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Open AccessJournal ArticleDOI

A Scalable Three-Step Approach for Demand Side Management of Plug-in Hybrid Vehicles

TLDR
Results show that the proposed three-step approach is able to charge PHEVs with comparable quality to optimal, centrally computed charging plans, while significantly improving scalability.
Abstract
In this paper, we present a scalable approach for DSM (demand side management) of PHEVs (plug-in hybrid electric vehicles). Essentially, our approach consists of three steps: aggregation, optimization, and control. In the aggregation step, individual PHEV charging constraints are aggregated upwards in a tree structure. In the optimization step, the aggregated constraints are used for scalable computation of a collective charging plan, which minimizes costs for electricity supply. In the real-time control step, this charging plan is used to create an incentive signal for all PHEVs, determined by a market-based priority scheme. These three steps are executed iteratively to cope with uncertainty and dynamism. In simulation experiments, the proposed three-step approach is benchmarked against classic, fully centralized approaches. Results show that our approach is able to charge PHEVs with comparable quality to optimal, centrally computed charging plans, while significantly improving scalability.

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Citations
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Journal ArticleDOI

Electric vehicle fleet management in smart grids: A review of services, optimization and control aspects

TL;DR: In this article, a review and classification of methods for smart charging (including power to vehicle and vehicle-to-grid) of electric vehicles for fleet operators is presented, and three control strategies and their commonly used algorithms are described.
Journal ArticleDOI

Residential Demand Response of Thermostatically Controlled Loads Using Batch Reinforcement Learning

TL;DR: The experiments show that batch RL techniques provide a valuable alternative to model-based controllers and that they can be used to construct both closed-loop and open-loop policies.
Journal ArticleDOI

Optimal Bidding Strategy of a Plug-In Electric Vehicle Aggregator in Day-Ahead Electricity Markets Under Uncertainty

TL;DR: In this paper, the problem of an aggregator bidding into the day-ahead electricity market with the objective of minimizing charging costs while satisfying the PEVs' flexible demand is addressed.
Journal ArticleDOI

Optimal Coordination and Scheduling of Demand Response via Monetary Incentives

TL;DR: This paper proposes a decentralized framework in which the aggregator seeks to maximize its profits while the consumers minimize their costs in response to time-varying prices, and additional incentives provided to mitigate potential overloads in the distribution system.
Journal ArticleDOI

Reinforcement Learning of Heuristic EV Fleet Charging in a Day-Ahead Electricity Market

TL;DR: This paper addresses the problem of defining a day-ahead consumption plan for charging a fleet of electric vehicles (EVs), and following this plan during operation, and shows that the approach is able to find a day's consumption plan with comparable quality to the benchmark solution, without requiring an exact day- Ahead model of each EVs charging flexibility.
References
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Journal ArticleDOI

Autonomous Demand-Side Management Based on Game-Theoretic Energy Consumption Scheduling for the Future Smart Grid

TL;DR: This paper presents an autonomous and distributed demand-side energy management system among users that takes advantage of a two-way digital communication infrastructure which is envisioned in the future smart grid.
Journal ArticleDOI

The Impact of Charging Plug-In Hybrid Electric Vehicles on a Residential Distribution Grid

TL;DR: In this article, the authors proposed a coordinated charging strategy to minimize the power losses and to maximize the main grid load factor of the plug-in hybrid electric vehicles (PHEVs).
Journal ArticleDOI

Management and Control of Domestic Smart Grid Technology

TL;DR: Using good predictions, in advance planning and real-time control of domestic appliances, a better matching of demand and supply can be achieved and a more energy-efficient electricity supply chain can be achieve.
Journal ArticleDOI

A Direct Load Control Model for Virtual Power Plant Management

TL;DR: In this paper, the authors proposed an optimization algorithm to manage a virtual power plant (VPP) composed of a large number of customers with thermostatically controlled appliances based on a direct load control (DLC).
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