• Energy Research

Abstract In recent years, distributed energy systems (DESs) have been recognized as a promising option for sustainable development of future energy systems, and their application has increased rapidly with supportive policies and financial incentives. With growing concerns on global warming and depletion of fossil fuels, design optimization of DESs through economic assessments for short-run benefits only is not sufficient, while application of exergy principles can improve the efficiency in energy resource use for long-run sustainability of energy supply. The innovation of this paper is to investigate exergy in DES design to attain rational use of energy resources including renewables by considering energy qualities of supply and demand. By using low-temperature sources for low-quality thermal demand, the waste of high-quality energy can be reduced, and the overall exergy efficiency can be increased. The goal of the design optimization problem is to determine types, numbers and sizes of energy devices in DESs to reduce the total annual cost and increase the overall exergy efficiency. Based on a pre-established DES superstructure with multiple energy devices such as combined heat and power and PV, a multi-objective linear problem is formulated. In modeling of energy devices, the novelty is that the entire available size ranges and the variation of their efficiencies, capital and operation and maintenance costs with sizes are considered. The operation of energy devices is modeled based on previous work on DES operation optimization. By minimizing a weighted sum of the total annual cost and primary exergy input, the problem is solved by branch-and-cut. Numerical results show that the Pareto frontier provides good balancing solutions for planners based on economic and sustainability priorities. The total annual cost and primary exergy input of DESs with optimized configurations are reduced by 21–36% as compared with conventional energy supply systems, where grid power is used for the electricity demand, and gas-fired boilers and electric chillers fed by grid power for thermal demand. A sensitivity analysis is also carried out to analyze the influence of energy prices and energy demand variation on the optimized DES configurations.

Abstract Thermal bridges are weak areas of the building envelope, determining heat flows higher than those characterizing the common dispersing surfaces (i.e., walls without discontinuities). This phenomenon induces uncontrolled thermal losses and hygiene problems, connected to the possible vapor condensation and mold growth. Presently, the numerical codes for the energy audits, as, for instance, EnergyPlus, carry out zero-dimensional (indoor air) and one-dimensional (conduction heat transfer) analyses, approximately estimating the thermal bridge effects on the seasonal heating demand of buildings. In this paper, results obtained by means of the simplified 1-D models are compared to those obtained by more sophisticated models 2-D or 3-D, in order to point out differences in terms of equivalent conductivity and thermal transmittance. Then, dynamic simulations compare the outcomes in terms of seasonal energy consumption. A typical office building has been considered, analyzing – according to three different approaches – the thermal bridge represented by the roof structure. The outcomes, with reference to several Italian climates, show that a proper modelling is necessary. In particular, an over estimation of the heat losses, determined by an approximate evaluation, induces higher cost of refurbishing, higher cooling energy requests in summer, minor thermal comfort in naturally ventilated buildings.

With the energy transition underway, the wider penetration of multi-energy hubs (MEHs) is inevitable as they allow for the integration of multiple energy carriers at the local level and especially at the users' side by enhancing flexibility of energy supply and renewabIes penetration. Thus, addressing their design properly is imperative. While numerous energy modeling software and tools are extensively discussed in the literature, they primarily focus on a single energy carrier, mainly dedicated to the electrical network. In this study, an optimization planning tool capable of analyzing the synergies of various energy carriers is presented. The tool aims to determine the optimal configuration of MEHs with sizes of the chosen technologies based on the modeler's preferences. The tool offers flexibility in modelling a wide range of technologies as potential options for the optimal configuration, and in considering different types of objectives as economic and environmental ones that can be assessed through a multi-objective approach. It is formulated through mixed-integer linear programming in a modular manner, facilitating the easy implementation of new emerging technologies, by enhancing scalability and applicability in real context. To prove the effectiveness of the optimization tool, it is applied for the design of a MEH for a residential building cluster located in Torino (Italy). Different scenarios are analyzed to determine the impact of high levels of renewabIes penetration on the design of the MEH while guaranteeing the economic sustainability of the solution.

Abstract Environmental problems have offered new challenges to the energy production sector, starting from the need of increasing the efficiency of thermodynamic systems to preserve fuel consumption. Accordingly, multi-energy generation systems are among the most efficient generation systems, and Heat Recovery Steam Generators (HRSGs) represent key components of such systems. In this regard, this paper shows a comprehensive approach to optimize a HRSG by using a multi-objective Genetic Algorithm (GA). The aim is to highlight how to determine the optimal values of geometrical and thermodynamic design variables according to two objective functions: the global costs to be minimized and the steam turbine output power to be maximized. Starting from a reference HRSG design, thermodynamic modeling and simulations as well as the optimization procedure are performed in MATLAB®. A validation is carried out to show the accuracy of the modeling approach. Latin Hypercube Sampling is applied to create a uniform sample to select the design variables based on a global sensitivity analysis, producing a significant reduction of computational efforts. Then, the GA optimization is performed to achieve the Pareto front, collecting the best trade-off design solutions. Economic savings up to 20% are achieved limiting the HRSG size.

