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Abstract This article introduces an effective stochastic operation framework for optimal energy management of the shipboard power systems including large, nonlinear and dynamic loads. The proposed framework divides the ship power system into several agents, which coordinate with each other based on their demands/supplies until. The alternating direction method of multipliers (ADMM) is deployed as the multi-agent framework to solve the reformulated distributed energy management problem in the ship. Two types of turbo-generators are considered in the proposed system model, including single-shaft and twin-shaft models, to increase the part-load efficiency in certain times when facing variable speed operation. The proposed distributed framework is equipped with a recursive mechanism, which helps the ship system for running optimal load scheduling when facing insufficient power generation. In order to model the uncertainty effects associated with the forecast error in the interval-ahead load demand, a stochastic framework based on unscented transform is devised which can work in the nonlinear and correlated environments of shipboard power systems. Due to the nonlinear cost function in each agent, a powerful optimization algorithm based on modified θ-firefly algorithm (Mθ-FOA) is proposed. This is a phasor algorithm, which helps for escaping from premature convergence and getting trapped in local optima. The appropriate performance of the proposed stochastic model is examined on the real dataset of a ship power system. The simulation results show the high robustness, guarantied consensus, economic operation and feasible solution when power generation shortage based on load shedding in the system.

Abstract Liquid fuels are likely to remain the main energy source in long-range transportation and aviation for several decades. To reduce our dependence on fossil fuels, liquid biofuels can be blended to fossil fuels – or used purely. In this paper, coconut methyl ester, standard diesel fuel (EN590:2017), and their blends were investigated in 25 V/V% steps. A novel turbulent combustion chamber was developed to facilitate combustion in a large volume that leads to ultra-low emissions. The combustion power of the swirl burner was 13.3 kW, and the air-to-fuel equivalence ratio was 1.25. Two parameters, combustion air preheating temperature and atomizing air pressure were adjusted in the range of 150–350 °C and 0.3–0.9 bar, respectively. Both straight and lifted flames were observed. The closed, atmospheric combustion chamber resulted in CO emission below 10 ppm in the majority of the cases. NO emission varied between 60 and 183 ppm at straight flame cases and decreased below 20 ppm when the flame was lifted since the combustion occurred in a large volume. This operation mode fulfills the 2015/2193/EU directive for gas combustion by 25%, which is twice as strict as liquid fuel combustion regulations. The 90% NO emission reduction was also concluded when compared to a lean premixed prevaporized burner under similar conditions. This favorable operation mode was named as Mixture Temperature-Controlled (MTC) Combustion. The chemiluminescent emission of lifted flames was also low, however, the OH* emission of straight flames was clearly observable and followed the trends of NO emission. The MTC mode may lead to significantly decreased pollutant emission of steady-operating devices like boilers, furnaces, and both aviation and industrial gas turbines, meaning an outstanding contribution to more environmentally friendly technologies.

AbstractThe bioenergy crops such as energycane, miscanthus, and sorghum are being genetically modified using state of the art synthetic biotechnology techniques to accumulate energy‐rich molecules such as triacylglycerides (TAGs) in their vegetative cells to enhance their utility for biofuel production. During the initial genetic developmental phase, many hundreds of transgenic phenotypes are produced. The efficiency of the production pipeline requires early and minimally destructive determination of oil content in individuals. Current screening methods require time‐intensive sample preparation and extraction with chemical solvents for each plant tissue. A rapid screen will also be needed for developing industrial extraction as these crops become available. In the present study, we have devised a proton relaxation nuclear magnetic resonance (1H‐NMR) method for single‐step, non‐invasive, and chemical‐free characterization of in‐situ lipids in untreated and pretreated lignocellulosic biomass. The systematic evaluation of NMR relaxation time distribution provided insight into the proton environment associated with the lipids in the biomass. It resolved two distinct lipid‐associated subpopulations of proton nuclei that characterize total in‐situ lipids into bound and free oil based on their “molecular tumbling” rate. The T1T2 correlation spectra also facilitated the resolution of the influence of various pretreatment procedures on the chemical composition of molecular and local 1H population in each sample. Furthermore, we show that hydrothermally pretreated biomass is suitable for direct NMR analysis unlike dilute acid and alkaline pretreated biomass which needs an additional step for neutralization.

