考虑用户有限理性的需求侧电能共享价格套餐设计

Pricing Package Design for Energy Sharing on the Power Demand Side Considering Bounded Rationality of Users

分布式灵活资源的大量接入为配电网运行带来了潜在的调节资源,与此同时,电能共享概念的提出为促进灵活资源的优化配置和市场化应用提供了新的解决思路,然而如何对海量分散灵活资源进行稳定聚合以参与本地市场亟待解决。提出了一种考虑用户有限理性的需求侧电能共享价格套餐设计方法。首先建立了产消者用户与电力零售商之间的电能共享零售框架,提出了共享套餐的零售模式。然后,考虑产消者用户的有限理性特征和风险偏好,基于累计前景理论(cumulative prospect theory,CPT)建立了用户累计前景效用模型,进而构建了产消者用户的电能共享决策模型。最后,基于主从博弈理论建立了零售套餐交易过程中零售商-用户之间的博弈模型,并通过灰狼优化(grey wolf optimization,GWO)算法进行寻优求解。算例结果表明,所提的价格套餐模式能够针对差异化的产消者用户提供个性化的共享价格套餐并实现对灵活资源的聚合引导,在满足用户累计前景效用的情况下实现零售商日收益的最大化,同时通过电能共享有效缓解了配电网峰谷时段的运行压力。

The widespread integration of flexible distributed resources into distribution grids has introduced a wealth of potential regulatory assets.Simultaneously,the concept of energy sharing has emerged as a novel solution for optimizing the allocation and market utilization of these flexible resources.However,the stable aggregation of massive,dispersed,and flexible resources for participation in local markets remains a pressing challenge.In this study,we propose a demand-side energy-sharing pricing package design method that considers user bounded rationality.First,we establish an energy-sharing framework between prosumers(producer-consumers)and electricity retailers,and then introduce a retail model for pricing packages.Next,considering the bounded rationality characteristics and risk preferences of prosumer users,we develop a cumulative prospect utility model based on cumulative prospect theory(CPT).This model forms the foundation for constructing a prosumer energy-sharing decision-making model.Finally,based on Stackelberg game theory,we create a game model between retailers and users and employ the grey wolf optimization(GWO)algorithm to optimize and solve it.Our case study results demonstrate that the proposed pricing package model can offer personalized shared pricing packages to diverse prosumer users and effectively aggregate flexible resources.While maximizing the retailer’s daily revenue,our model effectively alleviats operational pressures during peak and off-peak periods in distribution grids through energy sharing.