Aaltodoc (Aalto University) · 2017 · 13 citations · 0 references
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ArchitectureArchitectural EngineeringBuilding ScienceHeatingThermal ComfortVentilationBuilding Energy ModelingBuilding Energy SystemsBuilding Thermal PerformanceDistrict HeatingHeat Transfer In BuildingsThermal Comfort In Educational BuildingsBuilding Energy Performance SimulationBuilding Heating Load ReductionComfortDemand Response ControlDynamic Energy ModelingEnergy-comfort Trade-offsIndoor Thermal ComfortThermal Comfort Adaptation
Demand response on the building level aids stabilization of the consumption profile in the district \nheating and electricity grid. A stable consumption reduces peak demand and need for high cost peak \npower plants like heat-only boilers and gas turbines. The main benefit achieved is less CO2 emissions \nat the same time the producer and consumer benefit economically through cheaper production costs. \n \nThe main objective with this study was to simulate a detailed model of an educational office building \nfloor to determine the monetary saving potential of demand response combined with dynamic hourly \ndistrict heating and electricity prices. In addition, the difference in potential between centralized and \ndecentralized control approaches was to be examined. The impact on indoor environmental comfort \nand heating flexibility of the building were areas of interest. The heating flexibility is a measure of \nthe buildings ability to adapt the heating according to the dynamic price signals sent by the energy \nproducer. Both CAV and VAV ventilation designs were included in the study. In addition, the \nmonetary savings potential of contract-power limitation within district heating and its impact on \nthermal comfort were studied. \n \nThe impact of demand response was studied by control of space heating, adjustment of supply air \ntemperature and airflow regulation. The research was conducted by dynamic energy simulations of \nan educational office building on the Aalto University campus area. The simulation software used \nwas IDA Indoor Climate and Energy (version 4.7.1). Acceptable ranges of indoor environmental \ncomfort parameters (temperature, PMV, CO2) were chosen and rule based control algorithms were \ndeveloped and implemented into the simulation program. \n \nA centralized control approach of space heating did not show any significant potential in heat cost \nsavings (1.5%) and the heating flexibility remained low (2.9%). The decentralized approach reached \nheat cost savings of 5% – 6% and heating flexibility of up to 15% when controlling both space \nheating and supply air temperature in CAV ventilation cases. All demand response control \nalternatives managed to maintain a good thermal comfort for over 90% of the occupied time. \nOccupancy did not affect neither cost savings, heating flexibility nor thermal comfort in any of the \ndifferent simulation set-ups. \n \nThe contract power of the building could be cut by 35% without affecting the thermal comfort at all. \nThis brought an annual cost saving of 6.1 €/m2 – 26.9 €/m2 (27.1% – 35%) depending on district heat \nprovider. A peak demand cut by 43% had only minor impact on the thermal comfort and provided \neven greater annual cost savings. The main conclusions from the study are that demand response \nwithin heating is only beneficial with a decentralized control and that peak demand limiting within \ndistrict heating have a big cost saving potential.