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Descrierea sistemului de prognoza – WPMS

Wind Power Energy este prima companie din Romania care incepând cu 1 ianuarie 2009 este capabila să ofere servicii de prognoză de producţie pentru parcurile eoliene. Serviciul este un produs Dispecerat WPE furnizat sub brand-ul WPE Power Forecast :

Astfel, clienţii  pot intra pe PZU – Piaţa pe Ziua Următoare, obţinând un preţ mult mai bun pentru energia produsă. Prin acest serviciu, WPE poate oferi o acurateţe de plus/minus 5%, procent mic in comparatie cu alte firme din lume ce presteaza acelasi tip de servicii.

Sistemul de prognoza al WPE este un sistem online 24/24 , sistem ce foloseşte baze de date neuronale ce învaţă singure să-şi corecteze erorile folosind atât datele de producţie a turbinelor cât şi datele de vânt şi datele de model, din zona amplasamentului parcului eolian.

Despre “Wind Power Management System – WPMS”

WPE’s wind power monitoring and prediction model, the „Wind Power Management System – WPMS“ includes a cluster of prediction modules, being optimised for different targets. Each module consists of a set of artificial neural networks (ANN). The input of the networks is predicted meteorological data like wind speed and direction, air pressure, temperature,etc. and observed wind farm power output from the near past. The output is the wind farm power output for a specific time period in the future. Most of the national weather services provide forecasts of meteorological data for several times a day and for a specific period.

ANN’s are trained with predicted meteorological parameters and measured power data from the past, in order to learn the relation between wind speed and wind farm power output. The actual relation between wind speed (and other meteorological parameters) and wind farm power output is dependent on a multitude of local influences and is therefore very complex, i.e. physically difficult to describe. A further advantage of ANNs over other approaches is the “learning” of relations and “conjecturing” of results, also in the case of incomplete or contradictory entry data.

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