Abstract

By analyzing the comprehensive operation cost of the power supply company and the air conditioner load aggregator and the electricity consumption cost of the air conditioner user, the operation strategy of storing electricity by using the electricity trough, using the power peak and releasing the power with the level section, and adjusting the power of the refrigeration unit to achieve the The optimal scheduling of the ice storage trough output improves the system’s ability to dissipate wind. A multi-objective optimization model based on energy efficiency and economy was established to maximize the benefits of power supply companies, airconditioning load aggregators and air-conditioning users. The non-dominated sorting genetic algorithm-II (NSGAII) is used to solve the Pareto non-dominated solution set. The generated Pareto solution set is filtered by the fuzzy membership method to obtain the optimal solution. The simulation results of the IEEE ⁃ 37 distribution system are used to verify the effectiveness and feasibility of the proposed method.

Abstract

Soft Open Points (SOPs) have the ability to regulate the power flow among their terminals in a continuous manner, which can solve the problems brought by the synergy of distribution networks and PV, and improve the system reliability and power supply capability. To address the current lack of quantitative measurement on the effects of SOPs, the power supply capability evaluation method for active distribution networks with four-terminal SOPs considering reliability is proposed. Firstly, the topology and configuration modes of fourterminal SOPs are studied, and the control modes of them are investigated in normal operation and supply restoration conditions. Then, using the feeder partition method, the effects of four-terminal SOPs on the states of different load areas after a fault are studied, and the reliability evaluation process for active distribution networks with four-terminal SOPs is developed based on the quasi Monte Carlo method. Later, with reliability as the main constraint, the power supply capability evaluation model for active distribution networks with four-terminal SOPs is established, and the solution algorithm is proposed. Finally, the effectiveness and applicability of the method proposed are verified through case study.

Abstract

IPCC special report on Global Warming of 1.5°C presents the assessment based on available scientific literature that accelerated deep decarbonization is at the core of global mitigation strategy consistent with 1.5°C warming compared to pre-industrial level. The same report also presents the high agreement and robust evidence of risks evaluated by the scientific community in faster and deeper mitigation strategies through possible threats to multiple social and economic dimensions of sustainable development for countries with high dependency on fossil fuels for revenue, economic development and employment generation. The same concerns are coming from literature on just transition which are representing voices around possible job loss, loss of investment flow despite new resource identification, high risks of stranded assets, lower revenue earning with fluctuating oil and gas prices, dwindling resources. Another set of literature on policy instruments talk of need for diversification of economy and energy sector to ease these adverse consequences of transition and need for creating enabling conditions. The diversification discourse is mostly dominated by focus on new investment opportunities limited to wind and solar energy sectors. Also, the countries at risk discussion get dominated by GCC (Gulf Countries Council) countries. All these discourses ignore multiple challenges and realities in many small but fast emerging developing country perspectives. So, the research question for this paper is how can accelerated global transition address the ‘trio’: ‘just, sustainable and peaceful transition’ through cooperation for oil and gas dependent developing countries and what is the potential for leapfrog. We refer this ‘trio’ with reference to oil and gas based fossil fuel energy systems which is caught up in a complex combination of problems due to likely uncertainty and redundancy of human resource currently engaged in the sector, stranded asset due to prospective early retirement of infrastructure and projected reduction in investment and need for finding substitute of fossil based energy carrier to cleaner, renewable energy carrier. Our hypothesis is that for Bangladesh endowed with gas resources and drilling infrastructure one of the transition path can be through geothermal energy system. The policy can encompass objectives of scaling up contributions of renewable energy to electricity production, promoting appropriate, efficient and environment friendly use of renewable energy and promoting clean energy as the country is facing risk of natural gas depletion. However, currently policies make no reference to geothermal potential as a part of the solution. So this study will make a novel and unique contribution in the subject and discourse.

Abstract

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.

Abstract

Thermoelectric generation technology can be used for waste heat recovery of internal combustion engines to improve energy efficiency. In this study, the performance of a thermoelectric generator for exhaust heat recovery of a diesel engine under various operation conditions are analyzed. First, a three-dimensional model of the thermoelectric generator is built by CATIA software. The thermoelectric chip of TEP1-1264-3.4 is used in this study and its characteristic data such as Seeback coefficient, thermal conductivity, and internal resistance are modeled by different maps in MATLAB. Then, a mathematical model of the thermoelectric generator is setup and a finite volume method is employed to obtain a high accuracy. The results indicate that the power output of the thermoelectric generator is increased while the thermoelectric conversion efficiency reduces as the engine load increases. On the hand, the power output of the thermoelectric generator is decreased but the thermoelectric conversion efficiency is increased as the engine load rises.

Abstract

This paper experimentally investigates the chemisorption refrigeration technology, mixing carboncoated Nickel and Iron (Ni@C and Fe@C) with the conventional composite of MnCl2-EG as the sorbents. A modified manufacture methodology is developed and reported. The thermal conductivity is improved by the nanomaterials with a maximum increase of 3.0 %, and adsorption and desorption are accelerated as well. SCP of the sorbents is enhanced up to 11.02 %, indicating the enhancement of the low-grade heat conversing into the cooling power, by the application of MnCl2-EGNi/Al@C chemisorption.

