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Most of existing photovoltaic (PV)-Trombe wall systems use a single coolant which has the drawbacks of low utilization efficiency and unreasonable heat distribution of space heating. In order to address these problems, a novel micro-channel heat pipe PV-Trombe wall system is proposed in this paper. The system uses heat pipe and Trombe wall to cool the PV collector decreasing its operating temperature and thus improving the overall efficiency. Moreover, an air-cooled condenser is used to control the thermal energy transfer in the room to improve the thermal comfort. The mathematical model of the system under different operation modes is verified to investigate the performance of the system in Lhasa, Beijing and Nanjing. The results show that: (ⅰ) during the space heating mode, the average room temperature of 20.36 °C, 19.80 °C and 20.18 °C can be reached while the daily total power generation of 0.86 kWh, 0.81 kWh, 0.72 kWh can be achieved in Lhasa, Beijing and Nanjing, respectively; (ⅱ) during the hot water mode, the water temperature in the tanks increases only by 8.08°C–12.76 °C and the total power generation is around 0.20 kWh-0.23 kWh in the three cities while the indoor temperature increases by less than 0.1 °C due to the lowest facade solar radiation in summer. • Proposing a novel micro-channel heat pipe photovoltaic-Trombe wall system. • The system can realize multiple functions under different running modes without power equipment. • Establishing a dynamic mathematical model. • Investigating the performance of the system in representative cities in China. [ABSTRACT FROM AUTHOR]

Improving energy efficiency is one of the most effective ways to reduce energy waste and achieve carbon neutrality, but it may also bring the energy rebound effect and thus fail to achieve the desired energy conservations. In this paper, we examine the energy rebound effect of Beijing at the level of overall economy, industry and sector based on the Cobb-Douglas production function and the idea of Solow residual, so as to clarify the true impact of technological progress on energy-saving target. Results suggest that: (1) The overall economy of Beijing shows partial rebound effect in most years and appears backfire effect in some years, but the degree of the rebound effect has been gradually mitigated; (2) The energy rebound degree of the tertiary industry is higher than that of the secondary industry on the whole, but the rebound effect of the secondary industry fluctuates more obviously; (3) Energy savings at the sector level is also not ideal, and in most cases, sectors with low energy efficiency have a higher rebound effect than sectors with high energy efficiency. Based on these results, suggestions are provided to alleviate the energy rebound effect of Beijing. • The energy rebound effect of Beijing are quantified at the level of overall economy, industry and sector. • The overall economy of Beijing appears backfire effect and partial rebound effect. • The energy rebound effect of the tertiary industry is higher than that of the secondary industry in most years. • Sectors with low energy efficiency may have higher rebound effects. [ABSTRACT FROM AUTHOR]

Station-skipping and deadheading for subway operation regulations are two effective ways to reduce the effects of train variations, such as large passenger flow and unexpected incidents. These variations, if not properly eliminated through strategies, will lead to a gap in the train and eventually increase passenger waiting time and energy consumption. This paper addresses the last-train station-skipping, transfer-accessible, and energy-efficient scheduling problem for the subway system by optimizing the subway schedule and the last train station-skipping scheme. First, an integrated last train operational model was developed to achieve energy savings and better performance of transfer waiting and in-train travel times by adjusting train acceleration, cruising, coasting, and braking times on each rail segment. Second, a heuristic evaluation-based optimization algorithm was designed to solve a real-life case study of the Beijing Subway to demonstrate the effectiveness of our methods. Two operational strategies (station-skipping and deadheading) for the last trains were designed and compared quantitatively. The results indicate that the station-skipping plan shows an advantage in minimizing the in-train travel time and energy consumption. (1) This paper proposes the integrated last-train station-skipping, transfer-accessible, and energy-efficient scheduling problem for the subway system. (2) By optimizing train acceleration, cruising, coasting, and braking times on each rail segment, energy consumptions and train operating times are reduced. (3) Station-skipping and deadheading strategies for the last train operations are designed. (4) A heuristic evaluation-based optimization algorithm is designed to solve a real-life case study of the Beijing Subway. [ABSTRACT FROM AUTHOR]

The national and municipal government of China enacted a series of regulations and policies to stimulate/promote the development of new energy vehicles, in order to mitigate the increasingly serious carbon emissions, environmental pollution, and energy shortage. As a large metropolitan and populated city subject to the notorious air pollution, Beijing has been making a remarkable progress in the large-scale demonstration of new energy vehicles in recent years, which could result in a significant impact on both transport and electricity sectors. As a result, there is an urgent necessity to study the characteristics of the large-scale new energy vehicles adoption for a deep understanding of operational status (e.g., energy consumption and battery charging patterns) and benefits, as well as charging facilities. Based on the operational data collected from realistic electric-taxi demonstration in Beijing, the driver behavior and charging characteristics are examined in this paper. The energy consumption and efficiency of two representative electric-taxi platforms are compared, and the influence of the driving schedules is discussed. The results show that the average driving distance per day of these electric taxes is 117.98 km, and 92% of drivers recharge their cars twice per day. Further study shows that the drivers make two trips per day, and the two peaks in the distribution of departure and arrival times coincide with the rush hour in the morning and evening. The taxi recharge duration is largely influenced by the charging power. Generally, the associated battery SOC (state of charge) swing is between 40% and 100%. By evaluating the energy consumption of 282 trips recorded in 2013 and 2014, we find that the two platforms have similar energy efficiency. The micro-trips method is utilized to probe the correlation of energy consumption and average speed. [ABSTRACT FROM AUTHOR]