Showing papers in "Electric Power Components and Systems in 2009"
TL;DR: In this article, a genetic algorithm-based method was used to determine optimal location and size of the distributed generations to be placed in radial, as well as networked, systems with an objective to minimize the power loss.
Abstract: This article presents a genetic algorithm-based method to determine optimal location and size of the distributed generations to be placed in radial, as well as networked, systems with an objective to minimize the power loss. Several simulation studies have been conducted on radial feeders, as well as networked systems, considering single-distributed generation and multiple-distributed generations separately to minimize the power loss of the system subjected to no voltage violation at any of the buses. Simulation results are given, and the results are compared with the results of Wang and Hashem Nehrir [“Analytical approaches for optimal placement of distributed generation sources in power systems,” IEEE Trans. Power Syst., Vol. 19, No. 4, pp. 2068–2076, November 2004] and Gozel et al. [“Optimal placement and sizing of distributed generation on radial feeder with different static load model,” Proc. of IEEE International Conference on Future Power Systems (EPS 2005), pp. 1–6, Amsterdam, The Netherl...
144 citations
TL;DR: In this paper, a wavelet transform and wavelet-support vector machine (SVM) is used to extract the most important and significant feature from details and approximation waves. And the obtained severable feature vectors are used for training the support vector machines to classify the power quality disturbances.
Abstract: Recognition of power quality events by analyzing voltage waveform disturbances is a very important task for power system monitoring. This article presents a novel approach for the recognition and classification of power quality disturbances using wavelet transform and wavelet-support vector machines. The proposed method employs wavelet transform techniques to extract the most important and significant feature from details and approximation waves. The obtained severable feature vectors are used for training the support vector machines to classify the power quality disturbances. Various transient events, such as voltage sag, swell, interruption, harmonic, transient, sag with harmonic, swell with harmonic, and flicker, are tested. Sensitivity of the proposed algorithm under different noise conditions is investigated in this article. The results show that the classifier can detect and classify different power quality signals, even under noisy conditions, correctly.
80 citations
TL;DR: In this paper, the authors introduce a specific and simple model for electric vehicles suitable for load flow studies, which is modeled as a PQ bus with stochastic characteristics based on the concept of the queuing theory.
Abstract: This article introduces a specific and simple model for electric vehicles suitable for load flow studies. The electric vehicles demand system is modeled as a PQ bus with stochastic characteristics based on the concept of the queuing theory. All appropriate variables of stochastic PQ buses are given with closed formulas as a function of charging time. A specific manufacturer model of electric vehicles is used as study case.
72 citations
TL;DR: The proposed improved quantum evolutionary algorithm adopts both the simplified rotation gate and the decreasing rotation angle approach in order to improve the convergence performance of the conventional quantum-inspired evolutionary algorithm.
Abstract: This article presents a new approach for solving unit commitment problems using a quantum-inspired evolutionary algorithm The unit commitment problem is a complicated non-linear and mixed-integer combinatorial optimization problem with heavy constraints This article proposes an improved quantum evolutionary algorithm to effectively solve unit commitment problems The quantum-inspired evolutionary algorithm is considered a novel evolutionary algorithm inspired by quantum computing, which is based on the concept and principles of quantum computing such as the quantum bit and the superposition of states The proposed improved quantum evolutionary algorithm adopts both the simplified rotation gate and the decreasing rotation angle approach in order to improve the convergence performance of the conventional quantum-inspired evolutionary algorithm The suggested simplified rotation gate can determine the rotation angle without a lookup table, while the conventional rotation gate requires a predefined
64 citations
TL;DR: A biogeography-based optimization technique for solving constrained economic dispatch problems in a power system, considering the non-linear characteristics of generators such as valve point loading, ramp rate limits, prohibited operating zones, and multiple fuels cost functions, is presented in this article.
Abstract: This article presents a biogeography-based optimization technique for solving constrained economic dispatch problems in a power system, considering the non-linear characteristics of generators such as valve point loading, ramp rate limits, prohibited operating zones, and multiple fuels cost functions. In this article, the proposed algorithm has been tested in different systems under various simulated conditions. A comparison of simulation results reveals optimization efficacy of the proposed scheme over the genetic algorithm, particle swarm optimization, the Hopfield model, etc., for the global optimization of multi-objective constrained economic load dispatch problems.