Abstract

China has launched lots of environmental policies to address the serious air pollution. The effectiveness of such kinds of policies are still in debate. Whether the policy makes a difference or not, this article argues that it highly depends on policy targets recognition. To take the motor vehicle restriction policy as an example, the target of the policy may not only focus on developing the air condition, but also other objectives. This on-hand article conducts a regression discontinuity design to test two goals of Zhengzhou city’s motor vehicle restrictions policy which are efficiency target (“help to complete the political assessment goal”) and legitimacy target (“help to achieve pollution control goal”). This article measures the former goal based on daily data and the latter one based on monthly data, both from Jan. 2016 to Dec. 2018. Air quality is selected by monthly air monitoring station, economic activities data is sorted from the official statistic website, and government action data is collected from the government documents by hand which we follow seriously and scientifically coding rules. Other factors, like climate influences, consumption and production behavior, are also controlled in the experiment. Regression results show that the restriction policy doesn’t make an obvious difference on developing the air quality before and after, but it does have statistically significant effect on helping the urban government to achieve the political assessment goal of the so-called “Qualified days”. The experiment also adjusts the bandwidth of the policy timing. The results obtained were highly robust across a variety of tests. What’s more, to make explanations on the restriction policy failure, this article collects the vehicle selling data and gasoline consumption data during the same period to test the policy spillover effect on consumer behavior. Results show that the driving restriction policy lead to an obvious otherwise slight increase on consumers’ behavior of buying a second car or using the alternative car. This study contributes to empirical evidence and add to a new case of researches on the air pollutants governance and policy evaluation.

Abstract

Developing electric vehicles has become a common solution for the energy security problem and air pollution. In the field of electric vehicles, distributed drive is considered to be one of the cutting-edge technologies. It has advantages of flexible control, fast response and has shown great potential in terms of dynamic performance and energy saving, at the same time it has also brought some hotspot problems, such as torque distribution between drive wheels and dynamic control of each drive wheel. This research focuses on energy efficiency and dynamic response optimization of distributed drive electric vehicles. In terms of optimizing energy efficiency, most of existing researches for torque distribution are based on models, which means the control algorithm needs either accurate models of target vehicle or large quantities of calibration data. In this research, a torque distribution method based on golden ratio search algorithm is adopted, which can realize optimized torque distribution between front and rear axles while don’t need any target models. However, the main problem of this method is torque ripple in the process of searching. In order to solve this problem, an automatic calibration method of optimized torque distribution is proposed, which can solve the torque ripple problem successfully. After that, optimized torque distribution between four wheels when vehicle is turning is also studied, and its energy saving potential comparing with front and rear axle torque distribution method is analyzed. A joint simulation platform between Matlab/Simulink and Carsim has been set up to verify the function of automatic calibration method of optimized torque distribution. Results show that with the proposed torque distribution method, up to 12.5% of energy can be saved in NEDC cycle and 7.4% of energy can be saved in China’s typical cycle of city passenger cars. To further verify the feasibility of the proposed torque control methods in real application, two kinds of HIL (hardware in the loop) simulation platforms are set up. One is based on Matlab xPC platform, the other is based on communication between two controllers. With automatic code generation technology, algorithm models in Simulink are translated into executable code and downloaded to KPV13 rapid prototyping controller. The controller is tested in both of the two HIL simulation platforms. Results show that operation and communication speed of real control systems can satisfy the requirement of real-time search algorithm, the proposed control method can be applied in real control systems.

Abstract

Thermoacoustic heat engines are promising devices converting thermal power into acoustic power with the distinct merits of simplicity, and possibility for utilizing low-grade heat sources. As well known, design parameters are usually determined based on weakly non-linear thermoacoustics theory which of course produces significant deviations due to non-capturing of nonlinear phenomena. In order to improve inaccurate predictions of onset temperature obtained by DeltaEC linear thermoacoustic model, artificial neural network is first proposed to be hybridized with DeltaEC model to provide a new synergistic approach. This synergistic approach was applied to a twin thermoacoustic heat engine for improving the computational efficiency of DeltaEC model itself through considering some nonlinearities existing in the whole thermoacoustic system. The onset temperature was predicted as the responses to both resonator length and charging pressure and the obtained results had been proven to be desirable in their accuracy compared to experimental ones and better than literature DeltaEC results under same given conditions.

Abstract

Water content is one of the most significant internal states which affects the performance and durability of proton exchange membrane fuel cells (PEMFCs). However, water content inside fuel cells is difficult to be directly measured. This study aims at developing a new method to fast estimate the water content inside fuel cells. We investigated the relationship between water content and the exhaust back pressure of fuel cells, which indicated that the exhaust back pressure is positively correlated with exhaust water concentration. Then, a two-step algorithm was proposed to estimate water content inside fuel cells. Finally, this algorithm was validated by high frequency resistance experiments. This new estimation method can calculate water content inside fuel cells quickly and is important in developing real-time control strategy.