scholarly journals An Effective Reactive Power Compensation Method and a Modern Metaheuristic Algorithm for Loss Reduction in Distribution Power Networks

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Thang Trung Nguyen ◽  
Kim Hung Le ◽  
Tan Minh Phan ◽  
Minh Quan Duong
Keyword(s):  
Power Loss ◽  
Distribution Systems ◽  
Reactive Power ◽  
Reducing Power ◽  
Reactive Power Compensation ◽  
Compensation Method ◽  
New Method ◽  
Total Power ◽  
Loss Reduction ◽  
Power Networks

In this paper, a new method of reactive power compensation is proposed for reducing power loss of distribution power networks. The new method is the combination of local compensation at each load and distribution line compensation. In the method, local capacitors at each load are determined to increase power factor of load to an expected value first and then a number of capacitors are placed in distribution lines with two factors, location and capacity by using the three applied methods. Particle swarm optimization (PSO), parasitism predation algorithm (PPA), and tunicate swarm algorithm (TSA) are applied for the proposed method on four distribution systems with 15, 33, 69, and 85 buses. The comparisons of results with previous methods indicate that the three applied methods can reach higher loss reduction for all study cases. TSA can reach loss reduction more effectively than others by 19.4%, 0.5%, 7.9%, and 10.76% for the four distribution systems, respectively. The most important emphasis is that PSO, which was considered to be of low effectiveness in previous studies, can reach much better loss than approximately all previous methods thank to the proposed compensation method. PSO also reached better loss reduction than others by 18.97%, 0.4%, 7.73%, and 10.21%, respectively. Consequently, it is recommended that the proposed compensation method is useful for distribution systems in minimizing total power loss and TSA can be selected a new and powerful method for the problem.

Reactive Power Compensation of Oilfield Distribution Systems Based on Tabu Search Algorithm

2013 ◽  
Vol 397-400 ◽  
pp. 1113-1116
Author(s):  
Xiao Meng Wu ◽  
Wang Hao Fei ◽  
Xiao Mei Xiang ◽  
Wen Juan Wang
Keyword(s):  
Power Loss ◽  
Distribution Systems ◽  
Reactive Power ◽  
Search Algorithm ◽  
Global Optimum ◽  
Reactive Power Compensation ◽  
Active Power ◽  
Voltage Profile ◽  
Voltage Range ◽  
Shunt Capacitors

In order to solve the problem in reactive power compensation of oilfield distribution systems at present, a Taboo search algorithm is proposed in this paper, by which the optimal location and size of shunt capacitors on distribution systems are determined. Then the voltage profile is improved and the active power loss is reduced. In this paper, Voltage qualified is used as objective function to search an initial solution that meets the voltage constraints so that it is feasible in practicable voltage range; then the global optimum solution can be got when taking the reduced maximum of active power loss as objective unction. The examples show that the improved algorithm is feasible and effective.

scholarly journals Optimal Reactive Power Generation for Radial Distribution Systems Using a Highly Effective Proposed Algorithm

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-36
Author(s):  
Le Chi Kien ◽  
Thuan Thanh Nguyen ◽  
Bach Hoang Dinh ◽  
Thang Trung Nguyen
Keyword(s):  
Power Loss ◽  
Distribution Systems ◽  
Reactive Power ◽  
Search Algorithm ◽  
Diffusion Mechanism ◽  
Total Power ◽  
Total Cost ◽  
The Third ◽  
Stochastic Fractal Search Algorithm ◽  
Stochastic Fractal Search

In this paper, a proposed modified stochastic fractal search algorithm (MSFS) is applied to find the most appropriate site and size of capacitor banks for distribution systems with 33, 69, and 85 buses. Two single-objective functions are considered to be reduction of power loss and reduction of total cost of energy loss and capacitor investment while satisfying limit of capacitors, limit of conductor, and power balance of the systems. MSFS was developed by performing three new mechanisms including new diffusion mechanism and two new update mechanisms on the conventional stochastic fractal search algorithm (SFS). As a result, MSFS can reduce 0.002%, 0.003%, and 0.18% of the total power loss from SFS for the three study systems. As compared to other methods, MSFS can reduce power loss from 0.07% to 3.98% for the first system, from 3.7% to 7.3% for the second system, and from 0.92% to 6.98% for the third system. For the reduction of total cost, the improvement level of the proposed method over SFS and two other methods is more significant. It is 0.03%, 1.22%, and 5.76% for the second system and 2.31%, 0.87%, and 3.77% for the third system. It is emphasized that the proposed method can find the global optimal solutions for all study cases while SFS was still implementing search process nearby or far away from the solutions. Furthermore, MSFS can converge to the best solutions much faster than these compared methods. Consequently, it can be concluded that the proposed method is very effective for finding the best location and size of added capacitors in distribution power systems.

Maximum Loss Reduction and Voltage Profile Improvement with Placement of Hybrid Solar-Wind System

2013 ◽  
Vol 768 ◽  
pp. 371-377 ◽  
Author(s):  
E. Rekha ◽  
D. Sattianadan ◽  
M. Sudhakaran
Keyword(s):  
Radial Distribution ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Systems ◽  
Reactive Power ◽  
Optimization Technique ◽  
Future Generation ◽  
Loss Reduction ◽  
Voltage Profile ◽  
Voltage Profile Improvement

Distributed generators (DG) are much beneficial in reducing the losses effectively compared to other methods of loss reduction. It is expected to become more important in future generation. This paper deals with the multi DGs placement in radial distribution system to reduce the system power loss and improve the voltage profile by using the optimization technique of particle swarm optimization (PSO). The PSO provides a population-based search procedure in which individuals called particles change their positions with time. Initially, the algorithm randomly generates the particle positions representing the size and location of DG. The proposed PSO algorithm is used to determine optimal sizes and locations of multi-DGs. The objective function is the combination of real, reactive power loss and voltage profile with consideration of weights and impact indices with and without DG. Test results indicate that PSO method can obtain better results on loss reduction and voltage profile improvement than the simple heuristic search method on the IEEE33-bus and IEEE 90-bus radial distribution systems.

scholarly journals TECHNO-ECONOMIC ASSESMENT FOR DISTRIBUTED GENERATION PLACEMENT IN DISTRIBUTION SYSTEM

KURVATEK ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 1-6
Author(s):  
Sugiarto Kadiman
Keyword(s):  
Distributed Generation ◽  
Power Loss ◽  
Distribution Systems ◽  
Reactive Power ◽  
Test System ◽  
Optimal Placement ◽  
Loss Reduction ◽  
Voltage Profile ◽  
Power Loss Reduction ◽  
Reduction Index

This paper presents a proposed function which is known as techno-economic model for optimal placement of distributed generation (DG) resources in distribution systems in order to minimize the power losses and improve voltage profile. Combined sensitivity factors (CSF), such real power loss reduction index, reactive power loss reduction index, voltage profile improvement index, and life cycle cost, and particle swarm optimization (PSO) are applied to the proposed technique to obtain the best compromise between these costs. Simulation results on IEEE 14-bus test system are presented to demonstrate the usefulness of the proposed procedure.

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