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作 者:秦政[1] 包德梅[1] 赖晓路[1] 岳以洋[1] 王媛媛[1]
机构地区:[1]国电南京自动化股份有限公司,江苏南京210003
出 处:《计算机技术与发展》2013年第7期73-76,共4页Computer Technology and Development
基 金:中国华电科技计划项目(CHDKJ 12-01-24)
摘 要:对风电场发电功率的准确预测,可以有效优化电网调度,使得电网经济运行,同时提高风电场在电力市场中的竞争能力。文中提出了基于先进统计方法的风电功率预测系统,以高精度数值气象预报为基础,搭建完备的数据库系统,利用各种通讯接口采集风电场监控数据。提出并实现了"自适应逻辑网络"(ALN),为风电场建立功率预测算法引擎,可以准确预报风电场未来72小时短期功率负荷,并能针对单台风机、风电场或风机集群进行预测和上报,为风电场管理提供重要辅助手段。现场运行测试验证了系统在风速预测以及针对不同型号风机风功率预测的可行性和有效性。The accurate forecasting for wind power of wind farms can effectively optimize grid loading scheduling to obtain an economical operation for Grid Company. Meanwhile the market competitiveness of wind farms can be enhanced through wind power forecasting. In this paper, an advanced statistics model based wind forecasting system is proposed. The proposed system collects highly accurate numeri- cal weather prediction data, acquires wind farm monitoring data through multiple communication interfaces and builds complete database management system. The Adaptive Logic Network (ALN) is proposed and realized to build the wind forecasting model. The forecasting algorithm engine is aimed to forecast and submit short term power output of 72 hours ahead for a single wind turbine, a wind farm or wind farm group. The field testing proves the feasibility and effectiveness of the proposed system for both wind speed forecasting and wind power forecasting of wind turbines with different power capacity.
关 键 词:风功率预测 自适应逻辑网络 预测算法引擎 短期预测
分 类 号:TP39[自动化与计算机技术—计算机应用技术]
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