An optimal home energy management system for modulating heat pumps and photovoltaic systems

Efficient residential sector coupling plays a key role in supporting the energy transition. In this study, we analyze the structural properties associated with the optimal control of a home energy management system and the effects of common technological configurations and objectives. We conduct thi...

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Veröffentlicht in:Applied energy Jg. 278; S. 115661
Hauptverfasser: Langer, Lissy, Volling, Thomas
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 15.11.2020
Schlagworte:
batteries
Demand-side flexibility
economic sustainability
energy
heat
Heat pump
heat pumps
linear models
management systems
Mixed-integer linear programming(MILP)
Model predictive control(MPC)
Photovoltaics(PV)
prediction
tariffs
Thermal energy storage
Demand-side flexibility
Thermal energy storage
Mixed-integer linear programming(MILP)
Model predictive control(MPC)
Heat pump
Photovoltaics(PV)
ISSN:0306-2619, 1872-9118
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Zusammenfassung:Efficient residential sector coupling plays a key role in supporting the energy transition. In this study, we analyze the structural properties associated with the optimal control of a home energy management system and the effects of common technological configurations and objectives. We conduct this study by modeling a representative building with a modulating air-sourced heat pump, a photovoltaic(PV) system, a battery, and thermal storage systems for floor heating and hot-water supply. In addition, we allow grid feed-in by assuming fixed feed-in tariffs and consider user comfort. In our numerical analysis, we find that the battery, naturally, is the essential building block for improving self-sufficiency. However, in order to use the PV surplus efficiently grid feed-in is necessary. The commonly considered objective of maximizing self-consumption is not economically viable under the given tariff structure; however, close-to-optimal performance and significant reduction in solution times can be achieved by maximizing self-sufficiency. Based on optimal control and considering seasonal effects, the dominant order of PV distribution and the target states of charge of the storage systems can be derived. Using a rolling horizon approach, the solution time can be reduced to less than 1min (achieving a time resolution of 1h per year). By evaluating the value of information, we find that the common horizon of 24h for prediction and control results in unintended but avoidable end-of-horizon effects. Our input data and mixed-integer linear model developed using the Julia JuMP programming language are available in an open-source manner. •Mixed-integer linear program analyzes an integrated home energy management system.•Target states of charge and charging times are obtained from the optimal flows.•Grid feed-in increases the process efficiency and maintains the self-sufficiency.•Maximizing self-consumption reduces net profits due to inefficient PV processing.•Rolling horizons must be carefully configured to eliminate the end-of-horizon effect.
Bibliographie:ObjectType-Article-1
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ISSN:0306-2619
1872-9118
DOI:10.1016/j.apenergy.2020.115661