Size Of Static VAR Compensator Research Articles

Improving voltage collapse point under transmission line outage by optimal placement and sizing of SVC using genetic algorithm

In many power systems, voltage instability can increase the risk of voltage collapse and, as a result, turn the power system toward a blackout. Therefore, increasing the voltage collapse point is required. A transmission line outage is an emergency condition in power systems that can lead to voltage instability and voltage collapse. Thus, it is expected to employ shunt-connected flexible AC transmission systems (FACTS) such as the static var compensator (SVC) to increase the voltage collapse point when lines outage. This paper presents the genetic algorithm (GA) application to optimal placement and sizing of an SVC for increasing voltage collapse points following lines outage. The continuation power flow (CPF) technique has been used to determine the maximum loading point (MLP) corresponding to the point of voltage collapse. Also, to reduce the number of scenarios when line outages occur, a list in ascending order is established based on the line outage priority (LOP). The IEEE 14-bus test system is chosen to carry out simulations, and an SVC will be installed in the system based on the GA results. Simulation results confirm the effectiveness of an SVC for improving voltage stability as well as increasing voltage profile.

Optimal Location and Size of Static Var Compensators (SVC) to Enhance the Voltage Profile on the Main Interconnected System in Oman

This study aimed to optimize the incorporation of static var compensators (SVCs) into Oman’s main interconnected system (MIS) using real 2023 MIS data. Leveraging the particle swarm optimization (PSO) algorithm within MATLAB, substantial enhancements were achieved in voltage profiles, with associated losses reducing by roughly 2%. A multi-objective strategy effectively managed costs while preserving improved voltage profiles and controlled losses. Validation through DigSILENT showcased the dynamic advantages of optimal SVC placement through consistently elevating voltage profiles and mitigating losses, notably within the Muscat region. Analyses encompassing harmonics, transient stability, and load distribution indicated that harmonics remained within acceptable thresholds, and overall system stability was enhanced. Optimal SVC deployment expedited the attainment of steady-state conditions, as illustrated via the QV curve, demonstrating increased stability as the buses loaded from 18% to 96%. These findings underscore the robust and efficient nature of SVC integration as a viable solution within Oman’s MIS system, addressing voltage profile enhancement, loss minimization, and fortified system stability.

Optimal Placement and Size of SVC with Cost-Effective Function Using Genetic Algorithm for Voltage Profile Improvement in Renewable Integrated Power Systems

Given the concern for maintaining voltage stability in power systems integrated with renewable power systems due to a mismatch in generation and demand, there remains a need to invoke flexible alternating current transmission system (FACTS) devices in the distribution network. The present paper deals with identifying the locations of placement of a static var compensator in an experimental IEEE 14-bus system; the voltage drop in different buses in an IEEE 14-bus system is calculated by the standard formula. The total voltage drop in the network (TVDN) is also calculated as a reference. The ranking of buses in order of decreasing voltage drop is made, and the weak buses are identified as those showing the maximum or near-maximum voltage drop for the installation of a Static Var Compensator (SVC). The optimum usable size is calculated using a Genetic Algorithm approach to optimize the installation cost. After size optimization, installing a 2 MW solar generator is considered for the weak and most potential bus, which suffers from voltage drops or power loss. Based on the generator at the weakest bus, the total power loss in the network is calculated and compared with a similar method to assess the efficiency of the proposed model. Thus, the voltage stability enhancement problem is solved by applying a Genetic algorithm (GA) to optimize SVC size and using the Total Voltage Drop in Network (TVDN) method to identify weak buses in the systems. It is found that the performance of the proposed system is comparable with another existing system. It is further observed that a gain in power loss to 6.56% is achievable by adopting the proposed strategy, and the gain is better than the other system.

Improvement of system strength under high wind penetration: A techno-economic assessment using synchronous condenser and SVC