61 citations
TL;DR: In this article, the authors present an extensive survey of current research on the transformer loss problem, particularly from the view of practical engineering applications, and reveal that transformer loss remains an active research area.
Abstract: This article presents an extensive survey of current research on the transformer loss problem, particularly from the view of practical engineering applications. It reveals that the transformer loss problem remains an active research area. This article classified the transformer loss problem into three main groups: (a) tank losses due to high-current bushings, (b) losses in transformer core joints, and (c) stray losses in the transformer tank. It is based on over 50 published works, which are all systematically classified. The methods, the size of transformers, and other relevant aspects in the different works are discussed and presented.
57 citations
TL;DR: In this article, the influence of the length of transmission interface between the generator and the infinite bus is studied, and the effect of increased penetration of constant speed wind turbine generator power for different configurations, namely single turbine, wind farm, and scattered wind turbine, has been studied.
Abstract: This article analyzes the influence of constant speed wind turbine generators on power system oscillation. First, mode distributions have been compared between the constant speed wind turbine generator and the synchronous generator connected to an infinite bus, and the outcome of machine vulnerability to oscillatory instability is identified. The influence of the length of transmission interface between the generator and infinite bus is also studied. Then, the influence of load increase and penetration of a constant speed wind turbine generator on power system oscillation is studied in detail. Finally, the effect of increased penetration of constant speed wind turbine generator power for different configurations, namely single turbine, wind farm, and scattered wind turbine, has been studied. In all of the unstable cases, a static var compensator is used to improve the stability of the system.
56 citations
TL;DR: In this paper, the authors presented a new, improved particle swarm optimization algorithm with a selection operator for the solution of the combined heat and power economic dispatch problem, starting with a large swarm of particles, only those particles whose fitness is above the scaled average fitness are selected in successive iterations.
Abstract: This article presents a new, improved particle swarm optimization algorithm with a selection operator for the solution of the combined heat and power economic dispatch problem In this technique, starting with a large swarm of particles, only those particles whose fitness is above the scaled average fitness are selected in successive iterations, using a selection factor that is adjustable depending on the nature of the problem The method is illustrated using a test case The result compares favorably with other particle swarm optimization variants and other existing non-conventional methods
56 citations
TL;DR: In this article, a hierarchical Markov modeling technique for reliability evaluation of phasor measurement unit is presented, where each module is hierarchically represented using Markov state space models and equivalently converted into two-state Markov representations, such that the reliability of the entire PHASOR measurement unit can be easily evaluated.
Abstract: The consequence of a phasor measurement unit failure is very severe and may cause a blackout as it is a primary part of a wide-area measurement system. This article presents a hierarchical Markov modeling technique for reliability evaluation of phasor measurement unit. A phasor measurement unit is divided into seven modules for reliability modeling in terms of the functionalities of phasor measurement unit elements. Each module is hierarchically represented using Markov state space models and equivalently converted into two-state Markov representations, such that the reliability of the entire phasor measurement unit can be easily evaluated. The numerical results and sensitivity analyses indicate that the global positioning system module is the most unreliable source of phasor measurement unit, followed by the central processor unit module. The failure rate of the global positioning system receiver (λA) is the most crucial parameter to the phasor measurement unit reliability, followed by the failu...
53 citations
TL;DR: In this article, a steady-state permanent magnet synchronous generator model in a d-q reference frame is presented, and an integrative study that combines generator-converted power with extracted wind power characteristics is conducted.
Abstract: With the advance of power electronics, direct-driven permanent magnet synchronous generators have drawn increased interest to wind turbine manufacturers due to its advantages over other variable-speed wind turbines. This article studies permanent magnet synchronous generator characteristics under the general d-q control strategy in the rotor-flux-oriented frame so as to benefit the development of advanced permanent magnet synchronous generator control technology. Compared to traditional approaches, the specific features of the article are (1) a steady-state permanent magnet synchronous generator model in a d-q reference frame, (2) a simulation mechanism that reflects the general permanent magnet synchronous generator d-q control strategy, (3) an integrative study that combines generator-converted power with extracted wind power characteristics, and (4) a joint investigation incorporating both steady-state and transient evaluations. Extensive simulation-based analysis is conducted to study how per...
44 citations
TL;DR: The proposed algorithm involves less complex mathematical expressions, and a more efficient network configuration can be obtained with reduced power losses, because it takes a smaller number of switchings and less CPU time.
