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Application of rough sets theory in forecast of power generation for grid-connected photovoltaic system

机译:粗糙集理论在光伏并网发电量预测中的应用

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With photovoltaic technology development and application of the expansion of photovoltaic, the accuracy of power generation forecast will directly affect the grid load frequency, grid stability, system reliability, power quality, investment and the system operating efficiency. The short-term forecasting research of photovoltaic power generation will help to stabilize power system operation, to optimize grid dispatching and to provide effective protection for the distribution load management. The rough sets theory was first proposed to the forecast of photovoltaic power generation and given the forecast mathematical models in this paper. The redundant attribute was removed from the decision table with the attribute reduction algorithm of Pawlak attribute importance. The continuous attributes of PV systems is discrete by the improved greedy algorithm. Results comparison of actual operation data and the simulation of week, month, season and year shows that rough sets forecast models is more correct and accuracy.
机译:随着光伏技术的发展和光伏应用的扩展,发电量预测的准确性将直接影响电网的负荷频率,电网的稳定性,系统的可靠性,电能质量,投资和系统的运行效率。光伏发电的短期预测研究将有助于稳定电力系统的运行,优化电网调度,并为配电负荷管理提供有效的保护。粗糙集理论首先被提出来用于光伏发电的预测,并给出了预测数学模型。使用Pawlak属性重要性的属性减少算法从决策表中删除了冗余属性。光伏系统的连续属性通过改进的贪婪算法是离散的。实际运行数据的结果比较以及周,月,季和年的模拟表明,粗集预测模型更准确,更准确。

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