Abstract
With the continuing increase of offshore wind farm power scale, it is urgent to propose a simplified wind farm model, which aggregates the entire wind farm into single or several aggregated wind turbine generators (WTGs), aiming to save computing resources and improve simulation speed. A novel aggregation algorithm that considers the power loss of offshore submarine cable is proposed, which is different from the traditional wind farm modeling method that adopts amplifying transformer as aggregation medium. Moreover, multi machine aggregation (MMA) algorithm is furtherly proposed to improve the aggregation accuracy. Simulation results verify that the proposed aggregation method can present the dynamic characteristics of wind farm with high accuracy, and can be popularized for other types of wind farm.
Highlights
In recent years, the penetration of wind energy and the scale of wind farm are increasing rapidly (Zou et al, 2014), at the same time, since the energy efficiency for offshore wind energy is relatively higher than onshore wind energy, so there is an obvious trend that the application focus is shifting from offshore to onshore wind farm
A comprehensive aggregation algorithm is proposed considering the power loss of offshore wind farm submarine cable, including the aggregation of wind turbine generators (WTGs) electrical parameters, pneumatic parameters as well as the integration of transmission line, the power equivalent principle is used to calculate all the aggregation parameters of wind farm, simulation results verify that the proposed aggregation algorithm can match well with detailed model, while multi machine aggregation (MMA) model is more accurate than single machine aggregation (SMA) to reflect the operation of wind farm in various wind speed environment
When referring multi machine aggregation, wind speed for each WTG is selected as the main grouping index, all WTGs in a wind farm are grouped into four groups according to the WTG operation mode so as to minimize the aggregation error, since the operation mode is directly related to the wind speed and wind speed can be well estimated and calculated through various prediction algorithm, so it is easy to group one single wind farm based on wind speed for each WTG
Summary
The penetration of wind energy and the scale of wind farm are increasing rapidly (Zou et al, 2014), at the same time, since the energy efficiency for offshore wind energy is relatively higher than onshore wind energy, so there is an obvious trend that the application focus is shifting from offshore to onshore wind farm. Unlike the overhead line collection lines of onshore wind farms, the charging capacity of the cable collection lines of offshore wind farms is very large, generally 20–25 times than that of the overhead line circuits, which is equivalent to the reactive power compensation equipment being connected in parallel, so ignoring the transmission line capacitance in the conventional aggregation method will bring great errors, and the aggregation result will have a significant difference between the detailed model and the aggregated model. According to the principle that the reactive power consumed on the capacitor before and after the cable line equivalence is the same, the equivalent capacitor can be expressed as: Ceq. Equations 1–9 are the main calculation algorithm for PMSM wind farm single machine aggregation. When referring multi machine aggregation, wind speed for each WTG is selected as the main grouping index, all WTGs in a wind farm are grouped into four groups according to the WTG operation mode so as to minimize the aggregation error, since the operation mode is directly related to the wind speed and wind speed can be well estimated and calculated through various prediction algorithm, so it is easy to group one single wind farm based on wind speed for each WTG
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