Adaptive robust energy and reserve co-optimization of integrated electricity and heating system considering wind uncertainty

Jin Tan, Qiuwei Wu, Qinran Hu, Wei Wei and Feng Liu

Applied Energy, 2020, vol. 260, issue C, No S0306261919319178

Abstract: The uncertainty and variability of wind power pose significant challenges to secure and reliable operation of power systems. Coordinated operation of the electric power system and district heating system, which can provide sufficient reserve capacity and flexibility, is an effective way to cope with the uncertainty. This paper proposes an adaptive robust energy and reserve co-optimization for the integrated electricity and heat system to minimize the total system cost under the worst-case realization of wind uncertainty considering spatial correlations of wind uncertainties. The available reserve capacity and flexibility provided by the district heating system is fully used by exploiting the regulation capabilities of combined heat and power units and electrical boilers, as well as utilizing the building thermal inertia. To reduce the conservatism of the robust solution, the spatial correlation of wind uncertainties is considered in the uncertainty set. The column-and-constraint generation algorithm is adopted to solve the adaptive robust model iteratively by reformulating the second stage with its Karush-Kuhn-Tucker conditions. Simulation results demonstrate that the economic efficiency is improved by utilizing the reserve flexibility from the district heating system and considering wind farm spatial correlations. Compared with the conventional single-stage optimized model, the feasibility of the two-stage robust solution is always guaranteed by considering the real-time operation constraints of the electric power system and district heating system.

Keywords: Adaptive robust optimization; Energy and reserve co-optimization; Integrated electricity and heating system; Wind power uncertainty (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (34)

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DOI: 10.1016/j.apenergy.2019.114230

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