Line Loss Reduction Research Articles

Optimal Placement and Sizing of Modular Series Static Synchronous Compensators (M-SSSCs) for Enhanced Transmission Line Loadability, Loss Reduction, and Stability Improvement

This paper addresses the optimal placement and sizing of Modular Static Synchronous Series Compensators (M-SSSCs) to enhance power system performance. The proposed methodology optimizes four key objectives: reducing transmission line loadability, minimizing power losses, mitigating voltage deviations, and enhancing voltage stability using the L-index. The methodology is validated on two systems: the IEEE 14-bus test network and a sub-area of the Colombian power grid, characterized by aging infrastructure and operational challenges. The optimization process employs three metaheuristic algorithms—Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Teaching–Learning-Based Optimization (TLBO)—to identify optimal configurations. System performance is analyzed under both normal operating conditions and contingency scenarios (N − 1). The results demonstrate that M-SSSC deployment significantly reduces congestion, enhances voltage stability, and improves overall system efficiency. Furthermore, this work highlights the practical application of M-SSSC in modernizing real-world grids, aligning with sustainable energy transition goals. This study identifies the optimal M-SSSC configurations and placement alternatives for the analyzed systems. Specifically, for the Colombian sub-area, the most suitable solutions involve installing M-SSSC devices in capacitive mode on the Termocol–Guajira and Santa Marta–Guajira 220 kV transmission lines.

Integrated optimization for sizing, placement, and energy management of hybrid energy storage systems in renewable power systems

Power systems reliant on renewable energy sources (RES) encounter supply-demand imbalances and stability challenges due to their inherent uncertainties. Hybrid energy storage systems (HESS) have emerged as a flexible and cost-effective solution to address these issues. This paper proposes an integrated optimization method for the capacity, location, and energy management of a HESS in RES-based power systems. The method optimizes battery energy storage system (BESS), electrolyzer (EL), fuel cell (FC), and hydrogen storage tank (HST) to minimize total costs, including power purchase, curtailment compensation, operation and maintenance (O&M), and investment costs, alongside voltage profile deviation index (VPDI) and active power loss index (APLI). A novel hybrid framework is proposed, utilizing mixed-integer linear programming (MILP) optimization at the master level and non-dominated sorting genetic algorithm II (NSGA-II) optimization at the slave level. This framework ensures that MILP provides robust solutions, while NSGA-II derives balanced optimal solutions from the optimal Pareto front. The proposed method was validated using real seasonal data from Korea and tested in IEEE 33 and IEEE 69 bus systems against various benchmark cases. Results indicate significant improvements, with VPDI enhanced by 16.00 % and 10.11 %, APLI by 15.64 % and 12.15 %, and total costs reduced by 58.67 % and 50.56 %, respectively. The sensitivity analysis demonstrated the robustness of the proposed method, showing zero sensitivity to iterations and positive correlations with increased levels of RES. Further verification against other optimization algorithms showed that the proposed method excels in cost efficiency, voltage stability, and line loss reduction, providing highly reliable results.

Impact of integrating type-1 distributed generation on distribution network using modified genetic algorithm and voltage stability index: a technical and cost–benefit analysis approach

The position of the distribution network and its peculiar topology calls for viable means of addressing the issue of severe power loss and voltage instability confronting its ability to truly wheel out the received energy from the transmission arm of the network to the end users. Based on this premise, the current work employed a Lévy flight genetic algorithm (LF-GA) for the placement of type-1 photovoltaic-based distributed generation (PV-DG) into a radial network. The IEEE 33 and Government Residential Area (GRA) 11 kV and 34-bus feeder in Nigeria were used to investigate the effectiveness of the proposed approach. The backward-forward sweep formed the backbone of the load flow, while the voltage stability index was used to select the suitable buses where type-1 DG was integrated for optimal performance. The criteria considered for performance evaluation were the cost of energy loss, payback time, active power loss, and network voltage profile improvement without violating the essential network constraints. The paper proposed a relevant policy framework on DG integration, which filled knowledge gap in the previous studies. A multi-objective factor-based LF-GA subjected to appropriate constraints was used to optimize both the sizing and the locations of type-1 DG with the arrangements implemented in a MATLAB environment. The results obtained when compared with the existing contributions in the literature showed a credible improvement in line-loss reduction, voltage profile, and the system voltage stability index, including reduced cost of energy loss with minimal payback time on the investment of compensating devices.

