摘要:功角实时计算通常应用于电力系统稳定分析与振荡识别，但是现有的线路功角计算方法在两侧电势幅值不相等时存在较大误差，为此提出了一种新的实时功角计算方法。针对计算电压最低点位于电势连线内、外两种情况进行讨论，得到不同状态下的功角计算公式，并对两种功角计算公式进行判别。考虑到以稳态母线电压来近似电势幅值，会给功角计算带来一定误差，为此对电势幅值进行修正，并将修正后的功角计算误差与现有方法的误差进行对比。基于PSCAD的仿真验证证明了新方法的可靠性和有效性。结果表明，相比于现有功角计算方法而言，新方法有效降低了两侧电势幅值不相等时功角计算的误差，具有良好的计算精度和实用效果。

摘要:为了突破机组组合算法的自主可控问题，基于开源混合整数线性规划求解器CBC，提出一种快速获取机组组合问题可行解的固定—推断法。首先将机组组合模型转换为推断标准模型，然后按重要性对所有整数变量进行排序。并利用约束违反函数依次确定整数变量的值，实现整数变量的固定，利用约束关系推断出与其相关的整数变量值。最后经过多轮的固定—推断可以实现所有整数变量的取值，从而求解一个线性规划问题即可得到各机组的出力。仿真结果表明，所述算法能有效求解大规模机组组合问题，可在更短时间内获取质量较好的可行解。与CBC求解器结合，能显著提升CBC求解器对于机组组合问题的求解效率。此外，所述算法还具备在其他求解器上进行定制的潜力。

摘要:动态电压调节器(DVR)与模块化多电平转换器(MMC)组合的MMC-DVR可用于解决中高电压的动态电压补偿问题。目前MMC-DVR基本采用PID等线性控制方法，而MMC-DVR为非线性系统，因而其控制效果并不能令人满意。为此，提出了针对非理想条件下MMC-DVR系统的非线性李雅普诺夫(Lyapunov)控制方法来解决此问题。首先，建立MMV-DVR的数学建模。接着，设计了非理想条件下正、负序MMC-DVR的Lyapunov控制系统。最后，通过实验验证了所提的Lyapunov控制方法用于MMC-DVR的正确性和有效性。与传统PID控制相比，Lyapunov控制方法的电压在理想、非理想的多种不同工况下都能得到很好的补偿，且系统的动态响应更快、鲁棒性更强。

摘要:随着可再生能源渗透率的逐步提高，电力系统惯性水平下降，系统频率安全稳定面临挑战，迫切需要配置需求侧快速响应资源参与系统频率调节服务。针对此问题，分析了变频空调、储能和电动汽车提供电力系统调频备用的可行性，建立考虑上述需求侧快速响应资源的频率安全约束联合经济调度模型，以进行源荷双侧调频备用的统一优化。然后，引入基于高维模型表达的数据驱动方法将调频备用与最大频率偏移量之间的高阶非线性、隐式关系转换为低阶、显式表达式，从而实现频率安全约束经济调度模型的简化和求解。最后，结合IEEE 30节点系统验证了所提调度模型和方法的有效性，以及所提的数据驱动频率安全约束可确保系统在不平衡功率下的异常频率在约束范围内，且需求侧快速响应资源对于提升系统频率韧性具有重要正向作用。

摘要:对于带锁相环的并网VSC大扰动稳定性问题，首先依据VSC的内环电流控制和外环功率控制响应速度差异得到简化二阶非线性模型，然后分别定义了两个李雅普诺夫函数。第一个李雅普诺夫函数具有清晰的动能和势能概念，但推导的稳定域较小，第二个李雅普诺夫函数推导的稳定域较大但缺乏清晰的物理概念。最后结合这两个李雅普诺夫函数，得到实用的稳定性判据，兼具明确的物理意义和较宽的稳定域。如果在系统最后一次动作时已知锁相环状态量，则可以预测系统稳定性。仿真结果验证了该判据的正确性。

