DSR action by one party in the electricity market may have knock on impacts for others. For instance, a supplier will use DSR on a day to day basis, whereas the National Grid will use DSR for reserve purposes and the DNO will use DSR to deal with any peak events or outages. It may be necessary to coordinate the use of DSR at different levels of the supply chain.
Distributed Energy Resources (DER)
Smarter energy response and management shall also facilitate increased incorporation of distributed energy resources into the energy mix. Distributed Energy Resources are small power storage or generation sites that are decentralised and connect directly to the distribution network, rather than going through the transmission network. They are usually owned and operated separately from the central utility provider. These may come in the form of biomass boilers or small scale wind turbines and solar arrays (DSR can also be considered as a DER). Distributed generation will lead increasingly to customers becoming producers, or 'prosumers', a term used to describe a person both consuming and producing energy.
In the UK DER currently make up a very small portion of the energy mix, with less than 1% of demand being met by distributed generation. In 2010-11 there was 789.4 MW of distributed generation connected to the network. Despite this, work by the University of Bath has suggested it is technically plausible for distributed generation to make up 50% of the energy mix by 2050.
There are several potential benefits from the use of DER:
- Added flexibility, electricity can be provided by DER when demand and prices are high
- Reduced distances required for transport. In the UK 7% of all electricity transported is lost (20TWh) every year.
- Meeting demand on a local level
The location of distributed generation is critical to its ability to influence transmission network requirements and losses. For instance, if it is located in the north where there is already a greater level of production than demand then it will increase pressure on transmission systems. If it is in the south where there is a deficit in production compared to consumption then it will reduce the need for transmission network capacity. Despite this, Ofgem has estimated that for each kW of DER installed there will be £50-100 less investment required in transmission network capacity.
Between 2012 and 2014 there was more than £80 million of funding put towards the development of energy storage facilities across the UK. Most of the UK's storage capacity however continues to come from just a few large hydro-power projects. In Bristol this image shows there is 90kW of storage capacity available.
Realising the DSR potential at the customer level
It is clear that there are large potential benefits from DSR for various market actors across the energy supply chain; however, for this resource to be realised a lot of facilitation work must be done.
Currently the vast bulk of DSR comes from the I&C customer load, and very little from domestic customers. Shifting loads of domestic customers at peak times is particularly valuable: domestic consumption makes up a third of consumption overall, however at peak times this share increases to half of total demand. Research by the University of Cambridge has looked into how much of this demand is feasibly shiftable, they found: 5% of total domestic demand comes from stand-by devices which could be switched off; 6% from wet appliances (dishwashers, washing machines) whose use could be shifted to an off-peak period; 9% from cold appliances which could be cooled below the necessary level during off-peak times, allowing them to be switched off during peak times but to maintain an adequate temperature. There is significant potential value in shifting these loads. For instance, it has been estimated that 1.3GW of dynamically controlled refrigeration would be sufficient to reduce the need for £80m of expenditure by the national grid on frequency response contracts. (2004 figures).
Time of Use (ToU) Tariffs
Variable rate tariffs can be used as an incentive to force consumers to use cheaper, off-peak electricity. These tariffs can be split into three categories:
- Static time of use - There are two or more periods defined in the day which are charged at different rates, but the rates remain constant. Eg. Economy 7/10
- Dynamic time of use - Different prices are charged in different periods of the day, however, the rates are not constant and may fluctuate on a daily basis
- Direct load control - customers pass over some control to operators to cycle heating systems on and off within agreed level.
Currently, a mere 13% of the population is operating on a time of use tariff; the government is estimating that an additional 20% of the population will move to static time of use tariffs by 2030, post-smart meter roll out.
If suppliers are to realise and capture the benefits of their customers switching their demand in response to the existence of a Time of Use tariff then smarter settlement is required. As things currently stand, 29 million customers are settled on a non HH basis and just 120,500 sites use HH settlement methods (details in section x). The roll out of smart meters presents a significant opportunity to reform this process; the Profiling and Settlement Review Group (PSRG) ran between 2010 and 2015 to review how to adapt settlement and profiling processes for the use of smart meters.
Changes have begun to be made, and since April 2014 it has been mandatory for all meters in profile classes 5-8 (large commercial customers) to be capable of recording consumption on a HH basis and for this data to be capable of being read remotely. Ofgem has recently made an amendment to regulation, entitled P272 which will make it mandatory for this capability to be used to make HH settlement of these customers. The amendment comes into force in April 2017. The amendment has a strong economic case, with a cost-benefit analysis carried out by ELEXON concluding there would be a cost of £35.1 million of administering HH metering, but that it would be offset by benefits of £85.0 million.
