• Energy Research
• 2021-2025close
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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.

Abstract Energy storage systems (ESS) are widely used in active distribution networks (ADN) to smoothen the drastic fluctuation of renewable energy sources (RES). In order to enhance the scalability and flexibility of ESS, a virtual energy storage system (VESS), which is composed of battery energy storage system (BESS), RES as well as flexible loads (FL), is developed in this paper to realize the functionalities of ESS in more cost-effective way in ADN. Aiming at achieving voltage regulation, dynamic pricing strategies based on system voltage condition are designed for VESS. A distributed real-time power management model containing dynamic pricing strategies is proposed to accomplish the voltage regulation and economic power sharing in VESS. Moreover, a set of distributed algorithms, over time-varying unbalanced directed networks, are designed for dynamic pricing strategies and optimal power management model. Furthermore, the convergence property, optimality and system voltage stability are explained by detailed mathematical analysis. Three various case studies which were ran on a real time digital simulator (OPAL-RT OP5600) were designed to validate the effectiveness of the strategy. Finally, simulation results show that the economic power dispatch and voltage regulation are achieved among VESS simultaneously, even in the presence of time-varying directed and unbalanced communication networks.

The path congestion and communication risks of electric power communication network have emerged as the carried businesses are becoming more and more heavy. In this paper, a multi-objective optimization method for power communication network routing considering the importance of the carried businesses is proposed to reduce load imbalance and transmission risk. Firstly, information entropy is introduced as the objective of communication network load balancing optimization. And a risk assessment model for power communication network nodes and links is established. Then fuzzy membership functions are adopted to singularize the two objectives to jointly optimize path congestion and communication risks. The device nodes are dynamically divided according to the carried businesses to pursue the global optimization of the power communication network in which the Yen's algorithm is adopted. Finally, this paper uses the IEEE 30-bus communication network to carry out case simulations and analyzes the proposed method to verify the effectiveness and feasibility.

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.

Interest in the highly efficient energy hub (EH) model has been growing despite the high computational requirements of planning for a multi-energy, multi-device operation. To address both the device size limitation and the multi-scenario issue, we propose a new solution methodology for solving the EH planning problem. In the method, the decision variables are device sizes. First, a dimension reduction technique is proposed to address the curse of dimensionality based on the correlation of unknown variables such as the capacities of different devices in an EH. Second, to avoid local convergence, a solution method called the variable-sized unimodal searching (VUS) approach is proposed to assure a global optimal planning scheme for the one-dimensional non-convex optimization model obtained from the preceding dimension reduction process. The case study indicates that the proposed approach has a higher computing efficiency than the Benders decomposition (BD) algorithm to deal with a scenario-based stochastic planning problem with a large number of scenarios. Thus, the effectiveness of the EH planning approach is verified.

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.

Purpose This paper aims to study the corrosion inhibition behavior of imidazopyridine and its three derivatives on brass. Design/methodology/approach The authors performed weight loss experiments, electrochemical experiments including the polarization curve and electrochemical impedance spectrum, corrosion morphology observation using scanning electron microscope (SEM) and atomic force microscope (AFM) and surface composition analysis via X-ray photoelectron spectroscopy (XPS) to analyze the corrosion inhibition behavior of imidazopyridine and its three derivatives on brass by using quantum chemical calculation (Gaussian 09), molecular dynamics simulation (M-S) and Langmuir adsorption isotherm. Findings According to the results, imidazole-pyridine and its derivatives were found to be modest or moderately mixed corrosion inhibitors; moreover, they were spontaneously adsorbed on the metal surface in a single-layer, mixed adsorption mode. Originality/value The corrosion inhibition properties of pyrazolo-[1,2-a]pyridine and its derivatives on brass in sulfuric acid solution were analyzed through weight loss and electrochemical experiments. Moreover, SEM and AFM were simultaneously used to observe the corrosion appearance. Furthermore, XPS was used to analyze the surface. Then, Gaussian 09 and M-S were combined along with the Langmuir adsorption isotherm to investigate the corrosion inhibition mechanism of imidazole-[1,2-a]pyridine and its derivatives.