摘要:考虑到地磁感应电流(geomagnetically induced current, GIC)具有低频性，过去一直将其近似等效为高压直流输电(high voltage direct current, HVDC)诱发的不平衡电流进行研究。然而，与HVDC型直流偏磁相比，GIC型直流偏磁具有显著的随机性与时变性，因此简单地将两者完全等效处理并不合理，在特定场景下应加以区分。为此，首先，从理论上分析了两种类型直流偏磁在诱发原因及特点上的差异。其次，通过研究直流偏磁对变压器本体以及电流互感器的不利影响，进一步探究两种类型直流偏磁对电网一/二次设备的影响差异，为后续的偏磁治理提供有效参考。最后，基于PSCAD/EMTDC仿真平台搭建了等效仿真模型，并通过仿真验证了理论分析的正确性。

摘要:水轮机在云南电网中占比很大，为了解决水轮机的水锤效应带来的功率反调现象，提出了一种考虑风电调频特性补偿水锤效应的分析方法。首先，建立了含风、水、网、荷的简单系统数学模型。其次，使用直流潮流法得到水轮机及其调频策略、风机及其调频策略所对应的代数微分方程和系统网络方程。并在此基础上进行线性化处理，推导出负荷扰动时水轮机和风机并网节点频率响应的频域解析式。根据解析式分析调频控制参数等对系统频率的影响。最后，通过以双机系统及实际电网的仿真分析对风机补偿水轮机水锤效应的有效性和可行性进行了验证。

摘要:针对含新能源的多区域电力系统频率稳定问题，提出一种考虑控制信号更新周期变化的采样负荷频率控制(load frequency control, LFC)方案。首先，在充分考虑系统采样特性的基础上，建立新型电力系统采样LFC模型，并将模型转化为一个采样数据网络控制系统。然后，利用整个采样区间 信息，构建一个新的双边闭环型Lyapunov泛函。结合所提出的泛函与自由矩阵不等式，导出系统的低保守性稳定准则。基于这个准则，提出确保系统镇定的采样控制器设计方法。最后，通过实例仿真验证了所提方法的有效性与优越性。

摘要:现代电动汽车(electrical vehicle, EV)用户需求响应具有多样性和意愿模糊性的特点，当实施单一激励政策时，EV响应将达不到预期效果。为此，提出了考虑车主多模式需求响应及其模糊意愿的含EV微电网的主从博弈优化调度策略。微电网主体针对净负荷制定多模式动态电价激励政策，引导EV在多模式电价中做出选择，促进EV有序充放电，实现其净负荷均方差和运行成本最小。车主从体基于模糊逻辑推理意愿决策，响应多模式动态电价，极小化车主成本。采用非支配排序遗传算法(NSGA-Ⅱ)求解优化模型，获得最优多模式动态电价和EV充放电策略。仿真结果验证了所提方法的有效性。

摘要:针对传统无迹卡尔曼滤波(unscented kalman filter, UKF)谐波状态估计算法存在时变噪声和异常数据时估计准确度较差的情况，提出了一种基于自适应平方根无迹卡尔曼滤波(square- root UKF, SRUKF)的电力系统谐波状态估计算法。首先，针对时变噪声干扰，引入改进的Sage-Husa噪声估计方法实时估计噪声协方差。其次，针对异常数据干扰，引入异常数据修正方法，通过修正系数来降低异常数据对状态估计结果的影响。最后，通过搭建IEEE14节点系统验证自适应SRUKF算法的估计性能，能够有效地应用于电力系统的动态谐波状态估计。仿真结果表明，该算法在时变噪声和异常数据干扰时仍具有良好的估计性能。

摘要:为了提高综合能源服务商运营服务的高效性、清洁性和经济性，提出了一种基于需求侧博弈的综合能源服务商最优运营策略。通过对综合能源服务商模型的分析，以用户能源消耗量确定系统碳排放量，建立了区域综合能源服务商碳排放模型，确定了园区的碳排放量。在此基础上，考虑了用户对用能成本波动的可承受能力和服务商应对用户用能变化的风险成本，分别以综合能源服务商全天利润最大、用户用能成本最小为目标函数，建立了综合能源服务商-多用户博弈优化模型。采用迭代搜索法得到纳什均衡解，从而确定服务商最优运营策略。最后以典型工业园区为例对所提策略进行仿真验证。结果表明，所研究的服务商运营策略有效降低了系统碳排放量，提高了综合能源服务商的经济效益和用户满意度。

