This document discusses enhancing available transfer capability (ATC) in deregulated electricity markets using flexible AC transmission system (FACTS) devices. It analyzes using thyristor controlled series compensator (TCSC), static VAR compensator (SVC), and unified power flow controller (UPFC) individually and in combinations to boost single area ATC and multi-area ATC. Particle swarm optimization is employed to determine the optimal device settings. The study evaluates ATC enhancement on the IEEE 30 bus and 118 bus test systems for selected bilateral, multilateral, and area transactions, and also calculates the installation costs.
Enhancement of ATC by Optimal Allocation of TCSC and SVC by Using Genetic Alg...IOSR Journals
This document discusses using genetic algorithms to optimize the placement and compensation levels of thyristor controlled series compensators (TCSCs) to enhance available transfer capability (ATC) in transmission networks. TCSCs are flexible alternating current transmission system (FACTS) devices that can control line reactance. The paper proposes using a genetic algorithm to determine the optimal locations and compensation levels of one or two TCSCs to maximize ATC. It describes calculating ATC using multiple load flow simulations while incrementally increasing power transfers until a limit is reached. The genetic algorithm would seek to place and set TCSCs to allow higher power transfers before limits are violated, thus enhancing ATC.
The paper discusses about a hybrid model with an evolutionary algorithm (HEA) for identifying the multi-type flexible AC transmission systems (FACTS) procedures to improve the total transfer capability (TTC). To reduce the loss of power this transferences among various control regions. FACTS devices with Multi objective optimal power flow (OPF) which include TTC to determine a reasonable value without violating system limitations. The results are simulated for FACTS devices with the HEA algorithm which emerges TTC value using an efficient methods using conventional transmission system. The simulation results are obtained by MATLAB/SIMULINK environment.
Optimal Location of Multi-types of FACTS Devices using Genetic Algorithm IJORCS
The problem of improving the voltage profile and reducing power loss in electrical networks is a task that must be solved in an optimal manner. Therefore, placement of FACTS devices in suitable location can lead to control in-line flow and maintain bus voltages in desired level and reducing losses is required. This paper presents one of the heuristic methods i.e. a Genetic Algorithm to seek the optimal location of FACTS devices in a power system. Proposed algorithm is tested on IEEE 30 bus power system for optimal location of multi-type FACTS devices and results are presented.
Penetration of PluginHybrid Electric Vehicles via Distribution NetworkRaja Larik
This paper proposes a model for simulating plug-in hybrid electric vehicle (PHEV) charging loads on a power distribution system and employs a network reconfiguration technique using binary particle swarm optimization to minimize power losses due to high PHEV penetration. The model generates a PHEV load profile based on random battery capacities and charging times. Adding this load to the base system load increases total load by over 600 kW during peak hours. Applying reconfiguration reduces losses by up to 30% compared to no reconfiguration. Results on the IEEE 33-bus test system show reconfiguration effectively lowers losses and improves voltage profiles when accommodating increased PHEV charging demands on the grid.
A hybrid approach for ipfc location and parameters optimization for congestio...eSAT Journals
Abstract
The deregulated power system operation with competitive electricity market environment has been created many challenging tasks to the system operator. The competition with strategic bidding has been resulted for randomness in generation schedule, load withdrawal and power flows across the network. The economic efficiency of electricity market is mainly dependent on network support. In the event of congestion, it is required to alter the base case market settlement and hence the economic inefficiency in terms of congestion cost can occur. In order to anticipate congestion and its consequences in operation, this paper has been considered Interline Power Flow Controller (IPFC).This article proposed a tactical approach for optimal location and then its parameters in Decoupled Power Injection Modeling (DPIM) are optimized using Gravitational Search Algorithm (GSA). The case studies are performed on IEEE 30-bus test system and the results obtained are validating the proposed approach for practical implementations.
Keywords: Deregulated power system, competitive electricity market, congestion management, IPFC, Gravitational Search Algorithm (GSA)
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
This document summarizes two methods for allocating transmission line costs: the Generation Shift Distribution Factor (GSDF) method and the Bialek Tracing method. The GSDF method uses linear power flow approximations to calculate distribution factors that measure the incremental use of transmission lines by generators and loads. These factors can then be used to allocate total fixed transmission costs. The Bialek Tracing method is based on the proportional sharing principle and uses a topological approach to determine the contribution of individual generators or loads to every line flow. Both methods aim to generate appropriate economic signals to recover fixed transmission costs from market participants.
Cost Allocation of Reactive Power Using Matrix Methodology in Transmission Ne...IJAAS Team
This document presents a matrix methodology for allocating the costs of reactive power flows in transmission networks. The methodology traces reactive power flows through the network using Kirchhoff's current law and proportional sharing principles. It then allocates the costs of reactive power to generators and loads using the MVAr-mile method. The methodology is demonstrated on sample 6-bus and IEEE 14-bus test systems. Results show the allocated reactive power flows to different loads and the costs allocated to loads for recovery of total reactive power costs in the transmission network.
Enhancement of ATC by Optimal Allocation of TCSC and SVC by Using Genetic Alg...IOSR Journals
This document discusses using genetic algorithms to optimize the placement and compensation levels of thyristor controlled series compensators (TCSCs) to enhance available transfer capability (ATC) in transmission networks. TCSCs are flexible alternating current transmission system (FACTS) devices that can control line reactance. The paper proposes using a genetic algorithm to determine the optimal locations and compensation levels of one or two TCSCs to maximize ATC. It describes calculating ATC using multiple load flow simulations while incrementally increasing power transfers until a limit is reached. The genetic algorithm would seek to place and set TCSCs to allow higher power transfers before limits are violated, thus enhancing ATC.
The paper discusses about a hybrid model with an evolutionary algorithm (HEA) for identifying the multi-type flexible AC transmission systems (FACTS) procedures to improve the total transfer capability (TTC). To reduce the loss of power this transferences among various control regions. FACTS devices with Multi objective optimal power flow (OPF) which include TTC to determine a reasonable value without violating system limitations. The results are simulated for FACTS devices with the HEA algorithm which emerges TTC value using an efficient methods using conventional transmission system. The simulation results are obtained by MATLAB/SIMULINK environment.
Optimal Location of Multi-types of FACTS Devices using Genetic Algorithm IJORCS
The problem of improving the voltage profile and reducing power loss in electrical networks is a task that must be solved in an optimal manner. Therefore, placement of FACTS devices in suitable location can lead to control in-line flow and maintain bus voltages in desired level and reducing losses is required. This paper presents one of the heuristic methods i.e. a Genetic Algorithm to seek the optimal location of FACTS devices in a power system. Proposed algorithm is tested on IEEE 30 bus power system for optimal location of multi-type FACTS devices and results are presented.
Penetration of PluginHybrid Electric Vehicles via Distribution NetworkRaja Larik
This paper proposes a model for simulating plug-in hybrid electric vehicle (PHEV) charging loads on a power distribution system and employs a network reconfiguration technique using binary particle swarm optimization to minimize power losses due to high PHEV penetration. The model generates a PHEV load profile based on random battery capacities and charging times. Adding this load to the base system load increases total load by over 600 kW during peak hours. Applying reconfiguration reduces losses by up to 30% compared to no reconfiguration. Results on the IEEE 33-bus test system show reconfiguration effectively lowers losses and improves voltage profiles when accommodating increased PHEV charging demands on the grid.
A hybrid approach for ipfc location and parameters optimization for congestio...eSAT Journals
Abstract
The deregulated power system operation with competitive electricity market environment has been created many challenging tasks to the system operator. The competition with strategic bidding has been resulted for randomness in generation schedule, load withdrawal and power flows across the network. The economic efficiency of electricity market is mainly dependent on network support. In the event of congestion, it is required to alter the base case market settlement and hence the economic inefficiency in terms of congestion cost can occur. In order to anticipate congestion and its consequences in operation, this paper has been considered Interline Power Flow Controller (IPFC).This article proposed a tactical approach for optimal location and then its parameters in Decoupled Power Injection Modeling (DPIM) are optimized using Gravitational Search Algorithm (GSA). The case studies are performed on IEEE 30-bus test system and the results obtained are validating the proposed approach for practical implementations.
Keywords: Deregulated power system, competitive electricity market, congestion management, IPFC, Gravitational Search Algorithm (GSA)
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
This document summarizes two methods for allocating transmission line costs: the Generation Shift Distribution Factor (GSDF) method and the Bialek Tracing method. The GSDF method uses linear power flow approximations to calculate distribution factors that measure the incremental use of transmission lines by generators and loads. These factors can then be used to allocate total fixed transmission costs. The Bialek Tracing method is based on the proportional sharing principle and uses a topological approach to determine the contribution of individual generators or loads to every line flow. Both methods aim to generate appropriate economic signals to recover fixed transmission costs from market participants.
Cost Allocation of Reactive Power Using Matrix Methodology in Transmission Ne...IJAAS Team
This document presents a matrix methodology for allocating the costs of reactive power flows in transmission networks. The methodology traces reactive power flows through the network using Kirchhoff's current law and proportional sharing principles. It then allocates the costs of reactive power to generators and loads using the MVAr-mile method. The methodology is demonstrated on sample 6-bus and IEEE 14-bus test systems. Results show the allocated reactive power flows to different loads and the costs allocated to loads for recovery of total reactive power costs in the transmission network.
Genetic algorithm based Different Re-dispatching Scheduling of Generator Unit...IDES Editor
Proper pricing of active power is an important issue
in deregulated power environment. This paper presents a
flexible formulation for determining short run marginal cost
of synchronous generators using genetic algorithm based
different re-dispatching scheduling considering economic load
dispatch as well as optimized loss condition. By integrating
genetic algorithm based solution, problem formulation became
easier. The solution obtained from this methodology is quite
encouraging and useful in the economic point of view and it
has been observed that for calculating short run marginal
cost, generator re-dispatching solution is better than classical
method solution. The proposed approach is efficient in the
real time application and allows for carrying out active power
pricing independently. The paper includes test result of IEEE
30 bus standard test system.
Energy Audit And Management Of Induction Motor Using Field Test And Genetic A...IDES Editor
This paper proposes an economical method that
can be used by industries/plants to make a right decision in
replacing the inefficient induction motors with efficient
ones. proposed method focuses on the field efficiency of
motors without the needs for removing motors and
measuring the output power. The use of a few sets of
measured data from field test coupled with the genetic
algorithms using one operating point for evaluating motor
equivalent circuit parameters instead of using the no load
and blocked-rotor tests is proposed. Test results indicate
that this method has a high accuracy, then it is suitable for
conducting onsite energy audit of motors in order to project
cost savings and payback and to support a confidence
decision regarding the investment in higher efficiency
motors.
Multi-Objective based Optimal Energy and Reactive Power Dispatch in Deregulat...IJECEIAES
This paper presents a day-ahead (DA) multi-objective based joint energy and reactive power dispatch in the deregulated electricity markets. The traditional social welfare in the centralized electricity markets comprises of customers benefit function and the cost function of active power generation. In this paper, the traditional social welfare is modified to incorporate the cost of both active and reactive power generation. Here, the voltage dependent load modeling is used. This paper brings out the unsuitability of traditional single objective functions, e.g., social welfare maximization (SWM), loss minimization (LM) due to the reduction of amount of load served. Therefore, a multi-objective based optimization is required. This paper proposes four objectives, i.e., SWM, load served maximization (LSM), LM and voltage stability enhancement index (VSEI); and these objectives can be combined as per the operating condition. The simulation studies are performed on IEEE 30 bus test system by considering the both traditional constant load modeling and the proposed voltage dependent load modeling.
