Energy Consumption Performance Research Articles

Analysis of Energy Consumption and Economy of Regional Gas Tri-Supply Composite System

With the development of Chinese society, there is an increasing demand for emissions reduction and the stable operation of the power grid. Regional comprehensive energy supply systems have entered the public’s view owing to their advantages of reducing capacity, unified dispatch, improving efficiency, and reducing energy consumption. This paper focuses on a system under construction in Chongqing, which adopts a combined gas tri-supply (combined cooling, heat, and power, CCHP) and dynamic ice storage cooling system as the research object. By establishing a mathematical model for the simulation research, this study examines the start–stop priority sequence of the gas tri-supply subsystem and the heat pump subsystem under the ice storage priority strategy in winter and summer and proposes corresponding optimization solutions. By comparing the annual operating energy consumption of the system, we conclude that the gas tri-supply composite system has good economic efficiency and peak-shaving capability, indicating that regional gas tri-supply composite systems have great application potential in the future. The proposed optimized operation strategy and simulated energy consumption calculation provide theoretical guidance for the construction and operation of both this project and similar projects.

Carbon Footprint of Seawater Desalination Technologies: A Review

Abstract As an important and effective way of mitigating water shortages, desalination has steadily and rapidly increased its global capacity over the decades. This raises concern about its environmental impacts, especially its carbon footprint (CF). Although the CF of desalination has been extensively studied, the existing literature lacks reviews exclusively for it. To help fill the research gap, this study presents a comprehensive and up-to-date review of the CF of seawater desalination technologies, including the conventional reverse osmosis (RO), multi-stage flash (MSF), multi-effect distillation (MED), electrodialysis (ED), and mechanical vapor compression (MVC), and the emerging membrane distillation (MD) and humidification–dehumidification (HDH). To our knowledge, this is the first review that focuses on the CF of seawater desalination. A general procedure for assessing the CF of a desalination system is discussed. The CF data of 211 scenarios from 34 studies published from 2004 to 2023 are reviewed and analyzed, with special focuses on the CF of different technologies, the roles of different life-cycle phases and material/energy flows, and the mitigation measures. The results highlight the CF advantage of RO and low-carbon heat-driven MSF, MED, and MD, and emphasize the dominant role of the operational energy consumption (the amount, the form, and especially the source of the energy) in the CF of desalination. This review improves the understanding of the CF of seawater desalination technologies and of the ways to reduce it.

Exploring the Impact of Rice Husk Ash Masonry Blocks on Building Energy Performance

Operational building energy consumption accounts for 55% of global energy consumption. Most of this is attributed to residential buildings, as they make up the largest building type when compared to the total building stock worldwide. As the building envelope is a major contributor to building energy performance, especially the external walls, its optimisation is therefore imperative to reduce energy consumption and carbon emissions. This study set out to assess the effects of waste material additions to external walls and their effect on building energy performance. This research aimed to critically investigate the effect of rice husk ash (RHA) masonry blocks on building energy performance when compared to conventional masonry blocks in tropical climates. A mix of methods, including experimental investigation and simulation studies, were employed for this study. Three variations of RHA block samples were created for this investigation: RHA 5%, RHA 10%, and RHA 15%. Using prototype buildings from the study context, the building simulation results helped quantify the impact on building energy performance from the reuse of rice waste. The largest improvement to the building fabric was recorded with the RHA15% blocks, which resulted in a 9.9% and 11.3% reduction in solar heat gains through the external walls for the selected bungalow and duplex/storey building, respectively. This resulted in a 6.55% and 4.2% reduction in cooling loads and a 4.1% and 2.8% reduction in carbon emissions, respectively, for the bungalow and duplex/storey building. The findings of this research will prove valuable to householders, researchers, architects, and policymakers in their decision-making processes. The findings will also be useful in introducing new methods that can be adopted for similar studies, bridging the knowledge gap while promoting a circular economy through the reuse of landfilled waste.

