Electrical vehicle grid integration for demand response in distribution networks using reinforcement learning

Abstract

Most utilities across the world already have demand response (DR) programs in place to incentivise consumers to reduce or shift their electricity consumption from peak periods to off-peak hours usually in response to financial incentives. With the increasing electrification of vehicles, emerging technologies such as vehicle-to-grid (V2G) and vehicleto-home (V2H) have the potential to offer a broad range of benefits and services to achieve more effective management of electricity demand. In this way, electric vehicles (EV) become distributed energy storage resources and can conceivably, in conjunction with other electricity storage solutions, contribute to DR and provide additional capacity to the grid when needed. Here, an effective DR approach for V2G and V2H energy management using Reinforcement Learning (RL) is proposed. Q-learning, an RL strategy based on a reward mechanism, is used to make optimal decisions to charge or delay the charging of the EV battery pack and/or dispatch the stored electricity back to the grid without compromising the driving needs. Simulations are presented to demonstrate how the proposed DR strategy can effectively manage the charging/discharging schedule of the EV battery and how V2H and V2G can contribute to smooth the household load profile, minimise electricity bills and maximise revenue.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

A Dynamic Peer-to-Peer Electricity Market Model for a Community Microgrid With Price-Based Demand Response

“…Therefore, P2P energy market may not only depend on the excess of power from PV generation, but also involves EVs in energy trading during their charging and discharging operations. To enable the participation of EVs in P2P energy markets, an efficient pricing strategy must be adopted to balance the interests of all the players [19]. This paper focuses on energy sharing problem inside a residential community.…”

“…𝑃 𝒾,𝒿 = 𝓇 𝒾,𝒿 ℓ 𝒾,𝒿 + 𝑝 𝒿 + ∑ 𝑃 𝒿,𝓀 𝒽:(𝒿,𝓀)∈ℰ(17) 𝑄 𝒾,𝒿 = 𝓍 𝒾,𝒿 ℓ 𝒾,𝒿 + 𝑞 𝒿 + ∑ 𝑄 𝒿,𝓀 𝒽:(𝒿,𝓀)∈ℰ(18) 𝑣 𝒾 − 𝑣 𝒿 = 2(𝓇 𝒾,𝒿 𝑃 𝒾,𝒿 + 𝓍 𝑖,𝒿 𝑄 𝒾,𝒿 ) − (𝓇 𝒾,𝒿 2 + 𝓍 𝒾,𝒿 2 )ℓ 𝑖,𝒿(19) …”

Are Commercial EV Chargers Ready to Aid with Household Power Consumption?

“…As a result, in addition to offering the energy required for driving, EV batteries bring a great amount of unused capacity. EV as a distributed energy storage system can become an essential element of the smart grid if the idle battery is used to store and feed power to the grid or consumers [5]. EVs as a short-term energy storage system can supply electricity to household appliances throughout blackouts (vehicle-to-home (V2H)), provide quick charging to other EVs (vehicle-to-vehicle (V2V)), or feed energy to the transmission network (vehicle-to-grid (V2G)) [1,5].…”

Resilience-Oriented Scheduling of Shared Autonomous Electric Vehicles: A Cooperation Framework for Electrical Distribution Networks and Transportation Sector

“…Like conventional EVs, an important potential of SAEVs is the ability to deliver the electrical energy stored in their batteries to the power grid, called V2G capability. Tis feature of SAEVs can provide the power system with various ancillary services such as peak shaving [40][41][42], demand response [43,44], mitigating renewables generation variability and intermittency [45,46], voltage, and frequency regulation [47][48][49][50][51][52]. In addition, SAVEs can help distribution networks in emergency conditions to make the grid more resilient.…”