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Clean energy has become one of the more broadly acceptable options for the future transformation of existing energy systems. The energy transformation also requires comprehensive preparatory actions. Organizing a multi-chain clean energy value chain into a complex clean energy network system is likely to be critical to the successful utilization of clean energy in the future. This article proposes a novel concept for a clean energy value co-creation system covering the entire clean energy value chain with division on power generation, energy storage, and end utilization sections. This article mainly analyzes the self-organizing evolution mechanism and value co-creation of the clean energy value co-creation system (CEVCS), which is therefore critical to the further development of the renewable energy industry. First, this article analyzes the connotation and basic structure of CEVCS and introduces the self-organizing characteristics of CEVCS. Second, the self-organizing evolution mechanism of CEVCS is discussed, which is analyzed from four aspects: evolutionary power, evolutionary path, evolutionary form, and evolutionary process. Third, this paper analyzes the information cooperative evolution process of CEVCS, defines the value order parameter, and studies how the constituent elements of CEVCS realize value creation through a synergy mechanism based on the theory of synergy. Then the dissipative structure model and information resource collaborative model of CEVCS are presented. Finally, the conclusions are given in the end. The proposed CEVCS concept would support the effective operation of the clean energy value chain within municipalities by establishing virtual energy cooperatives aimed at meeting energy needs and supporting community development. [ABSTRACT FROM AUTHOR]

After the rapid development of China's wind power industry, the lack of core technology and the mismatch between the expansion and development speed have become increasingly prominent. In order to correctly understand the current situation and problems, the whole research process is divided into the following four steps. The first step takes the profit rate of main business from 2017 to 2019 as sample variable to study the smile pattern of the wind power industry value chain. The second step takes the Principal Component Analysis as the research method, and the evaluation index system is constructed, so as to further analyze the value-added driving factors. The third step uses the Data Envelopment Analysis (DEA) and Malmquist model as evaluation methods, and the static and dynamic efficiencies of each value chain link are evaluated, respectively. In step four, the selected companies are effectively clustered with the Cluster Analysis. The results show that the value chain shows a gradual deepening smile, the overall value-added efficiency is not ideal, and there are specific problems in each link. This paper aims to provide reference for enterprises to make targeted improvement on the basis of analyzing the current situation. It also provides reference for the comparison and promotion of other countries. [ABSTRACT FROM AUTHOR]

With the rapid development of the wind power value chain, the selection of appropriate node companies has become the focus of wind power alliance, especially in the value chain of energy storage. Through the optimization of the selection of energy storage node enterprises, the role of energy storage in the wind power value chain can be better utilized. At the same time, the optimal selection of energy storage nodes can accelerate the realization of value increment in the wind power value chain. In this study, we combine Interval type-2 fuzzy number and Grey Theory the Interval type-2 fuzzy number with Cumulative Prospect Theory, which is called IGCPT, and select the optimal energy storage nodes in the value chain based on it. First, considering the sustainable development of the entire value chain, 10 decision criteria from the four dimensions of BOCR: benefits, opportunities, costs, and risks are determined. Based on this, the IGCPT method is used to select the optimal scheme, and an optimization model is proposed to determine the significance of the criteria. Then, through the comparative analysis of the multi-criteria decision-making method and the sensitivity analysis of the obtained results, it is shown that the method can be effectively applied to the selection of energy storage nodes in the wind power value chain. Finally, suggestions and conclusions for the selection of wind power value chain node companies are given. [ABSTRACT FROM AUTHOR]