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This research presents a 100% renewable energy (RE) scenario by 2050 with a high share of electric vehicles on the grid (V2G) developed in Ecuador with the support of the EnergyPLAN analysis tool. Hour-by-hour data iterations were performed to determine solutions among various features, including energy storage, V2G connections that spanned the distribution system, and long-term evaluation. The high participation in V2G connections keeps the electrical system available; meanwhile, the high proportions of variable renewable energy are the pillar of the joint electrical system. The layout of the sustainable mobility scenario and the high V2G participation maintain the balance of the electrical system during most of the day, simplifying the storage equipment requirements. Consequently, the influence of V2G systems on storage is a significant result that must be considered in the energy transition that Ecuador is developing in the long term. The stored electricity will not only serve as storage for future grid use. Additionally, the V2G batteries serve as a buffer between generation from diversified renewable sources and the end-use stage.

This paper explores the advantages of using relative free energy instead of exergy to build a mathematical theory of thermodynamic costs to diagnose malfunctions in thermal systems. This theory is based on the definition of a linearized characteristic equation that represents the physical behavior of each component. The physical structure of the system described by its energy interrelationships is called “primal”, and its derivatives are the costs and consumptions. The obtained costing structure is the mathematical “dual” of its primal. The theory explains why the F and P cost assessment rules and any other suggestion may (or may not be) rational under a given disaggregation scheme. A result of the theory is a new thermodynamic function, called the relative free energy, and a new parameter called deterioration temperature due to a component’s deterioration cause, characterized by a h-s thermodynamic trajectory describing the effects on the exiting stream. The relative free energy function allows for an exact relationship between the amount of used resources and the increase in entropy generation caused by the deterioration path of the component. This function allows the obtaining of, for the first time, an appropriate characteristic equation for a turbine and a new definition of efficiency that does not depend on the environment temperature but on its deterioration temperature. Also, costing with relative free energy instead of exergy may open a new path for more precise and straightforward assessments of component deteriorations.

This paper presents an economic assessment of three drying systems (DS) with different configurations: diesel-powered (DDS), grid-powered (GDS), and photovoltaic-powered (PVDS). The third configuration, PVDS, presents important technological innovations regarding the electric configuration (stand-alone PV, without batteries or grid support) and the heat pump technology used (optimized for drying the recirculated air, which permits a reduction in the electricity consumption by more than 45% if compared to a diesel air-heater or an electric resistance). The profitability of the investment required for the installation of the three systems is proven by calculating the profitability index (PI), the internal rate of return (IRR), the payback period (PBP), and the levelized cost of energy (LCOE). All the indicators show good profitabilities for the three technologies (the PI values range from 6.78 to 10.11, the IRR values range from 24% to 37%, and the PBPs are between 3 and 4 years), but the PVDS clearly offers important economic advantages: its PI and IRR are more than 40% higher, the PBP is 25% shorter, and the LCOE is between 40 and 47% lower than for the two other systems. The results of this analysis correspond to a particular base case but are obviously sensitive to geopolitical and economic changes: the ultimate strength of the PVDS configuration is its resilience against a possible rise in electricity and diesel prices, reducing the uncertainty for investors and policymakers.

Variable refrigerant flow (VRF) systems are one possible tool to meet the objective that all new buildings must be nearly zero-energy buildings by 31 December 2020. Building Information Modelling (BIM) is a methodology that centralizes building construction project information in a digital model promoting collaboration between all its agents. The objectives of this work were to develop a more precise model of the VRF system than the one available in EnergyPlus version 8.9 (US Department of Energy) and to study the operation of this system in an office building under different climates by implementing the building energy simulation in an Open BIM workflow. The percentage deviation between the estimation of the VRF energy consumption with the standard and the new model was 6.91% and 1.59% for cooling and heating respectively in the case of Barcelona and 3.27% and 0.97% respectively in the case of Madrid. The energy performance class of the analysed building was A for each climatic zone. The primary energy consumption of the office building equipped with the VRF system was of 65.8 kWh/(m2·y) for the Mediterranean climate of Barcelona and 72.4 kWh/(m2·y) for the Continental climate of Madrid.

This work addresses the problem of energy consumption time series forecasting. In our approach, a set of time series containing energy consumption data is used to train a single, parameterised prediction model that can be used to predict future values for all the input time series. As a result, the proposed method is able to learn the common behaviour of all time series in the set (i.e., a fingerprint) and use this knowledge to perform the prediction task, and to explain this common behaviour as an algebraic formula. To that end, we use symbolic regression methods trained with both single- and multi-objective algorithms. Experimental results validate this approach to learn and model shared properties of different time series, which can then be used to obtain a generalised regression model encapsulating the global behaviour of different energy consumption time series.

In this study, the results of simulations generated from different thermodynamic models of Stirling engines are compared, including characterizations of both instantaneous and indicated operative parameters. The aim was to develop a tool to guide the decision-making process regarding the optimization of both the performance and reliability of Stirling engines, such as the 2.9 kW GENOA 03 unit—the focus of this work. The behavior of the engine is characterized using two different approaches: an ideal isothermal model, the simplest of those available, and analysis using the ideal adiabatic model, which is more complex than the first. Some of the results obtained with the referred ideal models deviated considerably from the expected values, particularly in terms of thermal efficiency, so a set of modifications to the ideal adiabatic model are proposed. These modifications, mainly related to both heat transfer and fluid friction phenomena, are intended to overcome the limitations due to the idealization of the engine working cycle, and are expected to generate results closer to the actual behavior of the Stirling engine, despite the increase in the complexity derived from the modelling and simulation processes.

Improving the energy performance of existing buildings is one of the main strategies defined by the European Union to reduce global energy costs. Amongst the actions to be carried out in buildings to achieve this objective is working with passive measures adapted to each type of climate. To assist designers in the process of finding appropriate solutions for each building and location, different tools have been developed and since the implementation of building information modeling (BIM), it has been possible to perform an analysis of a building’s life cycle from an energy perspective and other types of analysis such as a comfort analysis. In the case of Spain, the first BIM environment tool has been implemented that deals with the global analysis of a building’s behavior and serves as an alternative to previous methods characterized by their lack of both flexibility and information offered to designers. This paper evaluates and compares the official Spanish energy performance evaluation tool (Cypetherm) released in 2018 using a case study involving the installation of sunlight control devices as part of a building refurbishment. It is intended to determine how databases and simplifications affect the designer’s decision-making. Additionally, the yielded energy results are complemented by a comfort analysis to explore the impact of these improvements from a users’ wellbeing viewpoint. At the end of the process the yielded results still confirm that the simulation remains far from reality and that simulation tools can indeed influence the decision-making process.