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Abstract The OECD/NEA Sandia Fuel Project provided unique thermal-hydraulic experimental data associated with Spent Fuel Pool (SFP) complete drain down. The study conducted at Sandia National Laboratories (SNL) was successfully completed (July 2009 to February 2013). The accident conditions of interest for the SFP were simulated in a full scale prototypic fashion (electrically heated, prototypic assemblies in a prototypic SFP rack) so that the experimental results closely represent actual fuel assembly responses. A major impetus for this work was to facilitate severe accident code validation and to reduce modeling uncertainties within the codes. Phase I focused on axial heating and burn propagation in a single PWR 17 × 17 assembly (i.e. “hot neighbors” configuration). Phase II addressed axial and radial heating and zirconium fire propagation including effects of fuel rod ballooning in a 1 × 4 assembly configuration (i.e. single, hot center assembly and four, “cooler neighbors”). This paper summarizes the comparative analysis regarding the final destructive ignition test of the phase I of the project. The objective of the benchmark is to evaluate and compare the predictive capabilities of computer codes concerning the ignition testing of PWR fuel assemblies. Nine institutions from eight different countries were involved in the benchmark calculations. The time to ignition and the maximum temperature are adequately captured by the calculations. It is believed that the benchmark constitutes an enlargement of the validation range for the codes to the conditions tested, thus enhancing the code applicability to other fuel assembly designs and configurations. The comparison of lumped parameter and CFD computer codes represents a further valuable achievement.

In the present work, a novel hybrid solar-based smart building energy system is introduced and studied. The system comprises innovative photovoltaic-thermal-cooling (PVTC) panels integrated with hot and cold storages with two-way interaction with electricity, heat, and cooling networks (if any). The proposed system is compared with PV-based systems integrated with battery and heat pump for a case study complex building in Aarhus, Denmark. The comparison is conducted by evaluating the performance and economic indicators and investigating the effect of significant parameters on each scenario via a parametric study. Furthermore, the optimal operating conditions and sizing of the proposed system are determined using the genetic algorithm method considering initial cost and traded energy with local energy networks as the objective functions. The comparison results show that the proposed solution is the most cost-effective scenario with the lowest initial cost of about 457,000 $ and a payback period of 6.6 years. This is mainly due to the simultaneous interaction with electricity/heat/cooling networks as well as the elimination of the battery and the heat pump, which are offered by the proposed scenario. It is shown that, in comparison to PV panels, the PVTC can produce 328.7 MWh and 125.6 MWh extra heat and cooling annually. The scatter distribution of significant parameters shows that the panel area and heat storage capacity are not sensitive parameters, and keeping the cold storage capacity at the lower bound is a techno-economically better option.

Abstract Building-integrated photovoltaic (BIPV) panels are emerging as a useful technology for helping to achieve net-zero energy buildings. At this time, the main drawback with BIPV systems is the cost per kilowatt per hour of electricity generated. Besides cheaper production of photovoltaic panels, increases in their efficiency can be obtained by reducing panel temperatures. This is often achieved by adding a cavity beneath the panels to allow ventilation of the rear of the panel. However, the details of airflow in the cavity and the effect on cooling have not been rigorously researched. Life-time enhancement against degradation is also an effective technique to reduce the cost of electricity generated. Moisture ingress and thermal stresses are among the primary reasons for degradation of BIPVs; these processes are directly affected by air and moisture flow around the panels. The surface temperature thermography and airflow observations performed in this work helps to understand the transport mechanisms above and below the panels. For this purpose, a novel setup was developed consisting of a building model with a mock BIPV panel plus a solar simulator placed inside an atmospheric wind tunnel. Particle image velocimetry (PIV) and infra-red thermography were performed to simultaneously monitor the surface temperature and airflow above and below the panel. The study clearly shows how the accelerated airflow within the cavity increases the heat exchange between the PV and airflow and consequently reduces the PV temperature. It is also shown that the stepped open arrangement of panels is more effective in reducing the temperature comparing to a flat arrangement. This arrangement also has a better resistant against the air and moisture ingress.

