A convective wind resource model for Solar Vortex power generation

ABSTRACT

Climate change has increased the need for clean, nonpolluting energy sources to decrease dependence on fossil fuels. Alternative energy sources, mainly solar and horizontal wind, have been the primary focus for producing clean energy. New technologies are being developed, such as the Solar Vortex (SoV), which was developed at the Georgia Institute of Technology, and relies on a vertical wind resource to generate power. The National Renewable Energy Lab (NREL) has resource models representing solar and horizontal wind resources across the 48 United States. This research developed a vertical wind resource model that is comparable in resolution to NREL’s solar and horizontal wind resource models and uses the model for estimating power output for the SoV. This model complements NREL’s existing resource models and supports the deployment of an additional clean energy generation technology. The model was applied to Mesa, Arizona to find feasible sites for a small-scale vertical wind farm.     

Integrated energy management strategy of powertrain and cooling system for PHEV

ABSTRACT

Energy management strategy (EMS) is crucial in improving the fuel economy of plug-in hybrid electric vehicle (PHEV). Existing studies on EMS mostly manage powertrain and cooling system separately which cannot get the minimum total energy consumption. This paper aims to propose a novel EMS for a new type of dual-motor planetary-coupled PHEV, which considers cooling power demand and effect of temperature on fuel economy. Temperature-modified engine model, lithium-ion battery model, two motors, and cooling system models are established. Firstly, the separated EMS (S-EMS) is designed which manages powertrain and cooling system separately. Sequentially, after the analysis of thermal characteristics of the powertrain and cooling system, the thermal-based EMS (T-EMS) is then proposed to manage two systems coordinately. In T-EMS, cooling power demand and the charging/discharging energy of motors are calculated as equivalent fuel consumption and integrated into the object function. Besides, a fuzzy controller is also established to deicide the fuel-electricity equivalent factor with consideration of the effect of temperature and state of charge on powertrain efficiency. Finally, the hardware-in-loop experiment is carried out to validate the real-time effect of EMS under the New European Driving Cycle. The result shows that cooling power demand and temperature can significantly affect the fuel economy of the vehicle. T-EMS shows better performance in fuel economy than S-EMS. The equivalent fuel consumption of the cooling system of T-EMS decreases by 27% compared with that of S-EMS. The total equivalent fuel consumption over the entire trip of PHEV using T-EMS is reduced by 9.7%.     

Natural gas engine driven heat pump system – a case study of an office building

ABSTRACT

An eQUEST model was developed to conduct a simulation study of a natural gas engine-driven heat pump (GEHP) for an office building in Woodstock, Ontario, Canada. Prior to the installation of the GEHP, the heating and cooling demands of the office building were provided by rooftop units (RTUs), comprising of natural gas heater and electric air conditioner. Energy consumption for both GEHP and RTUs were monitored for operation in alternating months. These recorded energy consumptions along with weather data were used in the regression analysis. The developed eQUEST models were validated and calibrated with the regression analysis results with respect to the ASHRAE Guideline 14–2014. The eventual models were then applied to investigate the potential annual energy consumption, greenhouse gas (GHG) emission and energy cost savings achieved by using the GEHP in Woodstock, and other cities in Canada, particularly in Ontario.     

Energy consumption estimation model for dual-motor electric vehicles based on multiple linear regression

ABSTRACT

The drive range of electric vehicle (EV) is one of the major limitations that impedes its universalism. A great deal of research has been devoted to drive range improvement of EV, an accurate and efficiency energy consumption estimation plays a crucial role in these researches. However, the majority of EV’s energy consumption estimation models are based on single motor EV, these models are not suitable for dual-motor EVs, which are composed of more complex transmission mechanisms and multiple operating modes. Thus, an energy consumption estimation model for dual-motor EV is proposed to estimate battery power. This article focuses on studying the operating modes and system efficiency in each operating mode. The limitation of working area of each mode ensures the vehicle dynamic performance, then PSO algorithm is adopted to optimize the torque (speed) distribution between two motors to improve the system efficiency in the coupled driving mode. Finally, the energy consumption estimation model is established by multiple linear regression (MLR). The result shows that the proposed model has a high precision in energy consumption estimation of dual-motor EV.     

