Current Issue : January - March Volume : 2020 Issue Number : 1 Articles : 5 Articles
An on-glass optically transparent monopole antenna with ultrawide bandwidth is presented\nin this work, and the proposed antenna is of ring shape and coplanar waveguide fed structure. Optically\ntransparent indium tin oxide (ITO) thin film with a thickness of Approximately 160 nm is used as the conductive\nlayer, which is sputtered on an optically transparent glass substrate. An impedance bandwidth of\n6 GHz from 1 to 7 GHz is achieved, with a return loss lower than -10 dB, meaning a fractional\nbandwidth of 150%. The proposed antenna exhibits reasonable radiations of omni-directionality\nin the H plane and bi-directionality in the E plane. Like other transparent antennas discussed in\nliterature, the antenna gain is relatively low (-4 dBi at 5 GHz)......................
The current research study focuses on the feasibility of stand-alone hybrid solar-geothermal organic Rankine cycle (ORC)\ntechnology for power generation from hot springs of Bhurung Tatopani, Myagdi, Nepal. For the study, the temperature of the\nhot spring was measured on the particular site of the heat source of the hot spring. The measured temperature could be used for\noperating the ORC system. Temperature of hot spring can also further be increased by adopting the solar collector for rising the\ntemperature. This hybrid type of the system can have a high-temperature heat source which could power more energy from\nORC technology. There are various types of organic working fluids available on the market, but R134a and R245fa are\nenvironmentally friendly and have low global warming potential candidates. The thermodynamic models have been developed\nfor predicting the performance analysis of the system. The input parameter for the model is the temperature which was\nmeasured experimentally. The maximum temperature of the hot spring was found to be 69.7DegreeC. Expander power output,\nthermal efficiency, heat of evaporation, solar collector area, and hybrid solar ORC system power output and efficiency are the\noutputs from the developed model. From the simulation, it was found that 1 kg/s of working fluid could produce 17.5kW and\n22.5kW power output for R134a and R245fa, respectively, when the geothermal source temperature was around 70DegreeC. Later\nwhen the hot spring was heated with a solar collector, the power output produced were 25kW and 30kW for R134a and\nR245fa, respectively, when the heat source was 99DegreeC. The study also further determines the cost of electricity generation for the\nsystem with working fluids R134a and R245fa to be $0.17/kWh and $0.14/kWh, respectively. The levelised cost of the electricity\n(LCOE) was $0.38/kWh in order to be highly feasible investment. The payback period for such hybrid system was found to have\n7.5 years and 10.5 years for R245fa and R134a, respectively....
Solar flare is one of the violent solar eruptive phenomena; many solar flare forecasting models are built based on the properties of\nactive regions. However,most of these models only focus on active regions within 30Degree of solar disk center because of the projection\neffect. Using cost sensitive decision tree algorithm, we build two solar flare forecasting models from the active regions within 30Degree\nof solar disk center and outside 30Degree of solar disk center, respectively. The performances of these two models are compared and\nanalyzed. Merging these two models into a single one, we obtain a full-disk solar flare forecasting model....
Concentrating solar power (CSP) station is counted as a promising flexible power supply\nwhen the net load power curve is duck-shaped in high photovoltaic (PV) penetration power system,\nwhich may lead to the serious phenomenon of PV curtailment and a large-capacity power shortage.\nThis paper presents a mitigation strategy that replaces thermal power station with CSP station to\nparticipate in the optimal operation of power system for solving the duck-shaped net load power\ncurve problem. The proposed strategy utilizes the dispatchability of thermal storage system (TSS)\nand the fast output regulation of unit in the CSP station. Simultaneously, considering the operation\nconstraints of CSP station and network security constraints of the system, an optimization model is\ndeveloped to minimize the overall cost including operation and penalty. The results obtained by\nnonlinear optimization function demonstrate that the replacement of concentrating solar power\n(CSP) station contributes to reducing the PV curtailment and lost load, while increasing the available\nequivalent slope for power balance. Thus, the proposed mitigation strategy can promote the\npenetration of PV generation and improve the flexibility of power system....
The development of perpetually powered sensor networks for environment monitoring to avoid periodic battery replacement\nand to ensure the network never goes offline due to power is one of the primary goals in sensor network design. In many\nenvironment-monitoring applications, the sensor network is internet-connected, making the energy budget high because data\nmust be transmitted regularly to a server through an uplink device. Determining the optimal solar panel size that will deliver\nsufficient energy to the sensor network in a given period is therefore of primary importance. The traditional technique of sizing\nsolar photovoltaic (PV) panels is based on balancing the solar panel power rating and expected hours of radiation in a given area\nwith the load wattage and hours of use. However, factors like the azimuth and tilt angles of alignment, operating temperature, dust\naccumulation, intermittent sunshine and seasonal effects influencing the duration of maximum radiation in a day all reduce the\nexpected power output and cause this technique to greatly underestimate the required solar panel size.Themajority of these factors\nare outside the scope of human control and must be therefore be budgeted for using an error factor. Determining of the magnitude\nof the error factor to use is crucial to prevent not only undersizing the panel, but also to prevent oversizing which will increase the\ncost of operationalizing the sensor network. But modeling error factors when there are many parameters to consider is not trivial.\nEqually importantly, the concept of microclimate may cause any two nodes of similar specifications to have very different power\nperformance when located in the same climatological zone. There is then a need to change the solar panel sizing philosophy for\nthese systems. This paper proposed the use of actual observed solar radiation and battery state of charge data in a realistic WSNbased\nautomatic weather station in an outdoor uncontrolled environment.We then develop two mathematical models that can be\nused to determine the required minimum solar PV wattage that will ensure that the battery stays above a given threshold given\nthe weather patterns of the area. The predicted and observed battery state of charge values have correlations of 0.844 and 0.935\nand exhibit Root Mean Square Errors of 9.2% and 1.7% for the discrete calculus model and the transfer function estimation (TFE)\nmodel respectively.The results show that the models perform very well in state of charge prediction and subsequent determination\nof ideal solar panel rating for sensor networks used in environment monitoring applications....
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