松弛MPEC和MIQP的启发–校正两阶段动态无功优化算法

Two-stage Heuristic-correction for Dynamic Reactive Power Optimization Based on Relaxation-MPEC and MIQP

为快速求解计及离散调节设备动作次数约束和电网安全约束的多时段动态无功优化问题,建立以有功网损最小为目标函数的混合整数非线性规划模型,并提出一种启发搜索加变量校正的两阶段求解方法:启发搜索首先将离散变量松弛为连续变量,形成一个带平衡约束的的优化模型,进而得到各个时段的连续优化结果,然后建立以方差最小化为目标并严格满足原模型中离散调节设备动作次数约束的整数二次规划模型,得到最优动作次数和离散归整结果;变量校正是固定启发搜索得到的离散变量优化结果,重新校正连续变量的优化量。通过IEEE 14测试系统详细讨论了无功调节设备的步长和动作次数对优化结果的影响;此外,IEEE 30、57、118节点测试系统的优化结果表明,所提方法能够快速得到优化结果,实现并行求解,且其精度可满足实际工程需要。

To achieve a fast approach to the dynamic reactive power optimization model, a mixed integer nonlinear programming model was set up, with consideration of the discrete reactive power equipment operation limit and power grid security constraints, to minimize the transmission losses. Furthermore, a method called heuristic search and variable correction was proposed that for the first stage, the discrete variables are relaxed into continuous ones, which leads to an optimization model with equilibrium constraints. According to the optimal value of relaxed model, a mixed integer quadratic programming model is formulated to minimize the objective of approximation variance, satisfied the discrete switching operation constraints in primary model. For the second stage, the continuous variables are redressed with respect to the determined discrete variables. The impact of adjustment step and operation limit on the optimal solution was fully studied in IEEE 14-bus test system. Besides, the resuk of IEEE 30, 57, 118 test systems show that an optimal solution can fast be obtained by proposed method, and the precision satisfies the actual engineering, which can also employ the parallel technology.