In this work, a novel multi-port bidirectional converter is proposed for energy storage in electric vehicles (EV). The proposed converter has the ability to work in both bidirectional step-up (boost) and step-down (buck) modes. There are three ports in the proposed structure that the energy can flow between them. The main features of the proposed converter are the low components count, the low peak voltage of the main switches and low losses. Moreover, only two power switches are utilized in the proposed converter, which makes it easy to transfer the power between the sources. The suggested converter can be worked in energy storage system (ESS) due to the ability of step-up and step-down operation principles. Thus, it can charge and discharge the ESS with high voltage conversion ratio. Besides, the low number of components is utilized in the suggested converter to provide a bi-directional feature that leads to a reduction in the overall cost of the system. In order to investigate the effectiveness of the proposed converter, a technical survey, mathematical calculation, and a comparison study with other existing structures have been introduced in this paper. Finally, to validate the performance of the proposed converter, a laboratory prototype is implemented with a 150 W output power rate at 50 kHz switching frequency 20 V and 12 V input voltages, efficiency about 94.11% in step-up mode and 94.46% in step-down mode.

The distributed power flow controller (DPFC) has a positive effect of UC problem on the network side based on its ability to manage capacity of power flow. This study presents a novel two-stage robust model to optimize the status of the generator and location–allocation of the DPFC, while simultaneously considering wind and load uncertainties. The column-and-constraint generation (CCG) method is utilized to solve the two-stage problem into the master problem and the subproblem iteratively. The optimal status of the generator and location of the DPFC can be easily obtained with the master problem, and the dispatch solution and compensation level of the DPFC are solved in the subproblem. We conduct the IEEE 24 bus system to verify the performance of the proposed procedure. There are effects on wind spillage/load shedding and generator dispatch scheduling planning once the DPFC is injected. Detailed simulation results illustrate the effect of the proposed approach.

Distributed power flow controller (DPFC) has a considerable potential to regulate the power flow and generator rescheduling continuously. This study presents a novel two-stage stochastic model for optimal location allocations of the DPFC coupled with the interactions of DPFC to search for the optimal solutions. The Benders decomposition is utilized to reformulate the two-stage problem into the master problem and the subproblem. The optimal solution can be easily obtained with the master problem and subproblem iteratively. The relaxed DC power flow with a DPFC in the master problem accelerates the efficiency of optimal locations under a base condition. Slack variables are incorporated in the subproblem to check the feasibility of relaxed AC power flow. The optimal compensation levels of DPFC at different load/wind scenarios are optimized in the subproblem. The IEEE 118 bus system is conducted to verify the performance of the proposed procedure. The DPFC has positive impacts on unit costs, voltage performance, wind absorption, and power losses. Detailed simulation results illustrate the effect of the proposed approach.

随着电力系统中不确定量日益复杂,同时存在的随机与区间变量使得采用概率或区间潮流计算难以准确获取系统的运行状态.为此,提出一种基于双层代理模型的概率-区间潮流计算方法.该方法仅需较少次数的确定性潮流计算便可实现上、下层代理模型的构建,进而通过代理模型求解概率-区间潮流常规求解方法中所需要的大量确定性潮流计算,可实现输出变量的快速获取.此外,该文还提出了用于描述输出变量特征的灵敏度指标,并结合所提出的双层代理模型开展灵敏度分析,以量化输入区间变量对输出变量的影响程度.在IEEE 118节点系统中进行算例分析,通过与已有方法对比验证了所提方法的精确性和快速性,借助灵敏度分析可识别对输出变量具有显著影响的关键区间变量,有助于揭示系统运行状态与区间变量之间的关系.

负荷重分配(LR)攻击是一种特殊的网络攻击形式,对LR攻击进行建模并研究其对电力系统运行的影响具有重要的现实意义.首先,对LR攻击过程进行了分析,并基于半马尔可夫链建立了LR攻击的随机过程模型;其次,对LR攻击作用下攻击者与调度员之间的交互作用过程进行分析,建立了考虑LR攻击的发输电系统负荷削减模型;然后,从保护关键量测数据的角度出发,提出了一种基于输电线路利用率的脆弱线路防御策略,并进一步提出了考虑LR攻击和脆弱线路防御的发输电系统可靠性评估算法;最后,以IEEE 14节点修改系统为例进行算例分析,验证了所提出的考虑LR攻击的发输电系统可靠性评估算法的正确性以及脆弱线路防御策略的有效性.

