As wind and photovoltaic energy become more prevalent,the optimization of power systems is becoming increasingly crucial.The current state of research in renewable generation and power forecasting technology,such as w...As wind and photovoltaic energy become more prevalent,the optimization of power systems is becoming increasingly crucial.The current state of research in renewable generation and power forecasting technology,such as wind and photovoltaic power(PV),is described in this paper,with a focus on the ensemble sequential LSTMs approach with optimized hidden-layers topology for short-term multivariable wind power forecasting.The methods for forecasting wind power and PV production.The physical model,statistical learningmethod,andmachine learning approaches based on historical data are all evaluated for the forecasting of wind power and PV production.Moreover,the experiments demonstrated that cloud map identification has a significant impact on PV generation.With a focus on the impact of photovoltaic and wind power generation systems on power grid operation and its causes,this paper summarizes the classification of wind power and PV generation systems,as well as the benefits and drawbacks of PV systems and wind power forecasting methods based on various typologies and analysis methods.展开更多
论文在传统一阶隐马尔可夫模型的基础上,针对隐马尔可夫模型结构信息挖掘不全面的问题,提出了一种双层隐马尔可夫模型。双层隐马尔可夫模型在使用Baum-Welch算法的过程中将词性序列视为观测序列,通过Baum-Welch算法提取更多信息并最大...论文在传统一阶隐马尔可夫模型的基础上,针对隐马尔可夫模型结构信息挖掘不全面的问题,提出了一种双层隐马尔可夫模型。双层隐马尔可夫模型在使用Baum-Welch算法的过程中将词性序列视为观测序列,通过Baum-Welch算法提取更多信息并最大化词性序列概率从而更加贴合实际情况,同时对Viterbi算法做了相应的改动。模型在Penn Treebank语料库和Groningen Meaning Bank语料库上进行10折交叉验证,并与传统一阶、二阶隐马尔可夫模型进行对比。结果表明双层隐马尔可夫模型相较传统一阶、二阶隐马尔可夫模型词性标注正确率更高。展开更多
基金This project is supported by the National Natural Science Foundation of China(NSFC)(Nos.61806087,61902158).
文摘As wind and photovoltaic energy become more prevalent,the optimization of power systems is becoming increasingly crucial.The current state of research in renewable generation and power forecasting technology,such as wind and photovoltaic power(PV),is described in this paper,with a focus on the ensemble sequential LSTMs approach with optimized hidden-layers topology for short-term multivariable wind power forecasting.The methods for forecasting wind power and PV production.The physical model,statistical learningmethod,andmachine learning approaches based on historical data are all evaluated for the forecasting of wind power and PV production.Moreover,the experiments demonstrated that cloud map identification has a significant impact on PV generation.With a focus on the impact of photovoltaic and wind power generation systems on power grid operation and its causes,this paper summarizes the classification of wind power and PV generation systems,as well as the benefits and drawbacks of PV systems and wind power forecasting methods based on various typologies and analysis methods.
文摘论文在传统一阶隐马尔可夫模型的基础上,针对隐马尔可夫模型结构信息挖掘不全面的问题,提出了一种双层隐马尔可夫模型。双层隐马尔可夫模型在使用Baum-Welch算法的过程中将词性序列视为观测序列,通过Baum-Welch算法提取更多信息并最大化词性序列概率从而更加贴合实际情况,同时对Viterbi算法做了相应的改动。模型在Penn Treebank语料库和Groningen Meaning Bank语料库上进行10折交叉验证,并与传统一阶、二阶隐马尔可夫模型进行对比。结果表明双层隐马尔可夫模型相较传统一阶、二阶隐马尔可夫模型词性标注正确率更高。