Loss reduction optimization strategies for medium and low-voltage distribution networks based on Intelligent optimization algorithms

ProblemWith the rapid development of social economy, the problem of line losses in distribution networks gradually becomes prominent, which directly affects the efficiency and economy of power systems.MethodologyIn order to reduce line losses, a loss optimization model for low and medium voltage distribution networks based on an improved Gray Wolf optimization support vector machine is proposed. The optimization model introduces a dimensional learning strategy based on the original model to enhance the adaptability and robustness of the model.ResultsThe experimental results show that the Mean Absolute Percent Error (MAPE) of the proposed algorithm is 8.62%, the Mean Absolute Error (MAE) is 1.30% and the Root Mean Square Error (RMSE) is 2.26%. Compared with the traditional Gray Wolf Optimized Support Vector Machine, the errors of the improved model are reduced by 15.27%, 3.33% and 4.70%, respectively.ContributionsOur study demonstrates that extracellular vesicles secreted by the gut microbiota can influence the nervous system via the microbial-gut-brain axis. Furthermore, we found that the extracellular vesicles secreted by the gut microbiota from the probiotic group exert a beneficial therapeutic effect on anxiety and hippocampal neuroinflammation.

Comprehensive power loss analysis for hybrid distribution transformer

Compared with traditional power transformers, Hybrid Distribution Transformers (HDTs) generate higher power losses due to the application of power electronic converters. However, HDTs can apply reactive power compensation as well as three-phase load current unbalance compensation, which leads to line loss reduction of the distribution power grid. When comparing the power losses of HDTs and traditional transformers, it is necessary to comprehensively consider the operational power loss of HDTs and line losses of the distribution network reduced by its converter. This article proposes a comprehensive loss model for the application of HDTs in distribution networks and conducts theoretical calculations on HDT self-losses and distribution network line losses caused by reactive power and three-phase asymmetric load currents. The power losses on the transmission wire of the distribution power grid with the application of HDTs instead of traditional transformers are analyzed. The calculation and simulation results based on parameters such as reactive power, three-phase unbalanced current, and HDT comprehensive loss have verified the correctness of the theoretical analysis.

A Modified Genetic Algorithm for Optimizing the Placement and Sizing of Distributed Generators in Radial Distribution Systems Including Security Analysis

In this paper, a Modified Genetic Algorithm (MGA) combined with ETAP (Electrical Transient Analyzer Program), is proposed to optimize the placement and sizing of Distributed Generation (DG) units while considering multiple objectives, such as improving voltage profiles, reducing line losses, and managing short-circuit levels. These factors are critical for maintaining power quality, system reliability, and overall stability. The MGA approach is validated through simulations using the IEEE 33-bus distribution system, modeled in both MATLAB and ETAP. The results show significant improvements in voltage stability, loss reduction, and short-circuit level management, enhancing energy management and operational efficiency. A comparative analysis with alternative algorithms, including the Bat Algorithm (BA), Bacterial Foraging Optimization Algorithm (BFOA), and Artificial Immune System (AIS), demonstrates that MGA achieves superior convergence speed and accuracy, making it highly effective for DG placement and power system performance optimization.

A Generalized Deep Reinforcement Learning Model for Distribution Network Reconfiguration with Power Flow-Based Action-Space Sampling

Distribution network reconfiguration (DNR) is used by utilities to enhance power system performance in various ways, such as reducing line losses. Conventional DNR algorithms rely on accurate values of network parameters and lack scalability and optimality. To tackle these issues, a new data-driven algorithm based on reinforcement learning is developed for DNR in this paper. The proposed algorithm comprises two main parts. The first part, named action-space sampling, aims at analyzing the network structure, finding all feasible reconfiguration actions, and reducing the size of the action space to only the most optimal actions. In the second part, deep Q-learning (DQN) and dueling DQN methods are used to train an agent to take the best switching actions according to the switch states and loads of the system. The results show that both DQN and dueling DQN are effective in reducing system losses through grid reconfiguration. The proposed methods have faster execution time compared to the conventional methods and are more scalable.

