多馈入直流系统(multi-infeed direct current,MIDC)多回直流间电气联系紧密,交流侧故障导致的换相失败若无干预极易引发后续连锁反应直至直流闭锁,严重毁坏系统安全稳定.动态无功补偿装置可在电压跌落瞬间为换流母线提供有效支撑,抑制直流后续换相失败风险,但由于配置成本较高,大规模应用仍较为困难.为合理降低动态无功补偿配置成本,提高配置方案的经济性和实用性,提出一种考虑抑制MIDC后续换相失败风险的节点差异化动态无功补偿方法.首先对后续换相失败发生机理进行分析,提出一种抑制后续换相失败风险效果的评价指标;根据节点特性对候选补偿节点进行了换相失败关联度的评估和预分区;建立了抑制后续换相失败风险的节点差异化动态无功补偿装置配置模型,利用基于精英改进策略的"教与学"优化(teaching-learning-based optimization,TLBO)算法求解该模型,得到了灵活考虑经济效益与无功补偿效果的动态无功补偿装置差异化配置方案;最后在PSD-BPA和MATLAB联合仿真平台上,用华东电网实际算例验证了所提方法的合理性与有效性.

转矩极限控制利用双馈风机(DFIG)的转子动能提供惯性响应,存在减速初期功率下降过快以及在加速阶段转速恢复速度较慢的问题.针对该问题,提出了一种改进频率控制方案.在减速阶段双馈风机提供恒定有功支撑,直至转子的动能达到最低限值或频率到达最低点,然后有功输出随转速线性下降,直到与机械功率的差额趋近于0;在加速阶段,双馈风机有功先随时间下降,然后维持恒定至与最大功率跟踪输出值相等.该方案能有效减小系统频率跌落幅度,同时避免二次跌落,且在较短时间内恢复转速.基于Matlab/Simulink仿真平台建立含风电场的3机9节点模型,通过仿真验证了所提控制方案的有效性和优越性.

提出了基于双馈风电机组的改进短时过载控制策略.首先阐述了DFIG的基本理论及运行特性,随后深入分析了目前常用的双馈风电机组短时过载控制方式的工作原理及其局限性,针对其存在转子动能过度释放的隐患及造成频率二次跌落的现象分析成因.基于此提出了改进短时过载控制策略,并利用Matlab/Simulink建立3机9节点系统模型进行仿真,验证了该策略提高暂态频率响应性能的有效性.

The doubly-fed induction generator (DFIG) uses the rotor’s kinetic energy to provide inertial response for the power system. On this basis, this paper proposes an improved torque limit control (ITLC) strategy for the purpose of exploiting the potential of DFIGs’ inertial response. It includes the deceleration phase and acceleration phase. To shorten the recovery time of the rotor speed and avoid the second frequency drop (SFD), a small-scale battery energy storage system (BESS) is utilized by the wind-storage combined control strategy. During the acceleration phase of DFIG, the BESS adaptively adjusts its output according to its state of charge (SOC) and the real-time output of the DFIG. The simulation results prove that the system frequency response can be significantly improved through ITLC and the wind-storage combined control under different wind speeds and different wind power penetration rates.

With the continuous expansion of wind power integration scale, the stability of the power system has been greatly affected, especially the changes of the traditional grid structure, which makes the system splitting face major challenges. In the context of the widespread use of wind energy, a bi-level planning method considering optimal location-allocation of wind power to reduce the difficulty of splitting was proposed. Based on the slow coherence theory, a correlation model that reflects the coherence degree of system buses was constructed. Furthermore, an improved intelligent optimization algorithm was proposed to solve the optimal location-allocation of wind power. The proposed method was conducted in the Institute of Electrical and Electronics Engineering (IEEE) 39-bus system to centralize the splitting scope. It is verified that the proposed method can reduce the system's possible oscillation modes to realize that less instability occurs under small disturbances, and restrict the range of splitting sections under large disturbances, which ensures the effectiveness of splitting devices to maintain the stable operation of the power grid.

