Volume 14

Paper deals with actual problem orientated to cloud technology applying within implementation of information systems in area of manufacturing corporations and process control. The mainly part is aimed at analysis of requirements to MES systems, which are directly responsible for support of production control and global monitoring of manufacturing process. Special part is aimed at creating of recommendations for implementations of SaaS (Software and services) within MES system implementation.

Issue of the article represents the actual problem of security constructions applying which are an important part of control and information systems integration in conditions of industrial plants. A special section is dedicated to the issue of the use the cryptographic mechanisms in industrial communications system especially for applications of safety-relevant (SR) processes control with a higher integrity level SIL (Safety Integrity Level) and the possibilities of their evaluation based on mathematical approaches.

The paper presents investigation results concerning the accuracy analysis of calculating the defined stability factors of the Polish Power System on the basis of power system state matrix eigenvalues associated with electromechanical phenomena. The eigenvalues were calculated by analysis of the disturbance waveforms of the instantaneous power when taking into account introduction of a disturbance to different units.

Transmission system is one of the major components in the electric power industry. In this paper, a novel approach is proposed using biogeography-based optimization (BBO) for the solution of Transmission-expansion planning (TEP) long range problem. It applies a constrained BBO algorithm where network stability constraints as lower and upper limits of bus voltage magnitudes and swing angles are included, as well as the AC load flow equations. The cost function is formulated including both fixed and variable costs of planned transmission lines, in addition to energy losses cost.

Power quality monitors handle and store several gigabytes of data within a week and hence automatic detection, recognition and analysis of power disturbances require robust data mining techniques. Literature reveals that much work has been done to evolve several feature extraction and subsequent classification techniques for accurate power disturbance pattern recognition. However, the features extracted have been rarely evaluated for their usefulness. Classification fusion combines multiple classifications of data into a single classification solution of greater accuracy.

Pattern recognition generally requires that objects be described in terms of a set of measurable features. Multi-classification process can be significantly enhanced byselecting an optimal set of the features used as input for the training operation. The selectionand quality of the features representing each pattern have aconsiderable bearing on the success of subsequent pattern classification .The selection of such a subset willreduce the dimensionality of the data samples and eliminate the redundancy and ambiguity introduced by some attributes.

The purpose of the power management controller subsystem in the Parallel Hybrid Electric Vehicle (PHEV) is to optimally arrange the engine and electric motor for load sharing providing the desired vehicle power while increasing the overall efficiency. This work adopts a PMSM as an electric drive for the HEV system. An experimental electric driving system is implemented in the Laboratory. The Borland C Language was used to implement the control algorithm during experimental work. The algorithm was executed via a data acquisition card.