Affiliation:
1. Department of Electrical Engineering and Automation, School of Automation, Xiasha Campus, Hangzhou Dianzi University, Hangzhou 310018, China
Abstract
In order to improve the utilization of user-side power resources in the distribution network and promote energy conservation, this paper designs a distributed system suitable for power demand response (DR), considering multi-agent system (MAS) technology and consistency algorithms. Due to the frequent changes in the power system structure caused by changes in the load of a large number of users, this paper proposes using cluster partitioning indicators as communication weights between agents, enabling agents to utilize the distribution network for collaborative optimization. In order to achieve the integration of multiple load-side power resources and improve the refinement level of demand-side management (DSM), two types of agents with load aggregator (LA) functions are provided, which adopt the demand response strategies of Time-of-Use (TOU) or Direct Load Control (DLC) and model the uncertainty of individual device states using Monte Carlo method, so that the two typical flexible loads can achieve the target load-reduction requirements under the MAS framework. The research results demonstrate that this method achieves complementary advantages of the two types of loads participating in DR on a time scale, reducing the costs of power companies and saving customers’ electricity bills while peak shaving.
Funder
National Natural Science Foundation of China
Fundamental Research Funds for the Provincial Universities of Zhejiang
Research on Design Theory and Method of Novel High Torque Permanent Magnet Traction Motor
Reference29 articles.
1. The People’s Political Consultative Conference Website (CPPCC) (2023, August 15). Local Development and Consumption Are the Key to Distributed “Wind and Solar Power”. Available online: http://www.rmzxb.com.cn/c/2021-07-13/2903585.shtml.
2. Vulnerability analysis of demand-response with renewable energy integration in smart grids to cyber attacks and online detection methods;Tang;Reliab. Eng. Syst. Saf.,2023
3. Bin, Y., Zhenyu, C., Yao, H., Wenjun, R., Hongquan, Z., and Zhiguo, G. (2020, January 4–7). Bi-Level Scheduling Model of Air Conditioning Load Aggregator Considering Users. Proceedings of the 2020 5th Asia Conference on Power and Electrical Engineering (ACPEE): 1995–2001, Chengdu, China.
4. Distributed control method for air conditioner load participation in distribution network voltage management;Wu;Autom. Electr. Power Syst.,2021
5. Incentive strategies for small and medium-sized customers to participate in demand response based on customer directrix load;Wang;Int. J. Electr. Power Energy Syst.,2024
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献