scholarly journals Review on population-based metaheuristic search techniques for optimal power flow

2019 ◽  
Vol 15 (1) ◽  
pp. 373
Author(s):  
Muhammad Affiq Abd Rahman ◽  
Bazilah Ismail ◽  
Kanendra Naidu ◽  
Mohd Khairil Rahmat
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Pso Algorithm ◽  
Optimization Techniques ◽  
System Operation ◽  
Linear Solution ◽  
Search Techniques ◽  
Optimal Power ◽  
Metaheuristic Search ◽  
Non Linear

<span>Optimal power flow (OPF) is a non-linear solution which is significantly important in order to analyze the power system operation. The use of optimization algorithm is essential in order to solve OPF problems. <br /> The emergence of machine learning presents further techniques which capable to solve the non-linear problem. The performance and the key aspects which enhances the effectiveness of these optimization techniques are compared within several metaheuristic search techniques. This includes the operation of particle swarm optimization (PSO) algorithm, firefly algorithm (FA), artificial bee colony (ABC) algorithm, ant colony optimization (ACO) algorithm and differential evolution (DE) algorithm. This paper reviews on the key elements that need to be considered when selecting metaheuristic techniques to solve OPF problem in power <br /> system operation.</span>

scholarly journals A Multi-Objective Optimal Power Flow Control of Electrical Transmission Networks Using Intelligent Meta-Heuristic Optimization Techniques

2021 ◽  
Vol 13 (9) ◽  
pp. 4979
Author(s):  
Hatem Diab ◽  
Mahmoud Abdelsalam ◽  
Alaa Abdelbary
Keyword(s):  
Power Systems ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Pso Algorithm ◽  
Optimization Techniques ◽  
Operating Conditions ◽  
Control Technique ◽  
Heuristic Optimization ◽  
Multi Objective ◽  
Optimal Power

Optimal power flow (OPF) is considered one of the most critical challenges that can substantially impact the sustainable performance of power systems. Solving the OPF problem reduces three essential items: operation costs, transmission losses, and voltage drops. An intelligent controller is needed to adjust the power system’s control parameters to solve this problem optimally. However, many constraints must be considered that make the design process of the OPF algorithm exceedingly tricky due to the increased number of limitations and control variables. This paper proposes a multi-objective intelligent control technique based on three different meta-heuristic optimization algorithms: multi-verse optimization (MVO), grasshopper optimization (GOA), and Harris hawks optimization (HHO) to solve the OPF problem. The proposed control techniques were validated by applying them to the IEEE-30 bus system under different operating conditions through MATLAB simulations. The proposed techniques were then compared with the particle swarm optimization (PSO) algorithm, which is very popular in the literature studying how to solving the OPF problem. The obtained results show that the proposed methods are more effective in solving the OPF problem when compared to the commonly used PSO algorithm. The proposed HHO, in particular, shows that it can form a reliable candidate in solving power systems’ optimization problems.

Optimal Power Flow Problem Solution Based on Hybrid Firefly Krill Herd Method

2019 ◽  
Vol 44 ◽  
pp. 213-228 ◽  
Author(s):  
Aboubakr Khelifi ◽  
Bachir Bentouati ◽  
Saliha Chettih
Keyword(s):  
Light Intensity ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Optimization Problems ◽  
Test System ◽  
Optimization Techniques ◽  
System Control ◽  
Problem Solution ◽  
Optimal Power ◽  
Krill Herd

Optimal Power Flow (OPF) problem is one of the most important and widely studied nonlinear optimization problems in power system operation. This study presents the implementation of a new technology based on the hybrid Firefly and krill herd method (FKH), which has been provided and used for OPF problems in power systems. In FKH, an improved formulation of the attractiveness and adjustment of light intensity operator initially employed in FA, named attractiveness and light intensity the update operator (ALIU), is inserted into the KH approach as a local search perform. The FKH is prove with the solving of the OPF problem for various types of single-objective and multi-objective functions such as generation cost, reduced emission, active power losses and voltage deviation which are optimized simultaneously on exam system, viz the IEEE-30 Bus test system, which is used to test and confirm the efficiency of the proposed FKH technique. By comparing with several optimization techniques, the results produced by using the recommended FKH technique are provided in detail. The results obtained in this study appear that the FKH technique can be efficiency used to solve the non-linear and non-convex problems and high performance compared with other optimization methods in the literature. This study can achieve a minimum objective by finding the optimum setting for system control variables.

scholarly journals OPTIMAL POWER FLOW WITH TCSC DEVICE USING CUCKOO OPTIMIZATION ALGORITHM

2018 ◽  
Vol 54 (3A) ◽  
pp. 52
Author(s):  
Duong Thanh Long
Keyword(s):  
Power System ◽  
Optimization Algorithm ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Power Transmission ◽  
Optimization Techniques ◽  
Operating Conditions ◽  
Cuckoo Optimization Algorithm ◽  
Facts Devices ◽  
Optimal Power