Abstract: This article presents a simple reconfiguration algorithm that is specially suited for balanced and unbalanced radial distribution systems. The proposed algorithm involves less complex mathematical expressions, and a more efficient network configuration can be obtained with reduced power losses. The choice of the switches to be closed is based on the calculation of bus voltages and the minimum total system losses using a power flow program. This method takes a smaller number of switchings and less CPU time. Results obtained on one balanced system and two unbalanced systems are also presented and compared with the existing methods.
TL;DR: In this paper, an evolutionary algorithm-based optimal reactive power planning approach was developed and implemented using differential evolution, particle swarm optimization, and the genetic algorithm to minimize real power loss and improve the voltage profile of an interconnected power system.
Abstract: This article presents evolutionary algorithm-based optimal reactive power planning. A “loss sensitivity” approach is developed and implemented using differential evolution, particle swarm optimization, and the genetic algorithm. The objectives are to minimize real power loss and to improve the voltage profile of an interconnected power system. Transmission loss is expressed in terms of voltage increments by relating the control variables, i.e., reactive var generations by the generators, tap positions of transformers, and reactive power injected by the shunt capacitors. Based on the values of the loss sensitivity, corrective action is taken by adding a shunt capacitor at the weak buses identified by weak bus analysis, by controlling reactive generations at the generator buses by judging the sensitivity at these buses, and also by controlling tap changing positions if the tap changing transformers are in between the loss sensitive buses. The solutions obtained by this method is compared with the s...
TL;DR: In this paper, the authors address two well-known problems of competitive electricity markets: (1) reactive power procurement and (2) congestion management, using social welfare maximization in pool-based competitive energy markets.
Abstract: This article addresses two well-known problems of competitive electricity markets: (1) reactive power procurement and (2) congestion management, using social welfare maximization in pool based competitive electricity markets. The social welfare function, which customarily consists of the benefit function of consumers and cost function of real power generation, is modified to include the cost function of reactive power generation. This will incorporate an economic signal regarding production and consumption of reactive power within locational marginal prices payable to the suppliers and chargeable from the consumers at different locations. The reactive power cost function of a synchronous generator is modeled using the lost opportunity to trade real power to produce required amount of reactive power. An approximate P-Q capability curve of the synchronous generator is used for this purpose. Further, the effect of incorporation of consumers' benefit bids on managing system congestion at an acceptabl...
TL;DR: In this article, an internal model control with a conditional integrator is proposed for the robust output regulation of a DC/DC buck converter, which can be converted into a robust stabilization problem of an augmented system consisting of the given buck converter and the internal model by introducing a proper internal model.
Abstract: An internal model control with a conditional integrator is proposed for the robust output regulation of a DC/DC buck converter. Based on the input–output linearization from the state-space averaged model of DC/DC buck converter, the robust output regulation problem of the converter can be converted into a robust stabilization problem of an augmented system consisting of the given buck converter and the internal model by introducing a proper internal model. The procedures include the design of an internal model with conditional integrator and a sliding-mode robust controller. Also the closed-loop robust stability is theoretically analyzed. Finally, the effectiveness of the proposed converter is verified in comparing the proposed controller performance with open-loop control, single-loop proportional-plus-integral control, and double-loop proportional-plus-integral control under load disturbances and supply voltage variations.
TL;DR: It has been shown that the proposed variable-segmented support vector machine model possessed better forecasting abilities than the other models and its performance was least affected by the volatility.
Abstract: In this article, the wholesale price of the Ontario electricity market has been forecasted by splitting the time series into 24 series, one for each hour of the day. Then, a one-step ahead forecast for each hour of the next day for a test period of three years has been made using the respective hour–time series and by employing a support vector machine. A detailed sensitivity analysis was performed for the selection of model parameters. Furthermore, the performance of a support vector machine model has been compared with a heuristic technique, simulation model, linear regression model, neural network model, neuro-fuzzy model, autoregressive integrated moving average model, dynamic regression model, and transfer function model. It has been shown that the proposed variable-segmented support vector machine model possessed better forecasting abilities than the other models and its performance was least affected by the volatility.
TL;DR: In this paper, a novel scheme for automatic mode switching of a microturbine-based distributed generation system between the grid-connected and islanding modes of operation is proposed, based on the phase angle estimated by the phase-locked loop.
