基于最大评价差异的储能多场景区间模糊层次选型方法OA北大核心CSTPCD
A fuzzy hierarchical selection method for an energy storage multi scenario interval based on maximum evaluation difference
为满足新能源场站升级背景下多类型储能的选型需求,提出一种基于最大评价差异的区间模糊层次选型方法.从经济、环境、安全、技术、动态维度建立储能评价指标集,并基于梯形区间二型模糊集量化表征指标数据.分别基于专家多轮评价法和指标相对重要性法实现主、客观赋权,并采用最大评价差异法融合赋权.建立了基于多准则妥协解排序法的区间模糊层次选型模型,实现多场景下储能方案优选.IEEE39算例结果表明,所提方法能有效提升方案区分度,可根据波动抑制与削峰填谷场景特性给出针对性方案,为新能源场站配储提供决策支撑.
To accommodate the selection needs for multiple types of energy storage in the context of upgrading new energy stations,a fuzzy hierarchical selection method based on the maximum evaluation difference is proposed.Energy storage evaluation indicators are established from economic,environmental,safety,technical,and dynamic dimensions,and indicator data is quantitatively represented using trapezoidal interval type-2 fuzzy sets.Subjective and objective weights for these indicators are assigned through both multiple rounds of expert evaluation and criteria importance,with integration achieved using the maximum evaluation difference method.A fuzzy hierarchical selection model based on the ViseKriterijumska Optimizacija I Kompromisno Resenje method is developed to facilitate the optimal selection of energy storage solutions across various scenarios.Case results on the IEEE 39-bus system demonstrate that the proposed method effectively enhances the differentiation of solution.Targeted solutions are provided based on the characteristics of scenarios involving fluctuation suppression and peak shaving and valley filling,offering decision support for energy storage integration at new energy stations.
齐彩娟;李牧远;吴奕辰;王铱;宋蕙慧
国网宁夏电力有限公司经济技术研究院,宁夏 银川 750000哈尔滨工业大学(威海)新能源学院,山东 威海 264200中国电力工程顾问集团东北电力设计院有限公司,吉林 长春 130000
储能选型最大评价差异区间二型模糊集主客观评价层次分析法
energy storage selectionmaximal evaluation differenceinterval type-2 fuzzy setsubjective and objective evaluationanalytic hierarchy process
《电力系统保护与控制》 2024 (022)
104-115 / 12
This work is supported by the Natural Science Foundation of the Ningxia Hui Autonomous Region(No.2023AAC03823). 宁夏回族自治区自然科学基金项目资助(2023AAC03823)
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