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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. [ABSTRACT FROM AUTHOR]

Buildings consume large amounts of energy resources and emit considerable amounts of greenhouse gases, especially existing buildings that do not meet energy standards. Building retrofitting is considered one of the most promising and significant solutions to reduce energy consumption and greenhouse gas emissions. However, finding suitable energy efficiency measures for existing buildings is extremely difficult due to the existence of thousands of retrofit measures and the need to meet various objectives. In this paper, a multi-stage decision framework, including a multi-objective optimization model, and a ranking method are proposed to help decision-makers select the optimal energy efficiency measures. The multi-objective optimization model considers the economic and environmental objectives, expressed as the retrofit cost and energy consumption, respectively. The entropy weight ideal point ranking method, an evaluation and ranking method that combines the entropy weight method and ideal point method, is adopted to sort the Pareto front and make a final decision. Then, the proposed decision framework was implemented for the retrofit planning of an educational building in Chongqing, China. The results show that decision-makers can quickly identify near-optimal energy efficiency measures through multi-objective optimization and can select suitable energy efficiency measures using the ranking method. Moreover, energy consumption can be reduced by building retrofitting. The energy consumption of the case building was 64.20 kWh/m2 before retrofitting, and the value can be reduced by 6.79% through retrofitting. Furthermore, the reduction in building energy consumption was significantly improved by applying the decision framework. The highest value of energy consumption was 59.84 kWh/m2, while the lowest value was 27.11 kWh/m2 when implementing the multi-stage decision framework. Thus, this paper provides a useful decision framework for decision-makers to formulate suitable energy efficiency measures. [ABSTRACT FROM AUTHOR]

Urban housing stock is of large scale and diversity, with low and uneven energy efficiency. In view of this situation, this paper investigates the urban housing of Chongqing during 1950 and 2000 with the typology approach and the CHAID decision tree algorithm, summarizes three major categories and 24 subcategories of building envelopes from 373 samples according to three attributesof construction year, unit type and unit composition, and constructs physical models of the archetypes. By simulation, it shows that classified evaluation can better explain the impact factors and their significance for various types of cooling and heating load demands, contributing to screening out the types with the worst energy efficiency, and the parts of each type that are most unfavorable for energy efficiency. The saving rates of retrofit measures with different depths on cooling and heating loads also depends on the contributions of different types and their different parts. It is proposed to subdivide the evaluation standards for energy-efficiency retrofitting based on CHAID decision tree, and to extrapolate to a larger area for energy-efficiency evaluation and retrofit potential prediction. [ABSTRACT FROM AUTHOR]

China's Hot Summer and Cold Winter zone, with a 550 million population, accounts for 45% of China's building energy consumption; as such, building retrofits could offer substantial energy savings. This paper presents results from a dynamic thermal modeling study of a typical urban multistory residential building under three types of air conditioning (A/C) operating schedules. Seven energy-saving retrofit measures (external wall insulation, roof insulation, double-glazing, air infiltration control, window shading, communal staircase design, and energy-efficient A/C) were evaluated, and the retrofit strategy with the highest annual energy savings and lowest thermal discomfort was identified. This retrofit strategy was subsequently evaluated for other flats (apartments) with different orientations and positions in the typical building. The annual space-conditioning energy could be reduced by 59%–68%, depending on the flat location, orientation and A/C operating schedule. The findings were then scaled up to estimate the potential energy savings in the city of Chongqing. More than 320 multistory residential buildings were represented by 12 archetypes. Space-conditioning energy consumption was reduced by up to 58% (18.8 TWh). This work provides evidence of the potential energy savings of city-scale retrofit that could aid China in reducing building energy consumption and achieving net-zero carbon emissions by 2050. It was possible to explore a wide range of refurbishment options for China's highly energy-consuming Hot Summer and Cold Winter zone with hot, humid summers and mild, chilly winters using dynamic thermal models. The simulation models developed in this paper revealed that double-glazing with air infiltration control is the most effective retrofit measure for middle-floor flats, but for top-floor flats, roof insulation is the most effective; south-facing flats consume more high energy consumption than north-facing flats. Furthermore, high-rise buildings consume less energy than low-rise buildings per square meter, and one-bedroom flats consume more energy than three-bedroom flats per square meter. This study also demonstrated the procedure to develop thermal comfort evaluation methods, A/C operating schedules, and construction parameters from literature in this climate zone when there were no standards or databases available. Findings offer a tangible, clear retrofit strategy that considers different A/C operating schedules, flat locations, and building archetypes. It can assist decision-making by practitioners and homeowners aiming to upgrade the building stock of this climate zone which covers 3.4 billion m2 with a 550 million population to reduce energy consumption and improve occupant comfort. [ABSTRACT FROM AUTHOR]