Energy consumption estimation and profiling for queries in distributed database systems based on a bottom-up comprehensive energy model

Quantifying energy consumption of database operations is the foundation of building energy-efficient database systems. Existing approaches only focused on stand-alone database servers, while we are interested in modeling energy consumption of database operations in the distributed environments. In this study, we aim at providing an accurate energy consumption model for queries executed in distributed database systems, profiling energy consumption characteristics of both the individual queries and the system as a whole, to guide the design of green database systems and to reveal opportunities for energy-efficient computing. As the execution of a distributed query is a combination of a set of subqueries that decomposed from it, we start from building energy models for individual subqueries by extracting basic operations that can effectively reflect their energy consumption. Then we use a bottom-up measuring and modeling method as the basis to provide a comprehensive energy estimation model for the entire distributed query. To validate the accuracy of the model, we use queries with a variety complexity that generated from three standard benchmarks (TPC-H, SSB, and Sysbench) on real distributed databases. Extensive experimental results show that our solution can achieve a high average accuracy of 94.63% for distributed queries. More importantly, based on these results we further explored energy consumption patterns for distributed queries and presented several important implications. And finally, a significant role of distributed joins has been discovered in saving both idle and dynamic energy cost of the system. We hope that taking advantage of our observations can help readers who wish to substantially improve energy efficiency for distributed database systems.

Impacts of On-board Energy Storage Devices on the Energy Consumption of Train Operations

Urban rail transit systems consume significant electrical power, with traction accounting for 50% of the total energy (from China Urban Rail Transit Association [1]). As operational mileage and vehicle counts rise, so does energy consumption, underscoring the importance of vehicular energy conservation. This study evaluates the impact of on-board energy storage devices on train energy efficiency. Using operational data from Changsha Metro Line 5 and incorporating literature reviews and simulations, the energy-saving potential was assessed. Integrating these storage devices with vehicle energy monitoring systems shows promising potential for energy conservation and operational efficiency. This research presents a viable strategy to reduce energy consumption in urban rail vehicles, enhancing system competitiveness.

Impact of groundwater seepage on thermal performance of capillary heat exchangers in subway tunnel lining

The metro tunnels are currently facing challenges associated with thermal pollution, which significantly affects their operational safety and energy consumption. The subway source heat pump system (SSHPS) with front-end tunnel lining capillary heat exchangers (CHEs) is an effective technology to address this problem. The heat transfer characteristics of SSHPS have been previously investigated; however, there is a lack of research on the thermal performance of tunnel lining CHEs under groundwater seepage. This study established a numerical simulation model of tunnel lining CHEs based on a demonstration project of SSHPS. Subsequently, the influence of groundwater seepage on the heat transfer characteristics of tunnel lining CHEs was comprehensively analyzed. The findings suggest that an increase in groundwater seepage velocity leads to the initial expansion and subsequent contraction of the thermal influence range caused by CHEs. Simultaneously, the performance of CHEs is enhanced with increasing flow velocity. When the seepage velocity increases from 0 to 1 × 10−4 m/s, the heat exchange capacity per meter and efficiency of the CHEs during the cooling season increase by 450 % and 446 %, respectively. During the heating season, they experience a growth of 320 % and 310 %, respectively. In addition, the heat exchange performance of CHEs is also influenced by the relative flow direction between the fluid within CHEs and the groundwater. The counter flow arrangement exhibits a 7.7 % higher efficiency of heat exchange during the cooling season compared to the parallel flow arrangement, and a 3.9 % higher efficiency of heat exchange during the heating season. Therefore, it is highly recommended to evaluate groundwater seepage conditions during the design phase of SSHPS in order to enhance the performance of tunnel lining CHEs. This study serves as a valuable theoretical reference for the design of tunnel lining CHEs.

