Jakub Jurasz

Investigating Theoretical PV Energy Generation Patterns with Their Relation to the Power Load Curve in Poland

Polish energy sector is (almost from its origin) dominated by fossil fuel feed power. This situation results from an abundance of relatively cheap coal (hard and lignite). Brown coal due to its nature is the cheapest energy source in Poland. However, hard coal which fuels 60% of polish power plants is picking up on prices and is susceptible to the coal imported from neighboring countries. Forced by the European Union (EU) regulations, Poland is struggling at achieving its goal of reaching 15% of energy consumption from renewable energy sources (RES) by 2020. Over the year 2015, RES covered 11.3% of gross energy consumption but this generation was dominated by solid biomass (over 80%). The aim of this paper was to answer the following research questions: What is the relation of irradiation values to the power load on a yearly and daily basis? and how should photovoltaics (PV) be integrated in the polish power system? Conducted analysis allowed us to state that there exists a negative correlation between power demand and irradiation values on a yearly basis, but this is likely to change in the future. Secondly, on average, daily values of irradiation tend to follow power load curve over the first hours of the day.

Day ahead electric power load forecasting by WT-ANN

This paper presents a method for forecasting energy demand based on WT-ANN (Wavelet Transform - Artificial Neural Network). Model has been developed and assessed for system data for the period 2002-2014. As input variables following have been considered: five levels of signal decomposition (t-1, t-2), values of time series (t-1, t-2) and qualitative variables denoting day of the week. Streszczenie. W artykule przedstawiono metode prognozowania zapotrzebowania na moc elektryczną w oparciu o model hybyrdowy WT-ANN (Wavelet Transform - Artificial Neural Network). Budowe oraz ocene jakoś prognoz modelu przeprowadzono dla danych systemowych za okres 2002-2014. Jako dane wejściowe uwzgledniono: piec poziomow dekompozycji sygnalu, wartości szeregu czasowego (t-1, t-2) oraz zmienne jakościowe określające dzien tygodnia. (Prognozowania obciązenia sieci elektroenergetycznej na kolejny dzien w oparciu o model WT-ANN)

A strategy for the photovoltaic-powered pumped storage hydroelectricity

Pumped storage hydroelectricity is the most natural and almost the only bulk energy storage technology available today. Due to the variability of energy demand, and recently also of the supply side of the energy market, there is a need to compensate these differences. In market reality this is usually done on the so-called balancing market where energy prices are significantly higher than on the power exchange market. In this paper we introduce a mathematical model for simulating the operation of photovoltaic-powered pumped storage hydroelectricity along with an optimization model and a procedure for operation on the balancing market. A simulation was performed based on data covering the year 2015 with an hourly time step. The results from the proposed approach were juxtaposed with an optimal solution generated from the optimization model.

Application of artificial neural networks (ANN) in Lake Drwęckie water level modelling

Abstract This paper presents an attempt to model water-level fluctuations in a lake based on artificial neural networks. The subject of research was the water level in Lake Drwęckie over the period 1980-2012. For modelling purposes, meteorological data from the weather station in Olsztyn were used. As a result of the research conducted, the model M_Meteo_Lag_3 was identified as the most accurate. This artificial neural network model has seven input neurons, four neurons in the hidden layer and one neuron in the output layer. As explanatory variables meteorological parameters (minimal, maximal and mean temperature, and humidity) and values of dependent variables from three earlier months were implemented. The paper claims that artificial neural networks performed well in terms of modelling the analysed phenomenon. In most cases (55%) the modelled value differed from the real value by an average of 7.25 cm. Only in two cases did a meaningful error occur, of 33 and 38 cm.

Site selection for wind and solar parks based on resources temporal and spatial complementarity – mathematical modelling approach

The aim of this paper was the assessment of spatial and temporal complementarity of wind and solar resources based on selected locations in Poland. More specifically, we asked the following questions: a) does the spatial distribution of photovoltaic systems and wind farms own the property of smoothing the energy generation curve? b) is it possible as a result of renewable energy sources distribution over several locations to decrease instances of outliers in terms of energy production? c) to what extent depending on time step exists complementarity of sun and wind energy?. Conducted calculations were based on daily measurements of wind speed and insolation for the period 1984-2004 which were acquired from Institute of Meteorology and Water Management (IMGW) and www.soda-is.com. Obtained results are encouraging since the positive impact of spatial distribution on smoothing the energy generation curve was observed. From the power system point of view an expedient correlation between available wind and solar radiation in yearly time scale exists in analyzed locations. Streszczenie. Celem przeprowadzonych badań było zbadanie czasowej oraz przestrzennej komplementarności energii promieniowania słonecznego oraz wiatru w wybranych lokalizacjach na terenie Polski. W pracy podjęto się odpowiedzi na następujące pytania: a) czy dystrybucja przestrzenna instalacji fotowoltaicznych oraz parków wiatrowych prowadzi do wygładzenia krzywej uzysku energii elektrycznej? b) czy jest możliwym by na skutek rozmieszczenia źródeł energii na kilka lokalizacji zminimalizować występowanie skrajnych wartości uzyskiwanego wolumenu energii c) w zależności od kroku czasowego, jak kształtuje się komplementarność zasobów wiatru oraz energii promieniowania słonecznego. Przeprowadzone analizy operały się na szeregach czasowych średniej dobowej prędkości wiatru oraz sumie nasłonecznienia, które obejmowały lata 1984-2004 i zostały pozyskane z Instytutu Meteorologii i Gospodarki Wodnej – Państwowy Instytut Badawczy oraz platformy www.soda-is.com. Uzyskane wyniki są zachęcające, ponieważ wykazano istnienie pozytywnego wpływu dystrybucji przestrzennej na wygładzenie krzywej uzysku energii. Co więcej zaobserwowano istnienie silnej ujemnej korelacji pomiędzy zasobami energii wiatru i promieniowania słonecznego w ujęciu rocznym. (Wybór lokalizacji pod elektrownie wiatrowe i fotowoltaiczne w oparciu o czasową i przestrzenną komplementarność zasobów – podejście: modelowanie matematyczne).

Forecasting surface water level fluctuations of lake Serwy (Northeastern Poland) by artificial neural networks and multiple linear regression

The aim of this study is to assess the possibility of forecasting water level fluctuations in a relatively small (<100 km2), post-glacial lake located in a temperate climate zone by means of artifi...