This work proposes a novel design incorporating a passive heat recovery device into a windcatcher and investigates its performance using numerical and experimental analysis. Numerical modelling and experimental testing were used to characterise the radial blade design of the heat recovery rotary wheel in terms of performance. Two configurations of the radial blades provide data that can be used to assess how air velocity is affected by the design, the pressure drop across the device and the heat transfer capabilities of the radial blades. To further assess the potential of the proposed devices, it was incorporated into a multi-directional windcatcher ventilating a small room. Despite the blockage of the rotary heat recovery wheel, it was able able to provide adequate ventilation. In addition to sufficient ventilation, the heat in the exhaust airstreams was captured and transferred to the incoming airstream, raising the temperature between 0.5-4K depending on the indoor/outdoor conditions, this passive recovery has the potential to reduce demand on space heating systems.
Owing to the rapid development of the global economy, the demand for energy and water resources is the main global challenge in the 21st century. This article focuses on the consumption and transfer of the water resources in China’s West–East electricity transmission project. The input–output method is employed to construct a water footprint assessment model for this project. Results show that 606.4 billion kWh of electricity and 2.5 billion m3 of virtual water were transferred from the western to eastern region in 2016. Coordinated policy making the optimal use of water resources for energy generation needs to be further discussed for promoting sustainable regional development.
Energy is vital in modern society and almost in every production process for sustainable economic growth. China is developing country and poverty is always higher especially in rural areas. The study examines the relationship between renewable energy (RE), as whole & by sources solar, wind, geothermal, foreign direct investment (FDI) and poverty alleviation (PA) for sustainable economic development in China. Ordinary Leas Square OLS and Fully Modified OLS methods are use in this study. The results found that there is long run relationship between variables and increase in investment and renewable energy sources production to reduce the poverty. Poverty causes lack of income and production resources, poor infrastructure, inequality and social discrimination. China first needed to overcome these issues for poverty alleviation for sustainable economic development.
The dynamic responses of Solid oxide fuel cell (SOFC) power system across multiple time scales from micro seconds to minutes due to the phenomena of different nature that governing. Mismatching the time scale differences may lead to fuel starving and thermal shock during the fast load following. In this paper, the singular perturbation (SP) theory was introduced for modeling the mutli-time scale system dynamics. The dynamic model of SOFC power system in the coordinates in which slow and fast variables were explicitly defined and exactly separated. The resulting multi-single time scale models facilitate a better understanding of system dynamics, key parameters and their interactions, such as temperature, mass flow rate, current and voltage. Effective SOFC power system controllers can be designed based on these results.
Hydro power production strictly depends on the geography and weather peculiarity of locations where power plants are settled. In this paper, we produce long term estimates of hydro power capacity factors for all European countries based on future climate scenarios. We use machine learning techniques for formalizing models able to capture the complex relation between climate variables and energy production on a European scale and use the results of regional and global climate models for future projections.
Promoting clean heating in winter in the northern region is related to the warmth of the masses in the northern region and whether fog and haze can be reduced. On the basis of summarizing the current situation of heating in rural areas of northern China, this paper expounds the practical problems and basic needs of clean heating. Taking Shandong as the research object, this paper studies the applicability of different modes of clean heating technology in rural areas of North China.The author calculates the heat load demand during heating period, screens the suitable clean heating technology in Shandong area, and obtains the suitable technical path and application mode for rural clean heating in Shandong area.The technical feasibility, economic feasibility and environmental impact of different modes of clean heating, such as solar heating, gas heating and biomass pyrolysis multi-generation heating, are analyzed. The results show that under the existing economic and technological conditions, biomass pyrolysis polygeneration is suitable for clean heating in rural areas of Shandong Province, especially for demonstration and promotion of small centralized or decentralized heating in natural villages or new rural communities. This study provides a new way to solve the problem of clean heating in rural areas of northern China.
Hourly energy readings from heat billing meters are valuable data source for energy performance assessment of district heating substations and the buildings they serve. The quality of such analyses is bounded by the accuracy of the hourly readings. Thus, assessing the accuracy of the hourly heat meter readings is a necessary (but often overlooked) first step to ensure qualitative subsequent analyses. Due to often limited bandwidth capacity hourly readings are quantized before transmission, which can cause severe information loss. In this paper we study 266 Swedish heat meters and assess the quantization effect by information entropy ranking. Further, a detailed comparison is conducted with three heat meters with typically occurring quantization errors. Uncertainty due to the quantization effect is compared with the uncertainty due to typical accuracy of the meter instrumentation. A method to conflate information from both energy readings and energy calculated from flow and temperature readings is developed. The developed conflation method is shown to be able to decrease uncertainty for heat meters with severely quantized energy readings. However, it is concluded that a preferable approach is to work with the heat meter infrastructure to ensure future recorded readings holds high enough quality to be useful for energy performance assessments with hourly or subhourly readings.
Optical fiber daylighting system is a promising alternative for indoor illumination, which provides not only comfortable and safe lighting but also environmental benefits. Economic analysis results show that, total cost of traditional fluorescent lighting system is higher than that of hybrid optical fiber daylighting system after 7 years of operation. In addition, results of environmental benefits for the studied case show that, an annual average 39410kg of CO2 emission can be reduced when traditional lighting system is replaced by the hybrid daylight system. The potential of applying the hybrid optical fiber daylighting system to save energy and protect environment is promising.
In this study the performance characteristic of a CO2 ejector-expansion system applied for battery pack cooling is investigated. An experimental bench is set up and the performance of the system is experimentally studied under different working conditions. The cooling capacity and COP of the system decrease with the increasing of gas cooler outlet temperature. There is an optimal opening degree of EEV for both the capacity and COP to get a maximum value. The entrainment ratio of the ejector is improved by introducing an IHX. Compared with the basic cycle, ejector-expansion system can improve both the cooling capacity and COP significantly, around 21.7% increment in cooling capacity and 28.0% increment in COP, respectively.
With the large-scale penetration of electric vehicles, the research on the influence factors of energy consumption of electric vehicles has become an important requirement for the estimation of energy efficiency, energy-saving route planning and the optimal design of power system structure. In this paper, the real-world driving data of 59 electric taxis in Beijing are obtained and divided into three-level driving fragments. The influence factors of energy consumption, including vehicle-related factors (velocity, acceleration and kinematic states), environment-related factors (ambient temperature and traffic condition) as well as driver-related factors are extracted and studied. Results show that the energy consumption of electric vehicle is significantly influenced by velocity, acceleration and kinematic states. Benefit from the energy-saving at idling state and the braking energy regeneration technology, traffic congestion has a slighter influence on energy consumption. Besides, the appropriate ambient temperature around 19.5℃ and moderate driving pattern can help reduce energy consumption to a certain extent. This work builds an essential foundation for accurate estimation and prediction of energy consumption of electric vehicles.