TY - JOUR
T1 - A Mean Field Game Approach for Distributed Control of Thermostatic Loads Acting in Simultaneous Energy-Frequency Response Markets
AU - De Paola, Antonio
AU - Trovato, Vincenzo
AU - Angeli, David
AU - Strbac, Goran
PY - 2019/11/30
Y1 - 2019/11/30
N2 - This paper proposes a novel distributed solution for the operation of large populations of thermostatically controlled loads (TCLs) providing frequency support. A game-theory framework is adopted, modelling the TCLs as price-responsive rational agents that schedule their energy consumption and allocate frequency response provision in order to minimize their operational costs. The novelty of this work lies in the use of mean field games to abstract the complex interactions of large numbers of TCLs with the grid and in the introduction of an innovative market structure, envisioning distinct price signals for electricity and response. Differently from previous approaches, such prices are not designed ad hoc but are derived instead from an underlying system scheduling model.
AB - This paper proposes a novel distributed solution for the operation of large populations of thermostatically controlled loads (TCLs) providing frequency support. A game-theory framework is adopted, modelling the TCLs as price-responsive rational agents that schedule their energy consumption and allocate frequency response provision in order to minimize their operational costs. The novelty of this work lies in the use of mean field games to abstract the complex interactions of large numbers of TCLs with the grid and in the introduction of an innovative market structure, envisioning distinct price signals for electricity and response. Differently from previous approaches, such prices are not designed ad hoc but are derived instead from an underlying system scheduling model.
U2 - 10.1109/TSG.2019.2895247
DO - 10.1109/TSG.2019.2895247
M3 - Article
VL - 10
SP - 5987
EP - 5999
JO - IEEE Transactions on Smart Grids
JF - IEEE Transactions on Smart Grids
SN - 1949-3053
IS - 6
ER -