Effect of multi-unit and multi-type DG installation using integrated optimization technique in distribution power system planning

With the rise in load demand, improving the voltage profile and reducing line loss is vital to ensure reliable power delivery to the customer. However, increasing power plant generation capacity is limited by environmental and economic factors, requiring a careful assessment of locally optimal options. Distributed Generation (DG) installation into the electricity grid is one of the reliable remedial actions to ensure a smooth power delivery. Installation of DG requires an optimization process to identify the appropriate placement and sizing. Inaccurate sizing and placement of the DG installation may result to over-compensation or under-compensation phenomena. This paper proposes a novel approach termed the Integrated Immune Moth Flame Evolutionary Programming technique (IIMFEP) for optimizing the installation of DG sources in distribution systems. It handles various scenarios, including multi-DG single-type and multi-DG multi-type installations, with the main objective of minimizing power loss in the system. This technique employs a hybrid approach that combines elements of immune algorithms, moth flame optimization, and evolutionary programming to achieve more accurate and efficient results. Two cases were considered in this study termed Case 1 and Case 2. Results in Case 1 discovered that the optimal sizing and placement of four Type III DGs exhibit the lowest power loss worth 2.74 kW (98.78 % reduction) for the 69-Bus RDS, while for the 118-Bus RDS the power loss is 319.89 kW (75.36 % reduction). In Case Study 2, the combination of DG Types I and III provided the highest power loss reduction. With one DG Type I and two DG Type III units installed, power loss was reduced by 97.15 % to 6.41 kW for the 69-Bus RDS and by 62.01 % to 493.21 kW for the 118-Bus RDS. The proposed IIMFEP managed to alleviate the setback experienced in the traditional EP, AIS and MFO which found to be stuck at local optimum. The IIMFEP method is compared to Moth Flame Optimization, Artificial Immune System and Evolutionary Programming and validated using the IEEE 69-Bus and 118-Bus Radial Distribution Systems, resulting in outstanding performance.

Umbilical Line Securement Bundle to Reduce Line Loss in the Neonate.

Umbilical line migration not only increases the risks of complications but also results in malposition and, ultimately, loss of the umbilical line. To evaluate the use of an umbilical line securement bundle to reduce unintended line discontinuation after line adjustment in the neonate at a single 40-bed Level IV neonatal intensive care unit. A pre-post design of 75 neonates, preimplementation (n=50) and postimplementation (n=25), was analyzed using data collection from the electronic health record. There was a 37.5% absolute reduction in removal of the umbilical line due to malposition after line adjustment utilizing the umbilical line bundle, standardizing the adjustment order, nursing process, and follow-up x-ray evaluation. This absolute reduction has clinical significance although not statistically significant. Provider compliance rates with line adjustment order bundle were 75%, decreasing with additional adjustments (50%). Nursing staff reported comfort with umbilical line management, ranging from 63% to 87% on different tasks. The use of umbilical line bundles reduces rates of line discontinuation due to malposition. The adoption of umbilical line bundles in neonatal intensive care unit practice may help to prevent unintended line discontinuation. There is a need for continued research regarding the use of secondary securement devices for decreased rate of malposition and the timing and methods for surveillance of umbilical line position.

Influence of Ni and Be elements on Al‐Mg‐Si alloys in different states

AbstractTo improve the comprehensive performance of Al‐Mg‐Si alloy conductors in overhead power lines, enhance the energy‐saving and emission‐reduction efficiency of transmission links, and reduce line loss indicators, this paper investigates the effects of trace Ni and Be elements on the electrical conductivity and mechanical properties of Al‐Mg‐Si alloys in the as‐cast, extruded and ageing states, and explores their effects on the microstructure of aluminium alloys in different states through OM, SEM and TEM. The results show that the addition of Ni and Be improves the comprehensive performance of the extruded state of aluminium alloys and greatly increases the tensile strength of the ageing state of aluminium alloys but has some effects on the electrical conductivity. The Ni element is able to refine the grain size of the as‐cast aluminium alloys and extruded aluminium alloys and promotes the precipitation of precipitated phases in the ageing state of aluminium alloys. The Be element has no obvious effect on the grain refinement of cast and extruded aluminium alloys, but it also promotes the precipitation of precipitated phases in ageing aluminium alloys and slows down the growth of the precipitated phases.

