Multi-objective particle swarm optimization based reactive power coordination control strategy for wind farms

Voltage stability problem is one of the most significant problems faced by grid-connected operation of wind farms. Traditionally, each wind farm adjusts its reactive power and voltage independently, which can not be able to optimize the regional power grid dispatching. In order to improve the voltage stability and operating economy of regional power grid connected with medium or large-scale wind farms, this paper presents a reactive power coordination optimization model to satisfy reactive power management of a wind farm group. To solve this multi-objective optimization problem, multi-objective particle swarm optimization algorithm was adopted for fast reactive power regulating of the wind farm group. Simulation results on case study demonstrated the effectiveness and feasibility of the proposed algorithm for reactive power coordination control considering voltage stability and economic operating.

[1]  I. Erlich,et al.  Impact of distributed generation on the stability of electrical power system , 2005, IEEE Power Engineering Society General Meeting, 2005.

[2]  Wang Hong-tao Two-tier and multi-stage voltage coordination control method for regional power grid with wind farms , 2012 .

[3]  Wang Qi,et al.  The cooperating distribution methods of reactive power in multi-wind farms integrated region , 2012 .

[4]  Carlos A. Coello Coello,et al.  Handling multiple objectives with particle swarm optimization , 2004, IEEE Transactions on Evolutionary Computation.

[5]  Fangxing Li,et al.  Reactive power planning considering high penetration of wind energy , 2014, 2014 IEEE PES T&D Conference and Exposition.

[6]  Chen Ning,et al.  An Approach to Configure Reactive Power in Wind Power Base Considering Operational Risk of Power Grid , 2013 .

[7]  S. Lauria,et al.  Voltage and reactive power control for maximum utilization of a GW-size EHVAC offshore wind farm interconnection , 2014 .

[8]  Tang Jun Principle and Application of PSO Algorithm , 2010 .

[9]  Min Yong Study on Reactive Power and Voltage Coordinated Control Strategy of Wind Farm Group , 2010 .

[10]  Prospero C. Naval,et al.  An effective use of crowding distance in multiobjective particle swarm optimization , 2005, GECCO '05.

[11]  Li Huiyu,et al.  Strategy of Large Power System Coping with Accession of Microgrid with High Penetration , 2010 .

[12]  T.K. Saha,et al.  Investigation of power loss and voltage stability limits for large wind farm connections to a subtransmission network , 2004, IEEE Power Engineering Society General Meeting, 2004..