Evaluating the Comprehensive Performance of Demand Response for Commercial Customers by Applying Combination Weighting Techniques and Fuzzy VIKOR Approach

Dong, Jun; Huo, Huijuan; Liu, Dongran; Li, Rong

doi:10.3390/su9081332

Cited by 19 publications

(11 citation statements)

References 59 publications

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“…OHDPM evaluation is taken as an MCDM problem, and FCEM is a mature and widely used method in the evaluation process at present. Therefore, FCEM [36,64] is selected to evaluate the evaluation object, and the results are taken as a reference to prove the rationality of the method proposed in this paper. In addition, in order to verify the effectiveness and advancement of the proposed cloud entropy optimization algorithm, MEECM based on the "3En" rule, the "50% relevance" rule, and the cloud entropy optimization algorithm rule are used to evaluate the status of OHDPM on the basis of the weight determined by the IPM.…”

Section: Comparison Of the Results Of Different Evaluation Methodsmentioning

confidence: 99%

“…To some extent, this violates the original intention of using fuzzy methods [33,34]. When a single term cannot accurately express the evaluation information of an object, researchers propose uncertain linguistic variables, but a rough description of the uncertainty of qualitative information is inevitable, which will also lead to information distortion [35,36]. However, the cloud model is a method of computing language without the shortcomings of the above methods.…”

Section: Introductionmentioning

confidence: 99%

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

Dong¹,

Wang²,

Liu³

et al. 2019

Sustainability

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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.

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Section: Comparison Of the Results Of Different Evaluation Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Dong¹,

Wang²,

Liu³

et al. 2019

Sustainability

View full text Add to dashboard Cite

show abstract

“…Likewise, the rest of the rough interval numbers can be obtained utilizing the above computing principles. Thus, the group rough direct influence matrices, Z p = RN( a Tables 9 and 10), can be derived using Equations (21) to (23). The network relationship map can be derived accordingly.…”

Section: The Derivation Of the Causal Network Via The Bayesian Rough mentioning

confidence: 99%

“…The fuzzy and grey theories are representative examples. The incorporation of these two theories into the MCDM model has been used to solve a great number of issues, such as project selection [22], performance evaluation [23], evaluation of renewable energy resources [24], and selection of sustainable recycling partners [25]. Rough interval numbers, which recently have received much more attention, is another effective approach that can be utilized to deal with imprecise numeric values in decision data and subjectively collective judgments without defining membership function.…”

Section: Introductionmentioning

confidence: 99%

Systemic Functions Evaluation based Technological Innovation System for the Sustainability of IoT in the Manufacturing Industry

2019

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Technological innovations are regarded as the tools that can stimulate economic growth and the sustainable development of technology. In recent years, as technologies based on the internet of things (IoT) have rapidly developed, a number of applications based on IoT innovations have emerged and have been widely adopted by various public and private sectors. Applications of IoT in the manufacturing industry, such as manufacturing intelligence, not only play a significant role in the enhancement of industrial competitiveness and sustainability, but also influence the diffusion of innovative applications that are based on IoT innovations. It is crucial for policy makers to understand these potential reasons for stimulating IoT industrial sustainability, as they can facilitate industrial competitiveness and technological innovations using supportive means, such as government procurement and financial incentives. Therefore, there is a need to ascertain different factors that may affect IoT industrial sustainability and further explore the relationship between these factors. However, finding a set of factors that affects IoT industrial sustainability is not easy. Recently, the robustness of a theoretical framework, termed the technological innovation system (TIS), has been verified and has been used to explore and analyze technological and industrial development. Thus, it is suitable for this research to use this theoretical model. In order to find out appropriate factors and accurately analyze the causality among factors that influence IoT industrial sustainability, this research presents a Bayesian rough Multiple Criteria Decision Making (MCDM) model based on TIS functions by integrating random forest (RF), decision making trial and evaluation (DEMATEL), Bayesian theory, and rough interval numbers. The proposed analytical framework is validated by an empirical case of defining the causality between TIS functions to enable the industrial sustainability of IoT in the Taiwanese smart manufacturing industry. Based on the empirical study results, the cause group consists of entrepreneurial activities, knowledge development, market formation, and resource mobilization. The effect group is composed of knowledge diffusion through networks’ guidance of the search, and creation of legitimacy. Moreover, the analytical results also provide several policy suggestions promoting IoT industrial sustainability that can serve as the basis for defining innovation policy tools for Taiwan and late coming economies.

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“…Experts from five groups expressed the importance of influencing factors for TPGGs' sustainable development in the electricity market in the first place. Based on the rule of "the minority is subordinate to the dominant" [74], the threshold value for the fuzzy Delphi method is determined by the majority. Then the relationships between each pair of influencing factors given by the experts were gathered according to Table 2.…”

Section: Introduction Of Expert Groups and Data Collectionmentioning

confidence: 99%

Identification of Key Influencing Factors of Sustainable Development for Traditional Power Generation Groups in a Market by Applying an Extended MCDM Model

et al. 2019

Self Cite

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With the deepening reform of the power market, the external environment of China’s power industry is going through a huge change. China’s traditional power generation groups (TPGGs), with assets all over the country, are, due to a lack of market awareness about energy policies, facing serious challenges in developing competitive advantages, improving power transaction modes, optimizing profit models, and even realizing basic corporate strategies. In this study, we focus on identifying the key factors influencing sustainable development in an unprecedented market environment for TPGGs, so as to achieve overall sustainable development for the whole power generation sector in China. A hybrid framework based on Multiple-Criteria Decision-Making (MCDM) was proposed to recognize the key influencing factors under vague rule conditions. We developed a novel method combining three different MCDM methods with triangular fuzzy numbers (TFNs), fuzzy Delphi, fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL), and Analytic Network Process (ANP), to cover uncertainty and make the problem-solving approach closer to the actual problem. A series of analyses indicate that the final 14 factors covering the five dimensions are considered to be important factors in the sustainable development of TPGGs. Based on the results, it can be said that “Gross energy margin” and “Pricing bidding strategy” dominate the impacts of TPGG’s sustainable development. Finally, we give some advice relating to practical measures to help TPGGs achieve sustainable development in the market-oriented industry environment.

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Evaluating the Comprehensive Performance of Demand Response for Commercial Customers by Applying Combination Weighting Techniques and Fuzzy VIKOR Approach

Cited by 19 publications

References 59 publications

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

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

Systemic Functions Evaluation based Technological Innovation System for the Sustainability of IoT in the Manufacturing Industry

Identification of Key Influencing Factors of Sustainable Development for Traditional Power Generation Groups in a Market by Applying an Extended MCDM Model

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