As a vital resource endowment area and ecological barrier area in China, low‐carbon development in the upper reaches of the Yangtze River is of great significance. This paper compiled the emission inventory in the Upper Yangtze River Economic Zone in the IPCC regional emission accounting method framework and used the Environmental Kuznets Curve (EKC) model to evaluate economic development and carbon emissions. Finally, this paper used the time series method to predict carbon emissions to 2030. We find that carbon dioxide (CO2) emissions increased rapidly from 2004 to 2012. The average annual growth rate reached 9.16%. After 2012, carbon emissions in the region no longer grow steadily but fluctuate or even decline. The secondary industry contributed 79.77%, the tertiary industry contributed 17.78%, and the primary industry only 2.45% from 2000 to 2015. From the industrial sector and energy consumption, thermoelectricity production and supply division and nonmetallic mineral products industry are the sectors with the most CO2 emissions, accounting for 35.54% and 13.34%, respectively. Raw coal and coke are the main factors causing emissions. Nearly 61.32% of the carbon dioxide produced by raw coal comes from the electricity production sector. However, from 2011 to 2015, the CO2 emissions of raw coal decreased year by year, down by 23.32%. The impact of economic growth on carbon dioxide emissions supports the EKC hypothesis. The CO2 emissions in the Upper Yangtze River Economic Zone will decline after 2020, but Chongqing has shown an upward trend. With the above results, provinces and cities can optimize the regional industrial structure based on sectoral carbon emissions. The study area needs to develop clean energy to optimize the coal‐led energy consumption structure. Provinces and cities in the district can learn from each other's advanced emission reduction experience. © 2021 The Authors. Greenhouse Gases: Science and Technology published by Society of Chemical Industry and John Wiley & Sons Ltd. [ABSTRACT FROM AUTHOR]

As an effective reinforcement learning (RL) algorithm, Q-learning has been applied to energy management strategy of hybrid electric vehicle (HEV) in recent years. In the existing literatures, the values of three hyperparameters based on Q-learning are all given in advance, which are respectively exploratory rate ε, discount factor γ and learning rate α. However, different values of hyperparameters will influence on fuel economy of the vehicle and offline computation speed. In this paper, it is proposed that the method of optimization on hyperparameters adapting to driving cycle. Firstly, the mathematical model between three hyperparameters and iteration times is established based on inherent regularity of hyperparameters influencing on vehicle performance respectively. Secondly, it is determined that the optimal changing index k_index of iteration number based on Q-learning corresponding to typical driving cycles. Finally, the simulation model of Yubei District in Chongqing is constructed based on the method of Kullback-Leibler (KL) driving cycle identification. The simulation results indicate that equivalent fuel consumption of the proposed strategy is reduced by 0.4 % and the offline operation time is reduced by 6 s. It can be concluded that the proposed strategy can not only improve fuel economy of the vehicle, but also accelerate the computation speed. [ABSTRACT FROM AUTHOR]

