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Urban green roofs have emerged as a significant trend in urban architecture worldwide, offering numerous benefits, including enhanced energy performance, improved urban microclimate, and public health. This study proposes a holistic framework for assessing the green roofs' energy-saving potential at the city scale, achieved by scaling up building-scale energy simulations to city-scale energy demands. Firstly, massive building information is collected using Geometric Information System (GIS) technologies. Subsequently, prototype buildings are generated to accurately represent the geometric characteristics of buildings at the city scale. Building performance simulation is further conducted considering three types of plants on roofs. A case study in Xiamen, China, demonstrates the effectiveness of the proposed framework to efficiently quantify the city-scale energy-saving potential of green roofs. By implementing green roofs in Xiamen, energy savings of 1.62–1.83% and peak load shaving of 1.10–1.63% can be achieved for the whole city. Overall, the proposed framework has the potential for widespread application in other cities with minor adjustments to accommodate variations in climate and building parameters. • Holistic framework for evaluating city-scale potential of green roofs. • Prototype buildings to capture various building characteristics at city scale. • GIS-informed scaling up of building-scale energy simulation toward city-scale. • Ophiopogon japonicus performing the best on city-scale green roofs in Xiamen. • Up to 1.83% energy saving and 1.63% peak load shaving by green roofs in Xiamen. [ABSTRACT FROM AUTHOR]

Green roofs have been recognized as an effective way to increase urban green space and improve building micro-environment. This paper investigated the thermal and energy performance of an extensive green roof under free-floating 1 1 Free-floating here means no heating or cooling system affecting the internal conditions of the room. and air-conditioned conditions in Shanghai, a coastal city with hot and humid summer. A field experiment was conducted on two full-scale rooms of a building from 30/07/2014 to 31/08/2014. One room was covered by a green roof while the other one was covered by a common roof. The results show that solar radiation has the strongest correlation with green roof’s cooling effect, and the correlation between solar radiation and heat flux through green roof is negative in free-floating condition but positive under air-conditioned condition. Outdoor temperature is the most correlated factor of green roof’s temperatures but the least correlated one for green roof’s cooling effect. Energy balance analysis indicates that evapotranspiration and long wave radiation dissipate most of heat gain for green roof, and soil water content has a significant impact on energy balance. This paper presents the basic thermal characteristic of extensive green roof in Shanghai and also make it possible for further validation of hygrothermal transfer model of green roof system. [ABSTRACT FROM AUTHOR]

• The so-called pseudo hierarchical energy management architecture built upon the smart EV charging point is firstly introduced. • The proposed energy management architecture is a compact, cost-effective, and easy-to-build scheme for nanogrid. • The introduced nanogrid operation strategy enables autonomous power coordination with V2G incorporated and efficient power dispatching simultaneously. • Comprehensive nanogrid operation scenarios and modes are analyzed via system simulation and hardware-in-loop experiment. Most recently, DC nanogrid incorporating effective energy management has attracted widespread attention. Due to its favorability to integrate renewable energy sources and emerging power electronic loads, such as photovoltaics and electric vehicles (EVs), DC nanogrid is believed to be able to improve the energy utilization efficiency and mitigate the carbon footprint in the coming decades. Towards a compact, cost-effective, and easy-to-build energy management scheme for nanogrid, this paper presents a pseudo hierarchical management architecture built upon the smart charging point. The proposed architecture incorporates the upper-level central controller with the local power role creatively and comprises two timescale management levels with corresponding operation strategies. In the short-timescale local management level, a state-triggered droop strategy based on the decentralized control mechanism is introduced to realize the autonomous power coordination without extensive communication links. The autonomous vehicle-to-grid (V2G) operation is also implemented with providing real-time power balance capability to unpredicted and short-timescale load variation in peak periods. In the power dispatching level, a multi-mode power dispatching strategy involving six operation modes is introduced to realize the efficient power scheduling for the nanogrid. The effectiveness of the proposed architecture and operation strategy is verified in the detailed simulation model and hardware-in-loop experiment platform. The results show that the real-time, autonomous, and stabilized power coordination in nanogrid could be realized along with a self-regulated V2G operation. Additionally, the peak-shaving and valley-filling of load curve, the satisfaction of EV charging demand, and an improved operation economy are achieved under the proposed architecture and operation strategy. [ABSTRACT FROM AUTHOR]

