Energy use of buildings

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Question

What is the use of energy of buildings?

Rationale

Baseline energy consumption

Baseline energy consumption per area unit(kWh/m2/a)

Obs	Building	Heating	Heat	User electricity	Total electricity	Year	Description
1	Detached houses	District	134.74	50	184.74	2010	Calculated from energy company´s data; Pöyry
2	Detached houses	Electricity	130	50	180	2010	Energiapolar; Pöyry
3	Detached houses	Oil	134.74	50	50	2010	Pöyry. Efficiency 90-95% (energiatehokaskoti.fi).
4	Detached houses	Wood	134.74	50	50	2010	Assumption. Efficiency of good kettles 80%(energiatehokaskoti.fi).
5	Detached houses	Geothermal	40	50	90	2010	Assumption
6	Row houses		168.88	73.5	73.5	2010	Calculated from energy company´s data. Based on district
7	Apartment houses		172.31	41.7	41.7	2010	Calculated from energy company´s data. Based on district
8	Commercial		161.82	229.6	229.6	2010	Calculated from energy company´s data. Based on district
9	Offices		161.07	93.1	93.1	2010	Calculated from energy company´s data. Based on district
10	Health and social sector		214.97	122.81	122.81	2010	Calculated from energy company´s data. Based on district
11	Public		165.47	110.4	110.4	2010	Calculated from energy company´s data. Based on district
12	Sports		121.38	85.9	85.9	2010	Calculated from energy company´s data. Based on district
13	Educational		170	116.4	116.4	2010	Calculated from energy company´s data. Based on district
14	Industrial		168.44	212.4	212.4	2010	Calculated from energy company´s data. Based on district
15	Leisure houses		2.4	1	3.4	2010	Calculated from energy company´s data. Based on electricity
16	Other		138.14	170.3	170.3	2010	Calculated from energy company´s data
17	Non-residential buildings		150	50			Guesstimate for Basel
18	Special constructions		150	50			Guesstimate for Basel
19	Single-family houses		150	50			Guesstimate for Basel
20	Multiple-family houses		150	50			Guesstimate for Basel
21	Residential buildings with subsidiary use		150	50			Guesstimate for Basel
22	Buildings with partial residential use		150	50			Guesstimate for Basel

Pöyry 2011.

Energiapolar.

Energiatehokaskoti.fi/Öljylämmitys

----#: . Note that below numbers are very preliminary (esp. electricity)! --Marjo 16:49, 13 March 2013 (EET) (type: truth; paradigms: science: comment)

Baseline energy consumption per volume unit(kWh/m3/a)

Obs	Building	Heating	Heat	User electricity	Year	Description
1	Detached houses	District	42.15	15.67	2010	Calculated from energy company´s data; Energiapolar
2	Detached houses	Electricity	40.66	15.67	2010	Energiapolar
3	Detached houses	Oil	42.15	15.67	2010	Energiapolar
4	Detached houses	Wood	42.15	15.67	2010	Assumption
5	Detached houses	Geothermal	18.56	15.67	2010	Assumption
6	Row houses	District	53.25	23.16	2010	From energy company
7	Apartment houses	District	49.2	11.9	2010	From energy company
8	Commercial	District	28.65	40.64	2010	From energy company
9	Offices	District	36.32	20.99	2010	From energy company
10	Health and social sector	District	55.2	31.53	2010	From energy company
11	Public	District	32.21	21.49	2010	From energy company
12	Sports	District	18.37	13	2010	From energy company; Electricity value comes from city´s renovation data
13	Educational	District	40.23	27.54	2010	From energy company
14	Industrial	District	30.57	38.55	2010	From energy company
15	Leisure houses	Electricity	0.68	0.29	2010	From energy company
16	Other	District	29.88	36.83	2010	From energy company

Energy efficiency in heating

What is the relative energy consumption of different efficiency classes compared with Old? This table tells that with some background information about heat (in kWh/m2/a), electricity, and water consumption.

Energy use by energy class of building(ratio)

Obs	Efficiency	Ratio	Heat	User electricity	Water	Description
1	Traditional	1.2-1.4	200			Guesstimate
2	Old	1	150		30	Pöyry 2011 s.28
3	New	0.4-0.5	70	50	40	Pöyry 2011 s.32 (2010 SRMK)
4	Low-energy	0.2-0.25	35	50	40	Personal communication
5	Passive	0.1-0.16	17.5 - 25	50	40	Pöyry 2011 s.33; Personal communication

Energy efficiency of new buildings in the future(%)

Obs	Efficiency	Constructed	Fraction	Description
1	New	2020-2029	10-20
2	Low-energy	2020-2029		The rest of energy class
3	Passive	2020-2029	25-35
4	New	2030-2039	5-10
5	Low-energy	2030-2039	20-50
6	Passive	2030-2039		The rest of energy class
7	New	2040-2049	0-5
8	Low-energy	2040-2049	10-30
9	Passive	2040-2049		The rest of energy class