摘要:为充分发挥光储联合系统提供调频辅助服务的能力、提高联合系统的收益，提出了一种基于自动发电控制(automatic generation control, AGC)调频分区控制的光储联合系统参与市场的投标策略。首先，考虑了光储系统运行特性和电网频率波动不确定性，提出了光储系统参与能量-调频市场的日前-实时两阶段交易方法。其次，提出了光储系统参与AGC的实时调频控制方法，根据区域控制偏差所处控制域动态分配光储系统所承担的调节量。然后，构建了光储联合系统参与电力市场的多时间尺度投标优化模型，其中日前市场考虑了潜在的实时能量偏差，实时市场利用滚动优化方法反馈校正多种不确定因素。最后，通过算例分析验证了该策略在充分考虑电力系统频率安全稳定的前提下，使利润增加了14.9%，显著提高了光储联合系统的收益。

摘要:针对目标域负荷数据样本不足导致模型训练不充分从而预测精度不高的问题，提出一种改进的分层级迁移学习策略结合多尺度CNN-BiLSTM-Attention模型的短期电力负荷预测方法。设计串并行相叠加的多尺度CNN作为特征提取器，把提取到的特征作为输入传递到两层BiLSTM结构进行进一步的学习，引入注意力机制调节捕获的信息向量权重。按照基础模型的结构划分层级，将源域数据按照拟合优度值的高低输入至模型进行分层级的迁移学习训练，保留每一层最优的训练权重，之后使用目标域数据对模型进行微调得到最终的预测模型。经实验证明，所提出的多尺度CNN-BiLSTM-Attention模型能有效提高负荷预测精度，在负荷数据样本不足时，改进的分层迁移学习策略相比于直接迁移学习能有效降低预测误差。以目标域6个月数据为例，MAPE指标降低13.31%，MAE指标降低15.16%，RMSE指标降低14.37%。

摘要:交直流混合电力系统中的有载调压变压器(on-load-tap-changer, OLTC)和换流器模型存在大量限幅、死区等非光滑特性，如何处理换流器引入的分段函数约束是当前状态估计的研究难点。构建了OLTC的混合整数非线性(mixed integer nonlinear programming, MINLP)模型，通过控制二次侧电压水平得到OLTC挡位的估计值。针对换流器采用分段函数描述包含限幅、死区等下垂控制特性的问题，提出采用近似拟合函数将分段函数光滑化。与采用MINLP描述分段函数的方法相比，所提模型显著提高了计算效率。通过3节点和IEEE14节点交直流混合系统算例，验证了所提状态估计模型的正确性和实用性，同时分析了拟合系数对状态估计的影响。算例表明，所提模型增强了状态估计处理不良数据的能力，提高了对非光滑特性的适应能力，在保证计算精度的前提下能够提高状态估计的收敛性。

摘要:输电线路上的鸟巢会对电力设备的安全运行构成威胁，甚至影响整个电力系统的稳定性。针对复杂场景下输电线路鸟巢检测方法适用性较差的问题，提出一种基于改进YOLOv5的输电线路鸟巢检测方法。该方法结合通道注意机制和空间注意机制设计特征平衡网络，以通道权值和空间权值作为引导，实现检测网络不同层次特征之间语义信息和空间信息的平衡。同时，为了避免因网络层数增加导致特征信息不断被弱化的问题，设计特征增强模块以捕获与鸟巢相关的通道关系和位置信息。最后，利用输电线路无人机巡检图像建立鸟巢数据集进行训练和测试。实验结果表明，所提出的输电线路鸟巢检测方法具有较强的泛化能力和适用性，同时也为电力图像缺陷检测提供技术参考。

摘要:新型电力系统的大力建设对电网监控信号的高效准确识别技术提出了更高的要求。首先分析了Soft-Masked BERT语言模型的基本原理，建立了基于Soft-Masked BERT的信号文本纠错模型。根据国家电网典型事件表梳理了包含常规与故障情况下的“信号语义—电网事件”规则字典。综合上述模型建立了基于RNN的电网态势感知模型，提出了基于深度学习的电网监控信号语义解析及态势感知求解流程。最后，以某地110 kV变电站实际监控信号为测试数据，利用所提RNN模型并结合Pycorrector工具包及Pytorch软件对该地区电网监控信号进行语义解析及态势感知仿真分析，验证了模型的有效性及正确性。

