基于变置信度机会约束规划的风电并网优化调度

Optimal Dispatching Under Grid-connection of Wind Farm Based on Variable Confidence Chance-constrain Model

风电的波动性和不稳定性给电网的调度增加了难度,为了兼顾系统运行的经济性和可靠性,提出一种变置信度机会约束模型,并将该模型引入机组旋转备用约束中。首先,建立考虑到系统经济性和可靠性的多目标函数,并在可靠性目标函数中引入风电预测误差置信度β,其值等于旋转备用机会约束置信度。其次,通过模糊隶属度方法将两目标函数变为无量纲的单目标函数,再通过基于线性递减惯性权值(LDIW)策略的改进粒子群优化算法求解各时刻最优置信度β,进而确定各机组最优出力与最优旋转备用容量。最后,利用IEEE-RTS96系统进行验证,其结果证明了文中所提方法均优于传统机会约束方法与现阶段常用的风电并网优化调度方法,既保证了经济性又确保了系统的可靠性,利用LDIW策略的改进粒子群算法也加快了算法的运算速度,保证了模型及算法的有效性。

Volatility and instability of wind power increases the difficult of power grid dispatching, for the economy and reliability, the paper raise variable confidence chance-constrained model to the spinning reserve constraint. First, the paper establishes economy and reliability objective functions, introducing confidenceβ to reliability objective function, that confidence equal to spinning reserve chance-constrained. Second, using the membership function combined two objective functions into the one. Third, using the improved PSO based on LDIW solve each time the optimal degree of confidenceβ and optimal output and the optimal spinning reserve capacity of each unit. Finally, IEEE-RTS96 system is used in the simulation. The results prove that the proposed method is both superior to conventional dispatching result with chance-constrained method and the conventional method of wind power optimization scheduling, both to ensure the economy and the reliability of the system, the improved particle swarm LDIW method has accelerated the speed of operation of the algorithm to ensure the validity of the model and algorithm.