Journal ArticleDOI
Forecasting Power Output of Photovoltaic Systems Based on Weather Classification and Support Vector Machines
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TLDR
In this paper, a one-day-ahead PV power output forecasting model for a single station is derived based on the weather forecasting data, actual historical power output data, and the principle of SVM.Abstract:
Due to the growing demand on renewable energy, photovoltaic (PV) generation systems have increased considerably in recent years. However, the power output of PV systems is affected by different weather conditions. Accurate forecasting of PV power output is important for system reliability and promoting large-scale PV deployment. This paper proposes algorithms to forecast power output of PV systems based upon weather classification and support vector machines (SVM). In the process, the weather conditions are divided into four types which are clear sky, cloudy day, foggy day, and rainy day. In this paper, a one-day-ahead PV power output forecasting model for a single station is derived based on the weather forecasting data, actual historical power output data, and the principle of SVM. After applying it into a PV station in China (the capability is 20 kW), results show the proposed forecasting model for grid-connected PV systems is effective and promising.read more
Citations
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Journal ArticleDOI
Forecasting of photovoltaic power generation and model optimization: A review
Utpal Kumar Das,Kok Soon Tey,Mohammadmehdi Seyedmahmoudian,Saad Mekhilef,Moh Yamani Idna Idris,Willem Van Deventer,Ben Horan,Alex Stojcevski +7 more
TL;DR: In this paper, a comprehensive and systematic review of the direct forecasting of PV power generation is presented, where the importance of the correlation of the input-output data and the preprocessing of model input data are discussed.
Journal ArticleDOI
Solar photovoltaic generation forecasting methods: A review
TL;DR: In this article, an extensive review on recent advancements in the field of solar photovoltaic power forecasting is presented, which aims to analyze and compare various methods of solar PV power forecasting in terms of characteristics and performance.
Journal ArticleDOI
Modeling, planning and optimal energy management of combined cooling, heating and power microgrid: A review
TL;DR: In this article, the authors present an overall review of the modeling, planning and energy management of a combined cooling, heating and power (CCHP) microgrid with distributed cogeneration units and renewable energy sources.
Journal ArticleDOI
A review and evaluation of the state-of-the-art in PV solar power forecasting:Techniques and optimization
TL;DR: In this paper, the authors reviewed and evaluated contemporary forecasting techniques for photovoltaics into power grids, and concluded that ensembles of artificial neural networks are best for forecasting short-term PV power forecast and online sequential extreme learning machine superb for adaptive networks; while Bootstrap technique optimum for estimating uncertainty.
Journal ArticleDOI
A Weather-Based Hybrid Method for 1-Day Ahead Hourly Forecasting of PV Power Output
TL;DR: A weather-based hybrid method for 1-day ahead hourly forecasting of PV power output is presented and achieves better prediction accuracy than the simple SVR and traditional ANN methods.
References
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Proceedings Article
Support Vector Regression Machines
TL;DR: This work compares support vector regression (SVR) with a committee regression technique (bagging) based on regression trees and ridge regression done in feature space and expects that SVR will have advantages in high dimensionality space because SVR optimization does not depend on the dimensionality of the input space.
Journal ArticleDOI
A 24-h forecast of solar irradiance using artificial neural network: Application for performance prediction of a grid-connected PV plant at Trieste, Italy
TL;DR: In this paper, a multilayer perceptron (MLP) model was proposed to forecast the solar irradiance on a base of 24h using the present values of the mean daily solar irradiances and air temperature.
Proceedings ArticleDOI
Support vector machine for regression and applications to financial forecasting
TL;DR: The main purpose of the paper is to compare the support vector machine (SVM) developed by Cortes and Vapnik (1995) with other techniques such as backpropagation and radial basis function (RBF) networks for financial forecasting applications.
Journal ArticleDOI
Short-term forecasting of solar radiation: a statistical approach using satellite data
TL;DR: In this paper, the authors use satellite images as a data source for short-term forecasting of solar irradiance, which is an important issue for many fields of solar energy applications.
Journal ArticleDOI
Solar energy development in China—A review
TL;DR: In this paper, the authors discuss the distribution zone and current developmental situation of solar energy in China, and some application practice is described, such as solar energy greenhouse, solar energy hearth, solar water heater, solar lighting system, solar power pump, distributed generation (DG), grid-connect photovoltaic generation (GPG) and wind-solar hybrid system.