Abstract

While urbanization is driving economic development, it has caused more than 70% of global carbon emissions. Reducing urban carbon emissions is an inevitable requirement for low-carbon city construction. At the same time, in order to alleviate the urban diseases caused by urbanization, polycentric agglomeration has become a new form of urban spatial expansion. Does the polycentric spatial structure help reduce regional carbon emissions? This paper uses nighttime light data to measure the polycentricity of provincial and municipal spatial structure in China and empirically analyzes the impact of polycentric spatial structure on carbon dioxide emissions at different geographic scales. The results show that the eastern region of China presents a significant stronger trend of polycentric spatial development, while its polycentricity has significantly increases emission due to excessing optimal level. As for western areas, polycentricity on provincial distribution strengthens specialization and increases productivity to reduce carbon emissions. At the city level, polycentric spatial structure is suitable emission reduction, especially for western area. Therefore, current common polycentric spatial structure is not beneficial to emission reduction. Urban planning needs to comprehensively consider internal and external conditions. Inter-provincial cities should strengthen collaboration and specialization and avoid vicious competition. The internal development of cities can properly develop multi center and form vertical division and efficiency improvement.

Abstract

The virtual synchronous generator (VSG) control strategy is beneficial to improve the damping characteristics of the system. However, the traditional VSG control method based on droop characteristics can lead to static frequency deviation for the frequency modulation. A kind of enhanced VSG control strategy is described in detail in this paper. The static frequency deviation can be eliminated. And the secondary frequency modulation can be realized within 0.5 seconds. A Matlab model is used to simulate the operation of working load fluctuation under isolated island operation mode. The simulation result shows that the design is feasible.

Abstract

This paper proposed a coupled application of phase change materials (PCMs) and distributed photovoltaic (PV) power generation systems for building energy efficiency. An experimental apparatus for buildings with PCMs and PV systems was constructed. The energy consumption and power generation of the experimental buildings was simulated using EnergyPlus and System Advisor Model (SAM) and verified against experimental data, respectively. The energy consumption was reduced by an average of 0.015 kW per hour and the peak load was delayed by an average of 1 h using PCMs. To realize the highest self-sufficiency rate, an additional 2 kWh battery was required for a reduction of 0.269 kWh air conditioning load. The more the PCMs of the buildings used, the larger the capacity of the battery was needed to be equipped.

Abstract

In this paper, from the current concern of solid waste treatment and disposal, considering the early stage of China’s green finance development, less data years and inconsistent statistical caliber, the relationship between green finance and solid waste treatment and disposal is studied as a grey system, and the grey correlation model is used to analyze the green finance and solid waste There is a strong correlation between the treatment and disposal of solid waste, so as to verify the importance of the development of green finance for the treatment and disposal of solid waste.

Abstract

Electric vehicles (EVs) are often considered as a promising technology and an attractive solution towards low-carbon future. Thus, it is necessary to model the market penetration of EVs and to detect the role of EV adoption in future urban decarbonization scenarios. This study attempts to develop an integrated land use-transport model to examine the interactions among location choice, land use, transport patterns, energy profiles, and economy when implementing the stringent EV policy. Two scenarios are structured to investigate the long-term (to year 2050) impacts of EV adoption on population distribution, land use patterns, transport demand, energy mix, emission profiles, and social welfare. Scenario simulations show that the energy transition and emission reduction can be realized by the stringent EV adoption. The influences of EV penetration on population distribution, land use changes, and emission intensity draw policy implications for transport engineers and urban planners. More importantly, ambitious market diffusion of EVs exerts significant positive effects on emission reduction in city center, while economic benefits tend to occur in suburban areas, implying that EV adoption plays a special role in the spatial organization and structure of cities. Spatial heterogeneity among zones deserves more attention when evaluating the effectiveness of sustainable urban policies. Since the disaggregated spatial interplays can be handled by this integrated model, such methodology offers a useful tool for sustainable urban planning.

Abstract

As one of the core characteristics of integrated energy system (IES), the coupling effect between energy carriers has been a hot topic in existing studies. However, from the perspective of the whole IES, the quantification of the extent of multi-energy coupling is rarely discussed. To solve this problem, this paper establishes an energy coupling index (ECI) to quantify the multi-energy coupling effect considering energy conversion process. Based on the operation data of an industrial park, a case study is carried out to validate the rationality of the proposed index. The calculation results show that when energy coupling unit connects into the IES, ECIs of different energy carriers show overall upward trend, which means ECI can effectively characterize the coupling status of IES. ECI could quantify and assess the design and operation scheme of IES.

