ponencias de la jornada técnica “proyectos europeos en eficiencia energética en edificación”
DESCRIPTION
Ponencia Luis Santos EDP Posibles modelos de negociso por la adopción del ENRIMATRANSCRIPT
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Oviedo, 27 February 2014
Paolo Michele Sonvilla
Minerva Consulting & Communication
Ahorros energéticos obtenidos con el EnRima DSS
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An Integrated Approach to Optimal Energy
Operations in Buildings
P. Rocha1 M. Groissböck2 A. Siddiqui1,3 M. Stadler2
1University College London
2Center for Energy and Innovative Technologies
3Stockholm University
e-nova 2013 Conference,
15 November 2013
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Background
EU policy objectives for year 2020 include:• ↓ greenhouse gas emissions by ≥ 20% below 1990 levels• ↑ contribution of renewable resources to EU energy consumption
to 20%• ↓ primary energy use by 20% relative to projections
=⇒ energy efficiency ofexisting buildingsmust be improved
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Background
Multiple objectives & combinations of resource-load pairs=⇒ operational optimisation model (Hobbs, 1995)
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Decision Support Schema
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Lower-Level Operational Module1
• Determines operation of heating, ventilation & cooling systems given:
• thermodynamics of conventional heating & HVAC systems• building’s physics• external temperatures & solar gains• internal loads
• Range for zone temperature =⇒ endogenous space heat & coolingdemand
1Groissböck et al. (2013), Liang et al. (2012)
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Upper-Level Operational Module
• Determines sourcing of energy & operation of installed equipment
• Upper-level constraints:• Energy balance equation:
EnergyPurchased − EnergySold + EnergyOutput − EnergyInput +EnergyFromStorage − EnergyToStorage = Demand
• Technology capacity limits
• Energy trading limits
• Energy storage constraints
• King and Morgan (2007), Marnay et al. (2008), Stadler et al. (2012),Pruitt et al. (2013)
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Integrated Operational OptimisationModel
minimise Energy trading costs + technology operation costs
subject to Upper-level constraints:Energy balanceTechnology capacity limitsEnergy trading limitsStorage constraints
Lower-level constraints:Zone temperature update & boundsEnergy flows & operational constraints for radiatorsEnergy flows & operational constraints for HVAC systems
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Numerical Examples• Two test sites:
• Centro de Adultos La Arboleya (Siero, Spain), from FundaciónAsturiana de Atención y Protección a Personas conDiscapacidades y/o Dependencias (FASAD)
• Fachhochschule Burgenland’s Pinkafeld campus (Pinkafeld,
Austria)
• Typical winter day, hourly decision intervals
• Cases:• FMT: Fixed mean temperature• OPT: Optimisation
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Operating Scenarios for FASAD
• Scenario 1 (Baseline):• Conventional heating and natural ventilation• 1293.3 kW and 232.6 kW natural gas-fired boilers, 5.5 kWe CHP
unit• Exogenous daily end-use electricity demand of 691 kWhe and
domestic hot water demand of 1592 kWh• Flat energy tariff rates: 0.14 e/kWhe for electricity purchases, 0.05e/kWh for natural gas purchases
• Electricity feed-in tariff (FiT) of 0.18 e/kWhe
• Scenario 2: Revocation of FiT
• Scenario 3: Regulation imposes that zone temperature ≤ 21◦C
• Scenario 4: Installation of a 7.58 kW solar thermal system
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FASAD’s ResultsScenarios 1, 2 and 4
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24−4−2
02468
101214161820222426283032
FMT
Time (h)
Tem
pera
ture
(o C)
Estimated Zone Temperature = Required Zone TemperatureExternal Temperature
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24−4−2
02468
1012141618202224262830
OPT
Time (h)
Tem
pera
ture
(o C)
Lower Limit TemperatureOptimal Zone TemperatureUpper Limit TemperatureExternal Temperature
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FASAD’s Results
FMT OPTSpace Heat Cost CO2 Space Heat Cost CO2
