IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

A wavelet-based digital directional relay for power transformer protection, implemented using field programmable gate array. The general purpose SPARTAN3E FPGA kit was employed for developing the prototype relay, with all the coding done using the hardware description language VHDL. The relay logic consists of two parts: disturbance detection based on first-level high-frequency details of the voltage signals and fault discrimination using a power-based directional signal derived from the first-level high-frequency details of both voltage and current signals. The real-time windows target Toolbox of MATLAB was used to apply the current and voltage input signals to the prototype relay in real-time. The logic is deterministic, computationally efficient, fast, secure and highly reliable. The operating time is 6ms, about one-third of power frequency cycle (20ms). The scheme uses only the sign of the directional signals, rather than the difference in their magnitudes, hence it can work reliably in the presence of fault resistance and current transformer saturation. The validity of the proposed logic was exhaustively tested by simulating various types of internal and external faults, energisation conditions and load variations on a 132kV system modelled in EMTP/ATP with a 31.5MVA, 132/33kV, Y-Δ transformer. The relay was able to correctly discriminate between internal faults, external faults and non-fault disturbances for the entire 880 test cases. © The Institution of Engineering and Technology 2008.

Department of Electrical Engineering

IET Electric Power Applications

Protective relaying for power transformers using field programmable gate array

This paper presents a differential evolution (DE) based optimal power flow (OPF) for reactive power dispatch in power system planning studies. DE is a simple population-based search algorithm for global optimization and has a minimum number of control parameters. The problem is formulated as a mixed integer non-linear optimization problem taking into account both continuous and discrete control variables. The proposed method determines control variable settings such as generator voltages (continuous), tap positions (discrete) and the number of shunt reactive compensation devices to be switched (discrete) for real power loss minimization in the transmission system using DE algorithm. Most of the evolutionary algorithm applications to optimization problems apply penalty function approach to handle the inequality constraints, involving penalty coefficients. The correct combination of these coefficients can be determined only by a trial and error basis. In the proposed approach, the inequality constraints are handled by penalty parameterless scheme. Voltage security margin was evaluated using continuation power flow (CPF), to ensure the feasibility of the optimal control variable setting. The suitability of the method was tested on IEEE 14 and IEEE RTS 24-bus systems and results compared with sequential quadratic programming (SQP) method. The DE provides near global solutions comparable to that obtained using SQP. © 2007 Elsevier B.V. All rights reserved.

Electric Power Systems Research

Network loss minimization with voltage security using differential evolution

Static security assessment and analysis using external system (Ward network) equivalent is presented. Contingency analysis is performed on the reduced network obtained using extended Ward equivalent. The Ward equivalent provides reasonably good results for contingency studies involving active power flows. Distribution factors method is used to perform contingency analysis. Fast line flow contingency screening is implemented for both the original unreduced network and the reduced network. The real power performance index (PIMW) that reflects the degree of severity of contingencies is calculated using the screening method and full AC load flow method. The effectiveness of the proposed method is demonstrated by performing contingency analysis on a standard 6-bus system, IEEE 14-bus, IEEE 30-bus and IEEE 57-bus systems, respectively. The performances of the reduced network and the screening method are compared with the traditional Newton-Raphson (NR) method and the results are discussed. The external network equivalent approach to security analysis was found to be suitable for fast line flow contingency analysis. © 2007 Elsevier Ltd. All rights reserved.

International Journal of Electrical Power and Energy Systems

Power system static security assessment and evaluation using external system equivalents

Artificial neural networks using pattern recognition methodology for security assessment of electric power systems is presented. Conventional numerical methods are either too complex or time consuming. An alternative method using neural networks to address the security assessment problem and its effectiveness against conventional methods is discussed. Neural networks using pattern recognition techniques is a promising methodology for different types of security assessment. Feature selection and extraction are used for selecting best features having highest discriminating capabilities. An important feature of the approach is that it can be generalized for steady state, transient and dynamic security assessment, which is a desirable feature for on-line security analysis. The proposed approach has been tested on the WSCC 9-bus 3-generator system. Steady state, transient and dynamic security assessment classification and contingency ranking results are provided to highlight the overall classification accuracy and suitability of the approach. © 2007 Elsevier B.V. All rights reserved.

