Uncertainty Modeling Methods in Integrated Energy Systems Planning: A Review

Abstract

Integrated energy system (IES) is considered as an effective system to integrate high penetration of intermittent renewable generation and achieve China’s national goal of reaching peak carbon emission by 2030 and carbon neutrality by 2060. As a result, there have been significant advancements over the recent years in IES modeling, planning, and operation, especially the treatment of uncertainty factors. This paper reviews the development of IES planning approaches focusing on modeling of uncertainty factors. Firstly, coordinated IES planning frameworks, processes and techniques are surveyed and categorized including their application scenarios, advantages and disadvantages, they are then compared with traditional grid planning. Secondly, the modeling of uncertainty factors was systematically reviewed and summarized. IES planning methods under uncertainty are further divided into a number of categories, such as probability optimization, stochastic optimization, robust optimization, possibility and mixed probability-possibility optimization. The uncertainty modeling methodologies are summarized and compared, including applications of uncertainty models in different situations. Finally, discussions on development trends, challenges and research directions in uncertainty modeling for IES planning are presented and recommendations are made.