This integrated approach aims to enhance the accuracy of short-term power load forecasting. The method was validated on load datasets from Singapore and Australia. The MAPE of this paper's model on the two datasets reached 0.42% and 1.79%, far less than other models, and the R2 ...
Short-term load forecasting (STLF) is crucial for intelligent energy and power scheduling. The time series of power load exhibits high volatility and complexity in its components (typically seasonality, trend, and residuals), which makes forecasting a challenge. To reduce the volatility of the powe...
Short term load forecasting model 翻译结果4复制译文编辑译文朗读译文返回顶部 Short-term electricity load forecast model 翻译结果5复制译文编辑译文朗读译文返回顶部 Short-term power load forecast model 相关内容 aHe's from the USA 他来自美国[translate] ...
Short-term load is random and variable with many influence factors that are difficult to establish function relationship between power load. In this paper, the advantages and disadvantages of three commonly used short-term power load forecasting methods are compared based on the analysis of load char...
Many uncertain factors to the planning and distribution of the power grid have been brought by connecting to the distributed power grid and increasing active loads. To obtain more accurate and comprehensive information of power load forecasting value, a short-term power load-interval multi-step forec...
which consists of the self-organized mapping, chaotic time series, intelligent optimization algorithm and long short-term memory (LSTM) is proposed to extend the load forecasting length, decrease artificial debugging, and improve the prediction precision for the short-term power load forecasting. Compar...
Short-term power load forecasting based on support vector machine and particle swarm optimization: Q Song,P Yang - SAGE PublicationsSage UK: London, England 被引量: 0发表: 2019年 Long term electric load forecasting based on particle swarm optimization This paper presents a new method for annual...
which consists of the self-organized mapping, chaotic time series, intelligent optimization algorithm and long short-term memory (LSTM) is proposed to extend the load forecasting length, decrease artificial debugging, and improve the prediction precision for the short-term power load forecasting. Compar...
During the operation of power system, short-term load forecasting is a basic component of energy management system, and also an important basis for the operation of power dispatching system. Accurate forecasting of short-term load is helpful for managers to put forward standard power generation plan...
forecasting of short-term power load. It means that the model combined with SVM and chaotic time series learning system have more advantage than other models. Keywords: Support vector machine, Chaotic time series, Lyapunov exponents, Parameter selection, Load forecasting Categories: F.2.1, H.1.1,...