基于改进信息间隙决策理论的考虑决策者风险态度的社区虚拟电厂经济-能源-环境调度策略选择

Selection of Economics-Energy-Environment Scheduling Strategy for a Community Virtual Power Plant Considering Decision-makersRisk Attitudes Based on Improved Information Gap Decision Theory

针对决策者风险态度(decision-makers’risk attitudes, DMRA)和不确定性对社区综合能源系统调度策略的影响,提出了社区虚拟电厂(community virtual power plant, CVPP)的多目标调度模型。首先,建立了考虑DMRA的CVPP模型和经济-能源-环境多目标满意度模型。其次,考虑可再生能源、负荷和DMRA的不确定性,对信息间隙决策理论(information gap decision theory, IGDT)模型进行了改进。第三,在考虑DMRA的基础上,拓展自信双层语言术语下的改进VIKOR方法。最后,以某居民区为例,对该模型的有效性进行了验证。结果表明:1)基于DMRA的CVPP提供了切合实际的调度策略。2)实施需求响应后,居民成本和净碳排放分别降低了9%和91%,提高了能源供应商的利润和可再生能源的利用率,所构建的IGDT模型也改进了多个目标。3)改进后的IGDT模型的不确定性和偏差因素允许采用多种调度策略。同时,改进的VIKOR方法为决策者选择策略提供了一种新的方法。该模型为调度策略的选择提供了指导,同时也为鼓励可再生能源的使用提供了途径。

To address the impact of decision makersrisk attitudes(DMRAs)and uncertainties on dispatch strategies in community-integrated energy systems,a multi-objective dispatch model of a community virtual power plant(CVPP)is proposed.First,a novel CVPP model that considers DMRA and a multi-objective economics-energy-environment satisfaction model was developed.The information gap decision theory(IGDT)model is then improved considering uncertainties of renewable energy,loads,and DMRA.Third,considering DMRA,an improved VIKOR method was proposed under self-confident double-hierarchy linguistic preference relations.Finally,the effectiveness of the proposed model was validated regarding a multi-scenario example of a residential area.The results indicate the following:1)The novel CVPP provides realistic scheduling strategies based on the DMRA.2)After implementing demand response,the resident cost and net carbon emissions are reduced by 9%and 91%,respectively.In addition,the energy supplier profit and renewable energy utilization rate are increased.The constructed IGDT model also improves multiple objectives.3)The improved uncertainty and deviation factors of the IGDT model allow diverse scheduling strategies.Simultaneously,the improved VIKOR method provides a new way for decision makers to select strategies.This model serves as a guide for selecting scheduling strategies and encourages the use of renewable energy sources.