Iossa, Raffaele (2025) The role of control strategies in optimal sizing of cogeneration systems: a multi vectorial problem. [Tesi di dottorato]

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Abstract

The ongoing energy transition requires distributed energy systems that are flexible, efficient, and resilient under variable operating conditions. Among these, Combined Heat and Power (CHP) technologies play a key role in enhancing energy efficiency and reducing primary energy consumption. However, most design approaches treat system sizing and operational control as separate problems, neglecting their interaction and the influence of uncertainty on real performance. This simplification often leads to non-optimal or unstable configurations over the plant lifetime. This work develops an integrated optimization framework that explicitly couples optimal sizing and control strategies of CHP systems within a unified numerical environment. The framework combines deterministic and robust multi-objective optimization methods, employing thermodynamic-based performance correlations for reciprocating internal combustion engines. It simultaneously evaluates energetic, economic, and environmental objectives while enforcing operational and thermodynamic constraints. A Hospital energy system in Basilicata (Italy) serves as case study. Results show that the control strategy and the hourly-based target profoundly affects the optimal configuration: maximizing the Total Primary Energy Saving (TPES) yields smaller and modular CHP units, while minimizing operating costs favors larger systems with shorter payback times. To address market variability, a robust optimization approach based on Monte Carlo sampling of energy tariffs is introduced. Compared to deterministic optima, robust solutions exhibit lower performance sensitivity and improved economic stability, confirming the necessity of incorporating uncertainty in CHP design. The proposed methodology provides a comprehensive and computationally efficient framework for CHP design and operation, enabling more reliable, cost-effective, and sustainable distributed energy systems aligned with next-generation multi-vector energy systems.

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