Neurocomputing

Artificial neural network using pattern recognition for security assessment and analysis

This paper presents differential evolutionary algorithm for optimal dispatch for reactive power and voltage control in power system operation studies. The problem is formulated as a mixed integer, nonlinear optimization problem taking into account both continuous and discrete control variables. The optimal setting of control variables such as generator voltages, tap positions of tap changing transformers and the number of shunt reactive compensation devices to be switched for real power loss minimization in the transmission system are determined. In the proposed method, the inequality operational constraints were handled by "penalty parameterless" approach. This helps in avoiding the time-consuming trial and error process for fixing the penalty parameter and makes the process system independent. The algorithm was tested on standard IEEE 14,30,57 and 118-Bus systems and the results compared with conventional method. © 2008 Elsevier Ltd. All rights reserved.

Differential evolutionary algorithm for optimal reactive power dispatch

A differential evolution approach to solve optimal power flow problem with multiple and competing objectives is presented. Two sub-problems of optimal power flow namely active power dispatch and reactive power dispatch are considered. The problem is formulated as a nonlinear constrained true multi-objective optimisation problem with competing objectives. Constrain-domination approach have been used to handle inequality constraints, which eliminates the use of penalty factors. The performance of the proposed approach was tested on standard IEEE 30-bus system and is compared with a conventional method. The result demonstrates the capability of the proposed approach to generate diverse and well-distributed Pareto-optimal solutions. © 2008 The Institution of Engineering and Technology.

IET Generation, Transmission and Distribution

Solving multi-objective optimal power flow using differential evolution

This paper proposes a novel wavelet transform based relaying scheme for power transformer protection. The relay logic consists of two parts: disturbance detection based on first level high frequency details of the voltage signals only and fault discrimination using a power based directional signal derived from the first level high frequency details of both voltage and current signals. The logic is deterministic, computationally efficient, fast, secure and highly reliable. The operating time is 6 ms, about 1/3rd of power frequency cycle (20 ms). The scheme uses only the sign of the directional signals, rather than the difference in their magnitudes, hence it can work reliably in the presence of transformer tap variation, fault resistance and CT saturation. The validity of the proposed logic was exhaustively tested by simulating various types of internal and external faults, energization conditions and load variations on a 132 kV system modeled in ATP/EMTP with a 31.5 MVA, 132/33 kV, Y-Δ transformer. The proposed logic was able to correctly discriminate between internal faults, external faults and non-fault disturbances for all the 880 test cases. © 2007 Elsevier B.V. All rights reserved.

Wavelet based transformer protection using high frequency power directional signals

A new Object-Oriented Design (OOD) for unbalanced distribution system is proposed and employed for developing short circuit analysis software. The difficulty associated with the procedure-oriented implementation of short circuit analysis program is overcome with a new object-oriented implementation. The purpose of using Object-Oriented Methodology (OOM) for unbalanced distribution system is to achieve a flexible software model for the complex nature of the system involving three-phase, two-phase and single-phase components. Considerable reduction in the programming complexity can be obtained by the proposed method. The method was successfully tested on benchmark systems like IEEE 13-bus and IEEE 34-bus systems.

IEEE Region 10 Annual International Conference, Proceedings/TENCON

Unbalanced distribution system short circuit analysis - An object-oriented approach

This paper proposes a differential evolution-based optimal power flow (OPF) for reactive power dispatch (Volt-Var) in power system planning and operational studies. The problem is formulated as a mixed-integer non-linear optimization problem, taking into account both continuous and discrete control variables. The proposed method determines control variable settings such as generator voltage magnitudes, tap positions, and the number of shunt capacitors to be switched for real power loss minimization in the transmission system using a differential evolution (DE) algorithm with efficient constraint handling. The proposed methodology is tested on standard test systems such as IEEE 14-, IEEE 30-, and IEEE 57-bus systems, and the performance is compared with the genetic algorithm (GA) and interior point method (IPM). It was observed that the DE-based method is more robust and faster compared to the GA.

Electric Power Components and Systems

Volt-Var optimization using differential evolution

This paper develops optimal bidding strategy for operating multi-unit pumped storage power plant in day-ahead electricity market. Based on forecasted hourly market clearing price, a multistage looping algorithm to maximize the profit of multi-unit pumped storage plant is developed considering both spinning and non-spinning reserve bids and meeting the technical operating constraints. The proposed model is adaptive for the nonlinear three-dimensional relationship between the power produced, the energy stored, and the head of the associated reservoir. Evolutionary Tristate Particle Swarm Optimization (ETPSO) based approach is also proposed to solve the same problem, combining basic Particle Swarm Optimization (PSO) with tri-state coding technique and mutation operation. The discrete characteristic of a pumped storage plant is modeled using tri-state coding technique and genetics based mutation operation is used for faster convergence in getting global optimum. The proposed approaches are applied with an actual utility consisting of four units. Experimental results for different operating cycles of the storage plant indicate the attractive properties of the ETPSO approach in a practical application, namely, a highly optimal solution and robust convergence behaviour. © 2008 IEEE.

