基于综合赋权与云熵优化的园区综合能源系统评价

Evaluation of park integrated energy system based on comprehensive weighting and cloud entropy optimization

综合能源系统(integrated energy system,IES)作为能源转型中的重要环节已得到越来越多国家的广泛关注。构建一套匹配中国国情的综合能源系统评价体系和评价方法不仅能够为综合能源系统规划后评价打下基础,以此对规划方案进行优劣排序;还能够提高综合能源系统项目的管理水平,在制定统一、完整的综合能源系统综合评价标准时提供参考。为此,首先结合园区IES基本特征以及运行特性,构建包含经济性、可靠性、环保性以及智能友好性4个方面的综合评价指标体系;然后为解决IES在运行中的不确定性问题,对基于传统云物元模型的综合评价体系提出云熵优化,即考虑不同评价者对模糊性的可接受程度;为解决单一赋权方法可能导致的评价结果过于主观或过于客观的问题,选择基于最小鉴别信息原理将决策实验室法与熵权法相结合的综合赋权法,并采用变权法进一步完善综合评价指标;最后通过算例分析,验证所提综合评价体系的科学正确性。

As an important part of energy transformation,integrated energy system(IES)has attracted widespread attention from more and more countries.Establishing an evaluation system and method for IES that matches China's national conditions can not only lay a foundation for post-evaluation of IES planning and rank the planning schemes accordingly,but also improve the management level of IES projects and provide a reference for formulating a unified and complete IES evaluation criterion.To this end,combining the basic characteristics and operational features of the park IES,a comprehensive evaluation index system including four aspects of economy,reliability,environmental protection,and intelligence and friendliness is constructed.Then,to address the uncertainty of IES operation,the comprehensive evaluation system based on the traditional cloud matter-element model proposes cloud entropy optimization,considering the varying degrees of acceptability of fuzziness among different evaluators.To solve the problem that the evaluation results caused by a single weighting method may be too subjective or too objective,a comprehensive weighting method combining the decision making trial and evaluation laboratory method with the entropy weight method based on the principle of minimum discrimination information is selected,and the variable weight method is used to further improve the value of comprehensive evaluation index.Finally,the scientific correctness of the proposed comprehensive evaluation system is verified through case analysis.