Wind farm active power dispatching algorithm based on Grey Incidence

This study proposes a wind farm active power dispatching(WFAPD) algorithm based on the grey incidence method, which does not rely on an accurate mathematical model of wind turbines. Based on the wind turbine start-stop data at different wind speeds, the weighting coefficients, which are the participation degrees of a variable speed system and a variable pitch system in power regulation, are obtained using the grey incidence method. The incidence coefficient curve is fitted by the B-spline function at a full range of wind speeds, and the power regulation capacity of all wind turbines is obtained. Finally, the WFAPD algorithm, which is based on the regulating capacity of each wind turbine, is compared with the wind speed weighting power dispatching(WSWPD) algorithm in MATLAB. The simulation results show that the active power fluctuation of the wind farm is smaller, the rotating speed of wind turbines is smoother, and the fatigue load of highspeed turbines is effectively reduced.

Simulation research of discrete sliding mode control for active power filter

Because of the widely-used nonlinear loads, the problems of harmonics and low power factor in power systems are becoming more and more serious. In view of the above problems, a shunt three-phase active power filter （SAPF） based on discrete sliding mode control to suppress the harmonics was designed and the power factor improved. First, built the mathematical model of SAPF. Then, controlled the switch through analyzing the harmonic current that was controlled signal using discrete sliding mode control. Through simulation using MATLAB, verified the validity of the algorithm. By the simulation waveforms, it can be found that after the load current containing a large number of harmonics passes the active power filter, the waveform of the power current approximately becomes a sine wave and the harmonics is significantly reduced. As a result, it plays a good role in purifying power systems. Moreover, from the waveforms of harmonic current and power current, it can be found that the algorithm has a faster tracking speed. The waveform can fect.

Hierarchical Cluster Coordination Control Strategy for Large-scale Wind Power Based on Model Predictive Control and Improved Multi-time-scale Active Power Dispatching

The grid-connection of large-scale and high-penetration wind power poses challenges to the friendly dispatching control of the power system.To coordinate the complicated optimal dispatching and rapid real-time control,this paper proposes a hierarchical cluster coordination control(HCCC)strategy based on model predictive control(MPC)technique.Considering the time-varying characteristics of wind power generation,the proposed HCCC strategy constructs an improved multitime-scale active power dispatching model,which consists of five parts:formulation of cluster dispatching plan,rolling modification of intra-cluster plan,optimization allocation of wind farm(WF),grouping coordinated control of wind turbine group(WTG),and real-time adjustment of single-machine power.The time resolutions are sequentially given as 1 hour,30 min,15 min,5 min,and 1 min.In addition,a combined predictive model based on complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN),wavelet thresholding(WT),and least squares support vector machine(LSSVM)is established.The fast predictive feature of this model cooperates with the HCCC strategy that effectively improves the predictive control precision.Simulation results show that the proposed HCCC strategy enables rapid response to active power control(APC),and significantly improves dispatching control accuracy and wind power accommodation capabilities.

计及工况预测误差的主动配电网日前无功优化调度策略

为解决工况预测误差较大时,日前无功优化调度方案优化效果不佳的问题,提出了计及工况预测误差的主动配电网日前无功优化调度策略。首先,使用轻量级梯度提升机算法建立日前工况功率预测模型;其次,考虑大规模高比例分布式电源接入主动配电网,以调度时段内所有时间断面的多目标加权累加和为目标函数建立日前无功优化调度模型;最后,设计了一种变寻优粒子空间的改进引力搜索算法对日前无功优化调度模型进行求解,该算法根据历史工况预测误差评价指标调整寻优粒子空间各维度的上下限矩阵,从而抑制了当无功区域内工况预测误差较大时可控设备调度异常的缺陷。最后采用拓展的IEEE 33节点系统算例进行有效性验证。

新型电力系统频率安全稳定研究综述及展望

随着新型电力系统的发展,新能源的出力不确定性、弱支撑性、弱调节能力给电力系统的频率安全带来了巨大的挑战。首先,总结新型电力系统有功频率调节面临的新挑战,阐述了新型电力系统稳定运行存在的问题,并归纳了新型电力系统的频率响应模型。然后,介绍了应对频率安全问题的安全稳定控制措施,分析频率安全优化调度方面的研究现状和不足之处。最后,围绕新型电力系统在线安全调度、新型电力系统低频减载运行、多区域互联电网频率安全调度等重点研究方向进行了探讨和展望。

