Application of BP Neural Network to Short-Term-Ahead Generating Power Forecasting for PV System

Hao Jiang; Li Hong

doi:10.4028/www.scientific.net/AMR.608-609.128

Paper Titles

Direct Thermoelectric Microgeneration Using Residual Heat of Photovoltaic System
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Photovoltaic Power Generation Transient Modeling and Identifiability Analysis
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The Review of Photovoltaic Power Generation Technology
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Practical Model Educed and Simulation of Photovoltaic Power System
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Application of BP Neural Network to Short-Term-Ahead Generating Power Forecasting for PV System
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Study on the Power Generation Data of High-Power BIPV Grid-Connected PV Power Station
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The Analysis of Chinese Photovoltaic Industry with SWOT Model and AHP Method
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Design and Calculation of Cooling System to Eliminate Non-Uniform Heat Transfer on Concentration PV System (CPV)
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Global Utilization of Solar Energy and Development of Solar Cell Materials
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 608-609Application of BP Neural Network to...

Application of BP Neural Network to Short-Term-Ahead Generating Power Forecasting for PV System

Abstract:

A short-term generating capacity forecast model of a PV power station was proposed. The forecasting days were classified by the season and weather, and various neural network models were adopted to analyze the system. The radiation of PV power station was added to the model as an input parameter to improve the forecasting precision. The forecasting precisions based on the historical data of the actual PV power station in different seasons and weather were compared and analyzed. The results show that the proposed method can improve the forecasting precision of generating capacity.

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Periodical:

Advanced Materials Research (Volumes 608-609)

Pages:

128-131

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.608-609.128

Citation:

Cite this paper

Online since:

December 2012

Authors:

Hao Jiang*, Li Hong

Keywords:

BP Neural Network (BPNN), Forecasting, Pv System, Radiation

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* - Corresponding Author

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