考虑风电不确定性的区间经济调度模型及空间分支定界法

Interval Economic Dispatch Model with Uncertain Wind Power Injection and Spatial Branch and Bound Method

大规模风电接入电网后,其间歇性和随机性使网络注入功率呈现一定的波动性,给传统确定性的经济调度带来了极大的挑战。以区间数形式对不确定量进行刻画和建模后,采用经济调度得到的优化解也呈现为区间形式。为精确求解区间上下边界(乐观解和悲观解),将区间优化模型转化为两个确定性的数学规划问题:乐观优化模型为一个简单的线性规划问题,而悲观优化模型为一个NP难问题,根据对偶定理,进一步将该模型转化为一个双线性规划模型,基于线性松弛技术和空间分支定界方法,可以找到该模型的全局最优解。含不确定注入的区间经济调度为调度运行人员提供了直观的上下界信息,为安全评估提供支撑。最后,采用15机300节点系统,分别以日前计划和日内滚动计划为例,并与内点法和穷举法进行对比,结果验证了该方法的有效性。

Power injection becomes stochastic due to large-scale wind power integration into power grid, which greatly challenges the traditional power grid. If the uncertainty is modelled using the interval number, the solution of economic dispatch model can also be represented as an interval number. To achieve the precise upper and lower bound, two deterministic programming models were deduced： the optimistic solution can be obtained by an optimistic model using linear programming, whereas the pessimistic solution achieved by a pessimistic model is an NP-hard problem, which can be transformed into a bilinear programming by duality theory. Then a linear relaxation technology, spatial branch and bound method were used to obtain the global pessimistic solution. Therefore, the interval bound information can provide the operator with institutive bound information for the future security assessment. Finally, a test system with 15 generators and 300 nodes was studied at different time scales. The result, compared with interior point method and enumeration, shows the effectiveness of proposed method.