scholarly journals Finding Solutions for Optimal Reactive Power Dispatch Problem by a Novel Improved Antlion Optimization Algorithm

Energies ◽  
2019 ◽  
Vol 12 (15) ◽  
pp. 2968 ◽  
Author(s):  
Zelan Li ◽  
Yijia Cao ◽  
Le Van Dai ◽  
Xiaoliang Yang ◽  
Thang Trung Nguyen
Keyword(s):  
Power Systems ◽  
Optimization Algorithm ◽  
Reactive Power ◽  
Optimization Problems ◽  
Optimal Solution ◽  
System Optimization ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Reactive Power Dispatch ◽  
Antlion Optimization

In this paper, a novel improved Antlion optimization algorithm (IALO) has been proposed for solving three different IEEE power systems of optimal reactive power dispatch (ORPD) problem. Such three power systems with a set of constraints in transmission power networks such as voltage limitation of all buses, limitations of tap of all transformers, maximum power transmission limitation of all conductors and limitations of all capacitor banks have given a big challenge for global optimal solution search ability of the proposed method. The proposed IALO method has been developed by modifying new solution generation technique of standard antlion optimization algorithm (ALO). By optimizing three single objective functions of systems with 30, 57 and 118 buses, the proposed method has been demonstrated to be more effective than ALO in terms of the most optimal solution search ability, solution search speed and search stabilization. In addition, the proposed method has also been compared to other existing methods and it has obtained better results than approximately all compared ones. Consequently, the proposed IALO method is deserving of a potential optimization tool for solving ORPD problem and other optimization problems in power system optimization fields.

A Novel Evolutionary Optimization Technique for Solving Optimal Reactive Power Dispatch Problems

2016 ◽  
pp. 244-275 ◽  
Author(s):  
Provas Kumar Roy
Keyword(s):  
Reactive Power ◽  
Optimization Problems ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Search Space ◽  
Continuous Space ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Local Optimal Solution ◽  
Reactive Power Dispatch

Biogeography based optimization (BBO) is an efficient and powerful stochastic search technique for solving optimization problems over continuous space. Due to excellent exploration and exploitation property, BBO has become a popular optimization technique to solve the complex multi-modal optimization problem. However, in some cases, the basic BBO algorithm shows slow convergence rate and may stick to local optimal solution. To overcome this, quasi-oppositional biogeography based-optimization (QOBBO) for optimal reactive power dispatch (ORPD) is presented in this study. In the proposed QOBBO algorithm, oppositional based learning (OBL) concept is integrated with BBO algorithm to improve the search space of the algorithm. For validation purpose, the results obtained by the proposed QOBBO approach are compared with those obtained by BBO and other algorithms available in the literature. The simulation results show that the proposed QOBBO approach outperforms the other listed algorithms.

scholarly journals Solving Single- and Multi-Objective Optimal Reactive Power Dispatch Problems Using an Improved Salp Swarm Algorithm

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1222
Author(s):  
Andrei M. Tudose ◽  
Irina I. Picioroaga ◽  
Dorian O. Sidea ◽  
Constantin Bulac
Keyword(s):  
Power Systems ◽  
Reactive Power ◽  
Optimization Problems ◽  
Salp Swarm Algorithm ◽  
Multi Objective ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Metaheuristic Methods ◽  
Reactive Power Dispatch ◽  
Swarm Algorithm

The optimal reactive power dispatch (ORPD) problem represents a fundamental concern in the efficient and reliable operation of power systems, based on the proper coordination of numerous devices. Therefore, the ORPD calculation is an elaborate nonlinear optimization problem that requires highly performing computational algorithms to identify the optimal solution. In this paper, the potential of metaheuristic methods is explored for solving complex optimization problems specific to power systems. In this regard, an improved salp swarm algorithm is proposed to solve the ORPD problem for the IEEE-14 and IEEE-30 bus systems, by approaching the reactive power planning as both a single- and a multi- objective problem and aiming at minimizing the real power losses and the bus voltage deviations. Multiple comparison studies are conducted based on the obtained results to assess the proposed approach performance with respect to other state-of-the-art techniques. In all cases, the results demonstrate the potential of the developed method and reflect its effectiveness in solving challenging problems.

scholarly journals Pareto-based allocations of multi-type flexible AC transmission system devices for optimal reactive power dispatch using Kinetic Gas Molecule Optimization algorithm

2020 ◽  
Vol 53 (1-2) ◽  
pp. 239-249 ◽  
Author(s):  
Pradeep Panthagani ◽  
R Srinivasa Rao
Keyword(s):  
Optimization Algorithm ◽  
Reactive Power ◽  
Transmission System ◽  
Flexible Ac Transmission ◽  
Flexible Ac Transmission System ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Gas Molecule ◽  
Reactive Power Dispatch ◽  
Ac Transmission

