Optimal dispatch approach for rural multi-energy supply systems considering virtual energy storage

In response to the underutilization of energy and insufficient flexible operation capability of rural energy supply systems in China,this study proposes an optimal dispatch approach for a rural multi-energy supply system(RMESS)considering virtual energy storage(VES).First,to enable the flexible utilization of rural biomass resources and the thermal inertia of residential building envelopes,this study constructed VES-I and VES-II models that describe electrical-thermal and electrical-gas coupling from an electrical viewpoint.Subsequently,an RMESS model encompassing these two types of VES was formulated.This model delineates the intricate interplay of multi-energy components within the RMESS framework and facilitates the precise assessment of the adjustable potential for optimizing RMESS operations.Based on the above models,a day-ahead optimal dispatch model for an RMESS considering a VES is proposed to achieve optimal economic performance while ensuring efficient energy allocation.Comparative simulations validated the effectiveness of the VES modeling and the day-ahead optimal dispatch approach for the RMESS.

Research on Virtual DC Generator-Based Control Strategy of DCMicrogrid with Photovoltaic and Energy Storage

With the penetration of a large number of photovoltaic power generation units and power electronic converters,the DC microgrid shows low inertia characteristics,which might affect the stable operation of the microgrid in extreme cases.In order to enhance the“flexible features”of the interface converter connected to the DC bus,a control strategy of DCmicrogrid with photovoltaic and energy storage based on the virtual DC generator(VDCG)is proposed in this paper.The interface converters of the photovoltaic power generation system and the energy storage system simulates the inertia and damping characteristics of the DC generator to improve the stability of the DC bus voltage.The impedance ratio of DC microgrid was obtained by establishing the small-signal model of photovoltaic power generation system and energy storage system,and the Nyquist curves was applied to analyze the small-signal stability of the system.Finally,the simulation results were verified with MATLAB/Simulink.The results show that the proposed control strategy can slow down the fluctuation of bus voltage under the conditions of photovoltaic power fluctuation and load mutation,thus enhancing the system stability.

Battery Energy Storage System and Demand Response Based Optimal Virtual Power Plant Operation

With certain controllability of various distribution energy resources (DERs) such as battery energy storage system (BESS), demand response (DR) and distributed generations (DGs), virtual power plant (VPP) can suitably regulate the powers access to the distribution network. In this paper, an optimal VPP operating problem is used to optimize the charging/discharging schedule of each BESS and the DR scheme with the objective to maximize the benefit by regulating the supplied powers over daily 24 hours. The proposed solution method is composed of an iterative dynamic programming optimal BESS schedule approach and a particle swarm optimization based (PSO-based) DR scheme approach. The two approaches are executed alternatively until the minimum elec-tricity cost of the whole day is obtained. The validity of the proposed method was confirmed with the obviously decreased supplied powers in the peak-load hours and the largely reduced electricity cost.

Coordinated control strategy for a PV-storage grid-connected system based on a virtual synchronous generator

Due to the characteristics of intermittent photovoltaic power generation and power fluctuations in distributed photovoltaic power generation,photovoltaic grid-connected systems are usually equipped with energy storage units.Most of the structures combined with energy storage are used as the DC side.At the same time,virtual synchronous generators have been widely used in distributed power generation due to their inertial damping and frequency and voltage regulation.For the PV-storage grid-connected system based on virtual synchronous generators,the existing control strategy has unclear function allocation,fluctuations in photovoltaic inverter output power,and high requirements for coordinated control of PV arrays,energy storage units,and photovoltaic inverters,which make the control strategy more complicated.In order to solve the above problems,a control strategy for PV-storage grid-connected system based on a virtual synchronous generator is proposed.In this strategy,the energy storage unit implements maximum power point tracking,and the photovoltaic inverter implements a virtual synchronous generator algorithm,so that the functions implemented by each part of the system are clear,which reduces the requirements for coordinated control.At the same time,the smooth power command is used to suppress the fluctuation of the output power of the photovoltaic inverter.The simulation validates the effectiveness of the proposed method from three aspects:grid-connected operating conditions,frequency-modulated operating conditions,and illumination sudden-drop operating condition.Compared with the existing control strategies,the proposed method simplifies the control strategies and stabilizes the photovoltaic inverter fluctuation in the output power of the inverter.

