Cost optimal sizing of smart buildings' energy system components considering changing end-consumer electricity markets

Abstract

Managing the electricity system becomes increasingly challenging, calling for modifications of the current electricity market. High fluctuations in power generation could make the introduction of dynamic end-consumer electricity pricing reasonable. Furthermore, the prediction of end-consumers’ power consumption would get easier when charging the maximum power capacity, instead of the consumed energy. Thus, this paper discusses the capability of smart buildings to cope with such market models and evaluates how the design of the electrical and thermal energy system of a modern German building is affected. Therefore, cost optimal sizing of the main supply system components is carried out based on a hybrid MILP and a heuristic optimization algorithm. The results indicate that local photovoltaic generation is beneficial in almost all market conditions, while except for the capacity market, batteries are only economical if prices decrease by more than 60%. The identified electricity price dynamics are too low to incentivize investments into load shifting capable supply or storage systems. Nevertheless, if an installed heat pump and the associated thermal storage have smart home capabilities, they support the maximization of PV self-consumption and reduce electricity cost.