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Energy saving has become a key concern of metro systems to reduce operating costs and meet the requirements of sustainable development. Energy-efficient timetabling, an effective way to reduce traction energy consumption, has gotten much attention in recent decades. However, limited research about energy-efficient timetabling simultaneously considered realistic speed profiles and the influence of train loads, which change greatly in different sections and significantly affect energy consumption. Therefore, this paper proposes an energy-efficient timetabling approach to improve regenerative energy utilization based on varying train loads and realistic speed profiles for bidirectional metro lines. First, based on the operational and safety constraints, this paper constructs an integer energy-efficient timetabling model where dwell times and nonuniform headways are taken as decision variables. Besides, the turnaround process is also considered to ensure rolling stock circulation efficiency. Sectional passenger volumes are employed to determine the varying train loads. Energy consumption is calculated based on realistic speed profiles. Owing to the complexity of the model, an improved adaptive large neighborhood search (ALNS) algorithm is designed to solve this model according to its characteristics. Finally, numerical examples are conducted based on the practical data from Shanghai Metro Line 17. The results indicate that the proposed approach effectively solves the energy-efficient timetabling problem with varying train loads and realistic speed profiles for bi-directional metro lines. The approach is suitable for off peak hours and can reduce energy consumption effectively, and the reduction is up to 11.9% for the presented cases. The improved ALNS algorithm can find good solutions within reasonable times in different cases. Moreover, compared with the widely used genetic algorithm in the literature, the improved ALNS algorithm is more efficient in solving the proposed energy-efficient timetabling problem in different cases. [ABSTRACT FROM AUTHOR]

With the development of urbanization, the problem of the disintegrated between industry and city became more prominent, exploring the reasons. The efficiency of new-type industry has been the crucial factor in city-industry integration. This paper constructs the measurement index system of new-type urbanization via DEA-BCC methodology, starting from the quality of urbanization to analyze the efficiency of urbanization. This paper chooses the total energy consumption, general public budget expenditure, and the proportion of employment personnel in the tertiary industry in all urban units as input variables. The total retail sales of consumer goods, urbanization rate, average annual concentration of pm2.5 (popW), and built-up area as output variables. This paper uses DEA method to measure the comprehensive efficiency value, technical efficiency value, and scale efficiency value of new urbanization in Shanghai, and analyzes the influencing factors of urbanization efficiency. The results show the following: (1) The overall level of comprehensive efficiency value, technical efficiency value, and scale efficiency of Shanghai's new-type urbanization are relatively high, especially the technical efficiency basically stays at a high level. The overall trend of scale efficiency and comprehensive efficiency is consistent, and the comprehensive efficiency is greatly influenced by scale efficiency. (2) The technical efficiency of urbanization in Shanghai is close to the optimal, and there is little space for further increasing technological input to improve the comprehensive efficiency of new-type urbanization. The scale efficiency is slightly lower than the technical efficiency, and there is still some space for optimization. (3) In terms of urbanization input indicators, Shanghai's total energy consumption and general public budget input were too much in the early years, which led to the reduction of urbanization efficiency, and the situation has been improved in recent years. In terms of the output index of urbanization, increasing the total retail sales of social consumer goods and the output of built-up area can make the urbanization efficiency of Shanghai reach the optimal efficiency. [ABSTRACT FROM AUTHOR]

Energy internet zones (EIZ) supply multiple energy carriers to customers in certain regions. They can achieve high energy efficiency by energy cascade utilization. In mid‐term, they participate in the wholesale market and retail market simultaneously. Customers can shift their energy use among different hours and energy carriers to satisfy demand according to the retail prices. Unfortunately, multiple energy systems and markets bring various uncertainties on demand and prices. In this paper, the weekly bidding strategy for the EIZ is proposed to determine the optimal bilateral contracts to sign and the optimal energy retail prices. In retail market, the satisfaction degree and elasticity matrix describe customers' response. Distributionally robust optimization is adopted to consider the distributional uncertainties of random variables and Worst‐case Conditional Value‐at‐Risk is employed for risk management. The distributional uncertainties of pool prices and elasticity matrix are discussed in this paper. An EIZ in Shanghai, China is adopted to illustrate the proposed strategy. The results have great resistance to distributional uncertainties. The risk aversion and satisfaction degree affect the EIZ's strategy in wholesale market and retail market, respectively. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

This paper aims to focus on the path planning problem of AUV in the marine environment. As well as considering the path length and safe obstacle avoidance, ocean currents should not be ignored as the main factor affecting the navigation energy consumption of AUV. At the same time, the path should satisfy the mobility constraint of AUV; otherwise, the path is inaccessible to AUV. For the above problems, this paper presents a path planning algorithm based on an improved particle swarm (EPA-PSO); the fitness function is designed based on path length, energy consumption, and mobility constraints. The updated law of particle velocity and the initialization law of particles are improved, and the possible optimal solutions are stored in the feasible solution set; finally, the optimal solutions are obtained by comparison. The local jumping ability is given to the particle swarm so that the particles can jump out of the local optimal solution. The path planning simulation experiment is compared with the traditional PSO algorithm. The results show that the EPA-PSO algorithm proposed in this paper can be used in the AUV three-dimensional path planning process. It can effectively save energy and make the navigation path of AUV satisfy the requirements of maneuverability. The field experiment was completed in Shanghai, China, and the experiment proved that it was feasible to obtain a path satisfying the maneuverability constraints with optimal energy consumption for the problems studied in this paper. [ABSTRACT FROM AUTHOR]

"green" + "innovation" has become a new concept of development. The integration of the two can bring win-win for the environment and economy. This paper selects the annual data of 14309 A-share companies in Shanghai and Shenzhen Stock Exchange from 2012 to 2020 as the research sample. And it uses the two-way fixed effect model to empirically test the impact of green finance on enterprise innovation performance. The study found that the development of green finance can promote the improvement of enterprise innovation performance. The analysis of influence mechanism shows that the development of green finance can reduce the financing constraints of enterprises, and then improve the innovation performance of enterprises; the development of green finance can increase the R&D investment of enterprises, and then improve the innovation performance of enterprises; green finance development can increase corporate investment in environmental protection, which in turn can improve corporate innovation performance. The results of heterogeneity test analysis show that compared with the western region, private enterprises, small and medium-sized enterprises, and high energy consumption and high pollution enterprises, the development of green finance in the central and eastern regions, state-owned enterprises, large enterprises, and non double high enterprises has more obvious role in promoting enterprise innovation performance. Therefore, the government should issue relevant policies and actively promote green finance policies that can help improve environmental and economic issues. [ABSTRACT FROM AUTHOR]

