Multi-Objective Demand Response Model Considering the Probabilistic Characteristic of Price Elastic Load

Shengchun Yang, Dan Zeng, Hongfa Ding, Jianguo Yao, Ke Wang and Yaping Li
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Shengchun Yang: School of Electrical & Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
Dan Zeng: China Electric Power Research Institute-Nanjing Branch, Nanjing 210003, Jiangsu, China
Hongfa Ding: School of Electrical & Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
Jianguo Yao: China Electric Power Research Institute-Nanjing Branch, Nanjing 210003, Jiangsu, China
Ke Wang: China Electric Power Research Institute-Nanjing Branch, Nanjing 210003, Jiangsu, China
Yaping Li: China Electric Power Research Institute-Nanjing Branch, Nanjing 210003, Jiangsu, China

Energies, 2016, vol. 9, issue 2, 1-14

Abstract: 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: price elastic load (PEL); demand response; uncertainty; electricity consumption satisfaction (ECS); interaction benefit satisfaction (IBS); stochastic optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2016
References: View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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