摘要:针对现有智能优化算法在求解主动配电网故障定位问题时存在的收敛速度慢、易陷入局部最优解、容错性差、种群质量低等问题，提出一种改进的多元宇宙优化算法(improved multi-verses optimization, IMVO)。首先构建具有容错能力的主动配电网模型，根据故障定位问题的特点对多元宇宙的种群进行离散化编码。其次将自适应精英策略融入改进算法的多元宇宙种群的更迭中，以保证多元宇宙的种群质量。设计基于非线性曲线变化的虫洞存在概率(wormhole existence probability, WEP)与旅行距离率(travel distance rate, TDR)的更新机制，以提高算法前段搜寻相对最优宇宙的能力与后段调整最优探测距离的精度。最后通过自适应突变操作增强改进算法的局部搜索能力，进而提高全局寻优能力。仿真实验结果表明，改进多元宇宙优化算法在单点、多点以及信息畸变故障定位中全局寻优能力显著，相较于其他优化算法在解决配电网故障定位问题上具有更高的准确率与收敛速率。

摘要:在智慧楼宇以及电力检修运维中，需要及时获取设备或人员位置信息。针对室内因非视距传输和多径效应引起的定位精度不高问题，提出了一种基于奇偶交错布局的室分与5G结合的室内三维定位方案。首先，采用到达时间差(time difference of arrival, TDOA)和到达角度(angle of arrival, AOA)融合定位。其次，把具体定位算法融入到定位架构里，基于边缘计算快速获取室内对应移动目标的位置信息。在进行TDOA定位过程中，MEC端的定位服务器结合压缩感知进行信道估计，并在分段正交匹配追踪(stagewise orthogonal matching pursuit, StOMP)算法的基础上加入奇异值进行降噪处理。在进行AOA定位过程中，先利用改进的波束空间变换技术构造矩阵进行降维，为保证降维过程中信息不损失，提出对附加角度误差进行分析处理，然后，采用多重信号分类(multiple signal classification, MUSIC)算法进行定位。最后，5GC核心网服务器利用Chan-Taylor算法进行TDOA/AOA融合定位。仿真结果证明了所提出的定位方法能够实现对移动目标的精准定位。

摘要:State estimation plays a vital role in the stable operation of modern power systems, but it is vulnerable to cyber attacks. False data injection attacks (FDIA), one of the most common cyber attacks, can tamper with measurement data and bypass the bad data detection (BDD) mechanism, leading to incorrect results of power system state estimation (PSSE). This paper presents a detection framework of FDIA for PSSE based on graph edge-conditioned convolutional networks (GECCN), which use topology information, node features and edge features. Through deep graph architecture, the correlation of sample data is effectively mined to establish the mapping relationship between the estimated values of measurements and the actual states of power systems. In addition, the edge-conditioned convolution operation allows processing data sets with different graph structures. Case studies are undertaken on the IEEE 14-bus system under different attack intensities and degrees to evaluate the performance of GECCN. Simulation results show that GECCN has better detection performance than convolutional neural networks, deep neural networks and support vector machine. Moreover, the satisfactory detection performance obtained with the data sets of the IEEE 14-bus, 30-bus and 118-bus systems verifies the effective scalability of GECCN.

摘要:Emerging sub-synchronous interactions (SSI) in wind-integrated power systems have added intense attention after numerous incidents in the US and China due to the involvement of series compensated transmission lines and power electronics devices. SSI phenomenon occurs when two power system elements exchange energy below the synchronous frequency. SSI phenomenon related to wind power plants is one of the most significant challenges to maintaining stability, while SSI phenomenon in practical wind farms, which has been observed recently, has not yet been described on the source of conventional SSI literature. This paper first explains the traditional development of SSI and its classification as given by the IEEE, and then it proposes a classification of SSI according to the current research status, reviews several mitigation techniques and challenges, and discusses analysis techniques for SSI. The paper also describes the effect of the active damping controllers, control scheme parameters, degree of series compensation, and various techniques used in wind power plants (WPPs). In particular, a supplementary damping controller with converter controllers in Doubly Fed Induction Generator based WPPs is briefly pronounced. This paper provides a realistic viewpoint and a potential outlook for the readers to properly deal with SSI and its mitigation techniques, which can help power engineers for the planning, economical operation, and future expansion of sustainable development.