This paper mainly addresses the simultaneous attack of multiple missiles against a maneuvering target in three-dimensional (3-D) space. Here, we show that a novel fixed-time fast nonsingular terminal slide mode surface (FNTSMS), which has the characteristics of nonsingularity, converges in fixed time. With the help of the fixed-time FNTSMS, fixed-time adaptive distributed guidance laws along and perpendicular to the line of sight (LOS) direction are proposed. This realizes the dynamic adjustment of the target parameters in guidance laws, reduces the energy consumption of the guidance process, and realizes the constraints of the impact time and angle simultaneously. Additionally, considering that the communication topology will cause topology switching failure, this paper proves through graph theory that the proposed adaptive guidance laws will not be affected by topology switching. Moreover, through relevant auxiliary transformations, guidance laws with control input delay are demonstrated. To close to the actual action process of the missile, the air resistance item is added to guidance laws and analyzed. In addition, the control input amplitude is restricted to meet the actual working conditions of the missile. Finally, simulations are conducted to demonstrate the performance of the guidance law and its robustness against the mutation of communication topology. [ABSTRACT FROM AUTHOR]

• Build a co-optimization model to optimize supply and demand sides of IES. • Modify stochastic programming to capture both demand and supply sides' scenarios. • Co-optimization model achieves more cost-efficient design considering carbon tax. • Basic and Standard demand-side upgrading are cost-efficient while Premium is not. • Carbon tax accelerates both renewable penetration and demand-side upgrading. Integrated energy systems (IES) can help achieve greater energy efficiency, and then ultimately promote a climate-neutral economy by utilizing local renewable resources. Demand-side energy-saving measures can reduce operational costs associated with energy usage. Most existing IES models, however, focus on supply-side optimization, while the demand-side energy-saving potential and its impacts on whole-system performance are still not clear. The increasing carbon tax makes it even more important to understand the interactions between supply and demand sides to achieve a sustainable system with a minimal carbon charge. Hence, this study proposes a co-optimization model to simultaneously optimize the supply and demand sides of an IES considering the impact of the carbon tax. A selection tree is developed to describe various demand-side envelope upgrading technologies, and a binary tree is established by generating a set of supply-side scenarios with corresponding probabilities. Based on these results, an improved two-stage stochastic programming model is proposed. The robustness of the modeling results was further validated by a simulation–optimization-based uncertainty analysis addressing price uncertainties. A case study in Shanghai indicates that the proposed co-optimization model achieves more cost-efficient solutions than supply-side-only optimization considering carbon tax. Introducing carbon tax can reduce the installed capacity of fuel-based energy technologies by up to 24% and greatly accelerate the penetration of renewables. The increasing carbon tax also promotes the adoption of more advanced energy-saving technologies. Uncertainty analysis reveals acceptable robustness of the optimal demand-side scheme and supply-side configuration with a deviation of less than 5% and a coefficient of variation of 7%. Overall, the observations of the proposed model and case study provide valuable insights for IES design considering an emerging charge of carbon tax. [ABSTRACT FROM AUTHOR]

