Optimal operational planning of steam power systems using an IPSOSA algorithm

The operation optimization problem of steam power systems for multiperiod operation with varying demands is formulated. The objective function of the mode! is to minimize the operational cost of steam power systems for all periods, by taking into account the cost of fuel, and feed-water, as well as the expenses of maintenance and startup/shutdown. In order to obtain the optimal solution of the foregoing model, an improved particle swarm optimization method based on the ideal of simulated annealing algorithm (IPSOSA) is proposed, in which IPSOSA are applied to make particles have tendency to global optimum. Finally, cases are considered for illustrating the advantage of proposed optimization approach, with quantitive results presented. Results show that the IPSOSA algorithms are much more efficient and generate higher quality solutions than some existing particle swarm optimization algorithms.