多馈入直流系统中交流侧短路故障发生后,导致交流系统电压持续降低进而引起多条甚至全部直流同时发生换相失败,使电网安全稳定性受到严重破坏.同步调相机具备过载能力,且其无功输出受系统电压影响小,在面对交流故障带来的电压跌落可以提供较强的无功支撑,从而抑制直流换相失败的发生.为了抑制直流换相失败,提出了一种抑制多馈入直流换相失败的同步调相机优化配置方法,对其安装地点及容量这两个方面同时进行了优化配置.首先从直流换相失败持续时间出发,且考虑各直流间相互作用,提出了一种抑制换相失败效果指标;然后根据电气距离确定了安装待选区域,由无功补偿响应指标筛选出同步调相机最佳补偿地点;随后建立了同步调相机配置优化模型,对最佳配置方案进行二阶段的求解,获得最终配置方案;最后在实际大电网仿真结果表明,所得最终解能够考虑经济性的同时有效抑制交流故障引起的多馈入直流换相失败.

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.

New materials and related new equipment are increasingly important to maintain the safety and stability of the asynchronous interconnection systems. DC lines equipped with Frequency Limit Controller (FLC) are able to quickly balance power fluctuation and limit frequency deviation. However, the frequency stability problem, especially in the sending end system characteristics of "large generation and small network", still draws our attention for its significance to the gird. Based on the analysis of the primary frequency regulation principle of the power system and the impact of reserve configuration on frequency deviation in asynchronous interconnection, an optimization approach for primary frequency regulation reserve capacity, featured by the sequence quadratic programming, with the minimum quasi-steady-state frequency deviation, was proposed in this paper. The optimization idea of this approach is to arrange the reserve configuration in proportion to the unit's adjustment coefficient and the dead zone, in order to prevent non-performance of some units while other units are sufficient. A numerical simulation indicated that, compared with the original scheme, the system frequency deviation was effectively reduced.

针对在不同位置安装差异化容量的分布式潮流控制器(distributed power flow controller,DPFC)会带来不同的调控效能这一问题,提出选址定容两阶段DPFC优化方法.阐述了DPFC结构演变及其装置原理,对比统一潮流控制器分析DPFC的特点及优势.基于串联侧的分布式结构,研究DPFC运行状态及空间转移模型.考虑到在电网不同位置安装差异化容量的DPFC将产生不同效能,制订选址定容两阶段DPFC优化方法,以最优成本获得电网性能提升的最佳效果和最大经济效益.基于DPFC对断面潮流均衡的影响度、对母线电压稳定贡献度来选取最优安装点,应用经济性成本/效益分析来迭代优化其容量.选取某省220 kV地区电网开展仿真分析,在该电网中进行DPFC优化配置以验证策略的可行性与正确性.仿真试验表明:优选地点能够有效改善断面潮流均衡性,优选装置容量可大幅提升断面输电能力期望,且该方式下DPFC效能比最大,电网总效益能够取得极大值.

Various probabilistic power flow (PPF) and interval power flow (IPF) methods have been developed to deal with random and interval variables in power systems, respectively. However, the co-existence of these two types of variables poses great challenges to PPF and IPF calculations. To cope with this issue, we propose a clustering-based analytical method for hybrid probabilistic and interval power flow (HPIPF) calculation. The uncertainties of load demands and wind power outputs are treated as random and interval variables, respectively. The remarkable feature of this method is to propose an assumption called the unified optimal scenarios of wind power. On this basis, HPIPF calculation is transformed into IPF and PPF calculations, which can be solved by the optimal-scenarios method and the cumulant method, respectively. The accuracy and efficiency of the proposed method are validated on the IEEE 14-bus and 118-bus test systems through the comparisons with the double-layer Monte-Carlo simulation. Furthermore, the impacts of correlated interval variables are analyzed. The simulations indicate that the estimations of output variables may be conservative without considering the correlations of interval variables.

