scholarly journals Artificial Electric Field Algorithm for Optimal Power Flow Aiming Cost and Loss Minimization

2019 ◽  
Vol 8 (4S2) ◽  
pp. 400-402
Keyword(s):  
Electric Field ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Problem Formulation ◽  
Test System ◽  
Power Network ◽  
Power Losses ◽  
Loss Minimization ◽  
Optimal Power ◽  
Generation Cost

Optimal Power Flow (OPF) is a vital concern in a Electric power Network. Because of the intricacy and incoherence of strictures, the conventional formulations are not suitable to solve the problem. Hence, this study aims to resolve OPF problem consisting the objectives, by reducing the generation cost and Minimizing the Transmission power losses. So, the incessant and intermittent variables take part in the problem formulation. Artificial Electric Field Algorithm (AEFA) have been suggested to resolve the OPF problem. The simulations have been performed on IEEE -30-bus test system. The outcomes have been matched with other algorithms to exemplify the efficiency and heftiness of AEFA.

Optimal Power Flow Based Economic Generation Scheduling in Day-ahead Power Market

2017 ◽  
Vol 6 (3) ◽  
pp. 124
Author(s):  
Kshitij Choudhary ◽  
Rahul Kumar ◽  
Dheeresh Upadhyay ◽  
Brijesh Singh
Keyword(s):  
Power System ◽  
Electricity Market ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Congestion Management ◽  
Test Results ◽  
Loss Minimization ◽  
Optimal Power ◽  
Generation Scheduling ◽  
Generation Cost

The present work deals with the economic rescheduling of the generation in an hour-ahead electricity market. The schedules of various generators in a power system have been optimizing according to active power demand bids by various load buses. In this work, various aspects of power system such as congestion management, voltage stabilization and loss minimization have also taken into consideration for the achievement of the goal. The interior point (IP) based optimal power flow (OPF) methodology has been used to obtain the optimal generation schedule for economic system operation. The IP based OPF methodology has been tested on a modified IEEE-30 bus system. The obtained test results shows that not only the generation cost is reduced also the performance of power system has been improved using proposed methodology.

A Solution to Multi Objective Optimal Power Flow Using Hybrid Cultural-Based Differential Evolution

2013 ◽  
Vol 457-458 ◽  
pp. 1236-1240
Author(s):  
Isaree Srikun ◽  
Lakkana Ruekkasaem ◽  
Pasura Aungkulanon
Keyword(s):  
Differential Evolution ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Test System ◽  
System Operation ◽  
Power System Operation ◽  
Multi Objective ◽  
Optimal Power ◽  
Generation Cost ◽  
And Control

This paper presents a hybrid Cultural-based Differential Evolution for solving a multi-objective Optimal Power Flow (OPF) in support of power system operation and control . The multi-objective OPF was formulated for tackling with total generation cost and environmental impacts simultaneously. The proposed method was applied to the standard IEEE 30-bus test system. The results show that solving the multi-objective OPF problem by the Cultural-based Differential Evolution is more effective than other swarm intelligence methods in the literature.

scholarly journals An Optimization-Based Strategy for Solving Optimal Power Flow Problems in a Power System Integrated with Stochastic Solar and Wind Power Energy

2021 ◽  
Vol 11 (15) ◽  
pp. 6883
Author(s):  
Muhammad Riaz ◽  
Aamir Hanif ◽  
Shaik Javeed Hussain ◽  
Muhammad Irfan Memon ◽  
Muhammad Umair Ali ◽  
...  
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Optimal Solution ◽  
Test System ◽  
Distribution Functions ◽  
Control Variables ◽  
Real Power ◽  
Solution Approach ◽  
Optimal Power ◽  
Generation Cost

