海上风电场自适应多目标无功优化控制策略

针对传统固定权重多目标无功优化在应对新型电力系统复杂多变的工况时无法针对实时工况做出最合适的控制决策的问题，提出了一种自适应多目标无功优化控制策略，该策略以系统有功网损和并网点电压偏离量的加权最小作为目标函数，目标函数的权重系数根据并网点电压的偏离情况自适应调节。首先，分析海上风电场并网点电压波动与有功、无功输出的关系，建立相应的无功分配模型，并针对风电机组及静止无功发生器（static var generator，SVG）的输入输出特性，建立相应的无功控制模型。此外，考虑海上运行的功率约束、安全运行约束等，采用变惯性权重粒子群优化算法对无功控制策略进行求解。最后，在MATLAB中搭建海上风电场模型进行仿真验证，仿真算例表明：相较于传统固定权重多目标无功优化，自适应多目标无功优化控制策略可以根据电网实时工况，迅速调整各优化目标的优先级，较好地实现有功网损和并网点电压的协调优化。

Adaptive multi-objective reactive power optimization control strategy for offshore wind farms

Aiming at the problem that traditional fixed-weight multi-objective reactive power optimization cannot make the most appropriate control decisions for real-time operating conditions in response to complex and variable work circumstances of the new power system, an adaptive multi-objective reactive power optimization control strategy is proposed. The strategy takes the weighted minimum of the system active power loss and grid voltage deviation as the objective function, and adapts the weights of the objective function according to the degree of deviation of the grid voltage. Firstly, the relationship between the voltage fluctuation at the point of connection for offshore wind farms and the active and reactive power output is analyzed, and a corresponding reactive power allocation model is established. Additionally, considering the power constraints during offshore operations and safety regulations, an inertia weight particle swarm optimization algorithm is used to solve the reactive power control strategy by taking into account the input-output characteristics of the wind turbine generator and Static Var Generator (SVG). Finally, an offshore wind farm model is built in MATLAB for simulation verification. The simulation results demonstrate that compared to traditional fixed-weight multi-objective reactive power optimization, the adaptive multi-objective reactive power optimization control strategy can rapidly adjust the priority of each optimization objective according to the real-time operating conditions of the power grid, and achieve better coordination optimization between the active power loss and the grid connection voltage.