With increasing development of smart grid and restructuring of the power industry, the problem of operating schedule for a time-of-use (TOU) rate industrial customer may become a more important issue due to the inclusion of the variations in the TOU rate structures. This paper develops a new algorithm, named intelligent particle swarm optimization (INPSO), to solve the operating schedule of a renewable energy based TOU rate industrial user with battery energy storage system (BESS). Adding another particle best (Pbestap) item with a diversity based judgment mechanism, proposed INPSO algorithm can give a good direction to enhance its search capacity that leads to a higher probability of obtaining the global optimal solution. A TOU rate industrial customer of Taiwan Power Company (TPC) is used as an example to validate the feasibility of the INPSO algorithm for the application considered. Numerical experiments are included to understand how variations in the rate structures on the optimal operation of the TOU rate customer system. The computer program developed in this paper can also be a power tool for TOU rate industrial users to evaluate the economic benefits of the renewable energy sources (RES) and BESS.

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