Day-Ahead Optimal Scheduling of Integrated Energy System Based on Type-II Fuzzy Interval Chance-Constrained Programming

Xinyu Sun, Hao Wu, Siqi Guo and Lingwei Zheng ()
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Xinyu Sun: School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
Hao Wu: School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
Siqi Guo: School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
Lingwei Zheng: School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China

Energies, 2022, vol. 15, issue 18, 1-17

Abstract: Renewable energy sources (RES) generation has huge environmental and social benefits, as a clean energy source with great potential. However, the difference in the uncertainty characteristics of RES and electric–thermal loads poses a significant challenge to the optimal schedule of an integrated energy system (IES). Therefore, for the different characteristics of the multiple uncertainties of IES, this paper proposes a type-II fuzzy interval chance-constrained programming (T2FICCP)-based optimization model to solve the above problem. In this model, type-II fuzzy sets are used to describe the uncertainty of RES in an IES, and interval numbers are used to describe the load uncertainty, thus constructing a T2FICCP-based IES day-ahead economic scheduling model. The model was resolved with a hybrid algorithm based on interval linear programming and T2FICCP. The simulations are conducted for a total of 20 randomly selected days to obtain the advance operation plan of each unit and the operation cost of the system. The research results show that the T2FICCP optimization model has less dependence on RES output power and load forecasting error, so can effectively improve the economy of IES, while ensuring the safe and stable operation of the system.

Keywords: integrated energy system; type-II fuzzy sets; type-II fuzzy interval chance-constrained programming; hybrid algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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