Optimal Reactive Power Dispatch and Demand Response in Electricity Market Using Multi-Objective Grasshopper Optimization Algorithm

被引:0
|
作者
Das, Punam [1 ]
Dawn, Subhojit [2 ]
Gope, Sadhan [1 ]
Das, Diptanu [1 ]
Salata, Ferdinando [3 ]
机构
[1] Natl Inst Technol Agartala NITA, Dept Elect Engn, Agartala 799046, India
[2] Velagapudi Ramakrishna Siddhartha Engn Coll, Dept Elect & Elect Engn, Vijayawada 520007, India
[3] Sapienza Univ Rome, Fac Civil & Ind Engn, DIAEE, I-00185 Rome, Italy
关键词
demand response; electricity markets; Grasshopper Optimization Algorithm; Optimal Reactive Power Dispatch; CONGESTION MANAGEMENT; FLOW;
D O I
10.3390/pr12092049
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Optimal Reactive Power Dispatch (ORPD) is a power system optimization tool that modifies system control variables such as bus voltage and transformer tap settings, and it compensates devices' Volt Ampere Reactive (VAR) output. It is used to decrease real power loss, enhance the voltage profile, and promote stability. Furthermore, several issues have been faced in electricity markets, such as price volatility, transmission line congestion, and an increase in the cost of electricity during peak hours. Programs such as demand response (DR) provide system operators with more control over how small customers participate in lowering peak-hour energy prices and demand. This paper presents an extensive study on ORPD methodologies and DR programs for lowering voltage deviation, limiting cost, and minimizing power losses to create effective and economical operations systems. The main objectives of this work are to minimize costs and losses in the system and reduce voltage variation. The Grasshopper Optimization Algorithm (GOA) and Dragonfly Algorithm (DA) have been implemented successfully to solve this problem. The proposed technique has been evaluated by using the IEEE-30 bus system. The results obtained by the implementation of demand response systems show a considerable reduction in costs and load demands that benefit consumers through DR considerations. The results obtained from the GOA and DA are compared with those generated by other researchers and published in the literature to ascertain the algorithm's efficiency.
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页数:22
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