2008 IEEE International Conference on Sustainable Energy Technologies, ICSET 2008

Optimal bidding strategy for multi-unit pumped storage plant in pool-based electricity market using evolutionary tristate PSO

Differential evolution based optimal reactive power dispatch for real power loss minimization in power system is presented in this paper. The proposed methodology determines control variable settings such as generator terminal voltages, tap positions and the number of shunts to be switched, for real power loss minimization in the transmission system. The problem is formulated as a mixed integer nonlinear optimization problem. A generic penalty function method, which does not require any penalty coefficient, is employed for constraint handling. The formulation also checks for the feasibility of the optimal control variable setting from a voltage security point of view by using a voltage collapse proximity indicator. The algorithm is tested on standard IEEE 14, IEEE 30, and IEEE 118-Bus test systems. To show the effectiveness of proposed method the results are compared with Particle Swarm Optimization and a conventional optimization technique - Sequential Quadratic Programming. © 2007 Elsevier B.V. All rights reserved.

Applied Soft Computing Journal

Differential evolution approach for optimal reactive power dispatch

A new method for the solution of the problems of unit commitment (UC) and economic dispatch (ED) using Hopfield neural network (HNN) is proposed. The difficulty associated with combining these two problems is overcome with a new neural network architecture which uses the discrete type HNN for solving UC and the continuous type HNN for solving ED. The associated advantage of using HNN for the combined solution is the decoupling of their interdependence ie, both the UC and ED are iteratively solved using respective HNNfor the particular period. The implementation of the proposed method causes a considerable reduction in the HNN size, complexity and computation requirements. The proposed method was successfully tested on different systems (3, 5, 6,10, 26 generator units), with varying load pattern of different durations (24 h and 168 h).

Journal of the Institution of Engineers (India): Electrical Engineering Division

Solution of unit commitment and economic dispatch using hopfield neural network

Constrained evolutionary programming algorithm approach for two distinct studies of static and dynamic economic dispatch is presented. Economic dispatch (ED) is one of the main functions of power generation operation and control. The objective is to operate an electric power system most economically while the system is operating within its security limits. Multiple objective functions subjected to power flow constraints; Ramp rate limits for units, minimum and maximum allowable generations for each units are considered. Comparison of the computational efficiency and accuracy of constrained evolutionary programming (CEP) is provided. This paper proposes a novel methodology for solving dynamic economic dispatch. Comparison with other evolutionary methods like genetic algorithm, particle swarm optimization has been provided for 10-generator system with nonsmooth fuel cost functions to illustrate the suitability and effectiveness of the proposed method.

Constrained optimization using evolutionary programming for dynamic economic dispatch of power systems

This paper proposes a novel wavelet-transform-based directional algorithm for busbar protection. The algorithm decomposes the current and voltage signals into their first-level details, which consist of frequencies in 500- to 1000-Hz bandwidth, for generating directional signals. A high level of computational efficiency is achieved compared to the other wavelet-transform-based algorithms proposed, since only the high-frequency details at the first level are employed in this algorithm. The validity of this method was exhaustively tested by simulating various types of faults on a substation modeled in the Alternative Transients Program/Electromagnetic Transients Program. The algorithm correctly discriminated between bus faults, various types of external faults, and transformer energization even in the presence of current-transformer saturation. This paper also provides the design details of the algorithm using field-programmable gate array technology. © 2007 IEEE.

IEEE Transactions on Power Delivery

Computationally efficient wavelet-transform-based digital directional protection for busbars

Application of object-oriented design patterns for the development of power system computation software is presented. Important patterns such as "Iterator," "Decorator," and "Template Method " are utilized to develop a comprehensive power flow (load flow) analysis program, including FACTS devices such as SVC, TCSC, STATCOM, and UPFC. Analysis-independent object models of power system components are obtained by untying the attributes required for computation from the attributes representing the physical characteristics of an object. The proposed object-oriented design of power flow computation has been implemented in C++ on windows environment. The performance of the developed program has been tested with IEEE benchmark systems. © 2006 IEEE.