Collaborative optimization of reference powers and droop coefficients in DC distribution networks considering flexibility enhancement

In droop-controlled DC distribution networks (DCDNs), the uncertainties of loads and renewable energy powers worsen the system performances. This paper proposes a collaborative optimization method of reference powers and droop coefficients to optimize more objectives that including reducing line losses, improving the voltage level, and enhancing the flexibility of DCDNs. Firstly, a fast and accurate flexibility margin evaluation method is presented for DCDNs, in which the allowable power variation intervals under operational constraints are used to quantify the flexibility margins. The analytic relations of allowable power variation intervals and operational constraints are established by the linear power flow model, and the flexibility margins can be calculated quickly and directly. Secondly, the bi-level collaborative optimization method of reference powers and droop coefficients is proposed to optimize more objectives simultaneously. The reference powers are optimized to improve the voltage level and reduce line power losses in the upper-level optimization, and the droop coefficients are optimized to enhance the system flexibility in the lower-level optimization. Finally, multiple test systems with different topologies are simulated in detail. The case study demonstrates that: 1) The flexibility evaluation method can quantify the margins of operational constraints quickly and accurately. Compared with the bisection method, the calculation time of proposed flexibility evaluation method reduce 99.52% with the error of 1.68%. 2) The proposed collaborative optimization of reference powers and droop coefficients can effectively reduce line losses and the risks of voltage off-limit and VSC overload of DCDN under uncertainties.

Large scale penetration impact of PMS-WTGS on voltage profile and power loss for 5-bus, 330kV system of the Nigerian grid

In recent times, adverse environmental changes and the gradual reduction in fossil fuel deposits is making integration of renewable energy secure global attention. This paper therefore investigates the effect of high penetration of wind power on power loss and voltage profile of 52-bus, 330kV Nigerian grid. Modeling and simulation of the study were successfully done using the Continuation Power Flow method and Power System Analysis Toolbox in the Matrix Laboratory environment. The Ant Colony Optimization (ACO) technique codes were used to determine the best sites and sizes of Permanent Magnet Synchronous-based Wind Turbine Generators (PMS-WTGs) on the grid as nonoptimal placement and size of PMS-WTGs will result into active power losses and poor voltage profile. The ACO and power flow analysis indicated two load buses, Aladja bus and Yola bus as best sites for PMS-WTGs with optimal sizes of 100MW and 197MW respectively. The result shows a decrease in the system's active (42.1%) and reactive (43.9%) power losses while heightening voltage magnitudes of critical buses to statutory values and enhancing the grid power quality. The overall results indicate that integrating 297MW PMS-WTGs improves voltage stability and power loss reduction by maximizing system loadability and reducing line losses.

Network Reconfiguration Framework for CO2 Emission Reduction and Line Loss Minimization in Distribution Networks Using Swarm Optimization Algorithms

This paper presents the development of a generic active distribution network (ADN) operation simulation framework that incorporates selected swarm optimization algorithms (SOAs) for the purpose of reducing CO2 emissions and line loss minimization through network reconfiguration (NR). The framework has been implemented in the ADN of Taipower. Network data, provided by the Distribution Mapping Management System and Distribution Dispatch Control Center (DDCC) of Taipower, were converted into an OpenDSS script to create ADN models. The SOA is integrated into the framework and utilized to determine the statuses of both four-way and two-way switches in the planning and operating stages, in accordance with the proposed multi-objective function and operational constraints. The weightings for these decisions can be customized by distribution operators to meet their specific requirements. In this paper, the weighting for line loss reduction is set to one for minimizing CO2 emissions. The numerical results demonstrate that the proposed ADN framework can recommend a feeder switching scheme to distribution operators, aiming to balance feeder loading and minimize the neutral line current. Finally, this approach leads to reduced line losses and minimizes CO2 emissions. In contrast to relying solely on historical operational experience, this generic ADN reconfiguration framework offers a systematic approach that can significantly contribute to reducing CO2 emissions and enhancing the operational efficiency of ADNs.

Optimal Reactive Power Flow of AC-DC Power System with Shunt Capacitors Using Backtracking Search Algorithm

In this paper, it is proposed that a two-terminal high voltage direct current (HVDC) be integrated into the power system. Line-commutated converter (LCC)-HVDC is used because of its ability to reduce line losses, which improves overall system efficiency. Shunt capacitors also aid in voltage maintenance by compensating for the reactive power demand. In essence, limiting voltage drops in electrical networks promotes a more efficient power transmission and distribution by lowering resistive losses. In power system investigations, it was discovered that the HVDC link and SCB exist separately. So, for the first time, the backtracking search algorithm (BSA) is used to solve the optimal reactive power flow (ORPF) of a power system with a HVDC link and shunt capacitor banks (SCB). Although BSA simulations on a modified IEEE 30 bus yielded successful results, ABC was also utilized for comparing the outcomes of different methods. Overall, three separate cases of the modified IEEE 30 bus system were examined. When the acquired results are compared to other methods, the suggested algorithm is found to be better at concerning effectiveness as well as performance.

