the objective of this paper is to investigate the application of FACTS devices to increase the maximum loadability of power transmission lines which may be constrained by a transient stability limit. Hence, the online...
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the objective of this paper is to investigate the application of FACTS devices to increase the maximum loadability of power transmission lines which may be constrained by a transient stability limit. Hence, the online fuzzy control of superconducting magnetic energy storage (SMES) and static synchronous series compensators (SSSC) are suggested. the fuzzy rule-bases are defined and explained. the validity of the suggested control strategies are confirmed by simulation tests which show that by the use of the proposed method, the line power transfer can be increased via the improvement of the transient stability limit. Finally, the effect of the control loop time delay on the performance of the controller is presented.
this paper represents a technique based on constraints surrogate defined by the maximum entropy principle for optimal power flow (OPF) problems. One of the obstacles impeding the OPF calculations is the problem associ...
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this paper represents a technique based on constraints surrogate defined by the maximum entropy principle for optimal power flow (OPF) problems. One of the obstacles impeding the OPF calculations is the problem associated with handling a large number of functional inequality constraints, which cause computational inefficiencies for large power systems. To cope withthis problem, this paper proposes a methodology which aggregates all inequality constraints into one surrogate constraint with a single parameter according to the maximum entropy principle. this implementation not only reduces the scale or dimensions of OPF problems, but also improves the convergence characteristics. Several numerical examples including a practical power system are provided to show the efficiency of the proposed approach.
A fast, effective service restoration method is designed for large-scale distribution systems with priority customers. the service restoration problem is formulated as a constrained multi-objective optimization proble...
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A fast, effective service restoration method is designed for large-scale distribution systems with priority customers. the service restoration problem is formulated as a constrained multi-objective optimization problem. A ranking-based search method employing analytical information obtained from three-phase power flow simulations is designed to restore service to as many priority customers as possible while maximizing the amount of total load restored and minimizing the number of required switch operations. the proposed method is designed with consideration to networks which have predominantly manual switches. Comprehensive simulation results of the search method, including priority customers, single and multiple faults and multiple out-of-service areas are presented for a 416 bus distribution network.
Power system state estimation derives a real-time network model by extracting information from a redundant data set consisting of telemetered, predicted and static data items. this paper describes a generalized, fully...
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Power system state estimation derives a real-time network model by extracting information from a redundant data set consisting of telemetered, predicted and static data items. this paper describes a generalized, fully developed, estimation approach that fundamentally improves the information extraction process. Its main contribution is the successful inclusion of topology and parameters in the estimation and bad data analysis processes. this is valuable both in the initial commissioning of a state estimator, and in its routine real-time and study mode application. the approach involves a variety of novel concepts and methods. It is usable in weighted least squares (WLS) and other estimation approaches.
For pt.I see ibid., p.78-83 (1997). the results of the evaluation of a new type of digital filter are presented in this paper. the filter theory is outlined in part I of the paper. the new filter results from the appl...
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For pt.I see ibid., p.78-83 (1997). the results of the evaluation of a new type of digital filter are presented in this paper. the filter theory is outlined in part I of the paper. the new filter results from the application of a special window to the coefficients of the traditional Fourier, cosine and sine algorithms. It is compared in the paper withthe Fourier, cosine and sine filters in terms of steady-state and transient responses. Extensive time-domain simulations are performed to evaluate the filter transient behavior. the new filter is shown to be more accurate than the Fourier filter for window lengths equal or greater than 3 cycles of the fundamental frequency. It retains its accuracy even for window lengths being different from multiples of one cycle. the new filter is suitable for phasor computation for the fault location and measuring functions required in digital distance relays and fault recorders.
In competitive electricity markets, human decision-makers need assistance to determine potential coalitions that they can be part of. the authors present an approach for designing specialized intelligent software agen...
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In competitive electricity markets, human decision-makers need assistance to determine potential coalitions that they can be part of. the authors present an approach for designing specialized intelligent software agents that perform negotiations on behalf of their human counterparts, and then suggest market strategies that the human can adopt. the authors' negotiation protocol is derived from cooperative game theory; however, it differs from the game theory literature in requiring virtually no trustworthy information exchange between the potential condition partners. In this paper, they apply it to power markets.
