Managing Innovative Green Technologies: Residential Solar-Plus-Storage and Electric Truck Fleets

This dissertation considers two different problems: residential solar-plus-storage, and heavy-duty truck electrification. In part I, we examine the impact of the most common retail electricity price rules--flat rate and time-of-use (ToU) rates--on utility profits, emissions, and customer benefits in markets with these customers. ToU rates, which vary based on the time of consumption, are generally believed to offer more flexibility and are therefore assumed to be more favorable to utilities. However, our analysis reveals that under certain conditions, a flat rate may result in higher utility profits than ToU rates when residential solar-plus-storage customers are present. We find that the more favorable price rule for utilities depends on several factors, with the adoption level of residential solar-plus-storage systems being a critical determinant. Moreover, contrary to the perceived environmental superiority of ToU rates, we find that they may actually increase emissions compared to flat rates. Our study includes several extensions and verifies the robustness of our main insights. Using real-life data from California, we also conduct numerical studies and demonstrate that our key insights remain valid across a broad range of practical scenarios. Part II of the dissertation deals with fleet electrification for conventional heavy-duty trucks. Our analysis provides a framework for prioritizing electrification decisions with respect to investment and operating costs and emissions savings. We first identify the optimal time and cost of replacing the truck(s) serving a single route with electric trucks, and establish the conditions for its existence. We also compute emissions savings potential of electrifying the route at minimum cost. We investigate the sensitivity of the optimal solution to different problem parameters, demonstrating that the optimal electrification time is delayed and the optimal cost increases with demand and round-trip distance, while they both become smaller with electric truck's capacity. Our scenario analysis comparing a pair of routes shows that the optimal cost and emissions savings do not always agree on which route is the better choice for electrification. Using real-life data and dynamic programming formulation, we conduct a numerical analysis for electrification of multiple routes, and verify the analytical results obtained for the two-route case.