An extension of this move to make HH settlement for profile classes 1-4, who represent domestic and smaller commercial customers, has wide support in the industry. The National Grid have stated that HH settlement is "necessary and complementary to delivering the UK’s energy needs and achieving renewable and greenhouse gas targets in an affordable and secure manner.”  In a consultation by Ofgem a third of all respondents agreed that settlement reform is necessary if we are to capture the full potential of DSR in the market.
The advantages of HH settlement identified, include:
- Easier forecasting of demand - using actual data rather than profiles would improve forecasting. It would also expose suppliers more greatly to the impacts of errors in forecasting.
- Shortening settlement timescales - The comparison that takes places between the contracted and metered volumes of electricity used take place at set intervals called settlement runs. These begin around 3 weeks after real time, and the final run takes place 14 months after real time. Ability to remotely read data from smart meters would streamline this process. This could shorten the length of the whole process and remove the need for some of the interim runs.
- Better matching of local supply and demand (Expand MA)
- More effective DSR (discuss below). Currently, for NHH customers underlying costs relating to production, networks and balancing are all recovered across the whole of the NHH customer group (and suppliers) and so ...currently the option to reflect DSR of NHH customers in pricing does not exist.
- Accurate reflection of consumer behavior in settlement. Currently, profiling means that in any half hour period a customer may use more or less energy than was forecasted, but the supplier will not feel the impact of this. Once customers are being settled against real HH data suppliers will be exposed to the actual costs of purchasing and transporting any surplus energy and thus will have more incentive to signal to customers to reduce consumption, particularly at peak times.
Realising the DSR potential at the grid level
Despite the vast potential of DSR to become a major resource in the energy mix there are currently significant barriers hindering its progress. For instance, the UK electricity network infrastructure is designed for receiving large inputs from fossil fueled generation plants and is not equipped to deal with the bidirectional flow of electricity.
The incorporation of DER also presents a significant challenge. Most DER does not produce a 50/60Hz voltage output, which is the utility frequency of the National Grid. When DER enters the medium and low voltage networks it changes the voltage profile of the distribution grid; if there is not enough demand to consume this extra input of electricity then increases in voltage may go over operational limits.
One important step in the creation of a smart grid is aggregating grid resources: this can be done through the use of microgrids and Virtual Power Plants. These are commercial arrangements that attempt to use the existing infrastructure in a more efficient way.
Microgrids involve the aggregation of power production from various DER (Distributed Energy Resources) and DSRs providers on a small scale, generally at the level of a small town or neighbourhood. A system controller manages the microgrid, balancing load and generation by utilising the various resources available to them. The microgrid operates as a single and flexible resource on the energy market or alternatively they may sell their services to the National Grid as a system reserve. A microgrid also has the potential to disconnect from the central power grid, and operate as an 'island', only exporting or importing electricity from outside when local supply is not enough to meet demand.This function is also useful for reliability, allowing the microgrid to continue functioning in the event of a grid outage.
Microgrids offer a number of advantages:
- Reduced distribution losses as supply is close to demand
- Reliable power quality at a local scale
- Peak shaving and load shifting using DSR
Virtual Power Plants (VPP)
VPPs share many similarities with microgrids: they combine energy resources to produce one output that can be treated as a single, larger energy resource. However, for a VPP to function it is not necessary for the resources to be geographically close to one another. As such, VPPs may be made up of aggregations of various microgrids, located in different regions. A VPP is thus very dependent on transmission networks.
A recent report by Navigant Research looked into the global market for VPPs, and concluded that their total worldwide capacity was set to increase from 4,800MW in 2014 to nearly 28,000MW in 2023 - a five fold increase. By 2020 the market is expected by Navigant Research to have a value of $3.6 billion. A significant example of a VPP is found in Germany where 36 wind, solar, biogas, CHP and hydropower generators are operated as a single power plant and supply power 24/7 to around 12,000 households.The VPP concept has caught on particularly well in Germany, where there is a large amount of renewable capacity. RWE is expected to have a VPP portfolio of 200MW by 2015. The Swedish power company Vattenfall have 100,000 houses under their VPP control.
In the UK Flextricity aggregate DSR in order to provide reserve capacity for the National Grid. NPower offers a service called SmartSTOR which uses Flexitricity to communicate with electricity generating and consuming equipment on domestic and industrial sites and to turn them off and on as required to manage demand. KiwiPower are another aggregator, set-up in 2009, who are now operating a VPP with a capacity of more than 100 MW. Kiwi estimate that there are significant returns for businesses who offer up their demand repsonse services to aggregators, with medium enterprises capable of earning £20,000 a year, and large businesses £100,000.
