Daily solar radiation forecasting using historical data and examining three methods

Abstract

I IntroductionFilling up electronic demands using renewable energy is getting more interesting every day, not just only it is free to get, above of that because it is pollution free. Renewable energy sources as photovoltaic (PV), wind, bio-diesel generator are now utilized in integrated generation systems at sites that have a large potential of either solar, wind or both. At present, solar photovoltaic and wind systems have been promoted around the globe on a comparatively larger scale [1-6]. As it mentioned, these energies are free but doesn't mean that they are always available. For instants, solar photovoltaic energy system cannot be useful at night and also cannot be satisfied during cloudy days. It goes the same way for wind system, it cannot be efficient even during windy days, because amount of wind speed is required to get into that level, which makes the prediction harder for calculations. Even though if winds speed is satisfied doesn't mean that it will be constant even for an hour. Therefore, for saving energy to meet demands few of these system need to work together so they may cover each other up if it is possible for having a better reliability.Comparing to other efficient renewable energy system, solar is the most common cause, it is possible to use it daily, solar conversion, and renewable energy applications, particularly for the sizing of stand-alone photovoltaic (PV) systems [1]. Solar energy or radiation is not very easy to get as well, but comparing to others is more convenient, as it is known, in air there are a lot of particles which directly will effect on the solar radiation frequency that will effect on absorbing solar energy by PV's a good example would be clouds and haze. Complete sun radiation is the most essential alternative in forecasting of renewable energy systems, especially in designing PV power systems. Knowing a perfect sizing of solar system [2-4] (PV) is very important, by over-sizing the system, it doesn't mean that result will be better, because, by not considering prize and costs, by having a larger area, chances of having shaded area on PVs will increase which reduces efficiency of PVs performance quite a lot. In other hand, by having smaller size or in other word, under-sizing the system, reduces the power supply reliability [1]. That's why, accurate forecasting of radiation is one of the challenges for scientists, not just only to predict, for designing as well. For time being, there are many approaches for forecasting irradiance [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21]. It has grown from mathematical formula and combination of them up to analyzing satellite images by using artificial intelligence. Yet, results were surprising not as accurate as it was expected [7]. In this review paper, three most common used approaches for forecasting irradiation [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21] were examined, which are exponential smoothing, seasonal method and neural network. For all these three same historical database were used an...

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