In competitive electricity markets, human decision-makers need assistance to determine potential coalitions that they can be part of. the authors present an approach for designing specialized intelligent software agen...
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In competitive electricity markets, human decision-makers need assistance to determine potential coalitions that they can be part of. the authors present an approach for designing specialized intelligent software agents that perform negotiations on behalf of their human counterparts, and then suggest market strategies that the human can adopt. their negotiation protocol is derived from cooperative game theory; however, it differs from the game theory literature in requiring virtually no trustworthy information exchange between the potential coalition partners. In this paper, the authors present the negotiation model.
Electric utility SCADA systems must be highly reliable given the potential for the SCADA system to directly contribute to load curtailment. this paper presents an analysis of SCADA system reliability in terms of its e...
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Electric utility SCADA systems must be highly reliable given the potential for the SCADA system to directly contribute to load curtailment. this paper presents an analysis of SCADA system reliability in terms of its expected aggregate contribution to load curtailment on the power system. Expressing this aggregate in system minutes and applying an appropriate damage cost function then provides an annual cost measure of SCADA system reliability worth. A composite generation and transmission system reliability evaluation technique is used to perform the numerical analysis of the joint SCADA and power system model. this performs a Monte-Carlo simulation and includes an optimal power flow for enumerating grid load curtailment states and analysis of SCADA system component connectivity to determine availability of SCADA control. the application of this analysis is illustrated in a comparison of two alternative SCADA architectures. Trans Power has adopted a subtransmission SCADA architecture which utilises terminals operating off its national SCADA system. these terminals have replaced separate systems located in each area. the objective of the evaluation being to quantify the increased exposure to financial losses due to joint load curtailment.
In the literature, the co-ordination of static VAr compensators (SVC) and power system stabilizers (PSS) using generator speed deviation or modal speeds such as stabilizing signals is shown to damp power system oscill...
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In the literature, the co-ordination of static VAr compensators (SVC) and power system stabilizers (PSS) using generator speed deviation or modal speeds such as stabilizing signals is shown to damp power system oscillations. though such schemes are able to damp the SSR modes for small disturbances, they are unable to damp transient SSR due to large disturbances. In this report, an improvement in the control aspect of the SVC at the midpoint of the power transmission line is suggested. this scheme attempts different auxiliary signals that include line current, computed internal frequency and bus angle deviations. A system of configuration similar to IEEE First Bench Mark model is considered, eigenvalue analysis has been carried out and results indicate that bus angle deviation signal as an auxiliary control signal for SVC was able to damp most of the modes leaving some of them still oscillatory. the main feature of the proposed work is to use a combination of the deviation in speed and electrical power output of the generator as input signals to PSS which operates simultaneously along with SVC. Such a simultaneous PSS and SVC scheme is found to improve power system damping under large disturbances, i.e. the growth of system oscillations is arrested. Control simulations are carried out on PSCAD. the efficacy of controllers to damp SSR under steady state and faulted conditions, where one of the torsional modes is excited, is presented and discussed.
the paper is concerned withthe application of quadratic optimization for motion control to feedback control of robotic systems using neural networks. Explicit solutions to the Hamilton-Jacobi-Bellman (H-J-B) equation...
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the paper is concerned withthe application of quadratic optimization for motion control to feedback control of robotic systems using neural networks. Explicit solutions to the Hamilton-Jacobi-Bellman (H-J-B) equation for optimal control of robotic systems are found by solving an algebraic Riccati equation. It is shown how neural networks can cope with nonlinearities through optimization with no preliminary off-line learning phase required. the adaptive learning algorithm is derived from Lyapunov stability analysis, so that bothsystem tracking stability and error convergence can be guaranteed in the closed-loop system. the filtered tracking error or critic gain and the Lyapunov function for the nonlinear analysis are derived from the user input in terms of a specified quadratic performance index. Simulation results on a two-link robot manipulator show the satisfactory performance of the proposed control schemes even in the presence of large modeling uncertainties and external disturbances.
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