scholarly journals Optimal sizing and sitting of electric vehicle charging station by using archimedes optimization algorithm technique

2021 ◽  
Vol 12 (4) ◽  
pp. 2557
Author(s):  
Mohamed Abdelhamed Zaki ◽  
Tarek Mahmoud ◽  
Mohamed Atia ◽  
EL Said Abd El Aziz Osman
Keyword(s):  
Optimization Algorithm ◽  
Power Loss ◽  
Low Voltage ◽  
Search Algorithm ◽  
Reducing Power ◽  
Cuckoo Search ◽  
Electricity Sector ◽  
Voltage Profile ◽  
Real Power ◽  
Optimal Sizing

<p><span lang="EN-US">Increasing penetration of EV load into the electricity sector will result in generation imbalance, an increase in real power loss, a low voltage profile and consequently a decrease in the margin of stability of voltage. It is necessary for the coordination of charging stations (CSs) for EV at the relevant locations to minimize the effect of increased EV load penetration in radial systems. In this paper, a new optimization method named Archimedes optimization algorithm (AOA) is proposed; it determined the optimal location and size for EV-CS for reducing power losses and improved voltage profile. In this work we used the photo voltaic (PV) renewable source as a main feeder for the CSs. Many of Artificial Intelligence technique are applied to determine the optimal sizing and sitting of EV-CSs considering the objective of minimization of real power loss. IEEE 33-bus testing network conducts simulation tests. The results highlighted the need to refine the EV-CS allocation to improve the performance. The ability to solve complex, non-linear objective optimization issues using AOA and to compare the results with other algorithms, namely particle swarm optimization (PSO), Cuckoo search algorithm (CSA), shows its effectiveness in minimizing the power loss as required.</span></p>

Real Power Loss Reduction by Cinnamon ibon Search Optimization Algorithm

2021 ◽  
Author(s):  
Lenin Kanagasabai
Keyword(s):  
Optimization Algorithm ◽  
Power Loss ◽  
Search Algorithm ◽  
Loss Reduction ◽  
Real Power ◽  
Search Optimization ◽  
Power Loss Reduction ◽  
Voltage Stability Enhancement ◽  
Voltage Deviation ◽  
Stability Enhancement

In this paper Cinnamon ibon Search Optimization Algorithm (CSOA) is used for solving the power loss lessening problem. Key objectives of the paper are Real power Loss reduction, Voltage stability enhancement and minimization of Voltage deviation. Searching and scavenging behavior of Cinnamon ibon has been imitated to model the algorithm. Cinnamon ibon birds which are in supremacy of the group are trustworthy to be hunted by predators and dependably attempt to achieve a improved position and the Cinnamon ibon ones that are positioned in the inner of the population, drive adjacent to the nearer populations to dodge the threat of being confronted. The systematic model of the Cinnamon ibon search Algorithm originates with an arbitrary individual of Cinnamon ibon. The Cinnamon ibon search algorithm entities show the position of the Cinnamon ibon. Besides, the Cinnamon ibon bird is supple in using the cooperating plans and it alternates between the fabricator and the cadger. Successively the Cinnamon ibon identifies the predator position; then they charm the others by tweeting signs. The cadgers would be focussed to the imperilled regions by fabricators once the fear cost is more than the defence threshold. Likewise, the subterfuge of both the cadger and the fabricator is commonly used by Cinnamon ibon. The dispersion of the Cinnamon ibon location in the solution area is capricious. An impulsive drive approach was applied when dispossession of any adjacent Cinnamon ibon in the purlieu of the present population. This style diminishes the convergence tendency and decreases the convergence inexorableness grounded on the controlled sum of iterations. Authenticity of the Cinnamon ibon Search Optimization Algorithm (CSOA) is corroborated in IEEE 30 bus system (with and devoid of L-index). Genuine power loss lessening is attained. Proportion of actual power loss lessening is amplified.

scholarly journals Enhancing active radial distribution networks by optimal sizing and placement of DGs using modified crow search algorithm

