Congestion management using grey wolf optimization in a deregulated power market

2021 ◽  
Keyword(s):  
Optimization Technique ◽  
Differential Evolution Algorithm ◽  
Congestion Management ◽  
Grey Wolf ◽  
Transmission Congestion ◽  
Power Sector ◽  
Grey Wolf Optimization ◽  
Congestion Cost ◽  
Real Coded Genetic Algorithm ◽  
Line Overload

Abstract Transmission congestion issues became more severe and difficult to control as the power sector became more deregulated. The grey wolf optimization algorithm is proposed to relieve congestion by rescheduling generation effectively, resulting in the least congestion cost. The selection of participating generators is based on sensitivity, and the proposed technique is used to determine the best-rescheduled output active power generation to minimize line overload. The IEEE-30 bus system is used to test the proposed optimization technique. It has been demonstrated that when compared to other algorithms like the real coded genetic algorithm, particle swarm optimization, and differential evolution algorithm, the proposed approach produces excellent results in terms of congestion cost.

scholarly journals Multiobjective Optimization Methods for Congestion Management in Deregulated Power Systems

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
K. Vijayakumar
Keyword(s):  
Genetic Algorithm ◽  
Power Systems ◽  
Electricity Market ◽  
Optimization Methods ◽  
Evolutionary Programming ◽  
Congestion Management ◽  
Transmission Congestion ◽  
Nsga Ii ◽  
Line Overload ◽  
Nondominated Sorting

Congestion management is one of the important functions performed by system operator in deregulated electricity market to ensure secure operation of transmission system. This paper proposes two effective methods for transmission congestion alleviation in deregulated power system. Congestion or overload in transmission networks is alleviated by rescheduling of generators and/or load shedding. The two objectives conflicting in nature (1) transmission line over load and (2) congestion cost are optimized in this paper. The multiobjective fuzzy evolutionary programming (FEP) and nondominated sorting genetic algorithm II methods are used to solve this problem. FEP uses the combined advantages of fuzzy and evolutionary programming (EP) techniques and gives better unique solution satisfying both objectives, whereas nondominated sorting genetic algorithm (NSGA) II gives a set of Pareto-optimal solutions. The methods propose an efficient and reliable algorithm for line overload alleviation due to critical line outages in a deregulated power markets. The quality and usefulness of the algorithm is tested on IEEE 30 bus system.

scholarly journals Design of Power System by using Grey Wolf Optimization Technique

2019 ◽  
Vol 8 (6) ◽  
pp. 4169-4174
Keyword(s):  
Power System ◽  
Power Supply ◽  
Optimization Technique ◽  
Grey Wolf ◽  
Electrical System ◽  
Grey Wolf Optimization ◽  
Static Synchronous Compensator ◽  
Real Power ◽  
The Stability ◽  
Consumer Devices

Power supply determines the adequacy to the consumer devices. Without real power, an electrical device fails to function normally.The purpose of this article is to study and realise the stability of a power system and its modelling .Thus, the purpose of this study is to reduce the problem of sag / swell of the voltage by using the proposed Distribution Static Synchronous Compensator (D-STATCOM). iThe D-STATCOM is proposed with advanced optimization technique.The stability, modelling and simulation of the electrical system is evaluate by MATLAB.The results thus obtained showed compatibility with the performance of DSTATCOM in reducing the sag of tension and swell.The results are very positive and giving hope for future and have shown that GWO is an effective optimization technique for solving various problems

scholarly journals Transmission Congestion Management and Techno Economical Analysis using Placement of TCSC

2019 ◽  
Vol 8 (9S) ◽  
pp. 237-242
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Research Work ◽  
Congestion Management ◽  
Transmission Efficiency ◽  
Transmission Congestion ◽  
Economical Analysis ◽  
Congestion Cost ◽  
Thyristor Controlled Series Compensator ◽  
Critical Contingency

Congestion management is a major problem in deregulated power system. Congestion leads to increase in transmission line loading, increases losses and reducing transmission efficiency. It also leads to increase in congestion cost and thus affects technical as well as economical parameters. Research work is carried out under single line critical contingency condition. Critical contingency is found out by overall performance index (OPI). Optimal Power Flow (OPF) is carried out and objective is to maximize social welfare. Thyristor controlled series compensator is used to improve power flow, thus it reduces congestion and improves techno-economical parameters. Optimal location of Thyristor controlled series compensator (TCSC) is found out by LMP difference method.

Sign in / Sign up

Export Citation Format

Share Document