Optimal Placement of FACTS Controllers for Congestion Management in the Dereg...IJECEIAES
This paper proposes a methodology to determine the optimal location of Flexible AC Transmission System (FACTS) controllers for Congestion Management (CM) in the restructured electrical power system. An approach to find the optimum placement of Thyristor Controlled Phase Angle Regulators (TCPAR) and Thyristor Controlled Series Compensators (TCSC) has been proposed in this paper. The proposed methodology is based on the sensitivity of transmission loss which a controller is installed. The total system losses and the power flows are considered as the performance indices. The traditional optimal power flow (OPF) problem is modified to include the market players, who will compete and trade simultaneously, ensuring the system operation stays within the security limits. In this paper, pool and bilateral contracts are considered. Here, an integrated methodology is proposed that includes the FACTS Controllers in a bilateral contract framework to maintain the system security and to minimize the deviations from the contractual requirements. The simulation results on IEEE 30 bus system show that the sensitivity factors could be used effectively for the optimal location of FACTS controllers in response to the required objectives.
T04201162168Optimal Allocation of FACTS Device with Multiple Objectives Using...IJMER
In this paper Multi objective functions are simultaneously considered as the indexes of the system performance minimize total generation fuel cost and maximize system load-ability within system security margin. To find the optimal location and optimal value for Thyristor Controlled Series Compensator (TCSC) using optimization technique Genetic Algorithm (GA) to maximize system load-ability and minimize the system losses considering multi objectives optimization approach. A GA based Optimal Power Flow (OPF) is proposed to determine the type of FACTS (Flexible AC Transmission system) controllers, its optimal location and rating of the devices in power systems. The value of TCSC and line losses is applied as measure of power system performance. The type of FACTS controllers are used and modeled for steady-state studies: TCSC, minimize total generation fuel cost and maximize system load-ability within system security margin. Simulations will be carrying on IEEE30 bus power system for type of FACTS devices.
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
The document summarizes a comprehensive transmission expansion planning (CTEP) strategy proposed for developing countries. The strategy considers physical and operational constraints in the transmission system like power balance, generation limits, transmission line flow limits, right-of-way constraints, and voltage limits. The CTEP is applied to the Garver 6-bus test system considering various contingencies such as generator outages, line outages, load changes, and identifies optimal transmission line expansions. The CTEP aims to achieve optimal planning costs while improving reliability and reducing transmission losses. AC load flow is used to evaluate the CTEP using the Newton-Raphson method.
This document presents a methodology for allocating the cost of transmission networks among generators and demands. It proposes using an impedance matrix (Zbus) method which relies on circuit theory rather than arbitrary cost allocation principles. A case study using the IEEE 24-bus test system is presented to illustrate how the Zbus method works. Key conclusions are that the Zbus method exhibits a desirable proximity effect by allocating most costs to generators and demands near the lines, is independent of slack bus selection, and does not require pre-defining cost sharing proportions between generators and demands.
A MULTIPURPOSE MATRICES METHODOLOGY FOR TRANSMISSION USAGE, LOSS AND RELIABIL...ecij
In the era of power system restructuring there is a need of simplified method which provides a complete allocation of usage, transmission losses and transmission reliability margin. In this paper, authors presents a combined multipurpose matrices methodology for Transmission usage, transmission loss and transmission reliability margin allocation. Proposed methodology is simple and easy to implement on large power system. A modified Kirchhoff matrix is used for allocation purpose. A sample 6 bus system is used to demonstrate the feasibility of proposed methodology.
Enhancements of Extended Locational Marginal Pricing – Advancing Practical Im...Power System Operation
Price formation is critical to efficient wholesale electricity markets that support reliable operation and efficient investment. The Midcontinent Independent System Operator (MISO) developed the Extended Locational Marginal Pricing (ELMP) with the goal of more completely reflecting resource costs and generally improving price formation to better incent market participation. MISO developed ELMP based on the mathematical concept of convex hull. However, considering the computational challenges and the existing market structure, MISO implemented an approximate version of ELMP. This paper presents enhancements to ELMP to bring the practical implementation of ELMP closer to the theoretical ideal and to achieve greater benefits of ELMP in production. The Special Ordered Set of Type Two (SOS2) piece-wise linear cost function formulation is used to tighten the approximation of, and under certain conditions exactly match, the convex hull of the cost function. Regulation commitment logic is also enhanced to maintain optimality under degeneracy conditions while providing flexibility for real-time regulation scheduling and pricing. Simulation results on the MISO system illustrate expected benefits. With the increasing interests in inter-temporal constraints, the on-going work on ELMP ramp modelling is also discussed.
Performance of CBR Traffic on Node Overutilization in MANETsRSIS International
Mobile Ad hoc networks (MANETs) are power constrained since nodes are operated with limited battery supply. The important technical challenge is to avoid the node overutilization and increase the energy efficiency of each node with increasing traffic. If a node runs out of battery, its ability to route the traffic gets affected and hence, the network lifetime. There has been considerable progress in the battery technology, but not in par with the semiconductor technology. There are various techniques adopt the different approaches to achieve energy efficiency. The proposed approach uses a cost metric for path selection, which is a function of residual battery and current traffic load at a node. Further, the simulation and performance is carried through Qualnet network simulator. From the simulation results, it is observed that the proposed scheme has lower node overutilization with the less CBR connections.
Transmission Congestion Management by Using Series Facts Devices and Changing...IJMER
This document summarizes two methods for managing transmission congestion in a deregulated power system: 1) Using a thyristor-controlled series capacitor (TCSC) device and 2) Changing the participation factors of generators. It first describes modelling the TCSC device and selecting its optimal location using sensitivity analysis to minimize total reactive power losses. It then explains using transmission load relief (TLR) sensitivities to identify loads to curtail. The methods are demonstrated on modified IEEE 5-bus and 9-bus test systems, showing congestion is relieved when applying the TCSC and adjusting load participation factors.
ENHANCEMENT OF FUNDAMENTAL RMS OUTPUT VOLTAGE OF 5-LEVEL CASCADED H-BRIDGE MU...IAEME Publication
Cascaded H-bridge Multilevel Inverter (CHBMLI) is the most suitable topology for the PV power converters. In this paper an effort has been made to increase the performance of CHBMLI by improving the fundamental Root Mean Square (RMS) value of the output voltage. This work proposes a Modified Multi Carrier PWM (MMCPWM) technique where, reference sine wave has been replaced by ellipse wave, resulting in enhanced performances on the fundamental rms output voltage and lower Total Harmonic Distortion (THD). Analysis of single phase 5-level CHBMLI with and without load are carried for the different Multi Carrier PWM (MCPWM) techniques.
USAGE BASED COST ALLOCATION TECHNIQUE FOR EHV NETWORKS USING NON-LINEAR UTILI...ELELIJ
This document presents a modified Amp-Mile method for allocating the embedded costs of extra high voltage (EHV) networks. The key modifications include:
1) Using non-linear current sensitivity factors (current utility factors) instead of assuming linear sensitivities.
2) Introducing the concept of dispersed slack buses to better model how load and generation variations impact power flows.
3) Using a Newton Raphson load flow algorithm to more accurately calculate the current sensitivity factors.
4) Allowing the sensitivity to load variations to differ from the sensitivity to generation variations, rather than assuming they are equal in magnitude but opposite in sign.
The method is demonstrated on a 6 bus power system
GENCO Optimal Bidding Strategy and Profit Based Unit Commitment using Evolutio...IJECEIAES
In deregulated electricity markets, generation companies (GENCOs) make unit com- mitment (UC) decisions based on a profit maximization objective in what is termed profit based unit commitment (PBUC). PBUC is done for the GENCO’s demand which is a summation of its bilateral demand and allocations from the spot energy market. While the bilateral demand is known, allocations from the spot energy market depend on the GENCO’s bidding strategy. A GENCO thus requires an optimal bidding strategy (OBS) which when combined with a PBUC approach would maximize operating profits. In this paper, a solution of the combined OBS-PBUC problem is presented. An evolutionary particle swarm optimization (EPSO) algorithm is implemented for solving the optimization problem. Simulation results carried out for a test power system with GENCOs of differing market strengths show that the optimal bidding strategy depends on the GENCO’s market power. Larger GENCOs with significant market power would typically bid higher to raise market clearing prices while smaller GENCOs would typically bid lower to capture a larger portion of the spot market demand. It is also illustrated that the proposed EPSO algorithm has a better performance in terms of solution quality than the classical PSO algorithm.
The document discusses the evolution of transmission pricing in India and the need for changes to the pricing framework. It outlines the changing structure of the Indian power sector, from vertically integrated utilities to multiple regional and inter-regional transmission service providers. The key principles and mechanisms for determining point of charge transmission charges and losses are described, including the collection of technical and commercial information from various entities and the use of power flow analysis to estimate allocation of transmission costs and losses at different nodes.
This document summarizes a journal article that proposes a peak load pricing algorithm for dynamic radio spectrum management. It begins by introducing the concepts of dynamic spectrum access and a harmonized usage band (HUB) reserved for controlling dynamic spectrum access. It then describes climax load charging (CLC), a pricing model used by utilities where higher prices are charged during peak demand periods and lower prices during off-peak periods. The authors suggest applying CLC and peak load pricing theory to set spectrum prices in the HUB, with the optimal price determined by operating costs, the cost of additional capacity, and willingness to pay.
A Novel Idea of Dynamic Radio Spectrum Management Using Peak Load Pricing Al...Editor Jacotech
This document summarizes a research paper that proposes a Peak Load Spectrum Pricing (PLSP) algorithm for dynamic radio spectrum management. The PLSP algorithm uses peak load pricing concepts from economics to set spectrum prices. It calculates optimal prices for different time periods based on factors like operating costs, demand levels, and willingness to pay. The algorithm has five phases: request submission, pricing model determination, price calculation, auction, and spectrum allocation. It determines prices for both peak and off-peak periods, using auctions during peaks and peak load charging during off-peaks. The goal is to allocate spectrum efficiently while considering multiple factors like costs, demand, and fairness. The paper argues the PLSP algorithm provides advantages over single-price
This document discusses the use of PLEXOS software for modeling electricity and natural gas markets in the United States. It provides background on deregulated electricity markets operated by Independent System Operators, including two-settlement energy markets, capacity markets, and ancillary service markets. PLEXOS can simulate these complex multi-horizon markets, and additionally model gas-electric coordination and integration of renewables through sub-hourly modeling of energy and ancillary services. The document lists PLEXOS capabilities relevant to electricity market planning objectives and ongoing challenges around resource adequacy, environmental policies, and reliability in the US.
Recently various soft switching techniques have been developed for various DC-DC based LED drivers. Typical driver circuits in the market have efficiency between 80% - 95% with majority having efficiency between 80% - 90%. Various topologies and strategies are available to obtain the best performance. A comparison and discussion of different buck and floating buck topologies used as driver in LED lighting application are presented in this paper.
This document discusses using fuzzy logic to optimize the placement of Thyristor Controlled Series Capacitors (TCSC) devices for congestion management in deregulated electricity markets. TCSC devices can control power flows and enhance transmission capacity. The document models TCSC devices and transmission lines. It develops fuzzy logic rules based on bus voltage and power loss to determine the optimal bus to place TCSC devices. The method was tested on the IEEE 14-bus system to demonstrate its effectiveness for static congestion management.
