scholarly journals Continuous domain ant colony optimization for distributed generation placement and losses minimization

2020 ◽  
Vol 9 (2) ◽  
pp. 261
Author(s):  
Zulkiffli Abdul Hamid ◽  
Ismail Musirin ◽  
Ammar Yasier Azman ◽  
Muhammad Murtadha Othman
Keyword(s):  
Ant Colony Optimization ◽  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Test System ◽  
Ant Colony ◽  
Optimal Size ◽  
Voltage Profile ◽  
Radial Distribution System ◽  
Continuous Domain

This paper proposes a method for distributed generation (DG) placement in distribution system for losses minimization and voltage profile improvement. An IEEE 33-bus radial distribution system is used as the test system for the placement of DG. To facilitate the sizing of DG capacity, a meta-heuristic algorithm known as Continuous Domain Ant Colony Optimization (ACO<sub>R</sub>) is implemented. The ACO<sub>R</sub> is a modified version of the traditional ACO which was developed specially for solving continuous domain optimization problem like sizing a set of variables. The objective of this paper is to determine the optimal size and location of DG for power loss minimization and voltage profile mitigation. Three case studies were conducted for the purpose of verification. It was observed that the proposed technique is able to give satisfactory results of real power loss and voltage profile at post-optimization condition. Experiment under various loadings of the test system further justifies the objective of the study.

scholarly journals Recloser-Fuse settings in distribution systems with optimizing multiple distributed generation considering technical aspects

2020 ◽  
Vol 17 (3) ◽  
pp. 1135
Author(s):  
Ahmed Mohamed Abdelbaset ◽  
AboulFotouh A. Mohamed ◽  
Essam Abou El-Zahab ◽  
M. A. Moustafa Hassan
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Systems ◽  
Test System ◽  
Optimal Size ◽  
Loss Reduction ◽  
Voltage Profile ◽  
Power Loss Reduction ◽  
System Power

<p><span>With the widespread of using distributed generation, the connection of DGs in the distribution system causes miscoordination between protective devices. This paper introduces the problems associated with recloser fuse miscoordination (RFM) in the presence of single and multiple DG in a radial distribution system. Two Multi objective optimization problems are presented. The first is based on technical impacts to determine the optimal size and location of DG considering system power loss reduction and enhancement the voltage profile with a certain constraints and the second is used for minimizing the operating time of all fuses and recloser with obtaining the optimum settings of fuse recloser coordination characteristics. Whale Optimizer algorithm (WOA) emulated RFM as an optimization problem. The performance of the proposed methodology is applied to the standard IEEE 33 node test system. The results show the robustness of the proposed algorithm for solving the RFM problem with achieving system power loss reduction and voltage profile enhancement.</span></p>

scholarly journals Optimal distributed generation location and sizing for loss minimization and voltage profile optimization using ant colony algorithm

2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Adeseye Amos Ogunsina ◽  
Moses Omolayo Petinrin ◽  
Olutomilayo Olayemi Petinrin ◽  
Emeka Nelson Offornedo ◽  
Joseph Olawole Petinrin ◽  
...  
Keyword(s):  
Distributed Generation ◽  
Power Distribution ◽  
Distribution System ◽  
Power Loss ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Voltage Profile ◽  
Real Power ◽  
Power Distribution System ◽  
The Impact

AbstractA system of power generation whereby the generating equipment is located close to the point of usage, thereby reducing losses and operation cost is called distributed generation (DG). However, it is imperative that DGs are sited such that the quality of power delivered is optimized and the total real power loss within the system minimized. This paper proposes an approach for optimum sizing and siting of DGs sizing in a power distribution system using Ant Colony Optimization (ACO) algorithm. To validate the algorithm the IEEE 30 bus standard test system was employed. A 92% decrease in real power loss within the system relative to the value before the connection of DGs was observed, while the minimum bus voltage increased from 0.656 per unit to 0.965 per unit. The results obtained from ACO are further verified by creating an ETAP model of the IEEE 30 bus system and simulating the impact of DG on the system. A significant reduction in total real power losses within the system and improvement in voltage profile was observed when the DGs are placed at the ACO derived sites relative to at other locations. Therefore, Ant Colony Algorithm can be used in deriving the optimum sites and sizes of DGs in a power distribution system.

scholarly journals Power Quality Enhancement by Integrating Distributed Generation in Distribution System

2018 ◽  
Vol 7 (4.24) ◽  
pp. 167
Author(s):  
Mr. Rajesh Kumar Samala ◽  
Dr. K Mercy Rosalina
Keyword(s):  
Power Quality ◽  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Bat Algorithm ◽  
Optimal Placement ◽  
Optimal Size ◽  
Voltage Profile ◽  
Real Power ◽  
Optimal Capacity

This research is to enhance the quality of power by reduce real power loss in distribution system and enables voltage profile enhancement at each bus. This will achieve by integrating Distributed Generation (DG) in optimal place with suitable size. In order to overcome the disadvantage of sluggish convergence of conventional algorithms the BAT Algorithm (BA) is used. In this paper the week buses are finding by using Backward/Forward (BW/FW) sweep approach based on real power loss. Later by using BA approach determination of optimal capacity and location will be done. This optimal size and location will leads to great minimization in real power loss and improvement of voltage at each bus. In this research the wind energy and Photo Voltaic (PV) energies are consider as DGs. This research is to determine the advantage of the proposed analysis on IEEE-69 radial bus using MATLAB software. The results were evaluated with the GSA approach existing in literature. Finally simulation outcomes prove that the proposed approach performance is superior in enhancing the power quality by optimal placement of DG and capacity of the DG.

scholarly journals Optimal Integration of Capacitor and Distributed Generation in Distribution System Considering Load Variation Using Bat Optimization Algorithm