Comprehensive analysis of line losses and valuation of energy savings in optimized photovoltaic array subjected to partial shadings

In this manuscript, an attempt is made to reconfigure the conventional total cross-tied (TCT) array through a novel optimized SuDoKu (OPSDK) static reconfiguration technique. This approach helps to reduce the line losses occurring due to increased wire length and simultaneously diminishes the adverse effects of accumulated shadings in close vicinity by diffusing it across the photovoltaic array (PVA). The MATLAB/Simulink platform is used to study the variations in the performance of various existing topologies and the proposed OPSDK PVA model under various shading scenarios such as bottom-right corner, bottom-left corner, top-right corner, top-left corner and drifted-locus centre. The performance is monitored with regard to the specific characteristics viz., % fill-factor, mismatch power losses, % power loss, % efficiency, global maximum power point, maximum voltage, maximum current, local maximum power points (LMPPs), number of LMPPs, misleading power loss, current loss, voltage loss, % execution ratio, % power improvement, % thermal voltage, % power enhancement ratio, line loss and annual energy saving. Theresults show that the proposed OPSDKmethod generates 28.12852 kWh energy units per day, which is maximum when compared to other five topologies viz. SuDoKu (SDK), futoshiki SuDoKu (FSDK), skyscraper SuDoKu (SKYSDK), modified SuDoKu (MSDK), ancient chinese magic square (ACMS). Consequently, the annual income generatedby [9×9] SDK, FSDK, SKYSDK, MSDK, ACMS and OPSDK PVAs is ₹ 150,839.54, ₹ 141,514.52, ₹150,108.08, ₹ 150,751.94, ₹ 150,249.33 and ₹154,003.72, respectively, signifying that OPSDK PVA produces highest income. The extensive analysis signifies that the proposed OPSDK topology succeeds in reducing line losses by 25.62 %, 0.00 %, 37.98 %, 33.43 % and 35.49 % in comparison to SDK, FSDK, SKYSDK, MSDK and ACMS, respectively. The mismatch power losses in power output are also reduced by 643.1 W as compared to the other configurations. The OPSDK technique, thus, proves to be one of the most efficient, effective, optimised and sustainable PVA reconfiguration technique with good power savings and greater economic returns/viability.

A novel apparent power loss based distributed generator siting and sizing method considering dependent loads

In the present paper, it is first established that even though the standard Active Power Loss Sensitivity Factor (APLSF) based technique for Renewable Energy based Distributed Generation (REDG) system excels with respect to many available technical assessment indicators, its performance falls short in case of line loss reduction and power transfer capacity improvement indicators. On further investigation through Dynamic Fault Tree Analysis technique, it is found that the unsatisfactory performance of APLSF stem from neglecting reactive power loss and line reactance. Therefore, a novel apparent power loss augmented technique coined as Dynamic Loss Evaluation Indicator (DLEI) method is proposed here. The suitability of the proposed method is validated on IEEE 33 and 85 bus distribution systems for both voltage and voltage and frequency dependent load models and it is shown that the aforementioned indicators are improved along with the other indicators like voltage profile and voltage stability to name a few. For further validation, contingency and power quality analysis are also carried out and improved performance is observed in DLEI method when compared against the APLSF based method.

Impact Study of the Hetauda-Dhalkewar-Inaruwa Transmission Line on the Operation of Integrated Nepal Power System

Despite Nepal’s abundant hydroelectric resources, a substantial disparity exists between its electricity supply and demand. This discrepancy is exacerbated by the absence of high-voltage transmission lines, hindering efficient power evacuation from a handful of generating plants. This not only incurs financial losses for the utility but also compromises the reliability of the power supply. A prime example is the protracted delay in the construction of the 576 KM long Hetauda-Dhalkebar-Inaruwa 400kV double-circuit Transmission Line, primarily due to challenges posed by local residents unwilling to relinquish their land.The Integrated Nepal Power System (INPS) heavily relies on power generation concentrated in the central mid-hills region. The construction of the Hetauda-Dhalkebar-Inaruwa (HDITL) 400kV double-circuit Transmission Line is crucial for routing power to industrialize these areas, potentially bolstering the national GDP and generating employment opportunities. Furthermore, it is essential to connect the current hydropower output of around 2300 MW to the INPS system via a high-voltage transmission line to maximize its utilization. The HDITL project not only reduces line losses but also enhances grid stability. It facilitates energy export and direct transmission of high-generation power, such as the 456 MW from Upper Tamakoshi, thus saving approximately 400 MW of power and preventing losses for both the Government of Nepal (GoN) and the Nepal Electricity Authority. This research not only calculates the reduction in power and energy losses with the commissioning of HDITL but also assesses its monetary benefits. Utilizing INPS data and Digsilent Power Factory 15.1 for power flow analysis, the study estimates that HDITL can prevent a power loss of about 26.276 MW. Furthermore, it demonstrates that HDITL significantly improves the total generation power factor in INPS, from 0.88 to 0.99, and enhances the voltage profile, underscoring its critical role in Nepal’s energy infrastructure development.

