Placement Of Static Var Compensator Research Articles

Stability Improvement of Sulbagsel Electricity System Integrated Wind Power Plant Using SVC-PSS3C Based on Improved Mayfly Algorithm

This study thoroughly investigates the enhancement of power system stability through the coordinated design of Static VAR Compensator (SVC) and Multi-Band Power System Stabilizer type 3C (MB-PSS3C). An Improved Mayfly Algorithm (IMA) is employed to optimize the placement and tuning of SVC and MB-PSS3C within the Southern Sulawesi (Sulbagsel) integrated Wind Power Plant (WPP) electricity system. Mayfly intelligence is inspired by the mating and flight behaviors of adult mayflies. In its standard form, this algorithm cannot be applied to high-dimensional, nonlinear, and complex space problems. This study proposes an Exponent Decreasing Inertia Weight (EDIW) strategy to enhance the performance of the standard Mayfly Algorithm (MA). The IMA demonstrates superior performance compared to other methods, achieving a minimum fitness function value of 80.0582 and converging rapidly by 8th iteration. For SVC, the optimization analysis involved reviewing the voltage profile at each bus and analyzing Optimal Power Flow (OPF). For MB-PSS3C, the optimization focused on evaluating system stability through damping analysis, time-domain simulations, and eigenvalue visualization. The application of IMA-based SVC improved reactive power management in transmission systems, resulting in enhanced voltage profiles, OPF, and reduced transmission losses. Specifically, transmission losses decreased by 3.12% in the normal system case study and by 2.88% in the N-1 contingency case study. Meanwhile, the IMA-based MB-PSS3C enhanced system stability by increasing system damping, reducing generator oscillation overshoot, and improving system eigenvalues. The implementation of MB-PSS3C using IMA across 14 generators achieved the highest damping ratio of 0.7375, compared to 0.7274 for MB-PSS3C with MA.

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.

Optimization of SVC Placement and Capacity in the Electric Power System Transmission Networks using Multi-Objective Improved Sine Cosine Algorithm

Current technological developments are in line with the increasing consumption of electrical energy. There is a value of power losses of the electricity transmission process caused by an increase in the value of power losses, to overcome this, SVC (Static VAR Compensator) of the Flexible AC Transmission System (FACTS) can be used. From previous studies, the optimization of SVC placement in the transmission network has not been carried out to get better power losses. This research uses the Improved-Sine Cosine Algorithm (ISCA) that has a different function of r1 compared to the ordinary SCA, in which the use of the ISCA method is able to overcome the weaknesses of the SCA method. The determination of location and capacity can use more than one objective function. From the result, the optimization of SVC placement and capacity is able to reduce the value of power losses by up to 85%.

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.

Improving system static security via optimal placement of static VAR compensator using Multi Verse Optimizer (MVO)

Numerous Flexible AC Transmission System (FACTS) devices have been installed in transmission networks in recent years. Due to energy demand rising, so does load consumption, resulting in increased power losses. This paper aims Multi Verse Optimizer (MVO) for transmission loss minimization and to optimize the location and sizing of Static VAR Compensator (SVC) to be installed. Multi Verse Optimizer (MVO) approach is suggested as a solution to improve system static security and optimize location sizing via optimal placement of SVC then validate it on standard IEEE 30-bus Reliability Test System (RTS) system. The objective function of this research is to minimize power loss using MVO by determining the location and sizing of SVC to be installed in the system. The obtained results demonstrate that installing SVCs in the system can aid in minimizing losses in weak and secure buses. The expected result shows that using MVO can determine the optimal parameters and reduce losses.

Restoration of a new age power distribution system

The new age transformed distribution system became the most popular content in the literature. In that regard a simulation is attempted for the load flow with dynamically changing system data. Any topic of interest like electrical vehicle, distributed generators, FACTS devices were generalized and considered as an element and placed at different possible locations to observe their effect. The outcomes of the work were generalized to re-consider on site. As the power industry is undergoing a drastic change throughout the world. Restoration of a distribution system along with switching sequence has become a challenging task. In the last half of the twentieth century, analysis of transmission system was the prime concern and faced many challenges to power engineers. The chosen equivalent IEEE 33-bus electric power distribution system has been considered to analyze the system properties such as its maximum capacity, operating limits, restoration issues. The placement of static var compensator (SVC) was experimented for each and every bus. Considering the minimization of total power loss as a prime objective, the best location was found. This analysis also suggested a ranking of different buses and can be helpful in deciding the switching sequence, provided in case of fault, weak area clustering is done. So, congestion is managed in this distribution system.

