太陽光発電量予測に基づく複数BEMSにおける分散型電力取引システム

抄録

This paper proposes an optimal trading algorithm for a decentralized energy trading system among multiple building energy management systems (BEMS). Each building generates solar power and has a battery. As a decentralized energy trading algorithm, we first solve the proposed optimization problem to determine the optimal trading volume that minimizes the total purchase price of electricity while satisfying the battery capacity constraint under the consideration of the solar power generation error and the time-varying electricity price. To take into account the foregoing, model predictive control and a scenario-based robust optimization are applied. After the information on the desired amount of electricity transactions is communicated between buildings, the electricity sales price is updated. These steps are iterated until the termination condition is satisfied, and the final trading volume is determined. The convergence of the proposed algorithm is analyzed and the sufficient conditions for the convergence of the price update parameters are shown. Finally, the total price cost and computational cost are compared with the centralized one, and the effectiveness and the superiority of the decentralized control system are shown by several numerical simulations.