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.     

Short-term wind speed forecasting based on random forest model combining ensemble empirical mode decomposition and improved harmony search algorithm

ABSTRACT

Wind speed forecasting plays an important role in power grid dispatching management. This article proposes a short-term wind speed forecasting method based on random forest model combining ensemble empirical modal decomposition and improved harmony search algorithm. First, the initial wind speed data set is decomposed into several ensemble empirical mode functions by EEMD, then feature extraction of each sub-modal IMF is performed using fast Fourier transform to solve the cycle of each sub-modal IMF. Next, combining the high-performance parameter optimization ability of the improved harmony search algorithm, two optimal parameters of random forest model, number of decision trees, and number of split features are determined. Finally, the random forest model is used to forecast the processing results of each submodal IMF. The proposed model is applied to the simulation analysis of historical wind data of Chaoyang District, Liaoning Province from April 27, 2015 to May 22, 2015. To illustrate the suitability and superiority of the EEMD-RF-IHS model, three types of models are used for comparison: single models including ANN, SVM, RF; EMD combination models including EMD-ANN, EMD-SVM, EMD-RF; EEMD combination models including EEMD-ANN, EEMD-SVM, EEMD-RF. The analysis results of evaluation indicators show that the proposed model can effectively forecast short-term wind data with high stability and precision, providing a reference for forecasting application in other industry fields.     

Multi-objective-based optimal transmission switching and demand response for managing congestion in hybrid power systems

ABSTRACT

This paper proposes a novel congestion management (CM) approach by using the optimal transmission switching (OTS) and demand response (DR) for a system with conventional thermal generators and renewable energy sources (RESs). In this paper, wind and solar PV units are considered as the RESs. The stochastic behavior of wind and solar PV powers are modeled by using the appropriate probability density functions (PDFs). The proposed CM methodology simultaneously optimizes the generation dispatch, demand response, and also the network topology of the power system. The OTS identifies the branches that should be taken out of service by significantly reducing the operating cost of the system while respecting the system security. Here, the total operating cost minimization/social welfare maximization and system losses minimization are considered as the objectives to be optimized. The proposed CM problem is solved using the multi-objective Jaya algorithm and it is used to determine a set of Pareto-optimal solutions. The Jaya algorithm is simple and it does not have any algorithmic-specific parameters to be tuned. This aspect reduces the designer’s effort in tuning the parameters to arrive at the optimum objective function value. A fuzzy logic-based approach is used to identify the best compromise solution. The effectiveness of the proposed CM approach is examined on modified IEEE 30 and practical Indian 75 bus test systems. The obtained simulation results are analyzed and they show the effectiveness of the proposed approach.     

Investigation of sustainable energy alternatives for powering remote communities in northern Ontario

ABSTRACT

Remote communities in the North of Ontario survive in isolation as their proximity to the southern industrial sector of the province limits their accessibility to the major grid. The lack of grid connection has led to antiquated methods of power generation which pollute the environment and deplete the planet of its natural resources. Aside from the primary means of electricity generation being by diesel generators, generation infrastructure is deteriorating due to age and the stagnation of the power supply has led to communities facing load restrictions. These challenges may be resolved by introducing clean energy alternatives and providing a fuel blend option. The primary energy sources investigated in this research are solar, wind, and hydrogen. To assess the viability of these energy production methods in Northern communities, an exergy analysis is employed as it utilizes both the first and second law of thermodynamics to determine systems’ efficiency and performance in the surroundings. Local weather patterns were used to determine the viability of using wind turbines, solar panels and/or hydrogen fuel cells in a remote community. Through analysis of the resources available at the community, it was determined that the hydrogen fuel cell was best suited to provide clean energy to the community. Wind resulted in low efficiency in the range of 2–3% while solar efficiencies resulted in ranges of 18 – 19%, as the seasonal variations between the three years is not very great. Due to the higher operating efficiencies observed of the PV panels it would also be an attractive alternative to diesel generators however, the lack of consistent operation above 30% efficiency throughout the year, resulted in hydrogen fuel cells being a better alternative.     

The hybrid model of empirical wavelet transform and relevance vector regression for monthly wind speed prediction

ABSTRACT

In order to improve the prediction ability for the monthly wind speed of RVR, the hybrid model of empirical wavelet transform and relevance vector regression (EWT-RVR) is proposed for monthly wind speed prediction in this study. Compared with empirical mode decomposition (EMD), empirical wavelet transform (EWT) can obtain a more consistent decomposition and have a mathematical theory. In order to testify the superiority of EWT-RVR, several traditional RVR models are used to compare with the proposed EWT-RVR method under the situation of the same embedding dimensions. The experimental results show that the proposed EWT-RVR method has a better prediction ability for monthly wind speed than RVR. It can be concluded that the proposed EWT-RVR method for monthly wind speed is effective.     

电厂建设运行中的水土流失预测与水土保持设计

在燃煤电厂建设运行的同时,将引起一系列的水土流失问题.以四川国电金堂电厂二期扩建工程为例,简要说明项目区水土流失预测的内容和方法,并在其基础上对可能产生的水土流失和危害进行了分析,同时介绍了建设期和运行期采取的综合防治措施,为类似工程的水土保持提供借鉴.     

