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中国管理科学 ›› 2019, Vol. 27 ›› Issue (2): 179-186.doi: 10.16381/j.cnki.issn1003-207x.2019.02.018

• 论文 • 上一篇    下一篇

基于多目标加权灰靶决策模型的节能服务公司选择研究

张文杰1, 袁红平2   

  1. 1. 西南交通大学经济管理学院, 四川 成都 610031;
    2. 广州大学工商管理学院, 广东 广州 510006
  • 收稿日期:2017-01-11 修回日期:2017-06-30 出版日期:2019-02-20 发布日期:2019-04-24
  • 通讯作者: 袁红平(1983-),男(汉族),湖北荆州人,广州大学工商管理学院教授,博导,研究方向:可持续建筑环境、建筑废弃物管理、工程项目管理,E-mail:hpyuan2005@gmail.com. E-mail:hpyuan2005@gmail.com
  • 基金资助:

    国家自然科学基金资助项目(71573216);四川省科技计划项目(2017ZR0150)

A Weighted Multi-objective Gray Target Decision Model for Selecting an Optimum ESCO

ZHANG Wen-jie1, YUAN Hong-ping2   

  1. 1. School of Economics and Management, Southwest Jiaotong University, Chengdu 610031, China;
    2. School of Management, Guangzhou University, Guangzhou 510006, China
  • Received:2017-01-11 Revised:2017-06-30 Online:2019-02-20 Published:2019-04-24

摘要: 用能方对节能服务公司(Energy Service Company,ESCO)的选择关系到合同能源管理(Energy Performance Contracting,EPC)能否顺利实施。从用能方的角度,采用灰色系统理论中的多目标加权灰靶决策模型,对存在多决策目标的ESCO选择问题进行研究。通过层次分析法确定ESCO的11个决策目标的决策权数,根据综合效果测度值的比较,最终实现最优对策的选择。本文为用能方的ESCO选择问题提供了一种新的思路。

关键词: 合同能源管理, 节能服务公司, 灰色系统理论, 多目标加权灰靶决策模型

Abstract: Energy User (EU) can benefit from implementing Energy Performance Contract (EPC) projects. However, it is unclear how an EU can select an Energy Service Company (ESCO) efficiently from multiple candidates so as to maximize its interests. This arouses two particular questions:one is which method can be used by the EU to select asuitable ESCO, and the other is which indicators can be adopted to achieve effective outcomes toward ESCO selection. In practice the main concern of the EU is how to determine an optimal ESCOdepending on insufficient ESCO information. This paper aims to investigate the optimal ESCO selection problem from the perspective of the EU by using the weighted multi-objective gray target decision model. The weighted multi-objective gray target decision model is first introduced, followed by determining main decision-making objectives of ESCO selection based on a two-round expert consultation. Then according to different types of the decision-making objectives (i.e. benefit-based, cost-based, moderate),the objective effect sample matrix are formulated and the objective effects' threshold values are set. Finally, by calculating the uniform effect measurement matrix, the dimension of the three ESCOs' objective effect sample matrix is dispelled. The ultimate optimum of ESCO is identified by judging the three ESCOs' synthetic effect measurement values. The study reveals that in the process of determining an optimum ESCO, special attention should be paid on aspects including ‘the qualification of ESCO’, ‘the reputation of ESCO’, ‘the quality of energy-saving equipment’, ‘energy-saving retrofit period’, ‘energy-saving benefit sharing period’, ‘energy-saving design’, ‘participants’ energy-saving benefit sharing proportion, ‘the damage extent to the original building components’, ‘energy-saving during the contract period’, ‘feasibility to spot energy-saving volume’ and ‘pre-payment’. It is also proved that applying the weighted multi-objective gray target decision model to optimum ESCO selection could largely help the EU to address the problem effectively even the EU faces a dilemma of scarce data and information about the ESCO.

Key words: energy performance contract, energy service company, gray system theory, weighted multi-objective gray target decision model

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