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Reactive power consumption of the modern power system is a very important problem that to solve well. Due to the line commutated current source converter-based (LCC) HVDC system is a multivariable and strong coupling nonlinear system, it is difficult to model reactive power consumption of receiving end of LCC-HVDC by traditional analysis method. This paper proposes the reactive power consumption model of receiving end of LCC-HVDC on account of the radial basis function (RBF) neural network. The model with the turn-off angle for input, with reactive power loss on the inverter side of LCC-HVDC for output, using 500kV, 1000MW LCC-HVDC system PSCAD simulation test data training RBF neural network and testing network generalization ability. The results indicate that the reactive power loss model on account of the RBF neural network has much faster convergence speed and higher convergence precision.

Abstract Transient thermal behaviors of ultra-supercritical steam turbine control valves during the cold start warm-up process of steam turbine systems were comprehensively studied using conjugate heat transfer (CHT) simulation. The geometrical configurations and boundary conditions used in simulation were identical to the field setup in a thermal power plant. The simulated temperature variations were first validated using measurements by the flush-mounted thermocouples inside the solid valve bodies. The CHT simulation implementing the shear stress transport (SST) turbulence model demonstrated good agreement with the field data, and the overall numerical errors were below 10%; however, the numerical errors of the simulation, which used empirical heat transfer coefficients at the fluid–solid interfaces, reached 40%. The determined temperature differences between the cold valve bodies with the hot steam flow decreased significantly. Specifically, the temperature differences along the inner wall surfaces of the valve bodies decreased to less than 50 °C. Further investigation of the transient heat flux distributions and Nusselt number distributions confirmed that the unsteady flow behaviors, such as the alternating oscillations of the annular wall-attached jet, the central reverse flow and the intermediate shear layer instabilities, enhanced the fluid–solid heat convection process and thus contributed to the warming up of the solid valve bodies.

Microwave-assisted alkali pre-treatment of wheat straw and its enzymatic hydrolysis were investigated and compared with the conventional alkali pre-treatment process. First, the effect of microwave power and pre-treatment time on the weight loss and composition of wheat straw was examined. The results show that the higher microwave power with shorter pre-treatment time and the lower microwave power with longer pre-treatment time had the same effect on the weight loss and composition at the same energy consumption. The comparison was then made between the effect of the microwave-assisted alkali pre-treatment and the conventional alkali one on the weight loss and composition of wheat straw. The wheat straw had a weight loss of 48·4% and a composition of cellulose 79·6%, lignin 5·7% and hemicellulose 7·8% after 25 min microwave-assisted alkali pre-treatment at 700 W, compared with a weight loss of 44·7% and a composition of cellulose 73·5%, lignin 7·2% and hemicellulose 11·2% after 60 min conventional alkali pre-treatment. The microwave-assisted alkali pre-treatment removed more lignin and hemicellulose from wheat straw with shorter pre-treatment time compared with the conventional alkali one. Finally, the enzymatic hydrolysis of pre-treated wheat straw (substrate concentration 50 g l−1, enzyme loading 20 mg g−1 substrate) was also investigated and the results indicate that the microwave-assisted alkali pre-treated wheat straw had higher hydrolysis rate, reducing sugar concentration and glucose content in the hydrolysate than the conventional alkali pre-treated one. Microwave-assisted alkali pre-treatment is a potential alternative of wheat straw pre-treatment for its enzymatic hydrolysis.

Flexible butyl interconnection segments are synthetically incorporated into an electronically conductive poly(pyrene methacrylate) homopolymer and its copolymer. The insertion of butyl segment makes the pyrene polymer more flexible, and can better accommodate deformation. This new class of flexible and conductive polymers can be used as a polymer binder and adhesive to facilitate the electrochemical performance of a silicon/graphene composite anode material for lithium ion battery application. They act like a “spring” to maintain the electrode mechanical and electrical integrity. High mass loading and high areal capacity, which are critical design requirements of high energy batteries, have been achieved in the electrodes composed of the novel binders and silicon/graphene composite material. A remarkable area capacity of over 5 mAh/cm2 and volumetric capacity of over 1700 Ah/L have been reached at a high current rate of 333 mA/g.

