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

Rui Zhang, Zhe Chen, Yun Teng, Yunxu Hu
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Abstract

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.
电力零售商经济调度的双层规划方法
为了解决典型零售商应对分布式发电和需求侧波动带来的随机风险的经济调度问题,提出了一种引入随机变量的双层优化模型。在该模型中,上层子问题旨在模拟电力和备用辅助服务的市场出清过程,以市场出清价格和市场出清电量为决策变量;下层子问题旨在模拟市场出清给出的分时定价下的购买成本最小化。通过机会约束规划将模型转化为确定性模型,通过上下两层的迭代得到平衡解,利用CPLEX求解器分别求解上、下两层子问题。最后,通过对双层优化模型的数值模拟分析,阐明了不同置信水平对零售商决策的影响。验证了该模型能够有效地反映零售商决策行为对市场出清过程的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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