There has been a significant increase in the interest and implementations of heat pump systems for HVAC purposes in general and of ground source heat pumps (GSHPs) in particular. Though these systems have existed for decades, primarily in Europe, there has been an upward trend particularly in the United States in recent years. With the world-wide push toward CO2 emissions reduction targets, interest in heat pump systems to reduce CO2 emissions from heating and cooling is likely to only increase in the future. However, more than ever, financial considerations are also key factors in the implementation of any system. Ground source heat pumps (GSHPs) coupled to vertical borehole heat exchangers (BHEs) have been promoted as a viable heat pump system in climates where traditional air source heat pumps (ASHPs) may operate inefficiently. This type of system claims superior performance to ASHPs due to the relatively consistent temperature of the ground compared to the air, offering a higher temperature heat source in the heating season and a lower temperature sink in the cooling season. Projects designing and installing such a GSHP system have been implemented at large scales on several university campuses to provide heating and cooling. In this study, we aim to test the idea that a GSHP system, as a replacement for an existing CHP heating and conventional cooling systems, could reduce CO2 emissions, as well as provide a cost benefit to a large energy consumer, in this case the University of Massachusetts. This will be done using the existing heating and cooling loads provided by the conventional system and an established technique of modeling the heat pumps and BHEs. The GSHP system is modeled to follow the parameters of industry standards and sized to provide the best overall lifetime cost. The result on the overall annual costs, emissions, and university microgrid are considered.

The 2050 national energy scenarios as planned by the DECC, academia and industry specify a range of different decarbonised supply side technologies combined with the electrification of transportation and heating. Little attention is paid to the household demand side; indeed within many scenarios a high degree of domestic Demand Side Management (DSM) is implicit if the National Grid is to maintain supply-demand balance. A top-down, bottom-up hybrid model named Shed-able Household Energy Demand (SHED) has been developed and the results of which presented within this thesis. SHED models six published national energy scenarios, including three from the Department for Energy and Climate Change, in order to provide a broad coverage of the possible energy scenario landscape. The objective of which is to quantify the required changes in current household energy demand patterns via DSM, as are implicit under these highly electricity dominated scenarios, in order to maintain electrical supply-demand balance at the national level. The frequency and magnitude of these required household DSM responses is quantified. SHED performs this by modelling eleven years of supply-demand dynamics on the hourly time step, based on the assumptions of the published energy scenarios as well as weather data from around 150 weather stations around the UK and National Grid historic electricity demand data. The bottom-up component of SHED is populated by 1,000 households hourly gas and electricity demand data from a recently released dataset from a smart metering trial in Ireland. This aggregate pool of households enables national domestic DSM dynamics to be disaggregated to the aggregate household level. Using household classifications developed by the Office for National Statistics three typical ' households are identified within the aggregate pool and algorithms developed to investigate the possible required responses from these three households. SHED is the first model of its kind to connect national energy scenarios to the implications these scenarios may have on households consumption of energy at a high temporal resolution. The analysis of the top-down scenario modelling shows significant periods where electrical demand exceeds supply within all scenarios, within many scenarios instances exist where the deficit is unserviceable due to lack of sufficient spare capacity either side of the deficit period. Considering the level of participation required within the modelled scenarios in order to balance the electricity system and the current lack in understanding of smart metering and Time-Of-Use (TOU) tariffs within households, it would seem there is a disconnect between the electricity system being planned, the role this system expects of households and the role households are willing to play.