scholarly journals Optimal Allocation of Multiple Types of Distributed Generations in Radial Distribution Systems Using a Hybrid Technique

2021 ◽  
Vol 13 (12) ◽  
pp. 6644
Author(s):  
Ali Selim ◽  
Salah Kamel ◽  
Amal A. Mohamed ◽  
Ehab E. Elattar
Keyword(s):  
Power System ◽  
Radial Distribution ◽  
Distribution Systems ◽  
Optimal Allocation ◽  
Optimization Technique ◽  
Mathematical Formulation ◽  
Optimization Techniques ◽  
Sensitivity Factor ◽  
Hybrid Technique ◽  
Analytical Technique

In recent years, the integration of distributed generators (DGs) in radial distribution systems (RDS) has received considerable attention in power system research. The major purpose of DG integration is to decrease the power losses and improve the voltage profiles that directly lead to improving the overall efficiency of the power system. Therefore, this paper proposes a hybrid optimization technique based on analytical and metaheuristic algorithms for optimal DG allocation in RDS. In the proposed technique, the loss sensitivity factor (LSF) is utilized to reduce the search space of the DG locations, while the analytical technique is used to calculate initial DG sizes based on a mathematical formulation. Then, a metaheuristic sine cosine algorithm (SCA) is applied to identify the optimal DG allocation based on the LSF and analytical techniques instead of using random initialization. To prove the superiority and high performance of the proposed hybrid technique, two standard RDSs, IEEE 33-bus and 69-bus, are considered. Additionally, a comparison between the proposed techniques, standard SCA, and other existing optimization techniques is carried out. The main findings confirmed the enhancement in the convergence of the proposed technique compared with the standard SCA and the ability to allocate multiple DGs in RDS.

scholarly journals Developing a Hybrid Approach Based on Analytical and Metaheuristic Optimization Algorithms for the Optimization of Renewable DG Allocation Considering Various Types of Loads

2021 ◽  
Vol 13 (8) ◽  
pp. 4447
Author(s):  
Amal A. Mohamed ◽  
Salah Kamel ◽  
Ali Selim ◽  
Tahir Khurshaid ◽  
Sang-Bong Rhee
Keyword(s):  
Optimal Allocation ◽  
Optimization Technique ◽  
Hybrid Approach ◽  
Optimization Techniques ◽  
Constant Current ◽  
Hybrid Technique ◽  
Voltage Profile ◽  
Analytical Technique ◽  
Metaheuristic Optimization ◽  
Different Types

The optimal location of renewable distributed generations (DGs) into a radial distribution system (RDS) has attracted major concerns from power system researchers in the present years. The main target of DG integration is to improve the overall system performance by minimizing power losses and improving the voltage profile. Hence, this paper proposed a hybrid approach between an analytical and metaheuristic optimization technique for the optimal allocation of DG in RDS, considering different types of load. A simple analytical technique was developed in order to determine the sizes of different and multiple DGs, and a new efficient metaheuristic technique known as the Salp Swarm Algorithm (SSA) was suggested in order to choose the best buses in the system, proportionate to the sizes determined by the analytical technique, in order to obtain the minimum losses and the best voltage profile. To verify the power of the proposed hybrid technique on the incorporation of the DGs in RDS, it was applied to different types of static loads; constant power (CP), constant impedance (CZ), and constant current (CI). The performance of the proposed algorithm was validated using two standards RDSs—IEEE 33-bus and IEEE 69-bus systems—and was compared with other optimization techniques.

scholarly journals A Novel Multiobjective Hybrid Technique for Siting and Sizing of Distributed Generation and Capacitor Banks in Radial Distribution Systems

2021 ◽  
Vol 13 (6) ◽  
pp. 3308
Author(s):  
Chandrasekaran Venkatesan ◽  
Raju Kannadasan ◽  
Mohammed H. Alsharif ◽  
Mun-Kyeom Kim ◽  
Jamel Nebhen
Keyword(s):  
Multiobjective Optimization ◽  
Distributed Generation ◽  
Radial Distribution ◽  
Hybrid Method ◽  
Distribution Systems ◽  
Optimization Technique ◽  
Optimal Placement ◽  
Grey Wolf Optimizer ◽  
Hybrid Technique ◽  
Metaheuristic Optimization

