Operation Optimization Method for Factory Power Generation Plant Considering Probability Distribution

Shoichi Kitamura, Kazuyuki Mori, Yoshio Izui, Toshiyuki Miyamoto, and Shigemasa Takai


Power generation plant, factory energy management system, uncertainty, probability distribution, optimization


Factory power generation plants supply electric power and heat to the manufacturing lines. Because the demand changes are uncertain, the power plant must adjust its output to match the demands and to avoid the violation of constraints such as the inverse load flow. Conventionally, these violations have been avoided by purchasing surplus electric power. However, the surplus power raises the energy cost. There exists an optimization method, which considers the uncertainty in the demands for co-generation systems, and implements a triangle function to approximate its probability distribution. However, this method does not consider the tail of the probability distribution. In this paper, an operation optimization method considering an uncertainty in the demands for factory power plants is proposed. The proposed method aims to avoid violations of constraints and to reduce the energy cost. Through simulation experiments, the validity of the proposed method is confirmed.

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