Showing papers in "IEEE Transactions on Power Systems in 2004"

Definition and classification of power system stability IEEE/CIGRE joint task force on stability terms and definitions

Abstract: The problem of defining and classifying power system stability has been addressed by several previous CIGRE and IEEE Task Force reports. These earlier efforts, however, do not completely reflect current industry needs, experiences and understanding. In particular, the definitions are not precise and the classifications do not encompass all practical instability scenarios. This report developed by a Task Force, set up jointly by the CIGRE Study Committee 38 and the IEEE Power System Dynamic Performance Committee, addresses the issue of stability definition and classification in power systems from a fundamental viewpoint and closely examines the practical ramifications. The report aims to define power system stability more precisely, provide a systematic basis for its classification, and discuss linkages to related issues such as power system reliability and security.

Analytical approaches for optimal placement of distributed generation sources in power systems

Abstract: Power system deregulation and the shortage of transmission capacities have led to increased interest in distributed generation (DG) sources. Proper location of DGs in power systems is important for obtaining their maximum potential benefits. This paper presents analytical methods to determine the optimal location to place a DG in radial as well as networked systems to minimize the power loss of the system. Simulation results are given to verify the proposed analytical approaches.

Unit commitment-a bibliographical survey

Abstract: With the fast-paced changing technologies in the power industry, new power references addressing new technologies are coming to the market. So there is an urgent need to keep track of international experiences and activities taking place in the field of modern unit-commitment (UC) problem. This paper gives a bibliographical survey, mathematical formulations, and general backgrounds of research and developments in the field of UC problem for past 35 years based on more than 150 published articles. The collected literature has been divided into many sections, so that new researchers do not face any difficulty in carrying out research in the area of next-generation UC problem under both the regulated and deregulated power industry.

Load forecasting using support vector Machines: a study on EUNITE competition 2001

Abstract: Load forecasting is usually made by constructing models on relative information, such as climate and previous load demand data. In 2001, EUNITE network organized a competition aiming at mid-term load forecasting (predicting daily maximum load of the next 31 days). During the competition we proposed a support vector machine (SVM) model, which was the winning entry, to solve the problem. In this paper, we discuss in detail how SVM, a new learning technique, is successfully applied to load forecasting. In addition, motivated by the competition results and the approaches by other participants, more experiments and deeper analyses are conducted and presented here. Some important conclusions from the results are that temperature (or other types of climate information) might not be useful in such a mid-term load forecasting problem and that the introduction of time-series concept may improve the forecasting.

Probabilistic load flow computation using the method of combined cumulants and Gram-Charlier expansion

Abstract: Open access transmission has created a deregulated power market and brought new challenges to system planning. This paper proposes a new method to compute a probabilistic load flow in extensive power systems for the purpose of using it as a quick screening tool to determine the major investment on improving transmission system inadequacy. This innovative method combines the concept of Cumulants and Gram-Charlier expansion theory to obtain probabilistic distribution functions of transmission line flows. It has significantly reduced the computational time while maintaining a high degree of accuracy. This enables probabilistic analysis of power flow problems to be treated objectively and allows quantitative assessment of system reliability.

A method for synchronization of power electronic converters in polluted and variable-frequency environments

Abstract: This paper presents a new synchronization method which employs an enhanced phase-locked loop (EPLL) system. The operational concept of the EPLL is novel and based on a nonlinear dynamical system. As compared with the existing synchronization methods, the introduced EPLL-based synchronization method provides higher degree of immunity and insensitivity to noise, harmonics and other types of pollutions that exist in the signal used as the basis of synchronization. The salient feature of the EPLL-based synchronization method over conventional synchronization methods is its frequency adaptivity which permits satisfactory operation when the centre frequency of the base signal varies. The proposed EPLL-based method of synchronization is also capable of coping with the unbalanced system scenarios. Structural simplicity of the EPLL-based method greatly simplifies its implementation in digital software and/or hardware environments as an integral part of a digital control platform for power electronic converters. The primary application of the proposed synchronization method is for the distributed generation units, e.g., wind generation systems, which utilize power electronic converters as an integral part of their systems.

Analysis of electric grid security under terrorist threat

Abstract: We describe new analytical techniques to help mitigate the disruptions to electric power grids caused by terrorist attacks. New bilevel mathematical models and algorithms identify critical system components (e.g., transmission lines, generators, transformers) by creating maximally disruptive attack plans for terrorists assumed to have limited offensive resources. We report results for standard reliability test networks to show that the techniques identify critical components with modest computational effort.

