Study on Dynamic Pricing Strategy for Industrial Power Users Considering Demand Response Differences in Master–Slave Game
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Published:2023-08-11
Issue:16
Volume:15
Page:12265
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ISSN:2071-1050
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Container-title:Sustainability
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language:en
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Short-container-title:Sustainability
Author:
Liu Shuxin1ORCID, Xu Jing1, Xing Chaojian1, Liu Yang2, Tian Ersheng2, Cui Jia1, Wei Junzhu1
Affiliation:
1. The School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, China 2. State Grid Xuji Group Co., Ltd., Xuchang 461111, China
Abstract
With the deepening of power market reform, further study on power trading mechanisms has become the core issue of power market study. The development stage of the industrial electricity market requires efficient and flexible pricing mechanisms. Currently available pricing strategies are inadequate for demand response management. Therefore, this paper provides an in-depth study of the pricing mechanism in the industrial electricity market in the context of electricity market reform. It proposes a demand–response-based dynamic pricing strategy for industrial parks. The method proposes a dynamic pricing strategy for demand-side response in industrial parks based on master–slave game by establishing an exogenous model of demand-side response and incentives. Compared with the existing strategies, the strategy is more efficient and flexible, and effectively improves the economic efficiency of power trading and load regulation. Firstly, an exogenous model of demand-side response and incentive is built to characterize the demand-side response cost. The method focuses more on describing the exogenous characteristics of user incentives and response quantities. It only needs to analyze the exogenous indicators and random errors in various typical scenarios. The description of user demand-side response is more efficient. Secondly, a master–slave-game-based dynamic pricing strategy for industrial parks with demand-side response is proposed. The strategy is composed of a two-stage optimization. The primary regulation of customers is achieved by day-ahead time-of-use tariffs. The secondary regulation of customers is achieved by means of the same-day regulation of demand and purchase regarding clean electricity. The proposed two-stage price formation mechanism is more economical, more effective in load regulation, and improves the flexibility of industrial pricing. Finally, a case study is conducted on an industrial power user in a park in Liaoning Province. The results show that the proposed method is significantly better than existing methods in terms of improving the economic efficiency and load control effectiveness of the pricing strategy.
Funder
Grant for Multi-Energy Collaborative Optimization and Intelligent Control Technology for High-Scale Clean Energy High-Rail Stations Liaoning Province Science and Technology Major Special Project
Subject
Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction
Reference23 articles.
1. Quantitative flexibility assessment of a comprehensive set of demand response programs;Golshan;Int. J. Electr. Power Energy Syst.,2020 2. A comprehensive linear model for demand response optimization problem;Golshan;Energy,2020 3. Sundaramoorthy, S., Kamath, D., Nimbalkar, S., Price, C., Wenning, T., and Cresko, J. (2023). Energy Efficiency as a Foundational Technology Pillar for Industrial Decarbonization. Sustainability, 15. 4. Optimization Modeling for Dynamic Price Based Demand Response in Microgrids;Hassan;J. Clean. Prod.,2019 5. Pietrasanta, A.M., Shaaban, M.F., and Aguirre, P.A. (2023). Simulation and Optimization of Renewable Energy-Powered Desalination: A Bibliometric Analysis and Highlights of Recent Research. Sustainability, 15.
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