Dynamic Modeling and Seasonal Performance Evaluation of Air-to-Water Heat Pump Systems

In this Thesis a series of numerical models for the evaluation of the seasonal performance of reversible air-to-water heat pump systems coupled to residential and non-residential buildings are presented. The exploitation of the energy saving potential linked to the adoption of heat pumps is a hard task for designers due to the influence on their energy performance of several factors, like the external climate variability, the heat pump modulation capacity, the system control strategy and the hydronic loop configuration. The aim of this work is to study in detail all these aspects. In the first part of this Thesis a series of models which use a temperature class approach for the prediction of the seasonal performance of reversible air source heat pumps are shown. An innovative methodology for the calculation of the seasonal performance of an air-to-water heat pump has been proposed as an extension of the procedure reported by the European standard EN 14825. This methodology can be applied not only to air-to-water single-stage heat pumps (On-off HPs) but also to multi-stage (MSHPs) and inverter-driven units (IDHPs). In the second part, dynamic simulation has been used with the aim to optimize the control systems of the heat pump and of the HVAC plant. A series of dynamic models, developed by means of TRNSYS, are presented to study the behavior of On-off HPs, MSHPs and IDHPs. The main goal of these dynamic simulations is to show the influence of the heat pump control strategies and of the lay-out of the hydronic loop used to couple the heat pump to the emitters on the seasonal performance of the system. A particular focus is given to the modeling of the energy losses linked to on-off cycling.

Dynamic food systems and climate-induced risks transmission for food and nutritional security

Agriculture market instability impedes achieving the global goal of sustainable and resilient food systems. Currently, the support to producers reaches the mammoth USD 540 billion a year and is projected to reach USD 1.8 trillion by 2030. This gigantic increase requires a repurposing agricultural support strategy (RASS), considering the market country-specific circumstances. These circumstances may vary with geographic locations, marketing structures, and product value chains. The fruit production system is crucial for health-conscious consumers and profit-oriented producers for food and nutritional security. Export is one of the main driving forces behind the expansion of the fruit sector, and during the year 2010-2018, trade significantly outpaced production increases. The previous literature states that irregular and unpredictable behaviour — Chaos — can arise from entirely rational economic decision-making within markets. Different markets' direct/indirect linkages through trade create trade hubs, and uncertainty may function as an avenue to transmit adverse shocks and increase vulnerability rather than contribute to resilience. Therefore, distinguishing Chaos into an endogenous and exogenous pattern of behaviour is cradled to formulate an effective RASS for resilient food systems and to understand global food crises. The present research is aimed at studying the market dynamics of three regional trade hubs, i.e., Brazil (South America), Italy (Europe), and Pakistan (Asia), each representing advanced to traditional value chains to control uncertainty (risks). The present research encompasses 1) a systematic review to highlight the research dynamism and identify grey-areas of research. Based on the findings, we have investigated the 2) nonlinear impacts of climate-induced price responsiveness in monopsony markets. Once we highlighted the importance of marketing structures/arrangements, 3) we developed a risk transmission framework to address the co-evolving impacts in complex dynamic interactions.