Optimal investment planning for distributed generation in a competitive electricity market

Abstract: This paper proposes a new heuristic approach for distributed generation (DG) capacity investment planning from the perspective of a distribution company (disco). Optimal sizing and siting decisions for DG capacity is obtained through a cost-benefit analysis approach based on a new optimization model. The model aims to minimize the disco's investment and operating costs as well as payment toward loss compensation. Bus-wise cost-benefit analysis is carried out on an hourly basis for different forecasted peak demand and market price scenarios. This approach arrives at the optimal feasible DG capacity investment plan under competitive electricity market auction as well as fixed bilateral contract scenarios. The proposed heuristic method helps alleviate the use of binary variables in the optimization model thus easing the computational burden substantially.

On the optimization of the daily operation of a wind-hydro power plant

Abstract: This paper proposes the utilization of water storage ability to improve wind park operational economic gains and to attenuate the active power output variations due to the intermittence of the wind-energy resource. An hourly-discretized optimization algorithm is proposed to identify the optimum daily operational strategy to be followed by the wind turbines and the hydro generation pumping equipments, provided that a wind-power forecasting is available. The stochastic characteristics of the wind power are exploited in the approach developed in order to identify an envelope of recommended operational conditions. Three operational conditions were analyzed and the obtained results are presented and discussed.

A solution to the unit-commitment problem using integer-coded genetic algorithm

Abstract: This paper presents a new solution to the thermal unit-commitment (UC) problem based on an integer-coded genetic algorithm (GA). The GA chromosome consists of a sequence of alternating sign integer numbers representing the sequence of operation/reservation times of the generating units. The proposed coding achieves significant chromosome size reduction compared to the usual binary coding. As a result, algorithm robustness and execution time are improved. In addition, generating unit minimum up and minimum downtime constraints are directly coded in the chromosome, thus avoiding the use of many penalty functions that usually distort the search space. Test results with systems of up to 100 units and 24-h scheduling horizon are presented.

Unit commitment by enhanced adaptive Lagrangian relaxation

Abstract: This paper proposes an enhanced adaptive Lagrangian relaxation (ELR) for a unit commitment (UC) problem. ELR consists of adaptive LR (ALR) and heuristic search. The ALR algorithm is enhanced by new on/off decision criterion, new initialization of Lagrangian multipliers, unit classification, identical marginal unit decommitment, and adaptive adjustment of Lagrangian multipliers. After the ALR best feasible solution reached is obtained, the heuristic search consisting of unit substitution and unit decommitment is used to fine tune the solution. The proposed ELR is tested and compared to conventional Lagrangian relaxation (LR), genetic algorithm (GA), evolutionary programming (EP), Lagrangian relaxation and genetic algorithm (LRGA), and genetic algorithm based on unit characteristic classification (GAUC) on the systems with the number of generating units in the range of 10 to 100. ELR total system production costs are less expensive than the others especially for the large number of generating units. Furthermore, the computational times of ELR are much less than the others and increase linearly with the system size, which is favorable for large-scale implementation.

Slow coherency-based islanding

Abstract: This paper provides the analytical basis for an application of slow coherency theory to the design of an islanding scheme, which is employed as an important part of a corrective control strategy to deal with large disturbances. The analysis is conducted under varying networks conditions and loading conditions. The results indicate that the slow coherency based grouping is almost insensitive to locations and severity of the initial faults. However, because of the loosely coherent generators and physical constraints the islands formed change slightly based on location and severity of the disturbance, and loading conditions. A detailed description of the procedure to form the islands after having determined the grouping of generators using slow coherency is presented. The verification of the islanding scheme is proven with simulations on a 179-bus, 29-generator test system.

Evaluation of time delay effects to wide-area power system stabilizer design

Abstract: Centralized control using system-wide data has been suggested to enhance the dynamic performance of large interconnected power systems. Because of the distance involved in wide-area interconnections, communication delay cannot be ignored. Long time delay may be detrimental to system stability and may degrade system performance. The time delay tolerance of a centralized controller and the associated performance tradeoff is analyzed using a small gain criterion. Special attention is paid to the choice of weighting functions in a robust control design. As expected, it is found that time delay tolerance decreases when the system bandwidth increases, while the nominal system time-domain performance is concomitantly improved. Several approaches which can maintain a good system performance while increasing the time delay tolerance are suggested and compared. A modern controller design technique, like gain scheduling via linear matrix inequalities, is evaluated for the design of the supervisory power system stabilizer accounting for various time delays.