This document summarizes a research paper that proposes using a genetic algorithm to optimize the placement of FACTS devices (TCSC and SVC) to maximize available transfer capability (ATC) and minimize contingencies in a power system. It first provides background on ATC and FACTS devices. It then describes modeling TCSC and SVC and constructing the genetic algorithm. The algorithm is tested on a two-area 11 bus power system model. Results show that optimally placing TCSC and SVC using the genetic algorithm can increase ATC and reduce contingencies compared to having no FACTS devices.
ATC for congestion management in deregulated power systemBhargav Pandya
This document discusses congestion management in deregulated power systems through enhancement of available transfer capacity (ATC) using flexible AC transmission system (FACTS) devices. It proposes a new set of AC sensitivity factors called AC power transfer congestion distribution factors (ACPTCDF) to calculate ATC and identify the most congested transmission line. FACTS devices like UPFC can then be optimally placed to enhance ATC and relieve transmission congestion while maintaining system security and stability constraints. The document provides background on deregulation, open access, congestion management, ATC calculation methodology, and the role of various FACTS technologies to improve power transfer capability.
Genetic algorithm based Different Re-dispatching Scheduling of Generator Unit...IDES Editor
Proper pricing of active power is an important issue
in deregulated power environment. This paper presents a
flexible formulation for determining short run marginal cost
of synchronous generators using genetic algorithm based
different re-dispatching scheduling considering economic load
dispatch as well as optimized loss condition. By integrating
genetic algorithm based solution, problem formulation became
easier. The solution obtained from this methodology is quite
encouraging and useful in the economic point of view and it
has been observed that for calculating short run marginal
cost, generator re-dispatching solution is better than classical
method solution. The proposed approach is efficient in the
real time application and allows for carrying out active power
pricing independently. The paper includes test result of IEEE
30 bus standard test system.
Energy Audit And Management Of Induction Motor Using Field Test And Genetic A...IDES Editor
This paper proposes an economical method that
can be used by industries/plants to make a right decision in
replacing the inefficient induction motors with efficient
ones. proposed method focuses on the field efficiency of
motors without the needs for removing motors and
measuring the output power. The use of a few sets of
measured data from field test coupled with the genetic
algorithms using one operating point for evaluating motor
equivalent circuit parameters instead of using the no load
and blocked-rotor tests is proposed. Test results indicate
that this method has a high accuracy, then it is suitable for
conducting onsite energy audit of motors in order to project
cost savings and payback and to support a confidence
decision regarding the investment in higher efficiency
motors.
Multi-Objective based Optimal Energy and Reactive Power Dispatch in Deregulat...IJECEIAES
This paper presents a day-ahead (DA) multi-objective based joint energy and reactive power dispatch in the deregulated electricity markets. The traditional social welfare in the centralized electricity markets comprises of customers benefit function and the cost function of active power generation. In this paper, the traditional social welfare is modified to incorporate the cost of both active and reactive power generation. Here, the voltage dependent load modeling is used. This paper brings out the unsuitability of traditional single objective functions, e.g., social welfare maximization (SWM), loss minimization (LM) due to the reduction of amount of load served. Therefore, a multi-objective based optimization is required. This paper proposes four objectives, i.e., SWM, load served maximization (LSM), LM and voltage stability enhancement index (VSEI); and these objectives can be combined as per the operating condition. The simulation studies are performed on IEEE 30 bus test system by considering the both traditional constant load modeling and the proposed voltage dependent load modeling.
Optimal Placement of FACTS Controllers for Congestion Management in the Dereg...IJECEIAES
This paper proposes a methodology to determine the optimal location of Flexible AC Transmission System (FACTS) controllers for Congestion Management (CM) in the restructured electrical power system. An approach to find the optimum placement of Thyristor Controlled Phase Angle Regulators (TCPAR) and Thyristor Controlled Series Compensators (TCSC) has been proposed in this paper. The proposed methodology is based on the sensitivity of transmission loss which a controller is installed. The total system losses and the power flows are considered as the performance indices. The traditional optimal power flow (OPF) problem is modified to include the market players, who will compete and trade simultaneously, ensuring the system operation stays within the security limits. In this paper, pool and bilateral contracts are considered. Here, an integrated methodology is proposed that includes the FACTS Controllers in a bilateral contract framework to maintain the system security and to minimize the deviations from the contractual requirements. The simulation results on IEEE 30 bus system show that the sensitivity factors could be used effectively for the optimal location of FACTS controllers in response to the required objectives.
T04201162168Optimal Allocation of FACTS Device with Multiple Objectives Using...IJMER
In this paper Multi objective functions are simultaneously considered as the indexes of the system performance minimize total generation fuel cost and maximize system load-ability within system security margin. To find the optimal location and optimal value for Thyristor Controlled Series Compensator (TCSC) using optimization technique Genetic Algorithm (GA) to maximize system load-ability and minimize the system losses considering multi objectives optimization approach. A GA based Optimal Power Flow (OPF) is proposed to determine the type of FACTS (Flexible AC Transmission system) controllers, its optimal location and rating of the devices in power systems. The value of TCSC and line losses is applied as measure of power system performance. The type of FACTS controllers are used and modeled for steady-state studies: TCSC, minimize total generation fuel cost and maximize system load-ability within system security margin. Simulations will be carrying on IEEE30 bus power system for type of FACTS devices.
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
The document summarizes a comprehensive transmission expansion planning (CTEP) strategy proposed for developing countries. The strategy considers physical and operational constraints in the transmission system like power balance, generation limits, transmission line flow limits, right-of-way constraints, and voltage limits. The CTEP is applied to the Garver 6-bus test system considering various contingencies such as generator outages, line outages, load changes, and identifies optimal transmission line expansions. The CTEP aims to achieve optimal planning costs while improving reliability and reducing transmission losses. AC load flow is used to evaluate the CTEP using the Newton-Raphson method.
This document presents a methodology for allocating the cost of transmission networks among generators and demands. It proposes using an impedance matrix (Zbus) method which relies on circuit theory rather than arbitrary cost allocation principles. A case study using the IEEE 24-bus test system is presented to illustrate how the Zbus method works. Key conclusions are that the Zbus method exhibits a desirable proximity effect by allocating most costs to generators and demands near the lines, is independent of slack bus selection, and does not require pre-defining cost sharing proportions between generators and demands.
A MULTIPURPOSE MATRICES METHODOLOGY FOR TRANSMISSION USAGE, LOSS AND RELIABIL...ecij
In the era of power system restructuring there is a need of simplified method which provides a complete allocation of usage, transmission losses and transmission reliability margin. In this paper, authors presents a combined multipurpose matrices methodology for Transmission usage, transmission loss and transmission reliability margin allocation. Proposed methodology is simple and easy to implement on large power system. A modified Kirchhoff matrix is used for allocation purpose. A sample 6 bus system is used to demonstrate the feasibility of proposed methodology.
Enhancements of Extended Locational Marginal Pricing – Advancing Practical Im...Power System Operation
Price formation is critical to efficient wholesale electricity markets that support reliable operation and efficient investment. The Midcontinent Independent System Operator (MISO) developed the Extended Locational Marginal Pricing (ELMP) with the goal of more completely reflecting resource costs and generally improving price formation to better incent market participation. MISO developed ELMP based on the mathematical concept of convex hull. However, considering the computational challenges and the existing market structure, MISO implemented an approximate version of ELMP. This paper presents enhancements to ELMP to bring the practical implementation of ELMP closer to the theoretical ideal and to achieve greater benefits of ELMP in production. The Special Ordered Set of Type Two (SOS2) piece-wise linear cost function formulation is used to tighten the approximation of, and under certain conditions exactly match, the convex hull of the cost function. Regulation commitment logic is also enhanced to maintain optimality under degeneracy conditions while providing flexibility for real-time regulation scheduling and pricing. Simulation results on the MISO system illustrate expected benefits. With the increasing interests in inter-temporal constraints, the on-going work on ELMP ramp modelling is also discussed.
Performance of CBR Traffic on Node Overutilization in MANETsRSIS International
Mobile Ad hoc networks (MANETs) are power constrained since nodes are operated with limited battery supply. The important technical challenge is to avoid the node overutilization and increase the energy efficiency of each node with increasing traffic. If a node runs out of battery, its ability to route the traffic gets affected and hence, the network lifetime. There has been considerable progress in the battery technology, but not in par with the semiconductor technology. There are various techniques adopt the different approaches to achieve energy efficiency. The proposed approach uses a cost metric for path selection, which is a function of residual battery and current traffic load at a node. Further, the simulation and performance is carried through Qualnet network simulator. From the simulation results, it is observed that the proposed scheme has lower node overutilization with the less CBR connections.
Transmission Congestion Management by Using Series Facts Devices and Changing...IJMER
This document summarizes two methods for managing transmission congestion in a deregulated power system: 1) Using a thyristor-controlled series capacitor (TCSC) device and 2) Changing the participation factors of generators. It first describes modelling the TCSC device and selecting its optimal location using sensitivity analysis to minimize total reactive power losses. It then explains using transmission load relief (TLR) sensitivities to identify loads to curtail. The methods are demonstrated on modified IEEE 5-bus and 9-bus test systems, showing congestion is relieved when applying the TCSC and adjusting load participation factors.
ENHANCEMENT OF FUNDAMENTAL RMS OUTPUT VOLTAGE OF 5-LEVEL CASCADED H-BRIDGE MU...IAEME Publication
Cascaded H-bridge Multilevel Inverter (CHBMLI) is the most suitable topology for the PV power converters. In this paper an effort has been made to increase the performance of CHBMLI by improving the fundamental Root Mean Square (RMS) value of the output voltage. This work proposes a Modified Multi Carrier PWM (MMCPWM) technique where, reference sine wave has been replaced by ellipse wave, resulting in enhanced performances on the fundamental rms output voltage and lower Total Harmonic Distortion (THD). Analysis of single phase 5-level CHBMLI with and without load are carried for the different Multi Carrier PWM (MCPWM) techniques.
USAGE BASED COST ALLOCATION TECHNIQUE FOR EHV NETWORKS USING NON-LINEAR UTILI...ELELIJ
This document presents a modified Amp-Mile method for allocating the embedded costs of extra high voltage (EHV) networks. The key modifications include:
1) Using non-linear current sensitivity factors (current utility factors) instead of assuming linear sensitivities.
2) Introducing the concept of dispersed slack buses to better model how load and generation variations impact power flows.
3) Using a Newton Raphson load flow algorithm to more accurately calculate the current sensitivity factors.
4) Allowing the sensitivity to load variations to differ from the sensitivity to generation variations, rather than assuming they are equal in magnitude but opposite in sign.
The method is demonstrated on a 6 bus power system
GENCO Optimal Bidding Strategy and Profit Based Unit Commitment using Evolutio...IJECEIAES
In deregulated electricity markets, generation companies (GENCOs) make unit com- mitment (UC) decisions based on a profit maximization objective in what is termed profit based unit commitment (PBUC). PBUC is done for the GENCO’s demand which is a summation of its bilateral demand and allocations from the spot energy market. While the bilateral demand is known, allocations from the spot energy market depend on the GENCO’s bidding strategy. A GENCO thus requires an optimal bidding strategy (OBS) which when combined with a PBUC approach would maximize operating profits. In this paper, a solution of the combined OBS-PBUC problem is presented. An evolutionary particle swarm optimization (EPSO) algorithm is implemented for solving the optimization problem. Simulation results carried out for a test power system with GENCOs of differing market strengths show that the optimal bidding strategy depends on the GENCO’s market power. Larger GENCOs with significant market power would typically bid higher to raise market clearing prices while smaller GENCOs would typically bid lower to capture a larger portion of the spot market demand. It is also illustrated that the proposed EPSO algorithm has a better performance in terms of solution quality than the classical PSO algorithm.
