基于自适应混合差分进化算法的水火电力系统短期发电计划优化

Short-Term Scheduling Optimization for Hydro-Thermal Power Systems Based on Adaptive Hybrid Differential Evolution Algorithm

针对水火电力系统发电计划优化问题,引入差分进化(differential evolution,DE)算法,提出了一种自适应混合差分进化算法(adaptive hybrid differential evolution,AHDE)。该算法在计算过程中自适应调整交叉算子,保持了种群的多样性,提高了算法的全局搜索能力,克服了DE在寻优过程中容易早熟收敛的缺点。同时针对AHDE难以处理实际工程中复杂约束条件问题,提出了一种适合AHDE的约束处理方法。将AHDE应用于求解某水火电力系统的发电计划优化问题,与其他求解方法的对比表明,AHDE求解精度高、计算速度快。

Differential evolution （DE） algorithm is applied to solve short-term scheduling optimization of hydro-thermal power systems and an adaptive hybrid differential evolution （AHDE） is proposed. The proposed algorithm can adjust cross operator adaptively during the calculation so the diversity of population can be kept and the global searching ability of the proposed algorithm is improved; meanwhile,due to its strong searching ability, simulated annealing（SA） algorithm is adopted to remedy the defect of premature convergence of DE algorithm. In view of the problem that it is difficult for AHDE to deal with complex constraints in actual engineering, an approach to cope with constraints that is suitable to AHDE algorithm is put forward. Applying AHDE algorithm for solve the generation scheduling optimization of a certain hydro-thermal power system, the results show that the proposed AHDE algorithm can provide accurate solution with fast calculation speed.