The operational state of energy-efficient ultra-low energy consumption buildings is very important to achieve energy savings and emission reductions, which are currently necessary considerations for the development of the building industry. To date, studies on the implementation of ultra-low energy consumption have been based mainly on the analysis of the effects of certain technologies, and few studies have examined the regional implementation paths at different energy consumption levels. Based on an analysis of actual data obtained from energy consumption monitoring, verification of energy-saving renovations and green building evaluations in Chongqing, this paper suggests setting the target value for ultra-low energy consumption buildings in hot summers and cold winters areas at 29.04 kWh/(m2.a), proposes a technology system that includes the practical application of data for seven active energy-efficient technologies, and establishes an implementation path for the integrated application of active and renewable energy technologies. Then, a set of strategic models for the construction of implementation paths for ultra-low energy consumption buildings that can be promoted in different climatic areas and building types is proposed. The recommendations based on this model are of practical value for guiding policy makers in promoting the development of ultra-low energy consumption buildings. • Determined ULEB target value based on actual Chongqing energy consumption data • Proposed energy-efficient technology system based on effect and cost analysis • Proposed replicable strategic models for implementation path of ULEBs construction [ABSTRACT FROM AUTHOR]

Due to the gradual improvement of urban traffic network construction and the increasing number of optional paths between any two points, how to optimize a vehicle travel path in a multi-path road network and then improve the efficiency of urban distribution has become a difficult problem for logistics companies. For this purpose, a mixed-integer mathematical programming model with a time window based on multiple paths for urban distribution in a multi-path environment is established and its exact solution solved using software CPLEX. Additionally, in order to test the application and feasibility of the model, simulation experiments were performed on the four parameters of time, distance, cost, and fuel consumption. Furthermore, using Jingdong (JD), the main urban area in Chongqing, as an example, the experimental results reveal that an algorithm that considers the path selection can significantly improve the efficiency of urban distribution in metropolitan areas with complex road structures. [ABSTRACT FROM AUTHOR]

In recent years, water-side free cooling has been broadly applied in data centers to lessen the high cost of energy consumption. The energy-saving opportunities of free cooling have been recognized by numerous studies across the world. In this paper, the field test and energy performance evaluation were performed in an operational data center with water-side free cooling, located in Chongqing, China. Existing problems were found during tests, including the insufficient cooling capacity of towers in wintertime and the inability to activate partial-free cooling. The results of the tests show that the reduction in Power Usage Effectiveness (PUE) is much lower than the expected. To understand the marked discrepancies, the performance of the cooling tower was discussed in terms of the approach temperature and actual cooling capacity. The maximum cooling capacity in winter is only about 50 % of the rated. With the consideration of the cooling tower configuration performance in different climate conditions, the conservative energy effects were calculated in 34 provincial cities of China. To prolong the hours available, optimized operation schemes of cooling towers are presented. The available hours for free cooling could be increased from 730 h to 1300 h when operating at 67 % of rated flow rate, resulting in a decrease in the energy saving of chillers between 8.44 % and 21.05 %. [ABSTRACT FROM AUTHOR]

• The data requirements of quota methods are summarized, and a city-scale database containing 670 credible government office buildings is established. • By comparing the processes, the results and applicability, the selection basis of quota methods under different conditions is refined. • A flow chart of the formulation process and method selection of city-level building energy consumption quotas is constructed. • It is proposed that special attention should be paid to the outliers, and the characteristics of outliers in Chongqing are summarized. Energy consumption quota policies are effective management measures to promote energy conservation and emission reduction in China. Cities need to choose an appropriate method to formulate local energy consumption quota standards. This paper is based on the data of 670 government office buildings in Chongqing and the selected quantile method (QM), quota-level method (QLM) and multiple linear regression (MLR) method, which are widely used in the formulation of city-level energy quotas. By comparing their interpretability, evaluation, consistency and stability, the application conditions and applicability of each method are summarized. MLR has the strongest explanatory power but the highest requirements for the technology and information dimensions. The QLM is more explanatory and stable than the QM and is more suitable for the initial stage of energy quota management. When using the QLM, we should consider scientific classifications and reasonable quota levels. Special attention should be given to "outliers" with abnormal evaluations of the quota results. The outliers in Chongqing are characterized as buildings that have been used for more than 10 years and have an area of less than 5000 m2. Finally, this paper constructed a flow chart of the formulation process and method selection to help policymakers better understand how to choose the most appropriate method and identify inefficient buildings. [ABSTRACT FROM AUTHOR]