Wide-area measurement-based stabilizing control of power system considering signal transmission delay

Abstract: Recent technological advances in the area of wide-area measurement systems (WAMS) has enabled the use of a combination of measured signals from remote locations for centralized control purpose. The transmitted signals can be used for multiple swing mode damping using a single controller. However, there is an unavoidable delay involved before these signals are received at the controller site. To ensure satisfactory performance, this delay needs to be taken into account in the control design stage. This paper focuses on damping control design taking into account a delayed arrival of feedback signals. A predictor-based H/sub /spl infin// control design strategy is discussed for such time-delayed systems. The concept is utilized to design a WAMS-based damping controller for a prototype power system using a static var compensator. The controller performance is evaluated for a range of operating conditions.

Support vector machines for transient stability analysis of large-scale power systems

Abstract: The pattern recognition approach to transient stability analysis (TSA) has been presented as a promising tool for online application. This paper applies a recently introduced learning-based nonlinear classifier, the support vector machine (SVM), showing its suitability for TSA. It can be seen as a different approach to cope with the problem of high dimensionality. The high dimensionality of power systems has led to the development and implementation of feature selection techniques to make the application feasible in practice. SVMs' theoretical motivation is conceptually explained and they are tested with a 2684-bus Brazilian system. Aspects of model adequacy, training time, classification accuracy, and dimensionality reduction are discussed and compared to stability classifications provided by multilayer perceptrons.

Energy price forecasting in the Ontario competitive power system market

Abstract: This paper introduces a method for forecasting energy prices using artificial intelligence methods, such as neural networks and fuzzy logic, and a combination of the two. The new approach is compared with some of the exiting methods. Various factors affecting the market clearing price are investigated. Results for the Ontario electricity market are presented.

Application of linear matrix inequalities for load frequency control with communication delays

Abstract: Load frequency control has been used for decades in power systems. Traditionally, this has been a centralized control by area with communication over a dedicated and closed network. New regulatory guidelines allow for competitive markets to supply this load frequency control. In order to allow an effective market operation, an open communication infrastructure is needed to support an increasing complex system of controls. While such a system has great advantage in terms of cost and reliability, the possibility of communication signal delays and other problems must be carefully analyzed. This paper presents a load frequency control method based on linear matrix inequalities. The primary aim is to find a robust controller that can ensure good performance despite indeterminate delays and other problems in the communication network.

Optimal reconfiguration of radial distribution systems to maximize loadability

Abstract: This paper presents a new method for optimal reconfiguration of radial distribution systems (RDS). Optimal reconfiguration involves selection of the best set of branches to be opened, one each from each loop, such that the resulting RDS has the desired performance. Amongst the several performance criteria considered for optimal network reconfiguration, maximizing loadability is an important one. Owing to the discrete nature of the solution space, a fuzzy adaptation of the evolutionary programming algorithm for optimal reconfiguration of RDS to maximize loadability is proposed in this paper. This method maximizes a fuzzy index developed using a maximum loadability index. A 33-bus RDS is optimally reconfigured by the proposed method and the results are presented.

A zonal congestion management approach using real and reactive power rescheduling

Abstract: In a deregulated electricity market, it may always not be possible to dispatch all of the contracted power transactions due to congestion of the transmission corridors. System operators try to manage congestion, which otherwise increases the cost of the electricity and also threatens the system security and stability. In this paper, a new zonal/cluster-based congestion management approach has been proposed. The zones have been determined based on lines real and reactive power flow sensitivity indexes also called as real and reactive transmission congestion distribution factors. The generators in the most sensitive zones, with strongest and nonuniform distribution of sensitivity indexes, are identified for rescheduling their real power output for congestion management. In addition, the impact of optimal rescheduling of reactive power output by generators and capacitors in the most sensitive zones has also been studied. The proposed new zonal concept has been tested on 39-bus New England system and a 75-bus Indian system.

