Optimal scheduling of park-level integrated energy system considering multiple uncertainties: A comprehensive risk strategy-information gap decision theory method

Multiple uncertainties in the park-level integrated energy system (PIES) can affect the optimal operation of system. Information gap decision theory (IGDT) is a commonly used method of dealing with uncertainty by developing risky strategies to avoid risks or seek risky returns. However, there is no unified method or process for the selection of risk strategies and the setting of related parameters, leading to a certain blindness in the application of IGDT method. A comprehensive risk strategy (CRS)- IGDT approach is proposed for scheduling of PIES considering uncertainties of heat load, photovoltaic output and electric load. Risk averse strategy (RAS) and Risk seek strategy (RSS) scheduling models are constructed. Then an optimized solution method based on adaptive steps ratio (ASR) is proposed to solve the above two models. The CRS and comprehensive risk cost function are proposed from a risk equalization perspective. The target deviation coefficient and steps ratio in the IGDT model are automatically optimized with the objective of minimizing the comprehensive risk cost. Combining the two cases, the average cost reduction is 6.6 % compared to Risk-neutral (RN), 11 % compared to RAS-IGDT, and 4.1 % compared to RSS-IGDT. Moreover, the average costs of CRS-IGDT are lower compared to stochastic programming and robust optimization methods. The experiments verify the generalization and superiority of the proposed method in coping with different information gap situations caused by uncertainty. CRS-IGDT provides new research ideas for dealing with uncertainty problems in PIES and other fields.