A MODA and MODE Comparison for Optimal Allocation of Distributed Generations with Different Load Levels

Salem Alkhalaf, Tomonobu Senjyu, Ayat Ali Saleh, Ashraf M. Hemeida and Al-Attar Ali Mohamed
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Salem Alkhalaf: Department of Computer Science, Alrass College of Science and Arts, Qassim University, Qassim, Arass 51921, Saudi Arabia
Tomonobu Senjyu: Department of Electrical and Electronics Engineering, Faculty of Engineering, University of the Ryukyus, Senbaru 9030213, Japan
Ayat Ali Saleh: Department of Electrical Engineering, Faculty of Energy Engineering, Aswan University, Aswan 81528, Egypt
Ashraf M. Hemeida: Department of Electrical Engineering, Faculty of Energy Engineering, Aswan University, Aswan 81528, Egypt
Al-Attar Ali Mohamed: Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan 81542, Egypt

Sustainability, 2019, vol. 11, issue 19, 1-18

Abstract: In this paper, the performance of different optimization techniques namely, multi-objective dragonfly algorithm (MODA) and multi-objective differential evolution (MODE) are presented and compared. The uncertainty effect of a wind turbine (WT) on the performance of the distribution system is taken into account. The point estimate method (PEM) is used to model the uncertainty in wind power. Optimization methods are applied to determine the multi-objective optimal allocation of distributed generation (DG) in radial distribution systems at a different load level (light, normal, heavy load level). The multi-objective function is expressed to minimize the total power loss, total operating cost, and improve the voltage stability index of the radial distribution system (RDS). Multi-objective proposed algorithms are used to generate the Pareto optimal solutions; and a fuzzy decision-making function is used to produce a hybrid function for obtaining the best compromise solution. The proposed algorithms are carried out on 33-bus and IEEE-69-bus power systems. The simulation results show the effectiveness of installing the proper size of DG at the suitable location based on different techniques.

Keywords: multi-objective dragonfly algorithm (MODA); multi-objective differential evolution (MODE); distributed generation; power loss; voltage stability index; renewable energy source (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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