Studying the dynamic behavior of electric power systems is important part of a power engineer’s work. Transient phenomena in electric power systems can be naturally and conveniently modelled as hybrid or event-continuous systems, which are a generalization of classical dynamical systems. The approach is illustrated by a model of a large electric power system with controllers and protective devices. An original event detection algorithm for explicit numerical methods with error and stability control is presented and used to simulate the model. The simulation results show that the approach can be successfully applied to modeling and simulation of electric power systems. The model was composed and simulated in the modeling and simulation environment ISMA.
It is well known that the process of controlling a rotorcraft with a drive referred to as a rotor aircraft,\r\nin the event of adverse weather conditions, e.g. under the influence of strong wind, is the most difficult phase of\r\nthe flight, requiring a lot of commitment and skill from the pilot/operator. This situation is confirmed by a\r\nrelatively large number of aviation accidents that occur during the implementation of the process of controlling\r\na multi-rotor in difficult weather conditions. In view of the above, it should be noted that the degree of\r\ndifficulty of piloting an unmanned aircraft increases significantly when this operation is performed remotely by\r\nmeans of radio signals. As a consequence, the process of safely bringing an unmanned aircraft to the ground is\r\nextremely difficult even for an experienced operator who receives limited information about the flight condition\r\nof a multi-rotor. In view of the above, it is necessary to implement on-board control systems that enable\r\nautomatic implementation of the flight stabilization process, e.g. during a storm. The key goal of this work is to\r\ndesign a multi-rotor control system based on the proposed algorithms for controlling unmanned aerial vehicles\r\nduring high-wind flight, supported by a mathematical apparatus and selected simulation tests in the\r\nMatlab/Simulink environment. Based on the above, in the final part of this work, practical conclusions were\r\nformulated, reflecting the desirability of the tests carried out and confirmation of the results obtained.
Fiber Bragg Gratings (FBG) are widely used in different areas of the state-of–the -art fiber optics. Every task imposes specified requirements to the FBG spectral characteristics, which are scheduled at the gratings manufacturing stage. Manufacturing and using the Bragg fiber-optic gratings is impossible without measuring their characteristics at every stage of manufacturing the gratings themselves and devices on their basis. To select FBG’s optimal parameter we will compare the parameter SGW with several different the most widely used apodization functions. Upon manufacturing the FBG there applied strict requirements to their parameters. Recording or manufacturing the fiber Bragg gratings might be classified according to the type of the laser being used, radiation wave length, recording techniques, irradiation material and grating type. The article is dedicated to the techniques of computing and measuring the FBG’s principal parameters; it is necessary to define optimal parameters of the characteristics for the grating quality operation.
The relationships of the individuals in social networks give rise to interesting and important features in various fields, such as graph mining and communication networks. Among those useful features are clique structures which represent fully connected relations between members, and the maximum cliques which identify the highest-connected subgroups. In this work, we propose the modified differential evolution algorithm (moDE) for finding a maximum clique in social networks. The moDE solves the constrained continuous optimization problem which is transformed from the discrete maximum clique problem. It uses a new mutation strategy to generate and adjust mutant vectors, mixes two important crossover rates in crossover, and incorporates the extracting and extending clique procedure to increase the performance of clique finding. The algorithm is tested on several social network problems and compared with the previously developed method. The results show that moDE is effective for finding a maximum clique and outperforms the compared method. Key-Words: Maximum clique problem, social network, differential evolution algorithm, constrained continuous optimization problem
The European Energy Road Map 2050 and the Spanish Renewable Energies Plan for 2011-2020 are promoting the use of renewable energies as a necessary path to achieve the greenhouse gas reduction target necessary to avoid the rising global warming, and in particular, the use of Ocean Energy. Within the different types of on-shore wave-based energy devices, Oscillating Water Column (OWC) converters are one of the more widely used ones. An OWC plant is basically composed by a capture chamber coupled to a turbo-generator module. This paper deals with the model development for on-shore OWC wave energy power devices.
