Joint Shaping and Altering the Demand Profile by Residential Plug-in Electric Vehicles for Forward and Spot Markets in Smart Grids
Farshad Rassaei, Wee-Seng Soh, Kee-Chaing Chua

TL;DR
This paper presents a decentralized algorithm for managing electric vehicle charging and discharging to optimize electricity procurement costs in smart grids, achieving significant cost savings and demand flexibility.
Contribution
It introduces a novel joint demand shaping and altering algorithm for V2G-enabled PEVs that is scalable, privacy-preserving, and effective in reducing procurement costs in two-settlement markets.
Findings
Up to 28% cost savings for retailers.
Effective demand profile management in high renewable integration scenarios.
Enhanced market competitiveness and lower consumer costs.
Abstract
Plug-in electric vehicles (PEVs) can significantly increase the elasticity of residential electricity demand. This elasticity can be employed to shape the daily aggregated electricity demand profile of a system comprised of a large number of residential PEVs' users sharing one electricity retailer or an aggregator. In this paper, we propose a joint demand shaping and altering algorithm for managing vehicle-to-grid (V2G) enabled PEVs' electricity assignments (charging and discharging) in order to diminish the overall electricity procurement costs for a retailer bidding to two-settlement electricity markets, i.e., a day-ahead (DA) and a real-time (RT) market. This approach is decentralized, scalable, fast converging and does not violate users' privacy. Our simulations' results demonstrate significant overall cost savings (up to 28\%) for a retailer bidding to an operational electricity…
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