考虑平行系统特征的双活调度系统的设计与应用

为提高电网运行的稳定性,需要构建稳定可靠的电网调度系统,现提出一种考虑平行系统特征的双活调度系统。通过构建主备两个数据中心,根据应用业务量在主备调间进行调整,实现对资源的充分利用。发生故障时,另一个正常运行的中心将承担所有业务。并将平行系统视为电网虚拟运行系统,将真实与虚拟系统结合后得到电网双活调度系统,并具有管理和控制模块、实验和评估模块、学习和培训模块等功能。该系统通过对数据进行初始化处理,计算出电力分配结果,建立双层任务调度模型,利用遗传算法求解模型,从而实现双活调度系统的优化调度。对系统进行试验测试,试验结果表明:设计系统所提方法达到最优分配值所需时间短、效率高、电网信息调度总量大,调度能力强,调度信息的安全性高。说明所设计的双活调度系统具有可行性,利于区域电网的优化调度。

低碳背景下智能电网减排双目标调度规划方法

在构建电网调度数学模型时,应充分考虑模型的最优解、电网发电成本、可再生能源利用率。提出一种低碳背景下智能电网减排双目标调度规划方法。将最小化机组发电成本、最大化减排收益分别作为节能目标和减排目标,构建电网调度双目标函数;将有功平衡约束、机组出力约束、机组爬坡约束、旋转备用约束和机组启停时间约束作为电网调度的约束条件,建立电网调度模型;采用粒子群优化算法,将火电机组编号和功率视为粒子位置,通过不断更新粒子位置直至适应值达到最大,即为输出模型全局最优解,得到火电机组出力最优调度方案。实验结果表明,在实验周期的各个时段中,所需发电成本始终低于2500元,CO_(2)排放量始终低于630 kg/h,可再生能源利用率的最高值达到87.5%。该方法可有效降低发电成本和排污量,提高可再生能源利用率,实现节能减排双重优化。

基于含多微网接入的主动配电系统自主优化经济调度

针对含多微网接入的主动配电系统经济调度方法在中断负荷的影响下,调度结果与微网出力情况不一致导致的经济性差的问题,提出基于含多微网接入的主动配电系统自主优化经济调度方法。以多微网的电源特性为依据,计算主动配电系统的运行成本和环境成本,以运行成本和环境成本经济效益最大化为目标,建立自主优化经济调度目标函数,并从环境成本和运行成本两方面设计目标函数的约束条件,进行支路潮流约束,限制微网的输出功率等,使配电系统输出功率变化与电池出力情况变化趋势保持一致,在约束条件下求解目标函数,获得目标函数解集,求解集合中各个解与理想权重的接近程度,筛选出最优解,实现主动配电系统的自主优化经济调度。实验结果表明:设计的调度方法在中断负荷的情况下,运行成本低,优化水平高,微网输出功率稳定,并且与电池出力情况一致,该方法的经济性得到了提高。

Distributionally Robust Optimal Reactive Power Dispatch with Wasserstein Distance in Active Distribution Network

The uncertainties from renewable energy sources(RESs)will not only introduce significant influences to active power dispatch,but also bring great challenges to the analysis of optimal reactive power dispatch(ORPD).To address the influence of high penetration of RES integrated into active distribution networks,a distributionally robust chance constraint(DRCC)-based ORPD model considering discrete reactive power compensators is proposed in this paper.The proposed ORPD model combines a second-order cone programming(SOCP)-based model at the nominal operation mode and a linear power flow(LPF)model to reflect the system response under certainties.Then,a distributionally robust optimization(WDRO)method with Wasserstein distance is utilized to solve the proposed DRCC-based ORPD model.The WDRO method is data-driven due to the reason that the ambiguity set is constructed by the available historical data without any assumption on the specific probability distribution of the uncertainties.And the more data is available,the smaller the ambiguity would be.Numerical results on IEEE 30-bus and 123-bus systems and comparisons with the other three-benchmark approaches demonstrate the accuracy and effectiveness of the proposed model and method.

Optimal Active Power Dispatching of Microgrid and Distribution Network Based on Model Predictive Control

First, a three-tier coordinated scheduling system consisting of a distribution network dispatch layer, a microgrid centralized control layer, and local control layer in the energy internet is proposed. The multi-time scale optimal scheduling of the microgrid based on Model Predictive Control（MPC） is then studied, and the optimized genetic algorithm and the microgrid multi-time rolling optimization strategy are used to optimize the datahead scheduling phase and the intra-day optimization phase. Next, based on the three-tier coordinated scheduling architecture, the operation loss model of the distribution network is solved using the improved branch current forward-generation method and the genetic algorithm. The optimal scheduling of the distribution network layer is then completed. Finally, the simulation examples are used to compare and verify the validity of the method.

