In this, study, a type-2 fuzzy chance-constrained programming (TFCP) method is developed for supporting energy systems planning (ESP) under uncertainty. TFCP incorporates chance-constrained programming within a type-2 fuzzy programming framework to handle uncertainties (i.e. type-2 fuzzy sets and probabilistic distributions) in the objective and constraints, as well as to examine the reliability of satisfying (or risk of violating) system constraints. A TFCP-based energy system (TFCP-ES) model is then formulated for energy systems planning of Shanghai, where multi-energy resources, multi-processing technologies, multi-conversion technologies and multi-end users are considered. Solutions of energy supply, electricity generation, capacity expansion, and air-pollutant emission associated with different constraint-violation risks are obtained. Results reveal that (i) natural gas is one of the major energy-supply sources for the city in the future (increasing by 13.0%); (ii) the city's electricity-generation structure tends to the transition from coal-dominated into clean energy-dominated (e.g., natural gas, onshore wind, offshore wind, and photovoltaic power); (iii) the city's energy-supply security is enhanced by provoking the utilization of renewable energies (increasing by 1.0%). The results are helpful for managers to adjust the city's current energy structure, enhance the energy supply security, as well as make tradeoff between system cost and constraint-violation risk. (C) 2017 Elsevier Ltd. All rights reserved.