3 research outputs found
Congestion Management by Applying Co-operative FACTS and DR program to Maximize Renewables
This research proposes an incremental welfare consensus method based on
flexible alternating current transmission systems (FACTS) and demand response
(DR) programs to control transmission network congestion in order to increase
the penetration of wind power. The locational marginal prices are used as input
by the suggested model to control the FACTS device and DR resources. In order
to do this, a cutting-edge two-stage market clearing system is created. In the
first stage, participants bid on the market with the intention of maximizing
their profits, and the ISO clears the market with the goal of promoting
societal welfare. The second step involves the execution of a generation
re-dispatch issue in which incentive-based DR and FACTS device controllers are
optimally coordinated to reduce the rescheduling expenses for generating firms.
Here, a static synchronous compensator and a series capacitor operated by a
thyristor are used as two different forms of FACTS devices. A case study on the
modified IEEE one-area 24-bus RTS system is then completed. The simulation
results show that the suggested interactive DR and FACTS model not only reduces
system congestion but also makes the system more flexible so that it can
capture as much wind energy as feasible.Comment: 23 pages, 8 figures, 8 table
A Comprehensive Review of Congestion Management in Power System
In recent decades, restructuring has cut across all probable domains, involving the power supply industry. The restructuring has brought about considerable changes whereby electricity is now a commodity and has become a deregulated one. These competitive markets have paved the way for countless entrants. This has caused overload and congestion on transmission lines. In addition, the open access transmission network has created a more intensified congestion issue. Therefore, congestion management on power systems is relevant and central significance to the power industry. This manuscript review few congestion management techniques, consists of Reprogramming Generation (GR), Load Shedding, Optimal Distributed Generation (DG) Location, Nodal Pricing, Free Methods, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Fuzzy Logic System Method, as well as Additional Renewable Energy Sources. In this manuscript a review work is performed to unite the entire publications on congestion management
A Comprehensive Review of Congestion Management in Power System
In recent decades, restructuring has cut across all probable domains, involving the power supply industry. The restructuring has brought about considerable changes whereby electricity is now a commodity and has become a deregulated one. These competitive markets have paved the way for countless entrants. This has caused overload and congestion on transmission lines. In addition, the open access transmission network has created a more intensified congestion issue. Therefore, congestion management on power systems is relevant and central significance to the power industry. This manuscript review few congestion management techniques, consists of Reprogramming Generation (GR), Load Shedding, Optimal Distributed Generation (DG) Location, Nodal Pricing, Free Methods, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Fuzzy Logic System Method, as well as Additional Renewable Energy Sources. In this manuscript a review work is performed to unite the entire publications on congestion management