摘要:An integrated energy system with multiple types of energy can support power shortages caused by the uncertainty of renewable energy. With full consideration of gas network constraints, this paper proposes a multi-energy inertia-based power support strategy. The definition and modelling of gas inertia are given first to demonstrate its ability to mitigate power fluctuations. Since partial utilization of gas inertia can influence overall gas network parameters, the gas network is modelled with an analysis of network dynamic changes. A multi-energy inertia-based power support model and strategy are then proposed for fully using gas-thermal inertia resources in integrated energy systems. The influence of gas network constraints on strategy, economy and power outputs is analyzed. Special circumstances where the gas network can be simplified are introduced. This improves the response speed and application value. The feasibility and effectiveness of the proposed strategy are assessed using a real scenario.

摘要:Thermostatically controlled loads (TCLs) are regarded as having potential to participate in power grid regulation. This paper proposes a scheduling strategy with three-stage optimization for regional aggregators jointly participating in day-ahead scheduling to support demand response. The first stage is on the profit of aggregators and peak load of the grid. The line loss and voltage deviation of regulation are considered to ensure stable operation of the power grid at the second stage, which guarantees the fairness of the regulation and the comfort of users. A single temperature adjustment strategy is used to control TCLs to maximize the response potential in the third stage. Finally, digital simulation based on the IEEE 33-bus distribution network system proves that the proposed three-stage scheduling strategy can keep the voltage deviation within ± 5% in different situations. In addition, the Gini coefficient of distribution increases by 20% and the predicted percentage of dissatisfied is 48% lower than those without distribution.

摘要:Voltage imbalance (VI) is caused by the difference in connected single-phase load or generation in a low voltage distribution network (DN).VI increase in a smart distribution grid is due to the current practice of increasing single-phase distributed generators such as photovoltaic (PV) systems. This paper proposes a decentralized control method to mitigate VI using distributed batteries included in smart grid interfaced residential PV systems. To mitigate VI using the batteries in this way, five challenges must be overcome, i.e., equalizing all battery stress currents within the DN, mitigating VI in abnormal conditions such as signal loss among bus controllers, being immune from the distorted feedback measurements, minimizing the steady-state error at different loads, and overcoming the insufficient number or capacity of the distributed batteries at the same bus. Three fuzzy logic controllers (FLC) are proposed at each bus to overcome these five tasks based on a decentralized control scheme. The proposed decentralized control based on FLC is compared with centralized control based on a PI controller. The proposed control method is tested and verified using simulations in the MATLAB/Simulink software, and the results validate the ability of the scheme to alleviate VI on a smart distribution network under both normal and abnormal conditions.

摘要:The ongoing transformation of electrical power systems highlights the weaknesses of the protection schemes of traditional devices because they are designed and configured according to traditional characteristics of the system. Therefore, this work proposes a new methodology to study the fault-generated high frequency transient signals in transmission lines through multiresolution analysis. The high frequency components are determined by a new digital filtering technique based on mathematical morphology theory and a spectral energy index. Consequently, wide spectra of signals in the time–frequency domain are obtained. The performance of this method is verified on an electrical power system modeled in ATP-Draw, where simulation and test signals are developed for different locations, fault resistances, inception angles, high frequency noises, sampling frequencies, types of faults, and shapes of the structuring element. The results show the characteristics of the fault such as the traveling wave frequency, location, and starting time.

摘要:With the rapid development of electrical power systems in recent years, microgrids (MGs) have become increasingly prevalent. MGs improve network efficiency and reduce operating costs and emissions because of the integration of distributed renewable energy sources (RESs), energy storage, and source-load management systems. Despite these advances, the decentralized architecture of MGs impacts the functioning patterns of the entire system, including control strategy, energy management philosophy, and protection scheme. In this context, developing a convenient protection strategy for MGs is challenging because of various obstacles, such as the significant variance in short-circuit values under different operating modes, two-way power flow, asynchronous reclosing, protection blinding, sympathetic tripping, and loss of coordination. In light of these challenges, this paper reviews prior research on proposed protection schemes for AC-MGs to thoroughly evaluate network protection's potential issues. The paper also provides a comprehensive overview of the MG structure and the associated protection challenges, solutions, real applications, and future trends.