Electromechanical Transient Modeling Analysis of Large-Scale New Energy Grid Connection

The synchronous virtual machine uses inverter power to imitate the performance of the conventional synchronous machine.It also has the same inertia,damping,frequency,voltage regulation,and other external performance as the generator.It is the key technology to realize new energy grid connections’stable and reliable operation.This project studies a dynamic simulation model of an extensive new energy power system based on the virtual synchronous motor.A new energy storage method is proposed.The mathematical energy storage model is established by combining the fixed rotor model of a synchronous virtual machine with the charge-discharge power,state of charge,operation efficiency,dead zone,and inverter constraint.The rapid conversion of energy storage devices absorbs the excess instantaneous kinetic energy caused by interference.The branch transient of the critical cut set in the system can be confined to a limited area.Thus,the virtual synchronizer’s kinetic and potential energy can be efficiently converted into an instantaneous state.The simulation of power system analysis software package(PSASP)verifies the correctness of the theory and algorithm in this paper.This paper provides a theoretical basis for improving the transient stability of new energy-connected power grids.

Low-Carbon Dispatching for Virtual Power Plant with Aggregated Distributed Energy Storage Considering Spatiotemporal Distribution of Cleanness Value

The scale of distributed energy resources is increasing,but imperfect business models and value transmission mechanisms lead to low utilization ratio and poor responsiveness.To address this issue,the concept of cleanness value of distributed energy storage(DES)is proposed,and the spatiotemporal distribution mechanism is discussed from the perspectives of electrical energy and cleanness.Based on this,an evaluation system for the environmental benefits of DES is constructed to balance the interests between the aggregator and the power system operator.Then,an optimal low-carbon dispatching for a virtual power plant(VPP)with aggregated DES is constructed,where-in energy value and cleanness value are both considered.To achieve the goal,a green attribute labeling method is used to establish a correlation constraint between the nodal carbon potential of the distribution network(DN)and DES behavior,but as a cost,it brings multiple nonlinear relationships.Subsequently,a solution method based on the convex envelope(CE)linear re-construction method is proposed for the multivariate nonlinear programming problem,thereby improving solution efficiency and feasibility.Finally,the simulation verification based on the IEEE 33-bus DN is conducted.The simulation results show that the multidimensional value recognition of DES motivates the willingness of resource users to respond.Meanwhile,resolving the impact of DES on the nodal carbon potential can effectively alleviate overcompensation of the cleanness value.

Research on VSG Frequency Characteristics and Energy Storage Device Capacity and Charge-Discharge Characteristics Based on Feedforward Branch

Renewable energy is connected to the grid through the inverter,which in turn reduces the inertia and stability of the power grid itself.The traditional grid-connected inverter does not have the function of voltage regulation and frequency regulation and can therefore no longer adapt to the new development.The virtual synchronous generator(VSG)has the function of voltage regulation and frequency regulation,which has more prominent advantages than traditional inverters.Based on the principle of VSG,the relationship between the frequency characteristics and the energy storage capacity of the feedforward branch-based virtual synchronous machine(FVSG)is derived when the input power and grid frequency change.Reveal the relationship between the virtual inertia coefficient,damping coefficient,and frequency characteristics of VSG and energy storage capacity.An energy storage configuration method that meets the requirements of frequency variation characteristics is proposed.A mathematical model is established,and the Matlab/Simulink simulation software is used for modeling.The simulation results verify the relationship between the inertia coefficient,damping coefficient,and energy storage demand of the FVSG.

