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Distributionally Robust Co-Optimization of Energy and Reserve Dispatch of Integrated Electricity and Heat System

Authors :
Skalyga, Mikhail
Wu, Quiwei
Skalyga, Mikhail
Wu, Quiwei
Source :
Skalyga , M & Wu , Q 2020 , Distributionally Robust Co-Optimization of Energy and Reserve Dispatch of Integrated Electricity and Heat System . in Proceedings of 2020 International Conference on Probabilistic Methods Applied to Power Systems . IEEE , pp. 1-6 , 2020 International Conference on Probabilistic Methods Applied to Power Systems , Liege , Belgium , 18/08/2020 .
Publication Year :
2020

Abstract

The combined operation of integrated energy systems is increasingly becoming a crucial topic for renewable energy dominated power systems operation. Flexibility from the district heating system could be used to deal with the uncertainty of renewable energy sources. We formulate a distributionally robust optimization problem for co-optimizing energy and reserve dispatch of the integrated electricity and heating system with a moment-based ambiguity set. The reserve allocation has been modeled through the participation vectors of the controllable generation units. The total reserve capacity has been defined implicitly and is a function of the uncertainty. The proposed model has been transformed into a second-order cone programming (SOCP) optimization problem by applying convex relaxation and linearization of the district heating network equations. Case studies on the integrated six-bus and seven-node system to demonstrate the efficacy of the proposed model.

Details

Database :
OAIster
Journal :
Skalyga , M & Wu , Q 2020 , Distributionally Robust Co-Optimization of Energy and Reserve Dispatch of Integrated Electricity and Heat System . in Proceedings of 2020 International Conference on Probabilistic Methods Applied to Power Systems . IEEE , pp. 1-6 , 2020 International Conference on Probabilistic Methods Applied to Power Systems , Liege , Belgium , 18/08/2020 .
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1233158240
Document Type :
Electronic Resource