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Stochastic model predictive control operation strategy of integrated energy system based on temperature‐flowrate scheduling model considering detailed thermal characteristics
Author(s) -
Wei Shangshang,
Li Yiguo,
Sun Li,
Zhang Junli,
Shen Jiong,
Li Zuyi
Publication year - 2020
Publication title -
international journal of energy research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.808
H-Index - 95
eISSN - 1099-114X
pISSN - 0363-907X
DOI - 10.1002/er.6069
Subject(s) - scheduling (production processes) , thermal , volumetric flow rate , control theory (sociology) , temperature control , computer science , electricity , mathematical optimization , engineering , process engineering , control engineering , mechanics , thermodynamics , control (management) , mathematics , physics , artificial intelligence , electrical engineering
Summary A scheduling model is a prerequisite for an operation strategy of integrated energy system (IES). Existing scheduling models of IES, however, are typically based on heat‐transfer variables either completely or partially, which oversimplify detailed thermal characteristics. To this end, a novel scheduling model is proposed where all thermal processes are modeled by temperature and flowrate of working fluids. This improvement renders the capability to the scheduling model to incorporate different thermal processes. Furthermore, the nonlinear product terms of temperature and flowrate in the proposed model are linearized by the binary expansion method. Based on the linearized scheduling model, a stochastic model predictive control (SMPC) operation strategy is exploited to optimize the economic performance by energy forecast, scenario reduction, rolling optimization, and feedback correction. Afterwards, four operation modes considering different temperature changes of the devices, networks, and the environment are performed and compared. The results found that thermal characteristics will affect device operation results and the degree of influence varies. The network temperature changes have the broadest influence, followed by the device and the ambient temperature changes. Moreover, system operation costs are also affected by detailed thermal characteristics. The total cost, the gas cost, and the electricity cost under Mode 2 are almost the same to those of Mode 1. However, the first two costs are reduced by 3.4% and 5.3% under Mode 3, and are reduced by 2.7% and 4% under Mode 4, despite that the electricity cost increases by 0.2% under Mode 3 and remains almost the same under Mode 4. These indicate that reliability and economy of an IES are affected by thermal characteristics, and it is thus the necessity to consider detailed thermal characteristics in an operation. Moreover, the results demonstrate the capability of the generalized temperature‐flowrate based scheduling model and the effectiveness of the SMPC operation strategy.