Abstract: The intentional islanding operation of grid-connected distributed generation systems can greatly improve the reliability and quality of the power supply. The existing control techniques for distributed generation systems are designed to operate either in the grid-connected or islanding modes of operation, thus, not allowing for both modes to be implemented and transitioned between. In this article, a novel scheme for automatic mode switching of a microturbine-based distributed generation system between the grid-connected and islanding modes of operation is proposed. The presented scheme is based on the phase angle estimated by the phase-locked loop. The developed phase-locked loop provides an accurate estimation of the phase angle even under unbalanced conditions. The presented scheme does not negatively affect the distributed generation system or utility operations and can work even under matching distributed generation and load power ratings. In this work, back-to-back converters are used to in...
TL;DR: In this paper, a hybrid methodology integrating artificial immune systems with sequential quadratic programming for solving the dynamic economic dispatch problem of generating units considering valve-point effects is proposed, which can give good direction to the optimal region and local search procedure, which is used to fine tune that region for achieving the final solution.
Abstract: Dynamic economic dispatch deals with the scheduling of online generator outputs with predicted load demands over a certain period of time so as to operate an electric power system most economically. This article proposes a hybrid methodology integrating artificial immune systems with sequential quadratic programming for solving the dynamic economic dispatch problem of generating units considering valve-point effects. This hybrid method incorporates artificial immune systems as a base level search, which can give good direction to the optimal region and sequential quadratic programming as a local search procedure, which is used to fine tune that region for achieving the final solution. Numerical results of a ten-unit system have been presented to demonstrate the performance and applicability of the proposed algorithm. The results obtained from the proposed algorithm are compared with those obtained from a hybrid of particle swarm optimization and sequential quadratic programming and a hybrid of ev...
TL;DR: In this article, a new model for wind turbine systems with asynchronous generators is proposed, which facilitates the computation of real and reactive power outputs for a specified mechanical power input and terminal voltages in a simple way.
Abstract: In this article, a new model for wind turbine systems with asynchronous generators is proposed. The model is developed by using the steady-state model of an induction machine. It is validated with an experimental setup composed by an induction generator coupled with an induction motor as a prime mover, and it is also tested on a simulation system. Results are also compared with the results of the other models reported in the literature for both systems. It is concluded that the developed model is comparable with the existing ones. The main advantage of the model is that it facilitates the computation of real and reactive power outputs for a specified mechanical power input and terminal voltages in a simple way such that it does not require computation of any system parameters (i.e., rotor slip and/or current), which causes computational complexity.
TL;DR: Test results indicate that the proposed neural network is better than the other methods due to a lower total cost and faster computational time, especially for large-scale combined heat and power economic dispatch problems.
Abstract: This article proposes an augmented Lagrange–Hopfield network for the combined heat and power economic dispatch problem. The augmented Lagrange–Hopfield network method is the continuous Hopfield neural network with its energy function based on augmented Lagrangian relaxation. In the proposed augmented Lagrange–Hopfield network, the energy function is augmented by Hopfield terms from the Hopfield neural network and penalty factors from the augmented Lagrangian function to damp out oscillation of the Hopfield network during the convergence process, leading to a fast convergence. The proposed augmented Lagrange–Hopfield network has been tested on various systems and compared to Lagrangian relaxation, the genetic algorithm, the improved ant colony search algorithm, evolutionary programming, the improved genetic algorithm with multiplier updating, and the harmony search algorithm. Test results indicate that the proposed neural network is better than the other methods due to a lower total cost and faste...
TL;DR: In this article, the reactive power capability of a doubly-fed induction generator through the use of performance capability curves was derived. But the performance of the generator was not analyzed.
Abstract: In the new electricity grid code, reactive power generation by wind farms, which must operate similarly to other conventional power plants, is a major concern during both steady-state and fault conditions. This article presents the reactive power capability of a doubly-fed induction generator through the use of performance capability curves. First, three steady-state models of doubly-fed induction generators are derived in terms of (i) stator and rotor voltage (V S and V R), (ii) stator voltage and rotor current (V S and I R), and (iii) stator voltage and stator current (V S and I S), to derive the limitations in the reactive power production caused by the rotor voltage, rotor current, and stator current limits, respectively. Second, the reactive power capability of the grid-side converter is included. Finally, a complete capability curve of doubly-fed induction generators for stator voltages is developed by optimization of rotor speed employing the maximum power point tracking algorithm. It is e...
TL;DR: The results show that the optimal time domain performance of the system can be achieved with the fuzzy logic controller, which removes the steady-state error in less time with no overshoot and oscillation.
