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ABSTRACT: Charging infrastructure supports the rapid development of China's new energy vehicle industry. It not only plays a decisive role in providing accessible and convenient services for electric vehicle (EV) users but also, in one of the seven new infrastructure areas, plays an important role in stabilizing growth and unleashing economic potential during the new coronavirus (COVID-19) pandemic, impacting China's economy. In this study, the system dynamics model was used to predict the development of the EV industry and the demand for charging infrastructure, while considering the influence of policy, increase in EV mileage, and consumer purchase intention index. Furthermore, using the matching of EVs and charging infrastructure in Beijing and policy-oriented sensitivity analysis, a simulation of the construction of battery swap taxis and power stations under three policy scenarios was conducted. This research shows that with policies implemented to support charging infrastructure and swapping compatible taxis, Beijing can achieve its goal of replacing all EVs with fast-swap batteries and fast-charging functions within three years.

Wind characteristics (e.g., mean wind speed, gust factor, turbulence intensity and integral scale, etc.) are quite scattered in different measurement conditions, especially during typhoon and/or hurricane processes, which results in the structural engineer ambiguously determining the wind parameters in wind-resistant design of buildings and structures in cyclone-prone regions. In tropical cyclones (including typhoons and hurricanes), the inconsistent wind characteristics may be in part ascribed to the complex flow structure with the coexistence of both mechanical and convective turbulence in the boundary layer of tropical cyclones. Another significant contribution to the scattered wind characteristics is due to various measurement conditions (e.g., terrain exposure and height) and data processing schemes (e.g., averaging time). The removal of the inconsistency in the field-measurement system may offer a more rational comparison of measured wind data from various observation platforms, and hence facilitates a better identification scheme of the wind characteristics to guide the urban planning design and wind-resistant design of buildings and structures. In this study, an analytical framework was firstly proposed to eliminate the potential observation-related effects in wind characteristics and then the wind characteristics of seven field measured tropical cyclones (four typhoons and three hurricanes) were comparatively investigated. Specifically, field measurements of wind characteristics were converted to a standard reference station with a roughness length of 0.03 m, observation duration of 10 min for mean wind and averaging time of 3 s for gusty wind at a 10 m height. The differences of the measured wind characteristics between the typhoons and hurricanes were highlighted. The standardized turbulent wind characteristics under the analytical framework for typhoons and hurricanes were compared with the corresponding recommendations in standard of American Society of Civil Engineers (ASCE 7-10) and Architectural Institute of Japan Recommendations for Loads on Buildings (AIJ-RLB-2004).

To research the flow-induced vibration characteristics of the natural gas loop, unsteady numerical simulation is carried out on the loop calculation model under different ambient temperatures and different flow rates, and the influence of different flow rates on the dynamic characteristics of the flow field and its induced vibration characteristics is obtained. The results show that the inherent frequency of the natural gas loop increases slightly under the action of heat–fluid–solid coupling. The maximum equivalent stress of the loop increases with the increase in ambient temperature under low flow conditions, but it is almost constant under high flow conditions. The smaller the cross-sectional area of the loop pipeline inlet, the greater the pressure, and the more significant the pressure gradient along the flow direction. The pressure pulsation of monitoring points in the pipeline under different flow rates presents different rules, and the pulsation amplitude of pipes with different diameters is different, among which the amplitude of the pipe with a diameter of 250 mm is the largest and that of the pipe with a diameter of 150 mm is the smallest. The pressure pulsation signals are concentrated in the low-frequency band of 0–10 Hz, and the range of the band decreases with the increase in the flow rate. The vibration frequency of the loop structure is close to the fluid pressure pulsation frequency and the inherent frequency under the action of heat–fluid–solid coupling, which causes a resonance of about 2 Hz.

In this study, we investigated the influence of overall financial development and its components on energy consumption using the panel data of 120 countries and the generalized method of moments (GMM). By dividing the sample into developed and developing countries, we further examined the national differences of the impact of financial development on energy consumption. The empirical results indicate that the overall financial development significantly positively impacts energy consumption from a worldwide perspective, and its two components (financial institution and the financial market) have the same effect. The analysis of national differences indicates that the financial development also positively impacts energy consumption in developing countries but with no obvious effect in developed countries. The results also suggest that financial development cannot be used to restrain the increase in energy consumption from the global perspective, and policymakers in developing countries must balance the relationship between the development of the financial sector and energy consumption.

The most severe failures in power grids are often characterized as cascading failures where an initial event triggers consequent failures all along the grid often leading to blackouts. Upon identifying a failure and its cascade potential, timely control actions should be performed by the grid operators to mitigate the effect of the cascade. These actions have to be delivered to one or more control devices, creating a dependency between the power grid and its control network. This paper examines the dependency of the operation of the power grid on the control network. Different from literature studies on failure control, our dependency model captures the impact of networking parameters. We formulate an algorithmic model that describes the impact of this dependency on cascade control. Based on this model, we propose an efficient cascade control algorithm using load shedding with consideration of delays in the communication network for power grids. Finally, we evaluate the impact of the power-communication network dependency with uncontrolled grids, ideal/simple control grids and our proposed control scheme. The results demonstrate that the proposed algorithm can significantly reduce the failure of power lines while sustaining larger power demand for users.

A serious problem faced by the metal mineral mining industry is the challenge to the sustainable development of resource mining due to the continuous decline of ore geological grade. In the case of producing concentrates of the same quality, compared with using only high-grade raw ore, ore blending is a way to slow down the decline of ore geological grade by combining high- and low-grade raw ore. There are many ore blending models considering cost minimization or profit maximization as the target value, ignoring the fact that ore blending is intended to obtain a homogenized product. Moreover, the ore blending model cannot be solved by traditional operational research methods when blended grade stability of multiple elements is considered in the ore blending program. In this paper, a multi-objective ore blending optimization model is constructed for the comprehensive utilization of associated resources in ores. It minimizes the deviation of the grade of each metallic element in the blended associated ore from the beneficiation grade and the percentage of different types of rocks at the unloading point. To solve this multi-objective optimization model, an intelligent optimization method is proposed that is an improved multi-objective optimization algorithm based on the Non-dominated Sorting Genetic Algorithm III (NSGA-III). The case study shows that the proposed model and algorithm can effectively solve the mixing problem of polymetallic ores and obtain a satisfactory ore blending solution.

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.

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.