How value of smart energy response and smart grids will change over time
Increasing renewable generation
In an increasingly electric future the value of smart energy management will increase greatly. 22GW of renewables are in the pipeline to be generating by 2020. Many of these technologies, in particular wind, will add a much greater level of intermitency and variability to the network. As such, flexible response and reserve will become much more valuable.
Demand sides measures are generally focused on the idea of getting customers to shift or reduce their demand by providing incentives for them to manually do so. The possibility of the existence of smart devices connected through the 'internet-of-things, however, presents an option for devices to be automated and for control to lie with a third party. For example, In this situation consumers would buy smart devices, connect them to the internet through wi-fi and register their device with an aggregator. Consumers would then be paid by the aggregator for any DSR that their capacity provides through the aggregator remotely altering its usage.Studies have shown that smart appliances and enabling infrastructure increase the likelihood of customers responding to price signals.
Although smart meters will provide information for customers about how much energy they are using it is unlikely that without automation mechanisms that much DSR will be achieved. This is due to the electrificaiton of heating systems, with heat pumps creating peaks in cold, peak times. It has been estimated that the aggregate impact of heat pumps may be as much as 1.3kW per home.
Electrification of transport and heat
An increased incidence of low carbon technologies at a household level will lead to much more variable seasonal demand. The ratio of demand in winter compared to summer (in a high uptake of low carbon technology scenario) is expected to rise from 1.76 in 2010 to 2.15 in 2030.
One study has estimated that by 2050 the peak electrical load in the UK will have reached 184 GW, which with a 10% reserve, would result in a requirement for 205 GW of capacity; this equates to around three times the UK's current capacity.
Electric vehicles are expected to form an increasingly large portion of the UK transport mix. Although an increasingly electrified transport system will place an increased burden on the UK electricity market, the prevalence of electric cars will also provide an opportunity for DSR. Cars are parked 95% of the time and so each electric vehicle will represent a distributed storage device. V2G describes drawing power from parked EVs to supply the grid in times of need, whilst G2V involves using times of surplus to charge up the EVs. There will only be significant value in this resource if the vehicles are avaialble at the right time and can supply a large enough power load. The IEA assumes that each PHEV (Plug-in Hybrid Electric Vehicle) will have a capacity of 8kWh and each BEV (Battery Electric Vehicles) will provide a higher 30kWh capacity. IEA analysis has also suggested the use of V2G alongside G2V could lower the baseload by 10%.
A 2009 report for the CCC found it was likely that a lot of distribution transformers used to supply the low voltage distribution network will need to be replaced if there is an increased share of electric vehicles. In one scenario they have modeled there will be 15.9 million EVs by 2030 and if 20% of the distribution transformers were needed to be replaced to accommodate for them then this would cost £2.6-3.9 billion. This could could be significantly reduced with DSR. Another report has predicted that if there is a 50% penetration of electric vehicles (alongside heat pumps) by 2030 then the low voltage network will need to be reinforced to the cost of £21.8 billion, but if smart grid technologies are used then this cost be limited to £9.3 billion.
Combined Heat and Power (CHP)
The potential of CHP in controlling outputs of electricity and heat make it a valuable resource in DSR. Micro-CHP plants's outputs can be aggregated and used during periods of shortfall in electricity production in the form of a Virtual Power Plant (VPP). Statistics from DECC for 2011 to 2012 showed that there was 6.1GW of CHP capacity in the UK which accounts for 6.4% of UK’s total electricity needs.
mCHP is a form of distributed energy resource and will play an important role in localised demand response.
Heat pumps have some potential to assist in load shifting.
More Time of Use tariffs
DECC estimates that by 2030 an additional 20% of customers (on top of 19% currently) will be on a time of use tariff. 
The Local Scale
At the beginning of the 20th Century there was local level energy supply in the UK. Gradual shifts were made away from this until the system was fully nationalised in the 1940s, with the advent of the National Grid. The GB supply market is now dominated by the Big 6 and a range of smaller companies who each supply electricity and gas with no geographic constraints. Indeed each provider has an obligation to supply a customer regardless of their location.The result of this is that there is no recognition of the environmental, social and economical benefits to responding to local demand with local supply: local areas cannot benefit from energy value and that householders and businesses cannot benefit from demand side measures.
Research by Communities for Renewables showing the way money spent on energy flows out of the local economy. This is demonstrated through the example of Cornwall below. The study concludes that if we switched to more local energy markets then up to 70% of the electricity spend could remain in the local area. It was also estaimted that 2,000 jobs and £110 million GVA would be generated in 2020.
