摘要
大规模风电并网导致电网惯量不断削弱、系统频率特性恶化,虚拟惯量控制使风电具有与同步发电机相似的虚拟惯量,为电网提供惯量支撑,但需要根据频率安全约束,研究多个风电场对系统惯量支撑目标的协调分配。提出基于改进粒子群算法的风电场虚拟惯量优化分配方法。首先根据电网频率安全约束指标求解维持频率动态稳定的电网临界惯量,并结合电网实际惯量得到电网惯量补偿目标。然后将系统最大频率偏差最小作为优化目标,风电场虚拟惯量补偿目标作为优化对象,建立优化分配模型;采用改进粒子群算法求解该模型,得到虚拟惯量最优分配方案。最后在IEEE-39节算例系统中验证了所提方法的正确性和有效性。
The large-scale wind power grid connection leads to the continuous weakening of grid inertia and the deterioration of the system frequency characteristics.The virtual inertia control makes the wind power have the virtual inertia similar to the synchronous generator,and provides the inertia support for the grid.However,it is necessary to study the coordinated distribution of inertia support targets for multiple wind farms according to frequency safety constraints.The wind farm virtual inertia optimization allocation method based on improved particle swarm optimization algorithm is proposed.Firstly,the critical inertia of power grid to maintain dynamic stability of frequency is solved according to the frequency security constraint index of power grid,and the inertia compensation target of power grid is obtained combined with the actual inertia of power grid.Secondly,taking the minimum deviation of system maximum frequency as optimization target,the virtual inertia compensation target of wind farm as the optimization object,an optimization allocation model is established.Then the improved particle swarm optimization algorithm is used to solve the model,and the optimal allocation scheme of virtual inertia is obtained.Finally,the correctness and effectiveness of the proposed method are verified in IEEE-39 bus example system.
作者
李世春
苏凌杰
张志刚
罗林华
王丽君
王小雨
LI Shichun;SU Lingjie;ZHANG Zhigang;LUO Linhua;WANG Lijun;WANG Xiaoyu(College of Electrical Engineering and New Energy,China Three Gorges University,Yichang 443002,China;Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station,China Three Gorges University,Yichang 443002,China;Ningbo Electric Power Design Institute,Ningbo 315000,China)
出处
《智慧电力》
北大核心
2023年第8期8-14,22,共8页
Smart Power
基金
国家自然科学基金资助项目(51907104)。
关键词
大规模风电
虚拟惯量
优化分配
改进粒子群算法
临界惯量
large scale wind power
virtual inertia
optimize allocation
improved particle swarm optimization algorithm
critical inertia