The document discusses the evolution of transmission pricing in India and the need for changes to the pricing framework. It outlines the changing structure of the Indian power sector, from vertically integrated utilities to multiple regional and inter-regional transmission service providers. The key principles and mechanisms for determining point of charge transmission charges and losses are described, including the collection of technical and commercial information from various entities and the use of power flow analysis to estimate allocation of transmission costs and losses at different nodes.
This document summarizes a journal article that proposes a peak load pricing algorithm for dynamic radio spectrum management. It begins by introducing the concepts of dynamic spectrum access and a harmonized usage band (HUB) reserved for controlling dynamic spectrum access. It then describes climax load charging (CLC), a pricing model used by utilities where higher prices are charged during peak demand periods and lower prices during off-peak periods. The authors suggest applying CLC and peak load pricing theory to set spectrum prices in the HUB, with the optimal price determined by operating costs, the cost of additional capacity, and willingness to pay.
A Novel Idea of Dynamic Radio Spectrum Management Using Peak Load Pricing Al...Editor Jacotech
This document summarizes a research paper that proposes a Peak Load Spectrum Pricing (PLSP) algorithm for dynamic radio spectrum management. The PLSP algorithm uses peak load pricing concepts from economics to set spectrum prices. It calculates optimal prices for different time periods based on factors like operating costs, demand levels, and willingness to pay. The algorithm has five phases: request submission, pricing model determination, price calculation, auction, and spectrum allocation. It determines prices for both peak and off-peak periods, using auctions during peaks and peak load charging during off-peaks. The goal is to allocate spectrum efficiently while considering multiple factors like costs, demand, and fairness. The paper argues the PLSP algorithm provides advantages over single-price
This document discusses the use of PLEXOS software for modeling electricity and natural gas markets in the United States. It provides background on deregulated electricity markets operated by Independent System Operators, including two-settlement energy markets, capacity markets, and ancillary service markets. PLEXOS can simulate these complex multi-horizon markets, and additionally model gas-electric coordination and integration of renewables through sub-hourly modeling of energy and ancillary services. The document lists PLEXOS capabilities relevant to electricity market planning objectives and ongoing challenges around resource adequacy, environmental policies, and reliability in the US.
Recently various soft switching techniques have been developed for various DC-DC based LED drivers. Typical driver circuits in the market have efficiency between 80% - 95% with majority having efficiency between 80% - 90%. Various topologies and strategies are available to obtain the best performance. A comparison and discussion of different buck and floating buck topologies used as driver in LED lighting application are presented in this paper.
This document discusses using fuzzy logic to optimize the placement of Thyristor Controlled Series Capacitors (TCSC) devices for congestion management in deregulated electricity markets. TCSC devices can control power flows and enhance transmission capacity. The document models TCSC devices and transmission lines. It develops fuzzy logic rules based on bus voltage and power loss to determine the optimal bus to place TCSC devices. The method was tested on the IEEE 14-bus system to demonstrate its effectiveness for static congestion management.
This document summarizes a research paper that proposes using a genetic algorithm to optimize the placement of FACTS devices (TCSC and SVC) to maximize available transfer capability (ATC) and minimize contingencies in a power system. It first provides background on ATC and FACTS devices. It then describes modeling TCSC and SVC and constructing the genetic algorithm. The algorithm is tested on a two-area 11 bus power system model. Results show that optimally placing TCSC and SVC using the genetic algorithm can increase ATC and reduce contingencies compared to having no FACTS devices.
ATC for congestion management in deregulated power systemBhargav Pandya
This document discusses congestion management in deregulated power systems through enhancement of available transfer capacity (ATC) using flexible AC transmission system (FACTS) devices. It proposes a new set of AC sensitivity factors called AC power transfer congestion distribution factors (ACPTCDF) to calculate ATC and identify the most congested transmission line. FACTS devices like UPFC can then be optimally placed to enhance ATC and relieve transmission congestion while maintaining system security and stability constraints. The document provides background on deregulation, open access, congestion management, ATC calculation methodology, and the role of various FACTS technologies to improve power transfer capability.
TCSC Placement Problem Solving Using Hybridization of ABC and DE Algorithmpaperpublications3
Abstract: Flexible Alternating Current Transmission Systems (FACTS) devices represents a technological development in electrical power systems to have a tendency to generate the power with minimum price and less time that fulfill our requirement according to our need. Now a days Flexible AC Transmission System (FACTS) devices play a vital role in boost the power of system performance and power transfer capability. TCSC is an important member of family. In practical TCSC implementation, several such basic compensators may be connected in series to obtain the desired voltage rating and operating characteristics, so its placement is very important. This paper represent a meta heuristic hybrid Algorithm of Artificial Bee Colony (ABC) and Differential Evolution (DE) for finding the best placement and parameter setting of Thyristor Controlled Series capacitor to attain optimum power flow (OPF) of grid network. The proposed technique is tested at IEEE-30 bus test System. Result shows that the selected technique is one of the best for placement of TCSC for Secured optimum Power Flow (OPF).
Keywords: Optimal placement, Severity index, stressed power system, System loadability, TCSC, Hybrid DE/ABC.
Title: TCSC Placement Problem Solving Using Hybridization of ABC and DE Algorithm
Author: Ritesh Diwan, Preeti Sahu
ISSN 2349-7815
International Journal of Recent Research in Electrical and Electronics Engineering (IJRREEE)
Paper Publications
Power Quality Improvement in Power System using UPFCijtsrd
Occurrence of a fault in a power system causes transients. To stabilize the system, Power System Stabilizer (PSS) and Automatic Voltage Regulator (AVR) are used. Load flow analysis is done to analyze the transients introduced in the system due to the occurrence of faults. The Flexible Alternating Current Transmission (FACTS) devices such as UPFC are becoming important in suppressing power system oscillations and improving system damping. The UPFC is a solid-state device, which can be used to control the active and reactive power. This paper considers a power system as a case study for investigating the performance of UPFC is achieving stability. By using a UPFC the oscillation introduced by the faults, the voltage deviations and speed deviations can be damped out quickly than a system without a UPFC. The effectiveness of UPFC in suppressing power system oscillation is investigated by analyzing their voltage deviations and reactive power support in this paper. A proportional integral (PI) controller has been employed for the UPFC. It is also shown that a UPFC can control independently the real and reactive power flow in a transmission line. Navneet Kaur | Gagan Deep Yadav"Power Quality Improvement in Power System using UPFC" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-1 , December 2017, URL: http://www.ijtsrd.com/papers/ijtsrd7139.pdf http://www.ijtsrd.com/engineering/electrical-engineering/7139/power-quality-improvement-in-power-system-using-upfc/navneet-kaur
This paper proposes using a genetic algorithm to determine the optimal location of a thyristor controlled series capacitor (TCSC) device to enhance available transfer capability (ATC) between source and sink areas in a deregulated power system. The paper simulates placing a TCSC in the IEEE 14-bus test system and uses repeated power flow calculations to compute the ATC with and without the TCSC to determine how much it can enhance transmission capacity.
DETERMINISTIC APPROACH AVAILABLE TRANSFER CAPABILITY (ATC) CALCULATION METHODSRaja Larik
This document discusses three deterministic methods for calculating Available Transfer Capability (ATC): Optimal Power Flow (OPF), Continuation Power Flow (CPF), and Power Transfer Distribution Factors (PTDF). OPF aims to maximize generation and load while respecting constraints. CPF traces power system behavior under load/generation variations using repeated power flow solutions. PTDF provides quick estimates of line flow changes based on generation changes but is not very accurate. The document analyzes the principles, advantages, and limitations of each method.
This document discusses the calculation of available transfer capability (ATC) using AC power transfer distribution factors (AC PTDFs). It begins by defining ATC and explaining that ATC determination is important for competitive electricity markets. It then discusses previous methods for calculating ATC and their limitations. The document proposes using AC PTDFs calculated from power flow sensitivities and Jacobian matrices to determine ATC for single and simultaneous transactions. It explains the methodology and presents encouraging results from testing it on the IEEE 24 bus system.
Optimal Placement of TCSC and SVC Using PSOIOSR Journals
This document summarizes a research paper that proposes using a particle swarm optimization technique to determine the optimal placement of TCSC and SVC devices on power systems. The objective is to minimize a cost function that considers the costs of installing the devices, load bus voltage deviations from nominal values, and line loadings. The paper formulates the objective function and describes models for TCSC and SVC devices. It then provides an overview of the particle swarm optimization technique before describing the algorithm used to apply PSO to determine the optimal location and sizing of TCSC and SVC devices on IEEE 14-bus, 30-bus and 57-bus test systems while considering different load levels. Simulation results are presented to demonstrate the method.
This document summarizes a paper that presents a novel method for determining the optimal location of Flexible AC Transmission System (FACTS) controllers in a multi-machine power system using a Fuzzy Controlled Genetic Algorithm (FCGA). The proposed algorithm aims to simultaneously optimize the location, type, and rated values of FACTS controllers while minimizing the overall system cost, which includes generation and investment costs. The algorithm is tested on IEEE 14-bus and 30-bus test systems, incorporating thyristor-controlled series compensator (TCSC) and unified power flow controller (UPFC) devices. Simulation results show the obtained solution is feasible and accurate for solving the optimal power flow problem.
Best Power Surge Using Fuzzy Controlled Genetic TechniqueIOSR Journals
This document presents a novel method for optimizing power surge in a multi-machine power system using a fuzzy controlled genetic algorithm. The algorithm simultaneously optimizes the location, type, and rating of Flexible AC Transmission System (FACTS) controllers to minimize overall system cost, which includes generation and investment costs. Thyristor Controlled Series Compensator (TCSC) and Unified Power Flow Controller (UPFC) are considered as FACTS controllers. The algorithm uses a genetic algorithm and fuzzy logic to determine optimal FACTS controller placements and settings while satisfying power flow and voltage constraints. Simulation results on IEEE 14-bus and 30-bus test systems show feasible and accurate solutions are obtained for optimal power flow problems when incorporating
IRJET- Transmission Line Congestion Management using Hybrid Fish-Bee Algorith...IRJET Journal
This document discusses transmission line congestion management using a hybrid Fish-Bee algorithm with Interline Power Flow Controller (IPFC). It begins with an abstract that introduces the problem of transmission line overloading or congestion in deregulated power systems. It then provides background on congestion management approaches and Flexible AC Transmission Systems (FACTS) devices like IPFC that can increase line capacity. The document proposes using a hybrid Fish-Bee algorithm to identify the most congested line and optimal location to place an IPFC to relieve congestion by increasing power transfer capacity while minimizing voltage deviations. Simulation results on the IEEE 30 bus system show the proposed approach increases existing line capacity more than other algorithms using UPFC or IPFC for
Small Signal Stability Improvement and Congestion Management Using PSO Based ...IDES Editor
In this paper an attempt has been made to study the
application of Thyristor Controlled Series Capacitor (TCSC)
to mitigate small signal stability problem in addition to
congestion management of a heavily loaded line in a
multimachine power system. The Flexible AC Transmission
System (FACTS) devices such as TCSC can be used to control
the power flows in the network and can help in improvement
of small signal stability aspect. It can also provide relief to
congestion in the heavily loaded line. However, the
performance of any FACTS device highly depends upon its
parameters and placement at suitable locations in the power
network. In this paper, Particle Swarm Optimization (PSO)
method has been used for determining the optimal locations
and parameters of the TCSC controller in order to damp small
signal oscillations. Transmission Line Flow (TLF) Sensitivity
method has been used for curtailment of non-firm load to
limit power flow congestion. The results of simulation reveals
that TCSC controllers, placed optimally, not only mitigate
small signal oscillations but they can also alleviate line flow
congestion effectively.
