Abstract

At present the medium-deep borehole heat exchanger (MDBHE) performance was usually analyzed under the typical condition that inlet fluid temperature is deemed as constant. In practical application, inlet temperature is often related to the heating load. In this paper, the effects of heating load on the heat transfer performance of the MDBHE was investigated based on the proposed numerical model which has been validated. The sensitive analysis was implemented to analyze the variation regulations of inlet and outlet temperatures of pipe and thermal effect radius of rocksoil under different heating loads. Furthermore, the MDBHE performance was compared between the two scenarios: constant heating load and constant inlet temperature. The simulation results indicated that under high heating load, the fluid temperature of MDBHE varies substantially during the heat transfer process. Besides, annual drop of inlet temperature should be paid attention. The rock-soil temperature in vertical direction was influenced significantly by the heating load, while the thermal effect radius of rock-soil was affected slightly.

Abstract

To obtain a deep understanding of the pyrolysis mechanism of oil shale kerogen, critical organic intermediate——thermal bitumen was firstly prepared by heating Fushun oil shale up to the critical temperature point (450℃), and then extracted by IL(BmimCl) which was mixed with NMP. Scanning electron microscope, X-ray diffraction, Fourier transform infrared spectrophotometry and flash pyrolysis-gas chromatography-mass spectrometry were employed to investigate the physical and chemical transformation in oil shale pyrolysis and extraction processes. Results showed that thermal bitumen was mainly composed of aliphatic structures. In the thermolysis and extraction courses, aliphatic structures have poor stability by comparison of peak intensities. Thermal bitumen mainly comprised short and middle-chain alkanes/alkenes in the range from C4 to C26.

Abstract

There is a unity of opposites between energy and economy. In order to comprehensively consider the relationship of energy economy, this paper is based on the literature visualization analysis software CITESPACE for co-citation analysis, co-word analysis, cluster analysis, etc. The material of its operation is 2964 articles on energy economic research included in the core of web of science. (From 1998 to 2018) The results show that the results of energy economic research have risen sharply since 2015, and technology and energy are the core of the energy economy; Long-term concerns such as “sustainability”, “innovation”, “efficiency”, “climate change”, “carbon dioxide emissions” and “economic growth” need to be further implemented；Development paths such as “turning”, “replacement”, “co-integration”, “renewable energy” and “elasticity” will continue to be research hotspots; In the process of analyzing the energy economy, tools such as “cge model”,” penal data”, and “data envelopment analysis” will continue to be hot topics in the study of energy economic equilibrium.

Abstract

Petroleum contributes to more than 90% of the total energy consumption mix in the transport system, and transport emission releases approximately 14% of total greenhouse gas emission. To achieve emission reduction target of the transport sector, vehicle electrification is widely discussed under the concept of the next generation transportation system. In this study, we select Tokyo city as case study and collect personal travel data across the year of 2011. Travel model is classified by walk, bicycle, train and vehicle by Big Data. After capturing gasoline consumption distribution, this study further discusses the carbon emission distribution by city-scale input-output data. Findings firstly indicate the transport emission distribution has largely relocated after the vehicle electrification. The result also shows although the indirect emission after electrification has increased 1.167 times than before, the total emission has decreased by 73% and has a considerable reduction potentiality in the future.

Abstract

This paper introduces an energy management strategy that combines visual perception and deep reinforcement learning (DRL) algorithms to minimize fuel consumption. The proposed method is capable of autonomously learning the optimal control policy without any prediction efforts. We used a monocular camera in the windshield of a car to catch visual information as inputs. Next, we used state-of-the-art convolutional neural networks based object detection methods to detect and classify traffic light. The traffic light information is used as a state input for a model-free deep reinforcement learning based energy management system with continuous control action. Hence, the traffic light information is incorporated into the energy management system. The experimental results indicate that the fuel economy of the proposed vision-aided strategy achieves 94.5% of dynamic programming-based method’s, and is 6.8% better than that of the original DRL algorithm without traffic light information under a real-world driving cycle.

