Energy piles are heat capacity systems that have been increasingly exploited to provide both supplies of energy and structural support to civil structures. The energy and geotechnical behaviours of such foundations, which are governed by their response to thermo-mechanical loads, is currently not fully understood, especially considering the different design solutions for ground-coupled heat exchangers. This paper summarises the results of numerical sensitivity analyses that were performed to investigate the thermo-mechanical response of a full-scale energy pile for different (i) pipe configurations, (ii) foundation aspect ratios, (iii) mass flow rates of the fluid circulating in the pipes and (iv) fluid mixture compositions. This study outlines the impacts of the different solutions on the energy and geotechnical behaviour of the energy piles along with important forethoughts that engineers might consider in the design of such foundations. It was observed that the pipe configuration strongly influenced both the energy and the geotechnical performance of the energy piles. The foundation aspect ratio also played an important role in this context. The mass flow rate of the fluid circulating in the pipes remarkably influenced only the energy performance of the foundation. Usual mixtures of a water-antifreeze liquid circulating in the pipes did not markedly affect both the energy and the geotechnical performance of the pile

In this study a probabilistic approach for optimal sizing of cogeneration systems under long-term uncertainty in energy demand is proposed. A dynamic simulation framework for detailed modeling of the energy system is defined, consisting in both traditional and optimal operational strategies evaluation. A two-stage stochastic optimization algorithm is developed, adopting Monte Carlo method for the definition of a multi-objective optimization problem. An Italian hospital facility has been used as a case study and a gas internal combustion engine is considered for the cogeneration unit. The results reveal that the influence of uncertainties on both optimal size and annual total cost is significant. Optimal size obtained with the traditional deterministic approach are found to be sub-optimal (up to 30% larger) and the predicted annual cost saving is always lower when accounting for uncertainties. Pareto frontiers of different CHP configurations are presented and show the effectiveness of the proposed method as a useful tool for risk management and focused decision-making, as tradeoffs between system efficiency and system robustness

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