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Ponencia Jornada técnica “Proyectos europeos en eficiencia energética en edificación”

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Ponencia Jornada técnica “Proyectos europeos en eficiencia energética en edificación”

  1. 1. Oviedo, 27 February 2014 Paolo Michele Sonvilla Minerva Consulting & Communication Ahorros energéticos obtenidos con el EnRima DSS
  2. 2. An Integrated Approach to Optimal Energy Operations in Buildings P. Rocha1 M. Groissböck2 A. Siddiqui1,3 M. Stadler2 1 University College London 2 Center for Energy and Innovative Technologies 3 Stockholm University e-nova 2013 Conference, 15 November 2013
  3. 3. 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 of existing buildings must be improved
  4. 4. Background Multiple objectives & combinations of resource-load pairs =⇒ operational optimisation model (Hobbs, 1995)
  5. 5. Decision Support Schema
  6. 6. 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 & cooling demand 1Groissböck et al. (2013), Liang et al. (2012)
  7. 7. 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)
  8. 8. Integrated Operational Optimisation Model minimise Energy trading costs + technology operation costs subject to Upper-level constraints: Energy balance Technology capacity limits Energy trading limits Storage constraints Lower-level constraints: Zone temperature update & bounds Energy flows & operational constraints for radiators Energy flows & operational constraints for HVAC systems
  9. 9. Numerical Examples • Two test sites: • Centro de Adultos La Arboleya (Siero, Spain), from Fundación Asturiana de Atención y Protección a Personas con Discapacidades y/o Dependencias (FASAD) • Fachhochschule Burgenland’s Pinkafeld campus (Pinkafeld, Austria) • Typical winter day, hourly decision intervals • Cases: • FMT: Fixed mean temperature • OPT: Optimisation
  10. 10. 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, 0.05 e/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
  11. 11. FASAD’s Results Scenarios 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 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 FMT Time (h) Temperature(o C) Estimated Zone Temperature = Required Zone Temperature External 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 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 OPT Time (h) Temperature( o C) Lower Limit Temperature Optimal Zone Temperature Upper Limit Temperature External Temperature
  12. 12. FASAD’s Results FMT OPT Space 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 24 0 10 20 30 40 50 60 70 80 90 100 Space Heat Demand Time (h) SpaceHeatDemand(kWh) FMT OPT 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 Natural Ventilation Time (h) NaturalVentilation(m 3 /s) FMT OPT
  13. 13. FASAD’s Results FMT OPT Space 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 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 FMT Time (h) Temperature(o C) Estimated Zone Temperature = Required Zone Temperature External 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 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 OPT Time (h) Temperature( o C) Lower Limit Temperature Optimal Zone Temperature Upper Limit Temperature External Temperature
  14. 14. FASAD’s Results FMT OPT Primary Cost CO2 Primary Cost CO2 Energy 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%
  15. 15. 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, 0.08 e/kWhe for electricity sales, 0.08 e/kWh for district heat purchases • Scenario 2: Installation of a 100 kWp PV system & availability of an electricity 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 at 14:00-17:00, 0.14 e/kWhe otherwise) • Scenario 4: Installation of a 75 kW solar thermal system
  16. 16. 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 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 FMT Time (h) Temperature(o C) Estimated Zone Temperature = Required Zone Temperature External 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 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 OPT Time (h) Temperature( o C) Lower Limit Temperature Optimal Zone Temperature, Scenarios 1−3 Optimal Zone Temperature, Scenario 4 Upper Limit Temperature
  17. 17. Pinkafeld’s Results FMT OPT Space HVAC Cost CO2 Space HVAC Cost CO2 Heat 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 24 0 10 20 30 40 50 60 70 80 90 100 Space Heat Demand Time (h) SpaceHeatDemand(kWh) FMT OPT, Scenarios 1−3 OPT, 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 24 0 0.5 1 1.5 2 2.5 3 HVAC Ventilation Time (h) HVACVentilation(m 3 /s) FMT OPT, Scenarios 1−3 OPT, Scenario 4
  18. 18. Pinkafeld’s Results FMT OPT Primary Cost CO2 Primary Cost CO2 Energy 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%
  19. 19. Summary • Short-term building energy management model consisting of upper- and lower-level operational modules • Evaluated using data from two EU test sites and plausible future operating 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

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