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Abstract The methodology, the site and the dataset as well as the emissions scenario considered in the weather file definition influence the numerical evaluation of efficiency measures resilience. With a complete statistical and critical approach, the paper analyzes the importance of these aspects by means of a residential case study simulated in Benevento, a city of south Italy. Using data monitored from 2015 to 2020, a current weather file is built with different methodologies. The comparison indicates that there is not repeatability of the year chosen as a reference for the various months and thus the resolution of the building energy balance could bring different results. Some future climate projections are also generated on medium (2050 s) and long (2080 s) term considering different emission scenarios. With long term projection, the heating degree days are reduced also of − 21% meanwhile the cooling degree days are more than double compared with the current condition. This suggests a remarked transition towards a dominant cooling climate for Benevento. Moreover, when the climate change is considered, the insulation intervention and the installation of double glazed low emissive window is not resilient because the heating energy need decreases also of −56%, but the cooling energy need increases of + 62% (2080 s). If the efficiency measures include also the cool roof and the external shadings, the cooling demand could be reduced until –33% in some scenarios (e.g. RCP 4.5-50th percentile) and increased (+31%) in some others (e.g. 2080 s).

Abstract This paper presents a parametric analysis for a medium to large size (290–500 MW th receiver thermal power) central receiver plant considering the present market trends. The analysis is divided in 4 steps: • Size and location analysis: for a medium to large size central receiver power plant, three turbine power and three different locations that are involved in the development of power tower plants, have been analyzed to assess the impact over the design characteristics of the solar field and receiver sub-systems and over the levelized electricity cost. • Technology analysis: as commercial power tower plants in operation today are mainly using steam and molten nitrate salts, the present analysis compares the two main technologies, without thermal energy storage to evaluate both under similar design conditions. • Storage analysis: thermal energy storage increases the value of electricity produced and the plant capacity factor for both technologies (steam and molten nitrate salts). For this reason, the analysis shows for each optimized solar field and receiver thermal power, the optimum combination of turbine power and thermal energy storage that minimizes the levelized electricity cost, for both technologies. • Component’s cost analysis: market trends are focused on the specific cost reduction by means of larger plant size and through an improved economy of scale. As a result, and based on baseline cost parameters widely accepted in solar industry, an analysis over the specific costs of major components on the electricity cost has been carried out, to lead where the research and development efforts should be made.

Abstract Wind power technology is one of the cleanest electricity generation technologies that are expected to have a substantial share in the future electricity mix. Nonetheless, the expected increase in the market share of wind technology has led to an increasing concern of the availability, production capacity and geographical concentration of the metals required for the technology, especially the rear earth elements (REE) neodymium (Nd) and the far less abundant dysprosium (Dy), and the impacts associated with their production. Moreover, Nd and Dy are coproduced with other rare earth metals mainly from iron, titanium, zirconium, and thorium deposits. Consequently, an increase in the demand for Nd and Dy in wind power technology and in their traditional applications may lead to an increase in the production of the host metals and other companion REE, with possible implications on their supply and demand. In this regard, we have used a dynamic material flow and stock model to study the impacts of the increasing demand for Nd and Dy on the supply and demand of the host metals and other companion REE. In one scenario, when the supply of Dy is covered by all current and expected producing deposits, the increase in the demand for Dy leads to an oversupply of 255 Gg of total REE and an oversupply of the coproduced REE Nd, La, Ce and Y. In the second and third scenarios, however, when the supply of Dy is covered by critical REE rich deposits or Dy rich deposits, the increase in Dy demand results in an oversupply of Ce and Y only, while the demand for Nd and La exceeds their supply. In the case of an oversupply of REEs, the environmental impacts associated with the REEs production should be allocated to Dy and consequently to the technologies that utilize the metal. The results also show that very large quantities of thorium will be co-produced as a result of the demand for Dy. The thorium would need to be carefully disposed of, or significant thorium applications would need to be found.

