Optimal Sizing and Deployment of Renewable Energy Generators in Practical Transmission Network Using Grid-Oriented Multiobjective Harmony Search Algorithm for Loss Reduction and Voltage Profile Improvements

被引:0
作者
Kumar, Pramod [1 ]
Swarnkar, Nagendra Kumar [1 ]
Mahela, Om Prakash [2 ,3 ]
Khan, Baseem [3 ,4 ]
Anand, Divya [5 ,6 ]
Singh, Aman [6 ,7 ]
Mazon, Juan Luis Vidal [6 ,8 ]
Alharithi, Fahd S. [9 ]
机构
[1] Suresh Gyan Vihar Univ, Dept Elect Engn, Jaipur, India
[2] Rajasthan Rajya Vidyut Prasaran Nigam Ltd, Power Syst Planning Div, Jaipur 302005, Rajasthan, India
[3] Univ Int Iberoamericana, Engn Res & Innovat Grp ERIG, Campeche 24560, Mexico
[4] Hawassa Univ, Dept Elect Engn, Hawassa, Ethiopia
[5] Lovely Profess Univ, Sch Comp Sci & Engn, Phagwara 144411, Punjab, India
[6] Univ Europea Atlantico, Higher Polytech Sch, C Isabel Torres 21, Santander 39011, Spain
[7] Uttaranchal Univ, Uttaranchal Inst Technol, Dehra Dun 248007, Uttaranchal, India
[8] Univ Int Iberoamericana, Dept Engn, Arecibo, PR 00613 USA
[9] Taif Univ, Coll Comp & Informat Technol, Dept Comp Sci, POB 11099, Taif 21944, Saudi Arabia
关键词
DISTRIBUTED GENERATORS; OPTIMAL PLACEMENT; OPTIMIZATION; CAPACITORS;
D O I
10.1155/2023/6315918
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper presents grid-oriented multiobjective harmony search algorithm (GOMOHSA) to incorporate the multiple grid parameters for minimization of the active power loss, reactive power loss, and total voltage deviations (TVD) in a part of practical transmission network of Rajasthan Rajya Vidyut Prasaran Nigam Limited (RVPN) in southern parts of Rajasthan state of India. This is achieved by optimal deployment of optimally sized renewable energy (RE) generators using GOMOHSA. Performance indexes such as active power loss minimization index (APMLI), the reactive power loss minimization index (RPMLI), and the total voltage deviation improvement index (TVDII) are introduced to evaluate the health of the test network with different load scenarios. Performance of proposed GOMOHSA has been tested for five different operating scenarios of loads and RE generation. It is established that the proposed GOMOHSA finds the optimal deployment of optimally sized RE generators, and the investment cost of deployment of these RE generators can be recovered within a time period that is less than 5 years. Performance of GOMOHSA is superior compared to a conventional genetic algorithm (GA) in terms of performance indexes, RE generator capacity, payback period, and parameter sensitivity. Study is performed using MATLAB software for loading scenario of base year 2021 and projected year 2031.
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页数:19
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