Aggregator of Electric Vehicles Bidding in Nordic FCR-D Markets: A Chance-Constrained Program

TL;DR

This paper develops a chance-constrained optimization model for electric vehicle aggregators to participate in Nordic FCR-D markets, accounting for uncertainties and limited energy resources, demonstrating potential cost savings and strategic bidding advantages.

Contribution

It introduces a novel chance-constrained model for EV aggregator bidding in FCR-D markets, incorporating uncertainty and limited energy constraints, with real-world data validation.

Findings

Vehicle owners could save 6-10% on annual electricity bills.

Having more vehicles in a single portfolio enables larger bids.

The model effectively manages uncertainty in reserve capacity bids.

Abstract

The Danish system operator, Energinet, has recently introduced an innovative grid code called the P90 requirement, which allows stochastic flexible resources to bid their flexibility in Nordic ancillary service markets, contingent upon a minimum 90\% probability of successfully realizing the reserve capacity bid. For limited-energy resources, Energinet imposes additional requirements for participation in these markets. Given these requirements, this paper presents a chance-constrained optimization model designed for aggregators of electric vehicles, aiming to optimally place reserve capacity bids in the Nordic Frequency Containment Reserve for Disturbances (FCR-D) market while accounting for uncertainty in future consumption baselines. We analyze both FCR-D up and down markets, reformulating and solving the proposed joint chance-constrained model using two sample-based methods. Using real data from 1400 charging stations in Denmark from March 2022 to March 2023, we demonstrate the out-of-sample profit potential. Our findings indicate that vehicle owners could save between 6\% and 10\% on their annual electricity bills by providing FCR-D services. Additionally, we observed a synergy effect, where having more vehicles in a single portfolio enables larger bids per vehicle compared to a collective bid from multiple portfolios with the same total number of vehicles.