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Abstract Double and added double stage organic Rankine cycle systems are configured to recover exhaust gas waste heat of dual fuel engines. To evaluate the performance of the models proposed here, energy, exergy and economic analyses are performed. Several working fluids are evaluated for recommendation for double and added double stage organic Rankine cycle systems. In the double stage organic Rankine cycle, cycle 1 and cycle 2 are connected in parallel. Working fluids R123, R141b, and R601 are used in cycle 1, and R245fa, R236ea, and R1233zd in cycle 2. In the double stage organic Rankine cycle, the working fluid combinations of R601-R1233zd, R601-R245fa and R123-R245fa show better performance when considering power, heat transfer area and payback period, which are 1760 kW, 2108.9 m2 and 4.21 year, respectively for R601-R245fa. In the added double stage organic Rankine cycle, cycle 1 and cycle 2 are connected in two stages and cycle 1 and cycle 3 in parallel. The net power of the working fluid combinations of R123-R245fa and R123-R1233zd are 1799 kW and 1782 kW, respectively, which are higher than those of the others. Further, for R123-R245fa, the heat transfer area and payback period are 3352 m2 and 6.20 year, respectively, which is better compared to those of other working fluid combinations.

Construction involves the use of significant quantities of raw materials and entails high-energy consumption. For the sake of choosing the most appropriate solution that considers environmental and sustainable concepts, tools such as the integrated value model for sustainable assessment (Modelo Integrado de Valor para una Evaluación Sostenible, MIVES) used in Spain, plays a key role in obtaining the best solution. MIVES is a multi-criteria decision-making method based on the value function concept and the seminars delivered by experts. Such tools, in order to show how they may work, require application to case studies. In this paper, two concrete slabs manufactured with differing reinforcements during the construction of the La Canda Tunnels are compared by means of MIVES. The two concrete slabs were reinforced with a conventional steel-mesh and with polyolefin fibres. This research was focussed on the main aspects affecting the construction. That is to say, the environmental, economic, and social factors were assessed by the method, being of special impact the issues related with maintenance of the structure. The results showed that from the point of view of sustainability, the use of polyolefin fibres provided a significant advantage, mainly due to the lower maintenance required.

The operation of gas generators brings relatively high thermo-mechanical loads on the gas generator structure. The objective of this article is to determine the operating conditions, in terms of mechanical loads at extremely high temperatures in very limited and narrow space, of a multifunctional bulkhead for application on specific kinds of gas generators with back-to-back rotor concept. The paper contains numerical analysis and experimental investigation for determining the loads and behavior of the structure. Numerical analysis indicates that there is significant influence of the Tesla turbine effect on flow parameters. Also, uneven pressure distribution and significant thermal loads are identified. With experimental investigation and subsequent exploitation tests, it was concluded that the presented methodology identifies the operating conditions, truthfully simulates the bulkhead stress state and deformations and that the presented design solution satisfied all demands. Regarding results obtained by these numerical simulations, the innovative design solution for the multifunctional bulkhead was proposed.

The major goal of this research paper is to determine the long-run linkage among variables and the impact of civil aviation, energy productivity (efficiency), economic growth (GDP), on ecological footprint through conducting the multivariate regression method, Phillips‑Ouliaris and Engle‑Granger, Jarque – Bera Normality, and Cusum tests from 1970 to 2020. According to results of multivariate regression method, civil aviation, energy efficiency, and economic growth affect the ecological footprint from 1970 to 2020 in France which is coincide with Phillips‑Ouliaris and Engle‑Granger tests. On the contrary, there is no effect of independent variables on dependent variable (ecological footprint) in Finland which is consistent with Phillips‑Ouliaris and Engle‑Granger tests. In this respect, The long-run relation of the model is verified by the cointegration test of Engle-Granger and Phillips-Ouliaris for France. However, there is no long-run co-integration among variables for Finland from 1970-2020. To sum up, empirical results of France is verified EKC hypothesis. However, EKC hypothesis is not verified for Finland.

The battery power state (SOP) is the basic indicator for the Battery management system (BMS) of the battery energy storage system (BESS) to formulate control strategies. Although there have been many studies on state estimation of lithium-ion batteries (LIBs), aging and temperature variation are seldom considered in peak power prediction during the whole life of the battery. To fill this gap, this paper aims to propose an adaptive peak power prediction method for power lithium-ion batteries considering temperature and aging is proposed. First, the Thevenin equivalent circuit model is used to jointly estimate the state of charge (SOC) and SOP of the lithium-ion power battery, and the variable forgetting factor recursive least squares (VFF-RLS) algorithm and extended Kalman filter (EKF) are utilized to identify the battery parameters online. Then, multiple constraint parameters including current, voltage, and SOC were derived, considering the dependence of the polarization resistance of the battery on the battery current. Finally, the verification experiment was carried out with LiFePO4 battery. The experimental results under FUDS operating conditions show that the maximum SOC estimation error is 1.94%. And the power prediction errors at 20%, 50%, and 70% SOC were 5.0%, 8.1% and 4.5%, respectively. Our further work will focus on the joint estimation of battery state to further improve the accuracy.

Abstract Pollution control strategies currently in use by electric power systems are reviewed and a new minimum emission dispatch (MED) method is developed. This new method minimizes overall emission levels at an increased cost in large-scale power systems while simultaneously accommodating local pollution level requirements, as well as economic constraints.

Comfort temperature and sleep quality involving 20 participants were determined in two cases: Case A (arbitrary, controlled air-conditioner setting) and Case B (adjustment of 3 °C higher than the setting of Case A with cool bed linen). Data of indoor thermal comfort and electricity consumption were collected every night throughout the measurement period. Questionnaires on thermal comfort and sleep quality were distributed twice a night for a duration of three nights for each case; the first night was for respondents’ adaptation and the following two nights were for measurement. The sleep quality of the respondents was objectively measured using a commercially available activity tracker. Results found that most respondents were thermally comfortable in both cases, with 39% lower energy consumption reported for Case B compared to Case A. The thermal conditions of Case B were found to be more tolerable than those of Case A. Most respondents reported to have a calm and satisfied sleep for both cases. Comfort temperature and Sleep Efficiency Index (SEI) were found to be maintained in both cases.

Given the considerable scale of distribution networks in urban and rural areas, as well as the lack of management records, adjustments of switches during the distribution system operation are poorly documented. Such deficiency results in the inaccuracy of models stored in the distribution network automation system, and thus misleads the state estimation. With the emergence of information and communication technology, a large number of the feeder and residential smart meter data are accumulated. Such data can help recognize the operation modes of distribution networks by analyzing the relationships between the on/off states of switches and the voltage correlations among buses. However, the limited quantity and quality of the sampling data restrict the implementation of data-driven recognition. In this paper, a physical-probabilistic-network (PPN) model applied for inferring overall operation mode of distribution networks is proposed. Based on which, a belief propagation-based algorithm is proposed for the inference even under situations when there are only partial bus voltages data available. Meanwhile, the required variable for inference can be reduced from the active trail analysis. Experiment results are used to compare its performance with classic methods and to prove its effectiveness and advantages.