A revised branch current-based distribution system state estimation algorithm and meter placement impact

Abstract: With the development of automation in distribution systems, distribution supervisory control and data acquisition (SCADA) and many automated meter reading (AMR) systems have been installed on distribution systems. Also distribution management system (DMS) have advanced and include more sophisticated analysis tools. The combination of these developments is providing a platform for development of distribution system state estimation (DSE). A branch-current-based three-phase state estimation algorithm for distribution systems has been developed and tested. This method chooses the magnitude and phase angle of the branch current as the state variables. Because of the limited number of real-time measurements in the distribution system, the state estimator can not acquire enough real-time measurements for convergence, so pseudo-measurements are necessary for distribution system state estimator. The load estimated at every node from the AMR systems is used as a pseudo-measurement for the state estimator. The algorithm has been tested on three IEEE radial test feeders. In addition to this new strategy for DSE, another issue is meter-placement. This topic includes the type of measurement as well as the location of the measurement. Our results show the impact of these two issues on accuracy. Several general meter rules based on this analysis are outlined.

Market-based transmission expansion planning

Abstract: Restructuring and deregulation has exposed transmission planner to new objectives and uncertainties. Therefore, new criteria and approaches are needed for transmission planning in deregulated environments. A new market-based approach for transmission planning in deregulated environments is presented in this paper. The main contribution of this research is: i) introducing a new probabilistic tool, named probabilistic locational marginal prices, for computing the probability density functions of nodal prices; ii) defining new market-based criteria for transmission expansion planning in deregulated environments; and iii) presenting a new approach for transmission expansion planning in deregulated environments using the above tool and criteria. The advantages of this approach are: i) it encourages and facilitates competition among all participants; ii) it provides nondiscriminatory access to cheap generation for all consumers; iii) it considers all random and nonrandom power system uncertainties and selects the final plan after risk assessment of all solutions; and iv) it is value based and considers investment cost, operation cost, congestion cost, load curtailment cost, and cost caused by system unreliability. The presented approach is applied to IEEE 30-bus test system.

Numerical solutions to Nash-Cournot equilibria in coupled constraint electricity markets

Abstract: A numerical method based on a relaxation algorithm and the Nikaido-Isoda function is presented for the calculation of Nash-Cournot equilibria in electricity markets. Nash equilibrium is attained through a relaxation procedure applied to an objective function, the Nikaido-Isoda function, which is derived from the existing profit maximization functions calculated by the generating companies. We also show how to use the relaxation algorithm to compute, and enforce, a coupled constraint equilibrium, which occurs if regulatory, generation, and distribution (and more) restrictions are placed on the companies and entire markets. Moreover, we use the relaxation algorithm to compute players' payoffs under several player configurations. This is needed for the solution of our game under cooperative game theory concepts, such as the bilateral Shapley value and the kernel. We show that the existence of both depends critically on demand price elasticity. The numerical method converges to a unique solution under rather specific but plausible concavity conditions. A case study from the IEEE 30-bus system, and a three-bus bilateral market example with a dc model of the transmission line constraints are presented and discussed.

An electricity market with a probabilistic spinning reserve criterion

Abstract: This paper addresses the problem of reliability-constrained market-clearing in pool-based electricity markets with unit commitment. In general, probabilistic reliability criteria that implicitly set the reserve requirement are defined by the loss-of-load probability and by the expected load not served. As the computation of such metrics is complicated by their nonlinear and combinatorial nature, we introduce the notion of hybrid metrics based on the probabilities of loss-of-load due to single and double generation outages only. The reliability-constrained market-clearing problem can then be formulated as a mixed-integer linear program and solved with large-scale commercial solvers. Numerical tests with data from the IEEE Reliability Test System indicate that the new method is computationally efficient and produces market-clearing results with the desired probabilistic characteristics.

Ant colony system algorithm for the planning of primary distribution circuits

Abstract: The planning problem of electrical power distribution networks, stated as a mixed nonlinear integer optimization problem, is solved using the ant colony system algorithm (ACS). The behavior of real ants has inspired the development of the ACS algorithm, an improved version of the ant system (AS) algorithm, which reproduces the technique used by ants to construct their food recollection routes from their nest, and where a set of artificial ants cooperate to find the best solution through the interchange of the information contained in the pheromone deposits of the different trajectories. This metaheuristic approach has proven to be very robust when applied to global optimization problems of a combinatorial nature, such as the traveling salesman and the quadratic assignment problem, and is favorably compared to other solution approaches such as genetic algorithms (GAs) and simulated annealing techniques. In this work, the ACS methodology is coupled with a conventional distribution system load-flow algorithm and adapted to solve the primary distribution system planning problem. The application of the proposed methodology to two real cases is presented: a 34.5-kV system with 23 nodes from the oil industry and a more complex 10-kV electrical distribution system with 201 nodes that feeds an urban area. The performance of the proposed approach outstands positively when compared to GAs, obtaining improved results with significant reductions in the solution time. The technique is shown as a flexible and powerful tool for the distribution system planning engineers.

