Smooth Power Control Research Articles

Data-Driven Kernel Extreme Learning Machine Method for the Location and Capacity Planning of Distributed Generation

For the integration of distributed generations such as large-scale wind and photovoltaic power generation, the characteristics of the distribution network are fundamentally changed. The intermittence, variability, and uncertainty of wind and photovoltaic power generation make the adjustment of the network peak load and the smooth control of power become the key issues of the distribution network to accept various types of distributed power. This paper uses data-driven thinking to describe the uncertainty of scenery output, and introduces it into the power flow calculation of distribution network with multi-class DG, improving the processing ability of data, so as to better predict DG output. For the problem of network stability and operational control complexity caused by DG access, using KELM algorithm to simplify the complexity of the model and improve the speed and accuracy. By training and testing the KELM model, various DG configuration schemes that satisfy the minimum network loss and constraints are given, and the voltage stability evaluation index is introduced to evaluate the results. The general recommendation for DG configuration is obtained. That is, DG is more suitable for accessing the lower point of the network voltage or the end of the network. By configuring the appropriate capacity, it can reduce the network loss, improve the network voltage stability, and the quality of the power supply. Finally, the IEEE33&69-bus radial distribution system is used to simulate, and the results are compared with the existing particle swarm optimization (PSO), genetic algorithm (GA), and support vector machine (SVM). The feasibility and effectiveness of the proposed model and method are verified.

Comparative Analysis of Various Modulation Strategies for Induction Heating System

This paper presents a combined asymmetrical voltage cancellation and pulse density modulation technique for energy efficient induction heating system. The proposed technique minimizes the switching losses through soft switching operation and improves the efficiency at low power level. In this modulation technique, the smooth power control can be achieved. The study of power converter has been performed through MATLAB simulation tool and the results are presented. In this proposal, the efficiency of PDM and AVC control techniques are compared with the Hybrid Modulation technique.

Design and Evaluation of a Low-Cost High-Performance $ \Sigma$–$\Delta$ ADC for Embedded Control Systems in Induction Heating Appliances

The advantages of resonant power converters, such as high efficiency and high power density, make them a suitable solution for domestic applications such as induction heating (IH) cookers. The control systems of these appliances require performing accurate and smooth power control while assuring the safety of the power devices. In order to accomplish these tasks, it is necessary to have information about the target output power, which is selected by the user, and the specific parameters of the output current. In this paper, a single-bit second-order sigma-delta ( Σ-Δ) analog-to-digital converter (ADC) is proposed to measure the magnitude of interest in resonant power converters. An optimized digital low-pass filter architecture is proposed to extract the output current from the digitized bit stream. This filter improves the accuracy while having low logic-resource consumption. The proposed ADC has been verified using a resonant inverter applied to the IH cooktop application. The inverter switching frequency is in the range of 40-80 kHz. A statistical analysis of the final measurement system has been performed to assess the system accuracy. The proposed system achieves good accuracy in the inverter operating range.

An organic thyristor

Thyristors are a class of nonlinear electronic device that exhibit bistable resistance--that is, they can be switched between two different conductance states. Thyristors are widely used as inverters (direct to alternating current converters) and for the smooth control of power in a variety of applications such as motors and refrigerators. Materials and structures that exhibit nonlinear resistance of this sort are not only useful for practical applications: they also provide systems for exploring fundamental aspects of solid-state and statistical physics. Here we report the discovery of a giant nonlinear resistance effect in the conducting organic salt theta-(BEDT-TTF)2CsCo(SCN)4, the voltage-current characteristics of which are essentially the same as those of a conventional thyristor. This intrinsic organic thyristor works as an inverter, generating an alternating current when a static direct-current voltage is applied. Whereas conventional thyristors consist of a series of diodes (their nonlinearity comes from interface effects at the p-n junctions), the present salt exhibits giant nonlinear resistance as a bulk phenomenon. We attribute the origin of this effect to the current-induced melting of insulating charge-order domains, an intrinsically non-equilibrium phenomenon in the sense that ordered domains are melted by a steady flow.

Smooth power control for high current furnaces

A method is described whereby the temperature of resistances furnaces operating with currents of 500 to 2000 A can be adjusted continuously and smoothly. The furnace power is supplied from a saturable reactor, the output of which is controlled by a manually operated or motor driven auto-transformer in series with a rectifier. The system described will provide power output voltage supplies which vary as the first, second or third power of time, in response to impulses from a thermocouple or total radiation pyrometer.