基于目标权重导向多目标粒子群的节能减排电力系统优化调度

Optimizing Schedule for Electric Power System of Energy-saving and Emission-reducing Based Upon Objective-weight Oriented Multi-objective Particle Swarm Optimization

提出一种目标权重导向的多目标粒子群优化的新算法,用于节能减排的电力系统优化调度。优化过程中得到不同目标权重导向的可行解,种群中各粒子全局极值的选取都尽量接近于自身目前对于各目标的侧重,以便保持解的多样性。对决策者而言,新的进化策略既考虑了对于节能和减排两个不同目标的侧重,又并行地给出不同目标权重的解决方案。采用标准IEEE-30测试系统分别从考虑网损和不考虑网损两方面对新算法进行验证,与其他文献对比的结果表明,在求解速度、解的多样性和精度方面均达到了令人满意的效果,并为节能减排的电力系统优化调度提供了新的思路。

An objective-weight oriented multi-objective particle swarm optimization method applied to optimizing schedule for electric power system of energy-saving and emission-reducing was developed. In the process of optimization, feasible solutions with different objective weights can be gained. In order to ensure the diversity of population, global best guides of all current particles were chosen as near to their preferences of certain objectives as possible. For decision makers, new evolutionary strategies take into account not only their emphasis on operation cost or emission, but also the concurrent operation of more than one Pareto solutions with different objective weights. The proposed approach has been applied to the standard IEEE 30-bus test system. Results of considering power loss and lossless were respectively compared with other classical methods, where superiority of rapidly converging, satisfactory diversity characteristics and high precision were demonstrated. In addition, the method provides new idea to optimizing schedule for electric power system of energy-saving and emission-reducing.