如何提高风功率预测上报精度
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摘要
以某一个风电场为实例,将风电场1a的平均风速、预测发电量与实际发电量作为依据,结合风机的功率曲线,运用人工神经网络分析法,拟合出一个在不同风速条件下的发电量,对实际发电量与拟合发电量进行比较,并进行误差分析,得出一个接近实际发电量的值。最后将拟合发电量运用到云南电网考核系统中,计算出拟合发电量产生的经济价值。
Taking a wind farm as an example, the paper proposed an energy output under different wind velocity, made a comparison between the actual energy output and the proposed energy output, carried out error analysis and obtained an energy output close to the actual energy output using the artificial neutral network analysis method based on the average wind velocity of the wind farm la, on the predicted energy output and the actual energy output taking into consideration the power curves. The paper finally applied the proposed energy output to the assessment system of the Yunnan power grid and calculated the economic value resulted from the proposed energy output.
Taking a wind farm as an example, the paper proposed an energy output under different wind velocity, made a comparison between the actual energy output and the proposed energy output, carried out error analysis and obtained an energy output close to the actual energy output using the artificial neutral network analysis method based on the average wind velocity of the wind farm la, on the predicted energy output and the actual energy output taking into consideration the power curves. The paper finally applied the proposed energy output to the assessment system of the Yunnan power grid and calculated the economic value resulted from the proposed energy output.
引文
[1]王广.人工神经网络发展现状综述[J].中小企业管理与科技,2017(6):165-167.
[2]范高锋,王伟胜,刘纯,等.基于人工神经网络的风电功率预测[J].中国电机工程学报,2008,28(34):118-123.
[3]武小梅,白银明,文福拴.基于RBF神经元网络的风电功率短期预测[J].电力系统保护与控制,2011,39(15):80-83.
[4]王永翔,陈国初,张鑫.基于PF-RBF神经网络的短期风电功率预测[J].上海电机学院学报,2014(6):324-328.
[5]时庆华.基于卡尔曼滤波和神经网络的短期风电功率预测[D].东南大学,2010.
[6]杨剑.基于人工神经网络的短期风电功率预测研究[D].西安理工大学,2013.
[7]郭创新,王扬,沈勇,等.风电场短期风速的多变量局域预测法[J].中国电机工程学报,2012,32(1):24-31.
[8]崔闪,彭道刚,钱玉良.基于ACFOA优化RBF的短期风电功率预测[J].可再生能源,2017,35(1):80-85.
[9]向德军,王彬,郭文鑫,等.基于人工神经网络的电力系统精细化安全运行规则[J].电力系统保护与控制,2017(18):32-37.
[2]范高锋,王伟胜,刘纯,等.基于人工神经网络的风电功率预测[J].中国电机工程学报,2008,28(34):118-123.
[3]武小梅,白银明,文福拴.基于RBF神经元网络的风电功率短期预测[J].电力系统保护与控制,2011,39(15):80-83.
[4]王永翔,陈国初,张鑫.基于PF-RBF神经网络的短期风电功率预测[J].上海电机学院学报,2014(6):324-328.
[5]时庆华.基于卡尔曼滤波和神经网络的短期风电功率预测[D].东南大学,2010.
[6]杨剑.基于人工神经网络的短期风电功率预测研究[D].西安理工大学,2013.
[7]郭创新,王扬,沈勇,等.风电场短期风速的多变量局域预测法[J].中国电机工程学报,2012,32(1):24-31.
[8]崔闪,彭道刚,钱玉良.基于ACFOA优化RBF的短期风电功率预测[J].可再生能源,2017,35(1):80-85.
[9]向德军,王彬,郭文鑫,等.基于人工神经网络的电力系统精细化安全运行规则[J].电力系统保护与控制,2017(18):32-37.