This document summarizes research determining the optimal location for installing a unified power flow controller (UPFC) in an electric transmission system using particle swarm optimization (PSO) to minimize oscillations. The UPFC regulates voltages and controls power flows. PSO is an efficient method for solving nonlinear optimization problems with constraints. By varying parameters like power angle and incorporating time delays, the approach presents an innovative control scheme to apply UPFC beneficially for economical operation with reduced costs. Sensitivity analysis on the UPFC controller finds the optimal buses to place it and regulate flows.
Optimal siting and sizing of unified power flow controller using sensitivity...IJECEIAES
This paper presents Sensitivity constrained placement of unified power flow controller (UPFC) considering active-power flow sensitive index (APFSI) and static voltage stability index (STATIC-VSI) to minimize active-power losses and to improve power transmission capacity. The sensitive factors are derived with respect to voltage, phase angle and current to formulate APFSI. Transmission line impedance parameters along with active and reactivepower flow measurements are considered to formulate static-VSI. Sensitivity constrained differential evolutionary (SCDE) algorithm is proposed for parameter setting through which power control and minimization of losses in system can be achieved. Testing is performed on IEEE-5, 14 and 30-bus networks in MATLAB and results indicate that SCDE is robust optimization technique compared to conventional method and genetic algorithm (GA).
This document describes a methodology for optimally allocating Unified Power Flow Controller (UPFC) devices in a power transmission system using multi-objective optimal power flow and genetic algorithms. The objectives are to maximize social welfare by minimizing generation costs while also minimizing branch overloading. A multi-objective optimal power flow formulation is presented with two objective functions - minimizing total generation costs and minimizing an exponential branch loading function. A genetic algorithm is then used to determine the optimal number and locations of UPFC devices to place on the system to minimize the two objectives simultaneously. The approach is demonstrated on the IEEE 30-bus test system.
In recent years, studies have been investigated the effectiveness of UPFC and TCSC in increasing power transfer capability. However, the effectiveness of these FACTS devices in increasing power transfer capability when the load is non-linear has not been established in a comparative study yet. This paper will explore the steady-state performance of the UPFC and TCSC as impedance compensation models. The effectiveness of both FACTS devices are investigated when they are installed in multi-machine systems with different non-linear load models. Simulation results demonstrate that, upon installing UPFC, more active and reactive powers are received at the sending end bus for different types of non-linear load models. In addition, both active and reactive powers are more sensitive in changing the modulation index of the converters. Furthermore, both the active and reactive powers are less sensitive to the non-linearity of the load model type. However, active and reactive powers in case of installing TCSC are only sensitive in changing the firing angle (α) when it is between 90º to 110º. Therefore, results from this study clearly encourage the effectiveness of UPFC in comparison to TSCS in terms of increasing power transfer capability applied to non-linear load models.
Optimization of the Thyristor Controlled Phase Shifting Transformer Using PSO...IJECEIAES
This document summarizes an article that investigates optimizing the placement and sizing of a Thyristor Controlled Phase Shifting Transformer (TCPST) and Thyristor Controlled Series Capacitor (TCSC) combination on a 30-bus power system using a Particle Swarm Optimization (PSO) algorithm. The PSO algorithm was used to determine the optimal location and ratings of the TCPST-TCSC devices to minimize power losses. Implementing the optimized TCPST-TCSC combination resulted in a 46.47% reduction in power losses, outperforming the use of capacitor banks alone which achieved a 42.03% reduction. The TCPST-TCSC solution found with PSO also performed
PaperLoad following in a deregulated power system with Thyristor Controlled S...rajeshja
Load following is considered to be an ancillary service in a deregulated power system. This paper investigates
the effect of a Thyristor Controlled Series Compensator (TCSC) for load following in a deregulated
two area interconnected thermal system with two GENCOs and two DISCOs in either areas. Optimal
gain settings of the integral controllers in the control areas are obtained using Genetic Algorithm by
minimizing a quadratic performance index. Simulation studies carried out in MATLAB validates that a
Thyristor Controlled Series Compensator in series with tie-line can effectively improve the load following
performance of the power system in a deregulated environment.
The gravitational search algorithm for incorporating TCSC devices into the sy...IJECEIAES
This paper proposes a gravitational search algorithm (GSA) to allocate the thyristor-controlled series compensator (TCSC) incorporation with the issue of reactive power management. The aim of using TCSC units in this study is to minimize active and reactive power losses. Reserve beyond the thermal border, enhance the voltage profile and increase transmission-lines flow while continuing the whole generation cost of the system a little increase compared with its single goal base case. The optimal power flow (OPF) described is a consideration for finding the best size and location of the TCSCs devices seeing techno-economic subjects for minimizing fuel cost of generation units and the costs of installing TCSCs devices. The GSA algorithm's high ability in solving the proposed multi-objective problem is tested on two 9 and 30 bus test systems. For each test system, four case studies are considered to represent both normal and emergency operating conditions. The proposed GSA method's simulation results show that GSA offers a practical and robust highquality solution for the problem and improves system performance.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Infrastructure Challenges in Scaling RAG with Custom AI modelsZilliz
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
AI-Powered Food Delivery Transforming App Development in Saudi Arabia.pdfTechgropse Pvt.Ltd.
In this blog post, we'll delve into the intersection of AI and app development in Saudi Arabia, focusing on the food delivery sector. We'll explore how AI is revolutionizing the way Saudi consumers order food, how restaurants manage their operations, and how delivery partners navigate the bustling streets of cities like Riyadh, Jeddah, and Dammam. Through real-world case studies, we'll showcase how leading Saudi food delivery apps are leveraging AI to redefine convenience, personalization, and efficiency.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
CAKE: Sharing Slices of Confidential Data on BlockchainClaudio Di Ciccio
Presented at the CAiSE 2024 Forum, Intelligent Information Systems, June 6th, Limassol, Cyprus.
Synopsis: Cooperative information systems typically involve various entities in a collaborative process within a distributed environment. Blockchain technology offers a mechanism for automating such processes, even when only partial trust exists among participants. The data stored on the blockchain is replicated across all nodes in the network, ensuring accessibility to all participants. While this aspect facilitates traceability, integrity, and persistence, it poses challenges for adopting public blockchains in enterprise settings due to confidentiality issues. In this paper, we present a software tool named Control Access via Key Encryption (CAKE), designed to ensure data confidentiality in scenarios involving public blockchains. After outlining its core components and functionalities, we showcase the application of CAKE in the context of a real-world cyber-security project within the logistics domain.
Paper: https://doi.org/10.1007/978-3-031-61000-4_16
Things to Consider When Choosing a Website Developer for your Website | FODUUFODUU
Choosing the right website developer is crucial for your business. This article covers essential factors to consider, including experience, portfolio, technical skills, communication, pricing, reputation & reviews, cost and budget considerations and post-launch support. Make an informed decision to ensure your website meets your business goals.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Programming Foundation Models with DSPy - Meetup Slides
03 03085
1. 14 Journal of Electrical Engineering & Technology Vol. 6, No. 1, pp. 14~24, 2011
DOI: 10.5370/JEET.2011.6.1.014
Available Transfer Capability Enhancement with
FACTS Devices in the Deregulated Electricity Market
B.V. Manikandan†, S. Charles Raja* and P. Venkatesh*
Abstract – In order to facilitate the electricity market operation and trade in the restructured environ-
ment, ample transmission capability should be provided to satisfy the demand of increasing power
transactions. The conflict of this requirement and the restrictions on the transmission expansion in the
restructured electricity market has motivated the development of methodologies to enhance the avail-
able transfer capability (ATC) of existing transmission grids. The insertion of flexible AC transmission
System (FACTS) devices in electrical systems seems to be a promising strategy to enhance single area
ATC and multi-area ATC. In this paper, the viability and technical merits of boosting single area ATC
and multi-area ATC using Thyristor controlled series compensator (TCSC), static VAR compensator
(SVC) and unified power flow controller (UPFC) in single device and multi-type three similar and dif-
ferent device combinations are analyzed. Particle swarm optimization (PSO) algorithm is employed to
obtain the optimal settings of FACTS devices. The installation cost is also calculated. The study has
been carried out on IEEE 30 bus and IEEE 118 bus systems for the selected bilateral, multilateral and
area wise transactions.
Keywords: Available transfer capability, Flexible AC transmission systems, Particle swarm optimiza-
tion, Power transfer dsistribution factors, Participation factors, Installation cost
1. Introduction the increasingly difficult economic, environmental, and
social problems, have led to a much more intensive shared
The restructuring of the electric industry throughout the usage of existing transmission facilities by utilities and
world aims to create competitive markets to trade electric- independent power producers (IPPs). These concerns have
ity and generates a host of new technical challenges to motivated the development of strategies and methodologies
market participants and power system researchers. For to boost the ATC of existing transmission networks.
transmission networks, one of the major consequences of FACTS technology enables line loading to increase
the non-discriminatory open-access requirement is a sub- flexibly, in some cases, even up to the thermal limits.
stantial increase of power transfers, which demand ade- Therefore, it can theoretically offer an effective and prom-
quate available transfer capability (ATC) to ensure all ising alternative to conventional methods for ATC en-
transactions are economical. Researchers have proposed hancement. Undoubtedly, it is very important and impera-
the computation of ATC using AC power transfer distribu- tive to carry out studies on exploitation of FACTS technol-
tion factors (ACPTDF) [1]-[3]. New methods of evaluating ogy to enhance ATC [7]-[10]. The modeling of FACTS
ATC in a competitive environment are proposed in previ- devices for power flow studies, the role of such modeling
ous research[4], [5]. With the introduction of competition for power flow control and the integration of these devices
in the utility industry, it is possible for customers to buy into power flow studies were reported in the literature [11],
less expensive electrical energy from remote location. As a [12]. Modeling and the role of important FACTS devices
result, system operators face the need to monitor and coor- like static VAR compensator (SVC), Thyristor controlled
dinate power transactions taking place over long distances series compensator(TCSC) and unified power flow control-
in different areas. Therefore, it becomes essential to evalu- ler (UPFC) in solving power system restructuring issues
ate multi-area ATC, and a novel method for determining have been previously reported [13]-[15].
multi-area ATC has been presented in the literature[6]. Some well established search algorithms such as GA
Sufficient ATC should be guaranteed to support free [16] and evolutionary programming (EP) [17], [18] were
market trading and maintain an economical and secure successfully implemented to solve simple and complex
operation over a wide range of system conditions. However, problems efficiently and effectively. Most of the population
tight restrictions on the construction of new facilities due to based search approaches are motivated by evolution as
seen in nature. Particle Swarm Optimization (PSO), on the
† Corresponding Author: Mepco Schlenk Engineering College, other hand, is motivated from the simulation of social be-
Sivakasi Tamilnadu, India. (bvmani73@yahoo.com) havior and was introduced by Eberhart and Kennedy [19].
