• Energy Research
• Open Access close
• Closed Access close
• US close
• CN close
• IT close
• EU close

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.

In this study, levulinic acid (LA) was produced from rice straw biomass in co-solvent biphasic reactor system consisting of hydrochloric acid and dichloromethane organic solvent. The modified protocol achieved a 15% wt LA yield through the synergistic effect of acid and acidic products (auto-catalysis) and the designed system allowed facile recovery of LA to the organic phase. Further purification of the resulting extractant was achieved through traditional column chromatography, which yielded a high purity LA product while recovering ∼85% wt. Upon charcoal treatment of the resultant fraction generated an industrial grade target molecule of ∼99% purity with ∼95% wt recovery. The system allows the solvent to be easily recovered, in excess of 90%, which was shown to be able to be recycled up to 5 runs without significant loss of final product concentrations. Overall, this system points to a method to significantly reduce manufacturing cost during large-scale LA preparation.

ABSTRACTPlant heme oxygenases (HOs) regulate biosynthesis of phytochrome which accounts for photo‐acceptance and ‐morphogenesis. Recent studies have demonstrated that plant HOs also regulate many other physiological processes including response to environmental stimuli. To elucidate the mechanism by which HOs regulate plant adaptation to heavy metal exposure, three novel HOs genes were isolated from rapeseed (Brassica napus) and their expression patterns were analysed. Alignment of deduced protein sequences revealed that the three BnHOs share high identity with their corresponding orthologos (AtHO1‐3) from Arabidopsis. To investigate whether the BnHO regulates plant tolerance to Hg toxicity, we constructed B. napus transgenic plants overexpressing BnHO‐1. Under Hg stress, the transgenic plants had 1.41–1.59 folds higher biomass than the untransformants. However, overexpression of BnHO‐1 resulted in less accumulation of Hg in some lines of transformants than in untransformants. The transgenic plants show lower abundance of reactive oxygen species and attenuated oxidative injury compared with the untransgenic plants. We cloned the promoter sequences of BnHO‐1 from B. napus. Analysis revealed that the 1119 bp fragment contains a conserved Cd responsive element (CdRE) and others responding to multiple environmental stimuli. Transient expression in tobacco leaves showed differential responses to heavy metals (Zn, Cu, Pb, Hg and Cd).

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.

AbstractVentilation door are commonly found in tunnels and other underground engineering ventilation structures, disaster periods using its explosion isolation, explosion relief, wind regulation characteristics for disaster prevention and mitigation is of great significance. This paper numerically simulates the propagation characteristics of the gas explosion shock wave in the nearby tunnel when the ventilation door are opened at different degrees, and analyzes the influence mechanism of the opening degree on the change law of the shock wave overpressure distribution in the nearby tunnel. The results show that the shock wave forms a strong turbulence area (high pressure area) on both sides in front of the ventilation door, and the area range and the overpressure value decrease with the increase of the opening degree; the ventilation door reduce the intensity of the shock wave, so that the overpressure behind the ventilation door decreases, and the smaller the opening degree, the lower the overpressure behind the ventilation door. The secondary explosion formed shock wave and the ventilation door reflected shock wave meet to form a stronger shock wave, which leads to different opening degrees of ventilation door, its before, after the roadway and after the bifurcation of the main roadway in the measured points of the overpressure change curve is different, the main difference is that the peak overpressure for the first wave or the second wave peak. The peak overpressure in the tunnel before and after the ventilation door decreases and increases respectively with the increase of the opening length, and the overall decay of the peak overpressure at 5 m and 10 m before the ventilation door is 49.56% and 4.04% respectively and only has an effect on the peak overpressure in main tunnel within 20 m from the bifurcation.

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.

This article examines land-use, market and welfare implications of lignocellulosic bioethanol production in Hawaii to satisfy 10% and 20% of the State's gasoline demand in line with the State's ethanol blending mandate and Alternative Fuels Standard (AFS). A static computable general equilibrium (CGE) model is used to evaluate four alternative support mechanisms for bioethanol. Namely: (i) a federal blending tax credit, (ii) a long-term purchase contract, (iii) a state production subsidy financed by a lump-sum tax and (iv) a state production subsidy financed by an ad valorem gasoline tax. We find that because Hawaii-produced bioethanol is relatively costly, all scenarios are welfare reducing for Hawaii residents: estimated between -0.14% and -0.32%. Unsurprisingly, Hawaii.s economy and its residents fair best under the federal blending tax credit scenario, with a positive impact to gross state product of $49 million. Otherwise, impacts to gross state product are negative (up to -$63 million). We additionally find that Hawaii-based bioethanol is not likely to offer substantial greenhouse gas emissions savings in comparison to imported biofuel, and as such the policy cost per tonne of emissions displaced ranges between $130 to $2,100/tonne of CO2e. The policies serve to increase the value of agricultural lands, where we estimate that the value of pasture land could increase as much as 150% in the 20% AFS scenario.