The present work reports a study related to the potential improvement of the energy performances of a heat pump based heating system for a Swedish single-family house. The analysis is focused on the design of new rule-based control strategies which employ perfect predictions of weather forecast and human behaviour information. In particular, the considered signals are the outdoor temperature, the solar radiation, the internal gain due to inhabitants’ activities and the Domestic Hot Water (DHW) consumption. The study is performed by means of the TRNSYS® simulation software in which the model of the heating system is implemented. More specifically, it is composed by a Ground Source Heat Pump (GSHP) unit, a stratified storage tank of three hundred litres and the building element. The performances of the developed control logics are evaluated using a degree-minute on/off controller as reference case. The results show that the improved control logics yield to an increase of the energy efficiency of the system as well as an enhancement of the indoor and DHW temperatures stability. / EffSys Expand P18: Smart Cotnrol Strategies for Heat Pump Systems

The present work deals with a study related to the analysis of weather data for heat pump system control improvement based on both instantaneous and forecasted measurements. In particular, the analysis is firstly focused on the comparison of multiple weather sources for the assessment of weather forecast uncertainties, based on the evaluation of errors in prediction with respect to measured values. Afterwards, the results are compared with the ones related to persistent predictions methods that assumes the state of the atmosphere to be stationary over the considered time interval. The development and testing of a new preliminary “predictive” control logic is also performed, thanks to TRNSYS numerical simulations, considering a typical Swedish single-family house located in Stockholm, with the aim of optimizing the operation of a heat pump heating system based on solar radiation prediction to yield energy and cost savings. With the crucial points of accuracy and precision by which the local weather processes can be predicted, the same TRNSYS model is run accounting for perfect predictions and solar radiation forecasted values. From this perspective, given the fact that forecast of solar radiation are usually absent within most of the weather forecast datasets, a deep analysis is also performed on hourly measurements of solar radiation to define a simple and effective methods to calculate hourly solar radiation predictions. The results show that, when a short-time horizon is considered, persistent predictions allow to provide forecasts with a sufficient accuracy, whereas, when longer horizon time are considered, significantly higher errors are calculated when persistent prediction techniques are adopted. Independently of the uncertainties considered for weather forecasts, the improved control logics demonstrated a potential for energy savings and improvements in indoor temperature stability when compared with a reference case of variable speed compressor with PID controller. / EffSys Expand P18: Smart Cotnrol Strategies for Heat Pump Systems

The urgent need to combat climate change is increasingly being recognized. The Paris Agreement, which aims to limit global warming, requires carbon neutrality to be achieved by the mid-21st century. Further, the energy crisis in Europe that started in 2021 highlights the importance of energy security. Universities play a crucial role in promoting the transition to neutrality. This study aims to increase universities' electricity independence to further facilitate their transition to carbon neutrality. To this end, a multi-criteria decision analysis (MCDA) method was adopted to select scenarios for increasing a campus building complex's electricity independence, considering various stakeholders' interests together with the scenarios' performances on technical, environmental, economic, and social criteria. The findings show that photovoltaic technology, despite its perceived environmental benefits, performs poorly in reducing carbon emissions when considering lifecycle emissions, particularly in countries with low-carbon electricity like Sweden. Conversely, energy conservation through behavioral changes emerges as the optimal scenario for Campus Gotland due to its economic and environmental advantages. These results challenge the common reliance on energy production technology for carbon neutrality, highlighting the greater effectiveness of demand-side measures. This work suggests that universities need a more human-centric approach to transitioning to carbon neutrality. In a broader context, this study provides universities with insights to make informed decisions to achieve carbon neutrality, emphasizing the need to consider all stakeholders. By offering a comprehensive assessment and analysis of various scenarios, this work enhances the understanding of best practices for universities aiming to lead in the global effort against climate change.