カルマンフィルタ予測による 変動電力補償用SMESの容量最適化の検討

抄録

In photovoltaic (PV) and wind turbine (WT) power generation, which are typical examples of clean power, the amount of power generated changes rapidly and constantly according to the stochastic weather conditions. In order to ensure a high-quality power supply, including constant voltage and current, it is necessary to compensate for the power fluctuations. A system combining fuel cells (FCs), which can generate power for long periods of time, and a superconducting magnetic energy storage (SMES) system, which can produce large amounts of power quickly, can potentially function to compensate the power fluctuations all the time. In this paper, since WT power is resolved into trend and fluctuating components, the former is provided by FCs, and the latter is provided by the SMES system. The trend components are predicted using a Kalman filter, which describes the state-space model for WT power generation. Since the SMES system cost is very high, it is important to optimize the compensation capacity of SMES in the combined system. We found that the trend prediction method, a modification of the Kalman filter, allows us to optimize the SMES capacity.