* Thiagarajar College of Engineering, Madurai, TamilNadu, India. Instead of using evolutionary operators to manipulate indi-
(charlesrajas@tce.edu, pveee@tce.edu) viduals, like in other evolutionary computational algo-
Received: March 25, 2010; Accepted: June 7, 2010
2. B.V.Manikandan, S.Charles Raja and P.Venkatesh 15
rithms, each individual in PSO flies in the search space Pijmax Pij0
with velocity that is dynamically adjusted according to its ; ACPTDFij , mn 0
own and its companion’s flying experience. The velocity of ACPTDFij , mn
the particle that is updated according to its own previous
Tij , mn (infinite ) ; ACPTDFij , mn 0 (3)
best position and the previous best position of its compan-
( Pij Pij ) ;
max 0
ACPTDFij , mn 0
ions and more information are available in previous re-
search [20]. PSO is now applied for solving electrical en-
ACPTDFij , mn
gineering related problems [21].
In this paper, single area ATC is calculated using
Where the following holds true:
ACPTDF and multi-area ATC with ACPTDF and participa-
tion factors (PFs) in combined economic emission dispatch
Pijmax is the MW power limit of a line between bus i and j.
(CEED) environment [6], [18]. An attempt is made to en-
Pijo is the base case power flow in line between bus i and j.
hance ATC using TCSC, SVC and UPFC in single device
NL is the total number of lines.
and multi-type three similar and different device combina-
ACPTDFij,mn is the power transfer distribution factor for
tions. Limiting element strategy is proposed for placement
the line between bus i and j when a transaction is taking
of FACTS devices. Both bilateral and multilateral transac-
place between bus m and n.
tions are considered for single area ATC and area- wise
transaction is considered for multi-area ATC enhancement.
ACPTDF as given in equation (3) is operating point de-
The optimal settings of FACTS devices are obtained from
pendent and was computed using Jacobian inverse.
PSO Algorithm. The installation cost of FACTS devices
ACPTDFs remain fairly constant for reasonable variations
[22] has also been calculated. For the selected transactions,
in power injections. The method of formulating ACPTDF
the best single device type and multi-type device combina-
is common for both single area and multi-area ATC evalua-
tion have been suggested with reference to ATC enhanced
tion and this is explained in section 2.2. For multi-area
value and installation cost. The results are illustrated on
ATC calculation, in addition to ACPTDFs, PFs should also
both IEEE 30 bus and IEEE 118 bus systems.
be included and it is explained in section 2.3. In this paper,
the optimal settings of generators under CEED environ-
ment are considered as a base case power flow, which is
2. ATC explained in section 2.1.
ATC is a measure of the transfer capability remaining in 2.1 CEED Problem Formulation
the physical transmission network for further commercial
activity over and above the already committed uses. It can
In the restructured environment, generator companies
be expressed as follows:
are generally responsible for the re-dispatch of power by
considering the emissions according to state laws and sub-
ATC TTC Existing Transmissi on Commitment s (1)
mit their bids to the transmission system operator, which is
responsible for calculating ATC before committing the
Where, Total Transfer Capability (TTC) is defined as the transactions. However, in most developing countries, the
amount of electric power that can be transferred over the restructuring process of power industry is still in the infant
interconnected transmission network or particular path or stage wherein the structure is vertically integrated but the
interface in a reliable manner while meeting all of a spe- power is purchased from IPPs to meet the growing demand.
cific set of defined pre and post contingency conditions. Hence, the regional transmission operator is responsible for
the re-dispatch of generator power by considering the
ATC at the base case, between bus m and bus n using physical limits of the system and the emissions standards.
line flow limit (thermal limit) criterion is mathematically Furthermore, there are some power markets that support
formulated using ACPTDF as given in the below equation: both bilateral transactions based on ATC and centralized
dispatch based on bids. In these markets, assured firm
ATCmn min Tij , mn , ij N L (2) transactions are implemented first and then they will fol-
low centralized dispatch mechanism with the remaining
transfer capacity. Therefore the proposed CEED based ATC
Where Tij,mn denotes the transfer limit values for each
calculation method can be well suited for such cases de-
line in the system. It is given by the following:
scribed above.
The optimization of CEED problem has been mathe-
matically formulated and is given by the following equa-
tion:
Ng
min fi ( FC , EC ) (4)
i 1
3. 16 Available Transfer Capability Enhancement with FACTS Devices in the Deregulated Electricity Market
Where is the optimal cost of generation (US$/h) and Pi t k Pj t k (8)
Ng represents the number of generators connected in the
network. FC represents the total fuel cost of generation in With the above mismatch vector elements, the change in
US$/h and EC denotes the total emission of generation in voltage angle and magnitude at all buses can be computed
lb/h. The cost is optimized with the constraints such as from (7) & (8) and, hence, the new voltage profile can be
power flow equation of the power network, satisfying calculated. These can be utilized to compute all the trans-
power balance equation, inequality constraint on real mission quantities ql and hence the corresponding in these
power generation of each generator i, inequality constraint quantities ∆ql from the base case. Once the ∆ql for all the
on voltage of each PQ bus and power flow limit on each lines corresponding to a change in transaction ∆tk is known,
transmission line. PTDFs can be obtained from (6). These ACPTDFs, which
The bi-objective optimization problem (4) is converted are computed at a base load flow condition, have been util-
into single optimization problem by introducing price pen- ized for computing change in transmission quantities at
alty factor, h in $/lb, which blends fuel cost with emission, other operating conditions as well.
as expressed by the following:
2.3. PF for Multi-area ATC Calculation
Minimize ( FC h EC ) (5)
For transaction taking place between two areas i.e. one is
CEED optimization problem is solved using EP, subject the seller area and the other is the buyer area, the multi-
to the constraints mentioned above. More information is area
also available in the literature [6], [18]. ATC problem formulation is as follows:
For each generator inside the area, the actual participa-
2.2 ACPTDF Formulation tion factor used is the following;
ACPTDFs determine the linear impact of a transfer (or Geni
PFi (9)
changes in power injection) on the elements of the power All Geni in an area
system. These values provide a linearized approximation of
how the flow on the transmission lines and interfaces Where Geni represents the real power generation capac-
change in response to transaction between the seller and ity of generator i. Assuming the inverse of Jacobian i.e.,
the buyer. Considering a bilateral transaction tk between a [JT]-1 is [ST], equation (7) can be written as follows:
seller bus m and buyer bus n, line l carries the part of the
transacted power and is connected between buses i and j.
P
For a change in real power in the transaction between the V S T Q (10)
above buyer and seller by ∆tk MW, if the change in a
transmission line quantity q1 is ∆q1 , power transfer distri-
bution factors can be defined as follows: In the above equation, Pk = 0, where k = 1. . . . h, k i,
j and Q = 0. In the transaction matrix for seller area, in
ql the place of generators, the PF value assigned is as follows:
ACPTDFij ,mn (6)
t k
n
The transmission quantity ql can be either real power
PSi = + PFi subject to PF
i 1
i 1 (11)
flow from bus i to bus j (Pij ) (or) real power flow from
bus j to bus i (Pji ). The above factors have been proposed Meanwhile, in the transaction matrix for the buyer area,
to compute at a base case load flow with results using the in the place of generators, the PF value assigned is the fol-
sensitivity properties of NRLF Jacobian. Consider full lowing:
Jacobian in polar coordinates [JT], which is defined to in-
clude all the buses except slack (also including ∆Q-∆V n
equations for PV buses), we get the following: PBj = - PFj subject to PF
j 1
j 1 (12)
1
P P
Where n = the number of generators in the buyer and
V P J 1 P
V Q Q Q T Q (7) seller areas. All other entries in the buyer and seller area
transaction matrices other than PSi and PBj are zeros.
V The change in voltage angle and magnitude at all buses
present in the areas are calculated and hence the new volt-
In a base case load flow, if only one of the kth bilateral age profile can be determined. Area wise PTDF is simply
transactions is changed by ∆tk MW, only the following two a function of these voltages and angle sensitivities, there-
entries in the mismatch vector on right hand side of (7) will fore, the calculation of multi-area ATC is similar to the
be non zero.
4. B.V.Manikandan, S.Charles Raja and P.Venkatesh 17
procedure followed for single area ATC. More information 3.3 Device Placement Strategy
about multi-area ATC is available in a previous study [6].
ATC value is greatly influenced by the power flow in the
limiting line of the system. Therefore, a FACTS device is
3. FACTS Devices placed in the limiting line or at the corresponding bus to
which the limiting line is connected depending on the type
The insertion of FACTS devices in electrical systems of device. Only one FACTS device per line is allowed. If
seems to be a promising strategy to increase available only one device is used, it is placed in the first limiting line
transfer capability (ATC) [7]-[10]. of the system. If three devices are to be inserted, then the
first three limiting lines are selected. For this purpose, the
3.1 Selection of Devices limiting lines in the considered test systems are ranked and
ordered based upon the power carrying capacity in the line.
FACTS devices are categorized under four different head- For the multi-type device category, TCSC is considered as
ings as series controllers, shunt controllers, combined series- the first device, SVC as the second and UPFC as the third .
shunt controllers and combined series-series controllers. In If the device is TCSC, it is connected in series with the
this paper, one device from each category is selected i.e., limiting line. If the device is SVC, then the type of origi-
TCSC from series controllers, SVC from shunt controllers nating bus and terminating bus of the limiting line is
and UPFC from combined series-shunt controllers. checked. If the one end bus is PV bus, it is discarded and if
TCSC is connected in series with the line conductors to the other end bus is PQ bus, then SVC is connected. Sup-
compensate for the inductive reactance of the line. It may pose if two end buses happen to be PV buses, then the next
have one of the two possible characteristics namely capaci- limiting line in the order is selected and checked for type of
tive or inductive, respectively to decrease or increase the bus. For UPFC, the series device TCSC is connected in
reactance of the line XL respectively. Moreover, in order series with the limiting line and the shunt device SVC is
not to overcompensate the line, the maximum value of the connected at PQ bus after checking the type of the end
capacitance is fixed at -0.8XL while that for inductance, it is buses where the limiting line is connected.
0.2XL. Although TCSC is not usually installed for voltage
control purpose, it does contribute for better voltage profile
and reactive power control. 4. Problem Formulation
SVC is used for voltage control applications. It helps to
maintain a bus voltage at a desired value during load varia- The aim of the optimization is to perform the best utili-
tions. The SVC may have two characteristics namely, in- zation of the existing transmission lines. The objective is to
ductive or capacitive. In the inductive mode, it absorbs maximize the ATC i.e., uncommitted active transfer capac-
reactive power, whereas in the capacitive mode, reactive ity of the prescribed interface, when a transaction is taking
power is injected. It may take values characterized by the place between a seller bus (m) and buyer bus(n). It is repre-
reactive power injected or absorbed at the voltage of 1 p.u. sented as follows:
The values are between -100 Mvar and 100 Mvar.