Abstract

In this paper, a state of charge (SOC)estimation method for lithium battery based on extended Kalman filter is proposed, and the estimation accuracy of SOC for lithium battery at different temperatures is analyzed. Firstly, a Thevenin equivalent circuit model is adapted to describe the battery considering model complexity, model accuracy and robustness of the model. Secondly, battery capacity and dynamic working condition experiment are carried out based on the battery test bench. Then, battery model parameters are identified by Forgetting Factor Recursive Least Square Algorithms (FFLS) based on China City Bus Cycle (CCBC) experiment data at different temperatures. Last but not least, a state of charge estimation method based on Extended Kalman Filter is adapted and the estimation accuracy is analyzed base on Urban Dynamometer Driving Schedule (UDDS). The results show that the estimation error is less than 4% in different temperatures based on the proposed method.

Abstract

The simulation and experiment of two 400 W low-speed direct-drive permanent magnet synchronous generators (PMSGs) installed in a Floating Kuroshio Turbine (FKT) was implemented. We used ANSYS Maxwell design tool to design the 400 W low-speed direct-drive PMSG and simulate the interior magnetic field at different conditions. The test of FKT was carried out in the towing tank in National Taiwan University. The result shows generated power is more than 800 W in direct current (DC) at 1.5 m/s flow rate. The energy conversion efficiency of the PMSG measured from the testing platform is about 0.85. The power coefficient of FKT is about 0.4. It means FKT has high efficiency and stable power output.

Abstract

A dispatch method with synergy and interaction between integrated energy hub and users was put forward aimed at the problems of failure to consider the thermal storage characteristics of building envelopes and demand response subsidy mechanisms for users during the operation and dispatch of integrated energy hub. First of all, a building virtual storage model was established with the indoor air and building envelope as the main part of heat transfer through comprehensive consideration of influences of indoor and outdoor disturbances on thermal process, and a mathematical model of building virtual storage with equivalent storage and discharge power was put forward; secondly, a typical equipment composition structure of integrated energy hub with supply of cooling, heating and power systems and a multi-agent interactive transaction relationship among external power companies, integrated energy hub and users were established, and a stimulating demand response mechanism based on user subsidy was put forward; thirdly, an optimized economic dispatch model of integrated energy hub was established with the maximum earnings of power station as the target, containing external power purchase expenses, incomes through selling power to users, and subsidies and with the flexible comfort level of users as constraints, and the CPLEX solver was adopted to solve the problems; finally, the practicability and effectiveness of the expressed model and method was verified through examples.

Abstract

District energy systems have been shown to improve energy efficiency, GHG emission reduction, and air quality, yet they are not as widely adopted as these benefits would imply. Extensive studies have been conducted to optimize district energy system design but typically focus on optimization for low carbon emissions and low life cycle cost, ignoring optimization of capital expense (CAPEX) during critical ramp-up. This paper proposes an analytical framework using Integer Programming for district energy system design and installation to simultaneously optimize CAPEX phasing and OPEX (operating expense) including ramp-up and operations. A case study was conducted with preliminary results showing that CAPEX and OPEX could be reduced by 3% and 5% respectively. This approach brings significant advantages to the project predictability and profitability thus strongly promotes the use of district energy technologies.

Abstract

The use of SF6/N2 or SF6/CO2 mixture gas as a potential alternative to SF6 has attracted wide attention due to the easy availability of N2 and CO2, stable chemical and physical properties, non‐toxicity, nonflammability, and non‐combustion. In this paper, the simulation study of the arc formation process in the circuit breaker is carried out from a microscopic point of view. The simulation is based on the gas dynamics equation considering the complex collisions between charged particles and neutral molecules and obtaining the time‐varying law of the micro‐parameters such as the electron density and average electron energy in the arc forming process of SF6/N2 and SF6/CO2 mixture gas. The results can help us understand the characteristics of the mixture gas arc from the microscopic level, and provide a theoretical basis for the design and manufacture of the new circuit breaker.