Sky radiative cooling is a kind of passive cooling technology that uses the "atmospheric window" to emit the object's own heat to the low temperature of outer space; this technology has low energy consumption, no pollution, and other useful characteristics, so in recent years it has attracted widespread attention. The cooling effect of the sky radiative cooler is mainly affected by the constantly changing outdoor ambient temperature. In addition, the structure of the radiative cooler itself also means that its radiative cooling power undergoes obvious changes. Here, we utilized COMSOL simulation software to establish a numerical heat transfer model for radiative cooling, aimed at investigating the influencing factors on the sky radiative cooler and methods to enhance the structure of the radiative cooling. This study discusses outdoor ambient wind speed, the inlet flow rate of the cooler, installation angle of the cooler, and different cooler structures. Based on simulation results, it is observed that, for varying wind speeds, when the ambient radiation temperature is higher than the surface temperature of the cooler, a larger ambient wind speed leads to a poorer refrigeration effect. The maximum temperature difference in surface temperature at wind speeds of 0 m/s and 4 m/s is 0.59 °C. When the ambient temperature is lower than the surface temperature of the cooler, a smaller wind speed results in a greater net refrigeration power. The maximum temperature difference in this scenario is 0.32 °C. The net refrigeration power of the radiative cooler increases with an increase in water flow rate. As the water flow rate increases from 0 L/min to 5 L/min, the net refrigeration power increases from 25 W/m2 to 200 W/m2 and gradually stabilizes. Considering the radiative impact of the cooler on the surrounding environment, as the installation angle increases from 0° to 90°, the surface temperature of the cooler first increases and then decreases, reaching its highest temperature of 29.26 °C at 45°. The surface temperature of the cooler varies with the thickness of the air sandwich, increasing from 1 cm to 12 cm, and then decreasing. The lowest temperature of 23.4 °C is achieved at a thickness of 8 cm. The increase in the fin structure on the surface of the radiative cooler leads to a decrease in its refrigeration performance, and the difference between the inlet and outlet temperatures of the radiative cooler with a flat plate structure is always greater than that of the finned plate, and the difference in the average radiance is 23.52 W/m2. Finally, the energy-saving effect of the sky radiative cooling composite system is analyzed. Taking a typical small office building as an example, an energy consumption analysis model is set up, and the energy consumption of the composite system is simulated in four cities with different climates, using EnergyPlus software (version 8.6); the system's power consumption is the largest in hot and humid climates. Compared with the traditional vapor-compression refrigeration system, the composite system reduces air conditioning power consumption by 25.7%, 32.5%, 37.1%, and 44.8% in Guangzhou, Shanghai, Jinan, and Shenyang, respectively. The main innovations of this paper include analyzing and studying the influence of the tilt angle change of the radiative plate on the refrigeration performance of the cooler and the relationship between the surrounding buildings, adding air sandwiches and ribs to the radiative cooler to analyze the influence of convective heat transfer on the refrigeration effect, which plays a guiding role in the design and research of the sky radiative cooler. [ABSTRACT FROM AUTHOR]

This paper uses the EBM model to measure the collaborative governance efficiency of air pollution caused by energy consumption in 27 cities in the Yangtze River Delta (YRD) urban agglomeration. The collaborative governance efficiency of these cities ranges from 0.6665 to 0.9356, with Shanghai having the highest efficiency (0.8277–0.9356) and Chuzhou having the lowest (0.6665–0.8787). On this basis, this article uses a spatial Durbin model and government panel data to test the drivers of air pollution collaborative governance efficiency, the empirical testing found that the relationship between environmental regulation intensity (ERI) and air collaborative governance efficiency (AGE) is U-shaped, with an inverse coefficient of impact of − 0.5852 and a positive coefficient of influence of its squared term of 0.3427. Air pollution governance investment level (AGI) has a 0.8107 positive effect on governance efficiency. All spatial lag term coefficients in the spatial test are positive, indicating a spatial spillover effect of collaborative governance efficiency air pollution caused by energy consumption across cities in the urban agglomeration. In addition, control variables: energy consumption intensity (ECI), the air quality index (AQI), per capita CO2 emission scale (PCE), and air pollution loss rate (ALI), had inverse correlations with governance efficiency, with impact coefficients of − 0.5185, − 0.5107, − 0.6164, and − 0.5147. Per capita, GDP level (PGL) and R&D investment intensity (RDII) had positive relationships with governance efficiency with coefficients of 0.6026 and 0.5786, respectively. Based on this foundation, policy recommendations have been proposed to enhance the collaborative governance efficiency of air pollution in the Yangtze River Delta urban cluster. [ABSTRACT FROM AUTHOR]

Maximizing the carbon reduction in substations with minimum cost investments can be achieved by taking advantage of the potential of substations in terms of the envelope and renewable energy, which is significant in promoting carbon reduction in substations. Therefore, firstly, the relationship between building cost–energy consumption–carbon emissions is explored, and then the global optimal calculation model of substation envelope–renewable energy is established, with the lowest life-cycle carbon emission of the substation as the optimization goal. Finally, the validity of the model is verified based on a case study of a typical 110 kV outdoor substation. The model calculation results show that, without considering the cost constraint, Harbin has the highest maximum carbon reduction of 180,350 kg, which is 25.15% and 13.74% higher than the maximum carbon reduction in Shanghai and Haikou, respectively. Furthermore, based on the comparison of the cost and benefits of each carbon reduction technology, a prioritization of various carbon reduction technologies is given for each climate zone. The model established in this paper can provide the optimal configuration of substation carbon reduction technologies with different incremental cost constraints, and provide a reference for the low-carbon design of substations. [ABSTRACT FROM AUTHOR]

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Occupancy, which refers to the occupant count in this paper, is one of the main factors affecting the energy consumption of commercial buildings. It is important for both building managers and energy simulation engineers to understand how an entire building's energy consumption varies with different occupancy levels in the process of building automation systems or in assessments of building performance with benchmarking lines. Because commercial buildings usually have large scales, complex layouts and a large number of people, it is a challenge to simulate the relationships between an entire building's energy consumption and occupancy. This study proposes a fast method for calculating the influence of occupancy on the energy consumption of commercial buildings with different building layouts and existing occupancies. Other occupant behaviors, such as the opening of windows and adjustment of shading devices, are comprehensively reflected in two basic building parameters: the balance point temperature and the total heat transmission coefficient of the building. This new method can be easily used to analyze how building energy varies with occupancy without a physical building's energy model. An office building in Shanghai is taken as a case study to validate the proposed method. The results show that the coefficient of determination R2 between the calculated value and actual value is 0.86, 0.8 and 0.71 for lighting, cooling and heating energy, respectively, which is suitable in engineering applications. [ABSTRACT FROM AUTHOR]

The energy consumption of data center cooling systems accounts for a large proportion of total energy consumption. The optimization of airflow organization is one of the most important methods to improve the energy efficiency of cooling systems. The adjustment scale of many current air flow organization methods, however, is too large and does not support the data center's refined operation. In this paper, a new type of air supply terminal device is proposed, and it could adaptively adjust according to the power of servers in the rack for cold air redistribution. In addition, the corresponding regulation strategy is proposed. A CFD model is established according to field investigation of a real data center in Shanghai to investigate the adjustment range and the energy saving potential of the device. The simulation results indicate that the device can suppress the local hot spots caused by excessive server power to some extent and greatly improve the uniformity of servers exhaust temperature. The case study shows that the device can save energy consumption by 20.1% and 4.2% in mitigating local hot spots compared with reducing supply air temperature and increasing supply air flowrate. [ABSTRACT FROM AUTHOR]

This paper proposes a novel Distributed-Integrated Model Predictive Control (DI-MPC) strategy for the multi-vessel cooperative path following, formation control and obstacle avoidance. Each vessel is designed with an individually distributed controller based on the MPC theory and communication graph. Subject to actuator limitations and formation constraints, the motion control and thrust allocation are integrated into a dynamic model to achieve direct control to the thrusters. A bivariate thrust efficiency matrix is embedded into the model to consider the hydrodynamic interaction effects between adjacent thrusters. The Nominal System is introduced to generate the linearized predictive model. To achieve consensus among various vessels, a real-time iterative negotiation framework is established. The Kalman Filter is utilized to estimate the low-frequency state variables from the external disturbances of environment loads and measurement noises. Numerical simulations based on the proposed distributed strategy and the centralized strategy are carried out under the scenario of cooperative operation in the Huangpu River (in Shanghai). Comparative analysis results demonstrate the high control performance of both the strategies. DI-MPC mainly contributes to the system flexibility, computational cost reduction (67.65%), energy consumption reduction (5.03%) and fault-tolerant capability. Furthermore, DI-MPC also shows strong applicability to large-scale cooperative control problems. [ABSTRACT FROM AUTHOR]

