Integrated Forecasting Method for Wind Energy Management: A Case Study in China

Abstract

Wind speed forecasting helps to increase the efficacy of wind farms and prompts the comparative superiority of wind energy in the global electricity system. Many wind speed forecasting theories have been widely applied to forecast wind speed, which is nonlinear, and unstable. Current forecasting strategies can be applied to various wind speed time series. However, some models neglect the prerequisite of data preprocessing and the objective of simultaneously optimizing accuracy and stability, which results in poor forecast. In this research, we developed a combined wind speed forecasting strategy that includes several components: data pretreatment, optimization, forecasting, and assessment. The developed system remedies some deficiencies in traditional single models and markedly enhances wind speed forecasting performance. To evaluate the performance of this combined strategy, 10-min wind speed sequences gathered from large wind farms in Shandong province in China were adopted as a case study. The simulation results show that the forecasting ability of our proposed combined strategy surpasses the other selected comparable models to some extent. Thus, the model can provide reliable support for wind power generation scheduling.

Comparison of singular spectrum analysis forecasting algorithms for student’s academic performance during COVID-19 outbreak

“…The reconstructed series is the new dataset derived from the original data, which is clear from noise. It is a crucial aspect in SSA to ensure that the forecasting results are precise and accurate [33]. The trend component in the time series data was used to observe the occurrence of the trend and pattern, as it was randomly-tabulated as per daily cases.…”

Inverter Efficiency Analysis Model Based on Solar Power Estimation Using Solar Radiation

“…where ε is an independent error term that follows a normal distribution whose mean is zero and standard deviation is σ. For regression analysis, the given data can be defined as the matrix of independent variables X and the vector of dependent variables Y; β values representing regression coefficients can be expressed as a vector as shown in Equation (2). p is the number of independent variables, and n is the number of data.…”

“…The adjusted R-squared is an estimate for the coefficient of determination of the population, which reflects the degree of freedom for correcting the tendency of the coefficient of determination of the sample data to become larger than that of the population. The adjusted R-squared R 2 adj is given by…”

“…Accurate forecast results and dispatch departments can help to easily and effectively coordinate programs. Wind farms can minimize the negative impact on the grid and maximize the use of wind power in the global electricity market [2].…”

Special Issue on “Energy, Economy and Environment for Industrial Production Processes”

“…Dong et al [7] develop a combined wind speed forecasting strategy that includes data pretreatment, optimization, forecasting and assessment, by considering the prerequisite of data preprocessing and the objective of simultaneously optimizing accuracy and stability. It achieves high accuracy in wind speed forecasting.…”