scholarly journals Optimal Power Flow Using Flower Pollination Algorithm: A Case Study of 500 kV Java-Bali Power System

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Fredi Prima Sakti ◽  
Sarjiya Sarjiya ◽  
Sasongko Pramono Hadi
Keyword(s):  
Power System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Optimization Problems ◽  
Flower Pollination Algorithm ◽  
Flower Pollination ◽  
Optimal Power ◽  
Metaheuristic Methods ◽  
Owned Company

Flower Pollination Algorithm (FPA) is one of metaheuristic methods that is widely used in optimization problems. This method was inspired by the nature of flower pollination. In this research, FPA is applied to solve Optimal Power Flow (OPF) problems with case study of 500 kV Java-Bali power system in Indonesia. The system consists of 25 bus with 30 lines and 8 generating units. Control variables are generation of active power and voltage magnitude at PV bus and swing bus under several power system constraints. The results show that FPA method is capable of solving OPF problem. This method decreased the generator fuel cost of PT. PLN (Persero), the state-owned company in charge of providing electricity in Indonesia, up to 13.15%.

An Optimizer-Tool-Based Improved Metaheuristic Method for Solving Security Optimal Power Flow

2018 ◽  
pp. 191-226
Author(s):  
Belkacem Mahdad
Keyword(s):  
Power System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Power System Planning ◽  
System Planning ◽  
Planning And Control ◽  
Optimal Power ◽  
Interactive Tool ◽  
Metaheuristic Methods ◽  
And Control

In this chapter, an interactive tool using graphic user interface (GUI) environment-based MATLAB is proposed to solve practical optimal power system planning and control. The main particularity of the proposed tool is to assist student and researchers understanding the mechanism search of new metaheuristic methods. The proposed tool allows users to interact dynamically with the program. The users (students or experts) can set parameters related to a specified metaheuristic method to clearly observe the effect of choosing parameters on the solution quality. In this chapter, a new global optimization method named grey wolf optimizer (GWO) and pattern search algorithm (PS) have been successfully applied within the interactive tool to solve the optimal power flow problem. The robustness of the two proposed metaheuristic methods is validated on many standard power system tests. The proposed interactive optimal power flow tool is expected to be a useful support for students and experts specialized in power system planning and control.

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.

Optimal Power Flow using the Moth Flam Optimizer: A Case Study of the Algerian Power System

2016 ◽  
Vol 1 (3) ◽  
pp. 431 ◽  
Author(s):  
Bachir Bentouati ◽  
Lakhdar Chaib ◽  
Saliha Chettih
Keyword(s):  
Power System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Inequality Constraints ◽  
Interconnected Power System ◽  
Bee Colony ◽  
Optimal Power ◽  
Equality And Inequality Constraints ◽  
A New Technique

<p>In this paper, a new technique of optimization known as Moth-Flam Optimizer (MFO) has been proposed to solve the problem of the Optimal Power Flow (OPF) in the interconnected power system, taking into account the set of equality and inequality constraints. The proposed algorithm has been presented to the Algerian power system network for a variety of objectives. The obtained results are compared with recently published algorithms such as; as the Artificial Bee Colony (ABC), and other meta-heuristics. Simulation results clearly reveal the effectiveness and the robustness of the proposed algorithm for solving the OPF problem. </p>

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