Variable speed wind turbine generators (WTGs) are replacing traditional fossil fuel based synchronous generators in the generation fleet as wind penetration increases. These variable speed WTGs are decoupled from the grid by power electronics inverters and usually generate less fault current compared to synchronous generators. As a result, system strength (indicates the fault recovery capability) at the point of common coupling (PCC) of wind power plants may reduce. A minimum value level of system strength is essential for wind power plants to properly identify and overcome a fault. To enhance system strength at wind PCC buses, supplementary devices such as synchronous condenser and Static VAR Compensator (SVC) can be deployed to have additional fault current. Since these devices are expensive, their optimal allocation considering economic feasibility is a major concern. In the existing literature, locations and ratings of the optimally allocated synchronous condenser are reported. However, this approach may cause oversizing of synchronous condensers. In addition, a SVC can be utilised instead of a synchronous condenser to enhance system strength. However, no detailed study is carried out yet to find the optimal size of SVCs. Evidently, both synchronous condenser and SVC can be installed to improve system strength. However, no comprehensive techno-economic assessment is performed for selecting an appropriate choice between them. To address these research gaps, this paper develops a framework to find the optimal sizes of synchronous condensers and SVCs by taking into account the long-term financial viability. Also, to ensure the maximum possible fault contribution, synchronous condensers/SVCs are connected directly to those wind PCC buses where system strength is below the acceptable limit. Afterwards, a detailed techno-economic assessment using synchronous condenser and SVC is performed in a wind dominated grid. In addition, post-fault voltage recovery characteristics with optimally sized synchronous condenser and SVC are explored. The developed methodology is applied to the IEEE 39 bus test system considering 45% wind power penetration scenario. Also, the performance of the proposed approach is compared to that of an existing technique. Finally, based on the technical and economic aspects, a better choice between synchronous condenser and SVC is recommended to improve system strength under high wind penetration.

Multi-Heuristic Based Technique in Multi-SVCs Installation Scheme for Loss Control in Transmission System

Increasing demand of power system has been identified as one of the dominant factors in under-voltage phenomenon, instability condition and increment of transmission loss in power system. To alleviate this condition for the purpose of maintaining secure delivery of electricity, appropriate remedial actions are mandatory to be performed in either real time or offline studies. Amongst the popular remedial actions to avoid the loss control is the installation of static VAR compensator (SVC) scheme. This scheme requires a robust optimization technique which should be able to achieve optimal solution with less computation burden. This paper presents the application of multi-heuristic techniques for optimizing the sizing and locations of the SVC installation. Two optimization techniques are proposed in this study; namely the evolutionary programming (EP) and artificial immune system (AIS) for the purpose of optimal determination of locations and sizing of SVCs. Several cases are considered, based on number of units for the installation process; solved under different loading conditions subjected to the system. A reliability test system (RTS) model was utilized as the test specimen in this study; which ultimately highlights the merit of the optimization techniques.

Multistage artificial immune system for static VAR compensator planning

Interconnected network of transmission and distribution lines lead to losses in the system and weakening the voltage stability in the system. Installing Static VAR Compensator (SVC) in power system has known to improve the system by minimizing the total loss and improve the voltage profile of the system. This paper presents the application of Multistage Artificial Immune System (MAIS) technique to determine optimal size of SVC. The performance of this technique is tested on the IEEE 14-Bus Reliability Test System (RTS). The optimization results show that the proposed Multistage Artificial Immune System (MAIS) technique gives better solution of SVC compensator planning problem compared to single stage Artificial Immune System (AIS) in terms of lower total system loss and improved minimum voltage magnitude.

Power System Performance Improvement by Optimal Placement and Sizing of SVC using Genetic Algorithm

The power system loss minimization becomes more important as the need of power generation is more recent days. The loss minimization improves the voltage profile which improves the loadability of the system. In many types of Flexible AC Transmission System (FACTS) devices Static Var Compensators (SVC) are cost vise it is affordable and it improves the system performance with lesser size. Here SVC is optimally placed in a test system of 30 bus system. Genetic algorithm is used to find the optimal results.

Power System Performance Improvement by Optimal Placement and Sizing of SVC using Genetic Algorithm

The power system loss minimization becomes more important as the need of power generation is more recent days. The loss minimization improves the voltage profile which improves the loadability of the system. In many types of flexible AC transmission system (FACTS) devices static var compensators (SVC) are cost vise it is affordable and it improves the system performance with lesser size. Here SVC is optimally placed in a test system of 30 bus system. Genetic algorithm is used to find the optimal results.

Optimal Allocation and Size of Static VAr Compensator (SVC) for Voltage Stability Improvement in the National Grid of Sudan 500KV Transmission Lines

Optimal Allocation and Size of Static VAr Compensator (SVC) for Voltage Stability Improvement in the National Grid of Sudan 500KV Transmission Lines

