Two-Stage Distributionally Robust Optimization for Energy Hub Systems
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EN
Article de revue
Este ítem está publicado en
IEEE Transactions on Industrial Informatics. 2020-05, vol. 16, n° 5, p. 3460 - 3469
Resumen en inglés
Energy hub system (EHS) incorporating multiple energy carriers, storage and renewables can efficiently coordinate various energy resources to optimally satisfy energy demand. However, the intermittency of renewable generation ...Leer más >
Energy hub system (EHS) incorporating multiple energy carriers, storage and renewables can efficiently coordinate various energy resources to optimally satisfy energy demand. However, the intermittency of renewable generation poses great challenges on optimal EHS operation.This paper proposes an innovative distributionally robust optimization model to operate EHS with an energy storage system (ESS), considering the multimodal forecast errors of photovoltaic (PV) power. Both battery and heat storage are utilized to smooth PV output fluctuation and improve the energy efficiency of EHS. This paper proposes a novel multimodal ambiguity set to capture the stochastic characteristics of PV multimodality. A two-stage scheme is adopted, where i) the first stage optimizes EHS operation cost, and ii) the second stage implements real-time dispatch after the realization of PV output uncertainty. The aim is to overcome the conservatism of multimodal distribution uncertainties modelled by typical ambiguity sets and reduce the operation cost of EHS. The presented model is reformulated as a tractable semidefinite programming problem and solved by a constraint generation algorithm. Its performance is extensively compared with widely used normal and unimodal ambiguity sets. The results from this paper justify the effectiveness and performance of the proposed method compared to conventional models, which can help EHS operators to economically consume energy and use ESS wisely through the optimal coordination of multi-energy carriers.< Leer menos
Palabras clave en inglés
Constraint generation algorithm
distributionally robust optimization
energy hub system
multimodal ambiguity set
renewable energy
Centros de investigación