Abstract：The forecast of photovoltaic output is important to the grid-connection of the photovoltaic power generation system. Most of the current method of forecasting PV output can only obtain a single prediction results, lacking of the analysis of uncertainty factors. Taking into account that solar radiation and temperature are the two most important factors, a model is presented based on the uncertainty theory in the paper. After analyzing the fuzziness of the cloud cover and the birandomness of cloud cover index, the expectations and critical values of the cloud cover index are calculated corresponding to forecasted cloud cover by using the birandom theory. By correcting the radiation values got from the cloudless weather REST model with the cloud cover index, the forecast solar radiation can be got, and ultimately the PV output under different cloud cover andthe prediction interval under different confidence levels can be got. The model selects data from BMS PV plant in the U.S. to verify its validity. Prediction results show that the model can provide richer information andhas good practicability.
赵书强,王明雨,胡永强,刘晨亮. 基于不确定理论的光伏出力预测研究[J]. 电工技术学报, 2015, 30(16): 213-220.
Zhao Shuqiang,Wang Mingyu,Hu Yongqiang,Liu Chenliang. Research on the Prediction of PV Output Based on Uncertainty Theory. Transactions of China Electrotechnical Society, 2015, 30(16): 213-220.
[1] 王飞, 余世杰, 苏建徽, 等. 太阳能光伏并网发电系统的研究[J]. 电工技术学报, 2005, 20(5): 72-74. Wang Fei, Yu Shijie, Su Jianhui, et al. Research on photovoltaic grid-connected power system[J]. Transac- tions of China Electrotechnical Society, 2005, 20(5): 72-74. [2] 蒋亚娟. 光伏电池建模及其在光伏发电预测中的应用[D]. 武汉: 华中科技大学, 2011. [3] GablerH. Grid-connected photovoltaics[J]. Solar Energy, 2001, 70(6): 455-456. [4] 后尚, 田瑞, 闫素英. 呼和浩特地区太阳辐射模型分析[J]. 可再生能源, 2008, 26(2): 79-82. Hou Shang, Tian Rui, Yan Suying. Research and analysis on the solar radiation model of Huhehaote[J]. Renewable Energy Resources, 2008, 26(2): 79-82. [5] 邱国全, 夏艳君, 杨鸿毅. 晴天太阳辐射模型的优化计算[J]. 太阳能学报, 2001, 22(4): 456-460. QiuGuoquan, Xia Yanjun, Yang Hongyi. An optimized clear-day solar radiation model[J]. Acta Energiae Solaris Sinica, 2001, 22(4): 456-460. [6] Shah Alam. Prediction of direct and global solar irradiance using broadband models: validation of REST model[J]. Renewable Energy, 2006, 31: 1253-1263. [7] 李小芳, 陈青云. 用云遮系数法计算日光温室内太阳辐射[J]. 农业工程学报, 2004, 20(3): 212-216. Li Xiaofang, Chen Qingyun. Calculation of the solar radiation inside the sunlight greenhouse using the cloud cover coefficient method[J]. Transactions of The Chinese Society of Agricultural Engineering, 2004, 20(3): 212-216. [8] 栗然, 李广敏. 基于支持向量机回归的光伏发电出力预测[J]. 中国电力, 2008, 41(2): 74-78. Li Ran, Li Guangmin. Photovoltaic power generation output forecasting based on support vector machine regression technique[J]. Electric Power, 2008, 41(2): 74-78. [9] 傅美平, 马红伟, 毛建容. 基于相似日和最小二乘支持向量机的光伏发电短期预测[J]. 电力系统保护与控制, 2012, 40(16): 65-69. Fu Meiping, Ma Hongwei, Mao Jianrong. Short-term photovoltaic power forecasting based on similar days and least square support vector machine[J]. Power System Protection and Control, 2012, 40(16): 65-69. [10] 陈昌松, 段善旭, 殷进军. 基于神经网络的光伏阵列发电预测模型的研究[J]. 电工技术学报, 2009, 24(9): 153-158. Chen Changsong, Duan Shanxu, Yin Jinjun. Design of photovoltaic array power forecasting model based on neutral network[J]. Transactions of China Electrotech- nical Society, 2009, 24(9): 153-158. [11] 丁明, 王磊, 毕锐. 基于改进BP神经网络的光伏发电系统输出功率短期预测模型[J]. 电力系统保护与控制, 2012, 40(11): 93-99. Ding Ming, Wang Lei, Bi Rui. A short-term prediction model to forecast output power of photovoltaic system based on improved BP neutral network[J]. Power System Protection and Control, 2012, 40(11): 93-99. [12] 张艳霞, 赵杰. 基于反馈型神经网络的光伏系统发电功率预测[J]. 电力系统保护与控制, 2011, 39(15): 96-101. Zhang Yanxia, Zhao Jie. Application of recurrent neutral networks to generated power forecasting for photovoltaic system [J]. Power System Protection and Control, 2011, 39(15): 96-101. [13] 陈昌松, 段善旭, 蔡涛, 等. 基于模糊识别的光伏发电短期预测系统[J]. 电工技术学报, 2011, 26(7): 83-89. Chen Changsong, Duan Shanxu, Cai Tao, et al. Short- term photovoltaic generation forecasting system based on fuzzy recognition[J]. Transactions of China Elec- trotechnical Society, 2011, 26(7): 83-89. [14] 邰能灵, 侯志俭. 小波模糊神经网络在电力系统短期负荷预测中的应用[J]. 中国电机工程学报, 2004, 24(1): 24-29. Tai Nengling, Hou Zhijian. New short-term load forecas- ting principle with the wavelet transform fuzzy neural network for the power systems[J]. Proceedings of the CSEE, 2004, 24(1): 24-29. [15] 彭锦, 刘宝锭. 不确定理论及其公理化体系[J]. 黄冈师范学院学报, 2004, 24(3): 1-9. Peng Jin, Liu Baoding. Uncertainty theory and its axiomatic foundations[J]. Huanggang Nornal University, 2004, 24(3): 1-9. [16] 刘宝锭, 彭锦. 不确定理论教程[M]. 北京: 清华大学出版社, 2005. [17] 林媛. 太阳辐射强度模型的建立及验证[J]. 安徽建筑工业学院学报, 2007, 15(5): 44-46. Lin Yuan. The model of the solar radiation energy’s establishment and verification[J]. Journal of Anhui Institute of Architecture & Industry(Natural Science), 2007, 15(5): 44-46. [18] 申彦波, 赵宗慈, 石广玉. 地面太阳辐射的变化、影响因子及其可能的气候效应最新研究进展[J]. 地球科学进展, 2008, 23(9): 915-923. ShenYanbo, Zhao Zongci, Shi Guangyu. The progress in variation of surface solar radiation, factors and probable climatic effects[J]. Advances in Earth Science, 2008, 23(9): 915-923. [19] 张植明, 田景峰. 基于双重随机样本的统计学习理论的理论基础[J]. 计算机工程, 2008, 44(17): 33-36. Zhang Zhiming, Tian Jingfeng. Theoretical foundations of statistical learning theory of birandom samples[J]. Computer and Applications, 2008, 44(17): 33-36. [20] 廖志凌, 阮新波. 任意光强和温度下的硅太阳电池非线性工程简化数学模型[J]. 太阳能学报, 2009, 30(4): 430-435. Liao Zhiling, Ruan Xinbo. Non-linear engineering simplification model of silicon solar cells in arbitrary solar radiation and temperature[J]. Acta Energiae Solaris Sinica, 2009, 30(4): 430-435.
2015, Vol. 30 