Abstract Sustainability is an important and difficult consideration for the stakeholders/decision-makers when planning a biofuel supply network. In this paper, a Mixed-Integer Non-linear Programming (MINLP) model was developed with the aim to help the stakeholders/decision-maker to select the most sustainable design. In the proposed model, the emergy sustainability index of the whole biodiesel supply networks in a life cycle perspective is employed as the measure of the sustainability, and multiple feedstocks, multiple transport modes, multiple regions for biodiesel production and multiple distribution centers can be considered. After describing the process and mathematic framework of the model, an illustrative case was studied and demonstrated that the proposed methodology is feasible for finding the most sustainable design and planning of biodiesel supply chains.

The east German energy system is in a process of being completely rebuilt. Unfortunately, the huge investments are not used for implementing a technical and institutional restructuring, which is needed in order to achieve energy efficiency. The energy system will, among others, maintain its inefficient structure with separate production of heat and power. The ongoing changes are limited to improvements of power plant efficiency in combination with a change from a system based on brown coal for both heat and power into a system in which the electricity production is still based on brown coal and heating is produced on oil and natural gas. This rebuilding will bring the CO2-emission down from 20 t/inhabitant in 1989 to 13 t/inhabitant in year 2010, which is still much higher than the EU average on 8 t/inhabitant. This article describes how a restructuring could bring the figure below 7 t/inhabitant. The lack of ability to implement this restructuring of the energy system is, among others, due to an ownership structure, where networks of companies own the entire production and distribution chain from oil and coal to electricity. In this ownership structure, energy restructuring strategies which decrease the consumption of oil and coal will reduce the profits. At the same time the potential regulator, the parliamentary system, is politically and economically interlinked with and dependent upon the established energy companies. Consequently, it is difficult to establish the regulation reforms which are necessary for restructuring of the energy sector. There is still a lot to be gained from a restructuring of the east German energy sector. This restructuring requires institutional reforms, where the public regulation processes become independent of the industry which should be regulated.

Abstract This paper addresses the importance of the probabilistic analysis in determining the wave energy potential to support the design of electrical generators for wave energy conversion. The irregular activity of ocean waves induces variable frequencies and amplitudes of operation for point absorbers electrical generators, which may lead to the construction of inefficient electrical machines. Applying probabilistic models to describe the ocean wave's behavior allows the determination of the values most likely to be sampled for ocean-state parameters. Knowing these values, the most expected ocean wave potential can be determined and a proper device design can be performed. This work also refers to the importance of using the joint probability models instead of the marginal ones. Seven locations at the Portuguese coast are evaluated in order to determine their wave energy resource potential.

The direct-on-line start-up of a synchronous motor results in alternating torques which can excite the lowest torsional natural frequency of compressor trains used in the oil & gas industry. Considering a slip-dependent variation of the rotor parameters, an integrated electrical and mechanical simulation model is developed, providing an accurate estimation of the air-gap torque. The proposed approach is validated by an accurate testing campaign carried out during moto-compressor field test activities.

Abstract From the sustainable perspective, the optimum thickness calculations of the buildings envelope insulation materials published in scientific journals suffer a number of notable shortcomings. The most relevant are the short amortization time periods and the prevalence of economic criterion. The work presented shows that an increase from 20 to 50 years in the amortization time period involves, in some cases, to double the value of the optimum thickness. Moreover, the thicknesses calculated applying energetic or environmental criteria for the optimization give, in some cases, results 10 times higher than the ones obtained using the economic argument. The type of insulation materials (especially their different characteristics at the manufacturing stage) and the calculation conditions (e.g. Degree-Days zone) also affect optimum thicknesses determination.

In the last years, the concept of “smart city” has been the subject of increasing attention in urban planning and governance due to the sustainability challenges and great technological advancements. Although the relevant literature highlights those smart cities can create a fertile environment to drive innovation from a technological, managerial and organizational, and policy point of view how smart cities function, in terms of their value chain and in light of sustainability and circularity is still an open question. Based on these considerations, this work aims to investigate how smart cities deliver value by combining environmental, societal, and financial priorities to re-imagine their core business models and shift the boundaries of urban competition in light of circular economy principles. To reach this goal, the tool Sustainable Business Model Innovation Canvas has been applied in the urban context with the aim to create and leverage an environmental and societal surplus in light of circularity in the smart city framework. Preliminary results shed light on new vistas on the future and new challenges of smart cities particularly relevant for facing the current complexity of the economy, social, and environmental changes.