Design and implementation of power management system integrated with cooperative systems for an apartment building

The power management system (PMS) for detached houses has been studied for many years; however, the PMS for apartment buildings (APBs) is not fully understood considering the structures of the APBs. Furthermore, electric vehicle (EV) batteries, photovoltaic (PV) generation, and battery energy storage system (BESS) can be used as distributed energy resources. Therefore, this study proposes an integrated PMS that optimizes the power schedules of individual residents, EV batteries, and common facilities (PV power generation and BESS) in APBs considering the time-ofuse pricing policy. To develop the proposed system, a two-stage optimization was adopted using a genetic algorithm. For individual households, the first stage had three objectives: electricity cost, peak power, and user comfort. For the APB, the second stage had two objectives: total electricity cost and total peak power. To evaluate the performance of the proposed system, computational experiments were conducted in three cases: 1) unmanaged schedule, 2) conventional system, and 3) proposed system. For 50- and 100-unit APBs, the proposed PMS had lower total electricity costs (53119 JPY, 106150 JPY) and total peak power demands (184 kW, 366 kW) than the total electricity costs (54744 JPY, 109517 JPY) and total peak power demands (214 kW, 423 kW) of the conventional PMS. Based on a case study that used the proposed two-stage system with different weighting factors, the trade-off relationship among the five objectives of the proposed PMS was obtained. These findings suggest that the all-inclusive power scheduling of the APBs can be managed by dividing the comprehensive demand into individual household and common facility power demands, including cooperative systems. These results provide an important opportunity to advance the understanding of integrated PMS and cooperative systems for APBs. Further research is required to establish the dynamic relationships between households and APBs.