An Efficient Hybrid TLBO-PSO Approach for Congestion Management Employing Real Power Generation Rescheduling  

作　　者：Muneeb Ul Bashir Ward Ul Hijaz Paul Mubassir Ahmad Danish Ali Md. Safdar Ali Muneeb Ul Bashir;Ward Ul Hijaz Paul;Mubassir Ahmad;Danish Ali;Md. Safdar Ali(Department of Electrical Engineering, Jamia Millia Islamia, New Delhi, India)

机构地区：[1]Department of Electrical Engineering, Jamia Millia Islamia, New Delhi, India

出　　处：《Smart Grid and Renewable Energy》2021年第8期113-135,共23页智能电网与可再生能源（英文）

摘　　要：<span style="font-family:Verdana;">In the present deregulated electricity market, power system congestion is the main complication that an independent system operator (ISO) faces on a regular basis. Transmission line congestion trigger serious problems for smooth functioning in restructured power system causing an increase in the cost of transmission hence affecting market efficiency. Thus, it is of utmost importance for the investigation of various techniques in order to relieve congestion in the transmission network. Generation rescheduling is one of the most efficacious techniques to do away with the problem of congestion. For optimiz</span><span style="font-family:Verdana;">ing the congestion cost, this work suggests a hybrid optimization based on</span><span style="font-family:Verdana;"> two effective algorithms viz Teaching learning-based optimization (TLBO) algorithm and Particle swarm optimization (PSO) algorithm. For binding the constraints, the traditional penalty function technique is incorporated. Modified IEEE 30-bus test system and modified IEEE 57-bus test system are used to inspect the usefulness of the suggested methodology.</span><span style="font-family:Verdana;">In the present deregulated electricity market, power system congestion is the main complication that an independent system operator (ISO) faces on a regular basis. Transmission line congestion trigger serious problems for smooth functioning in restructured power system causing an increase in the cost of transmission hence affecting market efficiency. Thus, it is of utmost importance for the investigation of various techniques in order to relieve congestion in the transmission network. Generation rescheduling is one of the most efficacious techniques to do away with the problem of congestion. For optimiz</span><span style="font-family:Verdana;">ing the congestion cost, this work suggests a hybrid optimization based on</span><span style="font-family:Verdana;"> two effective algorithms viz Teaching learning-based optimization (TLBO) algorithm and Particle swarm optimization (PSO) algorithm. For binding the constraints, the traditional penalty function technique is incorporated. Modified IEEE 30-bus test system and modified IEEE 57-bus test system are used to inspect the usefulness of the suggested methodology.</span>

关 键 词：Congestion Management DEREGULATION Optimal Power Flow Teaching-Learning-Based Optimization (TLBO) Power System Modeling 

分 类 号：TP1[自动化与计算机技术—控制理论与控制工程]