IEEE Transactions on Power Systems

Development of power flow software using design patterns

An artificial neural network (ANN) approach to power system contingency analysis is proposed. Using fast voltage and line-flow contingency screening. Full AC load flow is performed for each contingency case. The off-line results of full AC load flow calculations are used to construct two kinds of performance indices, namely the real power performance index (PIMW) and voltage performance index (PIV), which reflect the degree of severity of contingencies. The results from off-line load flow calculations are used to train the "screening module", which is a multi-layered perceptron (MLP) network, for estimating the performance indices (PIMW, PIV PIV). The MLP is trained to classify the contingencies either as critical or non-critical cases using back-propagation (BP) algorithm. The screened critical contingencies are passed on to the "ranking module" for ranking of the contingencies. The effectiveness of the proposed method is demonstrated by contingency screening and ranking on a standard 6-bus and IEEE 14-bus systems. The performance of the proposed method is compared with a traditional Newton Raphson (NR) method and the results discussed. The proposed methodology was implemented using the MATLAB Neural Network Toolbox. The generalization capability of the trained neural network was able to identify unknown contingencies with large range of operating conditions and changes in network topology. The proposed approach to contingency analysis was found to be suitable for fast voltage and line-flow contingency screening and ranking. © 2006 Elsevier B.V. All rights reserved.

Neural network approach to contingency screening and ranking in power systems

Most of the distribution systems are usually unbalanced and radial or near radial (weakly meshed). Presently, the integration of dispersed generations with the distribution system is becoming more popular. This article proposes a new object-oriented software modeling for distribution system power flow analysis. Object-oriented design of radial distribution system, assuming balanced operation, is obtained. Extensibility property of the object-oriented design is exploited to extend the radial system model to weakly meshed system and to incorporate the dispersed generations. The "composition" technique of object-oriented design has been employed to model the unbalanced three-phase system using the objects of balanced system. The modeled objects are implemented in C++ and the robustness of the developed power ,flow program has been tested for various balanced (10-bus, 33-bus, 69-bus, IEEE 37-bus) and unbalanced (IEEE 13-bus, IEEE 34-bus, IEEE 123-bus) test systems. Copyright © Taylor & Francis, LLC.

Object modeling of balanced and unbalanced distribution systems for power flow analysis

An efficient and reliable evolutionary-based meta-heuristic approach, termed as swarm intelligence, is presented for the solution of optimal power flow with both continuous and discrete variables. The continuous control variables are unit-active power outputs and generator-bus voltage magnitudes, while the discrete variables are transformer tap settings and switchable shunt devices. Particle swarm optimization, a new evolutionary computation technique based on swarm intelligence, is illustrated for two case studies of IEEE-30 bus system and 3-area IEEE RTS-96 system. Both normal and contingency states are considered for the optimal power flow solution. The feasibility of the proposed method is compared with a simple genetic algorithm. The algorithm is computationally faster, in terms of the number of load flows executed, and provides better results than other heuristic techniques. © Indian Institute of Science.

Journal of the Indian Institute of Science

Swarm intelligence approach to the solution of optimal power flow

This paper presents an efficient and reliable evolutionary based approach to solve the economic load dispatch (ELD) with security constraints. A new approach is proposed which employs attractive and repulsive particle swarm optimization (ARPSO) algorithm for ELD. Incorporation of ARPSO as a derivative-free optimization technique in solving ELD with security (voltages and line-flows) constraints significantly relieves the assumptions imposed on the optimized objective function. The proposed approach has been implemented on three representative systems, i.e. IEEE 14 bus, IEEE 30 bus and IEEE 57 bus systems, respectively. The feasibility of the proposed method is demonstrated and the results are compared with linear programming, quadratic programming and genetic algorithm, respectively. The premature convergence problem, that is common in all evolutionary computation techniques, is solved in ARPSO by including the diversity factor in the Type 1 PSO algorithm. The developed algorithms are computationally faster (in terms of the number of load flows carried out) than the other methods because only one run is required. © 2006 Elsevier Ltd. All rights reserved.

A new evolutionary computation technique for economic dispatch with security constraints

This paper presents a new transformerless series hybrid active power filter topology (TL-SHAPF). The active filter is in series with a capacitor. This combination is in parallel with an inductor and the entire arrangement is inserted in series with the line without the transformer. In this topology, current division method is employed along with series and parallel resonance concepts. The source current is provided with two different paths, one for harmonic current and another for fundamental current. The control structures are derived in the stationary reference frame through low-pass to band-pass transformation. Two such control strategies are presented. The effect of the controller on system performances is illustrated using state space approach. The modelling and simulation results are presented.