Throughout time, European policies on climate and energy change have generated several transformations in the building sector. In this endeavour, digital technologies have played an essential role in energy efficiency through process optimisation. However, data integration and exchange between different solutions is still challenging to achieve. With the advancement of Internet of Things (IoT) based solutions, one of the latest innovations, new opportunities are envisioned. IoT solutions have been implemented in smart grids, intelligent buildings, smart cities, and other sectors in recent years. Following the guidelines of ISA/ANSI 95-Enterprise-Control System Integration, the edge computing apps and cloud platform are needed to solve data bottlenecks, data ingestion, data integration aspects, bringing at the same time new knowledge related to user comfort, energy management and accessibility. This research focuses on a case study that shows how the thermal comfort of a building can be controlled and improved through an IoT vertically integrated solution. The deployed solution opens new possibilities for cross-functional integration and data aggregation, an essential step towards energy efficiency.

The importance of mitigating energy intensity in the building sector is widely recognized by most stakeholders, and different strategies are proposed for minimizing fossil fuel dependency. This paper presents a complex study assessing the possibility of integrating an air-source heat pump (ASHP) into the retrofitting process of a typical Romanian residential building. Mathematical simulations were conducted to estimate the energy reduction potential of a complex renewable-energy-based HVAC system. The results showed that a more than 50% increase in energy efficiency could be obtained by using the right insulation materials, and the building’s fossil fuel dependency could be curbed by 75% by integrating the proposed renewable energy systems.

An optimization model that may be applied to analyze building retrofit strategies is presented in this research. The aim of this research paper is to identify the optimal thermal envelope configuration that will assure the minimum energy requirement for heating in the case of a residential building, while also considering price restrictions obtained through a specific market survey. To achieve this, several values for the following parameters are considered: thermal insulation materials’ conductivities and thicknesses, windows’ overall heat transfer coefficients and total solar energy transmittance and doors’ thermal proprieties. Additionally, this paper presents a method used to find the best option from among the available heat pumps that could cover most of the energy requirements for heating and domestic hot water systems, also considering the products’ prices. The proposed method is based on a Non-dominated Sorting Genetic Algorithm II (NSGA-II) model developed in the Pymoo (Multi-Objective Optimization in Python) library. The result shows that the energy requirement for heating can be reduced by up to approximately 75% compared to that obtained in the case of a non-insulated building by using suitable insulation materials and doors and windows with superior thermal proprieties chosen by the NSGA-II.

Heat pumps are increasingly used for low-temperature heating applications. But their operation can create electricity demand peaks during periods of high thermal load. This paper presents a concept and calculation study for integrating phase change materials (PCMs) with air-to-water heat pump (AWHP) systems as a condenser-side thermal buffer for residential buildings. The analyzed retrofit-oriented storage unit is a 200 L tank containing 30% PCM by volume, corresponding to 60 L of paraffin PCM and 140 L of water. The sizing calculation gives 3.08 kWh of PCM thermal storage, 0.81 kWh of sensible storage in the remaining water over the 55–60 °C interval, and almost 3.89 kWh of total short-term thermal reserve for the PCM-plus-water tank. A 200 L water tank over the same 5 °C interval would store approximately 1.16 kWh. At the nominal 14 kW heat pump output, the PCM buffer corresponds to about 13.2 min of operation. At representative part load it corresponds to about 53 min at 25% load and 26 min at 50% load. The PCM sizing model predicts storage capacity, buffer time and possible cycling relevance, but it does not by itself predict a seasonal COP increase. Therefore, annual electricity and economic effects are evaluated only as COP-uplift sensitivity cases, including 0%, 3%, 4%, 5%, 8%, 15% and 28.6%. Given the assumptions in this study, the PCM add-on reaches positive net present value at approximately 11% COP uplift when the initial marginal investment and discounted year 10 replacement cost are considered. Approximately 14.1% is reached if the replacement cost is added upfront as a simplified lifecycle basis. The results indicate that the condenser-side PCM buffer may be technically useful for short-term thermal buffering and possible on-off cycle reduction, but its annual energy and economic benefit requires dynamic simulation or experimental validation. Moreover, peak-demand reduction, demand shifting and renewable electricity utilization are discussed as potential applications of the buffer concept.