AI 中文总结
本文针对含多个竞争零售商的微电网，构建合作博弈框架，提出基于多目标优化的联盟形成算法，结合风险分担扩展，通过数值模拟验证其可用于分析多零售商需求侧管理系统的竞争与定价问题。
AI 中文摘要
本文为拥有多个竞争零售商的电力网络开发了需求侧管理框架，将零售商间的交互建模为合作博弈，得到一组耦合混合整数优化问题，其中零售价格、消费者电力需求和网络分区被联合优化。为求解该问题，我们提出了基于多目标优化原理的联盟形成算法，旨在识别平衡零售商利润与消费者福利的联盟结构。我们证明该算法在有限步内收敛，并能得到耦合优化问题的一组弱帕累托有效解。该框架进一步扩展为风险分担形式，其目标函数采用条件风险价值定义。对一个学术算例的数值模拟展示了该方法的行为，结果表明生成的均衡分区集包含多个竞争目标间的可接受权衡。研究结果为分析多零售商需求侧管理系统中的竞争、联盟形成及风险感知定价提供了一种易处理的方法。
英文摘要
This paper develops a demand-side management framework for electricity networks with multiple competing retailers. The interaction among retailers is formulated as a coalitional game, yielding a family of coupled mixed-integer optimisation problems in which retail prices, consumer power demands, and the network partition are jointly optimised. To solve this problem, we propose a coalition-formation algorithm based on multi-objective optimisation principles. The algorithm seeks to identify coalition structures that balance retailer profit and consumer welfare. We prove that the proposed algorithm converges in a finite number of steps and recovers a subset of weakly Pareto-efficient solutions of the coupled optimisation problems. The framework is further extended to a risk-sharing formulation, in which the objective is defined using conditional value-at-risk. Numerical simulations on an academic example demonstrate the method's behaviour and show that the resulting equilibrium partition set contains several admissible trade-offs between the competing objectives. The results provide a tractable approach for analysing competition, coalition formation, and risk-aware pricing in multi-retailer demand-side management systems.