Environmental protection and social obligation fulfillment have become hot subjects as the "dual carbon" approach has been developed and deepened. The ESG system is consistent with China's current policies, abandoning the traditional business philosophy of economic supremacy in favor of comprehensively measuring corporate social responsibility and sustainable development capability across three dimensions: environmental (E), social (S), and corporate governance (G), which receive widespread attention from all sectors of society. Based on observational data from A-share listed businesses in Shanghai and Shenzhen from 2011 to 2020, this study empirically evaluates the influence and mechanism of ESG on government subsidies. The research results indicate that enterprises can receive more government subsidies by improving ESG performance. Mechanism analysis found that corporate transparency plays a positive mediating role in the process of ESG affecting government subsidies. Further research on political affiliation and property rights has found that companies without political affiliation are more inclined to receive more government subsidies by improving ESG performance, and the impact of political affiliation and ESG performance on government subsidies is mutually complementary. Enterprises with different property rights have different strengths of motivation to increase government subsidies by improving ESG performance. State owned enterprises (excluding central enterprises) are the strongest, followed by non-state-owned enterprises, and central enterprises are the weakest. Therefore, enterprises should be further encouraged to strengthen ESG construction, improve the quality of ESG information disclosure, improve resource allocation efficiency, and promote high-quality development of enterprises. [ABSTRACT FROM AUTHOR]

Optimization on trajectory planning is significant offering the driver or automatic train operation system a guidance to drive the train efficiently. An optimal trajectory is subject to operational, geographic, physical and dynamic constraints. In previous studies, researchers have put much effort into offline optimization. However, operational errors in real situation are rarely taken into consideration. Thus, this paper proposes a dynamic trajectory planning to address the deviation. Specifically, first, we design an online optimization framework to display model predictive control-based train trajectory planning theory. Various constraints are set for optimization problem. Second, taking energy consumption and punctuality into consideration, we propose a moving window method to search the optimal variables, which are applied to evaluate the fitness function. Plus, to improve global search ability and convergence rate, we present a multi-swarm particle swarm optimization by dividing the population into several parts. On the basis of operational time error at reallocation positions, we design a novel weight allocation mechanism for the revaluation of fitness function. At last, taking real data from Beijing-Shanghai high-speed railway as an example, the robustness and effectiveness of the proposed algorithm is proved by comparing multiple parameters with some numerical results of simulations. The results show that the proposed method can adjust operating strategy dynamically so that the train runs in an energy-efficient way. Additionally, in delay scene, the proposed method can also guide the train to catch up with the scheduled time and save energy consumption. [ABSTRACT FROM AUTHOR]

Benchmarking the energy efficiency of buildings is important for optimizing the efficient use of energy and reducing carbon footprint. Healthcare facilities have especially high energy usage, but the historical difficulty of collecting energy data from a relatively large number of healthcare facilities has made it challenging to develop the appropriate benchmarking system. In this paper, we seek to foster the task of benchmarking the energy efficiency of healthcare facilities using three different methods: multiple linear regression (MLR), generalized additive model (GAM), and energy performance index (EPI). The analysis was applied using a unique dataset that contained information on energy consumption and various building features for 22 large-size public hospitals managed by the Shanghai hospital development center (SHDC). Findings suggest that different benchmarking methods yield substantially different energy performance ranking results. Furthermore, a comparative analysis of the three benchmarking methods was conducted in terms of goodness-of-fit, consistency, and robustness. The results show that MLR tends to be the most consistent and robust benchmarking model, while GAM appears to have the best goodness-of-fit. The proposed methodology can assist hospital managers identify potential improvements for more efficient use of energy in healthcare facilities. [ABSTRACT FROM AUTHOR]

To achieve carbon neutrality quickly and deal with urban greenhouse effect, it is necessary to study the energy consumption of urban buildings. Energy consumption prediction is an important step in planning and managing energy use in buildings. At present, few studies have comprehensively considered the relationship between geometric features, functional types, location and energy use of buildings in urban built-up areas. In this paper, a spatial data-driven framework is introduced for the analysis and assessment of building energy consumption. The framework is grounded in the building centroid and is combined with single photon radar and point of interest data through the utilization of the nearest neighbor classification algorithm. Two megacities, Beijing and Shanghai, are taken as examples to illustrate the method and to generate the regional building energy use database. The results show that: a) building physical feature (geometric form, functional type) have a significant impact on energy consumption, and energy consumption is correlated with the economic level of the region; b) Energy use in urban built-up areas has obvious spatial agglomeration characteristics, and the siphon effect is obvious in region with high energy consumption. The contribution of the framework is to provide insights into the feasibility of employing multiple spatial data fusion for the analysis of energy consumption within urban built-up areas. This can be employed to address energy planning concerns and help promote sustainable environmental practices in urban areas worldwide. • This paper attempts to provide a feasible framework for analyzing urban building energy use by utilizing real-time urban semantic perception information and building features. • The proposed framework have comprehensively considered the relationship between geometric features, functional types, location and energy use of buildings. • The proposed methodology can obtain regional energy consumption stocks and produce spatial distribution results, thus improving the interpretability of the data. • The results show that energy use in urban built-up areas has obvious spatial agglomeration characteristics, and the siphoning effect is obvious in regions with high energy consumption. [ABSTRACT FROM AUTHOR]

Railway transport becomes a more popular transportation in many countries due to its large transport capacity, low energy consumption, and benign environment. The passenger train service planning is the key of the rail operations system to balance the transport service and the passenger demand. In this paper, we propose a mixed binary linear programming formulation for the passenger train service planning to optimize the train route, frequency, stop schedule, and passenger assignment simultaneously. In addition, we analyze the computational complexities of the model and develop a Benders decomposition algorithm with valid inequalities to solve this problem. Finally, our model and algorithm are tested on a real-world instance of the Beijing-Shanghai high-speed railway line. The computational results show that our approach can solve these problems within reasonable solution time and small optimality gaps (less than 2.5%). [ABSTRACT FROM AUTHOR]

Im täglichen Stadtbetrieb sollte die Stromversorgung unterbrechungsfrei sein, was das moderne Energiemanagement vor Herausforderungen stellt. Die Prognose des Energiebedarfs kann die Strategie des Energiemanagements optimieren und die Energieeffizienz verbessern. Das traditionelle LSTM-Modell, das auf einer Codierungs-Decodierungs-Struktur basiert, codiert alle historischen Informationen als Vektor fester Länge, was zum Informationsverlust führt, wenn der vorhergesagte Wert von den Merkmalen abhängt die weit in der Vergangenheit liegen. Dies ist bei Energieprognosen aufgrund der Periodizität des Energieverbrauchs üblich. Um das oben genannte Problem zu lösen und das Potenzial der Betriebsdaten von Kraftwerken für Energievorhersagen vollständig auszuschöpfen, wird in diesem Artikel ein Energievorhersagemodell vorgeschlagen, das auf dem Aufmerksamkeitsmechanismus basiert. Ausgehend von der traditionellen Codierungs-Decodierungs-Architektur wird der räumliche und zeitliche Aufmerksamkeitsmechanismus eingeführt, um die räumlichen und zeitlichen Eigenschaften, die für den vorhergesagten Wert am relevantesten sind, adaptiv auszuwählen. Die experimentellen Ergebnisse zeigen, dass bei der Vorhersage des Strombedarfs von Shanghai für die nächsten 100 Tage, der Fehler des Hybridmodells 25,8 % niedriger ist als der des traditionellen LSTM-Modells. Darüber hinaus zeigt der Fehlertrend des Hybridmodells im Laufe der Zeit auch eine stärkere Stabilität als das herkömmliche Modell. In the daily operation of the city, the power supply should be non-interruptible, which brings challenges to the modern power management. Energy demand forecasting can optimize the strategy of power management and improve energy efficiency. The traditional Long Short-Term Memory model, based on the encoding-decoding structure, encodes all the historical information as a fixed-length vector, which will lead to the loss of information when the predicted value depends on the features of a long time ago. This is common in energy forecasting because of the periodicity of energy consumption. To solve the above problem and to fully realize the potential of the operational data from power plants in energy predictions, this paper proposes an energy prediction model based on the attention mechanism. Based on the traditional encoding-decoding architecture, the spatial- and temporal-attention mechanism is introduced to adaptively select the spatial and temporal characteristics most relevant to the predicted value. The experimental results show that the error of the hybrid model is 25.8 % lower than that of the traditional LSTM model when predicting the power demand of Shanghai in the next 100 days. In addition, the trend of the error of the hybrid model over time also shows stronger stability than the traditional model. [ABSTRACT FROM AUTHOR]

