In this article, a method for short-term forecasting of photovoltaic (PV) generation was proposed. The proposed method belongs to the group of physical methods and is based on numerical weather forecasts. The generation forecast was determined using the PV source model in the OpenDSS software. The results of calculations were compared with the results of measurements from the operating PV micro-installations.
PL
W artykule zaproponowana została metoda krótkoterminowego prognozowania generacji źródła fotowoltaicznego (PV). Metoda ta należy do grupy tzw. metod fizycznych i bazuje na numerycznych prognozach pogody. Do wyznaczenia prognozy generacji zastosowano model źródła fotowoltaicznego wchodzący w skład pakietu OpenDSS. Wyniki prognoz zostały porównane w wynikami pomiarów pochodzących z działających mikroinstalacji PV.
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The examination and integration of numerical forecast products are essential for using and developing numerical forecasts and hydrological forecasts. In this paper, the control forecast products from 2010 to 2014 of four model data (China Meteorological Administration (CMA), the National Centers for Environmental Prediction (NCEP), the European Centre for Medium-Range Weather Forecasts (ECMWF), and the United Kingdom Meteorological Office (UKMO)) from The Interactive Grand Global Ensemble (TIGGE) data center were evaluated comprehensively. On this basis, a study of runoff forecasting based on multi-model (multiple regression (MR), random forest (RF), and convolutional neural network-gradient boosting decision tree (CNN-GBDT)) precipitation integration is carried out. The results show that the CMA model performs the worst, while the other models have their advantages and disadvantages in different evaluation indexes. Compared with the single-index optimal model, CMA model had a higher root-mean-square error (RMSE) of 18.4%, and a lower determination coefficient (R2 ) of 14.7%, respectively. The integration of multiple numerical forecast information is better than that of a single model, and CNN-GBDT method is superior to the multiple regression method and random forest method in improving the precision of rainfall forecast. Compared with the original model, the RMSE decreases by 13.1 ~27.9%, PO decreases to 0.538 at heavy rainfall, and the R2 increases by 4~15.2%, but the degree of improvement decreases gradually with the increase in rainfall order. The method of multi-model ensemble rainfall forecasting based on a machine learning model is feasible and can improve the accuracy of short-term rainfall forecasting. The runoff forecast based on multi-model precipitation integration has been improved, and NSE increases from 0.88 to 0.935, but there is still great uncertainty about food peaks during the food season.
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In this paper a series of estimations has been performed in order to establish the actual cost-effectiveness of small wind turbines (SWTs). Different design solutions have been evaluated and based on their power curves and installation costs, using accurate wind data, a rate of investment return (ROI) period has been calculated for each one of them. The chosen turbines are: a classic three bladed horizontal axis wind turbine (HAWT), an advanced diffuser augmented HAWT and a Darrieus type vertical axis wind turbine (VAWT). The conclusions drawn from this study entertain the idea that from the economical point of view, a price reduction of SWT systems is more important, than aerodynamic complexity and efficiency.
W referacie przestawiono wprowadzenie do problematyki opracowywania numerycznych modeli prognoz pogody. Omówione zostały zagadnienia tworzenia modeli globalnych, regionalnych i mezoskalowych wraz z procedurą tzw. „zagnieżdżania modeli”. Przedstawiono charakterystykę mezoskalowego modelu UMPL dla obszaru Polski wraz z zasadami konstrukcji siatki obliczeniowej modelu oraz wyborem odwzorowań kartograficznych dla map zawierających horyzontalne rozkłady parametrów meteorologicznych. Oryginalnym wynikiem przeprowadzonych badań jest uzyskiwanie pionowych przekrojów atmosfery wzdłuż dowolnej trasy. Otrzymywane produkty wykorzystywane są do osłony meteorologicznej kraju, a w szczególności do zabezpieczenia działań lotnictwa.
EN
The paper presents a concept of application of non-standard atmospheric parameters charts, determined on the basis of the UMPL (Unified Model for Poland Area) mesoscale model data, to synoptic analysis. Effective weather forecasts for aviation, including additional information about vertical profiles of meteorological elements, require objective forecast of the atmospheric state based on the results of numerical models and remotely sensed data. The procedure can be applied to points of geographical coordinates corresponding e.g. to a planned route of an aircraft.
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