期刊
ELECTRIC POWER SYSTEMS RESEARCH
卷 214, 期 -, 页码 -出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.epsr.2022.108902
关键词
Renewable generation; Demand response programs; System flexibility; Microgrids; Multi-objective optimization
This paper proposes a multi-objective optimization framework to improve the performance of demand response programs in distribution networks. The uncoordinated response of customers creates new peaks in the load profile when market prices are low, so the framework focuses on reducing operating costs and enhancing program efficiency. The model introduces the Average Power Flexibility during Peak Period Index (APFDPPI) to evaluate energy flexibility and simulation results show significant improvements compared to uncoordinated programs.
This paper proposes multi-objective optimization framework to enhance the performance of demand response programs in distribution networks. The demand response programs are one of the main resources to enhance the flexibility of the energy systems to manage the uncertain behavior of renewable generation and demand loads. But, the uncoordinated response of customers creates a new peak in the load profile when the market prices are low. Therefore, we present a two-stage multi-objective framework that simultaneously reduces the operating costs and enhances the efficiency of demand response programs in the grid-connected microgrid systems. The first stage focuses on the optimal energy management of the grid-connected microgrid systems from the economic perspective. The second stage focuses on the demand-side flexibility to uniform the load profile. Also, we introduce the Average Power Flexibility during Peak Period Index (APFDPPI) to evaluate the energy flexibility of the demand response programs. The proposed model has been tested on a standard grid-connected microgrid, and the simulation results show that the proposed model improves the amount of energy not served by 22.12%. Also, the peak load and the load factor have been improved by 12.96% and 15.17%, respectively compared to uncoordinated demand response programs.
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