Robust damping of multiple swing modes employing global stabilizing signals with a TCSC

Abstract: This paper demonstrates a robust damping control design for multiple swing mode damping in a typical power system model using global stabilizing signals. A multiple-input, single-output (MISO) controller is designed for a thyristor-controlled series capacitor (TCSC) to improve the damping of the critical interarea modes. The stabilizing signals are obtained from remote locations based on observability of the critical modes. A H/sub /spl infin// damping control design based on the mixed-sensitivity formulation in a linear matrix inequality (LMI) framework is carried out. It is shown that, with local signal, supplementary damping control through three flexible AC transmission systems (FACTS) devices is necessary to provide damping to the three dominant interarea modes. On the other hand, the use of global signals has been shown to improve the damping of all the critical interarea modes with a single controller for the TCSC only. The damping performance of the centralized controller was examined in the frequency and the time domain for various operating scenarios. The controller was found to be robust against varying power-flow patterns, load characteristics, tie-line strengths, and system nonlinearities, including saturation.

Pricing energy and ancillary services in integrated market systems by an optimal power flow

Abstract: A detailed AC OPF-based formulation for procuring, pricing, and settling energy and ancillary service in simultaneous auctions by integrated market systems is presented. The paper provides clear definitions of locational marginal prices for energy and ancillary service marginal prices in terms of Lagrange multipliers. The characteristics of the prices are analyzed especially when economic substitution among ancillary services is required. The paper also evaluates the conditions under which opportunity costs are incurred to units that provide ancillary services. It is particularly shown that the intuitive belief that the provision of regulation down service does not incur opportunity cost to the provider, in general, is not true.

Multistage and coordinated planning of the expansion of transmission systems

Abstract: In this paper, an efficient genetic algorithm (GA) is presented to solve the problem of multistage and coordinated transmission expansion planning. This is a mixed integer nonlinear programming problem, difficult for systems of medium and large size and high complexity. The GA presented has a set of specialized genetic operators and an efficient form of generation of the initial population that finds high quality suboptimal topologies for large size and high complexity systems. In these systems, multistage and coordinated planning present a lower investment than static planning. Tests results are shown in one medium complexity system and one large size high complexity system.

Marginal loss modeling in LMP calculation

Abstract: This paper discusses the pricing of marginal transmission network losses in the locational marginal pricing approach recently deployed in the ISO New England (ISO-NE) standard market design (SMD) project implemented by ALSTOM's T&D Energy Automation and Information (EAI) Business. The traditional loss model is studied and a new model is proposed. The new model achieves more defendable and predictable market-clearing results by introducing loss distribution factors to explicitly balance the consumed losses in the lossless dc power system model. The distributed market slack reference is also introduced and discussed. The LMP components produced by the two models are studied and compared under changes in slack reference. Numerical examples are presented to further compare the two models.

A state-queueing model of thermostatically controlled appliances

Abstract: This paper develops a state-queueing model to analyze the price response of aggregated loads consisting of thermostatically controlled appliances (TCAs). Assuming a perfectly diversified load before the price response, we show that TCA setpoint changes in response to the market price will result in a redistribution of TCAs in on/off states and therefore change the probabilities for a unit to reside in each state. A randomly distributed load can be partially synchronized and the aggregated diversity lost. The loss of the load diversity can then create unexpected dynamics in the aggregated load profile. Raising issues such as restoring load diversity and damping the peak loads are also addressed in this paper.

A solution to the stochastic unit commitment problem using chance constrained programming

Abstract: This paper develops a solution method for scheduling units of a power-generating system to produce electricity by taking into consideration the stochasticity of the hourly load and its correlation structure. The unit commitment problem is initially formulated as a chance constrained optimization problem in which we require that the load be met with a specified high probability over the entire time horizon. The solution procedure consists of solving a sequence of deterministic versions of the unit commitment problem that converge to the solution of the chance constrained program. For the deterministic unit commitment problems, Lagrangian relaxation is used to separate the dual problem into its subproblems. Each subproblem is solved by a dynamic program. The initial results indicate that accounting for the correlation structure of the hourly loads reduces the value of the objective function when the optimization problem is formulated as a chance constrained program. Monte Carlo simulation is used to verify the accuracy of the solution provided by the algorithm. The relationship that the unit commitment solution found using the chance constrained optimization approach has with that found using conventional spinning reserves is discussed.