In this paper, a novel fault detection scheme is presented for networked controlsystems with random delays and noises. Since the random noises and delays existed in networked controlsystem are probably non- Gaussian...
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This paper presents a controlsystem design strategy for multi-input and multi-output (MIMO) networked controlsystems with random delays. The performance index of the controlsystems is constructed by entropies of tr...
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In view of the current high rate of abandoned wind, photovoltaic power generation costs and wind-fire bundling mode, in the active power control of the wind of low load operation of motor fluctuations in the fire team...
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A novel control algorithm is applied to control superheated steam temperature in power plants. Since the disturbances existed in practical processes are probably non-Gaussian, the performance index is constructed by m...
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Circulating fluidized bed boiler(CFBB) is a distributed parameter, nonlinear, time-varying and multivariate coupling system. Considering these, the core identity of Rough Set and the theory of self-organizing neural f...
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Market clearing price (MCP) forecasting techniques is very important for the development of the electricity market. A three-layered neural network is used to predict electricity prices. MCP is seen as a multi-input si...
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Market clearing price (MCP) forecasting techniques is very important for the development of the electricity market. A three-layered neural network is used to predict electricity prices. MCP is seen as a multi-input single-output system and the historical electricity price and load data is utilized in an electricity market. The neural network is based on Minimum Entropy Error (MEE) cost function and Batch-Sequential mode. Compared with other models, the proposed approach improves the prediction accuracy and speed.
Next-day electricity prices forecasting is essential to consumers and producers. Due to the stochastic characteristics of the electricity price time series, a novel model of electricity price forecasting is presented ...
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Next-day electricity prices forecasting is essential to consumers and producers. Due to the stochastic characteristics of the electricity price time series, a novel model of electricity price forecasting is presented based on the Hidden Markov Model (HMM). The factors impacting the electricity price forecasting are discussed. The proposed approach is utilized in an electricity market, the results show the effectiveness.
In an open electricity market, generation companies (GENCO) have to optimally bid to gain more profits with incomplete information of other competing generators. In this structure, market participants must develop the...
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In an open electricity market, generation companies (GENCO) have to optimally bid to gain more profits with incomplete information of other competing generators. In this structure, market participants must develop their bids in order to maximize their profits. Building optimal bidding strategies for GENCO could need to evaluate some market parameters such as forecasting market-clearing price (MCP), non-convex production cost function and forecasting load. A new framework to build bidding strategies for GENCO in an electricity market is presented in this paper. A normal probability distribution function (PDF) is used to describe the bidding behaviors of other competing generators. Bidding strategy of a generator for each trading period in a day-ahead market is solved by a new adaptive particle swarm optimization APSO). APSO can dynamically follow the frequently changing market demand and supply in each trading interval. A numerical example serves to illustrate the essential features of the approach and the results are compared with the solutions by other PSO algorithms.
A sliding mode control scheme is presented in αβframe for grid-side PWM rectifiers in wind power generation systems. The positive and negative sequence voltages are needed to design the controller, nevertheless, the...
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ISBN:
(纸本)9781424427994
A sliding mode control scheme is presented in αβframe for grid-side PWM rectifiers in wind power generation systems. The positive and negative sequence voltages are needed to design the controller, nevertheless, the positive and negative sequence currents are not needed. This scheme is compared with the dual current control scheme in the rotating frame d-q. The simulation results show that sliding mode control scheme can realize unit power factor operation when the amplitude is unbalanced.
It is difficult to deal with the variable speed constant frequency (VSCF) wind turbine systems due to the stochastic characteristics and the pneumatic effects of wind. In this paper, a new pitch controller based on ge...
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ISBN:
(纸本)9781424450459;9781424450466
It is difficult to deal with the variable speed constant frequency (VSCF) wind turbine systems due to the stochastic characteristics and the pneumatic effects of wind. In this paper, a new pitch controller based on generalized predictive control theory is designed to improve the power-output quality of variable speed constant frequency wind turbines. An application to a 300MW wind turbines is given, and simulation results show that the proposed method is effective in wind speed interference suppression and constant out power.
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