研究了直驱风电场次同步振荡分析的降阶模型，提出了基于交替方向隐式(alternating direction implicit，ADI)的平衡截断方法。首先，根据直驱式永磁同步风电机组的数学表征搭建风电场的数学模型，采用ADI方法迭代求解李亚普诺夫方程，得到可控的格莱姆矩阵与可观的格莱姆矩阵；然后，采用平衡截断的方法得到降阶模型；通过对比全阶模型与降阶模型的时域仿真波形、Bode图、计算耗时以及次同步振荡模式，验证了方法的有效性。仿真结果表明，降阶模型与全阶模型具有很好的一致性，同时计算速度提高，降阶阶数大大降低。

A reduced order model for subsynchronous oscillation analysis of direct drive wind farm was studied, and a balanced truncation method based on alternating direction implicit (ADI) was proposed. Firstly, the mathematical model of wind farm was built according to the mathematical representation of direct-driven permanent magnet synchronous wind turbine. The ADI method was used to solve the Lyapunov equation iteratively, and the controllable and observable Gramm matrixs were obtained. Then, the balanced truncation method was used to obtain the reduced order model. The time domain simulation waveform, Bode diagram, calculation time and subsynchronous oscillation mode of the full order model and the reduced order model were compared to verify the effectiveness of the proposed method. The simulation results show that the reduced order model has good consistency with the full order model, and the calculation speed is improved and the number of reduced order is greatly reduced.

目的 针对弱电网背景下直驱风机网侧电流内环PI控制器带宽影响并网系统稳定性，诱发次同步振荡(subsynchronous oscillation，SSO)现象，提出改进线性状态误差反馈(linear state error feedback，LSEF)控制律的线性自抗扰控制器(linear active disturbance rejection control，LADRC)替换电流内环的PI控制器去抑制SSO。 方法 首先，对LADRC控制器的LSEF进行改进，并对其跟踪误差、抗扰性能进行分析。然后，推导出计及频率耦合影响的系统阻抗模型，并且利用Nyquist判据分析线路阻抗值对于网侧变流器并网系统稳定性的影响。最后，通过PSCAD/EMTDC仿真软件进行分析验证。 结果 相较于传统LADRC，改进LADRC使直流侧电压波动范围减少了85%，有功功率波动范围减少了89%。 结论 与传统LADRC控制器相比，改进LADRC控制器可以更好地缩小功率波动范围及直流侧电压波动范围，减小跟踪误差。

Objectives In response to the impact of the bandwidth of the current inner loop PI controller on the stability of the grid connected system of direct drive wind turbines under the background of weak electricity network, which leads to the induction of sub synchronous oscillation (SSO) phenomenon, a linear active disturbance rejection control (LADRC) was proposed to replace the current inner loop PI controller with an improved linear state error feedback control law (LSEF) to suppress SSO. Methods Firstly, the LSEF of the LADRC controller was improved, and the tracking errors and anti-interference capabilities were studied. Moreover, an impedance model for the system considering frequency coupling effects was developed, and the Nyquist criterion was employed to assess the impact of line impedance values on the stability of the grid-connected converter system. Finally, the analysis and validation were performed using PSCAD/EMTDC simulation software. Results Compared with traditional LADRC, the improved LADRC can reduce the DC side voltage fluctuation range by 85% and the active power fluctuation range by 89%. Conclusions Compared with traditional LADRC controllers, improved LADRC controllers can better reduce the range of power fluctuations, DC side voltage fluctuations, and tracking errors.

在积极践行“双碳”目标、构建新型能源体系和建设新型电力系统的背景下，加快构建更加灵活、清洁、可持续的低碳能源系统成为能源转型的必经之路。基于对能源生产供应体系所需进行的“五个转变”的分析，阐述了低碳能源系统的内涵特征，明确了其构建思路，并详细探讨了实现低碳能源系统所需关键技术的发展趋势与面临的挑战。在此基础上，从供给侧和需求侧角度列举了2个具体实践案例，并展望了低碳能源系统未来的发展趋势。

In the context of actively implementing the " peak carbon dioxide emission and carbon neutrality" goal， building a new energy system and constructing a new power system， accelerating the construction of a more flexible， clean and sustainable low-carbon energy system has become the only way to energy transformation. Based on the analysis of the "five transformations" needed in the energy production and supply system， this paper expounds the connotation and characteristics of low-carbon energy system， clariifies its construction ideas， and discusses the development trends and challenges of key technologies needed to realize low-carbon energy system in detail. On this basis， two practical cases are listed from the perspective of supply side and demand side. Finally， the future development trend of low-carbon energy system is prospected.

