The development of a distributed generation will influence the structure of the power transmission and distribution network. Distributed sources have lower power and therefore the lines of lower voltage are used. Therefore, the electric field intensity near such lines is lower. On the other hand magnetic field intensity may prove essential. The main aim of the paper is to present a method estimating the “ballast” of the natural environment at 50 Hz electric and magnetic fields in the power system, with distributed and centralized generation in real operating conditions.
Arriving at a good combination of coding and modulation schemes that can achieve good error correction constitutes a challenge in digital communication systems. In this work, we explore the combination of permutation coding (PC) and pulse amplitude modulation (PAM) for mitigating channel errors in the presence of background noise and jitter. Since PAM is characterised with bi-polar constellations, Euclidean distance is a good choice for predicting the performance of such coded modulation setup. In order to address certain challenges facing PCs, we therefore introduce injections in the coding system, together with a modified form of PAM system. This modification entails constraining the PAM constellations to the size of the codeword’s symbol. The results obtained demonstrate the strength of the modified coded PAM system over the conventional PC coded PAM system.
The study presents a calculation method of the voltage induced by power-line sagged conductor in an inductively coupled overhead circuit of arbitrary configuration isolated from ground. The method bases on the solution utilizing the magnetic vector potential for modeling 3D magnetic fields produced by sagging conductors of catenary electric power lines. It is assumed that the equation of the catenary exactly describes the line sag and the influence of currents induced in the earth on the distribution of power line magnetic field is neglected. The method derived is illustrated by exemplary calculations and the results obtained are partially compared with results computed by optional approach.
The paper presents optimization of power line geometrical parameters aimed to reduce the intensity of the electric field and magnetic field intensity under an overhead power line with the use of a genetic algorithm (AG) and particle swarm optimization (PSO). The variation of charge distribution along the conductors as well as the sag of the overhead line and induced currents in earth wires were taken into account. The conductor sag was approximated by a chain curve. The charge simulation method (CSM) and the method of images were used in the simulations of an electric field, while a magnetic field were calculated using the Biot–Savart law. Sample calculations in a three-dimensional system were made for a 220 kV single – circuit power line. A comparison of the used optimization algorithms was made.
Low-power consumption and long-distance transmission are two problems that have to be solved by the application of broadband power line communication for the automatic meter reading system. To reduce the power consumption of the communication module, based on the analysis of the composition of the power consumption, some methods are proposed. From the communication chip level and the module circuit level, the design scheme of low-power consumption is given. To solve the problem of transmission distance, a frequency band of 2.44 MHz~5.6 MHz is used as the main working frequency band. The communication module supports multiple frequency bands. Using this feature, the optimal frequency band is adaptively selected for communication and automatic switching, which further improve the transmission distance. Field application shows that the above methods effectively decrease the power consumption of the communication module and extend the transmission distance.
To overcome the detrimental influence of α impulse noise in power line communication and the trap of scarce prior information in traditional noise suppression schemes , a power iteration based fast independent component analysis (PowerICA) based noise suppression scheme is designed in this paper. Firstly, the pseudo-observation signal is constructed by weighted processing so that single-channel blind separation model is transformed into the multi-channel observed model. Then the proposed blind separation algorithm is used to separate noise and source signals. Finally, the effectiveness of the proposed algorithm is verified by experiment simulation. Experiment results show that the proposed algorithm has better separation effect, more stable separation and less implementation time than that of FastICA algorithm, which also improves the real-time performance of communication signal processing.