Calculation and Influencing Factors of the Operating Efficiency of Chinese Airports under High-Quality Development

Based on the cross-sectional data of 40 large-scale international airports in China in 2019, this paper introduced natural and social factors into the calculation of airport operating efficiency and constructed a BCC-SFA-BCC-Tobit 4-stage analysis framework. Combining with the connotation of the “green, smart, humane, and safe” airport high-quality development, the paper applied the Tobit model to quantitatively analyze the influencing factors of the operating efficiency of airports, and the research shows that (1) the overall operating efficiency of the study airports is 0.734; in terms of the region, the operating efficiency of airports located in southwest and northwest regions is greatly affected by natural factors, while the operating efficiency of airports located in North China is mostly affected by social factors. (2) Under the perspective of human-earth relationship, the impact of natural factors on the operating efficiency of airports is greater than that of social factors, wherein PM2.5 and relative humidity have negative impact, while the actual foreign capital utilization of the city and domestic and foreign tourists have positive impact. (3) The regression results of the Tobit model indicate that green, smart, and safe indicators can promote the high-quality development of airports, while the humane indicator restrains the high-quality development of airports.

Numerical solutions to a fractional diffusion equation used in modelling dye-sensitized solar cells

Dye-sensitized solar cells consistently provide a cost-effective avenue for sources of renewable energy, primarily due to their unique utilization of nanoporous semiconductors. Through mathematical modelling, we are able to uncover insights into electron transport to optimize the operating efficiency of the dye-sensitized solar cells. In particular, fractional diffusion equations create a link between electron density and porosity of the nanoporous semiconductors. We numerically solve a fractional diffusion model using a finite-difference method and a finite-element method to discretize space and an implicit finite-difference method to discretize time. Finally, we calculate the accuracy of each method by evaluating the numerical errors under grid refinement. doi:10.1017/S1446181121000353

Determination and Application of Maximum Efficiency Curve of Crawler Electric Tractor Motors

With the excessive use of fossil fuels such as oil, the energy crisis and environmental pollution have become important problems related to people’s livelihoods. In agriculture, as a new type of green agricultural machinery, the electric tractor has the advantages of high energy utilization and no exhaust emission. The motor is the core component of an electric tractor’s drive system. Its characteristics and control directly affect a tractor’s operating efficiency, operating quality, and energy consumption. A motor drive control scheme based on a characteristic curve at the maximum efficiency of an electric motor was adopted to address the problems of low motor power utilization and short continuous operation time on a full charge in electric tractors. By leveraging methods to obtain characteristic curves at the lowest fuel consumption for gasoline engines, we determined the characteristic curve at the maximum efficiency for a motor in a crawler-type electric tractor. Plowing is the most basic form of tractor operation, and it represents the agricultural work that accounts for most of a tractor’s use. A field test was conducted on the drive control in plowing operation based on the curve, and the energy consumed to plow each m2, continuous plowing operation time on a full charge, and operating efficiency were tested. The test results showed plowing power consumption per m2 of about 8.40 × 10−3 kWh and work efficiency of 707.07 m2/h. Compared with the traditional tractor, the cost of plowing 1 m2 by the crawler-type electric tractor was reduced by 20.3%–32.5%. Because the control improves operating efficiency, battery energy consumption is reduced and continuous operation time is extended; hence, the control achieves its purpose.

Performance Evaluation Model of Public Resource Trading Platform Using Entropy-Based Gray Clustering Method

In order to standardize public resource trading activities and improve the operating efficiency of public resource trading platforms, this paper conducts research on the performance of public resource trading platforms. A three-level and 28-dimension performance evaluation index system for public resource trading platform is established by considering the four levels of “input-process-output-effect.” Besides, entropy weight method, gray clustering, and fuzzy comprehensive evaluation are integrated on this basis. Entropy weight method is used to determine the index weight, and the degree value of membership for indexes on gray class is determined based on gray clustering method and converted into a matrix. Then, fuzzy comprehensive evaluation method is used to determine the evaluation value and finally carry out the platform performance evaluation, which provides theoretical support for academic researchers to conduct follow-up research on the performance evaluation of public resource trading platforms.

