Short-term cascaded hydroelectric system scheduling based on chaotic particle swarm optimization using improved logistic map

In order to solve the model of short-term cascaded hydroelectric system scheduling, a novel chaotic particle swarm optimization (CPSO) algorithm using improved logistic map is introduced, which uses the water discharge as the decision variables combined with the death penalty function. According to the principle of maximum power generation, the proposed approach makes use of the ergodicity, symmetry and stochastic property of improved logistic chaotic map for enhancing the performance of particle swarm optimization (PSO) algorithm. The new hybrid method has been examined and tested on two test functions and a practical cascaded hydroelectric system. The experimental results show that the effectiveness and robustness of the proposed CPSO algorithm in comparison with other traditional algorithms.

► Chaotic PSO algorithm based on improved logistic map is proposed.
► It is used to solve the short-term cascaded hydroelectric system scheduling problem.
► The discharge flow process is used as the decision variable.
► Constraints are handled by piecewise linear interpolation and death penalty function.
► Examples show the new method obtains more effective performance than existed methods.