Operation Health Assessment of Power Market Based on Improved Matter-Element Extension Cloud Model

Jun Dong, Dongxue Wang, Dongran Liu, Palidan Ainiwaer and Linpeng Nie
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Jun Dong: Research Institute of Energy Markets, North China Electric Power University, Beijing 102206, China
Dongxue Wang: Research Institute of Energy Markets, North China Electric Power University, Beijing 102206, China
Dongran Liu: Research Institute of Energy Markets, North China Electric Power University, Beijing 102206, China
Palidan Ainiwaer: Research Institute of Energy Markets, North China Electric Power University, Beijing 102206, China
Linpeng Nie: Research Institute of Energy Markets, North China Electric Power University, Beijing 102206, China

Sustainability, 2019, vol. 11, issue 19, 1-25

Abstract: The complex power system and trading environment in China has led to higher requirements for the efficient and stable operation of the electricity market. With the continuous advancement of power system reforms, regular evaluation of the operation of the market can help us grasp its status and trends, which is of great significance for ensuring its sustainable development. In order to effectively evaluate the current operational status of the electricity market, the concept of operation health degree of power market (OHDPM) is proposed to measure whether the operation is safe, efficient, and sustainable. This paper establishes an improved model framework based on the matter-element extension theory for evaluation. In order to effectively avoid information distortion and loss in the evaluation process, this paper combines the cloud model, matter element extension theory, ideal point method (IPM), and cloud entropy optimization algorithm to deal with this problem. The matter-element extension cloud model (MEECM) can clearly represent the characteristics of the object to be evaluated. IPM is used to determine the weight of the index. For the improved matter-element extension model, the traditional rules of “3En” and “50% relevance” are taken into account, and the method of solving the entropy is optimized. Then, for the correlation degree between the object to be evaluated and the graded normal cloud, the weight vector solved by the IPM is used to weigh the cloud correlation degree, which can give a reliable evaluation result. The health evaluation index system of power market operation includes 16 sub-indicators in five categories: supply side, demand side, coordinated operation, market security, and sustainable development. In the empirical analysis, the OHDPM situation in Y Province was evaluated in May 2019. The results prove that the OHDPM level is medium, and the importance and health level of each index are given. The reliability of the power system, transaction price stability, Lerner index, residual proportion of producers, and user satisfaction have a greater impact on the health status. Finally, in order to verify the validity and stability of the model, different methods are used to evaluate the evaluation objects, and the advantages of OHDPM evaluation based on the model framework proposed in this paper are proven.

Keywords: operation health degree of power market (OHDPM); matter-element extension cloud model (MEECM); sustainable development; cloud model; cloud entropy; health level (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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