Techno-economic Feasibility Analysis of a Hybrid Energy System Under Different Load Forecasting Errors

The chapter delves into the techno-economic feasibility analysis of hybrid energy systems (HESs) under different load forecasting errors, a critical aspect of modern power system optimization. It begins by discussing the shift from traditional fossil energy to renewable energy sources and the increasing importance of HESs in this transition. The study focuses on the impact of load forecasting errors on the capacity optimization and performance evaluation of HESs, which are crucial for ensuring the balance between supply and demand. The authors employ a time series forecasting method based on Long Short-Term Memory (LSTM) networks to predict short-term loads and use the region contraction algorithm for system optimization. The results demonstrate that even with forecasting errors, the optimized system can achieve significant cost savings and improved operational performance. The chapter also highlights the importance of accurately simulating load demand profiles to optimize HES capacity and dispatch schedules effectively. Overall, the work provides valuable insights into the challenges and potential solutions for optimizing HESs under real-world conditions, making it a must-read for professionals in the field.