scholarly journals EWOA-OPF: Effective Whale Optimization Algorithm to Solve Optimal Power Flow Problem

Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 2975
Author(s):  
Mohammad H. Nadimi-Shahraki ◽  
Shokooh Taghian ◽  
Seyedali Mirjalili ◽  
Laith Abualigah ◽  
Mohamed Abd Abd Elaziz ◽  
...  
Keyword(s):  
Power System ◽  
Optimization Algorithm ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Optimization Problems ◽  
Whale Optimization Algorithm ◽  
Objective Functions ◽  
Multi Objective ◽  
Optimal Power ◽  
Whale Optimization

The optimal power flow (OPF) is a vital tool for optimizing the control parameters of a power system by considering the desired objective functions subject to system constraints. Metaheuristic algorithms have been proven to be well-suited for solving complex optimization problems. The whale optimization algorithm (WOA) is one of the well-regarded metaheuristics that is widely used to solve different optimization problems. Despite the use of WOA in different fields of application as OPF, its effectiveness is decreased as the dimension size of the test system is increased. Therefore, in this paper, an effective whale optimization algorithm for solving optimal power flow problems (EWOA-OPF) is proposed. The main goal of this enhancement is to improve the exploration ability and maintain a proper balance between the exploration and exploitation of the canonical WOA. In the proposed algorithm, the movement strategy of whales is enhanced by introducing two new movement strategies: (1) encircling the prey using Levy motion and (2) searching for prey using Brownian motion that cooperate with canonical bubble-net attacking. To validate the proposed EWOA-OPF algorithm, a comparison among six well-known optimization algorithms is established to solve the OPF problem. All algorithms are used to optimize single- and multi-objective functions of the OPF under the system constraints. Standard IEEE 6-bus, IEEE 14-bus, IEEE 30-bus, and IEEE 118-bus test systems are used to evaluate the proposed EWOA-OPF and comparative algorithms for solving the OPF problem in diverse power system scale sizes. The comparison of results proves that the EWOA-OPF is able to solve single- and multi-objective OPF problems with better solutions than other comparative algorithms.

scholarly journals A Harris Hawks Optimization Based Single- and Multi-Objective Optimal Power Flow Considering Environmental Emission

2020 ◽  
Vol 12 (13) ◽  
pp. 5248 ◽  
Author(s):  
Mohammad Zohrul Islam ◽  
Noor Izzri Abdul Wahab ◽  
Veerapandiyan Veerasamy ◽  
Hashim Hizam ◽  
Nashiren Farzilah Mailah ◽  
...  
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Fitness Function ◽  
Renewable Energy Sources ◽  
Weighted Sums ◽  
Objective Functions ◽  
Power System Control ◽  
Multi Objective ◽  
Optimal Power ◽  
Whale Optimization

The electric sector is majorly concerned about the greenhouse and non-greenhouse gas emissions generated from both conventional and renewable energy sources, as this is becoming a major issue globally. Thus, the utilities must adhere to certain environmental guidelines for sustainable power generation. Therefore, this paper presents a novel nature-inspired and population-based Harris Hawks Optimization (HHO) methodology for controlling the emissions from thermal generating sources by solving single and multi-objective Optimal Power Flow (OPF) problems. The OPF is a non-linear, non-convex, constrained optimization problem that primarily aims to minimize the fitness function by satisfying the equality and inequality constraints of the system. The cooperative behavior and dynamic chasing patterns of hawks to pounce on escaping prey is modeled mathematically to minimize the objective function. In this paper, fuel cost, real power loss and environment emissions are regarded as single and multi-objective functions for optimal adjustments of power system control variables. The different conflicting framed multi-objective functions have been solved using weighted sums using a no-preference method. The presented method is coded using MATLAB software and an IEEE (Institute of Electrical and Electronics Engineers) 30-bus. The system was used to demonstrate the effectiveness of selective objectives. The obtained results are compared with the other Artificial Intelligence (AI) techniques such as the Whale Optimization Algorithm (WOA), the Salp Swarm Algorithm (SSA), Moth Flame (MF) and Glow Warm Optimization (GWO). Additionally, the study on placement of Distributed Generation (DG) reveals that the system losses and emissions are reduced by an amount of 9.8355% and 26.2%, respectively.

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.

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