Rapid carbon emission measurement during the building operation phase based on PSO–SVM: electric big data perspective

With the rapid development of urbanization in China, urban energy consumption increases rapidly, leading to energy shortages and environmental pollution, of which building operational energy consumption carbon emissions (BECCE) account for a large proportion. It has a vital impact on global warming and urban green and sustainable development. Chengdu city in Sichuan Province is taken as the research area in this paper. First, basic information and power data on four types of single buildings, including large-sized buildings, small- and medium-sized buildings, government agencies, and residential buildings, are collected. Second, the characteristics of the four types of buildings are extracted, and the calculation model of BECCE (“electricity-carbon” model) based on particle swarm optimization algorithm–support vector machine (PSO–SVM) is constructed, and the model is trained and verified using the method of five-fold cross-validation. Then, according to the mean absolute error (MAE), root mean square error (RMSE), and R2 evaluation indicators, the constructed “electricity-carbon” model is compared and evaluated. Finally, the generalization ability of the “electricity-carbon” model is verified. The research results show that (1) the “electricity-carbon” model constructed in this paper has a high accuracy rate, and the fitting ability of the PSO–SVM model is significantly better than that of the support vector regression (SVR) model; (2) in the testing stage, the fitting situation of large buildings is the best, and MAE, RMSE, and R2 are 858.7, 1108.6, and 0.91, respectively; and (3) the spatial distribution map of regional BECCE can be quickly obtained using the “electricity-carbon” model constructed in this paper. The “electricity-carbon” model constructed in this paper can provide a scientific reference for building emission reduction.

Residential building energy consumption estimation: A novel ensemble and hybrid machine learning approach

In recent decades, there has been a substantial rise in both worldwide energy consumption and the accompanying increase in Carbon Dioxide (CO2) emissions, primarily propelled by population growth and the escalating demand for personal comfort. Operational energy consumption in buildings constitutes about 30% of the world's total final energy usage, underscoring the significance of predicting building energy usage for effective energy planning, management, and conservation. This study has enhanced the prediction of heating load (HL) and cooling loads (CL) for residential buildings using novel and dependable machine learning (ML) techniques. The study utilized two base models: Adaptive Boosting (ADA) and Extreme Gradient Boosting (XGBoost). An ensemble consisting of ADA and XGB was constructed to improve the model's performance, aligning with the principles of the Dempster-Shafer theory. To optimize the efficiency of ADA and XGB, five innovative optimizers, namely Victoria Amazonica Optimization (VAO), Giant Trevally Optimizer (GTO), Covariance Matrix Adaptation Evolution Strategy (CMAES), Coyote Optimization Algorithm (COA), and Mountain Gazelle Optimizer (MGO), were integrated. Statistical analysis has been employed to evaluate the performance of the proposed models. The results highlight the effectiveness of CMAES in optimizing the XGB and ADA models for predicting HL and CL. The most accurate result was achieved by the XGCM hybrid model, as evidenced by the impressive total R2 value of 0.9934 in HL and 0.9911 in CL prediction. The experimental findings illustrate that the suggested approach exhibits superior predictive performance across various scenarios of building energy consumption.

Optimal Vehicle Scheduling and Charging Infrastructure Planning for Autonomous Modular Transit System

Prioritizing the development of public transport is an effective way to improve the sustainability of the transport system. In recent years, bus passenger flow has been declining in many cities. How to reform the operating mode of the public transportation system is an important issue that needs to be solved. An autonomous modular bus (AMB) is capable of physical coupling and uncoupling to flexibly adjust vehicle capacity as well as provide high-quality service under unbalanced passenger demand conditions. To promote AMB adoption and reduce the operating cost of the bus route, this paper presents a joint optimization method to simultaneously determine the AMB dispatching plan, charging plan, and charging infrastructure configuration scheme. Then, a mixed-integer programming model is formulated to minimize the operating costs of the bus route. A hybrid intelligent algorithm combining enumeration, cloning algorithm, and particle swarm optimization algorithm is designed to resolve the formulated model. Subsequently, an actual bus route is taken as an example to validate the proposed method. Results indicate that the developed method in this paper can reduce the operating costs and operational energy consumption of the route compared with the real route operating plan. Specifically, the reduction ratio of the former is 23.85%, and the reduction ratio of the latter is 5.92%. The results of this study validate the feasibility and advantages of autonomous modular transit service, contributing positively to the sustainable development of the urban public transportation system.