高比例新能源接入配电网对配电网电压控制造成了巨大挑战。传统电压控制方法在高比例可再生能源渗透的情景下无法取得满意的控制效果，同时传统电压控制依赖机械式调压设备，其频繁机械式动作显著影响了使用寿命。为解决以上问题，提出一种基于模型预测控制(model predictive control， MPC)的多层电压控制方法。在所提方法中，机械式调压设备，例如变压器和并联电容，在上层以较长控制周期进行控制；而下层，对分布式电源的有功和无功输出以较短的时间尺度进行快速调节。在所提方法中，上层控制的控制目标是降低机械式调压设备的动作次数，下层的控制目标为降低系统的网损和有功消减，保证配电网运行的经济性。所提方法考虑了配电网当前及将来的系统状态，能确保高比例新能源接入后电压在允许的范围内。仿真结果表明：所提方法能有效解决高比例风光接入配电网带来的电压越限问题，系统电压均方误差从3.9%降低至0.97%；同时，该方法能显著降低有载调压变压器和并联电容的动作次数，仅为传统电压控制方法的40%和16.4%。

The integration of high proportion of new energy into distribution networks poses significant challenges for voltage control of distribution network. Traditional voltage control methods cannot ensure satisfactory control performance in scenarios with high penetration of new energy. Additionally， traditional voltage control relies on mechanical voltage regulation equipment， and frequent operation of these equipment significantly affects their lifespan. To address these issues， this paper proposes a multilayer voltage control method based on model predictive control (MPC). In the proposed method， mechanical voltage regulation equipment， such as transformers and shunt capacitors， is controlled in the upper layer with a longer control period， while active and reactive power outputs of distributed generations are rapidly adjusted in the lower layer with a shorter timescale. The objective of the upper-layer control is to reduce the number of operation of mechanical voltage regulation equipment， while the lower-layer control aims to minimize network losses and active power curtailment， ensuring the economic operation of the distribution network. The proposed method considers both the current and future states of the distribution network， ensuring that voltage operates within allowed limits under high penetration of new energy. Simulation results show that the proposed method can effectively address the voltage violation issues introduced by the high penetration of new energy in the distribution network， decreasing the system voltage mean square error from 3.9% to 0.97%. Additionally， the proposed method significantly reduces operation number of mechanical voltage regulation equipment， which is only 40% and 16.4% of those under traditional voltage control methods， respectively.

Intending to reach the peak of carbon and carbon neutrality, to become a global consensus, and to achieve the goal of “reaching the peak of carbon emissions before 2023 and carbon neutrality before 2060”, China proposed in March 2021 to construct a new power system with new energy as its core. For the realization of the above goals, the construction of a pumped storage power station is quite important, and it is the key to the realization of green and low-carbon energy transformation and has a crucial impact on the achievement of China’s “double carbon” goal. This paper first introduces the related concepts of dual-carbon background and pumped storage power stations. Then the development dynamics of the station in a period are analyzed to obtain its characteristics, such as wide distribution, fast construction, and variety. Finally, this paper puts forward and summarizes the suggestions and prospects of pumped storage power stations for China’s new energy growth.

为解决超级电容能量密度小、在运行过程中荷电状态(state of charge, SOC)容易越限的问题，对传统低通滤波法进行改进，提出考虑超级电容SOC的功率分配策略。该方法依据超级电容的SOC划分5个不同的工作区域，并以超级电容的SOC作为变量，在不同工作区域同滤波时间常数建立相应的函数关系，之后根据SOC的变化动态调整滤波时间常数，实现蓄电池和超级电容之间功率的合理分配，保证超级电容SOC维持在合理范围内。最后，在Matlab/Simulink中搭建相关模型并仿真验证所提方案的正确性和有效性。仿真结果表明，同传统低通滤波法相比，该方法可在平抑功率波动的同时，根据超级电容的SOC合理分配超级电容和蓄电池的功率需求，使超级电容的SOC自行恢复，防止其过充过放，提高了直流微电网系统运行的经济性和稳定性。

