Optimizing dynamic economic dispatch through an enhanced Cheetah-inspired algorithm for integrated renewable energy and demand-side management

被引:23
|
作者
Nagarajan, Karthik [1 ]
Rajagopalan, Arul [2 ]
Bajaj, Mohit [3 ,4 ,5 ,6 ]
Sitharthan, R. [2 ]
Dost Mohammadi, Shir Ahmad [7 ]
Blazek, Vojtech [8 ]
机构
[1] Hindustan Inst Technol & Sci, Dept Elect & Elect Engn, Chennai, Tamil Nadu, India
[2] Vellore Inst Technol, Ctr Smart Grid Technol, Sch Elect Engn, Chennai 600127, Tamil Nadu, India
[3] Graph Era Deemed Univ, Elect Engn Dept, Dehra Dun 248002, India
[4] AL Ahliyya Amman Univ, Hourani Ctr Appl Sci Res, Amman, Jordan
[5] Graph Era Hill Univ, Dehra Dun 248002, India
[6] Appl Sci Private Univ, Appl Sci Res Ctr, Amman 11937, Jordan
[7] Alberoni Univ, Fac Engn, Dept Elect & Elect, Kapisa, Afghanistan
[8] VSB Tech Univ Ostrava, ENET Ctr, Ostrava 70800, Czech Republic
关键词
EMISSION DISPATCH;
D O I
10.1038/s41598-024-53688-8
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
This study presents the Enhanced Cheetah Optimizer Algorithm (ECOA) designed to tackle the intricate real-world challenges of dynamic economic dispatch (DED). These complexities encompass demand-side management (DSM), integration of non-conventional energy sources, and the utilization of pumped-storage hydroelectric units. Acknowledging the variability of solar and wind energy sources and the existence of a pumped-storage hydroelectric system, this study integrates a solar-wind-thermal energy system. The DSM program not only enhances power grid security but also lowers operational costs. The research addresses the DED problem with and without DSM implementation to analyze its impact. Demonstrating effectiveness on two test systems, the suggested method's efficacy is showcased. The recommended method's simulation results have been compared to those obtained using Cheetah Optimizer Algorithm (COA) and Grey Wolf Optimizer. The optimization results indicate that, for both the 10-unit and 20-unit systems, the proposed ECOA algorithm achieves savings of 0.24% and 0.43%, respectively, in operation costs when Dynamic Economic Dispatch is conducted with Demand-Side Management (DSM). This underscores the advantageous capability of DSM in minimizing costs and enhancing the economic efficiency of the power systems. Our ECOA has greater adaptability and reliability, making it a promising solution for addressing multi-objective energy management difficulties within microgrids, particularly when demand response mechanisms are incorporated. Furthermore, the suggested ECOA has the ability to elucidate the multi-objective dynamic optimal power flow problem in IEEE standard test systems, particularly when electric vehicles and renewable energy sources are integrated.
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页数:22
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