An interactive optimization model for energy systems planning associated with clean‐energy development under uncertainty

In this study, an interactive fuzzy chance‐constrained resolution (IFCR) method is developed for supporting energy systems planning (ESP) under uncertainty. IFCR can not only tackle multiple uncertainties presented as fuzzy membership functions and probability distributions using an interactive resolution method, but also enable decision makers to seek optimal solutions between satisfaction degree of objective and feasibility of constraints. Then, an IFCR‐ESP model is formulated for energy systems of Bayingolin Mongol Autonomous Prefecture (abbreviated as Bazhou). Results provide decision makers with a complete view of the relationship between uncertain inputs and solutions. Policy‐based solutions concerning energy consumption, electricity generation, capacity expansion, pollutant emission, and system cost are analyzed, which can help decision makers to identify desired strategies for ESP. Results indicate that transitioning from the conventional energy system to a sustainable one is associated to policy support, resources availability, energy supply security, and capital investment; clean energy policy (e.g. shift from coal to gas) is an effective way to facilitate the local energy system development in a sustainable manner; the solutions under different feasibility degrees can help decision makers to conduct in‐depth analyses of tradeoffs between system cost and constraint‐violation risk in an interactive way. Copyright © 2016 John Wiley & Sons, Ltd. An IFCR‐ESP model is formulated for energy systems of the Bayingolin Mongol Autonomous Prefecture under uncertainty. Results provide decision makers with a complete view of the relationship between uncertain inputs and solutions. Policy‐based solutions reveal that policy support and financial incentive measures are important factors to accelerate the local energy system development in a sustainable manner.