The UPFC is capable of providing active and reactive Maximize ( ATCm n ) (13)
power control, as well as adaptive voltage magnitude con-
trol and regulates all the three variables simultaneously or
Where
any combination of them, provided no operating limits
are violated. The UPFC may act as an SVC, a TCSC or a
phase shift controller. The versatility afforded by the UPFC ATCmn min Tij , m n , ij N L as given in equation (2)
makes it a prime contender to provide many of the control
functions required to solve a wide range of dynamic and 4.1 FACTS device’s constraints
steady state problems encountered in electrical power net-
works [9]. UPFC can be modeled as a combination of one The constraints on the FACTS devices used in this work
series element i.e., TCSC and a shunt element i.e., SVC are given below:
[23]. Hence the operational range limits of TCSC and SVC
can be applied to UPFC as well. i) 0.8 X L X TCSC 0.2 X L p.u (14)
3.2 Modeling of FACTS Devices ii) 100 MVAR QSVC 100 MVAR (15)
iii) Equations (20) & (21) for UPFC (16)
TCSC has been modeled as a variable reactance inserted
in the transmission line connected between buses. SVC is Where XTCSC is the reactance added to the line by placing
modeled as a reactive power source added or connected at TCSC, XL is the reactance of the line where TCSC is lo-
the bus. Based on previous research [23], UPFC is modeled cated and QSVC is the reactive power injected at the bus by
as combination of an SVC at a bus and a TCSC in the line placing SVC.
connected to the same bus.
5. 18 Available Transfer Capability Enhancement with FACTS Devices in the Deregulated Electricity Market
4.2 Power Flow Constraints 5. Overview of PSO
The power flow constraint is given by: PSO is a population-based optimization method that was
first proposed by Kennedy and Eberhart [19]. This tech-
g ( v , ) 0 (17) nique finds the optimal solution using a population of par-
ticles. PSO is developed through the simulation of bird
Where flocking in two-dimensional space. The position of each
agent is represented in the X-Y plane with position (Sx, Sy),
Vx (velocity along X-axis), and Vy (velocity along Y-axis).
Pi ( v , ) Pi net
Modification of the agent position is realized by the posi-
Q ( v , ) Q net For each PQ bus i tion and velocity information. Bird flocking optimizes a
g (V , ) i i
(18) certain objective function. Each agent knows its best value,
Pm ( v , ) Pmnet For each PV bus m , thus called “Pbest”, which contains the information on posi-
not including ref . bus tion and velocities. This information is the analogy of per-
sonal experience of each agent. Moreover, each agent
knows the best value so far in the group, “'Gbest” among all
Pi , Qi represents calculated real and reactive power for “Pbest”. This information is the analogy of knowledge, on
PQ bus i respectively. Pi net and Qinet denotes specified how the other neighboring agents have performed. Each
agent tries to modify its position by considering current
real and reactive power PQ bus i respectively. Pm and positions (Sx, Sy), current velocities (Vx, Vy), the individual
net
Pm represents calculated and specified real power for PV intelligence (Pbest), and the group intelligence (Gbest).
The following equations are utilized, in computing the
bus m, respectively. v and represents voltage magni- position and velocities, in the X-Y plane:
tude and phase angles at different buses, respectively.
Vi k 1 W Vi k C1 rand1 ( Pbesti Sik )
4.3 Installation Cost (22)
C2 rand 2 ( Gbest Sik )
The installation cost of the corresponding FACTS de-
vices are given by,
Sik 1 Sik Vi k 1 (23)
IC C * S *1000 (19)
Where,Vik+1 is the velocity of ith individual at (k + 1 )th
where IC denotes optimal installation cost of FACTS de- iteration, Vik is the velocity of ith individual at kth iteration,
vices in US$. C represents cost of installation of FACTS W is the inertia weight, C1 and C2 are the positive con-
devices in US $/KVar. stants having values (0,2.5), rand1 and rand2 are the random
The cost of installation of UPFC, TCSC and SVC are numbers selected between 0 and 1, Pbesti is the best posi-
taken from Siemens data base and reported in [22]. The tion of the ith individual, Gbest is the best position among
cost of installation of various FACTS devices are given by the individuals (group best) and Sik is the position of ith
the following equations: individual at kth iteration. The acceleration coefficients C1,
and C2 control how far a particle will move in a single it-
CUPFC 0.0003 S 2 0.2691S 188.22 eration. Typically, these are both set to a value of 2.5.
CTCSC 0.0015 S 2 0.7130S 153.75 (20) The velocity of each particle is modified according to
(22) and the minimum and maximum velocity of each vari-
CSVC 0.0003 S 0.3051S 127.38
2
able in each particle is set within the limits of Vmin and Vmax
respectively. The position is modified according to (23).
Where S is the operating range of the FACTS devices in The inertia weight factor “W” is modified using (24) to
MVAR and it is given by: enable quick convergence [20].
S Q2 Q1 (21) (Wmax Wmin )
W Wmax iter (24)
itermax
Where Q2 is the reactive power flow in the line after
installing FACTS device in Mvar and Q1 represents reac- Where Wmax is the initial value of inertia weight equal to
0.9, Wmin is the final value of inertia weight equal to 0.4,
tive power flow in the line before installing FACTS device
iter is the current iteration number and itermax is the maxi-
in Mvar.
mum iteration number. Small values of w result in more
rapid convergence usually on a suboptimal position, while
a too large value may prevent divergence of solution. The
6. B.V.Manikandan, S.Charles Raja and P.Venkatesh 19
PSO system combines two models; a social-only model considered in this test system.
and a cognition-only model. These models are represented
by the velocity update, shown in (22). More information is Bilateral Transaction
also available in [20]. ATC value at the base case without employing FACTS
device is determined first, afterwards ATC is determined by
6. Simulation Results and Discussions employing FACTS devices in the single and multi-type
three similar and different device combinations. Table 1
In this paper, for the single and multi-area ATC determi- shows the results. The first four limiting lines are obtained
nation, the generator settings of the test systems are ob- for this transaction and the order of limiting lines are lines
tained from CEED environment as explained in [6, 18]. 6-28, 2-6, 6-8 and 22-24. The PSO convergence curve for
The thermal limit of each line is considered as a constraint. this transaction utilizing single UPFC is shown in Fig. 1.
Three types of FACTS device i.e., TCSC, SVC and UPFC In the multi-type, similar devices combination, three
are employed separately first and in three similar and dif- TCSCs are placed in the first three limiting lines i.e., 6-28,
ferent device combinations to enhance ATC. One set of 2-6 and 6-8. Similarly, three SVCs are placed at buses 28, 6
bilateral and multi-lateral transaction is considered for the and 8. For the three UPFCs, the placement of three TCSCs
two IEEE test systems in the single area configuration and and three SVCs are similar to the three similar devices. In
one area-wise transaction is considered for the two IEEE the single device type, UPFC is providing maximum en-
test systems in the multi-area configuration. The optimal hancement of ATC. Considering multi-type similar and
settings of FACTS devices are obtained from PSO Algo- different device combinations, three UPFCs are providing
rithm. Installation cost of FACTS devices has also been maximum enhancement of ATC. However, considering the
calculated and the best single and multi-type device is sug- cost of installation, TCSC-SVC-UPFC combination seems
gested for each transaction with reference to ATC value to be very effective for this transaction.
and cost of installation. The simulation studies are carried
out on Intel Pentium Dual Core, 2.40 GHz system in
MATLAB 7.3 environment.
6.1 Single area ATC Enhancement
The bus data and line data of the two IEEE test systems
are taken from [24] and the CEED base case values of the
generators are obtained as explained in [6, 18].
6.1.1 IEEE 30 Bus System
One bilateral transaction between buses (2-28) and a
multilateral transaction between buses (2, 11)-(28, 26) are Fig. 1. PSO convergence curve for single UPFC.
Table 1. ATC enhancement results for bilateral transaction (2-28)
Settings and placement
ATC without ATC with
Type of FACTS UPFC Installation Cost
( 106 US $)
FACTS FACTS TCSC SVC
device(s) TCSC SVC
(MW) (MW) (p.u) (Mvar)
(p.u) (Mvar)
0.030
TCSC 27.614 - - - 0.29
(6-28)
-92.772
SVC 25.413 - - - 4.66
(Bus 28)
0.030 -49.313
UPFC 31.004 - - 3.82
(6-28) (Bus 28)
TCSC 0.030
TCSC 24.756 -0.074 - - - 1.67
TCSC -0.021
24.821
SVC -100
SVC 25.637 - 59.258 - - 9.00
SVC -96.432
UPFC 0.026 -99.544
UPFC 33.516 - - 0.088 -99.127 12.27
UPFC -0.021 -50.472
TCSC
0.029 95.651 -0.021 97.228
SVC 30.938 3.21
(6-28) (Bus 6) (6-8) (Bus 8)
UPFC
7. 20 Available Transfer Capability Enhancement with FACTS Devices in the Deregulated Electricity Market
Multilateral Transaction
The order of the first four limiting lines based on the
power flow capacity is 6-28, 25-27, 9-11 and 27-30. The
base case ATC value is found to be 16.951 MW. In the sin-
gle device type, TCSC is placed in series with line 6-28
and its settings is 0.104 p.u. SVC is connected at bus 28
and its settings is -55.022 Mvar. For UPFC, the series ele-
ment is connected in the line 6-28, while the shunt element
is connected at bus 28. The settings of the shunt and series
elements are 0.046 p.u and -53.637 Mvar respectively. For
the three similar device combinations, three TCSCs are Fig. 2. ATC results - multilateral transaction of IEEE 30
placed in series with the lines 6-28, 25-27 and 9-11 with bus system.
settings of 0.104 p.u, 0.030 p.u and -0.083 p.u respectively.
Similarly, three SVCs are connected at buses 28, 25 and 9
with settings of -60.013 Mvar, -11.584 Mvar and 100 Mvar.
For the three UPFCs, the settings of the series elements are
-0.104 p.u, 0.030 p.u and -0.104 p.u. The three shunt
elements have the settings are -53.081 Mvar, -91.774 Mvar
and 100 Mvar respectively. For the three different device
combination, TCSC is connected in the line 6-28 with
setting of 0.029 p.u, SVC is connected at bus 25 with
setting of -97.643 Mvar and for UPFC, the series element
in the line 9-11and shunt element at bus 9. The
corresponding settings are -0.046 p.u and 89.225 Mvar. Fig.
2 shows the ATC enhancement results with single and Fig. 3. Installation Cost - multilateral transaction of IEEE
multi-type three similar and different device combinations. 30 bus system.
The installation cost details are shown in Fig. 3. For the
multi-lateral transaction, in the single device category, 6.1.2 IEEE 118 Bus System
TCSC is considered to be the best since it provides One bilateral transaction between buses (49-100) and a
maximum improvement of ATC with minimum cost of multilateral transaction between buses (25,59,46)- (89,100,
installation. In multi-type similar and different device 103,111) are considered in this large test system.
combinations, three UPFCs are providing maximum en-
hancement of ATC at very high installation cost. However,
Bilateral Transaction
considering the cost of installation, three SVCs are sug-
The first four limiting lines for this transaction is found
gested to be the best for this transaction.
to be lines 81-80, 68-81, 94-100 and 69-77. The results are
given in Table 2.