2019 ◽  
Vol 16 (3) ◽  
pp. 1179 ◽  
Author(s):  
Mohamed Abdelbadea ◽  
Tarek A. Boghdady ◽  
Doaa Khalil Ibrahim
Keyword(s):  
Radial Distribution ◽  
Distribution System ◽  
Power Loss ◽  
Search Algorithm ◽  
Reducing Power ◽  
Distribution Networks ◽  
Voltage Profile ◽  
Network Efficiency ◽  
Weighted Sum Method ◽  
Radial Distribution Networks

<p>Incorporating many Distributed Generators (DGs) technologies in power system networks has grown rapidly in recent years. Distributed generation (DG) plays a key role in reducing power loss and enhancing the voltage profile in radial distribution networks. However, inappropriate DGs site or size may cut network efficiency; moreover, injecting harmonics is one of the integration concerns of inverter-based DGs. Two-procedure based approach is introduced in this paper. The first procedure solves the DGs siting and sizing problem, as a multi-objective one by improving the voltage profile of the whole distribution network and also reducing its power loss. A weighted sum method is presented to create the Pareto optimal front in this procedure and get the compromised solution by applying a novel metaheuristic optimizer, named Crow Search Algorithm (CSA). A modification on CSA is also proposed and applied to improve its performance. The achieved solution for inverter-based DGs placement and size is checked in the second procedure to make sure the accepted voltage THD at all buses by implementing detailed simulation for the tested system using Matlab/Simulink. The proposed approach has been tested on IEEE 33-bus radial distribution system with photovoltaic DGs. To confirm the superiority of the modified CSA algorithm in terms of quality of solution, its achieved results are compared with the results offered by the original CSA algorithm and published results of some other nature-inspired algorithms.</p>

scholarly journals Integrated Algorithm for Decreasing Active Power Loss

2018 ◽  
Vol 7 (1) ◽  
pp. 33
Author(s):  
Lenin Kanagasabai
Keyword(s):  
Power Loss ◽  
Firefly Algorithm ◽  
Reactive Power ◽  
Cuckoo Search ◽  
Active Power ◽  
Voltage Profile ◽  
Swarm Optimization ◽  
Real Power ◽  
Simulation Results ◽  
Power Problem

This paper projects an Integrated Algorithm (IA) for solving optimal reactive power problem. Quick convergence of the Cuckoo Search (CS), the vibrant root change of the Firefly Algorithm (FA), and the incessant position modernization of the Particle Swarm Optimization (PSO) has been combined to form the Integrated Algorithm (IA).  In order to evaluate the efficiency of the proposed Integrated Algorithm (IA), it has been tested in standard IEEE 57,118 bus systems and compared to other standard reported algorithms. Simulation results show that Integrated Algorithm (IA) is considerably reduced the real power loss and voltage profile within the limits.

scholarly journals A Hybrid Ant Colony and Cuckoo Search Algorithm for Route Optimization of Heating Engineering

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2675 ◽  
Author(s):  
Yang Zhang ◽  
Huihui Zhao ◽  
Yuming Cao ◽  
Qinhuo Liu ◽  
Zhanfeng Shen ◽  
...  
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Search Algorithm ◽  
Fitness Function ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Elapsed Time ◽  
Route Design

The development of remote sensing and intelligent algorithms create an opportunity to include ad hoc technology in the heating route design area. In this paper, classification maps and heating route planning regulations are introduced to create the fitness function. Modifications of ant colony optimization and the cuckoo search algorithm, as well as a hybridization of the two algorithms, are proposed to solve the specific Zhuozhou–Fangshan heating route design. Compared to the fitness function value of the manual route (234.300), the best route selected by modified ant colony optimization (ACO) was 232.343, and the elapsed time for one solution was approximately 1.93 ms. Meanwhile, the best route selected by modified Cuckoo Search (CS) was 244.247, and the elapsed time for one solution was approximately 0.794 ms. The modified ant colony optimization algorithm can find the route with smaller fitness function value, while the modified cuckoo search algorithm can find the route overlapped to the manual selected route better. The modified cuckoo search algorithm runs more quickly but easily sticks into the premature convergence. Additionally, the best route selected by the hybrid ant colony and cuckoo search algorithm is the same as the modified ant colony optimization algorithm (232.343), but with higher efficiency and better stability.

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.

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