The top-down nature of the supply market, with generation controlled centrally and sent to supply demand wherever it arises, made sense when it was initiated. At this time computer systems were rudimentary and expensive and so controlling everything from one point made sense. The result of this is that charging systems and trading arrangements are all based on management of energy at the national level. Since these systems were put in place, however, a lot has changed. The increasing prevalence of smart technologies in particular suggest that a more local energy system might allow us to capture new value opportunities.
Currently suppliers have little motivation for prompting DSR on a local scale whereas distribution networks have key motivations (constraint management). However, customers are used to interacting with their supplier but not with their DNO. Distribution charges take into account of locational costs for larger customers and distributed generation but not for smaller generators or DSR. Concerns remain that if a move was made towards a greater cost reflection in network charges in order to create a stronger incentive for local demand side then there would be some groups who were unable to shift their load who would suffer.
In the coming years, with distributed, renewable energy sources and DSR playing an ever growing role in our energy system it is likely that the issue of locality will only become ever more relevant.
Sustainability First identified the following requirements for achieving matching of local supply and demand at the distribution level:
- Widespread existence of smart meters and half hourly data and settlement
- A direct link between distribution networks and end users, which has not historically existed.
- Automated control of loads such as hot-water cylinders, storage heaters, heat pumps and electric vehicles
- Signals and incentives in DUoS to suppliers to encourage DSR among domestic customers
In much of the South West the network is very constrained and during peak times the network is operating very close to its voltage limit. This means there is minimal spare capacity and thus any increases in demand would require high voltage network reinforcement. This will comprise the potential contribution from Hinkley Point C nuclear power plant, wind in the Bristol channel and marine power.
As a result, as of March 2015, the DNO Western Power Distribution, announced that its F-route was at full capacity. This is a critical 132kV route that runs from Bridgwater Grid Supply point to Seabank Grid Supply Point. This route is critical for the connection of any supply in Cornwall, Devon, Dorset, Somerset and Bristol Docks. Anyone seeking to connect new generation in the South West will be subject to a delay of 3-6 years; this will be subject to a planned upgrade of the F-route to a 400kV network. It has also been proposed to change boundary B13E shown in the diagram to B13E.
The cost of reinforcing this area has been estimated to be £450 million and will allow accommodation of 6GW.
Understanding potential financial value of using smart energy data in other services (e.g. health improvement – thermal safeguarding etc)
The SHIMMER program aims to integrate money and energy saving advice with the smart meter system in order to help low income, fuel poor households to reduce consumption to an affordable level and to better keep track of their finances. The project received TSB funding aimed at projects making use of smart meter capabilities to create smarter homes. A smart meter is connected with an online interface which allows consumers to monitor their consumption, but also provides them with advice on benefits and budgeting, switching deals and energy saving. Initial pilot projects have suggested these systems could allow users to save between £200 and £3,500 a year, however only 18 homes were involved and so conclusions carry limited weight. Extensions of the system hope to incorporate an option to automate appliances to save money and to link the smart meter to an online bank account, allowing money saved to be fed into future payments.
The Hydra project was carried out by a consortium of leading industrial and academic institutions with additional match funding provided by the TSB and the ESPRC. The projects aim was to demonstrate the social and financial value of using smart meters to provide additional functionality to patients by allowing them to access health related data. The pilot scheme involved 13 homes who were connected via their smart meters to health centre staff.
The health data recorded was primarily blood pressure and weight measurements; Zigbee enabled blood pressure monitors and weighing scales were used which allowed measurements to be transmitted wirelessly to the smart meter. From the smart meter the data moves on through the server and internet cloud to the healthcare professionals. Travel is thus avoided by the patient, with a nurse reviewing the data and appointments only being sought when anomalous data is detected.
This is an initiative, funded by the TSB, that aims to explore the value of creating an internet-of-things allowing individual people and councils to share information across and between cities. This will entail information from smart meters and about traffic and air quality being shared. The project aims to bring together people who know about technology with people who make plans for cities, who might be able to use the technology to solve city infrastructure challenges.
The real benefit of HyperCatCity lies in allowing devices to communicate with each other with reduced need for human interaction. This is currently not possible as there is no universal communication standard: most devices are connected to the internet through a web interface which controls the way that applications are able to interact and communicate with them. These interfaces, however, come in many different forms. This means a device will be unable to communicate with another device if it has a different interface; in order for different devices to communicate with each other an API (Application Program Interface) must be manually written by a human programmer. There is currently examples of linkages of smart devices, for instance Google has interconnected their Nest smart-thermostats with JawboneUp wristbands, allowing a message to be sent telling the thermostat to start controlling the heating once the wristband wearer has woken up. This type of linkup, however, is only possible due to the creation of an API, and generally can only occur between commercially connected companies. HyperCat aims to allow devices and data sets to find each other on the internet without the need for a human to write API programmes, through a data hub analogous to a address book. Different companies will be able to produce devices and applications using different data formats, however if what the device/application does is described in a common language then it will be easy to browse for functionality. This will allow for increased sharing of innovations. HyperCat has been compared to the advent of the world wide web and the way it unlocked the internet for mass use.