The purpose of the paper is to evaluate the shadow impact factor of buildings on building-integrated photovoltaic (BIPV) system efficiency and to determine optimal building configurations: shapes and orientation; to ensure BIPV efficiency based on the sun-shading effect. Also considered were the height, tilt angles, orientations and array spacing as well as different shapes of the podium building for BIPV system. A parametric design software called grasshopper and plug-in ladybug were used for the simulation. Model cases were built according to statistics of high-rise buildings in Shanghai. The simulation condition was based on the winter solstice of 21 December. The results show the best shapes for high-rise buildings are circle and square, to ensure the best BIPV system efficiency. The BIPV should be located on the roof and the 'U' type podium building is the best shape for mounting the BIPV system to provide a good sunlight exposure no matter what the high-rise building shape is. For PV panels, the best height is 0.618 m, the optimum tilt angle and array spacing is 30° and 1.214 m, respectively. The best orientation is southward followed by southeast, southwest and with the BIPV tilting upward at 30°. Therefore, to maximize the solar energy generation, architects should consider square and round high-rise buildings and 'U' type podiums for mounting BIPV systems in commercial complex buildings. [ABSTRACT FROM AUTHOR]

Hybrid systems combining heat pump and gas heater can demonstrate the economic benefits, while their environmental performance is rarely investigated. In this paper, a comprehensive environmental performance investigation has been conducted to reveal the potential for emission reductions. A new environmental impact methodology has been built, and various influencing factors are evaluated. In respect of the climates, the hourly energy consumption emission first increases and then declines, which is the result of multiple effects from the weighting factors of fuel source emissions and each heating sector's performance. Under the operation condition map for the current study, the effects of the target (final) water temperatures, electricity generation emission factor reduction, and price ratios are revealed to be the top 3 heaviest fluctuations for emissions for hourly system operation energy consumption, followed by each heating sector's efficiency enhancements. The environmental impacts due to hourly system operation do not closely follow the hourly energy consumption profile for the effect of climate conditions and can be quite opposite when considering the effect of fuel source price ratios. In addition, the lifetime environmental performance has been examined for typical cities in China. In the cold region, such as Shenyang, the emission due to the natural gas contributor shares more than 46% of the total emissions. For warm cities (Shanghai, Wuhan, and Chengdu), the emission of the natural gas is only responsible for ~ 9% or even less of the total emissions. A switch from R410A (GWP100:1924) to R452B (GWP100:675) can also lead to ~ 11% emission total reductions for city of Shanghai, Wuhan, and Chengdu. It is anticipated that the viewpoints and insights from this study can be beneficial for the engineers, policymakers, scholars, public, and manufactures to maintaining the maximum sustainability and economic benefits. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we adopt a non-radial directional distance function to analyze the efficiency and shadow price of CO 2 emissions of coal-fired power plants. Using a sample of Shanghai's 20 coal-fired power plants, we find that the efficiency performance of power plants remained steady during the period 2007–2010. On average, the carbon abatement costs of Shanghai's power plants increased from 20.58 yuan/ton to 39.67 yuan/ton during 2007–2010. Although the average shadow price of the power plants increased during the period, the price was still well below shadow prices for the energy consumption of the industries, and a little lower than the trading price in the ETS markets. In addition, the paper discusses the implications of the findings. [ABSTRACT FROM AUTHOR]

The objective of this paper is to optimize the passive design of newly-built residential buildings in hot summer and cold winter region of China for improving indoor thermal comfort while reducing building energy demand. In this respect, this paper investigates the performance of a representative apartment building in the city of Shanghai and evaluates the optimum solutions by using a developed optimization approach, which includes three major steps of 1) setting the model for multi-objective optimization, 2) sensitivity analysis for reducing the dimension of input variables, and 3) multi-objective optimization by using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) coupled with the Artificial Neural Network (ANN), among which a novel indicator for evaluating the annual indoor thermal comfort of residential buildings of Shanghai named Comfort Time Ratio (CTR) is defined based on the modification of Szokolay’s theory in terms of bioclimatic analysis, and the impacts of passive design variables on the indoor thermal comfort and building energy demand in terms of different directions are comprehensively investigated. Results of the multi-objective optimization indicate that the residential buildings of Shanghai have a great potential in comfort-improvement and energy-saving. A series of novel optimal passive design tactics for residential buildings in Shanghai are derived accordingly which could be easily understood and conveniently carried out by the architects in practice. [ABSTRACT FROM AUTHOR]

In order to achieve carbon peak and neutrality goals, many low-carbon operations are implemented in ports. Integrated energy systems that consist of port electricity and cooling loads, wind and PV energy devices, energy storage, and clean fuels are considered as a future technology. In addition, ports are important hubs for the global economy and trade; logistics optimization is also part of their objective, and most port facilities have complex logistics. This article proposes an energy–logistics collaborative optimization method to fully tap the potential of port-integrated energy systems. A logistics–energy system model is established by deeply examining the operational characteristics of logistics systems and their corresponding energy consumption patterns, considering ships' operational statuses, quay crane distribution constraints, and power balances. To better represent the ship–energy–logistics optimization problem, a hybrid system modeling technique is employed. The case of Shanghai Port is studied; the results show that costs can be reduced by 3.27% compared to the traditional optimization method, and a sensitivity analysis demonstrates the robustness of the proposed method. [ABSTRACT FROM AUTHOR]

The renewable electricity quota standard (RES) policy plays an important role in achieving sustainable and green development targets. Thus, it is essential to measure the sustainability of the electric power sectors in the context of RES. In terms of the energy and environmental efficiency (EEE) measurements, few studies divided energy inputs into renewable and non-renewable energy or explored the restricted problem of minimizing resource summation. To fill these gaps, we propose an improved fix-sum energy input data envelopment analysis (FSIDEA) model based on the adjustment strategy of weighted sum minimization of renewable energy inputs. The assurance region (AR) restriction and renewable energy input sum constraint (IC) are, respectively, imposed on the FSIDEA model to achieve the common equilibrium effective frontier (EEF). Finally, this study assesses the EEE of the electric power sectors in China's 30 main regions based on the common EEF. The result reveals that Beijing and Shanghai can be selected as benchmarks after efficiency comparison. In addition, our proposed model can compressively rank all decision-making units (DMUs) compared with traditional efficiency models. [ABSTRACT FROM AUTHOR]

Due to the high dehumidification performance realized by removing adsorption heat by inner cooing, desiccant coated heat exchanger (DCHE) has been proposed and widely studied. The heat pump is usually used as the cooling and heat sources of the dehumidification system composed of DCHE because the cooling and heat capacity could be provided by the heat pump at the same time. Moreover, considering the advantage of low-grade thermal energy utilization, solar thermal energy can be used to further enhance the regeneration of DCHE to improve dehumidification performance and energy efficiency. In this paper, the solar-enhanced fresh air dehumidification system using DCHE driven by heat pump was proposed and a series of experiments were conducted under typical Shanghai summer high humidity conditions. The typical moisture removal of the system can be increased by about 15% to 10.14 g/kgDA and the COP could be further increased by over 25% to 5.39. In addition, the influence of different regeneration temperatures enhanced by solar thermal energy on the system has also been studied. Considering the dehumidification performance improvement and energy utilization efficiency, the optimal regeneration temperature is between 60 °C and 65 °C for the system proposed in this paper. • Moisture removal and COP can be increased by 6%–28% by solar enhanced. • Performance enhanced is more obvious when regeneration temperature is below 65 °C. • Solar enhanced dehumidification 1.43 (g·kgDA−1)/kW and 1.12 kg/kWh can be achieved. • Higher efficiency solar collectors will achieve higher solar enhanced performance. [ABSTRACT FROM AUTHOR]

