饱和度自适应微分进化算法在电力经济调度中的应用

The Application of Saturation and Adaptive Differential Evolution Algorithm in Economic Dispatching of Power Grid

建立了电力系统经济调度模型,该模型以发电成本最小为目标,考虑了火电机组阀点效应和系统运行约束,并提出了求解该模型的饱和度自适应微分进化(saturation and adaptive differential evolution,SADE)算法。为避免算法搜索的盲目性,使算法既能集中于局部最优解又能兼顾全局最优解,引入了控制参数自适应调整策略和饱和度概念,该算法可避免"早熟"现象,收敛速度快。3机组、13机组和40机组算例结果验证了SADE算法的有效性。

An economic dispatching model of power grid, in which the minimized generation cost is taken as objective and valve point effect of thermal units and operation constraints of power grid are taken into account, is built, and a saturation and adaptive differential evolution （SADE） algorithm is proposed to solve the built model. To avoid the blindness in the search by the proposed SADE algorithm and to ensure that this algorithm can give priority to local optimal solution while the global optimal solution can be simultaneously considered, the adaptive adjustment strategy and the concept of saturation are led into the proposed SADE algorithm to prevent premature phenomena and speed up the convergence. Calculation results of 3-machine system, 13-machine system and 40-machine system verify the effectiveness of the proposed SADE algorithm.