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This work (and the companion paper, Part II) presents new experimental data for the combustion of n-C3–C6 alcohols (n-propanol, n-butanol, n-pentanol, n-hexanol) and a lumped kinetic model to describe their pyrolysis and oxidation. The kinetic subsets for alcohol pyrolysis and oxidation from the CRECK kinetic model have been systematically updated to describe the pyrolysis and high- and low-temperature oxidation of this series of fuels. Using the reaction class approach, the reference kinetic parameters have been determined based on experimental, theoretical, and kinetic modeling studies previously reported in the literature, providing a consistent set of rate rules that allow easy extension and good predictive capability. The modeling approach is based on the assumption of an alkane-like and alcohol-specific moiety for the alcohol fuel molecules. A thorough review and discussion of the information available in the literature supports the selection of the kinetic parameters that are then applied to the n-C3–C6 alcohol series and extended for further proof to describe n-octanol oxidation. Because of space limitations, the large amount of information, and the comprehensive character of this study, the manuscript has been divided into two parts. Part I describes the kinetic model as well as the lumping techniques and provides a synoptic synthesis of its wide range validation made possible also by newly obtained experimental data. These include speciation measurements performed in a jet-stirred reactor (p = 107 kPa, T = 550–1100 K, φ = 0.5, 1.0, 2.0) for n-butanol, n-pentanol, and n-hexanol and ignition delay times of ethanol, n-propanol, n-butanol, n-pentanol/air mixtures measured in a rapid compression machine at φ = 1.0, p = 10 and 30 bar, and T = 704–935 K. These data are presented and discussed in detail in Part II, together with detailed comparisons with model predictions and a deep kinetic discussion. This work provides new experimental targets that are useful for kinetic model development and validation (Part II), as well as an extensively validated kinetic model (Part I), which also contains subsets of other reference components for real fuels, thus allowing the assessment of combustion properties of new sustainable fuels and fuel mixtures.

Abstract The use of electric bus fleets has become a topical issue in recent years. Several companies and municipalities, either voluntarily or to comply with legal requirements, will transition to greener bus fleets in the next decades. Such transitions are often established by fleet electrification targets, which dictate the number of electric buses that should be in the fleet by a given time period. In this paper we introduce a comprehensive optimization-based decision making tool to support such transitions. More precisely, we present a fleet replacement problem which allows organizations to determine bus replacement plans that will meet their fleet electrification targets in a cost-effective way, namely considering purchase costs, salvage revenues, operating costs, charging infrastructure investments, and demand charges. We account for several charging infrastructure options, such as slow and fast plug-in stations, overhead pantograph chargers, and inductive (wireless) chargers. We refer to this problem as the electric bus fleet transition problem, and we model it as an integer linear program. We apply our model to conduct computational experiments based on several scenarios. We use real data provided by a public transit agency in order to draw insights into optimal transition plans.

Abstract Extracting features for early failure detection in rotating machinery of nuclear power plants (NPPs) is difficult because in the early stages of failure the impact on the vibration signals is weak. To improve early fault detection in rotating machinery, a fault feature extraction method based on the combination of parameter-adaptive Variational Mode Decomposition (VMD) and Teager energy operator (TEO) is proposed in this paper. Firstly, we introduce the maximum weighted kurtosis index (WKI) as the objective function, and the Artificial Bee Colony (ABC) is used to optimize the VMD parameters. Then, the optimized VMD is used to decompose the vibration signal into multiple intrinsic mode functions (IMFs). Finally, TEO is used to demodulate the sensitive mode with the maximum WKI and identify the fault frequencies. Simulation and experiment show that the early fault features in vibration signals can be effectively extracted by the proposed method, and the comparisons with other three methods highlight the advantages of the proposed method.

New energy generation and storage systems are continuously being developed due to climate change, resource scarcity, and environmental laws. Some systems are incremental innovations of existing systems while others are radical innovations. Radical innovation systems are risky investments due to their relevant technical and economic uncertainties. Prototyping can hedge these risks by spending a fraction of the cost of a full-scale system and in return receiving economic and technical information regarding the system. In economic terms, prototyping is an option to hedge risk coming at a cost that needs to be properly assessed. Real options analysis is the project appraisal approach for these assessments. This paper aims to introduce and test an algorithm based on real options analysis to quantitatively assess the “option to prototype” in the energy sector. First, the interrelated research areas of prototyping, energy systems, and real options analysis are reviewed. Then, a novel algorithm is presented and applied to an innovative Generation Integrated Energy Storage system: Wind-driven Thermal Pumping to demonstrate the effectiveness of option to prototype and the main parameters influencing this decision. Results show that the cost of the prototype and the market size (number of identical systems to build) are key parameters.

This brief analyzes the linear profiles presented by certain classes of bifurcation indices with respect to the variation of the loading parameter in power systems. The bifurcation indices discussed here are used in practice to predict proximity to saddle-node and some types of limit-induced bifurcations, given their special profiles. Thus, the linearity of these indices is studied with the help of a simple generic test system. Local analyses and observations are also presented and discussed for realistic power-system models.

Sustainability is characterized by a growing trend in the number of papers published in the last years, for an increasing impact factor and because today a large number of experts and researchers dealing with this issue have published in this journal [...]

Various dynamic reliability methods have been developed during the last several decades, such as Monte Carlo (MC) simulation, Dynamic Event Tree (DET) and Monte Carlo Dynamic Event Tree (MCDET) methods, to name a few. This paper benchmarks these particular methods by applying them to a classic level control dynamic system and to a realistic Emergency and Standby Power System (ESPS). The analysis is done with respect to different component aging dynamics and transition rate state dependences. Efficiency and computational cost are evaluated. The results show that: (1) the dynamic methods indeed are capable of capturing the effects of the dynamics in the process; (2) DET can model the possible accidental sequences, but at a large computational cost; (3) accurate modelling of sequences with low probabilities of occurrence can be achieved by the MCDET method.