Distributed generation (DG) and capacitor bank (CB) allocation in distribution systems (DS) has the potential to enhance the overall system performance of radial distribution systems (RDS) using a multiobjective optimization technique. The benefits of CB and DG injection in the RDS greatly depend on selecting a suitable number of CBs/DGs and their volume along with the finest location. This work proposes applying a hybrid enhanced grey wolf optimizer and particle swarm optimization (EGWO-PSO) algorithm for optimal placement and sizing of DGs and CBs. EGWO is a metaheuristic optimization technique stimulated by grey wolves. On the other hand, PSO is a swarm-based metaheuristic optimization algorithm that finds the optimal solution to a problem through the movement of the particles. The advantages of both techniques are utilized to acquire mutual benefits, i.e., the exploration ability of the EGWO and the exploitation ability of the PSO. The proposed hybrid method has a high convergence speed and is not trapped in local optimal. Using this hybrid method, technical, economic, and environmental advantages are enhanced using multiobjective functions (MOF) such as minimizing active power losses, voltage deviation index (VDI), the total cost of electrical energy, and total emissions from generation sources and enhancing the voltage stability index (VSI). Six different operational cases are considered and carried out on two standard distribution systems, namely, IEEE 33- and 69-bus RDSs, to demonstrate the proposed scheme’s effectiveness extensively. The simulated results are compared with existing optimization algorithms. From the obtained results, it is observed that the proposed EGWO-PSO gives distinguished enhancements in multiobjective optimization of different conflicting objective functions and high-level performance with global optimal values.

scholarly journals Loss Minimization by Reconfiguration in Radial Distribution Network using Whale Optimization Technique

2020 ◽  
Vol 9 (2) ◽  
pp. 1746-1751
Keyword(s):  
Radial Distribution ◽  
Optimization Algorithm ◽  
Distribution Systems ◽  
Heuristic Algorithms ◽  
Optimization Technique ◽  
Optimization Techniques ◽  
Whale Optimization Algorithm ◽  
Function Evaluation ◽  
Voltage Profile ◽  
Whale Optimization

This paper provides a new approach for solving the problem of network reconfiguration in the presence of Whale Optimization Algorithm (WOA). It is aimed at reducing actual power loss and enlightening the voltage profile in the supply system. The voltage and branch current capacity constraints have been included in the objective function evaluation. The method has been evaluated at three separate heuristic algorithms on 33-bus radial distribution systems to demonstrate the performance and effectiveness of the proposed method. In this paper the comparison of performance of two latest optimization techniques such as Whale Optimization Algorithm (WOA) with classic optimization techniques such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The new optimization technique produces better result compare to other two optimization logarithm..

scholarly journals Re-Allocation of Distributed Generations Using Available Renewable Potential Based Multi-Criterion-Multi-Objective Hybrid Technique

2021 ◽  
Vol 13 (24) ◽  
pp. 13709
Author(s):  
Chandrasekaran Venkatesan ◽  
Raju Kannadasan ◽  
Dhanasekar Ravikumar ◽  
Vijayaraja Loganathan ◽  
Mohammed H. Alsharif ◽  
...  
Keyword(s):  
Distribution Systems ◽  
Optimization Technique ◽  
Pso Algorithm ◽  
Optimization Techniques ◽  
Grey Wolf Optimizer ◽  
Hybrid Technique ◽  
Objective Functions ◽  
Distributed Generations ◽  
Multi Objective ◽  
Metaheuristic Optimization

Integration of Distributed generations (DGs) and capacitor banks (CBs) in distribution systems (DS) have the potential to enhance the system’s overall capabilities. This work demonstrates the application of a hybrid optimization technique the applies an available renewable energy potential (AREP)-based, hybrid-enhanced grey wolf optimizer–particle swarm optimization (AREP-EGWO-PSO) algorithm for the optimum location and sizing of DGs and CBs. EGWO is a metaheuristic optimization technique stimulated by grey wolves, and PSO is a swarm-based metaheuristic optimization algorithm. Hybridization of both algorithms finds the optimal solution to a problem through the movement of the particles. Using this hybrid method, multi-criterion solutions are obtained, such as technical, economic, and environmental, and these are enriched using multi-objective functions (MOF), namely minimizing active power losses, voltage deviation, the total cost of electrical energy, total emissions from generation sources and enhancing the voltage stability index (VSI). Five different operational cases were adapted to validate the efficacy of the proposed scheme and were performed on two standard distribution systems, namely, IEEE 33- and 69-bus radial distribution systems (RDSs). Notably, the proposed AREP-EGWO-PSO algorithm compared the AREP at the candidate locations and re-allocated the DGs with optimal re-sizing when the EGWO-PSO algorithm failed to meet the AREP constraints. Further, the simulated results were compared with existing optimization algorithms considered in recent studies. The obtained results and analysis show that the proposed AREP-EGWO-PSO re-allocates the DGs effectively and optimally, and that these objective functions offer better results, almost similar to EGWO-PSO results, but more significant than other existing optimization techniques.

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

2019 ◽  
Vol 11 (19) ◽  
pp. 5323 ◽  
Author(s):  
Salem Alkhalaf ◽  
Tomonobu Senjyu ◽  
Ayat Ali Saleh ◽  
Ashraf M. Hemeida ◽  
Al-Attar Ali Mohamed
Keyword(s):  
Radial Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Optimal Allocation ◽  
Load Level ◽  
Optimization Techniques ◽  
Total Power ◽  
Fuzzy Decision Making ◽  
Multi Objective ◽  
Point Estimate Method

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.

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