Hypercat enabled technologies have been trialed in Milton Keynes and London and are now being introduced in Bristol through the 'Bristol is Open' project. In Milton Keynes the council has teamed up with BT to offer value added services through the HyperCat City platform. One example of this is attaching sensors to bins which monitor when they are full, with bin lorries only being sent at this point. Another, is the use of sensory studs in parking spaces and sensors on street lights so they are only deployed when needed. In Bristol a 20% reduction in energy usage has been found in buildings through collection of energy data from buildings.
Energy supplier smart meter roll-out plans and potential for securing integrated city-wide approach
The Government expects that smart meter installation will accelerate sharply in 2016, when all the common standards come into force and the Data Communication Company (DCC) is live. The expectation is that around 20 million meters will be fitted in 2016-2018, with a peak in 2019 and finish in 2020. SMETS1 meters - piloted in the Foundation stage of the roll-out in 2014-2015 - will be replaced with SMETS2 meters that communicate via the DCC from 2016 onwards. Installation will begin with houses in urban and semi-urban areas as the location and housing density makes it easier to set up the communications infrastructure. Flats will come later, and high-rise flats will come last, starting in 2018. Roll-out to prepay customers should start at the same time as the full-scale roll-out programme.
In the UK 1.3 million domestic smart meters have been installed and over half a million smart and advanced meters installed in non-domestic settings . 2.5 % and 19.8% of total smart meters respectively for each group). Nearly 1.2 million domestic smart meters are in smart operation, (roughly 719,000 electric and 474,000 gas).
UK smart meter roll-out (July 2015)
Details of the smart meter roll-out is given in the table below.
|Supplier||Website||Smart meter activity|
|British Gas||www.britishgas.co.uk/smarter-living/control-energy/smart-meters.html||Currently rolling out. Initial screening on website to have a smart meter fitted. Must be in credit if have prepayment meter, have an accessible fuse box, not be in a flat, nor with E7 meter, nor if a smart meter is already there. Claim that 1.5 million smart or smart type meters installed (August 2015). Some have ToU tariff with free weekend electricity, and there are trials of My Energy app.|
|E.ON||www.eonenergy.com/for-your-home/saving-energy/smart-meters||April 2015 number installed 380, 141. Recently announced trial for 30,000 smart PAYG customers offering reduced tariff on weekday evenings and weekends as an incentive to have a smart meter. Rolling out in 2016 and can register interest on website. For smart PAYG website says that there will be £35 per fuel per year off standing charge. Dual fuel has an extra £20 reduction, and £10 off for paperless billing. Choice of four tariffs, including fixed price tariffs with price alert emails.|
|EDF||www.edfenergy.com/for-home/energy-efficiency/smart-meters||Information available on website but no numbers of smart meters indicated.|
|First Utility||https://www.first-utility.com/help/My_Meter/__kA1D00000008PaQKAU/What-is-a-smart-meter||Information on website but no numbers of smart meters indicated. Upgrading existing customers when meter needs replacing.|
|Green Star Energy||http://www.greenenergyuk.com||Rolling out gas and electricity meters, with mass roll-out in 2016.|
|npower||www.npower.com/home/help-and-support/types-of-meter/smart-meters||No current roll-out. When do roll-out meters not compatible with microgeneration.|
|OVO Energy||www.ovoenergy.com/energy-plans/pay-as-you-go||Offers smart and smart PAYG. Phone app ready. Working innovatively with local authorities like Cheshire East and Plymouth on local tariffs.|
|Scottish Power||www.scottishpower.co.uk/energy-efficiency/smart-meters||Small roll-out in 2015, full roll-out 2016 when technology becomes available.|
|SSE||www.sse.co.uk/HelpAndAdvice/SmartMeters||Upgrading existing customers in phased roll-out with plans to upgrade all customers by 2020. 100,000 smart meters installed (Sept 2015)|
|Utilita||www.utilita.co.uk/smart-meters/utilitas-smart-meters||Smart PAYG predominantly. 60% of their customers have a smart meter.|
|Utility Warehouse||https://www.utilitywarehouse.co.uk/help||No current roll-out.|
The potential for securing an integrated city-wide approach to smart meter installation
A 2013 DECC report highlighted the role that community groups can play in helping households during the smart meter roll-out. The need for trusted third party intermediaries has been noted as a key mechanism to promote and optimise customer acceptance and engagement with smart meters, and to overcome mistrust of energy suppliers. Community groups can help households with:
- awareness raising
- hand holding during and after the installation process
- providing practical assistance in using the smart meter display and energy behaviour change advice
- keeping an active smart meter profile to encourage ongoing use of the display.
