Accurate energy forecasting is essential to achieve greater efficiency and reliability in power system operation and security, energy pricing problems, and scheduling and planning of energy supply systems, among other areas. During the past few decades, many energy forecasting models have been proposed, including traditional statistical models and artificial intelligent models. However, most of these models often possess theoretical drawbacks which limit their forecasting performance.

Recently, due to the development of advanced intelligent computing technologies, many novel technologies hybridised or combined with the energy forecasting and economic planning models mentioned previously have received much attention. It is important to explore the development of the modeling methodology by applying these advanced intelligent technologies.

The aim of this Special Issue is to collate original research articles with a focus on the applications of advanced intelligent technologies in economical modelling and energy forecasting. Review articles discussing the current state of the art are also welcomed.

Potential topics include but are not limited to the following:

• Statistical forecasting models
• Artificial intelligent models
• Hybrid (combined) models
• Meta-heuristic algorithms
• Intelligent computing mechanisms (chaotic mapping, quantum computing, cloud mapping, seasonal mechanisms)
• Renewable energy
• Planning economics
• Robust optimization
• Stochastic programming