LAPSE:2018.0832
Published Article
LAPSE:2018.0832
Multi-Objective Demand Response Model Considering the Probabilistic Characteristic of Price Elastic Load
Shengchun Yang, Dan Zeng, Hongfa Ding, Jianguo Yao, Ke Wang, Yaping Li
November 16, 2018
Demand response (DR) programs provide an effective approach for dealing with the challenge of wind power output fluctuations. Given that uncertain DR, such as price elastic load (PEL), plays an important role, the uncertainty of demand response behavior must be studied. In this paper, a multi-objective stochastic optimization problem of PEL is proposed on the basis of the analysis of the relationship between price elasticity and probabilistic characteristic, which is about stochastic demand models for consumer loads. The analysis aims to improve the capability of accommodating wind output uncertainty. In our approach, the relationship between the amount of demand response and interaction efficiency is developed by actively participating in power grid interaction. The probabilistic representation and uncertainty range of the PEL demand response amount are formulated differently compared with those of previous research. Based on the aforementioned findings, a stochastic optimization model with the combined uncertainties from the wind power output and the demand response scenario is proposed. The proposed model analyzes the demand response behavior of PEL by maximizing the electricity consumption satisfaction and interaction benefit satisfaction of PEL. Finally, a case simulation on the provincial power grid with a 151-bus system verifies the effectiveness and feasibility of the proposed mechanism and models.
Keywords
demand response, electricity consumption satisfaction (ECS), interaction benefit satisfaction (IBS), price elastic load (PEL), Stochastic Optimization, uncertainty
Suggested Citation
Yang S, Zeng D, Ding H, Yao J, Wang K, Li Y. Multi-Objective Demand Response Model Considering the Probabilistic Characteristic of Price Elastic Load. (2018). LAPSE:2018.0832
Author Affiliations
Yang S: School of Electrical & Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China; China Electric Power Research Institute-Nanjing Branch, Nanjing 210003, Jiangsu, China
Zeng D: China Electric Power Research Institute-Nanjing Branch, Nanjing 210003, Jiangsu, China
Ding H: School of Electrical & Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
Yao J: China Electric Power Research Institute-Nanjing Branch, Nanjing 210003, Jiangsu, China
Wang K: China Electric Power Research Institute-Nanjing Branch, Nanjing 210003, Jiangsu, China
Li Y: China Electric Power Research Institute-Nanjing Branch, Nanjing 210003, Jiangsu, China
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Journal Name
Energies
Volume
9
Issue
2
Article Number
E80
Year
2016
Publication Date
2016-01-27
Published Version
ISSN
1996-1073
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PII: en9020080, Publication Type: Journal Article
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LAPSE:2018.0832
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doi:10.3390/en9020080
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Nov 16, 2018
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Nov 16, 2018
 
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Calvin Tsay
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