With the increased penetration of renewable energy, maintaining the system frequency stability is becoming more and more challenging due to the reduced inertia. This paper proposes an improved short-term over-production control strategy based on the virtual inertia provided by wind turbines. In particular, the limitations of the current short-time over-production control of DFIG wind turbines are investigated, including the excessive release of rotor kinetic energy and the secondary frequency drop. Then, an improved three-stage control strategy is proposed, including the frequency adjustment mode, the speed recovery mode and the maximum power tracking control mode. Test results on the 3-machine 9-bus system verify the effectiveness of the proposed control strategy in improving system transient frequency response performance.

In recent years, power system uncertainties have increased due to the growing integrations of intermittent renewable energy resources. It is imperative to introduce probabilistic load flow analysis in the study of power system operation and planning to adapt to the ever-increasing uncertainties. This paper proposes a scenario-based analytical method for the probabilistic load flow analysis, which takes advantage of both the scenario analysis method and the cumulant method. This method can not only consider various kinds of correlations among power inputs but also accurately represent the probability distributions of desired outputs with a reasonable computational burden. The performance of this method is evaluated on the IEEE 14-bus and 118-bus test systems. The accuracy and efficiency of the proposed method are validated through quantitative and graphical comparisons with Monte-Carlo simulation.

解列作为极端故障下确保重要负荷不间断供电的有效控制措施,对维护系统安全稳定有着重要意义.如何精准快速地找到失步断面并可靠断开,是当前解列问题的研究重点.针对当前解列过程中分群模式不显著,导致解列策略不收敛的难题,提出一种基于节点相关度的网架结构优化方法,通过调整线路支数降低解列难度.该方法基于慢同调理论构造节点相关度模型,综合考虑系统稳定约束条件,采用离散粒子群算法获取同调群强耦合、非同调弱连接的优化方案,使解列范围集中在弱连接区域.最后利用IEEE-118标准算例和新英格兰等值系统进行仿真验证,表明该方法确实能将高概率解列线路集中化,达到缩小解列决策范围的效果.

This paper presents an analytical method for calculating the limit proportion of wind power considering the primary frequency modulation and frequency constraints of wind power. By analyzing the response characteristics of primary frequency modulation of double-fed induction generator (DFIG), it is pointed out that the increment of primary frequency modulation power provided by DFIG is less than the expected. In order to accurately calculate the power increment of primary frequency modulation of DFIG, the transfer function model of primary frequency modulation of DFIG is established; the frequency response model of power system considering primary frequency modulation of DFIG is constructed, and the limit value of wind power proportion under frequency constraints is solved by analytical method. The accuracy of the proposed analytical calculation method of wind power limit proportion is verified by MATLAB/Simulink time-domain simulation platform.

建设坚强可靠的智能电网是输电网规划的核心环节,解列是应对电网失步振荡的重要控制手段.系统失稳时的失步断面主要分布在被称为弱连接的线路上,减少系统弱连接线路可以优化系统分区,减小解列断面的搜索解集和搜索时间,为解列装置动作提供参考,增强解列控制的有效性.基于慢同调理论提出了改进的识别与筛选弱连接线路的方法,并将弱连接线路条数与总线路数的比值定义为弱连接系数,建立了以弱连接系数最小为优化目标的考虑解列控制的输电网双层规划模型.利用基于Boruvka算法的拓扑连通修复策略与自适应变异和惯性权重的粒子群算法相结合的混合算法,在IEEE Graver 18节点系统和华东某实际电网对上述双层模型进行求解,PSD-BPA中故障仿真结果验证了所提出的改进的弱连接筛选方法和输电网规划模型的有效性.

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.

In recent years, hybrid wind-photovoltaic (PV) systems are flourishing due to their advantages in the utilization of renewable energy. However, the accurate assessment of the maximum integration of hybrid renewable generation is problematic because of the complex uncertainties of source and demand. To address this issue, we develop a stochastic framework for the quantification of hybrid energy hosting capacity. In the proposed framework, historical data sets are adopted to represent the stochastic nature of production and demand. Moreover, extreme combinations of production and demand are introduced to avoid multiple load flow calculations. The proposed framework is conducted in the IEEE 33-bus system to evaluate both single and hybrid energy hosting capacity. The results demonstrate that the stochastic framework can provide accurate evaluations of hosting capacity while significantly reducing the computational burden. This study provides a comprehensive understanding of hybrid wind-PV hosting capacity and verifies the excellent performance of the hybrid energy system in facilitating integration and energy utilization.