HomeKey Stats Bristol
(→Housing stock stats) |
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!Average Unit Price (£) | !Average Unit Price (£) | ||
!Average Annual Bill (£) | !Average Annual Bill (£) | ||
+ | !Total Spend (£000,000's) | ||
|- | |- | ||
− | | Domestic||Standard Electricity||593||171,945||3,450||0.15||518 | + | | Domestic||Standard Electricity||593||171,945||3,450||0.15||518||89 |
|- | |- | ||
− | | ||Economy 7 Electricity||116||22,138||5,246||0.17||910 | + | | ||Economy 7 Electricity||116||22,138||5,246||0.17||910||20 |
|- | |- | ||
− | | ||Gas||2003||167,876||11,934||0.05||586 | + | | ||Gas||2003||167,876||11,934||0.05||586||98 |
|- | |- | ||
− | | Non-Domestic||Electricity||1152||17,590||65,509||0.15||9,830 | + | | Non-Domestic||Electricity||1152||17,590||65,509||0.15||9,830||173 |
|- | |- | ||
− | | ||Gas||735||1,966||373,871||0.05||18,347 | + | | ||Gas||735||1,966||373,871||0.05||18,347||36 |
|- | |- | ||
|} | |} |
Revision as of 15:34, 20 August 2015
Demographic stats
2011 census | Mid 2013 estimated | |
Population | 428,100 | 437,500 |
Households | 182,747 | 186,760 |
Energy stats
Bristol has an annual consumption of 1862 GWh (data from 2013) and a daily peak of around 307 MW during winter months.
Type | Electrical Capacity | Heat Capacity |
---|---|---|
Seabank | 1,145 | - |
Renewable Electricity | 53.9 | - |
Renewable Heat | - | 19.9 |
CHP | 9.2 | 11.9 |
Total | 1,208 | 32 |
REngine.php:in
pdf(rpdf, width=5, height=5) library(ggplot2) elec.consumption <- data.frame(Year = c(2009,2010,2011,2012,2013),
DomesticConsumption = c(718754856.9, 718735925.8, 718586755.1, 715382012, 709352993.9), DomesticMPANs = c(189391, 191066, 192449, 193322, 194083), NonDomesticConsumption = c(1176217057, 1202799481, 1185903139, 1135575674, 1152307023), NonDomesticMPANs = c(17500, 17444, 17350, 17552, 17590))elec.consumption$Domestic <- elec.consumption$DomesticConsumption/elec.consumption$DomesticMPANs elec.consumption$NonDomestic <- elec.consumption$NonDomesticConsumption/elec.consumption$NonDomesticMPANs elec.consumption <- elec.consumption[,c(1,6,7)] ggplot(data=elec.consumption, aes(x=Year, y=Domestic)) +
geom_bar(stat="identity", fill="#4D4D4D") + theme_bw() + theme(panel.border = element_blank(), axis.line = element_line()) + theme(plot.title = element_text(vjust = 2)) + scale_y_continuous(expand = c(0,0)) + xlab("Year") + ylab("Average consumption (kWh)")+ ggtitle("Average domestic electricity consumption\nper customer in Bristol")
REngine.php:in
pdf(rpdf, width=5, height=5) library(ggplot2) elec.consumption <- data.frame(Year = c(2009,2010,2011,2012,2013),
DomesticConsumption = c(718754856.9, 718735925.8, 718586755.1, 715382012, 709352993.9), DomesticMPANs = c(189391, 191066, 192449, 193322, 194083), NonDomesticConsumption = c(1176217057, 1202799481, 1185903139, 1135575674, 1152307023), NonDomesticMPANs = c(17500, 17444, 17350, 17552, 17590))elec.consumption$Domestic <- elec.consumption$DomesticConsumption/elec.consumption$DomesticMPANs elec.consumption$NonDomestic <- elec.consumption$NonDomesticConsumption/elec.consumption$NonDomesticMPANs elec.consumption <- elec.consumption[,c(1,6,7)] ggplot(data=elec.consumption, aes(x=Year, y=NonDomestic)) +
geom_bar(stat="identity", fill="#4D4D4D") + theme_bw() + theme(panel.border = element_blank(), axis.line = element_line()) + theme(plot.title = element_text(vjust = 2)) + scale_y_continuous(expand = c(0,0)) + xlab("Year") + ylab("Average consumption (kWh)")+ ggtitle("Average non-domestic electricity consumption\nper customer in Bristol")
REngine.php:in
pdf(rpdf, width=5, height=5) library(ggplot2) gas.consumption <- data.frame(Year = c(2009,2010,2011,2012,2013),
DomesticConsumption = c(2188753981, 2158524075, 2014008753, 2045449904, 2003430860), DomesticMPANs = c(162126, 163573, 164780, 168961, 167876), NonDomesticConsumption = c(881539141, 832499075, 783226304, 783928929, 735031042), NonDomesticMPANs = c(2013, 1975, 1915, 1974, 1966))gas.consumption$Domestic <- gas.consumption$DomesticConsumption/gas.consumption$DomesticMPANs gas.consumption$NonDomestic <- gas.consumption$NonDomesticConsumption/gas.consumption$NonDomesticMPANs gas.consumption <- gas.consumption[,c(1,6,7)] ggplot(data=gas.consumption, aes(x=Year, y=Domestic)) +
geom_bar(stat="identity", fill="#4D4D4D") + theme_bw() + theme(panel.border = element_blank(), axis.line = element_line()) + theme(plot.title = element_text(vjust = 2)) + scale_y_continuous(expand = c(0,0)) + xlab("Year") + ylab("Average consumption (kWh)")+ ggtitle("Average domestic gas consumption\nper customer in Bristol")
