Optimized Energy Market Bidding Strategies to Create Revenue from Vehicle to Grid Operation in the Swiss Logistics Sector

Given the ever-increasing pressure created by climate change, everyone must contribute to preserving this planet. From a regulatory point of view, this is also the case for the logistics industry, which is facing the challenge of decarbonization as a significant change. Considering the resulting opportunities for new business models, this thesis deals with the statement," Vehicle-to-Grid operation can produce additional revenue by implementing optimal bidding strategies in the Swiss logistics sector through strategic energy market participation without affecting the efficiency of the core business of the logistics operation" and shows ways and strategies to confirm this. Common methods such as the systematic literature review, design science research, and experimental optimization are used. A model specific to the context is instantiated and applied using experimental optimization. As can be seen, profits or cost savings of 2,000€ to almost 70,000€ per month can be achieved under certain conditions without affecting the core business. This is supported by applying bidding strategies in the context of near-reality scenarios, applying actual context data - commodity prices - and using accurate exchange prices of EPEX Spot.

The model created is a maximization problem, which is optimized in two variants and meets the requirements of Swiss logistics providers. The first approach searches for volumes at a fixed price, and the second one searches for prices and volumes at a constrained price. For this purpose, the integer linear programming, CPLEX, and Gurobi are used in addition to an hourly price forward curve (HPFC) which is created as a multiple linear regression with inputs such as commodity prices or weather data. Based on the obtained results, the second approach can be seen as non-applicable because of low settlement rates. The first approach successfully supports the business model and can be applied and adapted to meet additional requirements. The presented model can be seen as future proof of changing prices or constraints because the HPFC relies on commodity and market prices that would align accordingly. Because of this, a successful conclusion can be drawn that the model and its experimental optimization could be applied in a real world scenario if the technical implementation is ready.