Optimal Placement of SVC Incorporating Installation Cost

As the FACTS controllers are an inequitable part of power system due to their fast and very flexible control. With the enhancement of FACTS technology, their role in the marginal cost determination should be considered taking their cost function into account. The aim of this paper is to compare the optimal performance of static VAR compensator (SVC) in voltage stability enhancement problem. During last decade, FACTS devices are broadly used for maximizing the margin of voltage stability and loadability of existing power system transmission networks. To get the optimal system, cost analysis might be necessary. In the cost analysis of SVC, authors analyzed the installation cost of SVC devices in USD, the cost of SVC in USD/KVAR and the average value of installation cost for given systems. Here, the voltage stability enhancement problem is solved applying Gravitational Search algorithm incorporating SVC. The following conditions are investigated with the incorporation of SVC: the role of SVC for improving the voltage profile, loss minimization and the approximate analysis on cost recovery and payback period with SVC in voltage stability enhancement problem. With this motivation, the location of SVC is finalized through weak bus identification methods. Voltage stability indices namely Fast Voltage Stability Index (FVSI) is utilized to identify weak buses in the systems. For calculation of the Size of SVC, an optimization routine Gravitational Search Algorithm (GSA) is established. The main purpose of optimization is to minimize the FVSI. The proposed approach has been tested on three standard IEEE bus systems with different loading scenarios. General Terms: Flexible AC Transmission System (FACTS), Marginal Cost, Voltage Stability Assessment, Static VAR Compensators.

Voltage Stability Assessment using GVSM and Preventive Control using SVC

Voltage stability is a major concern while designing a foolproof power network. In recent years deregulated environment put an additional pressure on transmission and distribution utilities. With this fact assessment of voltage stability along with the preventive control actions are major area of research. With this motivation, this paper presents assessment of voltage stability through Global Voltage Stability Margin (GVSM). GVSM is an indicator of the system’s health from a voltage stability perspective. Three standard IEEE bus systems are simulated with different loading scenarios. Static Var Compensator (SVC) has employed for preventive control in collapse condition. The location of SVC is finalised through weak bus identification methods. Voltage stability indices namely Fast Voltage Stability Indice (FVSI) and Lmn are utilized to identify weak buses in the systems. For calculation of the Size of SVC, an optimization routine is established. This routine has an aim to maximize the GVSM. Gravitational Search Algorithm (GSA) is used for the optimization. The results obtained from proposed method are promising. General Terms Flexible AC Transmission System (FACTS), Voltage Stability Assessment, Static VAR Compensators.

Cuckoo Search Algorithm for Optimal Placement and Sizing of Static Var Compensator in Large-Scale Power Systems

Abstract This paper presents an application of Cuckoo search algorithm to determine optimal location and sizing of Static VAR Compensator. Cuckoo search algorithm is a modern heuristic technique basing Cuckoo species’ parasitic strategy. The Lévy flight has been employed to generate random Cuckoo eggs. Moreover, the objective function is a multiobjective problem, which minimizes loss power, voltage deviation and investment cost of Static VAR Compensator while satisfying other operating constraints in power system. Cuckoo search algorithm is evaluated on three case studies and compared with the Teaching-learning-based optimization, Particle Swarm optimization and Improved Harmony search algorithm. The results show that Cuckoo search algorithm is better than other optimization techniques and its performance is also better.

Application of polynomial control to design a robust oscillation-damping controller in a multimachine power system

This paper addresses the application of a static Var compensator (SVC) to improve the damping of interarea oscillations. Optimal location and size of SVC are defined using bifurcation and modal analysis to satisfy its primary application. Furthermore, the best-input signal for damping controller is selected using Hankel singular values and right half plane-zeros. The proposed approach is aimed to design a robust PI controller based on interval plants and Kharitonov׳s theorem. The objective here is to determine the stability region to attain robust stability, the desired phase margin, gain margin, and bandwidth. The intersection of the resulting stability regions yields the set of kp–ki parameters. In addition, optimal multiobjective design of PI controller using particle swarm optimization (PSO) algorithm is presented. The effectiveness of the suggested controllers in damping of local and interarea oscillation modes of a multimachine power system, over a wide range of loading conditions and system configurations, is confirmed through eigenvalue analysis and nonlinear time domain simulation.

Comparison of EPSO, PSO and EP Approaches in Transmission Loss Minimization in Power System Network

The paper presents a comparison of Computational Intelligence techniques are Evolutionary Programming Swarm Optimization (EPSO), Particle Swarm Optimization (PSO), Evolutionary Programming (EP) to optimal placement and sizing of Static Var Compensator. The technique has been implemented to minimize the transmission loss and improve the voltage profile of the system. Simulation performed on standard IEEE 118-Bus RTS and indicated that EPSO a feasible to achieve the objective function.

