光伏发电功率预测预报系统升级方案设计及关键技术实现
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摘要
"光伏发电功率预测预报系统V2.0"开发完成于2012年初,由于国家能源行业标准《光伏发电功率预测系统功能规范》(2014)即将颁布,完善系统功能,提高系统适用性,对系统升级尤其必要。从系统框架完善、预报方法改进、网络技术应用以及功能模块优化等4个方面对"光伏发电功率预测预报系统V2.0"进行了升级。升级内容主要包括:新增集合预报法以实现多种预报方法的集成优化,新增B/S架构方式并通过Silverlight 4.0技术实现预报产品的网络发布,新增电站地理信息地图显示从而增强系统的展示性,加强入库数据的规范化管理及对系统进行发电单元划分。升级后的系统已推广应用于全国多家光伏电站,将有助于电网对光伏发电的合理有效调度及光伏电站发电效率的提高。
The "Solar Power Generation Forecasting System V2.0" was developed in early 2012. As the national energy industry standardthe "Functional Specification for Photovoltaic Power Prediction System "(2014) is to be issued soon, it's necessary to upgrade this system to further perfect its function and improve its suitability. The upgrade mainly consists the following respects. Firstly, the B/S technical architecture is added to achieve the network publishing of forecasting products through Silverlight 4.0. Secondly, the combined forecast method is included in the upgrade to integrate various forecasting methods as to improve the forecast accuracy. Thirdly, the Google Earth will be incorporated to show the geographic information of plant which can enhance the display performance of the system. Finally, the upgrade strengthens the standardized management of data and divides the system by power generation units. The upgraded system has been applied to several PV power plants and it will help to effectively schedule the photovoltaic power generation and improve the power generation efficiency.
The "Solar Power Generation Forecasting System V2.0" was developed in early 2012. As the national energy industry standardthe "Functional Specification for Photovoltaic Power Prediction System "(2014) is to be issued soon, it's necessary to upgrade this system to further perfect its function and improve its suitability. The upgrade mainly consists the following respects. Firstly, the B/S technical architecture is added to achieve the network publishing of forecasting products through Silverlight 4.0. Secondly, the combined forecast method is included in the upgrade to integrate various forecasting methods as to improve the forecast accuracy. Thirdly, the Google Earth will be incorporated to show the geographic information of plant which can enhance the display performance of the system. Finally, the upgrade strengthens the standardized management of data and divides the system by power generation units. The upgraded system has been applied to several PV power plants and it will help to effectively schedule the photovoltaic power generation and improve the power generation efficiency.
引文
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[2]张伯泉,杨宜民.风力和太阳能光伏发电现状及发展趋势[J].中国电力,2006,39(6):65-69.ZHANG Bo-quan,YANG Yi-min.Status and trend of wind/photovoltaic power development[J].Electric Power,2006,39(6):65-69.
[3]张岚,张艳霞,郭嫦敏,等.基于神经网络的光伏系统发电功率预测[J].中国电力,2010,43(9):75-78.ZHANG Lan,ZHANG Yan-xia,GUO Chang-min,et al.Photovoltaic system power forecasting based on neutral networks[J].Electric Power,2010,43(9):75-78.
[4]LORENZ E,HURKA J,HEINEMANN D,et al.Irradiance forecasting for the power prediction of grid-connected photovoltaic systems[J].IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2009,2(1):2-10.
[5]丁宇宇,丁杰,周海,等.基于全天空成像仪的光伏电站水平面总辐射预报[J].中国电机工程学报,2014,34(1):50-56.DING Yu-yu,DING Jie,ZHOU Hai,et al.Forecasting of global horizontal irradiance in photovoltaic power stations based on the total sky imager[J].Proceedings of the CSEE,2014,34(1):50-56.
[6]代倩,段善旭,蔡涛,等.基于天气类型聚类识别的光伏系统短期无辐照度发电预测模型研究[J].中国电机工程学报,2011,31(34):28-35.DAI Qian,DUAN Shan-xu,CAI Tao,et al.Short-term PV generation system forecasting model without irradiation based on weather type clustering[J].Proceedings of the CSEE,2011,31(34):28-35.
[7]陈正洪,李芬,成驰,等.太阳能光伏发电预报技术原理及其业务系统[M].北京:气象出版社,2011.
[8]BATES J M,GRANGER C W J.The combination of forecasts.Operational Research Quarterly,1969,20(4):451-468.
[9]MARINO L,ADOLFO L T,MIGUEL A.Perez-Toledano,et al.Providing RIA user interfaces with accessibility properties[J].Journal of Symbolic Computation,2011,46(2):207-217.
[10]陈强,姜立新,帅向华,等.Google Earth在地震应急中的应用[J].地震,2008,28(1):121-128.CHEN Qiang,JIANG Li-xin,SHUAI Xiang-hua,et al.The application of google earth in earthquake emergency[J]. Earthquake,2008,28(1):121-128.
[11]何明琼,成驰,陈正洪,等.太阳能光伏发电预报效果评价[J].水电能源科学,2011,29(12):196-199.HE Ming-qiong,CHENG Chi,CHEN Zheng-hong,et al. Prediction effect assessment of solar PV power generation[J].Water Resources and Power,2011,29(12):196-199.
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