This paper presents a life cycle assessment (LCA) study that examines a number of scenarios that complement the primary use phase of electric vehicle (EV) batteries with a secondary application in smart buildings in Spain, as a means of extending their useful life under less demanding conditions, when they no longer meet the requirements for automotive purposes. Specifically, it considers a lithium iron phosphate (LFP) battery to analyze four second life application scenarios by combining the following cases: (i) either reuse of the EV battery or manufacturing of a new battery as energy storage unit in the building; and (ii) either use of the Spanish electricity mix or energy supply by solar photovoltaic (PV) panels. Based on the Eco-indicator 99 and IPCC 2007 GWP 20a methods, the evaluation of the scenario results shows that there is significant environmental benefit from reusing the existing EV battery in the secondary application instead of manufacturing a new battery to be used for the same purpose and time frame. Moreover, the findings of this work exemplify the dependence of the results on the energy source in the smart building application, and thus highlight the importance of PVs on the reduction of the environmental impact.

Buildings’ heating and cooling systems account for an important part of total energy consumption. The EU’s directives and engagements motivate building owners and relevant stakeholders in the energy and construction sectors towards net zero energy buildings by maximizing the use of renewable energy sources, ICT, and automation systems. However, the high costs of investment for the renovation of buildings, in situ use of renewable energy production, and installation of expensive ICT infrastructure and automation systems in small–medium range buildings are the main obstacles for the wide adoption of EU building directives in small- and medium-range buildings. On the other hand, the concept of sharing computational and data storage resources among various buildings can be an alternative approach to achieving smart buildings and smart cities where the main control power resides on a server. Unlike other studies that focus on the implementation of AI techniques in a building or separated buildings with local processing resources and data storage, in this work a corporate server was employed to control the heating systems in three building typologies and to examine the potential benefits of controlling existing buildings in a unified energy-savings platform. The key finding of this work is that the AI algorithms incorporated into the proposed system achieved significant energy savings in the order of 20–40% regardless of building typology, building functionality, and type of heating system, despite the COVID-19 measures for frequent ventilation of the buildings, even in cases with older-type heating systems.

This paper describes the evolution of the thermal network and its applications for making simplified thermal models of buildings by means of thermal resistances (R) and capacitances (C). In the literature, there are several modelling schemes for buildings. Here, we investigate the advantages, disadvantages, and improvements of thermal networks. The thermal network method has been used in different studies for calculating indoor air temperature and heating load, estimating model parameters, and studying building interactions with heating and cooling systems. This review paper conducts an investigation into the application, system identification, and structure of thermal networks compared to other tools. Within the framework of the thermal network method, we conclude with some new proposals for research in this field to expand the idea of the thermal network to other engineering and energy management fields.

High energy demand in corporate and/or public buildings is nowadays one of the main reasons of excessive energy consumption. At the same time, electric vehicles (EVs) have become very popular worldwide being a considerable alternative power source when parked. In this work we propose a scheduling mechanism which optimizes the control of the charging-discharging schedule of an altered but finite number of EVs arriving at a university building for a typical load-day in February aiming at the minimization of the energy demand and the electricity cost of the building. In the aforementioned framework, a parallel operation of a small sized gas turbine generator (GGT) is considered. To this end, a mixed integer linear programing (MILP) model containing binary and continuous variables has been developed to optimize the control process and minimize energy cost. Results showed that the use of the EVs as an alternative energy source can significantly contribute to the reduction of the building's energy demand leading to important cost decrease. The exploitation of the energy produced by the GGT further contributed to the minimization of the total energy consumption of the building and the total electricity cost.

Rapidly increasing global energy demand has raised concerns about the exhaustion of energy resources and the consequent heavy environmental impact. Improving energy efficiency in cities comprises an initial measure for addressing these phenomena. Within the current context of globalization, EU initiatives and policy targets have been proposed in order to revise urban development strategies and motivate its member states (MSes) toward “zero-energy objectives”. Providing a methodological approach with a simulation district analysis, the present article summarizes how this challenge was analyzed in an existing district in Belgium. This study contributes to the scientific discussion by analyzing the applicability of a holistic approach to zero-energy objectives on a larger scale.