Optimal Multi-Objective Placement and Sizing of Distributed Generation in Distribution System: A Comprehensive Review

Mahesh Kumar, Amir Mahmood Soomro, Waqar Uddin and Laveet Kumar
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Mahesh Kumar: Department of Electrical Engineering, Mehran University of Engineering and Technology, Jamshoro 76062, Sindh, Pakistan
Amir Mahmood Soomro: Department of Electrical Engineering, Mehran University of Engineering and Technology, Jamshoro 76062, Sindh, Pakistan
Waqar Uddin: Electrical Engineering Department, National University of Technology, Islamabad 44000, Pakistan
Laveet Kumar: Department of Mechanical Engineering, Mehran University of Engineering and Technology, Jamshoro 76062, Sindh, Pakistan

Energies, 2022, vol. 15, issue 21, 1-48

Abstract: For over a decade, distributed generations (DGs) have sufficiently convinced the researchers that they are the economic and environment-friendly solution that can be integrated with the centralized generations. The optimal planning of distributed generations requires the appropriate location and sizing and their corresponding control with various power network types to obtain the best of the technical, economical, commercial, and regulatory objectives. Most of these objectives are conflicting in nature and require multi-objective solutions. Therefore, this paper brings a comprehensive literature review and a critical analysis of the state of the art of the optimal multi-objective planning of DG installation in the power network with different objective functions and their constraints. The paper considers the adoption of optimization techniques for distributed generation planning in radial distribution systems from different power system performance viewpoints; it considers the use of different DG types, distribution models, DG variables, and mathematical formulations; and it considers the participation of different countries in the stated DG placement and sizing problem. Moreover, the summary of the literature review and critical analysis of this article helps the researchers and engineers to explore the research gap and to find the future recommendations for the robust optimal planning of the DGs working with various objectives and algorithms. The paper considers the adoption of uncertainties on the load and generation side, the introduction of DGs with energy storage backups, and the testing of DG placement and sizing on large and complex distribution networks.

Keywords: distributed generation; electrical power network; artificial intelligence; grid network; grid-tied generation; distribution system (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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