Showing papers by "Violeta Holmes published in 2018"

Output-Power Enhancement for Hot Spotted Polycrystalline Photovoltaic Solar Cells

Abstract: Hot spotting is a reliability problem in photovoltaic (PV) panels where a mismatched cell heats up significantly and degrades PV panel output-power performance. High PV cell temperature due to hot spotting can damage the cell encapsulate and lead to second breakdown, where both cause permanent damage to the PV panel. Therefore, the development of two hot-spot mitigation techniques is proposed using a simple and reliable method. PV hot spots in the examined PV system were inspected using the FLIR i5 thermal imaging camera. Multiple experiments have been tested during various environmental conditions, where the PV module $I - V$ curve was evaluated in each observed test to analyze the output-power performance before and after the activation of the proposed hot-spot mitigation techniques. One PV module affected by the hot spot was tested. The output power during high irradiance levels is increased to approximately 1.26 W after the activation of the first hot-spot mitigation technique. However, the second mitigation technique guarantees an increase in the power up to 3.97 W. An additional test has been examined during the partial shading condition. Both proposed techniques ensure a decrease in the shaded PV cell temperature; thus, there is an increase in PV output power.

Evaluating Power Loss and Performance Ratio of Hot-Spotted Photovoltaic Modules

Abstract: The impact of photovoltaic (PV) hot-spots is assessed through the analysis of 2580 polycrystalline silicon PV modules distributed across the U.K. PV hot-spots were categorized into eight different groups using the percentage of power loss. All hot-spots groups were modeled using the cumulative density function, state-of-the-art geographical mapping, and performance ratio (PR) analysis. Significantly, it was found that 92.15% of the PV modules affected by hot-spotted PV string are located in northern U.K., where the effect of low-temperature levels, heavy snow, and hoarfrost are more significant. Finally, it was found that the distribution of PV modules affected by only one hot-spotted solar cell are likely (82.41%) located in coastal locations. Hence, coastal locations expect to have lower risks for causing multiple hot-spotted solar cells in PV modules, compared to central and colder locations. The PR of all examined PV modules was analyzed. It was evident that the mean PR is significantly reduced due to the existence of hot-spots in the PV modules. The least difference in the PR between healthy and hot-spotted PV modules is equal to −0.83%, whereas the most difference is calculated at −15.47%.

Preliminary assessment of the solar resource in the United Kingdom

Abstract: Solar radiation resources data are the foundation of knowledge for programs of large-scale deployment of solar energy technologies. This article summarizes the analysis of a new weather stations network in the United Kingdom. The analysis used three years (January 2015–December 2017) of data from 27 weather stations distributed across the country. The data comprises global horizontal irradiance (GHI), diffuse horizontal irradiance, direct normal irradiance and the ambient temperature. Network design, implementation and data quality assurance are described to document the network extent and quality. From all observed datasets, we found that Plymouth (located in southwest England) has the dominant GHI and ambient temperature among all other 26 locations. The least GHI is observed for Aberdeen (located in northeast Scotland) estimated at 77.3 kWh/m2. The least average ambient temperature is equal to 9.1°C; the data were detected by the weather station located in the capital of Scotland (Edinburgh). Although continued measurements are needed to understand the interannual resource variability, the current study should have significant applications for preliminary technology selection, power plant modeling and resource forecasting.

An Algorithmic Approach for Signal Measurement Using Symbolic Dynamics of Tent Map

Abstract: The symbolic time series generated by a unimodal chaotic map starting from any initial condition creates a binary sequence that contains information about the initial condition. A binary sequence of a given length generated this way has a one-to-one correspondence with a given range of the input signal. This can be used to construct analogue to digital converters (ADC). However, in actual circuit realizations, component imperfections and ambient noise result in deviations in the map function from the ideal, which, in turn, can cause significant error in signal measurement. In this paper, we propose the ways of circumventing these problems through an algorithmic procedure that takes into account the non-idealities. The most common form of non-ideality—reduction in the height of the map function—alters the partitions that correspond to each symbolic sequence. We show that it is possible to define the partitions correctly if the height of the map function is known. We also propose a method to estimate this height from the symbolic sequence obtained. We demonstrate the efficacy of the proposed algorithm with simulation as well as experiment. With this development, practical ADCs utilizing chaotic dynamics may become reality.

Parameter estimation for 1D PWL chaotic maps using noisy dynamics

Abstract: Many physical situations involve chaotic systems implemented in hardware. Among them one-dimensional piecewise linear maps are popular candidates for such applications because of their property of generating robust chaos. In physical implementations, the control parameter of these maps may deviate from its ideal value due to hardware imprecision. Since the dynamics of a chaotic map is completely defined by its control parameter, one needs to know the value of the parameter in a hardware realisation. In this paper, we show that it is possible to determine the parameter, through the realisation of the unstable fixed point of the map, by utilising noise that is always present in the system. We present this in the form of an algorithm and demonstrate its efficacy through simulated results. We also determine the bounds on the signal-to-noise ratio required for successful parameter estimation. The proposed approach is expected to be beneficial to the existing noise reduction techniques and time series recovery algorithms that require a reasonably accurate knowledge of the map.

Web-based Wireless Wake-on-LAN approach for Robots

Abstract: The ability to wake up robots over a wireless LAN remotely can improve the power consumption performance of remote robots or cloud robotics system. This paper presents a solution for power management of a mobile robot, using web-based wireless Wake-on-LAN (WWoL). The focus in on power management of a mobile robot, but this approach is also suitable for most of the IoT mobile devices, and other systems that are designed to be used remotely. The proposed solution allows the targeted device to be powered ON and OFF remotely via a web-based dashboard. This approach was validated in a case study with an AR drone 2.0 and demonstrated substantial power optimization for the drone. In addition, security issues are explored when WWoL is deployed in remote control of mobile devices. It was established that power consumption is reduced when the drone is in a standby mode waiting for an operator to send a wake-on request message wirelessly, without compromising security posed by wireless remote access to the devices.