Advanced capacity and dispatch co-design for the techno-economic optimization of integrated energy systems

Abstract

This thesis explores the techno-economic performance of integrated energy systems by means of a linear optimization framework performed using direct transcription inside the DTQP environment. Over operational and financial time horizons, the model co-optimizes generating and storing technologies to maximize net present value (NPV) under different techno-economic assumptions. The basic dynamics of the subsystems are specified, with a special focus on balancing important physical and financial domains to enable effective decision-making within the framework of capacity and dispatch optimization. Three sample case studies — natural gas with thermal storage, wind power with battery systems, and nuclear energy with hydrogen storage — are thoroughly analyzed in order to extend the basic concept, including sensitivity analysis. To assess their impact on ideal investment and deployment policies, key input parameters such as carbon tax levels, power and fuel prices, and capital and operating expenses are methodically changed. Results show that some factors, such as generator capital expenditures, especially electricity prices and energy prices, have an unusual influence on economic results, while others have little effect at all. These results are presented using scenario-specific outputs, comparison graphs, and trajectory-based insights, providing useful guidance on model robustness and decision-critical assumptions.