Coupling real-time simulation of power supply,trains and dispatching for urban rail transit

In order to study the interaction among the traction power supply,the train group and the operation dispatching of urban rail transit,a coupling simulation system of power supply system,trains and dispatching management is constructed.In order to solve the problems of different timescales and difficult cooperation operation for related subsystems,a multi-bus distributed real-time network architecture based on hierarchical management of communication data is established,and simulation management software is developed to facilitate the free expansion of the simulation system.Meanwhile,the track line,train operation and other large timescale subsystems are realized by the pure digital simulation.And the time-sensitive subsystems,such as train traction system,braking system,auxiliary power supply system and network system etc.,are built by the semi-physical simulation.In this article,the system structure and the main implementation principle of each simulation subsystem are given in detail,and the system is tested and verified at the end.The results show that the simulation system can meet the expected requirements.

含高渗透可再生能源的动态网络重构与无功电压调整协同优化

具有出力不确定性的可再生能源高渗透并入,导致传统单一的主动管理策略难以实现配网最优运行。在此背景下,提出一种动态网络重构与无功电压调整协同优化方法。首先,采用基于形态和幅值的双尺度相似性度量谱聚类算法对负荷进行聚类,进一步利用反映负荷曲线波动特征的自适应聚合算法对时段做出合理划分。其次,计及风光不确定性,构建考虑配电网动态重构与储能和微型燃气轮机出力调控协同的机会约束双层优化模型,模型上层以配电网综合运行成本最小为目标,下层以系统电压总偏差最小为目标,实现对配电网运行经济性和系统电压质量的综合优化。然后,针对该模型提出了基于十进制编码的改进鲸鱼优化算法和内点法相结合的混合策略对模型进行求解。最后,在改进的IEEE33节点系统中,对所提的运行优化模型进行分析和验证。仿真结果表明:所提双层优化模型能够有效提高电压质量和降低配电网运行费用,所提时段划分方法能够得到符合曲线变化趋势的分段方案,改进后的算法大大提高了求解效率。

A Method for Distributed Generator Dispatch Strategy in Distribution Network

Since a load of power system changes continuously,the generation also adjusted for supply-demand balance purpose.If there exist more distributed generators in the distribution network,the dispatch strategy becomes more crucial.The possibility of having numerous controllable microgrids,diesel generator(DG)units and loads for microgrids(MGs)system requires an efficient dispatch strategy in order to balance supply demand for reducing the total cost of the integrated system.In this paper,a method for the dispatch of the distributed generator in distributed power systems has been proposed.The dispatch strategy is such that it keeps a flat voltage profile,reduces the network losses,increases the maximum loading and voltage security margin of the system.The procedure is based on the analysis of continuous power flow.The method is executed on a 34-bus test system.The MATLAB based PSAT packages are used for simulation purpose.

基于DFIG有功下限的风火系统经济调度模型

为解决大规模风电接入电网场景下并网火电机组台数和系统有功备用容量减少的问题,该文提出一种计及双馈感应发电机(DFIG)向下调度能力的风火系统经济调度模型。首先,综合深度调峰火电机组运行成本、开机成本、寿命损耗和风电弃风成本等,建立风火系统经济调度模型。其次,考虑到高风速下转子侧变流器(RSC)容量制约DFIG有功下限,该文计及RSC容量约束,提出DFIG有功下限求解算法,进而提出计及DFIG有功下限约束的风火系统经济调度模型。最后,IEEE 30节点算例结果表明所提经济调度模型可降低火电运行成本和风电弃风量。

基于分布式深度强化学习的微网群有功无功协调优化调度

针对微网群的分布式有功无功协调优化调度问题,提出一种分布式多智能体深度强化学习方法,可训练智能体在与环境交互的过程中学习到最优调度策略,并克服传统优化方法对模型的依赖。相较于已有基于“集中训练”框架的多智能体深度强化学习方法,该方法无须收集全局信息,能够更好地保障各子微网信息的隐私,减轻通信压力,并且在训练和执行阶段均表现出对通信故障的鲁棒性。此外,考虑到微网群存在拓扑变化而强化学习模型泛化能力差,提出一种迁移强化学习方法,利用已有智能体知识为每种拓扑高效训练一组智能体。最后,通过改进的IEEE 33节点系统算例,验证了所提方法在解决微网群分布式有功无功协调优化调度问题上的有效性。

