Risk-aware strategies for optimal participation of parking lots in day-ahead electricity markets

Abstract

The decarbonization of the mobility industry rules the massive deployment of charging infrastructures worldwide. Frequently, charging points are installed by private companies and entities, which pursue a monetary profit through providing charging services. It is therefore interesting looking for business opportunities that maximize the monetary profit of such infrastructures. In this regard, large-scale parking lots can partake in wholesale electricity markets, where they can buy or sell energy, thus actuating as a high-capacity virtual battery storage system. In this paper, a novel methodology for optimal participation of parking lots in day-ahead electricity markets is developed. The new proposal contributes with two main advantages compared to other similar research. On the one hand, we properly consider both charging and discharging modes of electric vehicles, which enable full participation in electricity markets as load or generator. On the other hand, an adaptive uncertainty-aware model is proposed and accommodated into the developed tool, thus casting as a unified framework that allows adopting both risk-averse and risk-seeker operational strategies. To this end, a tailored mathematical model is proposed, wherein uncertainties and binary variables related to operational statuses of batteries are properly accommodated via an original Benders’ decomposition algorithm. Moreover, different improvement strategies are proposed, thus resulting in a practical tool with potential fields of application in industry. A number of numerical results are provided to validate the new tool, as well as analyse how the adoption of risk-averse or risk-seeker strategies affects the strategic participation of parking lots in electricity markets.