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Online Short-term Solar Power Forecasting

TL;DR: The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 h, where the results indicate that for forecasts up to 2 h ahead the most important input is the available observations ofSolar power, while for longer horizons NWPs are theMost important input.
Abstract: This paper describes a new approach to online forecasting of power production from PV systems. The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 h. The data used is 15-min observations of solar power from 21 PV systems located on rooftops in a small village in Denmark. The suggested method is a two-stage method where first a statistical normalization of the solar power is obtained using a clear sky model. The clear sky model is found using statistical smoothing techniques. Then forecasts of the normalized solar power are calculated using adaptive linear time series models. Both autoregressive (AR) and AR with exogenous input (ARX) models are evaluated, where the latter takes numerical weather predictions (NWPs) as input. The results indicate that for forecasts up to 2 h ahead the most important input is the available observations of solar power, while for longer horizons NWPs are the most important input. A root mean square error improvement of around 35% is achieved by the ARX model compared to a proposed reference model.

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Citations
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Journal ArticleDOI
TL;DR: An overview of forecasting methods of solar irradiation using machine learning approaches is given and it will be shown that other methods begin to be used in this context of prediction.

1,095 citations

Journal ArticleDOI
TL;DR: This paper appears with the aim of compiling a large part of the knowledge about solar power forecasting, focusing on the latest advancements and future trends, and represents the most up-to-date compilation of solarPower forecasting studies.

829 citations

Journal ArticleDOI
TL;DR: In this article, the authors review the theory behind these forecasting methodologies, and a number of successful applications of solar forecasting methods for both the solar resource and the power output of solar plants at the utility scale level.

813 citations


Cites background from "Online Short-term Solar Power Forec..."

  • ...2009 [270] Hourly PV power Out to 36 h AR, ARX, RX (regressive...

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  • ...(2009) [270] tested several stochastic models to predict hourly values of PV power for horizons out to 36 h....

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Journal ArticleDOI
TL;DR: This paper introduces the GEFCom2014, a probabilistic energy forecasting competition with four tracks on load, price, wind and solar forecasting, which attracted 581 participants from 61 countries and concludes with 12 predictions for the next decade of energy forecasting.

706 citations

Journal ArticleDOI
TL;DR: In this article, the authors present an in-depth review of the current methods used to forecast solar irradiance in order to facilitate selection of the appropriate forecast method according to needs.
Abstract: Integration of solar energy into the electricity network is becoming essential because of its continually increasing growth in usage. An efficient use of the fluctuating energy output of photovoltaic (PV) systems requires reliable forecast information. In fact, this integration can offer a better quality of service if the solar irradiance variation can be predicted with great accuracy. This paper presents an in-depth review of the current methods used to forecast solar irradiance in order to facilitate selection of the appropriate forecast method according to needs. The study starts with a presentation of statistical approaches and techniques based on cloud images. Next numerical weather prediction or NWP models are detailed before discussing hybrid models. Finally, we give indications for future solar irradiance forecasting approaches dedicated to the management of small-scale insular grids.

599 citations


Cites methods or result from "Online Short-term Solar Power Forec..."

  • ...In Bacher and al.[7], the authors investigate the use of a simpler AR model to directly predict PV power in comparison with other models....

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  • ...This approach is followed, for example, in Bacher and al.[7], and Kemmoku and al....

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References
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Journal ArticleDOI
TL;DR: A ordered sequence of events or observations having a time component is called as a time series, and some good examples are daily opening and closing stock prices, daily humidity, temperature, pressure, annual gross domestic product of a country and so on.
Abstract: Preface1Difference Equations12Lag Operators253Stationary ARMA Processes434Forecasting725Maximum Likelihood Estimation1176Spectral Analysis1527Asymptotic Distribution Theory1808Linear Regression Models2009Linear Systems of Simultaneous Equations23310Covariance-Stationary Vector Processes25711Vector Autoregressions29112Bayesian Analysis35113The Kalman Filter37214Generalized Method of Moments40915Models of Nonstationary Time Series43516Processes with Deterministic Time Trends45417Univariate Processes with Unit Roots47518Unit Roots in Multivariate Time Series54419Cointegration57120Full-Information Maximum Likelihood Analysis of Cointegrated Systems63021Time Series Models of Heteroskedasticity65722Modeling Time Series with Changes in Regime677A Mathematical Review704B Statistical Tables751C Answers to Selected Exercises769D Greek Letters and Mathematical Symbols Used in the Text786Author Index789Subject Index792

10,011 citations

Book ChapterDOI
TL;DR: This paper provides a concise overview of time series analysis in the time and frequency domains with lots of references for further reading.
Abstract: Any series of observations ordered along a single dimension, such as time, may be thought of as a time series. The emphasis in time series analysis is on studying the dependence among observations at different points in time. What distinguishes time series analysis from general multivariate analysis is precisely the temporal order imposed on the observations. Many economic variables, such as GNP and its components, price indices, sales, and stock returns are observed over time. In addition to being interested in the contemporaneous relationships among such variables, we are often concerned with relationships between their current and past values, that is, relationships over time.

9,919 citations


"Online Short-term Solar Power Forec..." refers background or methods in this paper

  • ...The methods used for evaluating the prediction models are inspired by Madsen et al. (2005) where a framework for evaluation of wind power forecasting is suggested....

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  • ...The motivation behind the proposed normalization of the solar power with a clear sky model is that the normalized solar power (the ratio of solar power to clear sky solar power) is more stationary than the solar power, so that classical time series models assuming stationarity (Madsen, 2007) can be used for predicting the normalized values....

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  • ...The solution at time t leads to ĥt 1⁄4 R 1 t ht; ð47Þ see Madsen (2007), where...

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  • ...Adaptive linear time series models (Madsen, 2007) are applied to predict future values of the normalized solar power st....

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  • ...Adaptive linear time series models (Madsen, 2007) are applied to predict future values of the normalized solar power τt....

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Journal ArticleDOI
TL;DR: An overview of forecasting methods of solar irradiation using machine learning approaches is given and it will be shown that other methods begin to be used in this context of prediction.

1,095 citations

Journal ArticleDOI
TL;DR: This paper appears with the aim of compiling a large part of the knowledge about solar power forecasting, focusing on the latest advancements and future trends, and represents the most up-to-date compilation of solarPower forecasting studies.

829 citations

Journal ArticleDOI
TL;DR: In this article, the authors review the theory behind these forecasting methodologies, and a number of successful applications of solar forecasting methods for both the solar resource and the power output of solar plants at the utility scale level.

813 citations