一种售电公司经济调度双层优化方法

为解决大型售电公司应对新能源接入和需求侧波动带来的随机性风险问题,文章提出了一种基于随机规划的双层优化模型:上层子问题以出清电价和出清电量为决策变量,模拟了市场电能与备用辅助服务的联合出清过程;下层子问题以售电公司的最优购电成本为目标,模拟了售电公司的经济调度行为。模型的求解过程中,通过机会约束规划将模型转换为确定性模型,再由CPLEX求解器分别求解上下层子模型,并通过上下层的迭代求得均衡解。最后,建立了不计及售电公司决策影响的两阶段模型作为对比模型,通过算例分析,验证了该模型可有效反映售电公司决策行为对出清过程的影响,并阐明了不同置信水平对售电公司决策的影响。

A Bi-level Programming Approach of Economic Dispatch of Electricity Retailers

In order to solve the economic dispatch problem of a typical retailer coping with the stochastic risk brought by the distributed generation and demand-side fluctuation, a bi-level optimization model with the introduction of random variables is proposed. In this model, the upper-level sub-problem aims to simulate the market clearing process of electricity and reserve auxiliary services, where market clearing price and market clearing electricity are the decision variables, while the lower-level sub-problem is formulated to minimize the costs of purchasing under time-of-use pricing given by the simulation of market clearing. The model is converted into a deterministic model by chance-constrained programming, and the equilibrium solution is obtained by iterations between the upper and lower layers, where the CPLEX solvers are employed to address the upper and lower level sub-problems, respectively. Finally, the impact of different confidence level on the decision carried out by retailers is clarified through the analysis of the numerical simulation of the bi-level optimization model. It is verified that the model can effectively reflect the impact of the decision-making behavior of retailers on the market clearing process.