Rights statement: This is the author’s version of a work that was accepted for publication in Applied Energy.. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Applied Energy, 170, 2016 DOI: 10.1016/j.apenergy.2016.01.095
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Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Synergy of smart grids and hybrid distributed generation on the value of energy storage
AU - Crespo Del Granado, Pedro
AU - Pang, Zhan
AU - Wallace, Stein William
PY - 2016/5/15
Y1 - 2016/5/15
N2 - In smart grids, demand response and distributed energy systems aim to provide a higher degree of flexibility for load-shifting operations and the leverage to control intermittent wind supply. In this more dynamic energy system, deployment of energy storage at the site of consumption is envisioned to create synergies with the local distributed generation (DG) system. From a large end-user perspective, this paper contributes to the practical understanding of smart grids by modelling the impact of real-time pricing schemes (smart grids) on a hybrid DG system (mixed generation for heating and electricity loads) coupled with storage units. Specifically, we address: How does the portfolio of DG units affect the value of energy storage? and, what is the value of energy storage when assessing different designs of demand response for the end-user? To this end, we formulate a dynamic optimization model to represent a real-life urban community’s energy system composed of a co-generation unit, gas boilers, electrical heaters and a wind turbine. We discuss the techno-economic benefits of complementing this end-user’s energy system with storage units (thermal storage and battery devices). The paper analyses the storages policy strategies to simultaneously satisfy heat and electricity demand through the efficient use of DG units under demand response mechanisms. Results indicate that the storage units reduce energy costs by 7–10% in electricity and 3% in gas charges. In cases with a large DG capacity, the supply–demand mismatch increases, making storage more valuable.
AB - In smart grids, demand response and distributed energy systems aim to provide a higher degree of flexibility for load-shifting operations and the leverage to control intermittent wind supply. In this more dynamic energy system, deployment of energy storage at the site of consumption is envisioned to create synergies with the local distributed generation (DG) system. From a large end-user perspective, this paper contributes to the practical understanding of smart grids by modelling the impact of real-time pricing schemes (smart grids) on a hybrid DG system (mixed generation for heating and electricity loads) coupled with storage units. Specifically, we address: How does the portfolio of DG units affect the value of energy storage? and, what is the value of energy storage when assessing different designs of demand response for the end-user? To this end, we formulate a dynamic optimization model to represent a real-life urban community’s energy system composed of a co-generation unit, gas boilers, electrical heaters and a wind turbine. We discuss the techno-economic benefits of complementing this end-user’s energy system with storage units (thermal storage and battery devices). The paper analyses the storages policy strategies to simultaneously satisfy heat and electricity demand through the efficient use of DG units under demand response mechanisms. Results indicate that the storage units reduce energy costs by 7–10% in electricity and 3% in gas charges. In cases with a large DG capacity, the supply–demand mismatch increases, making storage more valuable.
KW - Energy storage
KW - Smart grid
KW - Modelling
KW - Renewable
KW - Distributed generation
KW - Demand response
U2 - 10.1016/j.apenergy.2016.01.095
DO - 10.1016/j.apenergy.2016.01.095
M3 - Journal article
VL - 170
SP - 476
EP - 488
JO - Applied Energy
JF - Applied Energy
SN - 0306-2619
ER -