Abstract: Gas turbine generators, normally used in isolated operation, require an effective control and design for their parallel operation. Otherwise, the load variations and set-point variations may cause severe stability problems. Soft computing techniques, such as genetic algorithms, artificial neural networks, and fuzzy logic, have been utilized for developing a controller for a gas turbine plant. The proportional-integral-derivative controller is used to control the gas turbine plant because of its versatility, high reliability, and ease of operation. For better performance, the gains of the proportional-integral-derivative controller have been tuned using the Ziegler–Nichols method and genetic algorithm. The artificial neural network and fuzzy controllers are developed, and the performance is compared with the conventional proportional-integral-derivative controller. The results show that the optimal time domain performance of the system can be achieved with the fuzzy logic controller. The fuzzy log...
TL;DR: In this paper, a non-dominated sorting genetic algorithm-II is employed to approximate the set of Pareto solutions through an evolutionary optimization process, and a multi-attribute decision-making approach is adopted to rank these solutions from best to worst and to determinate the best solution in a deterministic environment with a single decision-maker.
Abstract: Dynamic economic dispatch plays an important role in power system operation, which is a complicated non-linear constrained optimization problem. It has non-smooth and non-convex characteristics when generation unit valve-point effects are taken into account. Environmental awareness and recent environmental policies have forced electric utilities to restructure their practices to account for their emission impacts. The dynamic economic/environmental dispatch problem is studied in the present analysis; this article proposes a hybrid approach. In the first stage, a non-dominated sorting genetic algorithm-II is employed to approximate the set of Pareto solutions through an evolutionary optimization process. In the subsequent stage, a multi-attribute decision-making approach is adopted to rank these solutions from best to worst and to determinate the best solution in a deterministic environment with a single decision-maker. This hybrid approach is tested on a ten-unit system to illustrate the analysis...
TL;DR: In this paper, the effect of a few types of ferroresonance suppression circuits on suppression of the phenomenon of ferrosonance in coupling capacitor voltage transformers is investigated.
Abstract: This article investigates the effect of a few types of ferroresonance suppression circuits on suppression of the phenomenon of ferroresonance in coupling capacitor voltage transformers A novel technique is proposed for damping of dangerous overvoltages due to ferroresonance In this technique, by using power electronic devices, a damping resistance is switched to the secondary side of the system transformer during dangerous oscillations This technique leads to important cost and damping-time reductions when compared with conventional alternatives Additional devices, such as surge arresters, may be added to improve the performance of the ferroresonance suppression circuit The technique proposed in this article is a “novel but classic” technique The prediction of ferroresonance is achieved by detailed modeling using a digital computer transient analysis program such as the EMTP/ATP
TL;DR: In this article, the authors presented the design technique of an adaptive power system stabilizer using adaptive neuro-fuzzy inference systems trained via data obtained from genetic algorithms, where a genetic algorithm was used to minimize a multi-objective optimization function that forces the damping ratio and settling time of the system to desired values.
Abstract: This article presents the design technique of an adaptive power system stabilizer using adaptive neuro-fuzzy inference systems trained via data obtained from genetic algorithms. The parameters of a standard power system stabilizer are tuned using adaptive neuro-fuzzy inference systems to achieve a certain damping ratio and settling time at all load points within a wide region of operation. The overall transfer function of the system is derived in terms of the power system stabilizer parameters. A genetic algorithm is used to minimize a multi-objective optimization function that forces the damping ratio and settling time of the system to desired values. The optimization process is separately conducted at selected operating points to yield power system stabilizer parameters that change with load variations. Results of genetic algorithm optimization are used to form a training dataset of an adaptive neuro-fuzzy inference systems agent, which could give the power system stabilizer parameters at any l...
TL;DR: In this paper, an improved top oil temperature rise model of a distribution transformer is used to assess the impact of ambient temperature change on distribution transformer life. But the model is not suitable for the case of large-scale distribution transformers.
Abstract: This article describes the use of an improved top oil temperature rise model of a distribution transformer. The IEEE Standard C57.91-1995 model for transformer thermal calculations is discussed briefly, and a loss of life calculation based on the “10-degree rule” is formulated. This loss of life formulation is used with the improved model for top oil temperature rise to assess the impact of ambient temperature change on distribution transformer life. A probabilistic model for ambient temperature rise is used, and an increased ambient temperature of 3.5°C in 100 years is studied. Seven artifact transformers and four loading test beds are considered. The service life calculated for a base case and an increased ambient temperature case shows that there is a reduction of the order of 3–6 years for the cases studied.
