Short-term load forecasting in electrical power systems via trajectory tracking and error correcting approach

Rapid and accurate load forecasting is essential for renewable yet highly stochastic power (such as wind and solar power) to be massively utilized in practice. While there are many load forecasting methods reported in the literature, most of which, however, do not literally guarantee the convergence of forecasting error. This paper proposes a new error correcting approach for load forecasting in power systems by using trajectory tracking stability theory. In principle, the proposed method is not an autonomous but heuristic correcting approach to assess and improve the results of other existing models. This method is able to ensure the convergence of forecasting error in theory and is independent of system model, making it more feasible and cost-effective for forecasting performance improvement. Simulation experiments confirm the effectiveness of the proposed method for multiple existing models and forecasting horizons. © 2014 AIP Publishing LLC.