Analysis of carbon emission differences between Chinese and Japanese buildings based on qualitative and quantitative comparisons

As the world's largest carbon emitter, China's building-related carbon emissions contributed to 50.9% of the country's total carbon emissions in 2020, making it an important area for carbon reduction. In contrast, Japan, one of the world's most energy-efficient nations, has already achieved carbon peaking. To further clarify the current status of China's building carbon emissions and explore a reasonable path for reducing them, this study applied life cycle assessment to analyze the differences in carbon emissions from buildings in China and Japan. Firstly, the impact of five factors (climate environment, building structure, energy structure, population and economy) on the carbon emissions of buildings was assessed qualitatively. Secondly, example calculation and statistical analysis were used to quantitatively compare the carbon emissions of office buildings in China and Japan at the embodied carbon emission, operation, and demolition stages. In the example calculation, the total carbon emissions of the Chinese case are smaller than those of Japan, with the embodied carbon emissions, operation, and demolition carbon emissions are 1.23 times, 0.8 times, and 0.89 times higher than those of Japan respectively. And the statistical results show that the average value of carbon emissions in the Chinese case is larger than that of Japan, and the embodied carbon emissions, operation, and demolition carbon emissions are 1.54 times, 1.29 times, and 2.46 times of Japan respectively. The operation phase contributes 70% of the difference in carbon emissions, with the nuclear shutdown leading to fluctuations in the carbon emission factor of electricity being the key to the opposite conclusion of the two comparisons. In addition, China has made a lot of efforts to save energy and develop clean energy, and Japan's operation energy consumption is 1.2 to 2.9 times higher than China's. Finally, recommendations are made in terms of energy saving, carbon reduction, and public awareness.

An investigation on shell-side thermal–hydraulic performance of helically coiled tube heat exchanger for deep underground space

Helically coiled tube heat exchanger (HCHE) was extensively used to enhance the thermal environment of deep underground space. The inefficiency of heat transfer in the mine cooling system results in increased operational energy consumption. To enhance heat utilization, this study examines the impact of air temperature, air velocity, coil diameter, pitch, and elliptical tube aspect ratio on the shell-side thermal performance of HCHE through experimental and numerical analysis. The performance evaluation criterion (PEC) and field synergy are introduced to provide a comprehensive assessment of performance. Results suggest that the air velocity can more significantly affect the thermal performance of HCHE than air temperature. Augmenting the coil diameter from 30 − 40 mm and coil pitch from 7.5 − 9.0 mm led to an increase in the Nu number by 16.5 % and 6.7 %, as well as an increase in friction factor f by 575.2 % and 147.1 %, while a reduction in PEC by 38.4 % and 21.1 % when the air velocity is 5 m/s, respectively. For the helically coiled elliptical-tube heat exchanger (HCHE-E), the thermal performance is significantly dependent on the long axis's direction and its aspect ratio. When the air velocity is 3 m/s, the increase in aspect ratio from 1.0 to 1.8 resulted in a decrease and increase in Nu by 14.7 % and 14.6 %, an increase and decrease in PEC by 24.5 % and 28.4 %, as well as a reduction and increase in f by 31.5 % and 48.1 % for the long axle in the horizontal and vertical directions, respectively. The PEC for HCHE is not significantly dependent on the air velocity. The increase in air velocity can result in the augment in PEC of HCHE-E regardless of long axis's direction. The variation of synergy angle is consistent with the change of Nu. These findings offer valuable insights for optimizing the design parameters of HCHE in deep underground spaces.

