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This paper addresses the problem of predicting a wind farm's power generation when no or few statistical data is available. The study is based on a time-series wind speed model and on a simple dynamic model of a DFIG wind turbine including cut-off and cut-in behaviours. The wind turbine is modeled as a stochastic hybrid system with three operation modes. Numerical results, obtained using Monte-Carlo...
It is recognized today that short-term (up to 2-3 days ahead) probabilistic forecasts of wind power provide forecast users with a paramount information on the uncertainty of expected wind generation. When considering different areas covering a region, they are produced independently, and thus neglect the interdependence structure of prediction errors, induced by movement of meteorological fronts,...
This paper reports new results in adopting entropy concepts to the training of mappers such as neural networks to perform wind power prediction as a function of wind characteristics (mainly speed and direction) in wind parks connected to a power grid. Renyi's Entropy is combined with a Parzen Windows estimation of the error pdf to form the basis of three criteria (MEE, MCC and MEEF) under which neural...
More and more wind power is being integrated into power grids in recent years. However, due to its intermittent characteristic, it is usually difficult to determine the appropriate penetration level to ensure a specified reliability requirement. For this purpose, the proper calculation of wind power capacity credit is of particular importance which is useful in both operations and planning stages...
Wind is being recognized as an encouraging and cost effective generation source both in large grid connected systems and small isolated applications. The actual benefits obtained from utilizing wind energy for electric power generation can be investigated using reliability and economic evaluation techniques. The focus of these techniques is usually directed to the areas of reliability and the investment/operation...
Better modelling and forecasting of very short-term power fluctuations at large offshore wind farms may significantly enhance control and management strategies of their power output. The paper introduces a new methodology for modelling and forecasting such very short-term fluctuations. The proposed methodology is based on a Markov-switching autoregressive model with time-varying coefficients. An advantage...
Wind energy on a power system alters the unit commitment and dispatch problem, as it adds a stochastic element due to the uncertainty of wind power forecasts. By explicitly taking into account the stochastic nature of wind power, it is expected that better schedules should be produced, thereby reducing costs on the system. This paper compares a stochastically optimised unit commitment and dispatch...
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