The market liberalization and renewable energy integration, increasing the uncertainty in operational planning, which implies more significant and more frequent deviations from schedules. A lack of proper decision-making tool, such as OPF, can impede the integration of renewable energy and system flexibility. A promising approach to model the OPF dealing with uncertainty is robust optimization (RO). Typically, a robust optimization model has a dual goal, generating performance as well as system reliability under uncertainty. This paper discusses an RO-based AC-OPF model for finding the optimal location of the energy storage system in the transmission network. An AC multi-temporal OPF algorithm that adopts a convex relaxation of the power flow equations to guarantee precise and optimal solutions with high algorithmic performance has been used. The developed model has been validated for storage planning on the IEEE-14 bus network.

Energy Storage Placement in the Transmission Network: A Robust Optimization Approach

Pisano G.;Pilo F.
2019-01-01

Abstract

The market liberalization and renewable energy integration, increasing the uncertainty in operational planning, which implies more significant and more frequent deviations from schedules. A lack of proper decision-making tool, such as OPF, can impede the integration of renewable energy and system flexibility. A promising approach to model the OPF dealing with uncertainty is robust optimization (RO). Typically, a robust optimization model has a dual goal, generating performance as well as system reliability under uncertainty. This paper discusses an RO-based AC-OPF model for finding the optimal location of the energy storage system in the transmission network. An AC multi-temporal OPF algorithm that adopts a convex relaxation of the power flow equations to guarantee precise and optimal solutions with high algorithmic performance has been used. The developed model has been validated for storage planning on the IEEE-14 bus network.
2019
978-8-8872-3745-0
energy storage; robust optimization; transmission network planning; uncertainty
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/282587
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