A novel ameliorated Harris hawk optimizer for solving complex engineering optimization problems

This article presents a metaheuristic algorithm namely Ameliorated Harris Hawk Optimizer (AHHO) to solve multiconstrained optimization problems. AHHO mimics the hunting behavior of Harris Hawks and is modified to draw a synergy between exploration and exploitation by conducting neighborhood search of already visited iterations utilizing random exploratory forage and local random forage. The oppositional based learning has been incorporated to generate adequate diversity among solutions. The proposed algorithm is substantiated on a set of 23 standard benchmark functions to test its characteristics in finding optimal solutions. The algorithm is mathematically modeled in the current work to obtain solution for voltage constrained reactive power dispatch (VCRPD) problem for IEEE 57 and 118 bus systems. The proposed method of VCRPD is implemented first with shunt capacitors as var sources and then replacing them with static var compensator (SVC) for improved performance. The optimal placement of SVC is determined by fast voltage stability index method. The proposed AHHO algorithm reduces the transmission losses by 9.42% with shunt capacitors in IEEE 57 bus and 10.344% in IEEE 118 bus system. Similarly, transmission loss with SVC compensated system is reduced by 12.86% in IEEE 57 bus and 14.74% in IEEE 118 bus system. Results reveal the proposed technique has the potent to solve real world optimization problems and is competitive with recent methods reported in state-of- art literature.

Metaheuristic optimization based placement of SVCs with multiple objectives

Purpose Optimal placement of static VAR compensator (SVC) devices not only improves the voltage profile (VP) but also reduces the active power loss (APL) and enhances the voltage stability (VS) through injecting appropriate VARs at optimal buses. The traditional mathematical methods may not provide global best solution and pose difficulties in handling multi-objective SVC placement (SVCP) problem with complex constraints and forcefully place all the given number of SVCs in the system without assessing their real requirements in enhancing the chosen performances. The purpose of this paper is to formulate the SVCP as a multi-objective optimization problem and solve it using a metaheuristic algorithm for global best solution. Design/methodology/approach The proposed SVCP method uses improved harmony search optimization (IHSO) with dissonance-avoiding mechanism for obtaining the global best solution through driving away the solution from the sub-optimal traps. In addition, the method uses a self-adaptive technique for optimally tuning the IHSO parameters and places only the required number of SVCs from the given number of SVCs. Findings This paper presents the results of the proposed method for 14, 30 and 57 bus systems and exhibits that the proposed method outperforms the existing SVCP methods in achieving the desired performances. Originality/value This paper proposes a new self-adaptive IHSO based SVCP method for optimally placing only the required number of SVCs with a goal of attaining the global best performances.

Improvement of Static Voltage Stability of 16-Bus Bali System by Optimal Placement of SVC

In a power system, the reactive power imbalance is related to the stability of the static voltage because the injection of reactive power that the bus receives from the system determines the bus's capability in the system. Rapid increases in real and reactive power losses occur as the system approaches the voltage drop point or the maximum load point. It is necessary to support local and adequate reactive power to avoid system leading to be voltage collapse. This study analyzes the improvement of the margin of static voltage stability using one type of modern control equipment of shunt flexible AC transmission system (FACTS), namely the static var compensator (SVC). The controller's representations are used in the continuation power flow (CPF) process to study static voltage stability. The proposed method's effectiveness has been investigated using a practical test system, namely the Bali 16-bus system, to increase the system loading capacity. The simulation was carried out by installing a modern controller in the best location, namely on bus 07 ASARI; an increase in system margin loading closed to 2% compared to the base case condition, namely λmax = 1,879 p.u with the voltage profile not changing significantly.