TL;DR: In this paper, a denoising scheme of wavelet transform coefficients in noisy environment is proposed to avoid the false alarm rate and to increase the detection capability of WT-based power quality monitoring schemes.
Abstract: The excellent time-frequency localization property of the wavelet transform has made it a very promising tool for detection and analysis of the power quality disturbances. Many researchers have shown the adverse effect of noise on wavelet-based power quality monitoring and demonstrated that the performance of the wavelet transform in detecting the power quality disturbance would be greatly degraded due to the difficulty of distinguishing the noise and the disturbances. Practically, the power quality signals are often mixed with electromagnetic noise. This article proposes a denoising scheme of wavelet transform coefficients in noisy environment to avoid the false alarm rate and to increase the detection capability of wavelet transform-based power quality monitoring schemes. Contrary to the threshold-based techniques used so far in the power area for denoising power quality data, the technique used in this article exploits the local structure of wavelet coefficients. The effectiveness of the propo...
TL;DR: In this paper, the steady-state modeling and analysis of a six-phase self-excited induction generator for stand-alone renewable generation is presented, based on graph theory as applied to the equivalent circuit.
Abstract: This article presents the steady-state modeling and analysis of a six-phase self-excited induction generator for stand-alone renewable generation. The basis of the analysis is the nodal admittance method based on graph theory as applied to the equivalent circuit. The proposed steady-state generalized model of a six-phase self-excited induction generator dispenses with the tedious work of segregating real and imaginary components of the complex impedance of the induction generator for deriving the specific models for each operating mode. Graph theory based matrix equations are easier to modify in order to account for specific effects such as uncompensated and compensated operation. The resulting equations have excellent symmetry, which makes the analysis very easy, fast, and accurate. The matrix equations developed by the nodal admittance method are solved by a genetic algorithm to determine the steady-state performance of a six-phase self-excited induction generator. The analytical results are fo...
TL;DR: A solution for the dynamic economic dispatch problem using a hybrid technique of the Hopfield neural network and quadratic programming and guaranteeing the global optimality of the solution due to its look-ahead capability is introduced.
Abstract: This article introduces a solution for the dynamic economic dispatch problem using a hybrid technique of the Hopfield neural network and quadratic programming. This hybrid algorithm is based on using the enhanced Hopfield neural network to solve the static part of the problem and the quadratic programming algorithm for solving the dynamic part of the dynamic economic dispatch. This technique guarantees the global optimality of the solution due to its look-ahead capability. The proposed technique is applied to and tested on an example from the literature, and the solution is then compared with that obtained by some other techniques to prove the validity and effectiveness of the proposed algorithm.
TL;DR: In this paper, the performance of a three-phase squirrel cage induction motor fed by an unbalanced voltage supply has been investigated using Matlab/Simulink simulation and experimental results.
Abstract: The performance of a three-phase squirrel cage induction motor fed by an unbalanced voltage supply has been investigated in this article. Matlab/Simulink software is used for simulation of the motor using simple (conventional) and exact models under different unbalanced voltage conditions. Simulation results are verified by performing experimental tests on a 1.5-kW standard three-phase induction motor. With the aid of simulation and experimental results, variations of stator current, motor efficiency, power factor, and rotor ripple have been investigated under various steady-state unbalanced voltage conditions. It is shown that, in addition to the voltage unbalance factor, the magnitude of positive and negative sequence components of the unbalanced supply voltage have an important role on motor performance. For instance, motor power factor decreases with the increase of positive sequence voltage component, even if the voltage unbalance factor is constant. Also, the motor efficiency decreases with...
TL;DR: In this paper, the authors illustrate the utilization of multi-state generating unit models in unit commitment risk analysis of a wind-integrated electric power system using the IEEE reliability test system.
Abstract: This article illustrates the utilization of multi-state generating unit models in unit commitment risk analysis of a wind-integrated electric power system. The IEEE reliability test system is used as the study system and has been augmented using actual generating unit data from the Canadian Electricity Association database to include multi-state models for the larger units. The effects on the unit commitment risk and on the peak load-carrying capability of the IEEE reliability test system due to adding wind-generating capacity are illustrated using a series of studies dealing with scheduled operating capacity levels, generating unit derated state models, and wind conditions.