Technical Impacts of Virtual Clean Hydrogen Plants: Promoting Energy Balance and Resolving Transmission Congestion Challenges

This paper presents the VCHP platform as a solution to address PV curtailment and line congestion in scenarios of increasing renewable energy penetration. Solar PV generation profiles and load profiles were generated for three scenarios (2025, 2030, and 2035) using data provided by KPX. Modifications were made to the IEEE 30 Bus model to accurately reflect the Korean power system, including the introduction of PCA and LCA at relevant buses. Line congestion was evaluated using metrics such as TUR, STUR, and TLR. The research findings indicate that integrating the VCHP platform in all scenarios effectively alleviates line congestion, as shown by the TUR remaining below 1. Importantly, the reduction in line losses exceeds the decrease in power flow, demonstrating the effectiveness of VCHP in reducing power losses. The results suggest that as renewable energy sources increase, line congestion issues may arise in the existing power system. However, integrating the proposed VCHP platform is a valuable solution for effectively utilizing surplus PV energy and improving the stability of the power grid. The adoption of such a platform can significantly enhance the operation and management of the power system.

A line loss reduction optimization for renewable energy‐based distribution networks using a probabilistic approach

SummaryThe large integration of distributed generation (DG) and electric vehicles (EVs) facilitates daily life and reduces carbon emissions. However, it brings problems such as increased uncertainty and power electronic permeability to the distribution network. In this context, it is important to solve the line loss optimization problem as closely as possible to the real situation. Therefore, this paper solves the line loss optimization problem based on a probabilistic model of three‐phase unbalanced modern power electrical distribution network. Firstly, the paper proposes a frequency domain model of the distribution network and the optimization problem model. Then, to deal with the uncertainty of the system, the point estimation method (PEM) and Monte Carlo Simulation (MCS) are used. Finally, this paper proposes two optimization schemes considering the power quality when single and multiple DGs are integrated. The simulation results demonstrate that the PEM using the Gram–Charlier series expansion of the fourth‐order statistical moments to estimate the probability density function (PDF) is significantly less time consuming than the traditional MCS method while maintaining accuracy. The comparative analysis reveals that under the optimization scheme with single DG integration, the expected value of system line loss and expected line loss rate are reduced from 283.95 kW to 218.96 kW (22.89% reduction) and from 13.44% to 10.68%, respectively. Under the dual DG integrated optimization scheme, the expected value of line losses and expected line loss rate are reduced from 283.95 kW to 208.88 kW (26.4% reduction) and from 13.44% to 10.25%, respectively. However, after taking the uncertainty into account, the operational reliability of the system has been enhanced under different scenarios. In addition, it is found that the optimization approach incorporating multiple DG units can effectively mitigate the system line loss under diverse operational scenarios while enhancing the system's DG integration capability.

Optimal location of multiple FACTS devices in N-1 contingency conditions using traditional genetic algorithm

<span lang="EN-US">Transmission systems are prone to contingency conditions that would either occur using a generator outage or line outage. Placing and sizing the flexible ac transmission systems (FACTS) devices appropriately can reduce the effects of the contingency condition. This paper optimally locates FACTS devices in a transmission system under the N-1 contingency condition. The genetic algorithm (GA) technique is used to locate different, multiple FACTS devices (thyristor-controlled series capacitor and static VAR compensator) optimally in a power system. This optimization technique is used to locate FACTS devices on the IEEE 9 bus system. MATLAB simulation is developed and checked for both single and multiple FACTS placements. Simulation results obtained for generator outage and line outage are tabulated with the type of FACTS device/rating, location, and generation cost with line loss reduction. The optimized results observed for the cost-optimized FACTS placement problem are found to be satisfactory. The results obtained in the IEEE 9 bus system have shown improvement in a decrease of generation cost and system loss component while placement and sizing of both the FACTS devices.</span>