Energy-saving regulation methods and energy consumption characteristics of office air-conditioning loads in hot summer and cold winter areas

The air-conditioning system of an office building may have much higher operational energy consumption than its designed value due to the actual use behavior which significantly deviates from the predicted one. To precisely analyze the actual air-conditioning energy consumption, in this paper, based on the impact of occupant air-conditioning behavior on the energy consumption of air-conditioning systems, a Supply-Side Cooling Load Regulation Method (SSRM) is proposed, and its air-conditioning energy consumption analysis model is established. The energy consumption characteristics of the air-conditioning system under SSRM were analyzed, with the assumption that the example office building is located in a hot summer and cold winter areas. The results indicate that the indoor air conditioning set temperature and the actual fresh air volume are important factors affecting the variation of the air conditioning system cooling load under the Demand-Side Cooling Load Regulation Method (DSRM) method, whereas under SSRM, the air conditioning system cooling load is not affected by the variation of the indoor set temperature and the fresh air volume; meanwhile, regulating human air-conditioning use behaviors is the key point of reducing air-conditioning cooling load. The increasing fresh air volume from 30 m3/(p∙h) to 90 m3/(p∙h) can result in about a 5°C increase in the average daily indoor air temperature in the rooms used by SSRM, and it also causes an increase in the total air-conditioning load in the rooms under DSRM by more than 45 kWh/day. Further, compared to the DSRM, the SSRM can well regulate occupant air-conditioning use behaviors, which reduces energy consumption by more than 35% in the summer.

Transient simulation and experimental analysis for the response of dual-cycle air-carrying energy radiant diffuse terminal

A novel air-carrying energy radiant diffuse terminal is proposed, and the response of the terminal is investigated by field experiment and numerical simulation. This paper explores the dynamic operation characteristics of the new system to guide the optimal operation of the system. A transient simulation method of three factors (conduction, convection, and radiation) with dual-circulation (air-carrying energy zone and occupied zone) is put forward for the radiant diffuse terminal with a fresh air system. This transient simulation sets up the porous baffle model coupling radiation model concurrently, revealing the dynamic thermal performance for the system's response accurately, quickly, and comprehensively. This method avoids the limits for the complexity of mini porous (Pore size of 1 mm–3mm) geometric models and the transient uncertainty in multiple combination models. The results show that the average error between the convective-conductive model and the convective-conductive-radiative model is about 8% at five different heights. This system has high response performance, which can quickly heat the room while maintaining the comfort requirements of vertical temperature. The radiated heat transfer between the radiant diffuse terminal and the occupied zone is greater than the convective heat transfer (Radiation accounts for 74%). This system has a short response time, high energy efficiency, uniform airflow, and eliminates draught rating. Moreover, the indoor non-uniform transient thermal and humid environments, the thermal comfort, and air quality for the response of the terminal with fresh air system under four different diffuser placements are compared using computational fluid dynamic simulation. The results indicate that introducing heating strategies featuring higher-positioned fresh air inlet and lower-positioned recirculation return air outlet for this system leads to a temperature efficiency increase by 5%, velocity uniformity by 8%, and age of air reduction by 16–50% in human-breathed zone and the response time by 25%, which shows substantial potential for energy savings. The transient simulation and experiments in the paper are beneficial to optimize design parameters and carry out energy-saving applications of operation energy consumption for the response of this terminal with a fresh air system in the future.

Evaluation of Technological Configurations of Residential Energy Systems Considering Bidirectional Power Supply by Vehicles in Japan

To reduce CO2 emissions in the residential and transportation sectors, distributed energy technologies, such as photovoltaic power generation (PV), stationary storage batteries (SBs), battery electric vehicles (BEVs), and vehicle-to-home (V2H) systems, are expected to be introduced. The objective of this study was to analyze the impact of the installed capacity of PV and SB, the type of vehicle, and their combination on the economic and environmental performance of the total energy consumption of residences and vehicles. Thus, this study developed a model to optimize the technological configuration of residential energy systems, including various vehicle types and driving patterns. The simulation results showed that it is more economically and environmentally efficient to install a BEV and a V2H system in households with longer parking times at the residence and to install an SB in addition to these technologies in households with shorter parking times at the residence. Furthermore, comparing a gasoline vehicle and an SB, the most economical combination, with a BEV and a V2H system and with a BEV, a V2H system, and an SB, estimated the carbon tax rate necessary for cost equivalence. The result indicated that the carbon tax rate needs to be increased from its current level.