摘要:A fault identification scheme for protection and adaptive reclosing is proposed for a hybrid multi-terminal HVDC system to increase the reliability of fault isolation and reclosing. By analyzing the "zero passing" characteristic of current at the local end during the converter capacitor discharge stage, the fault identification scheme is proposed. The distributed parameter-based fault location equation, which incorporates fault distance and fault impedance, is developed with the injection signal and the distributed parameter model during the adaptive reclosing stage. The fault distance is determined using a trust region reflection algorithm to identify the permanent fault, and a fault identification scheme for adaptive reclosing is developed. Simulation results show that the proposed scheme is suitable for long-distance transmission lines with strong anti-fault impedance and anti-interference performance. Also, it is less affected by communication delay and DC boundary strength than existing methods.

摘要:This paper proposes a novel deep reinforcement learning (DRL) control strategy for an integrated ofshore wind and photovoltaic (PV) power system for improving power generation efciency while simultaneously damping oscillations. A variable-speed ofshore wind turbine (OWT) with electrical torque control is used in the integrated ofshore power system whose dynamic models are detailed. By considering the control system as a partially-observable Markov decision process, an actor-critic architecture model-free DRL algorithm, namely, deep deterministic policy gradient, is adopted and implemented to explore and learn the optimal multi-objective control policy. The potential and efectiveness of the integrated power system are evaluated. The results imply that an OWT can respond quickly to sudden changes of the infow wind conditions to maximize total power generation. Signifcant oscillations in the overall power output can also be well suppressed by regulating the generator torque, which further indicates that complementary operation of ofshore wind and PV power can be achieved.

摘要:New energy storage devices such as batteries and supercapacitors are widely used in various felds because of their irreplaceable excellent characteristics. Because there are relatively few monitoring parameters and limited understanding of their operation, they present problems in accurately predicting their state and controlling operation, such as state of charge, state of health, and early failure indicators. Poor monitoring can seriously afect the performance of energy storage devices. Therefore, to maximize the efciency of new energy storage devices without damaging the equipment, it is important to make full use of sensing systems to accurately monitor important parameters such as voltage, current, temperature, and strain. These are highly related to their states. Hence, this paper reviews the sensing methods and divides them into two categories: embedded and non-embedded sensors. A variety of measurement methods used to measure the above parameters of various new energy storage devices such as batteries and supercapacitors are systematically summarized. The methods with diferent innovative points are listed, their advantages and disadvantages are summarized, and the application of optical fber sensors is emphasized. Finally, the challenges and prospects for these studies are described. The intent is to encourage researchers in relevant felds to study the early warning of safety accidents from the root causes.

摘要:Hybrid high-voltage direct current (HVDC) transmission has the characteristic of long transmission distance, complex corridor environment, and rapid fault evolution of direct current (DC) lines. As high fault current can easily cause irreversible damage to power devices, rapid and reliable line protection and isolation are necessary to improve the security and reliability of hybrid HVDC transmission system. To address such requirement, this paper proposes a single-ended protection method based on transient voltage frequency band characteristics. First, the frequency characteristics of the smoothing reactor, DC flter, and DC line are analyzed, and the characteristic frequency band is defned. A fault criterion is then constructed based on the voltage characteristic frequency band energy, and faulty pole selection is performed according to the fault voltage characteristic frequency band energy ratio. The proposed protection method is verifed by simulation, and the results show that it can rapidly and reliably identify internal and external faults, accurately select faulty poles without data communication synchronization, and has good fault-resistance and anti-interference performance.

摘要:It is important to achieve an efcient home energy management system (HEMS) because of its role in promoting energy saving and emission reduction for end-users. Two critical issues in an efcient HEMS are identifcation of user behavior and energy management strategy. However, current HEMS methods usually assume perfect knowledge of user behavior or ignore the strong correlations of usage habits with diferent applications. This can lead to an insufcient description of behavior and suboptimal management strategy. To address these gaps, this paper proposes nonintrusive load monitoring (NILM) assisted graph reinforcement learning (GRL) for intelligent HEMS decision making. First, a behavior correlation graph incorporating NILM is introduced to represent the energy consumption behavior of users and a multi-label classifcation model is used to monitor the loads. Thus, efcient identifcation of user behavior and description of state transition can be achieved. Second, based on the online updating of the behavior correlation graph, a GRL model is proposed to extract information contained in the graph. Thus, reliable strategy under uncertainty of environment and behavior is available. Finally, the experimental results on several datasets verify the efectiveness of the proposed mode.

