Game Theoretic Stochastic Energy Coordination under A Distributed Zeroth-order Algorithm
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Author / Producer
Date
2020-11
Publication Type
Conference Paper
ETH Bibliography
yes
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Abstract
Dealing with the effects from uncertainties properly is a key problem in stochastic energy management problems to achieve safe and efficient operation of the system. In this paper, we study the problem of coordinating multi-period electric vehicles charging amidst uncertainty from the embedded renewable generation in a local distribution network under transformer capacity limits. A stochastic generalized game is presented to formulate the underlying electric vehicle coordination problem wherein the cost function of each player is affected by the intermittent renewable energy supply. Existing algorithms for seeking the equilibrium rely on conditions on the form of the cost functions. In our setting, however, stochastic effects are not known in advance which results in an unknown form of the cost functions. We propose a distributed iterative zeroth-order algorithm, which only relies on the observations of costs, to achieve a stochastic generalized Nash equilibrium of the game under the concept of Gaussian smoothing. Under certain mild assumptions, the proposed algorithm is guaranteed to converge to the neighborhood of the stochastic generalized Nash equilibrium. We demonstrate the algorithm for a distribution network energy management problem with 3 heterogeneous subgroups of electric vehicles.
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Publication status
published
External links
Book title
21st IFAC World Congress
Journal / series
Volume
53 (2)
Pages / Article No.
4070 - 4075
Publisher
Elsevier
Event
1st Virtual IFAC World Congress (IFAC-V 2020)
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Energy coordination; random renewable generation; capacity limit; stochastic generalized Nash equilibrium; distributed zeroth-order algorithm
Organisational unit
03751 - Lygeros, John / Lygeros, John
Notes
Due to the Coronavirus (COVID-19) the 21st IFAC World Congress 2020 became the 1st Virtual IFAC World Congress (IFAC-V 2020).
Funding
787845 - Optimal control at large (EC)