Optimized placement of multiple FACTS devices using PSO and CSA algorithms

This paper is an attempt to develop a multi-facts device placementin deregulated power system using optimization algorithms. The deregulated power system is the recent need in the power distribution as it has many independent sellers and buyers of electricity. The problem of deregulation is the quality of the power distribution as many sellers are involved. The placement of FACTS devices provides the solution for the above problem. There are researches available for multiple FACTS devices. The optimization algorithms like Particle Swarm Optimization (PSO) and Cuckoo Search Algorithm (CSA) are implemented to place the multiple FACTS devices in a power system. MATLAB based implementation is carried out for applying Optimal Power Flow (OPF) with variation in the bus power and the line reactance parameters. The cost function is used as the objective function. The cost reduction of FACTS as well as generation by placement of different compensators like, Static Var Compensator (SVC), Thyristor Controlled Series Compensator (TCSC) and Unified Power Flow Controller (UPFC). The cost calculation is done on the 3-seller scenario. The IEEE 14 bus is taken here as 3-seller system

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

Optimal placement of TCSC for congestion management and power loss reduction using multi-objective genetic algorithm

© 2020 by the authors. Electricity demand has been growing due to the increase in the world population and higher energy usage per capita as compared to the past. As a result, various methods have been proposed to increase the efficiency of power systems in terms of mitigating congestion and minimizing power losses. Power grids operating limitations result in congestion that specifies the final capacity of the system, which decreases the conventional power capabilities between coverage areas. Flexible AC Transmission Systems (FACTS) can help to decrease flows in heavily loaded lines and lead to lines loadability improvements and cost reduction. In this paper, total power loss reduction and line congestion improvement are assessed by determining the optimal locations and compensation rates of Thyristor-Controlled Series Compensator (TCSC) devices using the Multi-Objective Genetic Algorithm (MOGA). The results of applying the proposed method on the IEEE 30-bus test system confirmed the efficiency of the proposed procedure. In addition, to check the performance, applicability, and effectiveness of the proposed method, different heuristic algorithms, such as the multi-objective Particle Swarm Optimization (PSO) algorithm, Differential Evolution (DE) algorithm, and Mixed-Integer Non-Linear Program (MINLP) technique, are used for comparison. The obtained results show the accuracy and fast convergence of the proposed method over the other heuristic techniques

Enhancement of deregulated and restructured power network performance with flexible alternating current transmission systems devices.

Doctoral degree. University of KwaZulu- Natal, Durban.The increase in power transactions, consequent open access created by deregulation and restructuring has resulted into network operation challenges including determination as well as enhancement of available transfer capability (ATC), and congestion management among others. In this study, repeated alternating current power flow (RACPF) approach was implemented for determination of ATC. ATCs for inter-area line outage and generator outage contingency conditions were obtained and analyzed. Analyses of most severe line outage contingencies resulting from evaluation of different performance index (PI) ranking methods were carried out for severe line outage contingency identification. A comprehensive review of FACTS controllers with their various background, topological structures, deployment techniques and cutting-edge applications was carried out for network performance enhancement. In addition, different placement methods were investigated for optimal performance evaluation of FACTS devices. Following this, comparative performance of static var compensator (SVC) and thyristor-controlled series compensator (TCSC) models for enhancement of ATC, bus voltage profile improvement and real power loss minimization was investigated. In addition, particle swarm optimization (PSO) and brain-storm optimization algorithms (BSOA) were engaged for optimum setting of FACTS devices through multi-objective problem formulation and allocation purposes. Thereafter, sensitivity-based technique involving incorporation of proposed FACTS device loss with the general loss equation for the determination of optimum location with same objectives was developed and TCSC location was established based on this sensitivity factors analyses, obtained from partial derivatives of the resultant loss equations with respect to control parameters. Subsequently, investigation and analyses of capability of an optimized VSC-HVDC transmission system in enhancing power network performance were conducted. Furthermore, this optimized VSC-HVDC transmission system was applied for mitigation of bus voltage and line thermal limit violation as a result of n-1-line outage contingency. All these investigations and analyses were implemented for bilateral, simultaneous and multilateral transactions as characterized by network liberalization and IEEE 5 and 30 bus networks were used for implementation in MATLAB environment. RACPF method found to be more accurate especially when compared with other methods with 11.574 MW above and 29.014 MW below recorded ATC values. Voltage and real power PI have also been proven to be distinctly dissimilar in severe contingency identification. In placement method comparison however, disparities in ATC enhancement ranges between 2% and 85% were achieved while real power loss minimization of up to 25% was obtained for different methods. Real power loss minimization of up to 0.06 MW and voltage improvement of bus 21 to 30 were achieved with SVC, while ATC enhancement of up to 14% were recorded for both devices. However, BSO behaved much like PSO throughout the achievements of other set objectives but performed better in ATC enhancement with 27.12 MW and 5.24 MW increase above enhanced ATC values achieved by the latter. The comparison of set objectives values relative to that obtained with PSO methods depict suitability and advantages of BSOA technique. Sensitivity based placement technique resulted into ATC enhancement of more than 60% well above the values obtained when TCSC was placed with thermal limit method. In addition, a substantial bus voltage improvement and active power loss reduction were recorded with this placement method. With incorporation of a VSC-HVDC based transmission system into ac network however, there was an improvement in power flow up to 15.66% corresponding to 46 MW for various transactions, transmission line power loss minimization up to 0.38 MW and bus voltage profile deviation minimization. Besides, automatic alleviation of violated thermal and voltage limits during contingency present VSC-HVDC system as a solution for network performance optimization especially during various transactions occasioned by unbundling power processes. Therefore, ATCs were properly enhanced, bus voltage profile improved, and system real power loss minimized. Likewise, HVDC system enhanced network performance and automatically alleviated violated thermal and voltage limits during contingency

