Optimal Day-Ahead Scheduling and Bidding Strategy of Risk-Averse Electric Vehicle Aggregator : A Case Study of the Nordic Energy and Frequency Containment Reserve Markets

Abstract: The Nordic synchronous grid is facing a number of challenges. The ongoingphaseout of synchronous generation coupled with increased penetration ofintermittent renewable generation is leading to reduced system inertia. Additionally,the electrification of sectors of the economy such as transport willresult in the addition of significant new electrical loads. All these factors arecontributing to increased complexities in maintaining the power balance. Assuch, it is imperative that every resource potentially capable of providing flexibility,on both sides of the balancing equation, must be closely examined.The electrification of private transport is a technology of growing interestthat can provide flexibility to the power system if adequately utilized. Electricvehicles (EV) can be considered as temporary energy storages with availability,energy and capacity constraints. If aggregated in sufficient numbers orcombined with other assets they can fulfill the minimum bid size of specificmarkets. Numerous previous references have studied the potential in aggregatingthe increasingly important EV charging load. However, they are basedon synthetic driving behavior and vehicle characteristics and commonly investigateonly energy arbitrage. Furthermore, no studies have examined an EVaggregator entering Nordic energy and primary reserve markets to the authors’best knowledge.In this study, we use first hand data of a real EV fleet of 806 Tesla vehiclesand their historical driving patterns to develop a two-stage stochastic optimizationproblem. Based on a scenario selection method, this research provides anoptimal risk-averse bidding strategy for an aggregator of EVs that places bidsin both the day ahead energy and primary reserve markets in the Nordicsthrough the use of GAMS/Matlab software. Only uni-directional charging isexamined, while we consider two sources of uncertainty from prices and vehicleutilization and model a risk averse aggregator that aims to maximize its profits.A case study is carried out modelling individual vehicles and their real worldcharacteristics and driving behavior in the price areas NO5 & SE3 in Norway& Sweden across a 24hr weekday period for winter and summer. Results showstrong alignment of EV availability and periods of high primary reserve marketprices, with consumption being shifted largely towards early hours of the morning.In Norway, 342 NOK can be expected as revenue from combined energyarbitrage and FCR-N per vehicle per year, while in Sweden the value is 1470SEK. When compared to a reference “cost of charging case”, up to 50% of thecost of charging can be covered in Norway, while the entire cost is essentiallymet in Sweden; resulting in the value proposition of “free charging” to the enduser.