Exploiting Chongqing's promotion to a province-level municipality, this paper investigates the causal effect of political hierarchy on corporate SO 2 emissions using a spatial regression discontinuity (RD) design. In 1997, the prefecture-level Chongqing was promoted to a province-level municipality, obtaining a substantial increase in decision-making power over fiscal, personnel and administrative affairs. Given the fact that the areas around the Chongqing-Sichuan border shared the same social, economic, and geographical conditions prior to the treatment, the novel findings show that political hierarchy negatively affects corporate SO 2 emissions and Chongqing's enterprises adjacent to the border have a 26% (1-e−0.301) reduction of SO 2 emissions comparatively. The effects are robust enough using alternative model specifications and bandwidths. Besides, this paper provides empirical evidence that enterprises of Chongqing have resource-receiving and external-financing advantages owing to its higher political status. These interwoven advantages help enterprises in Chongqing exhibit better financial performance and enable them to conduct energy substitution, improve energy efficiency and adopt more end-of-pipe treatment, thereby mitigating SO 2 emissions. Based on these findings, this study provides policy implications by shedding light on the effects of political hierarchy on corporate pollution emissions. • Political hierarchy can shape pollution geography. • Different positions in the political hierarchy lead to disparities in resource-receiving and external financing for firms. • Political hierarchy has negative impacts on corporate SO 2 emissions. • The influencing channels include clean energy substitution, improved energy efficiency and end-of-pipe treatment. [ABSTRACT FROM AUTHOR]

The full exploration of the energy-saving potential during the operation of buildings is an essential aspect of energy-efficiency retrofitting for existing residential buildings. Setting reasonable energy consumption quotas can promote the improvement of energy efficiency. The energy benchmark is one of the energy consumption quotas, which represents the general energy consumption level of similar buildings and serves as the energy-saving goal for high-energy-consuming buildings. This study aims to classify existing residential buildings based on their forms and actual energy consumption data and to set energy benchmarks for each building type. Taking typical existing residential buildings built before 2000 in Chongqing, a city in southwestern China, as an example, from the perspective of building typology, the study classified residential buildings into four types and determined the energy benchmarks. Then, energy-efficiency retrofitting measure evaluation and potential analysis were carried out for each type. The study shows that energy for cooling and heating accounts for a high proportion of energy use in existing residential buildings. The energy consumption of residential buildings is greatly affected by orientation and floor area. Point-like buildings with smaller areas facing west have higher energy benchmarks, while slab-like buildings with larger south-facing areas have lower energy benchmarks. The results and methods of the study can provide a basis for the formulation of energy benchmarks for residential buildings, as well as regional energy analysis, energy-saving potential prediction, and energy-saving measure evaluation. [ABSTRACT FROM AUTHOR]

Solar heat gain and natural ventilation cooling of the indoor environment in buildings are highly influenced by the shading and openable area of windows. In addition to the ambient condition, the Heating, ventilation and air conditioning (HVAC) system's mode of use can affect the windows' performance, especially when multiple modes are used in combination (mixed-mode). Although many studies have investigated the mixed-mode application, their conditions for starting/shutting down HVAC equipment and controlling window ventilation are inconsistent with the relevant codes. Here, we propose a mixed-mode operation that resolves the gap between the air conditioning operation temperature and the adaptive comfort upper temperature. It investigates residential buildings' indoor thermal environment and energy efficiency by combining the effective ventilation opening area ratio (REV) and shading design. Simulation results show that our mixed-mode can reduce the indoor overheating hours by about 50% and the building's energy consumption by about 50%. We thereby conclude that the openable area of exterior windows in residential buildings in Chongqing should not be less than 10% of the room's floor axis area where the exterior windows are located. In general, our study expands the existing knowledge of passive energy-saving measures and provides a method for further research on building energy design in hot summer and cold winter regions. [ABSTRACT FROM AUTHOR]