GREY WOLF OPTIMIZER BASED OPTIMAL PLACEMENT OF MULTIPLE FACTS DEVICES IN THE TRANSMISSION SYSTEM UNDER DYNAMIC LOADING SYSTEM

The application of grey wolf optimization technique for multiple FACTS placement is presented in this paper for the reduction of total system losses and minimization of voltage deviation via optimal placement of Flexible AC Transmission System (FACTS) device. Grey wolf optimization (GWO) technique is inspired by social hierarchy and hunting behaviour of wolves and offers a right balance between exploration and exploitation during the search for global optimal. Series-shunt FACTS device; unified power flow controller (UPFC) is considered as a formidable device that can provides an alternative option for the flexible controllability and improvement of power transfer capability of a transmission lines. The analyses were conducted by increasing the number of UPFC in the network in order to evaluate the optimal number of FACTS devices that would give the least loss under maximum loading and contingency conditions. The efficacy of this proposed technique is demonstrated on 31-bus, 330 kV Nigeria National Grid (NNG) using MATLAB environment. The results show that optimal placement of FACTS device along with optimization technique provides a promising solution to the high power loss and voltage deviation bedevilling Nigeria National Grid

Market-based transmission congestion management using extended optimal power flow techniques

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 5/9/2001This thesis describes research into the problem of transmission congestion management. The causes, remedies, pricing methods, and other issues of transmission congestion are briefly reviewed. This research is to develop market-based approaches to cope with transmission congestion in real-time, short-run and long-run efficiently, economically and fairly. Extended OPF techniques have been playing key roles in many aspects of electricity markets. The Primal-Dual Interior Point Linear Programming and Quadratic Programming are applied to solve various optimization problems of congestion management proposed in the thesis. A coordinated real-time optimal dispatch method for unbundled electricity markets is proposed for system balancing and congestion management. With this method, almost all the possible resources in different electricity markets, including operating reserves and bilateral transactions, can be used to eliminate the real-time congestion according to their bids into the balancing market. Spot pricing theory is applied to real-time congestion pricing. Under the same framework, a Lagrangian Relaxation based region decomposition OPF algorithm is presented to deal with the problems of real-time active power congestion management across multiple regions. The inter/intra-regional congestion can be relieved without exchanging any information between regional ISOs but the Lagrangian Multipliers. In day-ahead spot market, a new optimal dispatch method is proposed for congestion and price risk management, particularly for bilateral transaction curtailment. Individual revenue adequacy constraints, which include payments from financial instruments, are involved in the original dispatch problem. An iterative procedure is applied to solve this special optimization problem with both primal and dual variables involved in its constraints. An optimal Financial Transmission Rights (FTR) auction model is presented as an approach to the long-term congestion management. Two types of series F ACTS devices are incorporated into this auction problem using the Power Injection Model to maximize the auction revenue. Some new treatment has been done on TCSC's operating limits to keep the auction problem linear

Unified Power Flow Controller: A Brief Review on Tuning and Allocation for Power System Stability

The Power System can become unstable due to disturbances. To enhance system stability the Unified Power Flow Controller (UPFC) is tuned and allocated in the System. In this paper, a brief review of UPFC tuning and allocation studies for power systems stability is presented. The databases consulted for literature are the IEEE Xplore, ScienceDirect, Google Scholar and IOP Publications. The search terms used are Allocation, Tuning, UPFC, Power System and Stability to find the literature used in this review. A total of 26 Journal articles and conference papers were found and reviewed based on tuning and allocation studies. The Researchers applied Fuzzy coordination, Genetic Algorithm (GA), Particles Swarm Optimization (PSO), Grey Wolf Optimization (GWO) and Linear Quadratic Tracker (LQT) to tune the UPFC for enhancing power system stability. For studies on UPFC allocation in power systems, the Researchers applied frequency response of power system transfer function, power flow, Tabu Search (TS), PSO and GA. For allocation based on optimization, the Researchers minimized power losses, voltage index and investment costs considering equality and inequality constraints

Load frequency controllers considering renewable energy integration in power system

Abstract: Load frequency control or automatic generation control is one of the main operations that take place daily in a modern power system. The objectives of load frequency control are to maintain power balance between interconnected areas and to control the power flow in the tie-lines. Electric power cannot be stored in large quantity that is why its production must be equal to the consumption in each time. This equation constitutes the key for a good management of any power system and introduces the need of more controllers when taking into account the integration of renewable energy sources into the traditional power system. There are many controllers presented in the literature and this work reviews the traditional load frequency controllers and those, which combined the traditional controller and artificial intelligence algorithms for controlling the load frequency