Probabilistic Global Maximum Power Point Tracking Algorithm for Continuously Varying Partial Shading Conditions on Autonomous PV Systems

A photovoltaic (PV) string with multiple modules with bypass diodes frequently deployed on a variety of autonomous PV systems may present multiple power peaks under uneven shading. For optimal solar harvesting, there is a need for a control schema to force the PV string to operate at global maximum power point (GMPP). While a lot of tracking methods have been proposed in the literature, they are usually complex and do not fully take advantage of the available characteristics of the PV array. This work highlights how the voltage at operating point and the forward voltage of the bypass diode are considered to design a global maximum power point tracking (GMPPT) algorithm with a very limited global search phase called Fast GMPPT. This algorithm successfully tracks GMPP between 94% and 98% of the time under a theoretical evaluation. It is then compared against Perturb and Observe, Deterministic Particle Swarm Optimization, and Grey Wolf Optimization under a sequence of irradiance steps as well as a power-over-voltage characteristics profile that mimics the electrical characteristics of a PV string under varying partial shading conditions. Overall, the simulation with the sequence of irradiance steps shows that while Fast GMPPT does not have the best convergence time, it has an excellent convergence rate as well as causes the least amount of power loss during the global search phase. Experimental test under varying partial shading conditions shows that while the GMPPT proposal is simple and lightweight, it is very performant under a wide range of dynamically varying partial shading conditions and boasts the best energy efficiency (94.74%) out of the 4 tested algorithms.

Spotted Hyena-Bat Optimized Extreme Learning Machine for Solar Power Extraction

Artificial intelligence,machine learning and deep learning algorithms have been widely used for Maximum Power Point Tracking(MPPT)in solar systems.In the traditional MPPT strategies,following of worldwide Global Maximum Power Point(GMPP)under incomplete concealing conditions stay overwhelming assignment and tracks different nearby greatest power focuses under halfway concealing conditions.The advent of artificial intelligence in MPPT has guaranteed of accurate following of GMPP while expanding the significant performance and efficiency of MPPT under Partial Shading Conditions(PSC).Still the selection of an efficient learning based MPPT is complex because each model has its advantages and drawbacks.Recently,Meta-heuristic algorithm based Learning techniques have provided better tracking efficiency but still exhibit dull performances under PSC.This work represents an excellent optimization based on Spotted Hyena Enabled Reliable BAT(SHERB)learning models,SHERB-MPPT integrated with powerful extreme learning machines to identify the GMPP with fast convergence,low steady-state oscillations,and good tracking efficiency.Extensive testing using MATLAB-SIMULINK,with 50000 data combinations gathered under partial shade and normal settings.As a result of simulations,the proposed approach offers 99.7%tracking efficiency with a slower convergence speed.To demonstrate the predominance of the proposed system,we have compared the performance of the system with other hybrid MPPT learning models.Results proved that the proposed cross breed MPPT model had beaten different techniques in recognizing GMPP viably under fractional concealing conditions.

Global point tracking based panoramic image stabilization system

A novel image stabilization system is presented,which consists of a global feature point tracking based motion estimation,a Kalman filtering based motion smoothing and an image mosaic based panoramic compensation.The global motion is estimated using feature point matching and iteration with the least-square method.Then,the Kalman filter is applied to smooth the original motion vectors to effectively alleviate unwanted camera vibrations and follow the intentional camera scan.Lastly,the loss information of image boundary due to the motion compensation is reconstructed with image mosaic to improve the visual quality.The experimental results show that this system can smooth unwanted translation or rotation of the video sequences and realize a panoramic stabilization at real-time speed.

北斗导航系统卫星激光测距综述

Satellite laser ranging(SLR)is an unambiguous measurement technique and generates high accuracy satellite orbit data.All satellites in the BeiDou navigation satellite system(BDS)carried laser retro-reflector arrays(LRAs),so they can be tracked by ground SLR stations in order to provide the accurate observation data.The Shanghai astronomical observatory(SHAO)designed the LRAs,and also developed the dedicated SLR systems using a 1 m-aperture telescope and a transportable cabin-based SLR system with a telescopes of 60 cm aperture.These enable BDS satellite ranging during daytime and nighttime with centimeter-level precision,allowing highly accurate estimations of satellite orbits.Moreover,some of the BDS satellites are also equipped with laser time transfer(LTT)payloads,which were developed by the SHAO and China Academy of Space Technology(CAST),providing a highly accurate time comparison between the satellites and ground clocks.This paper describes the dedicated SLR system and the design of the LRAs for BDS satellites,as well as global SLR measurements.The SLR tracking data is used for evaluating the orbit accuracy of BDS satellites and broadcast ephemeris,with an accuracy of less than 1 m.The LTT measurements to BDS satellites for a single shot have a precision of approximately 300 picoseconds,with a time stability of 20 picoseconds in 500 s.

On the new results of global attractive set and positive invariant set of the Lorenz chaotic system and the applications to chaos control and synchronization

Constructing a family of generalized Lyapunov functions, a new method is proposed to obtain new global attractive set and positive invariant set of the Lorenz chaotic system. The method we proposed greatly simplifies the complex proofs of the two famous estimations presented by the Russian scholar Leonov. Our uniform formula can derive a series of the new estimations. Employing the idea of intersection in set theory, we extract a new Leonov formula-like estimation from the family of the estimations. With our method and the new estimation, one can confirm that there are no equilibrium, periodic solutions, almost periodic motions, wandering motions or other chaotic attractors outside the global attractive set. The Lorenz butterfly-like singular attractors are located in the global attractive set only. This result is applied to the chaos control and chaos synchronization. Some feedback control laws are obtained to guarantee that all the trajectories of the Lorenz systems track a periodic solution, or globally stabilize an unstable (or locally stable but not globally asymptotically stable) equilibrium. Further, some new global exponential chaos synchronization results are presented. Our new method and the new results are expected to be applied in real secure communication systems.

An empirical comparison of four technology-mediated travel survey methods

The increasing demana for advanced modelling methods, which can reflect complex travel activities of individuals, requires enhanced travel data collection methods. The introduction of GPS-assisted data collection methods has provided an alternative to the conventional methods of travel data collection. GPS-assisted data collection methods improve the accu- racy of data collection and enable capturing more details of individuals＇ travel behaviour. Recent technological advancements in smartphone-based positioning technologies and communication facilities have opened up new opportunities to apply smartphones as the media of GPS-assisted data collection. Although, different GPS-assisted methods have been employed recently, their performance has not been widely evaluated in real-world experi- ments compared to traditional data collection methods. Accordingly, this paper evaluates the performance of three GPS-assisted methods, namely handheld GPS tracking, smart- phone-based GPS tracking and smartphone-based prompted-recall data collection methods, in conjunction with the web-based data collection to shed light on different aspects of GPS- assisted data collection methods. These methods are compared in terms of the quality and accuracy of the collected data, the demographic attributes of participants and the specifi- cations of labelled trips. The results show that an appropriate employment of smartphones enhances the accuracy of data collection. It is also found that putting an extra burden on participants during a travel data collection survey results in lower trip-rates and poor data quality. Finally, it is found that the application of smartphone-assisted data collection methods help reporting non-motorised trips more accurately.