Traditionally, the management of power distribution networks relies on the centralized implementation of the optimal power flow and, in particular, the minimization of the generation cost and transmission losses. Nevertheless, the increasing penetration of both renewable energy sources and independent players such as ancillary service providers in modern networks have made this centralized framework inadequate. Against this background, we propose a nonco-operative game-theoretic framework for optimally controlling energy storage systems (ESSs) in power distribution networks. Specifically, in this paper we address a power grid model that comprehends traditional loads, distributed generation sources and several independent energy storage providers, each owning an individual ESS. Through a rolling-horizon approach, the latter participate in the grid optimization process, aiming both at increasing the penetration of distributed generation and leveling the power injection from the transmission grid. Our framework incorporates not only economic factors but also grid stability aspects, including the power flow constraints. The paper fully describes the distribution grid model as well as the underlying market hypotheses and policies needed to force the energy storage providers to find a feasible equilibrium for the network. Numerical experiments based on the IEEE 33-bus system confirm the effectiveness and resiliency of the proposed framework.

A game-theoretic control approach for the optimal energy storage under power flow constraints in distribution networks / Scarabaggio, Paolo; Carli, Raffaele; Dotoli, Mariagrazia. - ELETTRONICO. - (2020), pp. 1281-1286. (Intervento presentato al convegno 16th International Conference on Automation Science and Engineering, CASE 2020 tenutosi a Hong Kong, China nel August 20-21, 2020) [10.1109/CASE48305.2020.9216800].

A game-theoretic control approach for the optimal energy storage under power flow constraints in distribution networks

Scarabaggio, Paolo
;
Carli, Raffaele;Dotoli, Mariagrazia
2020-01-01

Abstract

Traditionally, the management of power distribution networks relies on the centralized implementation of the optimal power flow and, in particular, the minimization of the generation cost and transmission losses. Nevertheless, the increasing penetration of both renewable energy sources and independent players such as ancillary service providers in modern networks have made this centralized framework inadequate. Against this background, we propose a nonco-operative game-theoretic framework for optimally controlling energy storage systems (ESSs) in power distribution networks. Specifically, in this paper we address a power grid model that comprehends traditional loads, distributed generation sources and several independent energy storage providers, each owning an individual ESS. Through a rolling-horizon approach, the latter participate in the grid optimization process, aiming both at increasing the penetration of distributed generation and leveling the power injection from the transmission grid. Our framework incorporates not only economic factors but also grid stability aspects, including the power flow constraints. The paper fully describes the distribution grid model as well as the underlying market hypotheses and policies needed to force the energy storage providers to find a feasible equilibrium for the network. Numerical experiments based on the IEEE 33-bus system confirm the effectiveness and resiliency of the proposed framework.
2020
16th International Conference on Automation Science and Engineering, CASE 2020
978-1-7281-6904-0
A game-theoretic control approach for the optimal energy storage under power flow constraints in distribution networks / Scarabaggio, Paolo; Carli, Raffaele; Dotoli, Mariagrazia. - ELETTRONICO. - (2020), pp. 1281-1286. (Intervento presentato al convegno 16th International Conference on Automation Science and Engineering, CASE 2020 tenutosi a Hong Kong, China nel August 20-21, 2020) [10.1109/CASE48305.2020.9216800].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/206772
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