An optimal home energy management system for modulating heat pumps and photovoltaic systems. (15th November 2020)

• Record Type: Journal Article
• Authors: Langer, Lissy; Volling, Thomas
• Is Part Of: Applied energy. Volume 278(2020)
• Publication Date: 2020-11-15
• Subjects: Heat pump -- Photovoltaics(PV) -- Demand-side flexibility -- Thermal energy storage -- Model predictive control(MPC) -- Mixed-integer linear programming(MILP); Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2020.115661
• Languages: English
• ISSNs: 0306-2619

Abstract

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 1 min (achieving a time resolution of 1 h per year). By evaluating the value of information, we find that the common horizon of 24 h 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. Highlights: 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.