Power Loss Analysis for Wind Power Grid Integration Based on Weibull Distribution

The growth of electrical demand increases the need of renewable energy sources, such as wind energy, to meet that need. Electrical power losses are an important factor when wind farm location and size are selected. The capitalized cost of constant power losses during the life of a wind farm will continue to high levels. During the operation period, a method to determine if the losses meet the requirements of the design is significantly needed. This article presents a Simulink simulation of wind farm integration into the grid; the aim is to achieve a better understanding of wind variation impact on grid losses. The real power losses are set as a function of the annual variation, considering a Weibull distribution. An analytical method has been used to select the size and placement of a wind farm, taking into account active power loss reduction. It proposes a fast linear model estimation to find the optimal capacity of a wind farm based on DC power flow and graph theory. The results show that the analytical approach is capable of predicting the optimal size and location of wind turbines. Furthermore, it revealed that the annual variation of wind speed could have a strong effect on real power loss calculations. In addition to helping to improve utility efficiency, the proposed method can develop specific designs to speeding up integration of wind farms into grids

New Fuzzy Speed Controller For Dual Star Permanent Magnet Synchronous Motor

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Hyperparameter Bayesian Optimization of Gaussian Process Regression Applied in Speed-Sensorless Predictive Torque Control of an Autonomous Wind Energy Conversion System

This paper introduces a novel approach to speed-sensorless predictive torque control (PTC) in an autonomous wind energy conversion system, specifically utilizing an asymmetric double star induction generator (ADSIG). To achieve accurate estimation of non-linear quantities, the Gaussian Process Regression algorithm (GPR) is employed as a powerful machine learning tool for designing speed and flux estimators. To enhance the capabilities of the GPR, two improvements were implemented, (a) hyperparametric optimization through the Bayesian optimization (BO) algorithm and (b) curation of the input vector using the gray box concept, leveraging our existing knowledge of the ADSIG. Simulation results have demonstrated that the proposed GPR-PTC would remain robust and unaffected by the absence of a speed sensor, maintaining performance even under varying magnetizing inductance. This enables a reliable and cost-effective control solution

Analysis of the effect neutral connection mode for permanent magnet synchronous generator-vienna rectifier set

In this paper, it was considered to investigate a new electrical architecture for the conversion of mechanical energy from renewable sources into electrical energy, fault tolerant and high energy and dynamic performance for the exploitation of marine renewable energy (MRE). The architecture to be investigated concerns a three-phase permanent magnet synchronous generator combined with a Vienna rectifier, with a topology that minimizes the number of active switches to increase the reliability of the energy conversion chain. Despite the high non-linearity of this architecture, this control is made possible through to the dynamic performance and control of the maximum switching frequency of the self-oscillating controller called the Phase-Shift Self-Oscillating Current-Controller (PSSOCC). The study of the impact of the connection of the PMSG neutral to the mid-point of the DC bus is being investigated

Improved control strategy of dual star permanent magnet synchronous generator based tidal turbine system using sensorless field oriented control and direct power control techniques

International audienceThis paper aims at presenting an energy management strategy (EMS) based upon optimal control theory for a battery–supercapacitor hybrid power system. The hybrid power system consists of a lithium-ion battery and a supercapacitor with associated bidirectional DC/DC converters. The proposed EMS aims at computing adaptive gains using the salp swarm algorithm and load following control technique to assign the power reference for both the supercapacitor and the battery while achieving optimal performance and stable voltage. The DC/DC converter model is derived utilizing the first-principles method and computes the required gains to achieve the desired power. The fact that the developed algorithm takes disturbances into account increases the power elements’ life expectancies and supplies the power system with the required power