As a key component in the wind turbine system, the power electronic converter and its power semiconductors suffer from complicated power loadings related to environment, and are proven to have high failure rates. Therefore, correct lifetime estimation of wind power converter is crucial for the reliability improvement and also for cost reduction of wind power technology. Unfortunately, the existing lifetime estimation methods for the power electronic converter are not yet suitable in the wind power application, because the comprehensive mission profiles are not well specified and included. Consequently, a relative more advanced approach is proposed in this paper, which is based on the loading and strength analysis of devices and takes into account different time constants of the thermal behaviors in power converter. With the established methods for loading and lifetime estimation for power devices, more detailed information of the lifetime-related performance in wind power converter can be obtained. Some experimental results are also included to validate the thermal behavior of power device under different mission profiles.

Thermal Loading and Lifetime Estimation for Power Device Considering Mission Profiles in Wind Power Converter

Similar to other renewable energy sources, wind energy is characterized by a low power density. Hence, for wind energy to make considerable contributions to the world's overall energy supply, large wind farms (on- and offshore) consisting of arrays of ever larger wind turbines are being envisioned and built. From a fluid mechanics perspective, wind farms encompass turbulent flow phenomena occurring at many spatial and temporal scales. Of particular interest to understanding mean power extraction and fluctuations in wind farms are the scales ranging from 1 to 10 m that comprise the wakes behind individual wind turbines, to motions reaching 100 m to kilometers in scale, inherently associated with the atmospheric boundary layer. In this review, we summarize current understanding of these flow phenomena (particularly mean and second-order statistics) through field studies, wind tunnel experiments, large-eddy simulations, and analytical modeling, emphasizing the most relevant features for wind farm design and operation.

Flow Structure and Turbulence in Wind Farms

This paper deals with power fluctuations from wind farms. The time range in focus is between one minute and up to a couple of hours. In this time range, substantial power fluctuations have been observed during unstable weather conditions. A wind power fluctuation model is described, and measured time series from the first large offshore wind farm, Horns Rev in Denmark, are compared to simulated time series. The comparison between measured and simulated time series focuses on the ramping characteristics of the wind farm at different power levels and on the need for system generation reserves due to the fluctuations. The comparison shows a reasonable agreement between simulations and measurements, although there is still room for improvement of the simulation model.

Power Fluctuations From Large Wind Farms

The increasing penetration of wind power impacts the frequency stability of power systems. A doubly fed induction generator (DFIG)-based wind power plant naturally does not provide frequency response because of the decoupling between the output power and the grid frequency. DFIGs also lack power reserve margin because of the maximum power point tracking (MPPT) operation. Therefore this study presents a novel frequency regulation by DFIG-based wind turbines to coordinate inertial control, rotor speed control and pitch angle control, under low, medium or high wind speed mode. Inertial control emulates the inertia of wind generators and supports frequency control during transient. The gain of inertial control is calculated from a creative viewpoint of protecting the wind turbine from stalling. Rotor speed control and pitch angle control enable DFIGs to reserve sufficient active power for a steady-state frequency adjustment. The numerical simulations demonstrate that the coordinated control enhances the frequency regulation capability and damps the frequency oscillations effectively.

Coordinated frequency regulation by doubly fed induction generator-based wind power plants

Wind models for simulation of power fluctuations from wind farms

Wind models for prediction of power fluctuations from wind farms

Fast wind modelling for wind turbines

Electric vehicle (EV) charging may impose a substantial power demand on existing low voltage (LV) and medium voltage (MV) networks, which are usually not prepared for high power demands in short time intervals. The influx of E-mobility may require an increase in grid reinforcements, but these can be reduced and optimized by a combination of new technologies, tools, and strategies, such as the deployment of solar PV generation integrated with aggregated energy storage systems. One of the challenges in the implementation of charging infrastructures in public stations is coupling the projected sizes of energy demand and power requirements in each location for each charger. This paper describes a method to estimate projected values for energy consumption and power demand in EV fast charging stations (CS). The proposed ideas were applied in a concept facility located in Campinas, Brazil, in a structure equipped with two 50 kW DC Fast Chargers, local 12.5 kW/13.2 kWp PV generation (to reduce energy impacts to the grid), and a 100 kW/200 kWh storage system, using electrochemical batteries (to minimize peak power requirements).

https://www.mdpi.com/1996-1073/15/17/6106/pdf?version=1661257259

Pedro Andre Carvalho Rosas

Papers

Wind models for simulation of power fluctuations from wind farms

Wind models for prediction of power fluctuations from wind farms

Fast wind modelling for wind turbines

Energy and Demand Forecasting Based on Logistic Growth Method for Electric Vehicle Fast Charging Station Planning with PV Solar System

A frequency domain model for wind turbines power quality analysis (poster)