Optimal Placement of DGs in Distribution System Using an Improved Harris Hawks Optimizer Based on Single- and Multi-Objective Approaches

In this paper, improved single- and multi-objective Harris Hawks Optimization algorithms, called IHHO and MOIHHO, respectively are proposed and applied for determining the optimal placement of distribution generation (DG) in the radial distribution systems. Harris Hawks optimizer (HHO) is a new insp...

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Bibliographic Details
Main Authors: Ali Selim, Salah Kamel, Ali S. Alghamdi, Francisco Jurado
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9034010/
Description
Summary:In this paper, improved single- and multi-objective Harris Hawks Optimization algorithms, called IHHO and MOIHHO, respectively are proposed and applied for determining the optimal placement of distribution generation (DG) in the radial distribution systems. Harris Hawks optimizer (HHO) is a new inspired meta-heuristic optimization technique that is mainly based on the intelligence behavior of the Harris hawks in chasing prey. The IHHO and MOIHHO are applied for determining the optimal size and location of DG at different operating power factors (p.f) with the aim of minimizing the total active power loss, reducing the voltage deviation (VD), and increasing the voltage stability index (VSI) considering the operational constraints of distribution system. In IHHO, the performance of the conventional HHO algorithm is improved using the rabbit location instead of the random location. In MOIHHO, grey relation analysis is applied for identifying the best compromise solution among the non-dominance Pareto solutions. To verify the effectiveness of the proposed algorithms, IEEE 33-bus and IEEE 69-bus radial distribution systems are used, and the obtained results are compared with those obtained by other optimization techniques. The results prove the efficiency of the proposed algorithms in terms of best solutions obtained so far for the single- and multi-objective scenarios.
ISSN:2169-3536