TY - JOUR
T1 - Measuring the value of energy storage systems in a power network
AU - Agrali, Cansu
AU - Gultekin, Hakan
AU - Tekin, Salih
AU - Oner, Nihat
N1 - Funding Information:
The first author is partially supported by the Scientific and Technological Research Council of Turkey (TÜBİTAK ), Grant No. 2228 . We would like to thank to the anonymous reviewers whose comments have greatly improved this manuscript.
Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2020/9
Y1 - 2020/9
N2 - The increased use of renewable generators and their intermittent behavior motivates network operators to deploy energy storage systems. In this study, energy storage types, locations, and capacities are optimized for a capacitated electric power network with renewable generation. Short term operational decisions that include charging/discharging schedules and capacity management of the storage systems are included in this optimization framework to capture hourly, daily, and seasonal fluctuations of the demand, renewable generation, and energy prices. A Mixed Integer Linear Programming (MILP) formulation is developed but because of the computational complexity, a mathematical programming based metaheuristic algorithm is proposed. With a numerical study, the proposed heuristic method is proved to be highly effective compared to the MILP formulation and an existing state of the art algorithm. The effects of storage installation costs, line capacities, demand and generation variance on the values of storage systems and on the installation decisions are analyzed through numerical studies.
AB - The increased use of renewable generators and their intermittent behavior motivates network operators to deploy energy storage systems. In this study, energy storage types, locations, and capacities are optimized for a capacitated electric power network with renewable generation. Short term operational decisions that include charging/discharging schedules and capacity management of the storage systems are included in this optimization framework to capture hourly, daily, and seasonal fluctuations of the demand, renewable generation, and energy prices. A Mixed Integer Linear Programming (MILP) formulation is developed but because of the computational complexity, a mathematical programming based metaheuristic algorithm is proposed. With a numerical study, the proposed heuristic method is proved to be highly effective compared to the MILP formulation and an existing state of the art algorithm. The effects of storage installation costs, line capacities, demand and generation variance on the values of storage systems and on the installation decisions are analyzed through numerical studies.
KW - Energy storage
KW - Heuristics
KW - Mixed integer linear programming
KW - Renewable energy
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U2 - 10.1016/j.ijepes.2020.106022
DO - 10.1016/j.ijepes.2020.106022
M3 - Article
AN - SCOPUS:85082554043
SN - 0142-0615
VL - 120
JO - International Journal of Electrical Power and Energy Systems
JF - International Journal of Electrical Power and Energy Systems
M1 - 106022
ER -