• Model community-level energy by combining GIS, simulation, and data-driven approaches. • Propose a GIS-based urban building energy modeling method with low computational cost. • Generate various prototype buildings through two-stage clustering process to describe buildings' diversity. • Integrate urban building energy modeling with global sensitivity analysis to discovery urban planning factors. • Identify FAR and BCR as the most influential factors affecting communities' energy use. The residential sector accounts for an increasing amount of global energy use with continued urbanization. Residential energy-informed urban planning offers an economical and easy-to-operate approach to achieve more efficient urban energy utilization. However, quantifying the interactions between residential energy and urban planning remains an open challenge. This study proposes a holistic approach integrating GIS techniques, building energy modeling, and a global sensitivity analysis to prioritize eight key urban planning factors on the community energy performance based on a building energy dataset. The dataset, including urban planning and building information, was first established using GIS techniques and validated using survey data. The residential energy performance model at the community scale was developed using the clustering tree structure of residential building prototypes and building performance simulations. A combined data-driven and global sensitivity analysis approach was further applied to prioritize the impacts of eight vital urban planning factors on energy use intensity and peak load intensity. A case study of 1963 communities in Shanghai revealed that, for the energy performance of residential communities, the floor area ratio and building coverage ratio are the most influential factors, followed by the maximum height and high-rise proportion having a relatively low impact but higher than other factors. Overall, the proposed holistic approach generates robust insights into urban-scale residential energy performance, which can effectively inform urban planners to achieve more energy-efficient regulatory planning. [ABSTRACT FROM AUTHOR]

• An integrated and reconfigurable hybrid AC/DC microgrid architecture based on a novel interlinking converter is proposed. • The hierarchical control strategy for the proposed microgrid architecture is designed considering 17 operation modes. • The optimal coordination of power exchanges between AC and DC sub-grid can be realized. • The utilization and local consumption of renewable energy resources in the proposed microgrid architecture are increased. With the ever-increasing of population and economy worldwide, buildings have become major energy consumers and greenhouse gas (GHG) emitters. The hybrid AC/DC microgrid is a promising alternative for existing power distribution systems to achieve the goal of nearly/net zero energy buildings (nZEBs). However, the increasing demand for compact structure, seamless integration of distributed generators (DGs) and loads, as well as more control flexibility of hybrid microgrids cannot be adequately satisfied by conventional grid architectures. In view of this, an integrated and reconfigurable hybrid AC/DC microgrid architecture with its hierarchical control strategy is proposed in this paper. Firstly, a novel interlinking converter named smart interlinking unit (SIU) is presented, which can provide multiple AC/DC interfaces and diverse operation modes with various control functionalities. Secondly, the SIU-based hybrid microgrid architecture and its hierarchical control structure are established. The dedicated interfaces and cluster controllers for electric vehicles (EVs) facilitate the implementation of centralized vehicle-to-grid (V2G) service. Thirdly, a hierarchical control strategy of SIU, which involves local control in primary control level and power flow control in secondary control level, is introduced to realize coordinated operation of microgrid. The model of the proposed hybrid microgrid architecture is built, and the simulation results demonstrate that the microgrid architecture and hierarchical control strategy can achieve a reliable and coordinated system operation under various kinds of scenarios. Additionally, the mutual power support between AC and DC sub-grids is realized with increased utilization and local consumption of renewable energy resources (RESs). [ABSTRACT FROM AUTHOR]

Pulsed electric fields (PEF) and cold plasma (CP) show the potential to improve drying efficiency, but the understanding of their comparison and combined effects in PEF-driven dielectric barrier discharge (DBD) is lacking. This study aims to develop a non-chemical pre-treatment to improve drying efficiency and quality by exploring the effects of using PEF, atmospheric pressure plasma jet, and PEF-driven DBD for pre-treating wolfberry. Exploring the synergistic effects and mechanisms of PEF and CP in pre-treatment innovatively provided a new dimension for efficient drying. Results showed that DBD pre-treatment reduced the drying time by 50.6% and energy consumption by 46.0% compared to untreated wolfberry. DBD-pre-treated wolfberries showed better sensory quality and retained critical nutrients by reducing enzyme activities and drying time. DBD combined cold plasma etching and PEF cell disintegration to increase the surface area and pore volume of wolfberry. Furthermore, DBD affected the molecular and tissue structure, altering the binding state of water molecules. [Display omitted] • DBD reduced drying time by 50.6% and cut energy use by 46.0% than untreated. • Dried wolfberries obtained by DBD pretreated showed the best overall quality. • DBD reduced enzymatic browning and the accumulation of 5-HMF. • DBD combined CP etching and PEF cell disintegration to improve the drying rate. • DBD altered the water binding by affecting the molecular and tissue structure. [ABSTRACT FROM AUTHOR]