Abstract

Rooftop solar photovoltaic power generation provides a feasible solution for the sustainable development of the city. The estimation of rooftop solar potential is of great significance to the formulation of urban energy plans. Quantifying the rooftop area is the basis of estimating the rooftop solar potential, but how to extract the rooftop information quickly in large-scale is still a challenge. In this study, a scalable framework is used to estimate the rooftop solar potential based on Google Earth satellite images. This framework uses a deep learning semantic segmentation method to extract the rooftop, which provides support for estimating the solar potential of the rooftop. In order to reduce the labor cost invested in the training process of the rooftop extraction model, a training data acquisition strategy was developed based on prior knowledge of the urban and rural spatial layout and landuse. This paper takes Nanjing, China as an example to make an empirical analysis. The results show that the framework can achieve good rooftop extraction effect. It is also found that the solar potential of buildings in Nanjing is huge.

Abstract

To mitigate traffic congestion and improve environment condition, license plate control(LPC) policy has been implemented in Beijing since 2011. For instance, almost 100,000 vehicle license plates are distributed in 2019, including 60,000 electric vehicle (EV) license plate and 40,000 gasoline vehicle (GV) license plate. This paper tends to quantify the optimal EV license plate under the LPC policy in Beijing. A two-level Stackelberg game is proposed to model the interaction between vehicle consumers and the government. The equilibrium allocation of EV and its market share are derived from the Stackelberg model. According to the optimal result, the government should adjust the license plate distribution in order to maximize social utility. Once the government plans to enlarge the total quota to meet the excessive demand in the future, more quotas should be allocated to EV to promote EV adoption. Sensitive analysis is conducted to illustrated the impact of certain influential factors such as gasoline price, electricity price, and renting cost, on EV adoption. The result shows that when gasoline price is in a comparatively low level, consumers are more sensitive to the electricity price. Nevertheless, it becomes less significant if gasoline price goes higher. Besides, the impact of car-renting cost variation on EV adoption is studied. To be specific, if the car-renting cost declines from 2377 CNY/month to 1577 CNY/month due to the mature of renting market, the market share of EV will increase by 0.3%.

Abstract

This paper presents a strategy for optimizing the comfortability of hybrid electric powertrains in acceleration mode. A parallel hybrid electrical vehicle (HEV) powertrain system with two motors and single turbo-charged engine is considered, and during the acceleration mode, it is assumed that the desired acceleration rate cannot be satisfied by the electrical motor only. Then, the first challenging issue is how to manage the combustion engine to assist the power generation and the power split such that the system satisfies comfortability, and the second challenging is difficulty in modeling the comfortability, e.g. analytically describing the human feeling. This paper exploits a black- box module to evaluate the comfortability quantitatively which is used in automotive industry. A genetic algorithm (GA) is applied to seek the optimum power split and gear schedule in acceleration mode which improves the comfortability evaluated by the module. Finally, the simulation results conducted on a simulator with practical background are demonstrated where to validate the proposed design approach.

Abstract

The high demand of passivhaus technology for building envelop improves the insulation property and air tightness, which effectively decreases the cold or heat loss caused by thermal conductivity and air infiltration. However, in order to meet the requirement of indoor sanitation and thermal comfort, ventilation and air conditioning are necessary, thus the energy consumption of air handling and distribution is more prominent. Based on the differences between passivhaus standard and domestic relevant design standard for energy efficiency of residential buildings, builds the different models for comparison. Performs simulation and contrastive analysis about cooling and heating load, as well as energy consumption of ventilation and air conditioning systems under different levels of outdoor air in residential buildings in Beijing. The results show that when the minimum outdoor air volume is 30 m³/(person·h), the maximum heat load of passivhaus standard model is 22W/m2, and the maximum cooling load is about 55W/m2, where the outdoor air load can occupy 63.8% and 34.2% in winter and summer, respectively. A certain degree of energy utilization efficiency can be obtained by using mechanical ventilation and energy recovery devices. Then the heating and cooling energy consumption of passivhaus standard model can be 22.66 kW·h/(m2·a), which saves energy by about 7% than the model with Design standard for energy efficiency of residential buildings.