They can also generate interest in local energy initiatives and renewable energy. Drawing on roll-out experiences from Australia, community groups can also act as independent voices responding spontaneously to local concerns and criticisms of smart meters.
‘Green’ groups are useful but should not be used exclusively. Energy professionals or single purpose groups can also convey energy messages effectively. Existing community energy networks can also play a key role to facilitate a city-wide roll-out (e.g. Transition Towns, Low Carbon Communities Network and the umbrella Communities and Climate Action Alliance). Over the longer term, data from smart meters could contribute to more accurate, regularly updated information on energy use and carbon emissions at community level.
To action greater community group involvement in the smart meter roll-out suppliers/another agencies would need to provide household-friendly information on smart meters to groups, and possibly templates and examples of the technology. Community groups could work alongside or partner with energy suppliers, agreeing roles and addressing organisational needs at an early stage in the roll-out process. Focusing on a partnership with one or two suppliers in a geographical area would be sensible. Alternatively groups could position themselves as impartial advisors and not work alongside a supplier, or work in partnership with their local authority or housing providers.
The long roll-out period offers challenges for community groups, in that supporting all households might be difficult. However this does give scope for demonstration programmes. Pilot programmes could offer opportunities for communities to bid to run projects to promote and explore uptake of smart meters in their area. Different roll-out activities could be tested, building on local knowledge, to determine successful methodologies and marketing approaches.
Besides community groups the other key players at city-wide level in relation to smart meters are local authorities and social housing providers. Local authorities can be useful for additional support/resources and local knowledge during the roll-out. They could take a more active stance, partnering with energy suppliers to provide locally-endorsed energy efficiency guidance during smart meter installations. Where possible, suppliers should share their roll-out plans with local authorities. Social housing providers could take on a key role by actively promoting smart meters, particularly to vulnerable householders.
In Florida during the smart meter roll-out a range of local opinion leaders and independent organisations were contacted and briefed, including the business community, local government leaders, the media, community advocates and public service providers.
There is little information on the role of private landlords in the smart meter roll-out. They are a key group given that many vulnerable customers live in private rented accommodation.
Finally, the House of Commons Energy and Climate Change Committee point out that greater participation of network operators in the roll-out can have significant benefits. Whilst recognising that at this late stage transferring the responsibility for roll-out to network operators is impractical, the Committee emphasised that improved regional installation and the resolution of interoperability issues could result by increasing their involvement, and that the feasibility of this should be explored.
Potential business models for city-wide approach
Project SoLa BRISTOL (Buildings, Renewables and Integrated Storage with Tariffs to Overcome network Limitations)
SoLa is a project funded by WPD in Bristol through the Low Carbon Network Fund. Bristol City Council, Knowle West Media Centre, the University of Bath and Siemens are all involved in the project. The project aims to explore the difficulties that DNOs may experience as a result of Solar PV connecting to the low voltage network and the potential for using distributed storage to manage this problem. Batteries have been installed within homes and the DNO is able to communicate with them, charging and discharging them as needed to help with network management.
The project looks at the potential of using battery storage, demand response and direct current networks within school, homes and offices to help the DNO manage network constraints. Siemens are contributing the ICT solutions necessary for the project in the form of smart monitoring and automation devices. The project runs from 2013 to 2015.
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Trial participants - reduction/generation capacity agreed and payment to be made. Falcon DSR trials take place between 4 and 8pm weekdays, November to February. Any time during this period WPD's control centre will give 30 minutes notice to participants to reduce their load or switch on their own generated supply for up to two hours. Smart meter will report event performance.
Project FALCON (Flexible Approaches for Low Carbon Optimised Networks)
The FALCON project is funded by Ofgem's Low Carbon Network Fund with the objective of helping WPD to develop a smarter network with increased flexibility. The project began in January in 2012 in Milton Keynes and will continue until September 2015. The objectives of the project are to create a smarter network with increased flexibility that will allow better management of constraints, increase capacity and provide security of supply.
In order to achieve these aims, FALCON is trialling 6 alternative methods of developing the networks, whilst avoiding a conventional process of reinforcement. To do this, a Scenario Investment Model (SIM) has been created: this is a tool which analyses the solutions for developing the 11kV network and considers future load/constraint scenarios before selecting the most viable option. The solutions examined include working with businesses to reduce their electricity demand, with around 15 businesses taking part in a trial where WPD were able to request them to reduce consumption or switch demand, another option was using flexibility and customer demand and a further option involved use of distributed generation.
