Reactive Power Compensation of the Distribution Power System with Distributed Generation Using Improved Tabu Search Algorithm

2013 ◽  
Vol 765-767 ◽  
pp. 2503-2508
Author(s):  
Xiang Lei ◽  
Yan Li ◽  
Shao Rong Wang ◽  
Hong Zhao ◽  
Fen Zhou ◽  
...  
Keyword(s):  
Tabu Search ◽  
Distributed Generation ◽  
Power Loss ◽  
Cost Allocation ◽  
Reactive Power ◽  
Search Algorithm ◽  
Test System ◽  
Local Optimum ◽  
Tabu Search Algorithm ◽  
Optimal Position

Taking account of the mutual impacts of distributed generation and reactive power, to determine the optimal position and capacity of the compensation device to be installed, the paper proposed an improved Tabu search algorithm for reactive power optimization. The voltage quality is considered of the model using minimum network active power loss as objective Function. It is achieved by maintaining the whole system power loss as minimum thereby reducing cost allocation. On the basis of general Tabu search algorithm, the algorithm used memory guidance search strategy to focus on searching for a local optimum value, avoid a global search blindness. To deal with the neighborhood solution set properly and save algorithm storage space , some corresponding improvements are made, thus, it is easily to stop the iteration of partial optimization and it is more probable to achieve the global optimization by use of the improved algorithm. Simulations are carried out on standard IEEE 33 test system and results are presented.

scholarly journals REDUCTION OF ACTIVE POWER LOSS BY IMPROVED TABU SEARCH ALGORITHM

2018 ◽  
Vol 6 (7) ◽  
pp. 1-9
Author(s):  
K. Lenin
Keyword(s):  
Tabu Search ◽  
Power Loss ◽  
Simulated Annealing Algorithm ◽  
Reactive Power ◽  
Search Algorithm ◽  
Active Power ◽  
Tabu Search Algorithm ◽  
Real Power ◽  
Annealing Algorithm ◽  
Power Problem

In this paper, an Improved Tabu Search (ITS) algorithm has been proposed to solve the optimal reactive power problem. In this work Tabu Search- has been hybridized with Simulated Annealing algorithm to solve the optimal reactive power problem. Hybridization of these two algorithms improves the exploration & exploitation capabilities during the search. Proposed Improved Tabu Search (ITS) algorithm has been tested in Standard IEEE 57,118 bus systems & real power loss has been comparatively reduced with voltage profiles are within the limits.

Application of Tabu Search for Optimal Placement and Sizing of Distributed Generation for Loss Reduction

2012 ◽  
Vol 433-440 ◽  
pp. 7190-7194 ◽  
Author(s):  
Nattachote Rugthaicharoencheep ◽  
Thong Lantharthong ◽  
Awiruth Ratreepruk ◽  
Jenwit Ratchatha
Keyword(s):  
Tabu Search ◽  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Power Flow ◽  
Search Algorithm ◽  
Optimal Placement ◽  
Loss Reduction ◽  
Placement Problem ◽  
Bus Voltage

This paper presents the optimal and sizing of distributed generation (DG) placement in a radial distribution system for loss reduction. The main emphasis of this paper is to identify proper locations for installing DGs in a distribution system to reduce active power loss and improve bus voltages. Nevertheless, proper placement and sizing of DG units are not straightforward to be identified as a number of their positions and capacities need to be determined. It is therefore proposed in this paper to solve a DG placement problem based on a Tabu search algorithm. The objective function of the problem is to minimize the system loss subject to power flow constraints, bus voltage limits, pre specified number of DGs, and their allowable total installed capacity, and only one distributed generator for one installation position. The effectiveness of the methodology is demonstrated by a practical sized distribution system consisting of 69 bus and 48 load points. The results show that the optimal DG placement and sizing can be identified to give the minimum power loss while respecting all the constraints.

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.

scholarly journals Power loss reduction by chaotic based predator-prey brain storm optimization algorithm

2020 ◽  
Vol 9 (3) ◽  
pp. 218
Author(s):  
Kanagasabai Lenin
Keyword(s):  
Power Loss ◽  
Reactive Power ◽  
Test System ◽  
Local Optimum ◽  
Loss Reduction ◽  
Optimal Parameters ◽  
Predator Prey ◽  
Brain Storm Optimization ◽  
Power Loss Reduction ◽  
Power Problem

<div data-canvas-width="34.43688268494255">In this paper chaotic predator-prey brain storm optimization (CPB) algorithm is proposed to solve optimal reactive power problem. In this work predator-prey brain storm optimization position cluster centers to perform as predators, consequently it will move towards better and better positions, while the remaining ideas perform as preys; hence get away from their adjacent predators. In the projected CPB algorithm chaotic theory has been applied in the modeling of the algorithm. In the proposed algorithm main properties of chaotic such as ergodicity and irregularity used to make the algorithm to jump out of the local optimum as well as to determine optimal parameters CPB algorithm has been tested in standard IEEE 57 bus test system and simulation results show the projected algorithm reduced the real power loss considerably.</div>

