Decentralized Charging Control of Large Populations of Plug-in Electric Vehicles

Ma, Zhongjing; Callaway, Duncan S.; Hiskens, Ian A.

doi:10.1109/tcst.2011.2174059

Cited by 855 publications

(528 citation statements)

References 21 publications

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“…In other words, each appliance regulates automatically and in a decentralized fashion its power demand based on the mains frequency. A similar concept characterizes a recent literature on "load control" in power systems [12,14,26,28,37]. In particular, [12] surveys issues related to the redistribution of the load away from peak hours and the design of decentralized strategies to produce a predefined load trajectory (see also [14]).…”

Section: Introductionmentioning

confidence: 88%

“…Thus the aforementioned conflicting objectives have led scientists to adopt noncooperative games as paradigmatic models. In [26] the authors present a large population game where the agents are plugin electric vehicles and the Nash-equilibrium strategies (see [9]) correspond to distributed charging policies that redistribute the load away from peaks (called valley-filling strategies). In this paper we adopt the same perspective in that we show that network frequency stabilization can be achieved by giving incentives to the agents to adjust their strategies in order to converge to a a mean field equilibrium.…”

Section: Introductionmentioning

confidence: 99%

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Mean-Field Games and Dynamic Demand Management in Power Grids

Bagagiolo

Bauso

2013

Dyn Games Appl

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This paper applies mean field game theory to dynamic demand management. For a large population of electrical heating or cooling appliances (called agents), we provide a mean field game that guarantees desynchronization of the agents thus improving the power network resilience. Second, for the game at hand, we exhibit a mean field equilibrium, where each agent adopts a bang-bang switching control with threshold placed at a nominal temperature. At the equilibrium, through an opportune design of the terminal penalty, the switching control regulates the mean temperature (computed over the population) and the mains frequency around the nominal value. To overcome Zeno phenomena we also adjust the bang-bang control by introducing a thermostat. Third, we show that the equilibrium is stable in the sense that all agents' states, initially at different values, converge to the equilibrium value or remain confined within a given interval for an opportune initial distribution.

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Section: Introductionmentioning

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Mean-Field Games and Dynamic Demand Management in Power Grids

Bagagiolo

Bauso

2013

Dyn Games Appl

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“…After a detailed theoretical analysis, we provide a semi-decentralized scheme that allows to coordinate the appliances and induce a Nash equilibrium under very general conditions. Decentralized convergence of flexible appliances to a Nash equilibrium has already been obtained by introducing some quadratic term in the cost function of the agents, as proposed by Ma et al (2013), or under some conditions on the price function and the number of devices, as presented for example in Chen et al (2014). The main novelty of the proposed semidecentralized scheme is the possibility to induce a stable solution for any penetration level of flexible demand, with no additional terms in the cost function of the agents nor precise knowledge of the electricity price function.…”

Section: Introductionmentioning

confidence: 99%

A Semi-Decentralized Scheme for Integration of Price-Responsive Appliances in the Electricity Market

2017

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A novel semi-decentralized control strategy is proposed for the integration in the power system of large populations of flexible loads, such as electric vehicles and "smart" appliances. To characterize the interactions between the single agents and their effects on the grid, a game theory framework is adopted. The price responsive appliances are modelled as competing players, characterizing a stable and efficient solution as a Nash equilibrium (no device has unilateral interest in changing its scheduled power consumption when the final electricity price is considered). We extend previous results on distributed control of flexible demand, proposing a partial centralization of the power scheduling at critical time instants. In this way, it is possible to ensure convergence to a Nash equilibrium for a wider range of scenarios, considering higher penetration levels of flexible demand and a wider range of parameters for the devices. The effectiveness of the proposed scheme is theoretically proved and its performance is evaluated in simulations, considering a future UK grid with high penetration of flexible demand.

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“…Metering is intended to inform a deregulated spot-price system which is in turn intended to incentivize the efficiencies found in free markets (e.g., [23], [11], [4]), in particular through demand-side management. Such consumer load management is even more crucial as plug-in electric vehicles (PEVs), including plug-in hybrid electric vehicles (PHEVs), are coming to the market [18], [13]. With battery capacities varying from 15 to 50 kWh, these vehicles are expected to double the average household load during charging time [9].…”

Section: Introductionmentioning

confidence: 99%

“…The design of appropriate incentives and efficient energyconsumption scheduling algorithms (e.g., [15], [1], [13]) is a primary goal for the smart grid, i.e., incentivizing consumers to offload demand to off-peak periods, also known as "peak shaving," see, e.g., [25].…”

Section: Introductionmentioning

confidence: 99%

Avoiding overages by deferred aggregate demand for PEV charging on the smart grid

Pang

Kesidis

Konstantopoulos

2012

2012 IEEE International Conference on Communications (ICC)

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Abstract-In this paper, we model the aggregate overnight demand for electricity by a large community of (possibly hybrid) plug-in electric vehicles (PEVs) each of whose power demand follows a prescribed profile and is interruptible. The community is serviced by a regional electrical utility which is assumed to purchase electricity from a state/national distribution grid according to a flat-rate φ per kilowatt-unit-time up to a threshold L, and thereafter overage charges π > φ are leveed per kilowatt-unit-time. Rather than a spot-price system for household consumers (which would necessarily need to be operated by automated means overnight when most people sleep), the "grid" (regional utility) is "smart" in that it monitors its total load and, when overages threaten, can reduce load by signaling certain consumers to defer their load by one unit of time. In this paper, we model undeferred load by a Gaussian process which we justify by means of a functional central limit theorem. This limiting Gaussian process is the arrival process of a discrete-time queue which is used to model the deferred load over a finite timehorizon. We can then compute the mean amount of overage at the end of this time horizon (say at 6 AM when charging is to be completed ahead of the morning commute).

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Decentralized Charging Control of Large Populations of Plug-in Electric Vehicles

Cited by 855 publications

References 21 publications

Mean-Field Games and Dynamic Demand Management in Power Grids

Mean-Field Games and Dynamic Demand Management in Power Grids

A Semi-Decentralized Scheme for Integration of Price-Responsive Appliances in the Electricity Market

Avoiding overages by deferred aggregate demand for PEV charging on the smart grid

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