Optimal placement of static VAR compensator in transmission network for loss minimization and voltage deviation index reduction

Optimal placement of static VAR compensator in transmission network for loss minimization and voltage deviation index reduction

Optimal Location of Static Var Compensator to Regulate Voltage in Power System

This paper proposes a novel method to find the optimal location of the shunt connected Flexible AC Transmission Systems (FACTS) such as Static Var Compensator (SVC) or Static Synchronous Compensator (STATCOM) to the power system for regulating voltage levels of all buses. Three indices include Voltage Drop Index (VDI), Total Voltage Drop Index (TVDI), and Total Voltage Drop of Network Index (TVDNI) are presented to find the location of the SVC. Also, to minimize the solution space, a ranking list will be established. For the case studies, the IEEE 14-bus test system is selected, and an SVC is located in the system. Simulations are done in two cases: network loads increase with constant coefficient and randomly. According to simulation results in both cases, the proposed method can identify the optimal placement of SVC, and the voltage drop due to increasing the load will be compensated. For the IEEE 14-bus test system, the optimal location of the SVC is bus 9. Variable loads are considered for 24 h, and SVC is installed at bus 9 to validate the introduced method. Results show the voltage level for all buses is compensated so that the voltage levels are higher than the minimum voltage level, i.e. 95%.

SVC device optimal location for voltage stability enhancement based on a combined particle swarm optimization-continuation power flow technique

The increased power system loading combined with the worldwide power industry deregulation requires more reliable and efficient control of the power flow and network stability. Flexible AC transmission systems (FACTS) devices give new opportunities for controlling power and enhancing the usable capacity of the existing transmission lines. This paper presents a combined application of the particle swarm optimization (PSO) and the continuation power flow (CPF) technique to determine the optimal placement of static var compensator (SVC) in order to achieve the static voltage stability margin. The PSO objective function to be maximized is the loading factor to modify the load powers. In this scope, two SVC constraints are considered: the reference voltage in the first case and the total reactance and SVC reactive power in the second case. To test the performance of the proposed method, several simulations were performed on IEEE 30-Bus test systems. The results obtained show the effectiveness of the proposed method to find the optimal placement of the static var compensator and the improvement of the voltage stability.

An intermittent contingency approach with optimal placement of static VAR compensator in a renewable -integrated power systems

ABSTRACT The incredible abatement in the expense of sustainable power source age and growing solicitation, deregulated power systems are comprehensive of sustainable power sources to improve voltage stability and power exchangeability of the network. To reap the economic benefits of renewable energy sources completely, there is a need for in-depth understanding of the dynamics of the system for contingency conditions. In this paper, diverse indices are studied to assess the health of the system under various contingencies conditions and a Composite Bus Utilisation Index (CBUI) is proposed for optimal placement of static VAR compensator (SVC). Further, Grey Wolf algorithm is used to optimise the power flow for fuel cost reduction with valve-point effect, real power losses and carbon emissions. The deliverable power of wind and solar generation is estimated using the Weibull and Lognormal probability density function (PDF) respectively. The proposed methodology is validated on IEEE 30 bus systems under normal loading and contingency conditions using intermittent approach in simulation environment and is compared with Newton Raphson method for its efficacy.

Effect of SVC installation on loss and voltage in power system congestion management

<span>In this paper, a new hybrid optimization technique is proposed namely Adaptive Embedded Clonal Evolutionary Programming (AECEP). This idea comes from the combination part of the clone in an Artificial Immune System (AIS) and then combined with Evolutionary Programming (EP). This technique was implemented to determine the optimal sizing of Flexible AC Transmission Systems (FACTS) devices. This study focused on the ability of Static Var Compensator (SVC) is used for the optimal operation of the power system as well as in reducing congestion in power system. In order to determine the location of SVC, the previous study has been done using pre-developed voltage stability index, Fast Voltage Stability Index (FVSI). Congested lines or buses will be identified based on the highest FVSI value for the purpose of SVC placement. The optimizations were conducted for the SVC sizing under single contingency, where SVC was modeled in steady state analysis. The objective function of this study is to minimize the power loss and improve the voltage profile along with the reduction of congestion with the SVC installation in the system. Validation on the IEEE 30 Bus RTS and IEEE 118 Bus RTS revealed that the proposed technique managed to reduce congestion in power system.</span>

Optimal Placement of FACTS Devices for Voltage Stability Improvement with Economic Consideration Using Firefly Algorithm

