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Highlights: [•] The model proposed aims at minimizing local impact of energy systems. [•] The model is meant to minimize the impact starting from system thermodynamics. [•] The formulation combines exergy analysis and quantitative risk analysis. [•] The approach of the model is dual to Thermoeconomics. [ABSTRACT FROM AUTHOR]

Faults and malfunctions occurring in engineering systems may cause additional resources consumptions and economic expenditures, thus their detection and isolation is of great practical significance. The procedure to discover faults is known as diagnosis , and it can be based on different techniques, depending on the purpose of the analysis: to predict the failure time of the component, or to quantify the inefficiencies of the system due to the anomaly. Among the existing approaches adopted to diagnose the energy systems, Thermoeconomic diagnosis provides useful information to detect the anomalies and to quantify its negative impacts. However, this method does not allow to identify possible strategies useful to reduce the inefficiencies caused by anomalies, which could be a crucial need for the system operator. To face this issue, this article proposes a method to perform Thermoeconomic diagnosis of energy systems that enables the analyst to understand the interdependencies between the components, and decomposing the main indicator resulting from Thermoeconomic diagnosis, known as malfunction. The method provides useful information for the system operators to define practical strategies to reduce the negative effects of malfunctions. This approach is also formalized and applied to the CGAM benchmark to highlight the practical achievements of this approach with numerical values. It is found that the proposed approach provides useful insight about the effects of malfunctions, and it may be helpful for system operators to reduce the negative impacts of the anomaly by pinpointing the component with higher contribution in total inefficiency of the system. In this specific case, proper intervention on the pinpointed component mitigated the total inefficiency of the system by almost 40%, and recovered the reference efficiency of the system. [ABSTRACT FROM AUTHOR]

Exergy Life Cycle Assessment (ELCA) is proposed by literature to account for the exergy embodied in products of energy systems. In order to make results of ELCA comparable, supply chains that support the life cycle of the system should be analyzed through a unified model: this is one of the main concerns related to Life Cycle Assessment and Industrial Ecology disciplines. In this paper, Hybrid Input-Output analysis is proposed as the computational structure of ELCA: according to this method, national supply chains are modeled through the Monetary Input Output Tables (MIOTs) of national economies, a constantly updated and freely available data source. Then, the adopted national MIOT is expanded to include the detailed model of the considered energy system, hence defining a Hybrid Input-Output model. The (non-renewable) exergy embodied in electricity production and the Exergy Return on Investment (ExROI) are defined as the appropriate performance indicators based on ELCA. The introduced model is here adopted for the analysis of a Waste-to-Energy (WtE) power plant currently operating in the Italian context. It is found that the primary non-renewable exergy embodied in electricity produced by the analyzed WtE is non-negligible for both the construction (127.1 toe) and the operation phases (11.6 toe/y). Nonetheless, the plant is able to produce a net amount of electricity that pays back such primary non-renewable resources requirements about a hundred times. Finally, the joint application of Exergy Analysis and ELCA lead to improve the overall thermodynamic performances of the WtE system, increasing its exergy efficiency by 1%, and reducing the non-renewable exergy embodied in electricity production by 7938 toe. [ABSTRACT FROM AUTHOR]

Due to the rapid increase of the World’s primary energy demand of the last decades, low-temperature processes for the purification of natural gas streams with high carbon dioxide content has gained interest, since they allow to make profitable exploitation of low-quality gas reserves. Low temperature purification processes allow the direct production of a methane stream at high purity and at low-temperature, suitable conditions for the direct synergistic integration with natural gas cryogenic liquefaction processes, while CO 2 is obtained in liquid phase and under pressure. In this way, it can be pumped for transportation, avoiding significant compression costs as for classical CO 2 capture units (where carbon dioxide is discharged in gas phase and at atmospheric pressure), and further uses such as Enhanced Oil Recovery (EOR) or underground storage. In this paper, the three most common natural gas low-temperature purification techniques have been modelled and their performances have been evaluated through energy and exergy analyses. Specifically, the dual pressure low-temperature distillation process, the anti-sublimation process and a hybrid configuration have been considered. It is found that the dual pressure low-temperature distillation scheme reach the highest thermodynamic performances, resulting in the best values of exergy efficiency and equivalent methane requirements with respect to the other configurations. This is mainly due to the distributed temperature profile along a distillation column, resulting in a less irreversible heat exchanging process. [ABSTRACT FROM AUTHOR]

This paper proposes an exergy-based well-to-wheels analysis to compare different passenger vehicles, based on three key indicators: petroleum energy use, CO 2 emissions, and economic cost. A set of fuel pathways, including petroleum-based fuels, compressed natural gas, biofuels, and electricity are considered in five representative national energy mixes, namely Brazil, China, France, Italy, and the United States of America. Results show no fundamental difference in the fossil fuel pathways among the five scenarios considered. Compressed natural gas vehicles and electric vehicles can completely displace oil consumption in the personal transportation sector. Compressed natural gas vehicles also reduce CO 2 emissions by over 20% compared to gasoline vehicles. Emissions from electric vehicles greatly vary depending on the electricity mix. In low-carbon electricity mixes electric vehicles reach almost-zero CO 2 emissions, while the use of biofuels leads to the lowest CO 2 emissions in carbon-intensive electricity generation mixes, where vehicles running on E85 could reduce CO 2 emission by over 50% compared to gasoline vehicles. Hybrid electric vehicles show the lowest overall economic cost, due to improved efficiency and low cost of petroleum-based fuels. Vehicles running on electricity are characterized by significantly higher capital cost and lower operating costs. Thus, different electricity generation costs impact minimally the overall cost. These results can be used to inform decision-makers regarding the multi-dimensional impact of passenger vehicles, including environmental impact, economic cost, and depletion of primary energy resources, with particular focus on petroleum. [ABSTRACT FROM AUTHOR]