Regional forecasts and smoothing effect of photovoltaic power generation in Japan: An approach with principal component analysis |
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| Affiliation: | 1. National Institute of Advanced Industrial Science and Technology, AIST, Research Center of Photovoltaic Technologies, System and Application Team, AIST Tsukuba Central 2, 305-8568 Umezono 1-1-1, Tsukuba City, Ibaraki, Japan;2. University of Tokyo, Institute of Industrial Science, Collaborative Research for Energy Engineering, 153-8505 Komaba 4-6-1, Meguro-ku, Tokyo, Japan;1. College of Automation, Harbin Engineering University, Harbin 150001, China;2. Department of Electrical Engineering, Chung Yuan Christian University, Chung Li District 320, Taoyuan City, Taiwan;1. National Renewable Energy Laboratory, Golden, CO 80401, USA;2. IBM TJ Watson Research Center, Yorktown Heights, NY 10598, USA;3. Northeastern University, Boston, MA 02115, USA;4. University of Arizona, Tucson, AZ 85721, USA;5. Argonne National Laboratory, Lemont, IL 60439, USA;6. U.S. Department of Energy, Washington, D.C. 20585, USA;7. ISO New England, Holyoke, MA 01040, USA;8. Green Mountain Power, Colchester, VT 05446, USA;1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, Hebei Province, China;2. Department of Electrical Engineering, North China Electric Power University, Baoding 071003, Hebei Province, China;3. Department of Electrical Engineering, Tsinghua University, Beijing 100084, China;4. Electric Power Research Institute of Yunnan Power Grid Company, Kunming 650217, Yunnan Province, China;5. Huaneng Tendering Co., Ltd., Shijiazhuang 050071, Hebei Province, China;1. School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Ave., 639798, Singapore;2. Energy Research Institute @ NTU (ERI@N), #06-04 CleanTech One, 1 CleanTech Loop, 637141, Singapore |
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| Abstract: | Regional forecasts of power generated by photovoltaic systems have an important role helping power utilities to manage grids with a high level of penetration of such systems. The objective of this study is to propose a method to obtain one-day ahead hourly regional forecasts of photovoltaic power when regional information is available. The method is based on the use of principal component analysis, support vector regression and weather forecast data. One-day ahead regional forecasts of photovoltaic power were done for 4 of the main regions of Japan for 1 year, 2009, using hourly power generation data of 453 photovoltaic systems. The performance of the method was characterized comparing the results it yielded with the ones provides by a persistence approach and by an approach that do not employ the principal component analysis. Moreover, the expected smoothing effect on the error achieved when the regional forecasts are based on forecasts for each photovoltaic system is presented, constituting an additional reference to evaluate the proposed method. The results show that the method performed well; its regional forecasts had a normalized annual root mean square error of 0.07 kWh/kWrated in the worst case, and the persistence approach was outperformed by at least 51% regarding the same error. The use of principal component proved to be a simple and particularly effective approach, decreasing the bias of the forecasts in all regions, and causing a reduction of the normalized root mean square error from 20.2% to 57.8% depending on the region. The proposed method also yielded results within the same level of forecasts which benefitted from the smoothing effect; the former presented a maximum variation of 10.2% of the normalized root mean square error of the latter in the worst case. |
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| Keywords: | Photovoltaic systems One-day-ahead regional forecasts Smoothing effect Principal component analysis Support vector regression |
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