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3548
Author(s):  
Thangaraj Yuvaraj ◽  
Kaliaperumal Rukmani Devabalaji ◽  
Natarajan Prabaharan ◽  
Hassan Haes Alhelou ◽  
Asokkumar Manju ◽  
...  
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Systems ◽  
Peak Load ◽  
Test System ◽  
Sensitivity Factor ◽  
Optimal Size ◽  
Step Size ◽  
Light Load

In this article, an efficient long-term novel scheduling technique is proposed for allocating capacitors in a combined system involving distributed generation (DG) along with radial distribution systems (RDS). We introduce a unique multi-objective function that focuses on the reduction of power loss with the maximization of voltage stability index (VSI) subjected to constraints of equality and inequality systems. Loss sensitivity factor and VSI together are involved in pre-identifying the locations of capacitors and DG. Determination of the optimal size of capacitor and DG is performed by utilizing the Bat algorithm (BA) for all the loads in RDS. The conventional approach considers the medium load of (1.0) condition generally, but the proposed method changes the feeder loads linearly, ranging from light load (0.5) to peak load (1.6) with the value of step size as 1%. BA determines the optimal size of the capacitor and DG for each step load. The curve fitting technique is used for deducing the generalized equation of capacitor size and DG for all conditions of the load with the various loading condition sized by distributed network operators (DNOs). Further, various load models such as industrial, residential, and commercial loads have been considered to show the efficiency of the present approach. Validation of results is performed in different scenarios on a 69-bus test system and on a standard IEEE 33-bus system. The results exhibit improved accuracy with less power loss value, superior bus voltage, and stability of system voltage with a higher rate of convergence.

scholarly journals Voltage Profile Improvement of Distribution System via Integration of Distributed Generation Resources

2021 ◽  
Vol 1 (1) ◽  
pp. 33
Author(s):  
Biswas Babu Pokhrel ◽  
Ashish Shrestha ◽  
Sudip Phuyal ◽  
Shailendra Kumar Jha
Keyword(s):  
Ant Colony Optimization ◽  
Distributed Generation ◽  
Power Supply ◽  
Distribution System ◽  
Load Flow ◽  
Voltage Profile ◽  
Radial Distribution System ◽  
Distributed Generator ◽  
Sweep Algorithm ◽  
Voltage Profile Improvement

This study attempts to identify the causes and possible solutions for voltage profile issues in the lower land of Nepal, and is specifically focused on Laukahi feeder, a radial distribution system with an approximate length of 65 km and distributed at 11KV system voltage. Currently, the end-users feeding through this feeder are getting extremely poor voltage along with frequent interruptions in the power supply. In this study, a forward/ backward sweep algorithm is used to analyze the load flow of the distribution system, whereas ant colony optimization (ACO) technique is used to identify the best location for the Distributed Generator (DG) penetrations. After completion of this study, it is found that, the branch loss of the feeder can be reduced up to 87.22%, and voltage profile can be improved from 0.828 pu to 0.982 pu by integrating some form of DGs.

Optimal Capacitors in Radial Distribution System for Loss Reduction and Voltage Enhancement

2016 ◽  
Vol 2 (3) ◽  
pp. 566 ◽  
Author(s):  
S. Bhongade ◽  
Sachin Arya
Keyword(s):  
Radial Distribution ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Systems ◽  
Pso Algorithm ◽  
Load Flow ◽  
Base Case ◽  
Voltage Profile ◽  
Radial Distribution System ◽  
Case Load

The work presented in this paper is carried out with the objective of identifying the optimal location and size (Kvar ratings) of shunt capacitors to be placed in radial distribution system, to have overall economy considering the saving due to energy loss minimization. To achieve this objective, a two stage methodology is adopted in this paper. In the first stage, the base case load flow of uncompensated distribution system is carried out. On the basis of base case load flow solution, Nominal voltage magnitudes and Loss Sensitivity Factors are calculated and the weak buses are selected for capacitor placement.In the second stage, Particle Swarm Optimization (PSO) algorithm is used to identify the size of the capacitors to be placed at the selected buses for minimizing the power loss. The developed algorithm is tested for 10-bus, 34-bus and 85-bus Radial Distribution Systems. The results show that there has been an enhancement in voltage profile and reduction in power loss thus resulting in much annual saving.

Decline of Real Power Loss by the Combination of Ant Colony Optimization and Simulated Annealing Algorithm

2016 ◽  
Vol 23 ◽  
pp. 113-119 ◽  
Author(s):  
K. Lenin ◽  
B. Ravindhranath Reddy ◽  
M. Suryakalavathi
Keyword(s):  
Simulated Annealing ◽  
Ant Colony Optimization ◽  
Power Loss ◽  
Simulated Annealing Algorithm ◽  
Reactive Power ◽  
Test System ◽  
Ant Colony ◽  
Local Optimum ◽  
Real Power ◽  
Combined Algorithm

Combination of ant colony optimization (ACO) algorithm and simulated annealing (SA) algorithm has been done to solve the reactive power problem.In this proposed combined algorithm (CA), the leads of parallel, collaborative and positive feedback of the ACO algorithm has been used to apply the global exploration in the current temperature. An adaptive modification threshold approach is used to progress the space exploration and balance the local exploitation. When the calculation process of the ACO algorithm falls into the inactivity, immediately SA algorithm is used to get a local optimal solution. Obtained finest solution of the ACO algorithm is considered as primary solution for SA algorithm, and then a fine exploration is executed in the neighborhood. Very importantly the probabilistic jumping property of the SA algorithm is used effectively to avoid solution falling into local optimum. The proposed combined algorithm (CA) approach has been tested in standard IEEE 30 bus test system and simulation results show obviously about the better performance of the proposed algorithm in reducing the real power loss with control variables within the limits.

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