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Abstract Date biomass is a carbon-rich renewable resource that can be considered a potential carbon-rich substrate for energy generation over anaerobic digestion (AD). However, due to its complex nature, appropriate pretreatment is necessary to achieve a higher methane yield. Hence, the current study was envisioned to evaluate the influence of three different pretreatment strategies, namely acid, alkali, and hydrothermal pretreatment on biochemical methane potential (BMP) of seven diverse sorts of Algerian date biomass, namely Pedicels, Fibrilium, Petiole, Fruit bunch, Spath, Palm, and its mixture. Among all the pretreatment conditions, alkaline pretreatment highly influenced the lignin composition of date biomass and showed higher BMP. Among all sorts of biomass, higher BMP was detected through Palm as 295.9 mL CH4/g-TS, whereas the lowest BMP values were recorded with Petiole as 226.74 mL CH4/g-TS. Among all the experimental variations, ammonium pretreated Palm biomass documented the highest substrate conversion efficiency (63.80%), which correlates well with the observed higher BMP values. Nevertheless, there was a very marginal improvement in BMP detected in the case of other pretreatment strategies compared to alkaline pretreatment. This might be due to the efficacy of the applied pretreatment method on delignification of date biomass.

Abstract The rapid increase in energy demand and the limited resources of fossil fuel as well as the environmentally damaging effects, drive the world to find new options for sustainable electricity generation, which is represented by renewable energies. Concentrating solar power (CSP) is one of the most promising technologies in the field of electricity generation to tackle this issue with a competitive cost in the future. This paper presents an investigation of the potential of implementation of CSP plants in Libya. The socio-economic context, current energy situation of the country and different types of CSP plants are discussed. Moreover, an assessment of site parameters required for CSP plants including solar resources, land use and topography, water resources and grid connections are investigated in detail. In addition, thermo-economic simulation of a 50 MW parabolic trough power plant is performed. The simulation is conducted based on meteorological data measured by the weather station installed at the Centre for Solar Energy Research and Studies (CSERS) in Tajoura city. The performance results are compared with the reference plant Andasol-1 in Spain. Even though the proposed plant is located on the North coast where solar resources are at their minimum compared with other regions of the country, the outcome of the study proves that Libya is not only suitable but it can be economically competitive in the implementation of CSP technology.

Abstract The convergence characteristics of two Monte Carlo models are investigated in this paper. These two models or their variations have been used by the electric power industry. Model 1 is based on the random sampling of generator and transmission line status for each hour. Model 2 advances the generation and transmission using the next-event approach. Mathematical analysis and system studies indicate that model 2 converges slower than model 1. The simulation time for model 2 is generally more than twice the mean duration of loss of load. The CPU time per year of simulation is shorter for model 2. However, the total CPU time for model 2 is much longer than for model 1.

Global sensitivity analysis (GSA) of distribution system with respect to stochastic PV and load variations plays an important role in designing optimal voltage control schemes. This paper proposes a data-driven framework for GSA of distribution system. In particular, two representative surrogate modeling-based approaches are developed, including the traditional Gaussian process-based and the analysis of variance (ANOVA) kernel ones. The key idea is to develop a surrogate model that captures the hidden global relationship between voltage and real and reactive power injections from the historical data. With the surrogate model, the Sobol indices can be conveniently calculated through either the sampling-based method or the analytical method to assess the global sensitivity of voltage to variations of load and PV power injections. The sampling-based method estimates the Sobol indices using Monte Carlo simulations while the analytical method calculates them by resorting to the ANOVA expansion framework. Comparison results with other model-based GSA methods on the unbalanced three-phase IEEE 37-bus and 123-bus distribution systems show that the proposed framework can achieve much higher computational efficiency with negligible loss of accuracy. The results on a real 240-bus distribution system using actual smart meter data further validate the feasibility and scalability of the proposed framework.

Abstract This study develops a novel sustainability assessment methodology for energy systems using life-cycle emission factors and sustainability indicators. Here, the global warming and environmental impact dimensions of the sustainability assessment methodology are examined in detail. A comparative analysis shows that a wind-battery system produces fewer potential global warming, stratospheric ozone depletion, air pollution, and water pollution impacts compared to a gas-fired system. The wind-battery system generates 13% of the life-cycle GHG emissions and 22% of the life-cycle ozone-depleting substance emissions of a gas-fired power plant. Nitrous oxide contributes more than 90% of the stratospheric ozone depletion potential of gas-fired and wind-battery systems.

Abstract Accurate estimation of the remaining useful life of lithium-ion batteries is critically important for electronic devices. In the existing literature, the widely applied model-based approaches for remaining useful battery life estimation are limited by the complexity of the electrochemical modeling required. In addition, data-driven approaches for remaining useful battery life estimation commonly define unreliable sliding window sizes empirically and the prediction accuracy of these approaches needs to be improved. To address the above issues, use of a hybrid neural network with the false nearest neighbors method is proposed in this paper. First, the false nearest neighbors method is used to calculate the sliding window size required for prediction. Second, a hybrid neural network that combines the advantages of a convolutional neural network with those of long short-term memory is designed for model training and prediction. Remaining useful life prediction experiments for batteries with various rated capacities are performed to verify the effectiveness of the proposed approach, and the results demonstrate that the proposed approach offers wide generality and reduced errors when compared with the other state-of-the-art methods.

Phasor-based frequency measurement techniques have very good steady-state performance, but their dynamic performance is not well documented. This paper analyzes a phasor-based frequency measurement method that considers the effect of dynamic frequency, and proposes a method to improve the dynamic performance of the phasor-based frequency measurements. Simulation results verify the effectiveness of the proposed method. Results of laboratory experiments are presented to show the performance of the proposed method compared to frequency measurements obtained from commercial phasor measurement units (PMUs).

Abstract Vapour absorption heat transformers are thermodynamic cycles which are capable of upgrading the temperature of waste heat energy using only negligible quantities of electrical energy. Although marked as a future technology by the IEA (International Energy Agency), as being important for energy utilization in the 21st century, industrial applications of heat transformers are still very limited. This paper presents a comprehensive review of heat transformer research over the past two decades. Emphasis is placed upon optimisation studies, alternate cycle configurations, working fluids comparisons and industrial application case studies.

A rich n-heptane/air mixture was burned in a flat flame burner in an inert environment, and the soot limits of stable one-stage flames were measured. With a small thin metal plate placed on the flame to suppress soot-containing cusps on the flamelets, the richest soot-free flame burned was with a mixture for which the equivalence ratio was 2.25. Hydrogen yield was, however, low. Extremely rich soot-free two-stage flames could be obtained, but they were unstable.