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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| Published in: | Applied energy Vol. 278; p. 115661 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
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Elsevier Ltd
15.11.2020
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| ISSN: | 0306-2619, 1872-9118 |
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| Abstract | 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. |
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| AbstractList | 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. 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. |
| ArticleNumber | 115661 |
| Author | Volling, Thomas Langer, Lissy |
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| Keywords | Demand-side flexibility Thermal energy storage Mixed-integer linear programming(MILP) Model predictive control(MPC) Heat pump Photovoltaics(PV) |
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| SubjectTerms | 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 |
| Title | An optimal home energy management system for modulating heat pumps and photovoltaic systems |
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