Background: Increasing power demand forces the power systems to operate at their maximum operating conditions. This leads the power system into voltage instability and causes voltage collapse. To avoid this problem, FACTS devices have been used in power systems to increase system stability with much reduced economical ratings. To achieve this, the FACTS devices must be placed in exact location. This paper presents Firefly Algorithm (FA) based optimization method to locate these devices of exact rating and least cost in the transmission system. Methods: Thyristor Controlled Series Capacitor (TCSC) and Static Var Compensator (SVC) are the FACTS devices used in the proposed methodology to enhance the voltage stability of power systems. Considering two objectives of enhancing the voltage stability of the transmission system and minimizing the cost of the FACTS devices, the optimal ratings and cost were identified for the devices under consideration using Firefly algorithm as an optimization tool. Also, a model study had been done with four different cases such as normal case, line outage case, generator outage case and overloading case (140%) for IEEE 14,30,57 and 118 bus systems. Results: The optimal locations to install SVC and TCSC in IEEE 14, 30, 57 and 118 bus systems were evaluated with minimal L-indices and cost using the proposed Firefly algorithm. From the results, it could be inferred that the cost of installing TCSC in IEEE bus system is slightly higher than SVC.For showing the superiority of Firefly algorithm, the results were compared with the already published research finding where this problem was solved using Genetic algorithm and Particle Swarm Optimization. It was revealed that the proposed firefly algorithm gives better optimum solution in minimizing the L-index values for IEEE 30 Bus system. Conclusion: The optimal placement, rating and cost of installation of TCSC and SVC in standard IEEE bus systems which enhanced the voltage stability were evaluated in this work. The need of the FACTS devices was also tested during the abnormal cases such as line outage case, generator outage case and overloading case (140%) with the proposed Firefly algorithm. Outputs reveal that the recognized placement of SVC and TCSC reduces the probability of voltage collapse and cost of the devices in the transmission lines. The capability of Firefly algorithm was also ensured by comparing its results with the results of other algorithms.

Multi-Objective Evolutionary Programming for Static VAR Compensator (SVC) in Power System Considering Contingencies (N-m)

<span>Static VAR Compensators (SVCs) is a Flexible Alternating Current Transmission System (FACTS) device that can control the power flow in transmission lines by injecting capacitive or inductive current components at the midpoint of interconnection line or in load areas. This device is capable of minimizing the overall system losses and concurrently improves the voltage stability. A line index, namely <em>SVSI</em> becomes indicator for the placement of SVC and the parameters of SVCs are tuned by using the multi-objective evolutionary programming technique, effectively able to control the power. The algorithm was tested on IEEE-30 Bus Reliability Test System (RTS). Comparative studies were conducted based on the performance of SVC in terms of their location and sizing for installations in power system.</span>

Optimization Placement of Static Var Compensator (Svc) on Electrical Transmission System 150 kV Based on Smart Computation

To improve voltage profile, we can use FACTS equipment. One of them is SVC (Static Var Compensator). This study aims to determine the location and optimal capacity of SVC and to determine the effect after SVC installation. This research was conducted in 150 kV transmission system, West Java load regulator area of South Bandung and New Ujungberung subsystem. The research method used for power flow simulation is Newton Raphson and to determine the optimal position and capacity of SVC was using genetic algorithm in MATLAB R2014. After the SVC placement is optimized, then the system performance will increase such as the voltage of all buses is at the standard level and the decrease of power losses.

Optimization of Size and Cost of Static VAR Compensator using Dragonfly Algorithm for Voltage Profile Improvement in Power Transmission Systems

Voltage stability is a major concern in power transmission systems due to mismatch between power generation and demand. Hence maintenance of voltage profile within the acceptable limit becomes a challenging task. In this paper the weakest buses for implementing the reactive power compensators are identified by eigenvalue decomposition technique on partitioned Y-admittance matrix. The size and cost of the SVC are optimized using dragonfly algorithm. The algorithm is implemented on IEEE 14 and 30 bus systems and the results obtained with and without the placement of Static VAR Compensators are compared with the results of other algorithms to show its effectiveness. The further scope of this work is to extend this to renewable energy by implementing the wind generators at the weakest buses there by reducing the electrical distance between the generators and the farthest load buses and securing the system from voltage collapse.

Optimal SVC placement for Maximizing Photovoltaic Hosting Capacity in Distribution Network

Abstract It has become a challenging task to accommodate the proliferation of distributed photovoltaic (PV) generation in distribution networks (DN). In order to enhance the PV generation hosting capacity (HC) in DN, we propose a novel optimal static VAR compensator (SVC) placement model in this paper. The objective is to maximize the PV admissibility and minimize investment cost of SVC while maintaining required levels of power quality and system stability. To reduce the complexity of the problem, linearization is utilized to transform the original nonlinear problem into a mix-integer linear program. Finally, the effectiveness of the proposed model is validated using a modified IEEE 37-bus distribution system with excessive PVs.