Since China has put forward a series of obligatory Greenhouse Gas (GHG) emission reduction targets, provincial governments have issued provincial-level “Twelfth Five-Year” carbon intensity (CO 2 emissions/GDP) reduction targets. There are 653 cities distributed throughout the eastern, middle and western parts of China, and each region has different quotas and paths to reduce GHG emissions, while the western part has greater challenges than the others. This paper predicts CO 2 emission reduction potential of Chongqing, assesses the difficulty of achieving its CO 2 emission reduction targets, and analyses its low-carbon transition path. The results show that the carbon intensity of Chongqing in 2020 will range from 1.58 to 1.75 ton CO 2 /10 4 RMB, and there exist some scenarios with strong potential to meet carbon intensity reduction targets for 2020. Improved technology, energy efficiency, the optimization of energy input mix, and the adjustment of industrial structure are suggested to be major strategies to reach Chongqing’s carbon intensity targets. [ABSTRACT FROM AUTHOR]

Climate change, the imbalance between China's domestic energy supply and demand, and the success of the shale gas revolution in the United States have been the main motivators for China to actively issue shale gas development policies and explore its own path on this industry. This paper estimates three indicators of economic development: regional GDP, employment level, and the housing price index by using data from China's largest shale gas region, the Fuling District in Chongqing (a municipality in China). The analysis uses a Synthetic Control Method (SCM) model based on data from Fuling itself and other 34 counties of the Chongqing municipality over the period from 2005 to 2018. The results demonstrate that shale gas development has a significant positive effect on both regional GDP and employment level, with average impact growth rates respectively of 9.8% and 12.0%. By contrast, we find an insignificant effect of shale gas development on housing prices. These results support the case for further development of shale gas in China. Note that in some areas our results differ from existing literature, providing a reference for further research in this area. • We estimate the effect of shale gas development on the regional economy in China. • We apply the Synthetic Control Method for model identification. • We find a positive effect of shale gas development on regional GDP and employment. [ABSTRACT FROM AUTHOR]

Different from the state of large-scale energy use and concentrated energy conservation in urban areas, the state of energy use and energy conservation in rural areas has its own characteristics and typical problems. Rural areas have been concentrated on the multiple differences in economic, social, and construction characteristics such as mountain and peace dam topography, natural and artificial construction, developed and underdeveloped, rapid urban development, and relatively backward rural development. It has practical problems that need to be solved urgently, such as the "insufficient savings" in the construction of farmhouses and the "insufficient open source" of clean energy applications. The discussion will be conducted from three aspects: the planning and layout design of rural houses in Chongqing, the performance of the enclosure structure of rural houses in key seasons, and the application of renewable clean energy in rural houses. Then put forward is the energy-saving design path of Chongqing farmhouse. It aims to improve the indoor and outdoor thermal environment of farmhouses, saving heating energy consumption in winter and air-conditioning energy consumption in summer and effectively benefit users to use renewable energy such as biogas, straw, and solar energy. Finally, explore the adaptability between the design methods of farmhouses and the local characteristics of Chongqing's rural areas. In the work of Chongqing Design Going to the Countryside, we create a contemporary farmhouse case that is not only energy-saving but also has good indoor and outdoor space quality. It also provides a reference for the energy-saving design of farmhouses in Chongqing and other regions in China. [ABSTRACT FROM AUTHOR]