Abstract Catalyst layer structural changes in polymer electrolyte membrane fuel cells have significant impact on the cell performance and durability. In this study, ex-situ experiments are designed to investigate the effect of humidity and/or thermal cycles on the structural changes of catalyst layers. The relative humidity and temperature are controlled by an environmental chamber and the catalyst layer structure is characterized by scanning electron microscopy and optical microscopy. The experimental results indicate that crack growth and development, catalyst agglomerate detachment, and surface bulges are the main structural changes of the catalyst layers. Applying relative humidity and thermal cycling simultaneously causes the most significant crack growth, while applying thermal cycling alone causes no appreciable changes. This indicates that the absolute humidity is the key parameter for the crack growth. Through cyclic voltammetry analysis, it is shown that the electrochemical active surface area decreases from 64.1 m2 g−1 to 49.1 m2 g−1 after 500 combined relative humidity and thermal cycles. Analyses of electrochemical impedance spectroscopy show that the charge transfer resistance and ohmic resistance increase significantly after 500 combined relative humidity and thermal cycles, causing the cell performance degradation.

The purpose of research on calculation of low voltage distribution network theoretical line loss is define a calculating method and through the method to calculate the low voltage distribution network theoretical line losses. The calculation of low voltage distribution network theoretical line losses is the foundation of the power system economic operation, the reactive power optimization and the grid technique modification. Through the theoretical loss calculation, the operation management department can undertake line loss analysis, thus they can adopt feasible loss reduction measures, and achieve maximum economic benefits. this paper puts forward through the power flow calculation system, to calculate the low-voltage distribution network users theoretical line loss. Matpower is a softwate package of matlab, which is for power flow and optimal power flow. Based on the relationship between power loss and power flow calculation, calculated the power flow using matpower package, and explained the role in the use of computing to slove the line losses. Through the IEEE (Institute of Electrical and Electronic Engineers) example of 14 nodes and some specific instances of low voltage distribution network calculation, proves that the method is feasible. The results also shows that matpower is suitable for calculating low voltage distribution network theoretical line loss.

Renewable energy has become more popular since it is cost-effective and more efficient than conventional energy sources. Biomass-based renewable energy is primarily used in emerging economies to ensure environmental sustainability. This study examines the asymmetric correlation between biomass energy consumption and CO2 emissions in the top-10 biomass energy consumer countries (Brazil, Canada, Thailand, China, Italy, India, Germany, USA, UK, and Japan). A new approach "Quantile-onQuantile (QQ)" is employed by utilizing the data from 1991 to 2018. Biomass energy consumption, with the exception of Thailand, significantly mitigates CO2 emissions at various quantiles in selected countries. As a robustness check, we used the quantile regression test, whose findings are consistent with the outcomes from the quantile-on-quantile method. However, the degree of asymmetry in the biomass energy-CO2 nexus varies by country, necessitating extra attention and government vigilance when developing biomass energy and environmental policies.

Even with state of the art forecasting methods, the short-term generation of wind farms cannot be predicted with a high degree of accuracy. In a market situation, these forecasting errors lead to commercial risk through imbalance costs when advance contracting. This situation is one that needs to be addressed due to the steady increase in the amount of grid connected wind generation, combined with the rise of deregulated, market orientated electricity systems. In the presence of imbalance prices and uncertain generation, a method is required to determine the optimum level of contract energy to be sold on the advance markets. Such a method is presented here using Markov probabilities for a wind farm and demonstrates substantial reductions in the imbalance costs. The effect of market closure delays and forecasting window lengths are also shown.

After a halt of four years, the n TOF spallation neutron facility at CERN has resumed operation in November 2008 with a new spallation target characterized by an improved safety and engineering design, resulting in a more robust overall performance and e cient cooling. The rst measurement during the 2009 run has aimed at the full characterization of the neutron beam. Several detectors, such as calibrated ssion chambers, the n TOF Silicon Monitor, a Mi- croMegas detector with 10B and 235U samples, as well as liquid and solid scintillators have been used in order to characterize the properties of the neutron uence. The spatial pro le of the beam has been studied with a specially designed \X-Y