LEMMA (Local Energy Markets Modelling and Analysis)
This project is being run by a collaboration between IPL (an IT services company) and Swanburton (an engineering firm) with £2 million backing from the TSB. They are aiming to investigate the best ways to link consumers in a certain area with producers generating energy in their area. Making use of their respective specialities , IPL will examine the information structures necessary to allow local buying and selling of energy and Swanburton shall examine the infrastructure necessary to store energy locally and then distributing it to the network.
A major conclusion of the study was that although the necessary software and hardware was integral to the success of local energy markets, nothing was required beyond the bounds if what is already currently available. The study found significant economic benefits to the local area, with bill savings of between 5 and 10% and with producer revenue to increase by 17-58%, without and with storage respectively.
Wadebridge Renewable Energy Network (WREN)
WREN is a project trying to demonstrate the benefits of keeping energy expenditure within the local economy. This is despite the fact that Wadebridge, in Cornwall, has rich renewable energy potential. Wadebridge has a collective electricity consumption of 50,000MWh a year. The project targeted that 30% of this demand would be met with renewable energy by the end of 2015, with 100% of energy from local sources by 2020.
EcoGrid EU (Bonholm, Denmark)
There are 28,000 residents on the Danish island of Bonholm. Beginning in 2011 they have been involved in an EU funded project to test the balancing power of small, domestic customers.
2,000 of those will partake in DSR, in reaction to price signals received through smart devices .
NOBEL (Neighbourhood Oriented Brokerage Electricity and Monitoring System)
The NOBEL project is part of the EU funded Horizon 2020 research and innovation programme, with partners in Spain, Germany, Sweden and Greece. The project aimed to deal with the amount of energy that is currently lost due to inefficiency, in particular looking at how energy is often lost in the last mile of the distribution network. The project aimed to use ICT in order to create a more functional monitoring and control system; network operators and prosumers were monitored and analysed to assess levels of energy supply and demand on the network and then this data used to balance the system.
Currently, the amount of energy required for a particular area is estimated, and if actual demand does not meet this level then the excess energy will be wasted. NOBEL works on the basis that if information can be shared constantly about the energy that is being produced and consumed then it will be possible to more efficiently balance supply and demand on-the-fly at a local scale. In particular, the NOBEL project aimed to create a platform through which individual energy consumers were able to communicate directly with both small and large energy producers in the local area. The aim was to simultaneously reduce consumption through display of energy consumption data and also to promote greater use of local, renewable energy sources.
Part of the project involved investigating the financial gains that could be made from improved power quality monitoring. The benefits identified were in providing proof of supply to customers and also in optimizing the voltage delivered. In Sweden it was shown that this could reduce the amount of energy required by 4% (equivalent to 5.6TWh in 2011).
The pilot project took place in Alginet, an eastern Spanish village where 5,700 smart meters were installed.
There were three forms of participants in the pilot: DSO (the local DSO - Alginet Cooperative), STPs (Standard Prosumers - basic domestic end users, who may produce as well as consume energy) and SEP (Senior Prosumers - an STP with additional energy management requirements e.g. heavy industry). Two online interfaces were used during the project to allow communication between the different market actors. There was one tool for the DSO to keep track of electricity use in the neighborhood and another allowing STPs to manage the efficiency of their electricity usage. The latter gives a platform for the DSO to communicate with STPs and offer incentives for dropping consumption. The result was a situation allowing standard prosumers to increase or decrease their energy consumption in response to signals and additionally to trade energy through an online marketplace.
The project resulted in savings of energy savings of 12.2% across the village and significant economic results for individuals who accessed better deals. It is anticipated that the energy brokerage systems piloted here could play a role as an aggregator in local smart grids, with a third party given charge to manage loads on behalf of individuals.
Power Matching City - Hoogkerk, Netherlands
Power Matching City is project in Hoogkerk, Groningen designed to demonstrate the potential in future energy infrastructure through the example of 25 households. Hoogkerk's microgrid began operating in 2010 and included 25 connected houses. All of the houses have smart meters, solar PV panels, 12 have CHP and 13 have a heat pump: every house is producing as well as consuming energy. The 25 houses are virtually connected to one another and along with a community owned 2MW wind farm and 30kW micro-gas turbine they form a virtual power plant. Crucially, PowerMatching software is used to match supply and demand in the grid. The PowerMatcher will be able to alter the demand of household devices according to the availability of renewable energy. The main objective of this field trial is to analyse the scalability of the concept. Indeed, a large part of the trial was to reach 1 million households, however, as including 1 million real households was impossible a large section of the trial was based on simulations.
