Improving operational flexibility of integrated energy system with uncertain renewable generations considering thermal inertia of buildings

•A chance-constrained programming-based scheduling model is proposed for integrated energy systems.•A sequence operation theory-based solution approach is developed.•The effectiveness of the approach is verified via the modified IEEE 30-bus system.•The approach can improve system operational flexibi...

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Veröffentlicht in:Energy conversion and management Jg. 207; S. 112526
Hauptverfasser: Li, Yang, Wang, Chunling, Li, Guoqing, Wang, Jinlong, Zhao, Dongbo, Chen, Chen
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford Elsevier Ltd 01.03.2020
Elsevier Science Ltd
Elsevier
Schlagworte:
30 DIRECT ENERGY CONVERSION
Buildings
Cogeneration
Computer simulation
Constraints
energy
Energy consumption
Energy resources
Energy sources
Flexibility
heat
Heating
Heating load
Inertia
Integer programming
Integrated energy system
Integrated energy systems
Linear programming
Mixed integer
Operational flexibility
Photovoltaics
Renewable curtailment
Renewable energy
renewable energy sources
Renewable generation
Renewable resources
Scheduling
Specific heat
spinning
Thermal inertia
Thermal power
Thermal-electric decoupling
Turbines
uncertainty
Wind power
Wind turbines
winter
Integrated energy system
Thermal-electric decoupling
Renewable curtailment
Operational flexibility
Renewable generation
Thermal inertia
ISSN:0196-8904, 1879-2227
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Zusammenfassung:•A chance-constrained programming-based scheduling model is proposed for integrated energy systems.•A sequence operation theory-based solution approach is developed.•The effectiveness of the approach is verified via the modified IEEE 30-bus system.•The approach can improve system operational flexibility by leveraging building thermal inertia and auxiliary equipments. Insufficient flexibility in system operation caused by traditional “heat-set” operating modes of combined heat and power (CHP) units in winter heating periods is a key issue that limits renewable energy consumption. In order to reduce the curtailment of renewable energy resources through improving the operational flexibility, a novel optimal scheduling model based on chance-constrained programming (CCP), aiming at minimizing the lowest generation cost, is proposed for a small-scale integrated energy system (IES) with CHP units, thermal power units, renewable generations and representative auxiliary equipments. In this model, due to the uncertainties of renewable generations including wind turbines and photovoltaic units, the probabilistic spinning reserves are supplied in the form of chance-constrained; from the perspective of user experience, a heating load model is built with consideration of heat comfort and inertia in buildings. To solve the model, a solution approach based on sequence operation theory (SOT) is developed, where the original CCP-based scheduling model is tackled into a solvable mixed-integer linear programming (MILP) formulation by converting a chance constraint into its deterministic equivalence class, and thereby is solved via the CPLEX solver. The simulation results on the modified IEEE 30-bus system demonstrate that the presented method manages to improve operational flexibility of the IES with uncertain renewable generations by comprehensively leveraging thermal inertia of buildings and different kinds of auxiliary equipments, which provides a fundamental way for promoting renewable energy consumption.
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USDOE
National Natural Science Foundation of China (NSFC)
AC02-06CH11357; JJKH20200113KJ; 201608220144; 51677023
China Scholarship Council (CSC)
ISSN:0196-8904
1879-2227
DOI:10.1016/j.enconman.2020.112526