• Old: old buildings to be renovated (or in need of renovation)
• New: normal new buildings (no current need of renovation)
• Low-energy: buildings consuming about half of the energy of a new building
• Passive: buildings consuming a quarter or less of the energy of a new building
• Chinese green building system: [4] [5]

Impact of renovations

Energy saving potential of different renovations(%,kWh/m2/a)

Obs	Efficiency	Building2	Renovation	Relative	Absolute	Renovation details	Description
1	Old	Residential	Windows	15	25	New windows and doors	Pöyry 2011
2	Old	Residential	Technical systems	50	75	New windows, sealing of building's sheath, improvement of building's technical systems	Pöyry 2011
3	Old	Residential	Sheath reform	65	100	New windows, sealing of building's sheath, improvement of building's technical systems, significant reform of building's sheath	Pöyry 2011
4	Old	Non-residential	General	15	-	General renovation	Pöyry 2011
5	Old		None	0	0	Renovation not done
6	New		None	0	0	Renovation not done
7	Low-energy		None	0	0	Renovation not done
8	Passive		None	0	0	Renovation not done

Regulations regarding energy consumption of buildings

Maximum allowed energy consumption per unit (= E-value)(kWh/m2/a)

Obs	Building	Year	E-value	Description
1	Detached houses	2012 forward	204	Heated net area <120 m2; Finland´s Environmental Administration
2	Row houses	2012 forward	150	Finland´s Environmental Administration
3	Apartment houses	2012 forward	130	Finland´s Environmental Administration
4	Shops and other commercial buildings	2012 forward	240	Finland´s Environmental Administration
5	Offices	2012 forward	170	Finland´s Environmental Administration
6	Health and social sector: Hospitals	2012 forward	450	Finland´s Environmental Administration
7	Health and social sector: Health care centers etc.	2012 forward	170	Finland´s Environmental Administration
8	Public	2012 forward	240	Finland´s Environmental Administration
9	Sports	2012 forward	170	Does not apply to swimming- and ice halls; Finland´s Environmental Administration
10	Educational	2012 forward	170	Finland´s Environmental Administration
11	Industrial	2012 forward	-	E-value must be calculated but there´s no limit for it; Finland´s Environmental Administration
12	Leisure buildings	2012 forward	-	E-value must be calculated but there´s no limit for it; Finland´s Environmental Administration
13	Other	2012 forward	-	E-value must be calculated but there´s no limit for it; Finland´s Environmental Administration

Calculations for ovariables

+ Show code- Hide code library(OpasnetUtils) energyUse <- Ovariable( name = 'energyUse', ddata = 'Op_en5488', subset = 'Baseline energy consumption per area unit' ) levels(energyUse@data$Heating)[levels(energyUse@data$Heating) == ""] <- NA energyUse@data <- fillna(energyUse@data, "Heating") energyUse@data <- energyUse@data[ energyUse@data[["Energy use"]] == "Heat" , colnames(energyUse@data) != "Energy use" ] energy.per.volume <- Ovariable( name = 'energy.per.volume', ddata = 'Op_en5488', subset = 'Baseline energy consumption per volume unit' ) efficienciesNew <- Ovariable( name = 'efficienciesNew', ddata = 'Op_en5488', subset = 'Energy efficiency of new buildings in the future' ) efficienciesNew@data$Efficiency <- factor( efficienciesNew@data$Efficiency, levels = c("Old", "New", "Low-energy", "Passive"), ordered = TRUE ) Maximum.allowed.energy.consumption.per.unit <- Ovariable( name = 'Maximum.allowed.energy.consumption.per.unit', ddata = 'Op_en5488', subset = 'Maximum allowed energy consumption per unit (= E-value)' ) savingPotential <- Ovariable( name = 'savingPotential', ddata = 'Op_en5488', subset = 'Energy saving potential of different renovations' ) savingPotential@data <- savingPotential@data[ savingPotential@data$Observation == "Relative" , colnames(savingPotential@data) != "Observation" ] savingPotential@data$Renovation <- factor( savingPotential@data$Renovation, levels = c("None", "General", "Windows", "Technical systems", "Sheath reform"), ordered = TRUE ) levels(savingPotential@data$Building2)[levels(savingPotential@data$Building2) == ""] <- NA savingPotential@data <- fillna(savingPotential@data, "Building2") savingPotential@data$savingPotentialResult <- 1 - as.numeric(as.character(savingPotential@data$savingPotentialResult)) / 100 efficiencyRatio <- Ovariable( name = 'efficiencyRatio', ddata = 'Op_en5488', subset = 'Energy use by energy class of building' ) objects.store( energyUse, energy.per.volume, efficienciesNew, savingPotential, efficiencyRatio ) cat("Objects energyUse, energy.per.volume, efficienciesNew, savingPotential, efficiencyRatio initiated!\n")