AbstractTo estimate the life cycle cost of thermal power equipments in engineering, this paper established a comprehensive evaluation model of life cycle cost with the life cycle breakdown and cost breakdown structure. Based on the model, this paper defined the cost elements of the thermal power equipment, analyzed influences of the thermal power equipment. Finally, the model is applied to an instance to estimate various cost categories in each life phase, which were summed up to the life cycle cost of the thermal power equipment.

Lower Mekong Basin (LMB) experiences a recurrent drought phenomenon. However, few studies have focused on drought monitoring in this region due to lack of ground observations. The newly released Climate Hazards Group Infrared Precipitation with Station data (CHIRPS) with a long-term record and high resolution has a great potential for drought monitoring. Based on the assessment of CHIRPS for capturing precipitation and monitoring drought, this study aims to evaluate the drought condition in LMB by using satellite-based CHIRPS from January 1981 to July 2016. The Standardized Precipitation Index (SPI) at various time scales (1–12-month) is computed to identify and describe drought events. Results suggest that CHIRPS can properly capture the drought characteristics at various time scales with the best performance at three-month time scale. Based on high-resolution long-term CHIRPS, it is found that LMB experienced four severe droughts during the last three decades with the longest one in 1991–1994 for 38 months and the driest one in 2015–2016 with drought affected area up to 75.6%. Droughts tend to occur over the north and south part of LMB with higher frequency, and Mekong Delta seems to experience more long-term and extreme drought events. Severe droughts have significant impacts on vegetation condition.

A template‐agent can affect defect formation as well as influence interface properties, due to the rapid growth of perovskite film from the solution. Herein, diethylammonium iodide (DAI) is used as an effective template‐agent to control the perovskite crystallization during preparation. It is found that a very small amount of DAI in chlorobenzene (CB) can slow down the perovskite growth of the CH3NH3PbI3 (MAPbI3) film with more large grain size and compacted crystal‐grains resulting in the lesser grain boundaries (GBs) in favor of carrier transport in perovskite solar cells (PSCs). Moreover, some redundant PbI2 can be digested to form DA2PbI4. One part of DA2PbI4 can form the sub‐grains with the composition of (DA2PbI4)0.2(PbI2)0.8 to passivate the GB defects, and other part can cover the surface to passivate the surface defects in large MAPbI3 grains. Using an optimized DAI concentration of 0.5 mg mL−1 in CB solution, the corrsponding MAPbI3 PSC achieves an increased power conversion efficiency of 20.31% with suppressed current–voltage hysteresis. This DAI passivation strategy provides a simple approach to effectively assist the grain‐growth for improved device performance.

The rapid development of advanced metering infrastructure provides a new data source—building electrical load profiles with high temporal resolution. Electric load profile characterization can generate useful information to enhance building energy modeling and provide metrics to represent patterns and variability of load profiles. Such characterizations can be used to identify changes to building electricity demand due to operations or faulty equipment and controls. In this study, we proposed a two-path approach to analyze high temporal resolution building electrical load profiles: (1) time-domain analysis and (2) frequency-domain analysis. The commonly adopted time-domain analysis can extract and quantify the distribution of key parameters characterizing load shape such as peak-base load ratio and morning rise time, while a frequency-domain analysis can identify major periodic fluctuations and quantify load variability. We implemented and evaluated both paths using whole-year 15-minute interval smart meter data of 188 commercial office building in Northern California. The results from these two paths are consistent with each other and complementary to represent full dynamics of load profiles. The time- and frequency-domain analyses can be used to enhance building energy modeling by: (1) providing more realistic assumptions about building operation schedules, and (2) validating the simulated electric load profiles using the developed variability metrics against the real building load data.