Abstract This paper presents a novel multi-time-stage input–output-based modeling framework for simulating the dynamics of bioenergy supply chains. One of the key assumptions used in the model is that the production level at the next time-stage of each segment of the energy supply chain adjusts to the output surplus or deficit relative to targets at the current time period. Furthermore, unlike conventional input–output models, the technology matrix in this approach need not be square, and thus can include coefficients denoting flows of environmental goods, such as natural resources or pollutants. Introducing a feedback control term enables the system to regulate the dynamics, thus extending the model further. This is an important feature since the uncontrolled dynamic model exhibits oscillatory or unstable behavior under some conditions; in principle, the control term allows such undesirable characteristics to be suppressed. Numerical simulations of a simple, two-sector case study are given to illustrate dynamic behavior under different scenarios. Although the case study uses only a hypothetical system, preliminary comparisons are made between the simulation results and some broad trends seen in real bioenergy systems. Finally, some of the main policy implications of the model are discussed based on the general dynamic characteristics seen in the case study. In particular, insights from control theory can be used to develop policy interventions to impart desirable dynamic characteristics to nascent or emerging biofuel supply chains. These interventions can be used to guide the growth of bioenergy supplies along final demand trajectories with minimal fluctuation and no instability.

Abstract The legislation of various European countries imposes limits on the demand for building heating and cooling in order to reduce the primary energy consumptions. Moreover, the legislation prescribes that a fraction of the demand for building cooling, heating and power must be met through renewable energy sources. Among renewable energy systems, wind power, solar photovoltaic, solar thermal energy, solar cooling and heat pumps (though only “partially” renewable) have to be mentioned. In this framework combined heat and power (CHP) systems can provide a further solution to reduce the primary energy consumption. Due to the availability of different technologies, a key factor is the choice of the allocation strategy which allows the division of the energy demands among the various technologies in order to minimize the primary energy consumption. Since the cost of the technologies and the actual tariff and incentive scenarios depend on the specific country and may lead to not optimal allocation strategies in terms of primary energy consumption, these economic parameters are not taken into consideration in the analysis. Therefore, the obtained solutions represent a target which the policies should aim to achieve. This paper aims to develop and apply a methodology for the optimal allocation of the demand among CHP and renewable energy systems, with the aim of minimizing the primary energy consumption, by accounting for legislative constraints. The methodology is then applied to different climatic scenarios to evaluate the effects of a variation of the demand and technology characteristics on the allocation of the loads. Moreover, an analysis on the combined effects is presented. Finally, some guidelines are obtained.

Abstract 3D printing technologies are being called on to revolutionize the manufacturing industry of the energy sector, especially when involving functional materials and complete devices. These additive manufacturing technologies show competitive advantages over conventional processes, however only a few studies have assessed their environmental implications. In this work, the environmental performance of a Solid Oxide Fuel Cell stack produced using a novel 3D printing approach is conducted for the first time using Life Cycle Assessment. In addition, a comparative study with conventional manufacturing methods is carried out. The results reveal that the production of the 3D printing materials has the highest environmental impact (between 50% and 98%) in half of the categories studied. In contrast, the end-of-life stage represents less than 1% of the total impact. End-of-life scenarios are also presented and discussed, indicating that a recycling rate of 70% for Nickel and YSZ materials performs better than the defined landfill and incineration disposal scenarios. Furthermore, 3D printing shows the best overall environmental performance compared to other conventional methods. The main improvement is seen in the material production stage, where a savings ranging from 37% to 97% (depending on the category analysed) is observed. This is mainly due to the use of a ceramic material for the interconnects instead of Chromium-based alloys used in a more conventional approach. Finally, it was observed that the energy required for 3D printing in the manufacturing stage is a sensible parameter to the environmental performance of the SOFC 3D printing technology.

Polygeneration systems with thermal energy storage represent promising solutions to achieve energy saving and emissions reduction in the civil sector. The definition of customer-oriented design and operation strategies represents a most challenging task, in order to maximize the profitability and make the investment attractive. A large potential is often recognized for the installation of centralized plants serving a cluster of buildings located over a small area; in such cases the design problem becomes extremely complex and the analyst needs reliable instruments to identify the optimal solution. This paper in two parts presents a scientific tool for the optimization of design and operation for complex polygeneration plants serving a number of buildings with heat, cooling and electricity. The method is flexible with respect to boundary conditions as concerns the power exchange with the public grid, the tariff structure and the normative constraints. In Part I of the paper the method is described, focusing the attention on the most conceptual aspects. The Mixed Integer Linear Programming algorithm is also presented and error analyses are performed for each of the figures adopted, in order to assess the robustness of the method. In Part II of this paper the tool will be extensively applied to some explicative case studies, in order to better clarify its potential in supporting energy analysts and decision makers.

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.