The space-occupation behavior of rural residents can occur in an "indoor air-conditioned environment" or a "courtyard natural environment." High-quality outdoor environments can attract residents to spend more time in the outdoor space, thereby reducing the use of indoor space and building energy consumption. Quantifying the complementary effects of indoor and outdoor spaces on the thermal environmental quality is fundamental in detecting the potential of behavioral activities in building energy-saving. This study on Chinese farmhouses and resident space-occupation behavior in nine districts across various climatic zones investigated the typical farmhouse physical models and resident occupancy rates. Indoor temperature and humidity parameters without air conditioning were simulated, and the predicted indoor and outdoor mean thermal sensation votes were measured and compared hourly. The number of hours of indoor space out of comfort zone but yard space in comfort zone were calculated and analyzed. Finally, the air conditioning energy consumption of farmhouses with and without yard spaces was calculated and compared, considering the difference in spatiotemporal behavior in various rural buildings. The results indicated that yard spaces in rural buildings had a complementary effect on thermal comfort environment provision and have the potential to reduce building energy consumption of farmhouses by 7.21%–33.99%. • Discuss the conception of energy-saving spatiotemporal behavior pattern. • Characteristics of spatiotemporal behavior of rural residents in China being summarized. • Yard spaces in rural buildings had a complementary effect on thermal comfort. • Courtyards reduced building energy consumption of farmhouses by 7.21%–33.99%. [ABSTRACT FROM AUTHOR]

Due to high labour costs and difference of QC driver's handling efficiency existing between day and night, factors concerning QC drivers can significantly impact the schedule of berth allocation and quay crane assignment. This paper tackles the berth allocation and quay crane assignment problem considering QC driver cost, difference of the operating efficiency and performance-related pay between day and night. How QC driver-related factors affect the schedules is analyzed, and the objective composition including QC driver cost is given. A mixed integer programming model with model acceleration algorithms is developed for the proposed problem, and a meta -heuristic framework including a three-stage algorithm is proposed for solving the problem. Numerical experiments are conducted to validate the effectiveness of the proposed model and performance of the meta -heuristic approach, leading to a multitude of managerial insights. [ABSTRACT FROM AUTHOR]

• Develops a holistic large-scale field survey of winter heating in the HSCW zone. • Strong evidence of winter heating patterns classifies as part-time-part-space. • Spatial and temporal elements feature the end-users' heating demand. • Findings support energy policy and design solutions for building heating systems. The increasing demand for improving indoor thermal environment in the hot summer and cold winter climate zone (HSCW) in the Yangtze River region in China poses enormous challenges in terms of energy policy and design solutions for this unique region. A comprehensive understanding of people's habits and behaviors involving winter heating is imperative for decision making for urban heating infrastructure investment strategies that significantly impact the decarbonization of heating. However, there are little studies of a large-scale survey to gain such knowledge acrose the region. The aim of this study is to develop a rigorous survey method in order to obtain reliable data for analysis. Five municipal/capital cities across the upper, middle and downstream Yangtze River were surveyed based on 30 randomly generated locations in each city. A total of 8481 valuable samples were obtained in the survey conducted in the winter from November 2017 to March 2018. It is revealed that air conditioning/air source heat pumps are the predominant systems, accounting for 63% and 58% for bedroom and living room heating respectively. The use patterns of heating are diverse featuring 'part-time-part-space' systems in accordance with the occupancy patterns. There is significant evidence of the habit of opening a window to provide a gap for fresh air irrespective of whether the heating is in use. Two-step cluster analysis is employed to subdivide occupants' heating-related behaviors into three clusters to characterize households. This study fills the knowledge gap of winter-heating-related behaviors. The research outcomes will benefit building energy simulations for energy prediction and help policy makers making decisions on providing strategic guidance in terms of winter heating solutions in this region. [ABSTRACT FROM AUTHOR]