PV windows are considered to be a promising building-integrated PV technology due to their excellent electrical, daylighting and thermal performance. However, the shading of the PV cells increases the heating load in winter and the high temperature of PV cells exacerbates the cooling load in summer. Moreover, a significant portion of the heat absorbed by the PV modules is usually wasted. To address these issues, this paper proposed a multi-functional PV/T window. This system could recover the heat on PV cells for producing warm air in winter and hot water in other seasons. As a result, the proposed system can realize the combined PV/T utilization of solar energy and reduce the seasonal thermal needs of the building. First, the mathematical model of the proposed window was developed and validated. Next, the developed model was integrated into building energy software to evaluate the overall energy performance of the proposed window in four different cities of Yangtze River region: Shanghai, Nanjing, Wuhan, and Chongqing in China. These cities experience the subtropical humid climate (Cfa in the Köppen-Geiger classification) and belong to the zones with medium global horizontal irradiation. The sensitivity analysis revealed that the optimal slat angles are between 0o and 40o, while the optimal orientation angles range from 30o to 60o. Selecting low-iron glass as the inner glass resulted in the lowest overall energy consumption. By adopting the MFPV/T window, the annual operation cost of the studied case could be reduced by 34% (6.4 $/m2), 36% (7.0 $/m2), 28% (5.7 $/m2), and 16% (2.9 $/m2) in these four cites, respectively. Additionally, the annual CO 2 emissions could be curtailed by 53.5, 58.5, 47, and 22.3 kg/m2, respectively. • A novel PV/T window was proposed for addressing the common issues of PV windows. • The mathematical model of proposed window was developed and validated. • The parameter sensitivity was analyzed. • The overall energy performance was predicted in Yangtze River region. [ABSTRACT FROM AUTHOR]

New energy vehicles are regarded as an important measure for improving air quality, reducing oil dependence, fostering emerging industries, and promoting high-quality development. Since 2009, the Chinese government has been committed to promoting new energy vehicles through various policy measures, such as fiscal subsidies. Meanwhile, the outbreak of the COVID-19 pandemic at the end of 2019 has brought great impact on the economy and society. Thus, it is a topic of research to determine if the fiscal subsidy policy can assist new energy vehicles to resist the pandemic's impact and build consumption resilience. Current researches lack enough attention to the role of fiscal subsidy policy in enhancing consumption resilience under the pandemic impact. By utilizing monthly sales data of new energy vehicles in Shanghai from January 2018 to February 2021, this study employs regression discontinuity (RD) analysis and the combination of the RD with the differences-in-differences (DID) model, to comprehensively evaluate the impact of the COVID-19 pandemic on new energy vehicle consumption and the effectiveness of fiscal subsidy policies in enhancing consumption resilience. The findings reveal that the COVID-19 pandemic shock, with a bandwidth of 3 months, led to a 23% decrease in new energy vehicles sales. In comparison with unsubsidized vehicles, sales of subsidized new energy vehicles significantly increased by 15–80% during the pandemic shock, indicating that fiscal subsidies are crucial in enhancing the consumption resilience of new energy vehicles. Compared with other country-specific new energy vehicles, the subsidy effect of domestic new energy vehicles is relatively inadequate during the pandemic shock. The retreat from subsidy policies has contributed to a decline in the consumption of new energy vehicles in response to the pandemic shock. It is necessary to further improve the consumption resilience of domestic new energy vehicles and pure electric vehicles. [ABSTRACT FROM AUTHOR]

The influence of environmental regulation on haze pollution is a hot issue of scholar's attention. However, different types of environmental regulations have different effects on haze pollution. Based on PM2.5 annual mean data of 30 provinces and cities in China from 2005 to 2016, combined with the threshold effect model to test the nonlinear impact of different types of environmental regulations on haze pollution. The results show the haze pollution in China is still serious, and there are significant regional differences in the distribution of haze pollution. The heavily polluted areas are mainly concentrated in economically developed eastern regions such as Beijing, Tianjin and Shanghai, while haze pollution in the central and western regions is relative light. The threshold effect of formal and informal environmental regulations on haze pollution has significant regional differences. Further, industrial structure and technological level will suppress haze pollution, while structure of energy consumption and openness will promote haze pollution. At last, according to the situation of different regions, we put forward different environmental regulation policies for provinces and cities to control the haze. [ABSTRACT FROM AUTHOR]

In the past, the building energy consumption was surveyed without distinction of air-conditioning system types, which caused large dispersal of the energy consumption of the same building type. To study energy consumption of office buildings using air-source heat pump, six office buildings using air-source heat pump in Shanghai were investigated through energy audit and field test. The energy use intensity (EUI) per annum ranged from 102 to 139 kWh/m2, with an average value of 126 kWh/m2. The EUI range of office buildings using air-source heat pump is much smaller than the EUI of office buildings according to the literature. Based on field test of the air-conditioning (A/C) system, it was found that the present main problem of A/C system included insufficient refrigeration capacity of A/C system, low A/C system energy efficiency, and small cold water temperature difference. Countermeasures were brought forward to solve the problems, including ① retrofitting part of the present air-source heat pumps to water-cooled cold water air-conditioners, ② retrofitting present air-source heat pumps into new air-source heat pumps, and ④ pump variable frequency renovation. The A/C load is estimated by Bin method. According to the case study in this paper, the pay back period are about two years for the first measure, five to seven years for the second measure, and 0.65–2 years for the third measure.Practical application: Generally, the energy consumption survey gives a wide range of data. To some extent, it is caused by the survey method which does not take the air-conditioning type into consideration. The work stresses on the energy consumption of office buildings using air-source heat pump. The result showed that the energy consumption was in a relatively small range, which will be more meaningful to industry. Energy saving measures concerning air-conditioning system is studied on the basis of the survey. [ABSTRACT FROM PUBLISHER]

Shanghai, known as the economic, financial and cultural centre of China, lies in the southern portion of the Yangtze River Basin and is the largest and most prosperous city in mainland China. With a high rate of economic and population growth, Shanghai's demand for energy continues to rise. However, Shanghai is a city with a lack of traditional energy resources, and relies heavily on steady supplies of fossil fuels imported from other regions of China. In order to ensure the optimal use of energy resources and limit the environmental impact, the Shanghai government has launched a new energy strategy and is committed to the development of renewable energy, especially wind power. This paper assesses the wind energy resource in Shanghai, reviews the current status of wind power utilisation, and identifies the major challenges facing the development of a robust wind energy industry in this fastest growing city of China. [ABSTRACT FROM PUBLISHER]

