A split Bregman method solving optimal reactive power dispatch for a doubly-fed induction generator-based wind farm.

Area of Science:

• Electrical Engineering
• Renewable Energy Systems
• Optimization Theory

Background:

• Doubly-fed induction generators (DFIGs) are crucial for wind power integration.
• Optimizing reactive power control in wind farms is essential for revenue maximization and loss minimization.
• Existing control methods face challenges in distributed computation, information privacy, and fault tolerance.

Purpose of the Study:

• To propose an optimal reactive power control method for DFIG-based wind farms.
• To maximize wind farm revenue and minimize total electrical losses.
• To enhance system reliability and security during faults using a distributed approach.

Main Methods:

• The split Bregman method is employed to solve the optimal control problem in a distributed manner.
• The optimization problem is decomposed into independent sub-problems for local controllers.
• An economic financial model is developed to assess annual revenue, including impacts from certified emission reductions (CERs) under the clean development mechanism (CDM).

Main Results:

• The proposed split Bregman method yields the highest annual revenue (AR) compared to dual ascent (DA), sequential quadratic programming (SQP), and proportional dispatch method (PDM).
• The distributed control strategy effectively reduces computational burden and enhances information privacy.
• The method demonstrates robustness against system faults, improving overall system reliability and security.

Conclusions:

• The split Bregman method offers a superior approach for optimal reactive power control in DFIG wind farms.
• This distributed strategy balances economic benefits (revenue) with operational efficiency (loss reduction) and system resilience.
• The findings support the adoption of advanced optimization techniques for enhanced wind farm performance and economic viability.