摘要:he construction of integrated energy systems can help improve energy efciency and promote global energy transition. However, in recent years, the occurrence of extreme natural disasters has brought certain threats to the safe and stable operation of the integrated energy system. Thus, it is necessary to improve the ability of the integrated energy system to resist disasters, reduce disaster losses, and restore energy supply as soon as possible, i.e., improve its resilience. Considering the infuence of pre-disaster prevention measures and disaster-time operational measures on system disaster resilience and the correlation between the two, this paper proposes a system hardening strategy based on three-layer robust optimization. The upper layer formulates the optimal hardening strategy of the system before the disaster event occurs, the middle layer identifes the failed elements in the worst disaster situation, while the lower layer realizes the system operational optimization by coordinating the energy storage charging and discharging plan of each subsystem. The strategy can reduce the total supply shortage of the integrated energy system and improve the fexibility of the system in the pre-disaster prevention and disaster resistance integration stages.

摘要:Using an islanded microgrid (MG) with large-scale integration of renewable energy is the most popular way of solving the reliable power supply problem for remote areas and critical electrical users. However, compared with traditional power systems, the limited spinning reserves and network communication bandwidth may cause weak frequency stability in the presence of stochastic renewable active outputs and load demand fuctuations. In this paper, an adaptive event-triggered control (ETC) strategy for a load frequency control (LFC) system in an islanded MG is proposed. First, a bounded adaptive event-triggered communication scheme is designed. This not only saves on network resources, but also ensures that the control center has a sensitive monitoring ability for the MG operating status when the frequency deviations have been efectively damped. Secondly, by fully considering the spinning reserve constraints and uncertain communication delays, the LFC system is described as a nonlinear model with saturation terms. Design criteria for ETC parameters are strictly deduced based on Lyapunov stability theory. Finally, an ETC parameter optimization algorithm based on random direction search is developed to reconcile the bandwidth occupancy and control performance. The efectiveness of the proposed method is verifed in an MG test system.

摘要:Because there is insufcient measurement data when implementing state estimation in distribution networks, this paper proposes an attention-enhanced recurrent neural network (A-RNN)-based pseudo-measurement modeling metho. First, based on analyzing the power series at the source and load end in the time and frequency domains, a period-dependent extrapolation model is established to characterize the power series in those domains. The complex mapping functions in the model are automatically represented by A-RNNs to obtain an A-RNNs-based period-dependent pseudo-measurement generation model. The distributed dynamic state estimation model of the distribution network is established, and the pseudo-measurement data generated by the model in real time is used as the input of the state estimation model together with the measurement data. The experimental results show that the method proposed can explore in depth the complex sequence characteristics of the measurement data such that the accuracy of the pseudo-measurement data is further improved. The results also show that the state estimation accuracy of a distribution network is very poor when there is a lack of measurement data, but is greatly improved by adding the pseudo-measurement data generated by the model proposed.

摘要:This paper presents the issue of the Sub-synchronous resonance (SSR) phenomenon in a series compensated DFIGbased wind power plant and its alleviation using a Battery Energy Storage-based Damping Controller (BESSDCL). A supplementary damping signal is developed considering the angular speed deviation and is incorporated into the BESS control system. Wide-area Measurement System data is used to determine the angular speed deviation. A linearized system model is developed to perform eigenvalue analysis, and to detect and examine unstable SSR modes. The variation of wind speed and three-phase fault are also taken into consideration to validate the robustness of the controller. To further verify the efcacy of the proposed damping controller, time-domain simulations are performed using MATLAB/Simulink. The application of the proposed BESSDCL stabilizes all the unstable system modes efectively at wind speeds of 7 m/s, 9 m/s, and 11 m/s, and at 40%, 50%, and 60% series compensation levels, as well three-phase fault conditions.

