To address the increasing impact of extreme temperatures (ETs) on the power system and electricity supply, demand response (DR) programs are widely used to reduce peak demands at ETs. The customized pricing mechanisms are required for an effective DR to target the potential consumers accurately. This paper proposes a frequency control ancillary service and critical peak rebate (FCAS-CPR) strategy based on cumulative prospect theory (CPT) for a virtual power plant (VPP) in coupled FCAS and DR markets. In order to develop a customized pricing model in the proposed strategy, the load clustering technique is applied. This aims to classify the loads based on the typical characteristics of consumers’ reactions to ETs. The consumers’ load reactions to ETs are described by the peak temperature sensitivity and the lag length. Then, the subjective decisions of irrational consumers are reflected based on the CPT. Last, the interaction between VPP consumers and the retailer is modeled as a Stackelberg game and solved by the Salp Swarm Algorithm (SSA). The simulation results verify the effectiveness of the proposed FCAS-CPR pricing mechanism, which can efficiently reduce the peak loads to mitigate impacts of ETs on power systems, while achieving a win-win outcome in maximizing the utilities of both the retailer and VPP consumers.

中文翻译：

---

为虚拟电厂定制临界峰值回扣定价机制

为了解决极端温度 (ET) 对电力系统和电力供应的日益增加的影响，需求响应 (DR) 程序被广泛用于减少 ET 的峰值需求。有效的 DR 需要定制的定价机制来准确地针对潜在消费者。本文针对耦合 FCAS 和 DR 市场中的虚拟电厂 (VPP)，提出了一种基于累积前景理论 (CPT) 的频率控制辅助服务和关键峰值回扣 (FCAS-CPR) 策略。为了在所提出的策略中开发定制的定价模型，应用了负载聚类技术。这旨在根据消费者对 ET 反应的典型特征对负载进行分类。用电设备对 ET 的负载反应由峰值温度敏感性和滞后长度来描述。然后，非理性消费者的主观决策基于 CPT 得到反映。最后，VPP 消费者和零售商之间的交互被建模为 Stackelberg 游戏，并通过 Salp Swarm 算法 (SSA) 解决。仿真结果验证了所提出的 FCAS-CPR 定价机制的有效性，该机制可以有效地降低峰值负荷以减轻 ET 对电力系统的影响，同时在最大化零售商和 VPP 消费者的效用方面实现双赢。