With the increasing wind power in power systems and the wide application of frequency regulation technology, the accurate calculation of the limit wind power capacity in systems is critical to ensure the stability of the frequency and guide the planning of wind power sources. This paper proposes an analytical method for calculating the maximum wind generation penetration under the constraints of frequency regulation control and frequency stability taking doubly fed induction generator as an example. Firstly, the frequency-domain dynamic model of the doubly fed induction generator is established considering the supplementary frequency proportion-differentiation control under small disturbance. The equivalent inertia time constant of the doubly fed induction generator is calculated. On this basis, the frequency response model of the power system with the consideration of wind power integration in frequency regulation control is constructed. Then, the frequency-domain analytical solution of the system frequency is obtained. Finally, with the constraint by the steady-state deviation and dynamic change rate of the system frequency, the maximum wind generation penetration is analytically solved. The accuracy of the proposed analytical calculation method for the limit value of the percentage of wind power is verified by MATLAB/Simulink.

With the large-scale wind farm connected to the power grid, the impact on voltage stability is more serious. The research on the static voltage stability can better reflect the operation status of the system, the position of the weak buses and the voltage stability margin. This paper first analyzes the load margin index and the principle of the continuous power flow (CPF) algorithm. Then, the sensitivity index is used to determine the weak area of the system. And the P-V curves of these vulnerable buses are solved by CPF algorithm. Finally, after the wind farm is connected to the system, the impact of power injection of wind, line impedance ratio X/R and wind farm loads on the static voltage stability is discussed. To improve voltage stability, the reactive power compensation measure by grouped switched capacitors is proposed. Simulation results of the IEEE 30-bus system verify the correctness and effectiveness.

A robust and reliable grid is one of the core elements for power network planning. Specifically, splitting is an effective way for power grid out-of-step oscillation. Since the cross-section of system out-of-step is mostly found on the weak connection lines, reducing the number of those lines can be conducive to the system partition, save the finding time of the optimal splitting cross-section, and improve the performance of the splitting control. This paper proposed an enhanced method based on slow coherence theory for weak connection lines' identification and monitoring. The ratio of the number of weak connection lines to the number of all the lines, called weak connection coefficient, is considered as a crucial factor. A bi-level programming model, which perceives the minimum connection coefficient as the optimization goal, is built for the transmission network. Additionally, a fused algorithm, consisting of Boruvka algorithm and particle swarm optimization with adaptive mutation and inertia weight, is employed to solve the proposed method in the instances of an 18-node IEEE Graver system and a practical power grid in East China. Simulation results in PSD-BPA are conducted to verify the effectiveness of the weak connection monitoring method and transmission network planning model.

As the development of the power system is moving towards an intelligent direction, the probability of power system blackouts is effectively reduced. However, blackouts cannot be completely avoided due to many uncertainties. For a large-scale power system, there may be many generators with black-start capability and external power sources, which can be used as black-start power sources after a blackout. This paper presents a discrete particle swarm optimization (DPSO) system sectionalizing method, by which the entire blackout area can be sectionalized into several subsystems. Simulation results on the New England 39-bus system verify the effectiveness of the proposed parallel restoration scheme.

The DFIG uses a converter based on space vector pulse width modulation (SVPWM) to realize the decoupling of electromagnetic and mechanical power, but the DFIG cannot respond immediately when the power grid frequency fluctuates. In order to solve this problem, based on the existing model of the DFIG and its control methods, this paper proposes an additional frequency control link in the active power control of rotor side and make the DFIG's rotor release or absorb part of kinetic energy, which can change the active power output according to the change of the grid frequency, so as to realize the frequency control of wind turbines and increase the equivalent inertia of the power system. Simulation results demonstrate the effectiveness of the proposed method. The control strategy can make the wind farm of DFIGs participate in the frequency regulation of power system, and the regulation effect becomes better with the increase of wind power penetration rate.