Short term electricity load forecasting using hybrid prophet-LSTM model optimized by BPNN

Electrical load forecasting plays a vital role in the operation and planning of power plants for the utility companies and policy makers to design stable and reliable energy infrastructure. Load forecasting is categorized in long-term, mid-term and short-term. Among them, short term load forecasting that monitors weekly, daily, hourly and even sub-hourly operations is gaining a lot of attention which saves time and cost while satisfying consumers’ needs without interruption. Different models such as conventional, Artificial Intelligence (AI) and hybrid models have been developed to investigate short-term load forecasting. However, these models suffers various issues such as low speed convergence…

• NN
  National Natural Science Foundation of China

  Award: 51937005