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HomeKey Stats Bristol

Revision as of 12:31, 11 August 2015 by Joem (Talk | contribs) (Key stats about Bristol)

Key stats about Bristol

2011 census Mid 2013 estimated
Population 428,100 437,500
Households 182,747 186,760

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")
 
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