This paper proposes a model predictive control method based on dynamic multi-objective optimization algorithms (MPC_CPDMO-NSGA-II) for reducing freeway congestion and relieving environment impact simultaneously. A new dynamic multi-objective optimization algorithm based on clustering and prediction with NSGA-II (CPDMO-NSGA-II) is proposed. The proposed CPDMO-NSGA-II algorithm is used to realize on-line optimization at each control step in model predictive control. The performance indicators considered in model predictive control consists of total time spent, total travel distance, total emissions and total fuel consumption. Then TOPSIS method is adopted to select an optimal solution from Pareto front obtained from MPC_CPDMO-NSGA-II algorithm and is applied to the VISSIM environment. The control strategies are variable speed limit (VSL) and ramp metering (RM). In order to verify the performance of the proposed algorithm, the proposed algorithm is tested under the simulation environment originated from a real freeway network in Shanghai with one on-ramp. The result is compared with fixed speed limit strategy and single optimization method respectively. Simulation results show that it can effectively alleviate traffic congestion, reduce emissions and fuel consumption, as compared with fixed speed limit strategy and classical model predictive control method based on single optimization method. [ABSTRACT FROM AUTHOR]

• Performance deterioration of CO 2 heat pump water heaters in Shanghai was revealed. • Annual performance factor of heat pump water heaters was proposed and predicted. • Suggestions on system design and control of CO 2 HPWH for long-term operation were made. CO 2 heat pump water heating is an energy-efficient technology and being widely applied in Shanghai. However, its energy efficiency after long-term operation has not been well evaluated so far. In this paper, the energy efficiency and potential issues of CO 2 heat pump water heater after multi-year service are in-depth investigated. In-situ study of CO 2 heat pump water heating systems in Shanghai was carried out. Operating data were collected and field test was conducted. A typical case was chosen for comprehensive analysis. The results show that the annual performance factor (APF) of the actual system is 2.57, relative to 4.12 in its perfect shape. To find out what happened to this system, a simulation model was developed, calibrated and validated with field test data and operating data. In terms of simulations, suggestions were made on the system design and control for long-term performance improvement. [ABSTRACT FROM AUTHOR]

Highlights • We estimate the energy rebound effect caused by technological progress in Shanghai. • We use the state space model with time-varying parameter based on the IPAT identity. • Shanghai has a high partial rebound effect on average at the overall-economy level. • Mitigating the energy rebound effect can significantly reduce carbon emissions. • Energy efficiency improvement should not be the only way to conserve energy. Abstract The energy rebound effect is regarded as an obstacle of achieving the expected target of energy-saving policies, especially under a rapid urbanization background in developing counties, such as China. This has become a substantial drag of sustainable development in some cities. Shanghai is the economic center of China, and it is also a typical energy import-dependent mega-city. Investigating the evolution of Shanghai's energy-saving performance and the energy rebound effect is significant for the implementation of energy-saving policies in other similar cities of China and other developing countries. Using the state space model with time-varying parameters and based on the IPAT identity and the Solow residual approach, this paper is the first study to present a specific estimation on Shanghai's energy rebound effect caused by technological progress. The results show that, during the period of 1991–2016, the average energy rebound effect of overall economy and secondary industry in Shanghai was 93.96% and 73.10%, respectively, indicating a high partial rebound effect. Most of expected energy saving caused by improved energy efficiency is offset by extra energy consumption caused by technological progress. Regarding tertiary industry, the average rebound effect was 146.61%, indicating a backfire effect. However, the average energy rebound amount of tertiary industry is less than that of secondary industry. In particular, there is an increasingly negative impact of the rebound effect of tertiary industry on energy conservation in recent years, with the sector's rapid expansion and corresponding increase in energy demand. Furthermore, we estimate the carbon rebound amount (i.e., carbon emissions caused by the energy rebound effect) and find that, on average, the energy rebound effect caused 13.1% and 0.41% increases in carbon emissions in Shanghai and China, respectively. Therefore, mitigating the energy rebound effect can significantly reduce carbon emissions. Due to the substantial impact of the rebound effect, technological progress and energy efficiency improvement should not be the only way to achieve energy-saving target, especially in energy import-dependent mega-cities like Shanghai. Some supporting policies should be implemented to ensure that the expected outcome of energy-saving effort can be realized as far as possible. [ABSTRACT FROM AUTHOR]

The serious energy crisis and environmental problems resulting from fossil energy excessive consumption have caused severe challenges to the control of energy consumption and intensity (dual controls) and the sustainable development of China's economy and society. The current territorial management model (TMM) of energy consumption "dual control" needs urgent improvement. Therefore, this study proposes an inter-provincial energy consumption transfer tax model (ECTTM) based on the Stackelberg game and bi-level optimization theory. In this model, the central government is the leader at the upper-level, and provincial governments are the lower-level followers. An optimization algorithm based on NSGA-II was designed to solve this model to obtain the optimal transfer tax rate and provincial energy consumption. The ECTTM aims to maximize the socioeconomic benefits of energy consumption overall and in each province under the premise of achieving the dual control target. The model's effectiveness and superiority were illustrated through an empirical study of electricity consumption in Shanghai, Zhejiang, Shaanxi, and Guizhou. Compared with the TMM, the socioeconomic benefits under the ECTTM increased by 14.67%, and the electricity consumption per unit of gross domestic product decreased by 12.8%. Policy suggestions on the ECTTM's implementation are proposed to promote further improvements in dual controls. [ABSTRACT FROM AUTHOR]

The hospitality industry is an important energy consumer and carbon emitter. Behaviour-driven energy conservation is a strategy with great promise to strengthen the energy efficiency of hotel buildings. The aim of this study is to explore the driving psychological factors of hotel guests' energy-saving intentions and behaviours. This paper constructs two extensions of the theory of planned behaviour (TPB) with personal norms, past behaviours, and self-determined motivation to explain the guests' energy-saving behaviour in hotel buildings. This research compares the explanatory power of the original TPB and two extensions with structural equation modelling. The analysis is based on 530 valid, self-reported data from 827 surveyed hotel guests in Shanghai. The analysis suggests that the extended model gains greater explanatory power in predicting the behaviour patterns by employing the above three additional factors. In addition, self-determined motivation presents a more significant impact than other more developed TPB predictors, such as intention and perceived behaviour control. Aside from that, past behaviour replaces attitude as the most critical predictor of hotel energy-saving intention in the extended models. In addition to the existing interventions in office and residential buildings, the research highlights the role of self-determination in hotel energy conservation and further emphasises the long-term benefit of encouraging pro-environmental behaviours in hotel guests. The findings expand the existing research on pro-environmental behaviours and will contribute to energy-saving behaviour intervention in hotel buildings and policy formulations for sustainable hotel operation and maintenance. [ABSTRACT FROM AUTHOR]

The Star-ccm + multiphysics simulation software was used to perform Computer Fluid Dynamic (CFD) simulation on the five operating conditions of a swimming pool at the Jiading Swimming Hall of Tongji University in Shanghai, to determine the energy efficiency of these operations. The indoor environment of each working condition was evaluated. The relationship between the opening and closing area ratio and the indoor environment was also evaluated and obtained the optimal opening area ratio for the Jiading Swimming Hall. The simulation research of the open–closed roof further confirmed that the open–closed roof technology can effectively adjust the internal environment of the swimming pool in summer. The open–closed roof could improve the indoor comfort and reduce the summer energy consumption of the swimming pool and could also provide an organically integrate architectural art feature and technology to create a new stadium design. [ABSTRACT FROM AUTHOR]

The significance of form in green building design is well recognized, as it has a substantial impact on both energy performance and construction cost. This study investigates the impact of the U-shaped plan on the energy demand, which can be flexibly applied to irregular site forms and clustered building blocks, and is widely used in existing office buildings. Specifically, we select the U-shaped plan as the object of study and collect related case data primarily from Hangzhou and Shanghai. Using Python, we generate plans based on two lengths, two angles, and depth, which serve as basic parameters and boundary conditions. The EnergyPlus platform is utilized for dynamic simulation of the energy consumption of each model, and correlation analysis using the Spearman coefficient method identifies two planar factors (depth-length ratio and modified length) that have the most significant influence on energy consumption, including five basic parameters. Regression fitting and regression evaluation of the model further identify morphological critical information in the plan. Our research reveals that the critical interval of depth-length ratio (M1) is in (0.48, 1.02), and the critical point of the modified length (M2) is 109.38 m. Furthermore, the contour plot of M1–M2–E1 is obtained, illustrating the mutual trend between morphological parameters (M1 and M2) and annual energy use intensity, which serves as a useful aid for designing low energy consumption solutions. [ABSTRACT FROM AUTHOR]