A Novel Scheme for Placement and Sizing of SVCs to Improve Voltage Stability of Wind-Integrated Power Systems

On the grid front, issues concerning voltage instability worsen further as and when large wind farms are integrated at multiple locations in an existing network. Since the wind power is fluctuating in nature, it largely affects the reactive power mismatch and prevents the grid operators from injection of wind power to the grid even though it is available abundantly. Dynamic compensation of reactive power at multiple locations of the network could be an effective means for addressing such problems. This paper presents a novel method for suitable placement and sizing of Static VAR Compensators at desired locations, such that smooth evacuation of wind power can occur under various operating conditions, while maintaining voltage stability, simultaneously. The authors have studied the adverse impacts of wind penetration under various system conditions and implemented the scheme in order to improve voltage sensitivity index. The results obtained from the case studies conducted on the standard IEEE 30-bus and practical Indian 28-bus test systems validate the proposed scheme.

Improvement of Voltage Stability by Optimal Placement and Sizing of Static Var Compensator using Particle Swarm Optimization

Improvement of Voltage Stability by Optimal Placement and Sizing of Static Var Compensator using Particle Swarm Optimization

Hybrid GA–PSO for optimal placement of static VAR compensators in power system

In recent years, genetic algorithm (GA), particle swarm optimization (PSO) and hybrid genetic algorithm particle swarm optimization (HGAPSO) have attracted considerable attention among various modern heuristic optimization techniques. In this study the HGAPSO, PSO and GA optimization techniques are used for to search the optimal placement and sizing of static VAR compensator (SVC) in power system. The objective function is defined for reducing power loss, voltage deviation and investment costs of SVC. The effectiveness of the proposed hybrid based approach is applied and demonstrated on IEEE 30 Bus network. The results show that the proposed hybrid HGAPSO compared with PSO and GA optimization for performs and giving better solution.

A Comparative Study of BAT and Firefly Algorithms for Optimal Placement and Sizing of Static VAR Compensator for Enhancement of Voltage Stability

Modern electric power utilities are facing many challenges due to increasing power demand but the growth of power generation and transmission has been limited due to limited resources, environmental restrictions and right-of-way problems. These problems can be minimized by installing Flexible Alternating Current Transmission System (FACTS) devices in modern electric utilities to optimize the existing transmission system. Most effective use of the FACTS devices depend on the fact, how these devices are placed in the power system, i.e. the location and size. An optimal location and size of FACTS devices allows controlling its power flows and thus enhances the stability and reliability of the power systems. In this paper, Firefly Algorithm (FA) and BAT Algorithm (BAT) have been applied and compared to determine the optimal location and size of Static VAR Compensator (SVC) in a power system to improve voltage stability subjected to minimize the active power losses, fuel cost, branching loading and voltage deviation. The effectiveness of the proposed algorithms and improvement of power system stability has been demonstrated on IEEE 57 bus system using fast voltage stability index. The results obtained with variation of parameters of Firefly and BAT Algorithms has been studied and compared with Genetic Algorithm. The results are presented and analyzed.

Optimal Allocation of SVC for Minimization of Power Loss and Voltage Deviation using NSGA - II

Modern this paper proposes non dominated sorting genetic algorithm (NSGA-II) which has feature of adaptive crowding distance for finding optimal location and sizing of Static Var Compensators (SVC) in order to minimize real power losses and voltage deviation and also to improve voltage profile of a power system at the same time. While finding the optimal location and size of SVC, single line outages are considered as contingencies and voltage limits for the buses are taken as security constraints. To demonstrate the effectiveness of the proposed approach, NSGA-II has been applied for finding optimal location and sizing of SVC on IEEE 30-bus test system. The obtained results are highly encouraging and reveal the capability of the NSGA-II to generate well-distributed non-dominated Pareto front.

Voltage Collapse Proximity Indicator based Placement and Sizing of Static VAR Compensator using BAT Algorithm to Improve Power System Performance

Power systems are becoming increasingly more complex due to the interconnection of regional system and deregulation of the overall electricity market. At present owing to the increase in power demand, power system has become more complex and heavily loaded, and is subjected to unstable or insecure operations. For secure operation, it is required to enhance the level of a security margin of the power system. In this paper sensitivity analysis based Voltage collapse proximity Indicator (VCPI) is proposed to select the optimal location of Static VAR Compensator (SVC). An Optimal Power Flow using BAT algorithm is carried out in order to find the optimal size of SVC which minimizes the total real power generation cost. Power System security is assessed using Line security index and voltage security index for IEEE 14 and IEEE 30-bus system using MATLAB Simulation. The results are presented and analyzed for BAT Algorithm based Optimal Power Flow without and with SVC and compared with Genetic Algorithm (GA).