REngine.php:in
pdf(rpdf, width=5, height=5) library(ggplot2) gas.consumption <- data.frame(Year = c(2009,2010,2011,2012,2013),
DomesticConsumption = c(2188753981, 2158524075, 2014008753, 2045449904, 2003430860), DomesticMPANs = c(162126, 163573, 164780, 168961, 167876), NonDomesticConsumption = c(881539141, 832499075, 783226304, 783928929, 735031042), NonDomesticMPANs = c(2013, 1975, 1915, 1974, 1966))gas.consumption$Domestic <- gas.consumption$DomesticConsumption/gas.consumption$DomesticMPANs gas.consumption$NonDomestic <- gas.consumption$NonDomesticConsumption/gas.consumption$NonDomesticMPANs gas.consumption <- gas.consumption[,c(1,6,7)] ggplot(data=gas.consumption, aes(x=Year, y=NonDomestic)) +
geom_bar(stat="identity", fill="#4D4D4D") + theme_bw() + theme(panel.border = element_blank(), axis.line = element_line()) + theme(plot.title = element_text(vjust = 2)) + scale_y_continuous(expand = c(0,0)) + xlab("Year") + ylab("Average consumption (kWh)")+ ggtitle("Average non-domestic gas consumption\nper customer in Bristol")
Housing stock stats
REngine.php:in
pdf(rpdf, width=5, height=5) library(ggplot2) library(scales) library(grid) build_year <- data.frame (
build.year= c("pre-1870", "1871-1919", "1920-1945", "1946-1954", "1955-1979", "post-1980") , number=c(9847,37379,60307,25823,29126,18297))order <- c("pre-1870", "1871-1919", "1920-1945", "1946-1954", "1955-1979", "post-1980") ggplot(data=build_year, aes(x=build.year, y=number)) + geom_bar(stat="identity", fill="#4D4D4D", colour="black") +
theme_bw() + theme(panel.border = element_blank(), axis.line = element_line()) + scale_y_continuous(expand = c(0,0), labels=comma) + scale_x_discrete(limits = order) + ggtitle('Build year of Bristol homes') + theme(plot.title = element_text(vjust=2)) + theme(axis.title.y = element_text(vjust = 1)) + xlab("Build year") + ylab("Number of homes")
REngine.php:in
pdf(rpdf, width=5, height=5) library(ggplot2) library(scales) library(grid) built_form <- data.frame (
built.form= c("Detached", "Semi-detached", "Bungalow", "Terraced", "Flat") , number=c(8387,48887,2567,75569,45369))ggplot(data=built_form, aes(x=built.form, y=number)) + geom_bar(stat="identity", fill="#4D4D4D", colour="black") +
theme_bw() + theme(panel.border = element_blank(), axis.line = element_line()) + scale_y_continuous(expand = c(0,0), labels=comma) + ggtitle('Built form of Bristol homes') + theme(plot.title = element_text(vjust=2)) + theme(axis.title.y = element_text(vjust = 1)) + xlab("Built form") + ylab("Number of homes")
REngine.php:in
pdf(rpdf, width=5, height=5) library(ggplot2) library(scales) library(grid) bedrooms <- data.frame (
bedrooms= c("1 bedroom", "2 bedroom", "3 bedroom", "4 bedroom", "5 or more") , number=c(23952,40834,92492,11340,12161))ggplot(data=bedrooms, aes(x=bedrooms, y=number)) + geom_bar(stat="identity", fill="#4D4D4D", colour="black") +
theme_bw() + theme(panel.border = element_blank(), axis.line = element_line()) + scale_y_continuous(expand = c(0,0), labels=comma) + ggtitle('Number of bedrooms in Bristol homes') + theme(plot.title = element_text(vjust=2)) + theme(axis.title.y = element_text(vjust = 1)) + xlab("Number of bedrooms") + ylab("Number of homes")
REngine.php:in
pdf(rpdf, width=5, height=5) library(ggplot2) library(scales) library(grid) tenure <- data.frame (
tenure= c("Owner occupied", "Privately rented", "Council/housing association") , number=c(97622,29360,53797))ggplot(data=tenure, aes(x=tenure, y=number)) + geom_bar(stat="identity", fill="#4D4D4D", colour="black") +
theme_bw() + theme(panel.border = element_blank(), axis.line = element_line()) + scale_y_continuous(expand = c(0,0), labels=comma) + ggtitle('Tenure of Bristol homes') + theme(plot.title = element_text(vjust=2)) + theme(axis.title.y = element_text(vjust = 1)) + xlab("Tenure") + ylab("Number of homes")
The total energy bills for Bristol broken down by sector are:
Annual Consumption (GWh) | Meters | Average Annual Consumption (kWh) | Average Unit Price (£) | Average Annual Bill (£) | Total Spend (£000,000's) | ||
---|---|---|---|---|---|---|---|
Domestic | Standard Electricity | 593 | 171,945 | 3,450 | 0.15 | 518 | 89 |
Economy 7 Electricity | 116 | 22,138 | 5,246 | 0.17 | 910 | 20 | |
Gas | 2003 | 167,876 | 11,934 | 0.05 | 586 | 98 | |
Non-Domestic | Electricity | 1152 | 17,590 | 65,509 | 0.15 | 9,830 | 173 |
Gas | 735 | 1,966 | 373,871 | 0.05 | 18,347 | 36 |