计及源/网不确定性的区域电网有功不平衡度评估

区域电网互联可提高供电可靠性和新能源消纳能力,现有调度研究多关注全网功率平衡和联络线功率优化,忽略区域有功平衡能力。评估区域有功不平衡度,需要考虑长期运行中的不确定性因素,不能基于单个时间断面。计及风/光出力不确定性和电网随机故障,提出区域有功不平衡度指标和评估算法。首先改进K-means算法聚类风光出力场景。其次定义描述区域不平衡度的两个指标:电力不平衡度和供电能力不平衡度。考虑源/网不确定性,采用状态枚举和概率加权方法计算上述指标。将不平衡度指标分别纳入目标函数和约束条件,提出计及不平衡度的发电再调度模型。最后建立目标函数对不平衡度约束的灵敏度模型,估计放宽不平衡度约束对优化目标的影响。结果表明:所提算法以切负荷量增加为代价,可减小区域电网有功不平衡度。在不同出力/故障场景下,各区域综合不平衡度变化趋势基本一致。放松电力不平衡度约束,可减小综合优化目标。

基于集群的主动配电网双层分布式优化调度策略研究

随着主动配电网中大量分布式能源资源的接入,传统的集中式调控架构体系将无法有效处理这些分布式单元,因此有必要对主动配电网分布式资源集群优化调度开展研究。以基于多智能体架构的主动配电网为研究对象,根据“群内自治、群间协调”的分级调控思想,提出一种基于“源-荷”集群功率偏差的双层分布式优化调度策略。在上层全局优化阶段,提出基于“源-荷”集群功率偏差的改进一致性算法对各集群间进行分布式协调优化;在下层局部优化阶段,基于分布式一致性算法对各分布式单元进行协调优化,获取最优效益下“源-荷”需求,同时对所提策略的收敛性进行证明。通过IEEE 33节点系统验证所提策略的有效性和合理性。

基于改进模糊AHP的风电场有功功率分配方法

针对基于模糊评价的风电场有功功率分配中,模糊参数较多的问题,提出一种改进的模糊层次分析法(Analytic Hierarchy Process, AHP)的风电场有功功率分配算法。考虑变速变桨风电机组限功率调节特点,采用AHP方法确定变速和变桨系统的相对权重系数,结合TS(Takagi-Sugeno)模糊模型评价全风速限功率运行机组的功率调节能力,并完成基于功率调节能力的风电场有功功率分配。最终在MATLAB上验证文中所提算法,仿真结果表明,与模糊评价风电场分配算法相比,文中模糊参数少,风电场有功功率输出波动小,并且机组的桨距角行程小。

基于改进人工鱼群算法的主动配电网日前两阶段优化调度

分布式电源(distributed generation, DG)渗透率的不断提高使得传统火电机组正逐步被清洁能源所取代。为降低新能源接入对系统经济运行和稳定运行带来的影响,提出一种主动配电网(active distribution network, ADN)日前优化调度的两阶段模型:第1阶段根据分时电价、DG燃料成本、可中断负荷切除代价进行经济调度,进而确定DG的机组组合、从大电网的购电量及可中断负荷削减量;第2阶段对系统进行无功优化,在第1阶段经济调度结果的基础上,以DG和无功补偿装置的无功补偿量为调节措施,建立综合考虑系统有功损耗和电压质量的无功优化模型,对于所提优化模型提出一种基于变量分离思想的反哺人工鱼群算法(cross feedback artificial fish swarm algorithm, CFAFSA)进行求解,该算法在实现了实型变量和整型变量解耦的同时,降低了变量的维度,提高了算法的收敛速度和全局寻优能力。以IEEE 33节点主动配电系统为算例,验证了模型的有效性及算法的快速性。

基于多运行场景的主动配电网态势感知及优化调度

针对传统主动配电网态势感知在系统损耗值方面存在不达标的问题,考虑多运行场景对主动配电网态势感知及优化调度问题进行研究,并提出基于多运行场景的主动配电网态势感知及优化调度方法。针对主动配电网构建供电能力模型作为态势感知依据,搭建态势感知构架,对主动配电网实施态势感知。分别制定不同时间段下的优化调度策略并使其互相配合,达到主动配电网各单元的运行优化以及负荷的削峰填谷。改进IEEE33标准节点网络后实现主动配电网的模拟,在波动平抑场景与典型运行场景下对该方法的系统损耗值进行测试。测试结果证明,该方法无论在波动平抑场景下还是在典型运行场景下,其系统损耗值都更低,相较现有研究成果存在显著优势。