Demand Emissions Demand Emissions(kWh) (e) (kg) (kWh) (e) (kg)
Scen. 1,2,4 700 42 154 494 30 108-29% -29% -30%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 240
10
20
30
40
50
60
70
80
90
100Space Heat Demand
Time (h)
Spac
e He
at D
eman
d (k
Wh)
FMTOPT
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 240
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8Natural Ventilation
Time (h)
Natu
ral V
entila
tion
(m3 /s
)
FMTOPT
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FASAD’s Results
FMT OPTSpace Heat Cost CO2 Space Heat Cost CO2
Demand Emissions Demand Emissions(kWh) (e) (kg) (kWh) (e) (kg)
Scen. 3 558 34 123 474 29 104-15% -15% -15%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24−4−2
02468
101214161820222426283032
FMT
Time (h)
Tem
pera
ture
(o C)
Estimated Zone Temperature = Required Zone TemperatureExternal Temperature
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24−4−2
02468
1012141618202224262830
OPT
Time (h)
Tem
pera
ture
(o C)
Lower Limit TemperatureOptimal Zone TemperatureUpper Limit TemperatureExternal Temperature
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FASAD’s Results
FMT OPTPrimary Cost CO2 Primary Cost CO2Energy Emissions Energy Emissions(kWh) (e) (kg) (kWh) (e) (kg)
Scen. 1 4071.0 213.7 809.9 3847.9 202.0 764.9-5.5% -5.5% -5.5%
Scen. 2 3798.8 218.0 757.3 3576.1 206.4 712.3-5.9% -5.3% -6%
Scen. 3 3917.3 205.6 778.9 3827.2 200.9 760.7-2.3% -2.3% -2.3%
Scen. 4 4019.6 211.0 799.5 3796.6 199.3 754.5-5.5% -5.5% -5.6%
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Operating Scenarios for Pinkafeld
• Scenario 1 (Baseline):• Heating and HVAC systems• 1.28 kWp PV system• Exogenous daily end-use electricity demand of 543 kWhe
• Flat energy tariff rates: 0.15 e/kWhe for electricity purchases, 0.08e/kWhe for electricity sales, 0.08 e/kWh for district heat purchases
• Scenario 2: Installation of a 100 kWp PV system & availability of anelectricity FiT (0.18 e/kWhe)
• Scenario 3: Change to a time-of-use (TOU) electricity purchasing tariff(0.16 e/kWhe at 7:00-14:00 and 17:00-20:00, 0.15 e/kWhe at14:00-17:00, 0.14 e/kWhe otherwise)
• Scenario 4: Installation of a 75 kW solar thermal system
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Pinkafeld’s Results
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24−4−2
02468
101214161820222426283032
FMT
Time (h)
Tem
pera
ture
(o C)
Estimated Zone Temperature = Required Zone TemperatureExternal Temperature
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24−4−2
02468
101214161820222426283032
OPT
Time (h)
Tem
pera
ture
(o C)
Lower Limit TemperatureOptimal Zone Temperature, Scenarios 1−3Optimal Zone Temperature, Scenario 4Upper Limit Temperature
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Pinkafeld’s ResultsFMT OPT
Space HVAC Cost CO2 Space HVAC Cost CO2Heat Elec. Emis- Heat Elec. Emis-
Demand Demand sions Demand Demand sions(kWh) (kWhe) (e) (kg) (kWh) (kWhe) (e) (kg)
Scen. 1–3 696 5.73 55.9 20.9 629 3.64 50.5 18.9-10% -37% -10% -10%
Scen. 4 696 5.73 53.7 20.1 644 3.91 48.8 18.2-7.5% -38% -9% -9%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 240
10
20
30
40
50
60
70
80
90
100Space Heat Demand
Time (h)
Spac
e He
at D
eman
d (k
Wh)
FMTOPT, Scenarios 1−3OPT, Scenario 4
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 240
0.5
1
1.5
2
2.5
3HVAC Ventilation
Time (h)
HVAC
Ven
tilatio
n (m
3 /s)
FMTOPT, Scenarios 1−3OPT, Scenario 4
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Pinkafeld’s Results
FMT OPTPrimary Cost CO2 Primary Cost CO2Energy Emissions Energy Emissions(kWh) (e) (kg) (kWh) (e) (kg)
Scen. 1 1987.5 137.9 29.5 1851.2 132.2 27.5-6.9% -4.1% -6.8%
Scen. 2 1989.4 113.0 29.6 1853.1 107.3 27.5-6.9% -5.1% -7.1%
Scen. 3 1987.5 139.4 29.5 1851.2 133.7 27.5-6.9% -4.1% -6.8%
Scen. 4 1933.3 135.7 28.7 1808.8 130.5 26.9-6.5% -3.9% -6.3%
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Summary
• Short-term building energy management model consisting ofupper- and lower-level operational modules
• Evaluated using data from two EU test sites and plausible futureoperating scenarios
• 10-30% ↓ space heat demand and associated CO2 emissions
• 5-7% ↓ overall primary energy consumption
• Reflects load-shifting behaviour
• Future work:
• Multi-criteria objective function
• Further policy insights