Optimal reactive power dispatch is one of the key factors to attain cost-effective and stable functioning of power system. It is a complicated non-linear optimization issue with a combination of discrete and continuous control variables. Due to this complex feature of optimal reactive power dispatch, optimization technique has become an efficient method to solve this problem. In this work, Kinetic Gas Molecule Optimization algorithm with Pareto optimality is proposed for solving multi-objective optimal reactive power dispatch problem. The presentation of Kinetic Gas Molecule Optimization is improved by computing inertia weight and acceleration coefficients dynamically rather than a fixed value. Because of this reason, the searching capability of the particles in each iteration is improved. However, to improve the power system performance in optimal reactive power dispatch scenario, additional flexible AC transmission system devices like static VAR compensator, thyristor-controlled series compensator, and unified power flow controller are introduced to provide stable results when compared to conventional output because flexible AC transmission system devices are capable of controlling the flow of real power and reactive power. These details are implemented and tested on IEEE 30-bus test system with various objectives. The performance of proposed method is validated from MATLAB, which shows the value of power loss as 4.3583 and voltage deviation as 0.26499 with cost of US$469.6417 per MVAR, which shows considerably superior results when compared with implemented particle swarm optimization results. The proposed method provides an efficient result for solving multi-objective optimal reactive power dispatch issues.

scholarly journals A Novel Constraint Handling Approach for the Optimal Reactive Power Dispatch Problem

2018 ◽  
Author(s):  
Walter M. Villa-Acevedo ◽  
Jesús M. López-Lezama ◽  
Jaime A. Valencia-Velásquez
Keyword(s):  
Genetic Algorithm ◽  
Power Systems ◽  
Reactive Power ◽  
Constraint Handling ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Power Loss Reduction ◽  
Reactive Power Dispatch ◽  
Metaheuristic Techniques ◽  
System Variables

This paper presents an alternative constraint handling approach within a specialized genetic algorithm (SGA) for the optimal reactive power dispatch (ORPD) problem. The ORPD is formulated as a nonlinear single-objective optimization problem aiming to minimize power losses while keeping network constraints. The proposed constraint handling approach is based on a product of sub-functions that represents permissible limits on system variables and that includes a specific goal on power loss reduction. The main advantage of this approach is the fact that it allows a straightforward verification of both feasibility and optimality. The SGA is examined and tested with the proposed constraint handling approach and the traditional penalization of deviations from feasible solutions. Several tests are run in the IEEE 30, 57, 118 and 300 bus test power systems. The results obtained with the proposed approach are compared to those offered by other metaheuristic techniques reported in the specialized literature. Simulation results indicate that the proposed genetic algorithm with the alternative constraint handling approach yields superior solutions when compared to other recently reported techniques.

New Efficient Evolutionary Algorithm Applied to Optimal Reactive Power Dispatch

2014 ◽  
pp. 321-339
Author(s):  
Provas Kumar Roy
Keyword(s):  
Large Scale ◽  
Reactive Power ◽  
Transmission Loss ◽  
Optimization Problems ◽  
Evolutionary Process ◽  
Opposition Based Learning ◽  
Optimal Reactive Power Dispatch ◽  
Power Dispatch ◽  
Equality And Inequality Constraints ◽  
Reactive Power Dispatch

Evolutionary Algorithms (EAs) are well-known optimization techniques to deal with nonlinear and complex optimization problems. However, most of these population-based algorithms are computationally expensive due to the slow nature of the evolutionary process. To overcome this drawback and to improve the convergence rate, this chapter employs Quasi-Opposition-Based Learning (QOBL) in conventional Biogeography-Based Optimization (BBO) technique. The proposed Quasi-Oppositional BBO (QOBBO) is comprehensively developed and successfully applied for solving the Optimal Reactive Power Dispatch (ORPD) problem by minimizing the transmission loss when both equality and inequality constraints are satisfied. The proposed QOBBO algorithm's performance is studied with comparisons of Canonical Genetic Algorithm (CGA), five versions of Particle Swarm Optimization (PSO), Local Search-Based Self-Adaptive Differential Evolution (L-SADE), Seeker Optimization Algorithm (SOA), and BBO on the IEEE 30-bus, IEEE 57-bus, and IEEE 118-bus power systems. The simulation results show that the proposed QOBBO approach performed better than the other listed algorithms and can be efficiently used to solve small-, medium-, and large-scale ORPD problems.

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