Fast hierarchical coordination using price signal for town-scale home-EMSs aggregation with digital annealer

The demand response (DR), which balances power supply and demand, is attracting attention as a method of absorbing fluctuations in renewable energy when output is unstable. Since the Great East Japan Earthquake in 2011, Japan has made progress toward the liberalization of electricity and the introduction of renewable energy. In 2021, a supply and demand adjustment market will be opened. Unlike companies and factories, which can control large amounts of power for long periods, household demand has a small capacity and is short term. However, household demand is expected to be able to respond quickly to emergencies and to secure capacity by consolidating multiple households via an aggregator. This study concerns two problems in assessing town-scale residential DR capability. First, we evaluate residential DR response capacity. This capacity is assumed to be pre-cooling heating by an air conditioner according to thermal insulation and heat capacity characteristics, and energy storage by a hot water storage tank and a power storage device. Next, we investigate implementing the optimization of the town-scale DR by an aggregator. Optimal town-scale aggregation proposals are often formulated in large-scale combinatorial optimization problems. The challenge is that the calculation tends to be time-consuming and difficult to solve. In this research, we propose a framework that can be solved at high speed using digital annealer. Finally, we evaluate the possibility of town-scale residential DR in specific areas of Tokyo.