Table 2. ATC enhancement results for bilateral transaction (49-100)
Settings and placement
ATC without ATC with
Type of FACTS UPFC Installation Cost
( 106 US $)
FACTS FACTS TCSC SVC
device(s)
(MW) (MW) (p.u) (Mvar) TCSC SVC
(p.u) (Mvar)
TCSC 425.984 0.019 (81-80) - - - 5.63
-97.025
SVC 395.940 - - - 3.02
(Bus 81)
UPFC 425.986 - - 0.018(81-80) -68.213 (Bus 81) 10.18
TCSC 0.018
TCSC 448.845 0.010 - - - 11.90
TCSC 0.007
393.851 SVC -100
SVC 397.085 - -93.664 - - 7.69
SVC 98.335
UPFC 0.019 -90.644
UPFC 447.789 - - 0.010 -81.233 9.67
UPFC -0.018 -85.301
TCSC
0.018 -95.972 -0.027 91.766
SVC 428.891 11.35
(81-80) (Bus 81) (94-100) (Bus 94)
UPFC
8. B.V.Manikandan, S.Charles Raja and P.Venkatesh 21
In the multi-type, similar devices combination, three
TCSCs are placed in the first three limiting lines i.e., 81-80,
68-81 and 94-100. Similarly, three SVCs are connected at
buses 81, 68 and 94. For the three UPFCs, the placement of
three TCSCs and three SVCs are the same as that of the
three similar devices mentioned above.
In the single device category, UPFC and TCSC are pro-
viding equal improvement in ATC value. However, the
installation cost for UPFC is almost twice times when com-
pared with that for TCSC. Therefore, TCSC is the effective
device for this transaction. Considering multi-type similar
and different device combinations, three TCSCs are pro- Fig. 5. Installation cost– multilateral transaction of IEEE
viding maximum enhancement compared to all other com- 118 bus system.
binations. Therefore, for this transaction, the combination
of three TCSCs combination is the most effective followed For this multi-lateral transaction, UPFC is the best
by the three UPFCs. device in the single device type. SVC and three SVC
combinations are proved to be ineffective for this
Multilateral Transaction multilateral transaction. In the multitype, similar and
The four limiting lines in the order of power flow for different device combinations, three UPFCs and TCSC-
this transaction are 100-103, 81-80, 69-77 and 68-81. The SVC-UPFC combinations are producing equal enhancement.
ATC value without FACTS device is 51.072 MW. The ob- Cosidering the cost details, the TCSC-SVC-UPFC
tained ATC enhancement results are shown in Fig. 4. The combination is proved to most promising one.
installation cost details are shown in Fig. 5. In the single
device type, TCSC is placed in series with the line 100-103 6.2 Multi- area ATC Enhancement
with settings of 0.026 p.u. Since buses 100 and 103 are PV
buses, SVC is connected at bus 81 with settings of 65.773 For the multi-area ATC determination, two areas are
Mvar. For UPFC, since buses 100 and 103 are PV buses, considered for the IEEE 30 bus system and three areas are
the series element is connected in the line 81-80 and the considered for the IEEE 118 bus system.
shunt element is connected at the bus 81. The settings of
the shunt and series elements are 0.026 p.u and -58.961 6.2.1 IEEE 30 Bus System
Mvar respectively. For the three similar device combinations,
three TCSCs are placed in series with the lines 100-103, There are six generators present in this system. Genera-
81-80 and 69-77 with settings of 0.026 p.u, -0.008 p.u and tors at buses 8, 11 and 13 are considered in area 1, while
-0.010 p.u. Similarly, three SVCs are connected at buses 81, the remaining generators at buses 1, 2 and 5 are considered
77 and 68 with settings of 43.882 Mvar, 85.406 Mvar and in area 2. The tie-lines existing between the two areas are
100 Mvar respectively. For the three UPFCs, the settings of shown in Fig. 6. Transaction is carried out between Area 1
the series elements are 0.0262 p.u, 0.003 p.u and -0.010 p.u and Area 2. The first four limiting lines are lines 12-13, 15-
respectively. The settings of the three shunt elements are 23, 6-8 and 15-18. Table 3 shows the ATC improvement
15.048 Mvar, -72.141 Mvar and 81.511Mvar. For the three results for this area- wise transaction.
different device combination, TCSC is connected in the line In the multi-type, similar devices combination, three
100-103 with setting of 0.027 p.u, SVC is connected at bus TCSCs are placed in the first three limiting lines i.e., 12-13,
81 with setting of -66.458 Mvar and for UPFC, the series 15-23 and 6-8. Similarly, three SVCs are connected at
element in the line 69-77 and shunt element at bus 77. The buses 12, 23 and 8. For the three UPFCs, placement of
corresponding settings are -0.010 p.u and 90.973 Mvar. three TCSCs and three SVCs is the same as that of the
three similar devices.
In the single device type, TCSC is providing maximum
enhancement of ATC with minimum cost. Considering
multi-type similar and different device combinations, three
UPFCs are providing the maximum enhancement of ATC
but its cost is moderately high. In addition, the combination
Fig. 4. ATC results- multilateral transaction of IEEE 118
bus system. Fig. 6. Tie-lines between areas – IEEE 30 Bus system.
9. 22 Available Transfer Capability Enhancement with FACTS Devices in the Deregulated Electricity Market
Table 3. Multi-area ATC Enhancement results for IEEE 30 Bus system
Settings and placement
ATC without
Type of FACTS ATC with FACTS UPFC Installation cost
( 106 US $)
FACTS TCSC SVC
device(s) (MW) TCSC SVC
(MW) (p.u) (Mvar)
(p.u) (Mvar)
0.067
TCSC 94.552 - - - 2.28
(12-13)
-95.771
SVC 93.258 - - - 2.69
(Bus 12)
0.070 -83.788
UPFC 94.053 - - 3.06
(12-13) (Bus 12)
-0.0346
TCSC
-0.0128
TCSC 95.710 - - - 2.67
0.010
92.613 TCSC
SVC 15.589
5.53
SVC 95.299 - -83.552 - -
SVC 11.077
UPFC 0.048 -100
UPFC 98.038 - - 0.017 3.446 6.12
UPFC 0.021 -85.638
TCSC
-0.054 -57.017 0.021 -69.293
SVC 96.371 3.55
(12-13) (Bus 23) (6-8) (Bus 6)
UPFC
TCSC-SVC-UPFC seems to be the next best as it has pro-
vided marginal improvement of ATC at minimum cost of
installation.
6.2.2 IEEE 118 Bus system
For the multi-area ATC evaluation, three areas are con-
sidered in the IEEE 118 bus system. This system has 19
generators. The generators and buses allocation for each
area is given in Table 4. The lines between area 1 and area
2 are the lines between buses 15-33, 19-34, 30-38, 75-69,
75-118, 75-77 and 70-69. The lines connecting area 2 and Fig. 7. Multi-area ATC enhancement results- IEEE 118 bus
area 3 are the lines between buses 77-82, 80-96, 97-96, 98- system.
100 and 99-100. Similarly, the lines connecting area 1 and
area 3 are the lines between buses 70-24, 72-24 and 23-24.
Transactions are carried out between area 1 and area 2;
area 1 and area 3; and area 2 and area 3.
The order of first four limiting lines is 81-80, 68-81, 69-
77 and 100-103. Transaction is carried out between area 2-
area 3. The enhanced multi-area ATC results are shown in
Fig. 7 and the installation cost details are shown in Fig. 8.
In the single device type, TCSC is connected in series with
the first limiting line 81-80 and its setting is 0.018 p.u.
SVC is connected at bus 81 and the Mvar settings obtained
from the PSO is -99.231 Mvar. For UPFC, the series ele-
ment in the line 81-80 has the setting of 0.019 p.u and the
shunt element at bus 81 has the setting of -67.144 Mvar. Fig. 8. Installation cost details –IEEE 118 bus system.
Table 4. Area-wise generators / buses allocation for IEEE 118 bus system
Area / Generators Area / Buses
Area 1 Area 2 Area 3 Area 1 Area 2 Area 3
46, 49, 54, 59, 61, 1-23, 25-35, 33-69, 76-81, 97-99,
10, 12, 25, 26, 31 87, 89, 100, 103, 111 24, 82-96, 100-112
65, 66, 69, 80 70-75, 113-115, 117 116, 118
10. B.V.Manikandan, S.Charles Raja and P.Venkatesh 23
In the three similar device combinations, three TCSCs [4] A.M. Leite da silva, J.G.C. Costa, L.A.F. Manso and
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81, 68 and 77 with settings of -47.897 Mvar, -100 Mvar pp. 257-263, 2004.
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[1] J.Weber, “Efficient Available Transfer Capability
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11. 24 Available Transfer Capability Enhancement with FACTS Devices in the Deregulated Electricity Market
ence, Vol. 4, pp. 23-26, 2003. S. Charles Raja is presently working
[18] P. Venkatesh, R. Gnanadass and N.P. Padhy, “Com- as Lecturer in the Department of
parison and application of Evolutionary programming Electrical and Electronics Engineering
techniques to combined economic emission dispatch of Thiagarajar College of Engineering,
with line flow constraint”, IEEE Transactions on Madurai. He obtained his B.E., in
Power systems, Vol. 18, No. 2, 688-697, 2003. Electrical and Electronics Engineering
[19] J.Kennedy and R. Eberhart, “Particle Swarm Optimi- in 2005 and M.E., in Power Systems
zation”, Proceedings of IEEE international confer- Engineering in 2007 from Anna
ence on Neural Networks, Piscataway, NJ, Vol. IV, pp. University, Chennai. His topics of interest include Power
1942-1948, 1995. system security, Power system optimization techniques,
[20] M.A.Abido,“Optimal Power Flow using Particle control systems, application of FACTS controllers for all
Swarm Optimisation”, Electrical Power and Energy power system problems and power system deregulation.
Systems, Vol. 24, 563-571, 2002.
[21] S.Kannan, S.M.R.Slochanal, P.Subbaraj and N.P.Padhy,
“Application of Particle swarm optimization tech-
nique and its variants to generation expansion plan- P. Venkatesh received his degree in
ning problem”, Electric Power Systems Research, Vol. Electrical and Electronics Engineering,
70, pp. 203-210, 2004. Masters in Power System Engineering
[22] L.J. Cai, I. Erlich and G. Stamtsis, “Optimal choice with distinction and Ph.D from
and allocation of FACTS devices in deregulated elec- Madurai Kamaraj University, India in
tricity market using genetic algorithms”, IEEE PES 1991, 1994 and 2003, respectively, His
Power system conference and Exposition, USA, pp. area of interest is the application of
10-13, 2004. evolutionary computation techniques to
[23] M. Saravanan, S.M.R. Sulochanal, P.Venkatesh and power system problems and power system restructuring.
J.P.S.Abraham, “Application of particle swarm opti- He has received the Boyscast Fellowship award in 2006
mization technique for optimal location of FACTS from the Department of Science and Technology, India for
devices considering cost of installation and system carrying out research work at Pennsylvania State Univer-
loadability”, Electric Power Systems Research, Vol. sity, USA. He has more than 16 papers published in repu-
77, No. 3-4, pp. 276-283, 2005. table journals to his credit. He has chaired many techni-
[24] http://www.ee.washington.edu/research/ pstca cal sessions in seminars/workshops and gave number of
invited lectures in many forums. He is currently, an Asso-
ciate Professor in the Department of Electrical and Elec-
B.V. Manikandan obtained his B.E., tronics Engineering, Thiagarajar College of Engineering,
in Electrical and Electronics Engineering Madurai, India.
and M.E., in Power Systems Engineer-
ing from Madurai Kamaraj University
in 1990 and in 1992 respectively, and
Ph.D., degree from Anna University,
Chennai in 2010. His Ph.D., work deals
with issues of power system restructuring.
His special fields of interest includes power system restruc-
turing issues and application of FACTS controllers to
power system. He is presently working as Assistant Profes-
sor in the Department of Electrical and Electronics Engi-
neering of Mepco Schlenk Engineering College, Sivakasi.