Heating, ventilation, and air conditioning (HVAC) systems are the second largest energy consumers on cruise ships after the propulsion system. As a kind of HVAC system, active chilled beam (ACB) systems have been widely used for cabin service due to their performance of energy efficiency and good thermal comfort. However, conventional control strategies for ships' ACB systems are not intelligent enough and cannot balance energy consumption and cabin comfort during the voyages of ships. This study developed an optimal control strategy for cabins' ACB systems. First, a simulation environment considering dynamic conditions is established in TRNSYS. Second, an artificial neural network model is utilized to predict the energy consumption of the ACB system, while the predicted percentage dissatisfied is adopted to represent cabins' thermal discomfort. Third, an improved multi-objective salp swarm algorithm is proposed to dynamically minimize both energy consumption and thermal discomfort. A TRNSYS–MATLAB co-simulation testbed is established to simulate the cabins served by an ACB system on a small cruise ship navigating from Hong Kong to Shanghai for validation tests and a comparison study. Compared to the conventional strategies, the proposed strategy can achieve a maximum energy savings of 12% while maintaining a predicted mean vote index less than 0.5, meeting the comfort requirements set by ASHRAE. [ABSTRACT FROM AUTHOR]

For a certain functional building group, the coupling relationship between the load of a single unit and entire building groups lies in the spatial and temporal patterns personnel distribution. Using the DeST (Designer's Simulation Toolkit) method, the personnel flow trajectory in a university campus in Shanghai was analyzed and the established energy consumption calculation model based on personnel flow trajectory of university buildings. It is proposed that personnel mobility should be included in the application of DeST to predict the total load of building groups. The results show that after the people flow trajectory was included, the total annual accumulated load decreased from 27.01 to 19.39 GWh, reducing by 28.20%; the hourly load fluctuation became more stable, the daily peak load decreased by 22.57%, and the daily peak valley difference decreased by 43.74%. The results suggest that the prediction for the air conditioning load of building complexes would be better when the trajectory of human flow is considered, minimizing unnecessary system scale and investments. Under the "double carbon" policy, the personnel flow trajectory model can effectively reduce waste in air conditioning energy consumption in campus buildings. [ABSTRACT FROM AUTHOR]

Extreme environmental conditions are inappropriate for the cycling of phase change materials (PCMs) attached to building envelopes and have a negative impact on their energy performance. To solve this problem, therefore, thermochromic (TC) coatings are proposed to improve the energy efficiency of PCMs by regulating solar radiation influence. In this paper, the energy performance analysis of TC-PCM systems was carried out in five different representative climate zones. Simulation findings show that, compared to traditional PCM systems (TR-PCM), in the climate characteristics of Shanghai, the annual energy demand of TC-PCM systems decreases by 42.9 kWh/m2, and the corresponding energy-saving rate is high up to 39.9%. This is because the adaptive solar absorptance of TC-PCM systems could enhance the phase change cycle performance of PCMs to reduce both the cooling and heating energy demand. The results also show that the TC-PCM system, with a switching temperature of 26 °C for TC coatings and a transition temperature of 26 °C for PCMs, could achieve the lowest annual energy demand in the climate characteristics of Shanghai. Finally, we investigated that the TC-PCM system has huge potential for energy-savings in all provinces in hot summer and cold winter climate zones, and the highest energy-savings rate can be as high as 10.2%. • The impact of solar absorptance is analyzed in five Chinese representative cities. • TC-PCM systems are more suitable for application in hot summer and cold winter zone. • TC-PCM systems have an excellent ability to reduce both cooling and heating load. • The optimal switching temperature for climate characteristics of Shanghai is 26 °C. • Energy-saving of 10% by TC-PCM is achieved in the climate characteristics of Guangxi. [ABSTRACT FROM AUTHOR]

To recycle regenerative braking energy (RBE) while reducing demand charge in electrified railway, a co‐phase power supply system with hybrid energy storage system (HESS) is implemented. However, the dynamical degradation characteristic of battery is necessary to be considered in optimal operation of HESS. A bi‐level model considering battery degradation is proposed to obtain optimal sizing and operation of HESS. The proposed model includes a novel real‐time energy management strategy (EMS) using average power as thresholds, to effectively reduce the demand charge and energy consumption charge. Thresholds are dynamically adjusted with the consideration of battery capacity degradation. A real measured load profile from Beijing‐Shanghai high speed railway is studied. The results demonstrate that the proposed EMS performs better than previous EMS in cost saving. The dynamically adjusted thresholds of EMS are proved to be essential under the consideration of battery degradation. With the optimal sizing of the HESS, the traction substation can achieve 8.69% annual saving of demand charge and recycle 52.33% of the RBE. The results also show that a traction substation equipped with the HESS yields higher economic benefit than the energy storage systems equipped with only a battery or a supercapacitor. [ABSTRACT FROM AUTHOR]

Summary: China's building energy consumption accounts for 27.5% of China's total energy demand. This amount is increasing because of the considerable increase in the rate of household equipment mostly in air‐conditioning systems. In this study, the TRNSYS simulation tool and improved Battle Royal optimizer (IBRO) is coupled for energy optimization of the building based on the simulation to study the impact of the overhangs optimization. The thermal comfort enhancement is evaluated in three case studies of three different weather conditions in China. To validate the achieved results, a comparison of the optimum values with benchmark cases is performed with consideration of heating and cooling demands, and yearly discomfort percentage. According to the achievements, an improvement can be seen in the comfort level. Also, the cooling demand is decreased by 4.2% for Shanghai. [ABSTRACT FROM AUTHOR]

Obtaining reliable and detailed energy consumption information about building service (BS) systems is an essential prerequisite for identifying energy-saving potential and improving energy efficiency of a building. Therefore, in recent years, energy sub-metering systems have been widely implemented in public buildings in China. A majority of electrical systems and equipment can be directly metered. However, in actual sub-metering systems, the terminal units of heating, ventilation and air conditioning (HVAC) systems, such as fan coils, air handling units and so on, are often mixed with the lighting-plug circuit. This mismatch between theoretical sub-metering systems and actual electricity supply circuits constitutes a lot of challenges in BS system management and control optimization. This study proposed an indirect method to disaggregate the energy consumption of HVAC terminal units from mixed sub-metering data based on the CART algorithm. This method was demonstrated in two buildings in Shanghai. The case study results show that the weighted mean absolute percentage errors (WMAPE) are within 5% and 15% during working hours in the cooling and heating seasons, respectively. [ABSTRACT FROM AUTHOR]

• A linear regression model is proposed to properly evaluate energy consumption index in multifunctional buildings. • The sub-item energy consumption index in multifunctional buildings can be used to predict the energy consumption level in pure functional buildings. • The sub-item energy intensity of each functional zone in multifunctional buildings was obtained, providing reference for energy consumption prediction in Shanghai. Appropriate management of energy consumption provides great support for the sustainable development of buildings and even the whole cities. Nowadays, comprehensive energy consumption monitoring index is widely used in many practical projects to make horizontal comparisons among buildings. However, problems may occur when this method is applied in comprehensive buildings. This paper proposed a method to evaluate the overall energy consumption of buildings based on the energy index obtained from different functional sectors. A linear regression model was developed to predict energy consumption index in multifunctional areas. The model was based on online monitoring data from 30 single functional buildings and 20 multifunctional buildings. The sub-item energy consumption intensity difference between pure hotel buildings and hotel sector in comprehensive buildings was within 4.2%. The deviation of sub-item energy consumption intensity was less than 12% between pure shopping malls and shopping mall sector in comprehensive buildings. As for the pure office buildings and office sector in comprehensive buildings, except for heat pumps and chilled water pumps, the deviations of energy intensity of other sub-items ranged from 3.9% to 16.7%. The results from on-site experiments show that the sub-item energy consumption index obtained from multifunctional buildings had lower error than that of single functional buildings. Therefore, the sub-item energy consumption index can also be used to evaluate energy consumption in pure functional buildings. The model proposed in this paper provides a good reference for the prediction of energy consumption index in large public buildings. [ABSTRACT FROM AUTHOR]