Application of Tabu-Genetic Algorithm in Reactive Power Optimization

2014 ◽  
Vol 1006-1007 ◽  
pp. 1021-1025
Author(s):  
Song Tao Zhang ◽  
Gong Bao Wang ◽  
Hui Bo Wang
Keyword(s):  
Genetic Algorithm ◽  
Tabu Search ◽  
Local Search ◽  
Reactive Power ◽  
Power Optimization ◽  
Search Algorithm ◽  
Tabu Search Algorithm ◽  
Reactive Power Optimization ◽  
Simple Genetic Algorithm ◽  
Better Than

By using tabu search algorithm which has strong local search ability as mutation operator of genetic algorithm, the tabu-genetic algorithm is designed for reactive power optimization in this paper, the strong global search ability of genetic algorithm and strong local search ability of tabu search algorithm is combined, the disadvantage of weak local search ability of genetic algorithm is conquered. Otherwise, the over limit of population is recorded and filtered, to ensure the final individual is under limit and effective. The tabu-genetic algorithm and simple genetic algorithm are used for simulation of IEEE 14-bus system 500 times, the results indicate that the performance of the tabu-genetic algorithm is much better than the simple genetic algorithm, its local search ability is improved obviously, and the active power loss is reduced more.

scholarly journals TRUE POWER LOSS REDUCTION BY HARMONY SEARCH ALGORITHM

2018 ◽  
Vol 6 (9) ◽  
pp. 196-205
Author(s):  
K. Lenin
Keyword(s):  
Power Loss ◽  
Reactive Power ◽  
Search Algorithm ◽  
Harmony Search ◽  
Population Based ◽  
Test System ◽  
Harmony Search Algorithm ◽  
Perfect State ◽  
Real Power ◽  
Power Loss Reduction

This paper presents Harmony Search algorithm (HS) for solving the reactive power problem.  Real power loss minimization is the major objective & also voltage profiles are should be kept within the limits.  This paper introduces a new search model the harmony search (HS) algorithm is a relatively new population-based metaheuristic optimization algorithm. It emulates the music improvisation progression where musicians improvise their instruments’ pitch by searching for a perfect state of harmony. In order to evaluate the efficiency of the proposed algorithm, it has been tested on practical 191 test system & real power loss has been considerably reduced.

scholarly journals REDUCTION OF ACTIVE POWER LOSS BY COYOTE SEARCH ALGORITHM

2018 ◽  
Vol 6 (10) ◽  
pp. 130-138
Author(s):  
K. Lenin
Keyword(s):  
Power Loss ◽  
Reactive Power ◽  
Search Algorithm ◽  
Special Property ◽  
Test System ◽  
Active Power ◽  
Real Power ◽  
Simulation Results ◽  
Searching Ability ◽  
Power Problem

This paper presents Coyote Search Algorithm (CSA) for solving optimal reactive power problem. Coyote Search Algorithm is a new bio – inspired heuristic algorithm which based on coyote preying behaviour. The way coyote search for food and survive by avoiding their enemies has been imitated to formulate the algorithm for solving the reactive power problem. And the specialty of coyote is possessing both individual local searching ability & autonomous flocking movement and this special property has been utilized to formulate the search algorithm. The proposed Coyote Search Algorithm (CSA) has been tested on standard IEEE 57 bus test system and simulation results shows clearly about the good performance of the proposed algorithm in reducing the real power loss.

scholarly journals Multi-Objective Tabu Search for the Location and Sizing of Multiple Types of FACTS and DG in Electrical Networks

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2722 ◽  
Author(s):  
Othón Aram Coronado de Koster ◽  
José Antonio Domínguez-Navarro
Keyword(s):  
Tabu Search ◽  
Distributed Generation ◽  
Power Loss ◽  
Search Algorithm ◽  
Economic Benefits ◽  
Flexible Ac Transmission Systems ◽  
Transmission Systems ◽  
Multi Objective ◽  
Flexible Ac Transmission ◽  
Ac Transmission

Flexible AC transmission systems and distributed generation units in power systems provide several benefits such as voltage stability, power loss minimization, thermal limits enhancement, or enables power system management close to the limit operation points; and by extension, economic benefits such as power fuel cost and power loss cost minimization. This work presents a multi-objective optimization algorithm to determine the location and size of hybrid solutions based on a combination of Flexible AC transmission systems devices and distributed generation. Further, the work expands the types of FACTS usually considered. The problem is solved by means of a Tabu search algorithm with good results when tested in a network of 300 nodes.

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