Grasshopper Optimization Algorithm (GOA) is a recent swarm intelligence algorithm inspired by the foraging and swarming behavior of grasshoppers in nature. The GOA algorithm has been successfully applied to solve various optimization problems in several domains and demonstrated its merits in the literature. This paper proposes a comprehensive review of GOA based on more than 120 scientific articles published by leading publishers: IEEE, Springer, Elsevier, IET, Hindawi, and others. It provides the GOA variants, including multi-objective and hybrid variants. It also discusses the main applications of GOA in various fields such as scheduling, economic dispatch, feature selection, load frequency control, distributed generation, wind energy system, and other engineering problems. Finally, the paper provides some possible future research directions in this area.

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Grasshopper Optimization Algorithm: Theory, Variants, and Applications

https://www.econstor.eu/bitstream/10419/244147/1/1728587611.pdf

Multi-objective for optimal placement and sizing DG units in reducing loss of power and enhancing voltage profile using BPSO-SLFA

https://onlinelibrary.wiley.com/doi/pdf/10.1002/2050-7038.12230

Loss minimization techniques for optimal operation and planning of distribution systems: A review of different methodologies

ABC algorithm based optimal sizing and placement of DGs in distribution networks considering multiple objectives

Optimization of distribution system operation by network reconfiguration and DG integration using MPSO algorithm

Recent studies show that the majority of the researchers have focused on either Distributed Generation (DG) allocation or network reconfiguration for enhancing distribution network performance. How...

Optimal reconfiguration and renewable distributed generation allocation in electric distribution systems

Electric power generated in a centralized station is transmitted through the transmission system and supplied to the consumer end through an electric distribution substation. Electric power losses ...

Optimal Modeling and Allocation of Mixed Wind and Solar Generation Systems in Electric Distribution Networks

Distributed generation (DG) allocation is the most promising source for reducing network loss and enhancing bus voltage stability in a distribution system. Because of the vast availability and nonpolluting character of renewable energy resource, it is gaining more attention nowadays. The most widely used renewable-based DG (RDG) is wind turbine (WT) and solar photovoltaic (SPV). Power generation patterns of the WT and SPV modules are random and nonlinear because the power output of WT and SPV modules are dependent on wind speed and solar irradiation. These require a probabilistic model to represent the actual power generation. The present paper reflects the potency of WT and SPV modules for reducing system losses and enhancing voltage stability. A new hybrid gray wolf optimizer (HGWO) is proposed to solve the DG allocation problem. The proposed optimization method is tested on IEEE 12- and 15-bus radial distribution system (RDS) and it is found that the proposed HGWO has more potency in terms of loss reduction and voltage stability enhancement compared to the existing techniques.

Optimal Renewable Energy Resource Based Distributed Generation Allocation in a Radial Distribution System

In this paper, grasshopper optimization algorithm (GOA) a novel meta-heuristic optimization algorithm is used to solve the network reconfiguration problem in presence of distribution static compensator (D-STATCOM) and photovoltaic (PV) arrays in a distribution system. Here, D-STATCOM acts as distribution flexible ac transmission (D-FACT) device and PV arrays as decentralized or distributed generation (DG). The main purpose of the present research includes power loss minimization and voltage profile (VP) enhancement in radial distribution systems under different loading conditions. The proposed GOA is based on swarming behavior of grasshoppers in nature. The proposed GOA is validated using the standard 33, 69 and 118 – bus test systems. The simulation results proved that the optimal network reconfiguration in presence of D-STATCOM units and PV arrays leads to significant reduction in power loss and enhancement in VP. The results obtained by the proposed GOA are compared with base value and found that the optimal network reconfiguration in presence of D-STATCOM and PV arrays is more beneficial than individual objective optimization. Also, the proposed GOA is more accurate, efficient and reliable in finding optimal solution when compared to existing modified flower pollination algorithm (MFPA), firework algorithm (FWA), fuzzy-based ant colony optimization (ACO) and genetic algorithm (GA).

https://www.ejece.org/index.php/ejece/article/download/244/148

Kola Sampangi Sambaiah

Papers

Loss minimization techniques for optimal operation and planning of distribution systems: A review of different methodologies

Optimal reconfiguration and renewable distributed generation allocation in electric distribution systems

Optimal Modeling and Allocation of Mixed Wind and Solar Generation Systems in Electric Distribution Networks

Optimal Renewable Energy Resource Based Distributed Generation Allocation in a Radial Distribution System

Optimal Reconfiguration of Distribution Network in Presence of D-STATCOM and Photovoltaic Array using a Metaheuristic Algorithm