Adaptive Robust Dispatch of Integrated Energy System Considering Uncertainties of Electricity and Outdoor Temperature

• Published in: IEEE transactions on industrial informatics Vol. 16; no. 7; pp. 4691 - 4702
• Main Authors: Lu, Shuai, Gu, Wei, Zhou, Suyang, Yao, Shuai, Pan, Guangsheng
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.07.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive robust dispatch; Adaptive systems; Buildings; District heating; district heating network; Dynamic characteristics; Energy consumption; integrated energy system (IES); Integrated energy systems; Optimization; Parameter uncertainty; Pipelines; Resistance heating; Robustness; Temperature; Thermal comfort; Turbines; uncertainties; Uncertainty
• ISSN: 1551-3203; 1941-0050
• DOI: 10.1109/TII.2019.2957026

The integrated energy system (IES) has bright prospects in engineering applications for its excellent performance in energy efficiency and renewable energy consumption. In the IES, the thermal comfort is affected by the heating power, buildings parameters, and outdoor temperatures simultaneously. Therefore, the uncertainty of the outdoor temperature will bring some adverse effects on thermal comfort, which need to be considered in the dispatch decision of the IES. In this article, we propose a day-ahead adaptive robust dispatch model (ARDM) for the IES to make a dispatch plan under the uncertainties of the net electrical-load and outdoor temperature, with the aim of guaranteeing the safe operation of IES and the thermal comfort of end-users. The thermal dynamic characteristics of the district heating network and buildings are utilized to provide operational flexibility and improve economic performance. To decrease the conservatism of dispatch results, the multi-interval uncertainty set is introduced to model the uncertainties. The ARDM model is a two-stage robust optimization with a linear recourse problem, and the column-and-constraint generation method is used to solve it. Two cases of different scale are studied to verify the effectiveness and advantages of the proposed method.