Market-based Demand Response via Residential Plug-in Electric Vehicles in Smart Grids

TL;DR

This paper presents a decentralized demand response method for managing electric vehicle charging and discharging to reduce electricity costs for retailers in smart grids, demonstrating significant cost savings through simulations.

Contribution

It introduces a scalable, privacy-preserving algorithm for V2G-enabled PEVs to optimize demand response in two-settlement electricity markets, enhancing cost efficiency.

Findings

Significant cost savings for retailers using the proposed algorithm

The method is decentralized, scalable, and respects user privacy

Effective in scenarios with high renewable energy integration and demand fluctuations

Abstract

Flexibility in power demand, diverse usage patterns and storage capability of plug-in electric vehicles (PEVs) grow the elasticity of residential electricity demand remarkably. This elasticity can be utilized to form the daily aggregated demand profile and/or alter instantaneous demand of a system wherein a large number of residential PEVs share one electricity retailer or an aggregator. In this paper, we propose a demand response (DR) technique to manage vehicle-to-grid (V2G) enabled PEVs' electricity assignments (charging and discharging) in order to reduce the overall electricity procurement costs for a retailer bidding to a two-settlement electricity market, i.e., a day-ahead (DA) and a spot or real-time (RT) market. We show that our approach is decentralized, scalable, fast converging and does not violate users' privacy. Extensive simulations show significant overall cost savings can be achieved for a retailer bidding to an operational electricity market by using the proposed algorithm. This technique becomes more needful when the power grid accommodates a large number of intermittent energy resources wherein RT demand altering is crucial due to more likely contingencies and hence more RT price fluctuations and even occurring the so-called \textit{black swan events}. Finally, such retailer could offer better deals to customers as well.