In order to solve the problem that the energy density of supercapacitors is small and the state of charge(SOC) is easy to exceed the limit during operation, this paper improves the traditional low-pass filtering method and proposes a power allocation strategy considering the SOC of supercapacitors. The method divides five different working areas according to the supercapacitor SOC, and takes the supercapacitor SOC as the variable, establishes the corresponding functional relationship with the filter time constant in the different working areas, and then dynamically adjusts the filter time constant according to the SOC change, so as to realize the reasonable distribution of power between the battery and the supercapacitor, and ensure that the supercapacitor SOC is maintained in a reasonable range. Finally, the relevant model is built in Matlab/Simulink and the correctness and effectiveness of the proposed scheme is verified by simulation. The simulation results show that, compared with the traditional low-pass filtering method, this method can reasonably allocate the power demand of the supercapacitor and the battery according to the supercapacitor SOC while stabilizing the power fluctuation, so that the supercapacitor SOC can recover itself, prevent its overcharge and over discharge, and improve the economy and stability of the DC microgrid system operation.

针对风电场的有功功率波动,采用小波包分解的功率平抑算法,得到满足并网要求的低频信号分量和高频的混合储能系统参考功率,并使用低通滤波分频和信号平滑去噪方法获得飞轮储能和电池储能的参考信号,同时考虑放电深度和循环次数对电池储能系统寿命的影响,构建混合储能系统在计划年限内的全生命周期经济性模型,采用多跟踪器优化算法(MTOA)得到最优的混合储能容量配置。最后,结合风电场实际功率数据,仿真分析验证混合储能系统对功率平抑的有效性和经济性。结果表明:混合储能系统既能保证风电场的有功功率波动满足并网要求,又能充分发挥不同储能形式特性,降低系统运行成本。

In response to the fluctuation of active power in wind farms, a power smoothing algorithm based on wavelet packet decomposition was adopted to obtain low-frequency signal components that meet grid connection requirements and high-frequency hybrid energy storage system reference power. Low pass filtering, frequency division and signal smoothing denoising methods were used to obtain reference signals for flywheel energy storage and battery energy storage. Simultaneously, considering the impact of discharge depth and cycle count on the lifespan of the battery energy storage system, a hybrid energy storage system's full life cycle economy model was constructed within the planned years. The optimal configuration of the hybrid energy storage capacity was obtained through multi-tracker optimization algorithm (MTOA). Finally, based on actual power data from the wind farm, simulation analysis was conducted to verify the effectiveness and economic of hybrid energy storage system (HESS) in power smoothing. Results show that HESS can not only ensure that the active power fluctuation of the wind farm meets the grid connection requirements, but also fully utilize the characteristics of different energy storage forms to reduce the operating costs of the system.

为实现可再生能源的有效集成，减小风电的瞬时功率波动，利用锂电池类能量型储能与飞轮类功率型储能相结合的混合储能系统（HESS）对风电波动进行平抑。首先采用改进k-means算法得到典型日数据，利用经验模态分解（EMD）将其拆解得到HESS平抑任务；在综合考虑多种储能系统功率容量和充放电效率约束的基础上，构建相互协调运行的HESS能量管理系统。此外，以混合储能系统成本与风电功率机会补偿成本最低为目标函数，引入基准线变量和波动惩罚系数进行修正，构建平抑风电波动的HESS容量配置模型。最后结合实际并网数据，得到平滑效果和经济最优的配置方案。结果表明：所提配置方案风电累计欠补偿量共减少了91.8%，经济性提高了49.99%，最佳风储配比为1∶0.16，其中飞轮和锂电池比例为1∶4.65。

To achieve effective integration of renewables and reduce the instantaneous power fluctuations of wind power, a hybrid energy storage system (HESS) combining lithium battery-based energy storage and flywheel-based power storage was used to stabilize wind power fluctuations. Firstly, the improved <i>k</i>-means algorithm was used to obtain the typical daily data, and empirical mode decomposition (EMD) was used to disassemble it to obtain the HESS flattening task. Based on the comprehensive consideration of power capacity and charging-discharging efficiency constraints of various energy storage systems, a coordinated HESS energy management system was constructed. Moreover, with the minimum costs of hybrid energy storage system and wind power opportunity compensation as the objective function, a baseline variable and fluctuation penalty coefficient were introduced for correction, and a HESS capacity allocation model for stabilizing wind power fluctuations was developed. Finally, with the actual grid-connected data, a configuration scheme with optimized smoothing effect and economic performance was obtained. Results show that the cumulative under-compensation of wind power in the proposed configuration scheme is reduced by 91.8%, and the economic performance is increased by 49.99%. The optimal wind-storage ratio is 1∶0.16, of which the flywheel and lithium battery is 1∶4.65.