This paper compares particle swarm optimizations (PSOs) for optimal operational planning of energy plants. In order to generate optimal operational planning for energy plants, startup/shutdown status and/or input/output values of the facilities for each control interval should be determined. The facilities may have nonlinear input-output characteristics. Therefore, the problem can be formulated as a mixed-integer nonlinear optimization problem (MINLP). PSO is one of the meta-heuristic techniques. Original PSO, evolutionary PSO, and adaptive PSO are compared using typical energy plant operational planning problems.
['Shinji Kitagawa', 'Yoshikazu Fukuyama']
Comparison of particle swarm optimizations for optimal operational planning of energy plants