Strategy in Dispatching Trucks and Shovels with Different Capacity to Increase the Operating Efficiency in Cao Son Surface Coal Mine, Vietnam

In surface mining operations, the operating costs of truck-shovel system constitutes 50-60% ofthe total. Only a little save in the operation costs in this system will bring large profit for the mines. Dueto many investment periods, the capacity of both trucks and shovels in Cao Son surface coal mine isdifferent. This leads to the low efficiency and the difficulty in dispatching strategy for the mine. Thispaper presents the current situation and selection of advanced dispatching strategy for increasing theefficiency trucks and shovels at this surface coal mine. The results show the detailed match factor reflectsthe state of each team of loader and trucks and should be use as the indicator for dispatching decision forthe heterogeneous truck and shovel fleet at Cao Son surface coal mine.

Research and Solution Proposals to Optimize Distribution Power Grids in Smart Grid Condition

Smart Grid is a concept for transforming the electric power grid by using advanced automaticcontrol and communications techniques and other forms of information technology. It integratesinnovative tools and technologies from: generation, transmission and distribution. This also includesconsumer appliances and equipment. This concept integrates energy infrastructure, processes, devices,information and markets into a coordinated and collaborative process. All allowing energy to be generated,distributed and consumed flexibly and efficiently. However, the Smart Grid with the integration ofdistributed generation itself also creates a several disadvantages. There can be problems with: stabilityand reliability, relay protection, isolation and operational isolation in which the problem is to create aburden on the distribution grid when transmitting electrical energy sources. Optimizing power flow andbringing high operating efficiency on Smart Grid conditions is an urgent issue. This paper focuses onresearching and proposing solutions for optimal calculation of power flow on Smart Grid. The paper hasresearched, and analyzed calculation solutions to optimize power flow and proposed to use the Lagrangemultiplier method. The study performed calculations for a typical Smart Grid model with three distributedgenerations. Calculation results have shown that the role of the method is to fully perform the optimalcalculation of the power flow on the grid. This is in order to reduce power loss and energy loss as well asincreasing operational efficiency while improving power quality in Smart Grid conditions.

Optimization Design of Energy-Saving Mixed Flow Pump Based on MIGA-RBF Algorithm

Mixed flow pumps driven by hydraulic motors have been widely used in drainage in recent years, especially in emergency pump trucks. Limited by the power of the truck engine, its operating efficiency is one of the key factors affecting the rescue task. In this study, an automated optimization platform was developed to improve the operating efficiency of the mixed flow pump. A three-dimensional hydraulic design, meshing, and computational fluid dynamics (CFD) were executed repeatedly by the main program. The objective function is to maximize hydraulic efficiency under design conditions. Both meridional shape and blade profiles of the impeller and diffuser were optimized at the same time. Based on the CFD results obtained by Optimal Latin Hypercube (OLH) sampling, surrogate models of the head and hydraulic efficiency were built using the Radial Basis Function (RBF) neural network. Finally, the optimal solution was obtained by the Multi- Island Genetic Algorithm (MIGA). The local energy loss was further compared with the baseline scheme using the entropy generation method. Through the regression analysis, it was found that the blade angles have the most significant influence on pump efficiency. The CFD results show that the hydraulic efficiency under design conditions increased by 5.1%. After optimization, the incidence loss and flow separation inside the pump are obviously improved. Additionally, the overall turbulent eddy dissipation and entropy generation were significantly reduced. The experimental results validate that the maximum pump efficiency increased by 4.3%. The optimization platform proposed in this study will facilitate the development of intelligent optimization of pumps.

Regulation Characteristics and Load Optimization of Pump-Turbine in Variable-Speed Operation

In order to improve the operating and regulation characteristics of the hydropower unit and to stabilize the load fluctuations, variable-speed pumped storage technology based on converters has been proposed and given more attention recently. However, different from the conventional units, due to the variability of operation conditions, variable-speed units need to develop a load optimization strategy in terms of operating parameter identification to ensure state matching for operation. Therefore, this paper proposes an optimization search step based on the model test curve, and the process of parameter optimization search is elaborated and calculated in the turbine operating condition and pump operating condition, respectively. A mathematical model of the turbine regulation system is established to analyze the influence of speed and guide vane related parameters on the regulation characteristics, and the achievable operating range and regulation capacity in the variable-speed condition is pointed out based on pump-turbine model test, as well as the advantages over the fixed-speed operation. The results show that by applying the load optimization method, the variable-speed unit can be significantly improved in terms of operating efficiency, especially at low head and low power conditions. Meanwhile, a certain range of active power regulation can be realized by the decoupling control of the converter and measuring the guide vane opening in both modes. The analysis of the model test verifies the effectiveness of the variable-speed regulation operation of pump-turbine and provides a reference for the design and operation of the variable-speed hydropower units.