Optimization of electric power leveling systems by using taper-off-reflectance particle swarm optimization

Recently, it is desired to develop energy control technologies for environmental issues such as global warming and exhaustion of fossil fuel. Power fluctuations in large power consumers may cause the instability of electric power systems and increase the cost of the electric power facility and electricity charges. Developing the electric power-leveling systems (EPLS) to compensate the power fluctuations is necessary for future electric power systems. Now, EPLS with an SMES have been proposed as one of the countermeasures for the electric power quality improvement. The SMES is superior to other energy storage devices in response and storage efficiency. The authors proposed the EPLS based on fussy control with the SMES. For this practical implementation, optimizing control gain and SMES capacity is an important issue. This paper proposes a new optimization method of the EPLS. The proposed algorithm is novel particle swarm optimization based on taper-off reflectance (TRPSO). The proposed TRPSO optimizes the design variables of the EPLS efficiently and effectively.