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 Optimal power flow with transmission cost solution under bilateral and multilateral transactions

2014 ◽  
Vol 63 (2) ◽  
pp. 227-245
Author(s):  
Bastin Solai Nazaran J. ◽  
K. Selvi
Keyword(s):  
Objective Function ◽  
Electricity Market ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Severity Index ◽  
Test System ◽  
Operating Conditions ◽  
Real Power ◽  
Transmission Cost ◽  
Optimal Power

Abstract In a deregulated electricity market, it is important to dispatch the generation in an economical manner and to ensure security under different operating conditions. In this study evolutionary computation based solution for optimal power flow is attempted. Social welfare optimization is taken as the objective function, which includes generation cost, transmission cost and consumer benefit function. Transmission cost is calculated using Bialek’s power flow tracing method. Severity index is applied as a constraint to measure the security. The objective function is calculated for pre and post contingency periods. Real power generations, real power loads and transformer tap settings are selected as control variables. Different bilateral and multilateral conditions are considered for analysis. A Human Group Optimization algorithm is used to find the solution of the problem. The IEEE 30 bus system is taken as a test system.

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 OPTIMAL POWER FLOW EVALUATION OF POWER SYSTEM USING GENETIC ALGORITHM

2013 ◽  
pp. 115-120
Author(s):  
C. M. WANKHADE ◽  
A. P. VAIDYA
Keyword(s):  
Genetic Algorithm ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Discrete Control ◽  
Voltage Profile ◽  
Control Variables ◽  
Optimal Power ◽  
Generation Cost ◽  
Bus Voltage ◽  
The Individual

This paper presents an efficient genetic algorithm for solving non-convex optimal power flow (OPF) problems with bus voltage constraints for practical application. In this method, the individual is the binary-coded representation that contains a mixture of continuous and discrete control variables, and crossover and mutation schemes are proposed to deal with continuous/discrete control variables, respectively. The objective of OPF is defined that not only to minimize total generation cost but also to improve the bus voltage profile.. The proposed method is demonstrated for a IEEE 30-bus four generator ystem, and it is compared with conventional method.The experimental results show that the GA OPF method is superior to the conventional.

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.

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.

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.     

Optimal TCSC placement for optimal power flow

2012 ◽  
Vol 63 (5) ◽  
pp. 316-321 ◽  
Author(s):  
Fatiha Lakdja ◽  
Fatima Zohra Gherbi ◽  
Redouane Berber ◽  
Houari Boudjella
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Models ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Flow Analysis ◽  
Test System ◽  
Facts Devices ◽  
Optimal Power ◽  
Current Transmission ◽  
Flexible Alternating Current Transmission

Very few publications have been focused on the mathematical modeling of Flexible Alternating Current Transmission Systems (FACTS) -devices in optimal power flow analysis. A Thyristor Controlled Series Capacitors (TCSC) model has been proposed, and the model has been implemented in a successive QP. The mathematical models for TCSC have been established, and the Optimal Power Flow (OPF) problem with these FACTS-devices is solved by Newtons method. This article employs the Newton- based OPF-TCSC solver of MATLAB Simulator, thus it is essential to understand the development of OPF and the suitability of Newton-based algorithms for solving OPF-TCSC problem. The proposed concept was tested and validated with TCSC in twenty six-bus test system. Result shows that, when TCSC is used to relieve congestion in the system and the investment on TCSC can be recovered, with a new and original idea of integration.

scholarly journals Probabilistic Optimal Power Flow for Day-Ahead Dispatching of Power Systems with High-Proportion Renewable Power Sources

2020 ◽  
Vol 12 (2) ◽  
pp. 518
Author(s):  
Yue Chen ◽  
Zhizhong Guo ◽  
Hongbo Li ◽  
Yi Yang ◽  
Abebe Tilahun Tadie ◽  
...  
Keyword(s):  
Power Systems ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Test System ◽  
Power Sources ◽  
Renewable Power ◽  
Point Estimate Method ◽  
Optimal Power ◽  
Simulation Results ◽  
Point Estimation Method

With the increasing proportion of uncertain power sources in the power grid; such as wind and solar power sources; the probabilistic optimal power flow (POPF) is more suitable for the steady state analysis (SSA) of power systems with high proportions of renewable power sources (PSHPRPSs). Moreover; PSHPRPSs have large uncertain power generation prediction error in day-ahead dispatching; which is accommodated by real-time dispatching and automatic generation control (AGC). In summary; this paper proposes a once-iterative probabilistic optimal power flow (OIPOPF) method for the SSA of day-ahead dispatching in PSHPRPSs. To verify the feasibility of the OIPOPF model and its solution algorithm; the OIPOPF was applied to a modified Institute of Electrical and Electronic Engineers (IEEE) 39-bus test system and modified IEEE 300-bus test system. Based on a comparison between the simulation results of the OIPOPF and AC power flow models; the OIPOPF model was found to ensure the accuracy of the power flow results and simplify the power flow model. The OIPOPF was solved using the point estimate method based on Gram–Charlier expansion; and the numerical characteristics of the line power were obtained. Compared with the simulation results of the Monte Carlo method; the point estimation method based on Gram–Charlier expansion can accurately solve the proposed OIPOPF model

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