Difference between revisions of "Helsinki energy consumption"

Latest revision as of 11:17, 9 November 2015

Many pieces of data on this page came originally from Building stock in Helsinki, worked by the Decision analysis and risk management 2015 course.

Question

How much energy is consumed and to what purposes in Helsinki?

Answer

There is no answer code here, because the U value 1.661 W /m² /K is directly used in Energy use of buildings#Baseline energy consumption.

Rationale

U values based on overall data

The total heat consumption by district-heated buildings is 6921.65 GWh in 2013 (see below). We can derive the total energy efficiency value expressed as W /m² /K for floor area and temperature difference between indoors and outdoors. The typical energy efficiency calculations (using the so called U value) assume that outdoor 17 °C is thermoneutral and lower values require heating. The total floor area of district-heated buildings is 38990000 m² in 2015 according to the Helsinki energy decision 2015 model. The annual average temperature in Helsinki is 4.8 °C [1] and during heating season Sep-May 1.4 C (Opasnet data). Therefore the energy efficiency value (approximate U value) is

Failed to parse (Missing <code>texvc</code> executable. Please see math/README to configure.): U = \frac{6921.65 GWh/a /(24 h / d \times 365 d/a)}{38990000 m^2 (17 K - 4.8 K)} = 1.661 \frac{W}{m^2 K}

Energy consumption statistics

Data not used

This section contains data, that wasn't in the end used in the model's calculations, but is still important enough that it wasn't completely removed from the page. There include energy parameters, energy sinks for different building types, and some data about the total energy consumption in Helsinki.

Previous temperature calculations

This data was perviously used for calculating Helsinki energy consumption. However, a more relevant data is now used on page Outdoor air temperature in Finland.

The annual average ambient temperature is 2.5 °C in Kuopio (Ambient temperature in Urgenche cities). Therefore, we could use hourly temperature data from Kuopio if we add the temperature difference 2.3 K. Graphs of the data.

## This is code is Op_en7317/temperatures [[Helsinki energy consumption]]
library(OpasnetUtils)

ta <- opbase.data("Op_en6315", subset = "2014-5/2015") # [[Electricity use in a house with geothermal heating]]
hours <- as.character(ta$Date)

if(!exists("server")) {
	dates <- data.frame(
		EN = c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"), 
		FI = c("Tammi", "Helmi", "Maalis", "Huhti", "Touko", "Kesä", "Heinä", "Elo", "Syys", "Loka", "Marras", "Joulu")
	)
	for(i in 1:nrow(dates)) {
		hours <- gsub(dates$EN[i], dates$FI[i], hours)
	}
}

hours <- as.POSIXct(strptime(hours, format = "%Y-%b-%d %H:%M:%S"))
hours <- hours + as.difftime(as.character(ta$Time), format = "%H:%M")

# Adjust temperature data: 2.3 C is the average difference between Kuopio and Helsinki
hours <- data.frame(Time = hours, Result = as.numeric(as.character(ta$Result)) + 2.3)
hours <- hours[!is.na(hours$Result) , ]
hours$Date <- as.POSIXct(strptime(format(hours$Time, "%Y-%m-%d"), format = "%Y-%m-%d"))
hours <- hours[hours$Time >= as.POSIXct("2014-03-01 00:00:00") & hours$Time < as.POSIXct("2015-03-01 00:00:00") , ]

days <- aggregate(hours["Result"], hours["Date"], FUN = mean)
days$Temperature <- cut(days$Result, breaks = seq(-30, 33, 3))
temperatures <- Ovariable("temperature", data = aggregate(days["Result"], days["Temperature"], FUN = mean))
temperdays <- Ovariable("temperdays", data = aggregate(days["Result"], days["Temperature"], FUN = length))

objects.store(temperatures, temperdays)
cat("Objects temperature, temperdays stored.\n")

#ggplot(hours, aes(x = Time, y = Result))+geom_line() + geom_point(data = days, aes(x = Date, y = Result, colour = "Daily mean", size = 2))
#ggplot(hours, aes(x = Time, y = Result))+geom_point()

Energy parametres of buildings

Notes

Data from:

• CyPT Data collection - To Jouni
• Default Building Data - Helsinki
• Energy performance class A in building automation www.siemens.com [2]

The numbers found are not reliable, because most of the high technology buildings such as buildings with insulated walls or windows started to be build from 10 to 15 years ago. If we could find the building area in the year 2000, we could subtract that from the building area in Helsinki at the moment and get the building area which is built during these 10-15 years. Those would be the high tech building areas with regard to 2 % renovation rate and rebuilding which is on going every year and should be added to the total amount.

Technical notes: Sheets 5_Input Residential, 6.0_Input Non Residential, 6.2_Input Public Admin. Priority 1. Auxiliaries PPT.

Energy demand

Notes

• Data from Climate policies Helsinki additional data
• We went through the data mentioned above and also the files given in Climate policies Helsinki data but could not find the data for cooling, heating:infiltration, heating:other, heating:warm water:other and electricity:ventilation:residential.
• Total estimated amount of energy needed for cooling 23504480 kWh/a (whole Helsinki). Based on [3] 14332 GWh/a for housing (total energy demand minus traffic 18 % [4] and [5] 2 % of total energy demand of housing used for cooling. Total floor area of Helsinki needed (table 1).

Technical notes: Sheets 5_Input Residential, 6.0_Input Non Residential, 6.2_Input Public Admin. Priority 1. Auxiliaries: see table.

Efficiency increase

Changes in energy efficiency of different energy sinks.

• Cooling 2 % /a
• Warm water heating 1.1 % /a in residential buildings
• General improvement: 0.6 % /a: Estimated 3 % of houses renovated/year and 20 % increase in energy efficiency when renovated. [6] Data apart from 0.6% values from Climate policies Helsinki additional data
• The presentation about tables 4 and 5 PresentationHW9

Technical notes: Sheets 5_Input Residential, 6.0_Input Non Residential, 6.2_Input Public Admin. Priority 3. Auxiliaries Excel.

Heating parameters of buildings

Notes

• Data used: Unit heat consumption of buildings in Finland.
• Data Climate policies Helsinki additional data only contained 0.00 for all the parameters.
• EU legislation value for U-value of windows in the document below was 1.0, so we used it for building buildings and the past years' values for the non-residential buildings. We assumed this will be the new residential buildings to be within the legislative value. ^{[2] [3] [4]}
• HW9 table 6 presentation: Helsinki Building Stock

Technical notes: Sheets 5_Input Residential, 6.0_Input Non Residential, 6.2_Input Public Admin. Priority 3. Auxiliaries: see table.

Values derived from Unit heat consumption of buildings in Finland (these could be used to update Table 6):

See also

• Helsingin parhaat energiatehokkuuskäytännöt -työryhmän loppuraportti (2011-2013)

Keywords

References

Related files