A global optimization method for data center air conditioning water systems based on predictive optimization control

As the national digitization process accelerates, the number and energy consumption of data centers are increasing year by year. Want to reduce the PUE of the data center. It is correct to start from the perspective of optimizing the energy consumption of air conditioning system operation. In this paper, a predictive optimization control method that is different from previous real-time optimization control is proposed. Predict, optimize, control and adjust the operating parameters of the air conditioning water system in the data center. At the same time, it solves the energy saving problem of the air conditioning system and the lag problem of previous adjustments. Predictive optimization control has broad prospects in research on operation optimization of data center air conditioning water systems.

Optimization and Experimental Study of Operation Parameters for Fertilizer Injection Drilling Device Based on Discrete Element Simulation

In addressing the challenges of high energy consumption and low efficiency in fertilization borehole drilling for clayey soils in southern orchards, this study utilizes the Discrete Element Method to establish a simulation model for clayey soils. Through this approach, we identify an optimal set of operational parameters that significantly reduces energy consumption. By utilizing simulation technology to model the drilling process, we analyzed the impact of rotation speed and feed rate on the torque and resistance of the drilling apparatus. Initially, this paper describes field measurements of particle parameters in soils from southern orchards. Subsequently, utilizing the Discrete Element Method and particle contact theory, we established a simulation model to represent the interactions between soil and soil, as well as soil and auger in the soil environment of the southern region. For the Southern orchard clay with a moisture content of 16.8% and a measured angle of repose of 35.55°, parameter calibration was performed. The contact model “Hertz-Mindlin with Johnson-Kendall-Roberts” was selected in EDEM. Using Design Expert, a regression model variance analysis was applied to the discrete element model parameters, leading to the determination of the optimal values for significant soil model parameters. The soil JKR surface energy is 5.85 J·m−2, with a soil–soil restitution coefficient of 0.65 and a soil–steel static friction coefficient of 0.5. Subsequently, discrete element simulation experiments on the drilling apparatus were conducted in EDEM, considering various rotation speeds and feed rates. The simulation analysis indicates that the torque consistently increases with higher rotation speeds, with a maximum relative error of 7%. The torque initially rises from zero to a maximum value, then gradually decreases to a low value, followed by a rapid increase to a higher value, and finally drops back down. This cycle repeats in the observed pattern. The total force experienced reaches its minimum average value of 200 N at a feed rate of 0.05 m/s. Simulation test results indicate that, among the three forces acting on the auger (vertical resistance, horizontal resistance, and lateral resistance), vertical resistance is the primary factor contributing to power consumption. As the rotation speed increases, the maximum value of vertical resistance continues to rise, while horizontal resistance and lateral resistance exhibit a declining trend. As the feed rate increases, the maximum values of resistance in all three directions also increase. When the feed rate exceeds 0.05 m/s, the maximum lateral resistance experiences a sharp increase. Through comprehensive analysis, the optimal operational parameters for borehole fertilization are determined to be a rotation speed of 100 r·min−1 and a feed rate of 0.05 m/s. The aim of this study is to reduce the energy consumption of borehole fertilization operations, minimize carbon emissions, and promote the sustainable development of orchard production.

K2CO3 on porous supports for moisture‐swing CO2 capture from ambient air

AbstractDirect air capture (DAC) of CO2 is an important technology to mitigate mobile carbon emissions, reduce atmospheric CO2 concentration, and cope with climate change. Moisture‐swing adsorption is regarded as one of the most promising technologies in DAC due to its low energy consumption and ease of operation. In this work, a cheap and easily available moisture‐swing adsorbent of potassium carbonate loaded on porous supports (i.e., activated carbon, magnesium oxide, and zeolite) was prepared for CO2 capture from ambient air. The composite adsorbent of potassium carbonate on activated carbon showed the best performance with a DAC capacity of 0.562 mmol/g at 25°C and 5% relative humidity. The effects of temperature, relative humidity, and CO2 concentration on the adsorption performance were investigated systematically, as well as the cyclic DAC performance. In 50 adsorption–desorption cycles, the adsorption capacity of the composite adsorbent decreased by ~40% due to potassium carbonate leaching loss during water evaporation but can be fully recovered simply by re‐impregnating with potassium carbonate again.