• We selected three benchmarking methods to establish building energy benchmarking models based on a sample of 45 hotel buildings in China. • We compared the three benchmarking methods in terms of consistency, robustness and explanatory ability. • The energy efficiency performance obtained from the three methods were found to be inconsistent. • We came up with suggestions based on comparative analysis for policy-makers to develop building energy benchmarking programs. A reasonable building energy efficiency benchmarking program plays an important role in energy consumption control and supervision. Previous studies have focused on the process of establishing a single benchmarking method, but few have compared the performances and outcomes of different methods. To fill this gap, this paper selects three benchmarking methods—multiple linear regression (MLR) based on Energy Star, stochastic frontier analysis (SFA) and the descriptive statistics method (DSM) based on the national energy consumption standard in China—to develop benchmarking models. We demonstrate each method using data on the energy and building characteristics of 45 four- and five-star hotel buildings located in Chongqing, China. To compare the consistency, robustness and explanatory ability of the three methods, we first utilize the Spearman rank correlation analysis to test whether these methods have consistent energy efficiency ranks and then present Sankey diagrams to further reveal the interactions of the estimated energy efficiency grades obtained from the three methods. It is found that the results of DSM and SFA are most consistent, while MLR vs. SFA and MLR vs. DSM present significant differences in evaluating building energy performance. In addition, DSM is more robust for evaluating the ranks of sampled buildings, while SFA is more robust for evaluating energy efficiency grades. Furthermore, we discuss the explanatory ability of each method. In addition to the building characteristics, the design and operational characteristics of the HVAC system have great effects on building energy consumption. Finally, we present suggestions for policy-makers regarding the development and implementation of the building energy benchmarking program in Chongqing and for the management of buildings with different energy performances to further improve the energy efficiency. [ABSTRACT FROM AUTHOR]

• A multi-layer approach for estimating the Energy Use Intensity on an urban scale. • A new bottom-up engineering-based method of analyse the energy performance. • It assist of energy efficiency strategies in urban planning or retrofitting. • Multi-layer building stock information database offers flexibility for policy makers. • The case of Yuzhong district in Chongqing municipality has been demonstrated. Various governments are planning their cities to be climate responsive by reducing the energy consumption and carbon emissions according to different scenarios whilst maintaining good indoor comfort conditions. A robust and reliable tool that can estimate the Energy Use Intensity (EUI) of a city is required. This paper presents a new bottom-up engineering-based multi-layer approach able to analyse the energy performance of existing settlements of every size by retaining as much information as possible about their complexities. The process involves i) creating a 3D model of the urban area, ii) building up templates representing different building characteristics such as functions, the age-band of the buildings and operating schedules, iii) running dynamic thermal simulations and iv) displaying the EUI or total energy demand in the 3D model which can be post-processed for further analysis. This approach offers a flexible simulation process according to various purposes, which is particularly useful in decision-making for urban energy retrofitting or planning for new areas. The hourly high-resolution outcomes would benefit the detailed analysis of energy efficiency strategies in order to achieve carbon reduction. The application of this approach is demonstrated for the case of Yuzhong district in Chongqing municipality, China. [ABSTRACT FROM AUTHOR]

• Field measurements and simulation method were employed. • Tests and analyzes the thermal environment of a data center in Chongqing. • 77 cases were simulated to investigate servers' arrangement and air distribution strategy under partial load. • Inlet air temperature of racks and SHI value were regarded as the criteria for thermal environment. In recent years, with the rapid development of data centers, its huge energy consumption problem is increasingly prominent. Especially, with the development trend of large-scale data center, the load rate of racks is relatively low, which can easily lead to oversupply of cold capacity, thus resulting in energy waste. Hence, how to reasonably arrange servers so as to effectively utilize cooling capacity and improve energy efficiency has become an urgent problem to be solved. In this paper, field test was made to investigate the thermal environment. The test results indicated that the actual load rate of the data room is between 19.34%˜42.55%, and SHI value for test rows were between 0.128 and 0.594 owning to oversupply of CRACs, as a result of serious mixing of cold air and hot air. To reduce the energy consumption, the cooling capacity of CRACs were equal to IT equipment heat dissipation by using simulation tool through changing the load rate, servers' arrangement and air distribution strategy under partial load in data centers. The results showed that the servers uniformly distributed in all racks presented good inlet air temperature that fell in the acceptable temperature range by ASHRAE. And it suggests that the servers are uniformly mounted from the middle of the rack and then the upper for low load rates. When the load rate more than 60%, blanking plates need to be installed. [ABSTRACT FROM AUTHOR]