Optimal Power Flow (OPF) problem is an optimization tool through which secure and economic operating conditions of power system is obtained. In recent years, Flexible AC Transmission System (FACTS) devices, have led to the development of controllers that provide controllability and flexibility for power transmission. Series FACTS devices such as Thyristor controlled series compensators (TCSC), with its ability to directly control the power flow can be very effective to power system security. Thus, integration TCSC in the OPF is one of important current problems and is a suitable method for better utilization of the existing system. This paper is applied Cuckoo Optimization Algorithm (COA) for the solution of the OPF problem of power system equipped with TCSC. The proposed approach has been examined and tested on the IEEE 30-bus system. The results presented in this paper demonstrate the potential of COA algorithm and show its effectiveness for solving the OPF problem with TCSC devices over the other evolutionary optimization techniques.

scholarly journals Computational Analysis of Different Artificial Intelligence Based Optimization Techniques for Optimal Power Flow and Economic Load Dispatch Problem

2013 ◽  
Vol 4 (1) ◽  
pp. 82-87
Author(s):  
Netra M Lokhande ◽  
Debirupa Hore
Keyword(s):  
Artificial Intelligence ◽  
Power Systems ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Computational Analysis ◽  
Transmission Loss ◽  
Optimization Techniques ◽  
Bacterial Foraging Optimization ◽  
Economic Market ◽  
Optimal Power

The purpose of this paper is to present a computational Analysis of various Artificial Intelligence based optimization Techniques used to solve OPF problems. The various Artificial Intelligence methods such as Genetic Algorithm(GA), Particle Swarm Optimization(PSO), Bacterial Foraging Optimization(BFO), ANN are studied and analyzed in detail. The objective of an Optimal Power Flow (OPF) algorithm is to find steady state operation point which minimizes generation cost and transmission loss etc. or maximizes social welfare, load ability etc. while maintaining an acceptable system performance in terms of limits on generators’ real and reactive powers, power flow limits, output of various compensating devices etc. Traditionally, Classical optimization methods were used effectively to solve optimal power flow. But, recently due to the incorporation of FACTS devices and deregulation of power sector the traditional concepts and practices of power systems are superimposed by an economic market management and hence OPF have become more complex. So, in recent years, Artificial Intelligence (AI) methods have been emerged which can solve highly complex OPF problems at faster rate.

A Probabilistic Optimal Power Flow in Wind-Thermal Coordination Considering Intermittency of the Wind

2021 ◽  
Vol 10 (1) ◽  
pp. 82-110
Author(s):  
Sriparna Banerjee ◽  
Dhiman Banerjee ◽  
Provas Kumar Roy ◽  
Pradip Kumar Saha ◽  
Goutam Kumar Panda
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Optimization Techniques ◽  
Wind Energy Conversion ◽  
Optimal Power ◽  
Generation Cost ◽  
Bus Voltage ◽  
Doubly Fed ◽  
Probabilistic Nature

This article specifically aims to prove the superiority of the proposed moth swarm algorithm (MSA) in view of wind-thermal coordination. In the present article, a probabilistic optimal power flow (POPF) problem is formulated to reflect the probabilistic nature of wind. Modelling of doubly fed induction generator (DFIG) is included in the proposed POPF to represent the wind energy conversion system (WECS). To reduce DFIG imposed deviation of bus voltage ancillary reactive power support is considered. Moreover, three different optimization techniques, namely, MSA, biogeography-based optimization (BBO), and particle swarm optimization (PSO) are independently applied for the minimization of active power generation cost for wind-thermal coordination, considering different instances in case of IEEE 30-bus and IEEE 118-bus system. From the simulation results, it is confirmed and validated that the proposed MSA performs considerably better than BBO and PSO.

A unified optimal power flow modeling for VSC-HVDC converter: a novel methodology for optimal installation based on average loadability index

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sunilkumar Agrawal ◽  
Prasanta Kundu
Keyword(s):  
Objective Function ◽  
Direct Current ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Pso Algorithm ◽  
Transmission Network ◽  
Content Type ◽  
Hvdc Transmission ◽  
Optimal Power ◽  
The Impact

Purpose This paper aims to propose a novel methodology for optimal voltage source converter (VSC) station installation in hybrid alternating current (AC)/direct current (DC) transmission networks. Design/methodology/approach In this analysis, a unified power flow model has been developed for the optimal power flow (OPF) problem for VSC-based high voltage direct current (VSC-HVDC) transmission network and solved using a particle swarm optimization (PSO) algorithm. The impact of the HVDC converter under abnormal conditions considering N-1 line outage contingency is analyzed against the congestion relief of the overall transmission network. The average loadability index is used as a severity indicator and minimized along with overall transmission line losses by replacing each AC line with an HVDC line independently. Findings The developed unified OPF (UOPF) model converged successfully with (PSO) algorithm. The OPF problem has satisfied the defined operational constraints of the power system, and comparative results are obtained for objective function with different HVDC test configurations represented in the paper. In addition, the impact of VSC converter location is determined on objective function value. Originality/value A novel methodology has been developed for the optimal installation of the converter station for the point-to-point configuration of HVDC transmission. The developed unified OPF model and methodology for selecting the AC bus for converter installation has effectively reduced congestion in transmission lines under single line outage contingency.

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