High-quality urbanization is the core for realizing human well-beings, for which reason investigating how the relationship evolves between urbanization and eco-environment is of crucial importance. Differing from the rationale of revealing spatial spillover effects using traditional tests, we consider spatial network characteristics to enrich the notion of local coupling and telecoupling from a relational perspective. First, we adopt coupling coordination degree model (CCDM) and decoupling model (DM) to calculate the urbanization and eco-environment coupling coordination degree (UECCD) and the decoupling index (DI) in 30 provinces and municipalities of China from 2008 to 2017. Second, we use gravity model to construct urbanization and eco-environment coupling coordination network (UECCN), in which provinces are nodes and spatial connection relationships of UECCD are edges between nodes. Third, we introduce social network analysis (SNA) to reveal spatial network characteristics of UECCN without using local spatiotemporal heterogeneity. Finally, we employ spatial econometric model to reveal factors that influence urbanization and eco-environment coupling effect. The major findings and conclusions of this study are summarized as follows. (1) The main subclasses of UECCD and DI are basically uncoordinated patterns with eco-environment lagging and weak decoupling, respectively. (2) Only two spatial agglomeration types of UECCD exist, the high-high (H-H) clustering in Shanghai and the low-low (L-L) clustering in western China, whereas no significant spatial agglomeration effect is observed among most provinces. (3) The distribution characteristics of UECCN are sparse in western China and dense in eastern China, and the spatial correlation strength of UECCN improves. (4) Technological innovation plays a critical role in promoting UECCD, while the total population, per capita disposable income, coupling network structure, and environmental regulations exert significant impact on UECCD. Collectively, we propose to prioritize governance provinces with low UECCD in western China as well as adequately utilize the positive externalities of key node provinces in eastern China. Equally importantly, we suggest that it is also critical to fully exert a driving force of technological innovation on improving the UECCD by promoting renewable energy utilization. [ABSTRACT FROM AUTHOR]

Various measures have been taken to improve ship energy efficiency while decreasing CO2 emissions. In this work, the navigation environment between Wuhan and Shanghai in China has been classified based on an improved K-means algorithm in order to realize route division. A fuel consumption prediction model considering the navigation environment factors has been established. Consequently, speed optimization models with multiple different optimization objectives have been constructed and tested based on an actual case using an artificial fish swarm algorithm. Finally, sensitivity analysis has been carried out focusing on the navigation time, fuel price, charter rate, free carbon credits, and carbon tax rate. The results show that the total shipping cost and CO2 emissions could be reduced by 0.94% and 0.38%, respectively, after the optimization. Considering a carbon tax policy with a tax rate of roughly 1300 RMB/t, the optimization result (including the carbon tax cost) is close to the compromised solution of multi-objective optimization, and the corresponding carbon tax rate can provide a useful reference for policymakers. [ABSTRACT FROM AUTHOR]

Microgrids allow energy exchange among multiple interconnected microgrids for greater energy efficiency and collective economic interest. However, in some cases, the benefit of some microgrids within the network may not be uncertain. In view of the increasing development of electric vehicles (EVs), a multiobjective model is proposed to improve the performance of microgrids by integrating electric vehicles-to-grid (V2G) and vehicles-to-building (V2B) based on global and individual benefit balance. Two reference models are built to verify the validity of the proposed method, and models are formulated as mixed integer linear programming formats solved by the weighting method. A set of parameters of microgrids are adopted to model the driver behaviors (e.g., available hours of EV), energy transactions (e.g., electricity), performance factor (e.g., emission factor), distributed energy (e.g., solar panel), and energy load of five commercial buildings (e.g., hotel) located in Shanghai. Simulation results demonstrate the effectiveness of the operation decision models in the energy management of microgrids under neutral, proeconomic, proenvironmental, and proenergy weighting scenarios. The case study results specify that the proposed method can achieve operational cost, CO2 emission, and primary energy consumption reductions for each microgrid, with total benefits declining slightly. [ABSTRACT FROM AUTHOR]

The construction sector is a critical contributor to energy consumption and greenhouse gas emission. Promotion of green buildings may be a good way to tackle environmental problems. In this study, a choice experiment was undertaken to explore preferences and willingness to pay (WTP) for various attributes of green office buildings in Shanghai, with a sample of 309 respondents. Results of the mixed logit reveal that respondents value attributes relating to indoor comfortability and health, including Quiet Office Environment, Eco-Friendly Construction and Decoration Material, and Indoor Air Purification. Higher WTP is also observed for features of Power Saving and Water Saving, which provide both private and public benefits. According to heterogeneity analysis, people working in offices with a higher rent are more likely to pay for air purifier installation. In general, construction & manufacturing firms have higher WTP for Power Saving while lower WTP for Soundproof. On average, foreign firms are willing to pay more for eco-friendly materials. Finally, implications and suggestions for policymakers and building developers are discussed. [ABSTRACT FROM AUTHOR]

Thermal Energy Storage (TES) systems in Building Combined Cooling, Heating and Power (BCHP) plants are attracting more attentions nowadays in China. In this paper, a simple linear programming optimization model is developed for BCHP systems with an Ice Storage System (ISS), a hybrid Electric Chiller (EC) and Absorption Chiller (AC). Two BCHP systems (one with TES and the other without TES) are compared with the conventional system in a super high-rise building in Shanghai city. The design and operation of both BCHP systems are optimized with the linear programming tool. The results show that natural gas price is the most important factor regarding the economic performance of the BCHP plants, followed by electricity utility price and the price of the prime motor. In this case study, both BCHP options show higher energy use efficiency and better economic performance than the conventional solution. Compared with the BCHP system without TES, the one with TES has similar energy efficiency level, but lower operation cost due to its load shifting capability. Thus, considering the overall life cycle cost, the BCHP system with TES option is suggested to be used in similar high-rise buildings in Shanghai city. [ABSTRACT FROM AUTHOR]

Electric vehicles (EV) are expected to see a rapid growth in next decades as a substantial measure to achieve global climate goal. This course will be an unprecedented event in the industry history, and it will inevitably influence and change the power grid and the transportation network. The projection of EV population is the basis to coordinate the development of EV and urban systems. This paper proposes a modified Bass diffusion model to fulfill this task. Firstly, advantages of Bass diffusion model are analyzed, while car scrappage and technology competition with internal combust engine vehicle (ICEV) are involved to improve the model. Secondly, performance of the proposed model is evaluated with actual data during 2006–2020, and the EV stock up to 2050 is projected with the assessment of uncertainties. Thirdly, the policy on license plate quota and the ban on ICEV sales are discussed through experiment simulation. In a standard growing mode, EV is expected to dominant the new sales market by 2030 in Shanghai, and to completely replace ICEV before 2050. This research can provide a reference for urban power-transportation integrated system planning, renewable energy consumption, and carbon reduction path design. • The Bass diffusion model is modified with car scrappage and technology competition. • Effects of the license plate quota and the fuel vehicle sales ban are discussed. • Data of a pilot city for electric vehicle applications are collected for modeling. • The EV population growth up to 2050 is described with discussion of uncertainties. [ABSTRACT FROM AUTHOR]