In an effort to reduce greenhouse gas emissions, experts are looking to substitute fossil fuel energy with renewable energy for environmentally sustainable and emission free societies. This paper presents the hybridization of particle swarm optimization (PSO) with grey wolf optimization (GWO), namely a hybrid PSO-GWO algorithm for the solution of optimal power flow (OPF) problems integrated with stochastic solar photovoltaics (SPV) and wind turbines (WT) to enhance global search capabilities towards an optimal solution. A solution approach is used in which SPV and WT output powers are estimated using lognormal and Weibull probability distribution functions respectively, after simulation of 8000 Monte Carlo scenarios. The control variables include the forecast real power generation of SPV and WT, real power of thermal generators except slack-bus, and voltages of all voltage generation buses. The total generation cost of the system is considered the main objective function to be optimized, including the penalty and reserve cost for underestimation and overestimation of SPV and WT, respectively. The proposed solution approach for OPF problems is verified on the modified IEEE 30 bus test system. The performance and robustness of the proposed hybrid PSO-GWO algorithm in solving the OPF problem is assessed by comparing the results with five other metaheuristic optimization algorithms for the same test system, under the same control variables and system constraints. Simulation results confirm that the hybrid PSO-GWO algorithm performs well compared to other algorithms and shows that it can be an efficient choice for the solution of OPF problems.

scholarly journals An approach to solve OPF problems using a novel hybrid whale and sine cosine optimization algorithm

2021 ◽  
pp. 1-11
Author(s):  
Ramesh Devarapalli ◽  
B. Venkateswara Rao ◽  
Bishwajit Dey ◽  
K. Vinod Kumar ◽  
H. Malik ◽  
...  
Keyword(s):  
Optimization Algorithm ◽  
System Performance ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Optimization Techniques ◽  
Power Losses ◽  
Optimal Power ◽  
Generation Cost ◽  
Voltage Deviation ◽  
Power System Performance

Nowadays, improvement in power system performance is essential to obtaine economic and technical benifits. To achieve this, optimize the large number of parameters in the system based on optimal power flow(OPF). For solving OPF problem efficiently, it needs robust and fast optimization techniques. This paper proposes the application of a newly developed hybrid Whale and Sine Cosine optimization algorithm to solve the OPF. It has been implemented for optimization of the control variables. The reduction of true power generation cost, emission, true power losses, and voltage deviation are considered as different objectives. The hybrid Whale and Sine Cosine optimization is validated by solving OPF problem with various intentions using IEEE30 bus system. To varidate the proposed technique, the results obtained from this are compared with other methods in the literature. The robustness achieved with the proposed algorithm has been analyzed for the considered OPF problem using statistical analysis and whisker plots.

scholarly journals An Optimal Power Flow Solution of a System Integrated with Renewable Sources Using a Hybrid Optimizer

2021 ◽  
Vol 13 (23) ◽  
pp. 13382
Author(s):  
Muhammad Riaz ◽  
Aamir Hanif ◽  
Haris Masood ◽  
Muhammad Attique Khan ◽  
Kamran Afaq ◽  
...  
Keyword(s):  
Power System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Fossil Fuel ◽  
Renewable Energy Sources ◽  
Test System ◽  
Total System ◽  
Flow Solution ◽  
Optimal Power ◽  
Generation Cost

A solution to reduce the emission and generation cost of conventional fossil-fuel-based power generators is to integrate renewable energy sources into the electrical power system. This paper outlines an efficient hybrid particle swarm gray wolf optimizer (HPS-GWO)-based optimal power flow solution for a system combining solar photovoltaic (SPV) and wind energy (WE) sources with conventional fuel-based thermal generators (TGs). The output power of SPV and WE sources was forecasted using lognormal and Weibull probability density functions (PDFs), respectively. The two conventional fossil-fuel-based TGs are replaced with WE and SPV sources in the existing IEEE-30 bus system, and total generation cost, emission and power losses are considered the three main objective functions for optimization of the optimal power flow problem in each scenario. A carbon tax is imposed on the emission from fossil-fuel-based TGs, which results in a reduction in the emission from TGs. The results were verified on the modified test system that consists of SPV and WE sources. The simulation results confirm the validity and effectiveness of the suggested model and proposed hybrid optimizer. The results confirm the exploitation and exploration capability of the HPS-GWO algorithm. The results achieved from the modified system demonstrate that the use of SPV and WE sources in combination with fossil-fuel-based TGs reduces the total system generation cost and greenhouse emissions of the entire power system.