Abstract Predicting heat transfer is a primary task in the design of open-cell foams. When a Local Thermal Non Equilibrium (LTNE) model is employed, convection heat transfer between the solid and fluid phases is considered, and a volumetric heat transfer coefficient needs to be defined. Some recent studies pointed out that the effects of developing convection heat transfer between the fluid and the solid in a foam are to be taken into account. The developing thermal flow of air through an open-cell foam, with a uniform heat flux solid/fluid boundary condition, is investigated numerically in this paper. The geometry is modeled with reference to Kelvin's tetrakaidecahedron foam model. A correlation among the porosity, the cell diameter and the ratio of heat transfer surface to volume is derived. Three regions are identified along the flow direction: an impingement region, a thermally developing region and a thermally developed region. Dimensional and dimensionless convection heat transfer coefficients have been predicted numerically as a function of the axial coordinate of the foam, for different values of the Reynolds number and the porosity. A correlation is presented among the predicted values of the volumetric Nusselt number, the porosity, and the Reynolds number in the thermally developed region, which is in good agreement with experimental data and numerical predictions by other authors. Finally, the analysis of the convection heat transfer through a single foam cell, at a local pore-scale, is presented.

Abstract In this work, a new approach for the design of air conditioning systems with cold thermal energy storage is described and tested, considering the case study represented by a vapor-compression chiller, coupled with a chilled water storage system, producing cooling for a small multi-apartment building situated in Italy. In the present approach, at the aim of limiting shut-downs and start-ups of the chiller, which involve inefficiencies during transients, and can lead to a drastic reduction of the equipment lifetime, the nominal power of the chiller, and the amount of cooling to be stored are first estimated in a pre-design phase. Successively, the outputs of the pre-design are used to fix the size of the cold storage tank, and to set up the numerical simulation of the cold thermal energy storage system. Finally, the results of the numerical simulation of the cold storage system are used to evaluate the effective size of the chiller. Both the pre-design and the numerical simulations of the cold storage systems have been done by means of home-made numerical tool realized with Simulink. In the paper, the specifications relative to the operational strategy are explored, and the analytical models used for the numerical simulation of the cold storage system relative to the Italian case study are reported in detail. Finally, the results of the pre-design, and of the cold storage system simulations relative to the case study are presented and discussed. The results relative to the Italian case study demonstrates the effectiveness of the present approach in limiting the number of shut-downs and start-ups of the chiller. The present approach can represent a useful tool for the economic optimization of the design of air conditioning systems.

Abstract This work focuses on the experimental validation of a numerical tool realized to simulate a commercial hot water storage tank. The tool implements unsteady 1D models to simulate the temporal evolution of the temperature field inside the hot water storage tank, and the one relative to the heat transfer fluid flowing through the immersed coil heat exchanger. It has been implemented by means of the Simulink tool of Matlab. The first part of the paper is dedicated to the description of the indoor experimental facility used to realize the experimental test. Successively, the analytical models, and the numerical schemes and algorithms used to perform the numerical simulations are described. Finally, the results of the experimental validation of the tool, accomplished by comparing the experimental temperature profiles inside the tank, and the measured temperatures at the coil heat exchanger exit section over the entire experimental test duration, with the numerical results obtained from simulations performed using different correlations for the evaluation of the heat transfer rate between the tank water and the heat transfer fluid through the coil, are reported and discussed.

The growing need for renewable energy sources has highlighted the importance of technologies that can bridge the generation-demand gap in the energy system. Thermal Energy Storage (TES) can help to smooth out peaks in energy demand, thereby reducing waste resulting from excess capacity during offpeak periods. Due to their widespread use, significant effort has been dedicated to optimizing the control logic of TES components to maximize the harvested-to-stored energy ratio. The aim of this study is to compare MIX number and dimensionless exergy, two parameters commonly used to identify the storage’s ability to generate and maintain optimal temperature stratification. The investigation is conducted by comparing the parameter response to the thermo-fluid dynamic variations inside the store under several inlet temperatures and flow rates, using a two-dimensional CFD model validated on experimental data collected from an operating commercial stratified tank. The sensitivity of the two performance indicators in detecting stratification losses that are due to different charging conditions is compared, to better understand the applicability of the latter as control parameters during operational phases. Results show that the derivatives of such indicators are less sensible to the tank starting conditions and can be more robust indicators during the charging phase.