摘要:A coordinated scheduling model based on two-stage distributionally robust optimization (TSDRO) is proposed for integrated energy systems (IESs) with electricity-hydrogen hybrid energy storage. The scheduling problem of the IES is divided into two stages in the TSDRO-based coordinated scheduling model. The frst stage addresses the day-ahead optimal scheduling problem of the IES under deterministic forecasting information, while the second stage uses a distributionally robust optimization method to determine the intraday rescheduling problem under high-order uncertainties, building upon the results of the frst stage. The scheduling model also considers collaboration among the electricity, thermal, and gas networks, focusing on economic operation and carbon emissions. The fexibility of these networks and the energy gradient utilization of hydrogen units during operation are also incorporated into the model. To improve computational efciency, the nonlinear formulations in the TSDRO-based coordinated scheduling model are properly linearized to obtain a Mixed-Integer Linear Programming model. The Column-Constraint Generation (C&CG) algorithm is then employed to decompose the scheduling model into a master problem and subproblems. Through the iterative solution of the master problem and subproblems, an efcient analysis of the coordinated scheduling model is achieved. Finally, the efectiveness of the proposed TSDRO-based coordinated scheduling model is verifed through case studies. The simulation results demonstrate that the proposed TSDRO-based coordinated scheduling model can efectively accomplish the optimal scheduling task while considering the uncertainty and fexibility of the system. Compared with traditional methods, the proposed TSDRO-based coordinated scheduling model can better balance conservativeness and robustness.

摘要:Severe disturbances in a power network can cause the system frequency to exceed the safe operating range. As the last defensive line for system emergency control, under frequency load shedding (UFLS) is an important method for preventing a wide range of frequency excursions. This paper proposes a hierarchical UFLS scheme of “centralized real-time decision-making and decentralized real-time control” for inter-connected systems. The centralized decisionlayer of the scheme takes into account the importance of the load based on the equivalent transformation of kinetic energy (KE) and potential energy (PE) in the transient energy function (TEF), while the load PE is used to determine the load shedding amount (LSA) allocation in diferent loads after faults in real-time. At the same time, the infuence of inertia loss is considered in the calculation of unbalanced power, and the decentralized control center is used to implement the one-stage UFLS process to compensate for the unbalanced power. Simulations are carried out on the modifed New England 10-generator 39-bus system and 197-bus system in China to verify the performance of the proposed scheme. The results show that, compared with other LSA allocation indicators, the proposed allocation indicators can achieve better fnadir and td. At the same time, compared with other multi-stage UFLS schemes, the proposed scheme can obtain the maximum fnadir with a smaller LSA in scenarios with high renewable energy sources (RES) penetration.

摘要:The stability of a voltage source converters (VSC) system based on phase-locked loop (PLL) is very important issue during asymmetric grid faults. This paper establishes a transient synchronous stability model of a dual-sequence PLL-based VSC system during low voltage ride-through by referring to the equivalent rotor swing equation of synchronous generators. Based on the model, the synchronization characteristics of the VSC system under asymmetric grid faults are described, and the interaction mechanisms, as well as the transient instability phenomena of positive and negative sequence PLL during asymmetric faults are explained. Using the equal area criterion, the infuences of sequence control switching action, detection delay, and interaction between the positive and negative sequence PLL on the transient synchronous stability of the VSC system are analyzed, respectively. In addition, a transient stability assessment criterion based on the critical fault clearance angle and time and an enhancement control strategy based on the improved positive and negative sequence PLL are proposed. Finally, the analytical results are validated through simulation and experiments.

摘要:Given the “carbon neutralization and carbon peak” policy, enhancing the low voltage ride-through (LVRT) capability of wind farms has become a current demand to ensure the safe and stable operation of power systems in the context of a possible severe threat of large-scale disconnection caused by wind farms. Currently, research on the LVRT of wind farms mainly focuses on suppressing rotor current and providing reactive current support, while the impact of active current output on LVRT performance has not been thoroughly discussed. This paper studies and reveals the relationship between the limit of reactive current output and the depth of voltage drop during LVRT for doubly-fed induction generator (DFIG) based wind farms. Specifcally, the reactive current output limit of the grid-side converter is independent of the depth of voltage drop, and its limit is the maximum current allowed by the converter, while the reactive current output limit of the DFIG stator is a linear function of the depth of voltage drop. An optimized scheme for allocating reactive current among the STATCOM, DFIG stator, and grid-side converter is proposed. The scheme maximizes the output of active current while satisfying the standard requirements for reactive current output. Compared to traditional schemes, the proposed LVRT optimization strategy can output more active power during the LVRT period, efectively suppressing the rate of rotor speed increase, and improving the LVRT performance and fault recovery capability of wind farms. Simulation results verify the efectiveness of the proposed scheme.