Rapid preparation of P/O doped nano-porous carbon by microwave method for high-performance supercapacitors

This paper proposes a simple and rapid microwave-assisted phosphorus-oxygen doped porous carbon (P/O-PC) preparation strategy is proposed using potassium citrate, Phytic acid (PA), and ethanol under air atmosphere. PA can be used as both a phosphorus source and a microwave absorbing agent. The P/O-PC500–0.75 has a large specific surface area of 905 cm2/g. P/O doping introduces defects into the carbon structure, which enhances the capacitance of the porous carbon. The P/O-PC500–0.75 demonstrates excellent capacitance values of 330 F/g and 389.4 F/g in 6.0 M KOH and 1.0 M H2SO4, respectively (1 A/g). In addition, the symmetrical supercapacitors assembled with the P/O-PC500–0.75 exhibit good electrochemical stability over 5000 cycles at 5 A/g, with a capacitance loss of only 3.6%. This microwave-assisted strategy offers simplicity in operation and low energy consumption, providing a new and efficient pathway to prepare carbon materials in a fast and simple manner.

Constructing Covalent Organic Polymers through Dative B─N Bonds: Synthesis, Single Crystal Structures, and Physical Properties

AbstractGrowing single crystals of covalent organic polymers (COPs) for single‐crystal X‐ray diffraction analysis is very important and highly desirable because such strategy provides a deep understanding of crystallization kinetics and the structure‐property relationship of COPs. Based on the strategy that dynamic covalent bonds can allow self‐correction of structures during crystal growth, single crystals of two COPs (CityU‐15 and CityU‐16) based on dative boron‐nitrogen (B─N) bonds have been successfully obtained. Detailly, tetra(4‐pyridyl)tetrathiafulvalene (TTF(py)4) and tetra(4‐pyridyl)porphine (TPYP) are employed as N‐donor ligands to react with 1,4‐bis(benzodioxaborole) benzene to prepare single crystals of COPs, named as CityU‐15 and CityU‐16, respectively. CityU‐16 exhibits enhanced stability compared to CityU‐15, and the size of CityU‐16 single crystals can reach up to 0.7 cm. CityU‐15 shows good recyclability and reveals noticeable photosensitivity upon iodine doping. After treatment with iodine, both crystals display obvious color changes. Specially, the device based on I2‐treated CityU‐15 exhibits excellent low‐voltage operation and low energy consumption of 3.3 fJ, facilitating the development of artificial vision. This work highlights the successful introduction of functional groups into B‐N‐containing COPs, opening up new avenues for expanding their applications.

Energy-saving speed profile planning for a connected and automated electric bus considering motor characteristic

Speed profiles play an important impact on the operational energy consumption of electric buses (EBs). In this study, an eco-driving method is proposed for a connected and automated EB serving on the bus rapid transit (BRT) route. Considering the effect of speed and road load conditions on motor efficiency in estimating energy consumption, a nonlinear programming model is proposed to optimize the energy-saving speed profile. Then the sparrow search algorithm is used for the solution to ensure that the computing time is less than the predetermined time gap. Finally, a real BRT route is taken as an example to carry out comparative and sensitivity analyses. Results indicate that: (i) the average motor efficiency can be improved by 2.11% after taking into account the effect of speed and road load conditions on motor efficiency in estimating energy consumption; (ii) the number of driving stages with uniform speed on each segment is recommended as 2 for balancing the computation time and solution quality; (iii) planning the energy-saving speed profile while regulating the signal timing at intersections improves the operational efficiency and exploit the energy-saving potential of the CAEB; (iv) as bus operation punctuality constraints become tighter, there is an increase in the operational efficiency, but a decline in the energy-saving potential of the CAEB.