Mulheim's Into Metering
RWE installed more than 100,000 devices (almost every household) in Mulheim between 2008 and 2011, which gave a critical insight into the install process. Additionally research was carried out which aimed to test the impact of smart meters on consumption patterns.
ADDRESS (Active Distribution networks with full integration of Demand and distributed Energy Resources)
This is an EU funded project with the objective of researching technical solutions for prompting consumers to manage their demand actively. The project is grounded in the idea that in the future as renewables achieve a greater market penetration there will be an increased requirement for DSR. The project identified the 'architecture' required for this successful management of energy use at the customer level: this included DSR aggregators and an 'energy box' allowing communication between the consumer and the aggregator. This energy box will provide real time price signals and volume signals.
Innovation and research activities and funding sources for smart energy data/city development
words hereThis section is not identified under any of the challenges - it will be covered later on, after the workshops. Maybe delete from here?
- DECC, Average variable unit costs and fixed costs for electricity for selected towns and cities in the UK (QEP 2.2.4), and Average variable unit costs and fixed costs for gas for selected towns and cities in Great Britain (QEP 2.3.4), https://www.gov.uk/government/statistical-data-sets/annual-domestic-energy-price-statistics
- DECC, Prices of fuels purchased by non-domestic consumers in the United Kingdom excluding/including CCL (QEP 3.4.1 and 3.4.2), https://www.gov.uk/government/statistical-data-sets/gas-and-electricity-prices-in-the-non-domestic-sector
- DECC, Regional and local authority electricity consumption statistics: 2005 to 2013, https://www.gov.uk/government/statistical-data-sets/regional-and-local-authority-electricity-consumption-statistics-2005-to-2011
- DECC, Gas sales and numbers of customers by region and local authority: 2005 to 2013, https://www.gov.uk/government/statistical-data-sets/gas-sales-and-numbers-of-customers-by-region-and-local-authority
- Nee Joo Teh, Guillaume Goujon, Gilles Bortuzzo and Aidan Rhodes, 2011, UK Smart Grid Capabilities Development Programme Available from https://connect.innovateuk.org/c/document_library/get_file?groupId=2856395&folderId=3745741&title=UK+Smart+Grid+Capabilities+Development.pdf
- DECC (2012), 'Electricity System: Assessment of Future Challenges - Annex'
- DECC (2015), 'The first ever Capacity Market auction official results have been released today'
- Evans (2015), Carbon Brief: 'Old coal and gas plants won largest share of capacity market, final results confirm'
- Ward, Pooley and Owen (2012), Sustainability First: 'What demand side services can provide value to the electricity sector?'
- Mitchell (2014), 'Britain’s dinosaur capacity market will worsen energy ‘trilemma’.'
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- Houses of Parliament, Parliamentary Office of Science and Technology POSTnote (2014), "Electricity Demand-Side Response"
- (DSR can also be considered as a DER)
- Faruqui, A., Sergici, S., Shultz, E., 2013. Consistency of Results in Dynamic Pricing Experiments – Toward a Meta Analysis. Proceedings of DistribuTECH Conference, San Diego, CA, January 29, 2013.
- http://www.meter-on.eu/file/2014/10/Meter-ON%20Final%20report-%20Oct%202014.pdf .
- Smart Energy GB website. Available at: http://www.smartenergygb.org/national-rollout/how-its-happening
- DECC (2015) Smart Meters, Great Britain, Quarterly report to end June 2015. Available at:https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/459467/Smart_Meters_Quarterly_Statistics_Report_Q2_2015.pdf
- Smart Energy GB website. Available at: http://www.smartenergygb.org/get-a-smart-meter/energy-suppliers
- DECC (2013) Role of Community Groups in Smart Metering-Related Energy Efficiency Activities. Research by the Energy Saving Trust. Available at: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/166432/Role_of_community_groups_in_smart_metering-related.pdf
- Smart Meter Central Delivery Body (2013) Engagement Plan for Smart Meter Roll-out. Available at:http://www.smartenergygb.org/sites/default/files/engagement-plan-1213.pdf
- Which (2015) A local approach to energy efficiency. Available at:http://press.which.co.uk/wp-content/uploads/2015/03/EE-PDF-VERSION-FINAL-V4.pdf
- House of Commons Energy and Climate Change Committee (2015) Smart meters: progress or delay? Ninth Report of Session 2014–15. Available at: http://www.publications.parliament.uk/pa/cm201415/cmselect/cmenergy/665/66502.htm
- Bekiaris and Prentza (2013) "Evaluation of an Agent Based Monitoring and Brokerage System for Neighbourhood Electricity Usage Optimization"