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Electric demand response and bounded rationality: mean-field control for large populations of heterogeneous bounded-rational agents
Author(s) -
Andrea Marín Radoszynski,
Pierre Pinson
Publication year - 2021
Publication title -
philosophical transactions of the royal society a mathematical physical and engineering sciences
Language(s) - English
Resource type - Journals
eISSN - 1471-2962
pISSN - 1364-503X
DOI - 10.1098/rsta.2019.0429
Subject(s) - bounded rationality , mathematical optimization , bounded function , demand response , nash equilibrium , computer science , flexibility (engineering) , population , renewable energy , uniqueness , rational agent , optimal control , mathematical economics , electricity , mathematics , engineering , mathematical analysis , statistics , demography , artificial intelligence , sociology , electrical engineering
The increased penetration of renewable energy sources into existing power systems induces challenges in supply–demand balancing. Demand-side flexibility is seen as an option to accommodate variability and limited predictability from renewable energy generation. Heat pumps at residential level, if well coordinated, can be one of those flexibility sources. The complexity involved is high though, since their coordinated operation combines control, population effects and the fact agents may actually not behave as rational decision-makers. We describe here a coordinated control framework that accounts for those aspects altogether. Decentralized model predictive control for large populations of heterogeneous agents is employed. As the cost to be minimized is affected by the population behaviour as a whole through the electricity price, the decentralized control is re-thought as a mean-field game. Existence and uniqueness of a Nash equilibrium are discussed while the Picard–Banach algorithm is used as a solution approach. It is extended to the case of bounded-rational agents. The impact on system dynamics of modelling agents as bounded rational is illustrated through numerical simulations. This article is part of the theme issue ‘The mathematics of energy systems’.

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