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Very Short-Term PV Power Forecasting Model Based on Kalman Filter Algorithm And BP Neutral Network |
Wang Yu1, Su Shi2, Yan Yuting2 |
1. Graduate workstation of Yunnan Power Grid Co, Kunming 650217; 2. Electric Power Research Institute ,Yunnan Electric Power Research Institute (Group) Co., Ltd, Kunming 650217 |
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Abstract With the expanding of the capacity of photovoltaic power plants, uncertainty and volatility of the photovoltaic power generation will generate a negative impact on the safe operation of Power Grid. Therefore, To improve the PV power power forecasting accuracy and use the forecasting results will provide certain ancillary basis for Power Grid to operate and control PV power plants, which helps a lot for the grid stable operation. However, to be the most important impact factor of PV generation, irradiance is greatly influenced by cloud cover and changes randomly, especially when cloudy, changes rapidly and severely, which brings difficulty to the very short-term PV power forecasting. For this reason, this paper proposes a very short-term PV power forecasting model based on kalman filter algorithm and back propagation (BP) neutral network. This model applies extraterrestrial radiation and kalman filter algorithm to estimate irradiance, uses continuous prediction method to predict temperature and humidity, then input these three to BP neutral network to forecast PV power for the next 15 minutes. At last, apply actual historical data of three forecast days to test and verify effectiveness and feasibility of the proposed model.
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Received: 30 July 2014
Published: 23 January 2014
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Cite this article: |
Wang Yu, Su Shi, Yan Yuting. Very Short-Term PV Power Forecasting Model Based on Kalman Filter Algorithm And BP Neutral Network[J]. Electrical Engineering, 2014, 15(01): 42-46.
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URL: |
http://dqjs.cesmedia.cn/EN/Y2014/V15/I01/42
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