Short Term Prediction of Photovoltaic Power Based on FCM and CG-DBN Combination

Affected by many factors, the photovoltaic output power is characterized by nonlinearity, volatility and instability. Therefore, short-term forecasting models are required to have multiple inputs, levels, and categories. In order to solve the above problems and improve the accuracy of predictions, t...

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Vydáno v:Journal of electrical engineering & technology Ročník 15; číslo 1; s. 333 - 341
Hlavní autoři: Li, ZhengMing, Bao, ShiQuan, Gao, ZhaoLiang
Médium: Journal Article
Jazyk:angličtina
Vydáno: Singapore Springer Singapore 01.01.2020
대한전기학회
Témata:
Electrical Engineering
Electrical Machines and Networks
Electronics and Microelectronics
Engineering
Instrumentation
Original Article
Power Electronics
전기공학
Combined forecasting model
Depth belief network
Similar day clustering
Photovoltaic short-term forecast
ISSN:1975-0102, 2093-7423
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Popis
Shrnutí:Affected by many factors, the photovoltaic output power is characterized by nonlinearity, volatility and instability. Therefore, short-term forecasting models are required to have multiple inputs, levels, and categories. In order to solve the above problems and improve the accuracy of predictions, this paper proposes a combined model prediction method based on similar-day clustering and the use of Conjugate Gradient (CG) to improve Deep Belief Network (DBN). The initial method uses fuzzy C-Means Clustering Algorithm (FCM) to perform similar-day clustering on the original data according to the degree of membership. The CG-DBN prediction model is then designed according to the category, with the model ultimately being used to perform the short-term prediction of the PV output power. The proposed scheme uses data from Zhejiang Longyou power station for experimental analysis and verification, and the results were compared with the back propagation neural networks model, Support Vector Machine (SVM) model, and traditional deep belief network. The model’s predicted results are compared. Finally, it is concluded that, in the short-term PV power load forecasting, the prediction performance of the FCM and CG-DBN combination forecast model is better than the above three models and has strong feasibility in short-term PV power forecasting.
ISSN:1975-0102
2093-7423
DOI:10.1007/s42835-019-00326-3