上海市青浦区PM10污染状况及其与气象要素的关系

利用2006-2010年上海市青浦区PM10和同期地面气象要素的监测资料,定量分析PM10的季节变化规律以及PM10与降雨量、大气湿度和风速之间的关系。分析结果表明:PM10浓度在夏季处于低值,冬季处于高值;5mm/d以上的降雨对PM10有显著的清除作用,且春夏季降雨的清除作用大于秋冬季节。PM10浓度与大气湿度基本呈负相关关系。风速在一定范围内有利于PM10的扩散但不至造成扬尘,春夏季节的适宜风速是1.5～3.5m/s,冬季的适宜风速是1.5～2.5m/s。     

Physical Modeling of Emissions from Naturally Ventilated Underground Parking Garages

The dispersion of pollutants from naturally ventilated underground parking garages has been studied in a boundary layer wind tunnel. Two idealized model setups have been analysed, one was simulating pollutant dispersion around an isolated rectangular building and one was representing dispersion in a finite array of idealized building blocks. Flow and dispersion close to modelled ground level emission sources was measured. The results illustrate the complexity of the flow around buildings and provide insight in pollutant transport from ground level sources located directly on building surfaces. As a result, areas critical with respect to high pollutant concentrations could be visualized. Particularly, the results show high concentration gradients on the surface of the buildings equipped with modelled emission sources. Inside the boundary layers on the building walls, a significant amount of pollutants is transported to upwind locations on the surface of the building. The paper documents the potential of physical modelling to be used for the simulation and measurement of dispersion close to emission sources and within complex building arrangements.     

Experimental Study of the Criteria of Flow Laminarization in Two-Dimensional Dense Gas Plumes

Laminarization of flow in a two-dimensional dense gas plume was experimentally investigated in this study. The plume was created by releasing CO₂ through a ground-level line source into a simulated turbulent boundary layer over an aerodynamically rough surface in a meteorological wind tunnel. The bulk Richardson number (Ri_*), based on negative plume buoyancy, plume thickness, and friction velocity, was varied over a wide range so that the effects of stable stratification on plume laminarization could be observed. A variety of ambient wind speeds as well as three different sizes of roughness arrays were used so that possible effects of roughness Reynolds number (Re_*) on plume laminarization could also be identified. Both flow visualization methods and quantitative measurements of velocity and intermittency of turbulence were used to provide quantitative assessments of plume laminarization.Flow visualization provided an overall picture of how the plume was affected by the negative buoyancy. With increasing Ri_*, both the plume depth and the vertical mixing were significantly suppressed, while upstream propagation of the plume from the source was enhanced. The most important feature of the flow revealed by visualization was the laminarization of flow in the lower part of the plume, which appeared to be closely related to both Ri_* and Re_*.Measurements within the simulated dense gas plumes revealed the influence of the stable stratification on mean velocity and turbulence intensity profiles. Both the mean velocity and turbulence intensity were significantly reduced near the surface; and these reductions systematically depended on Ri_*. The roughness Reynolds number also had considerable influence on the mean flow and turbulence structure of the dense gas plumes.An intermittency analysis technique was developed and applied to the digitized instantaneous velocity signals. It not only confirmed the general flow picture within the dense plume indicated by the flow visualization, but also clearly demonstrated the changes of flow regime with variations in Ri_* and Re_*. Most importantly, based on this intermittency analysis, simple criteria for characterizing different flow regimes are formulated; these may be useful in predicting when plume laminarization might occur.     

苏南地区CO2本底浓度及源汇特征

基于2015~2018年苏州张家港站CO₂在线观测数据，采用时序检查、选取稳定性数据、异常值剔除等质量控制方法获得可靠数据，并通过平均移动过滤（MAF）本底筛分法获得本底数据，讨论苏南地区CO₂变化特征.结果发现：CO₂本底浓度日变化为单峰结构，谷值和峰值分别出现在下午15：00和凌晨5：00前后；季节变化为双峰结构，峰值分别出现在12月和4月；日、季节变化的分布特征均与陆地生态系统、气象条件和人类活动有关.此外，2015~2018年CO₂浓度呈逐年上升趋势，抬升浓度占比逐年增加，吸收浓度占比波动较小，表明人类活动对CO₂浓度的影响正在逐年增加；而陆地生态系统对CO₂吸收汇的作用则相对稳定.源汇分析显示，CO₂抬升浓度随季节小幅波动；吸收浓度则夏半年较低，冬半年较高；抬升浓度日变化为单峰结构，谷值和峰值分别出现在15：00和8：00前后，早晨正值上班高峰，机动车排放可能为早晨峰值的主要因素；吸收浓度日间低、夜间高，这主要与植物光合作用及对流输送有关.分析CO₂浓度与风的关系发现，所有季节静风情况下，CO₂浓度偏高均最为明显，大部分方向CO₂浓度高低与风速大小有明显的负相关，其中S~WNW方向偏高最为明显，这可能是因为SW~NW方向主要为内陆城市群，且测站周边建筑区主要位于W~N方向，弱风有利于本地排放累积的结果.此外，WNW方向风速较大时浓度仍偏高明显，可能与测站W~N方向为建筑区及内陆城市群有关；而测站偏东方向主要为农田和林区，受人类活动影响较小，且海上气流较为洁净，故偏东风较弱时浓度也不高；说明了CO₂浓度除了与风速大小有关外，与周边下垫面类型及较远距离环境特征（城市群或海洋）也有一定的关系.