Optimal Power Flow Based Economic Generation Scheduling in Day-ahead Power Market

2017 ◽  
Vol 6 (3) ◽  
pp. 123
Author(s):  
Kshitij Choudhary ◽  
Rahul Kumar ◽  
Dheeresh Upadhyay ◽  
Brijesh Singh
Keyword(s):  
Power System ◽  
Electricity Market ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Congestion Management ◽  
Test Results ◽  
Loss Minimization ◽  
Optimal Power ◽  
Generation Scheduling ◽  
Generation Cost

The present work deals with the economic rescheduling of the generation in an hour-ahead electricity market. The schedules of various generators in a power system have been optimizing according to active power demand bids by various load buses. In this work, various aspects of power system such as congestion management, voltage stabilization and loss minimization have also taken into consideration for the achievement of the goal. The Interior Point (IP) based Optimal Power Flow (OPF) methodology has been used to obtain the optimal generation schedule for economic system operation. The IP based OPF methodology has been tested on a modified IEEE-30 bus system. The obtained test results shows that not only the generation cost is reduced also the performance of power system has been improved using proposed methodology.

scholarly journals Use of Genetic Algorithm on Optimal Power Flow: An Illustration of Transmission Line Loss Minimization

2018 ◽  
Vol 1 (1) ◽  
pp. 1-4
Author(s):  
Bishal Lamichhane ◽  
Mahesh Chandra Luintel
Keyword(s):  
Genetic Algorithm ◽  
Power System ◽  
Transmission Line ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Problem Formulation ◽  
System Optimization ◽  
Loss Minimization ◽  
Optimal Power ◽  
Broad Concept

This paper presents the usefulness and effectiveness of Genetic Algorithm on solving Optimal Power Flow (OPF) problem formulation of a real world power system. Optimization is a broad concept that is generally directly or indirectly related to cost factor. In this case, transmission lines loss minimization is presented as the objective of optimization problem formulation keeping all other technical factors and parameters under operating constraints. Results of this study, presented in the Integrated Nepal Power System (INPS) transmission line network show that the Genetic Algorithm is effective method to optimize the power flow via assigned objective of transmission loss minimization in much quicker and effective way when compared to conventional Newton-Rapshon method.

Multi-Objective Optimal Power Flow Solutions Using Differential Search Algorithm

2014 ◽  
Vol 1077 ◽  
pp. 241-245
Author(s):  
Isaree Srikun
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Search Algorithm ◽  
Test System ◽  
System Operation ◽  
Power System Operation ◽  
Multi Objective ◽  
Optimal Power ◽  
Generation Cost ◽  
And Control

This paper presents a Differential Search Algorithm for solving a multi-objective Optimal Power Flow (OPF) in support of power system operation and control . The multi-objective OPF was formulated for tackling with total generation cost and environmental impacts simultaneously. The proposed method was applied to the standard IEEE 30-bus test system. The results show that solving the multi-objective OPF problem by the Differential Search Algorithm is more effective than other swarm intelligence methods in the literature.

Flexible Genetic Algorithm Based Optimal Power Flow of Power Systems

2018 ◽  
Vol 24 (3) ◽  
pp. 84
Author(s):  
Hassan Abdullah Kubba ◽  
Mounir Thamer Esmieel
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Test System ◽  
Multi Objective ◽  
Optimal Power ◽  
Blending Method ◽  
Real Coded Genetic Algorithm

Nowadays, the power plant is changing the power industry from a centralized and vertically integrated form into regional, competitive and functionally separate units. This is done with the future aims of increasing efficiency by better management and better employment of existing equipment and lower price of electricity to all types of customers while retaining a reliable system. This research is aimed to solve the optimal power flow (OPF) problem. The OPF is used to minimize the total generations fuel cost function. Optimal power flow may be single objective or multi objective function. In this thesis, an attempt is made to minimize the objective function with keeping the voltages magnitudes of all load buses, real output power of each generator bus and reactive power of each generator bus within their limits. The proposed method in this thesis is the Flexible Continuous Genetic Algorithm or in other words the Flexible Real-Coded Genetic Algorithm (RCGA) using the efficient GA's operators such as Rank Assignment (Weighted) Roulette Wheel Selection, Blending Method Recombination operator and Mutation Operator as well as Multi-Objective Minimization technique (MOM). This method has been tested and checked on the IEEE 30 buses test system and implemented on the 35-bus Super Iraqi National Grid (SING) system (400 KV). The results of OPF problem using IEEE 30 buses typical system has been compared with other researches.     

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