Risk-based optimal operation of hybrid power system using multiobjective optimization

ABSTRACT

This paper solves an optimal generation scheduling problem of hybrid power system considering the risk factor due to uncertain/intermittent nature of renewable energy resources (RERs) and electric vehicles (EVs). The hybrid power system considered in this work includes thermal generating units, RERs such as wind and solar photovoltaic (PV) units, battery energy storage systems (BESSs) and electric vehicles (EVs). Here, the two objective functions are formulated, i.e., minimization of operating cost and system risk, to develop an optimum scheduling strategy of hybrid power system. The objective of proposed approach is to minimize operating cost and system risk levels simultaneously. The operating cost minimization objective consists of costs due to thermal generators, wind farms, solar PV units, EVs, BESSs, and adjustment cost due to uncertainties in RERs and EVs. In this work, Conditional Value at Risk (CVaR) is considered as the risk index, and it is used to quantify the risk due to intermittent nature of RERs and EVs. The main contribution of this paper lies in its ability to determine the optimal generation schedules by optimizing operating cost and risk. These two objectives are solved by using a multiobjective-based nondominated sorting genetic algorithm-II (NSGA-II) algorithm, and it is used to develop a Pareto optimal front. A best-compromised solution is obtained by using fuzzy min-max approach. The proposed approach has been implemented on modified IEEE 30 bus and practical Indian 75 bus test systems. The obtained results show the best-compromised solution between operating cost and system risk level, and the suitability of CVaR for the management of risk associated with the uncertainties due to RERs and EVs.     

Sustainable Development in Small Island Developing States

This paper explores the status of sustainable development in small island developing states (SIDS), through the presentation of a case study on the Maldives, which is a typical small island developing state in the Central Indian Ocean. At the outset, a brief history of sustainable development as related to SIDS on the international agenda is outlined, starting from Rio to Barbados to Johannesburg. SIDS are expected to face many challenges and constraints in pursuing sustainable development due to their ecological fragility and economic vulnerability. It is the position of this paper that issues related to environmental vulnerability are of the greatest concern. A healthy environment is the basis of all life-support systems, including that of human well-being and socio-economic development. Priority environmental problems are: climate change and sea-level rise, threats to biodiversity, threats to freshwater resources, degradation of coastal environments, pollution, energy and tourism. Among these, climate change and its associated impacts are expected to pose the greatest threat to the environment and therefore to sustainable development. For small islands dependent on fragile marine ecosystems, in particular on coral reefs, for their livelihoods and living space, adverse effects of climate change such as increased frequency of extreme weather events and sea-level rise will exacerbate the challenges they already face. It is concluded that the paper path from Rio to Barbados to Johannesburg has made significant progress. However, much remains to be done at the practical level, particularly by the developed countries in terms of new and additional efforts at financial and technical assistance, to make sustainable development a reality for SIDS.     

Morphophysiological Rearrangements in Fish in Response to Pollution (in the Light of S.S. Shvarts' Theory)

The results of a study on morphophysiological variation in fish inhabiting a subarctic lake exposed to chronic industrial pollution are described using an example of cisco, Coregonus lavaretus. It is shown that indices of the heart, liver, kidneys, gills, and fatness in these fish are increased significantly and have retained increased values for the past 20 years. The observed changes are analyzed on the basis of biochemical data. The results of studies on the dynamics of hematological parameters in fish are used for characterizing the development of toxicosis. Adaptive rearrangements associated with an increase in the metabolic rate and the activation of protective systems in the fish are explained in the context of S.S. Schvarts' concept. The idea is proposed that the additional energy cost of detoxification may be responsible for morphophysiological variation in fish under conditions of water pollution.     

组合优化的能源消费量预测模型

针对非等间距灰色系统预测中存在误差较大的问题，结合序列本身的特点，利用世界能源消费的历史数据，采用3种灰色预测模型与神经网络进行组合优化，建立了灰色神经网络的能源消费量组合预测模型。实证分析结果表明，提高了模型的拟合和预测精度，拓宽了应用范围。该模型可对能源的消费趋势进行预测，为科学分析能源结构提供依据。     

等离子点火燃烧技术在电厂节能和环保方面的应用

介绍了等离子点火技术在浙江长兴电厂3号炉上的应用.自电厂进行等离子点火装置改造并正式投运以来,取得了良好的经济效益和节能效果,环境效益也十分显著,实现了低负荷断油燃烧,节油率达90%左右,1台300 MW机组可节约燃油成本180 万元/a.     

用烧结法从沸腾炉渣中提取铝和铁的研究

把沸腾炉渣和石灰及精煤混合制成小球,然后在大约1 000 ℃下烧结.取不同烧结时间的样品用硫酸浸取,得到含有铝离子和铁离子的溶液.试验表明,采用浓度为4 mol/l的硫酸,在80 ℃下浸取烧结球样品(50%沸腾炉渣∶40%精煤∶10%石灰)24 h,可以得到铝和铁的最大提取率,分别为86.50%和94.60%.滤渣可以作为固化材料用于高速公路的路基建设或水泥生产中的添加剂.