基于虚拟储能的综合能源系统用能协调控制策略

多能互补综合能源系统(Integrated Energy System,IES)是提高分布式新能源渗透率和增强终端能源消费灵活性的重要手段,针对现有技术在多能系统对外能量特性建模和多系统交互策略方面研究的不足,文章提出了一种基于虚拟储能的综合能源系统用能协调控制方法,基于多代理技术构建楼宇-代理商-配网三层能量交互架构,以描述系统对外特性的虚拟储能模型为交互接口,量化分析管控多楼宇和并网储能、微燃机等多能分布式资源的代理商的虚拟储能。在此基础上,按照系统空间范围扩大递进分析,构建基于多代理的综合能源系统用能协调控制策略,该策略能够根据决策目标最大化利用以配电网为核心的楼宇、园区等各层级综合能源系统的资源,尽可能实现自治运行。

考虑SOC的混合储能功率分配与自适应虚拟惯性控制

电力电子化的直流配电网存在低惯性问题,不利于系统稳定运行。混合储能设备可向电网提供虚拟惯性,但不同类型的储能之间存在功率协调问题,并且储能的荷电状态(state of charge, SOC)对虚拟惯性的调节也有约束作用。针对上述问题,提出了一种自适应时间常数的分频控制策略,时间常数根据混合储能系统(hybridenergy storage system, HESS)的SOC而动态调整以改变功率分配。首先,通过分析储能SOC与虚拟惯性的关系,并考虑储能充放电极限问题,研究兼顾SOC、电压变化率以及电压幅值的自适应虚拟惯性控制策略,提高系统惯性。然后,建立控制系统的小信号模型,分析虚拟惯性系数对系统的影响。最后,基于Matlab/Simulink搭建直流配电网仿真模型,验证了所提控制策略能合理分配HESS功率,提高超级电容器利用率,改善直流电压与功率稳定性。

综合能源系统下虚拟储能建模方法与应用场景研究综述及展望

为了促进多能耦合互补和实现可再生能源就地消纳,综合能源系统已成为多领域的研究热点。考虑到能源设备及网络的多样性、复杂性以及多种能源时间尺度的差异性,根据能量平衡原理,对系统内具有可调特性的源、网、荷进行储能化建模,并构成虚拟储能系统参与到综合能源系统的优化调度中。为了准确把握虚拟储能的研究重点,首先介绍了虚拟储能的定义、逻辑架构和技术内涵;其次针对综合能源系统源、网、荷端设备或网络,总结和归纳了4种虚拟储能建模方法和特性指标;然后重点分析了虚拟储能在4种典型场景的具体应用;最后展望了虚拟储能未来的发展方向。

基于MMC的分布式储能系统及其快速SOC均衡控制策略

提高基于模块化多电平换流器(modular multilevel converter,MMC)的分布式储能系统(distributed energy storage systems,DESS)的能量利用率,解决储能子模块(energy sub-module,ESM)荷电状态(state of charge,SOC)均衡问题至关重要。针对现有的SOC均衡控制策略的不足,提出内外分层的快速SOC均衡控制策略。外层针对桥臂间或相间的SOC差异,通过改进MMC模型预测控制(model predictive predictive control,MPC),配合自适应均衡系数,快速调整功率差额。内层引入自适应虚拟电阻法,根据ESM的SOC情况确定主导ESM,自适应调节各单元的虚拟电阻,产生相应的电压梯度,结合MMC排序算法使ESM按照各自SOC进行功率分配,从而实现ESM的SOC快速均衡,提高DESS能量利用率。通过在Matlab/Simulink构建仿真模型,证明了所提控制策略的有效性和可行性。

考虑储能约束的神经网络VSG参数自适应控制策略

虚拟同步发电机(Virtual Synchronous Generator, VSG)控制策略常用于处理高比例新能源并网导致系统惯量、阻尼缺失的问题,储能单元的配置制约着VSG惯量阻尼的设定。首先,建立考虑储能荷电状态(State of Charge, SOC)约束的VSG小信号模型,计算多约束条件下惯量阻尼取值范围。然后,借助径向基函数(Radial Basis Function, RBF)神经网络算法处理连续非线性函数的优点,提出一种计及储能约束的RBF神经网络VSG惯量阻尼自适应控制策略。该策略取频率偏差量和频率变化率为输入,输出为VSG转动惯量,根据二阶系统最优阻尼比确定阻尼系数取值。最后通过Matlab/Simulink仿真验证,结果表明所提计及多约束的VSG自适应控制策略能够快速响应系统频率变化,优化系统动态调节能力;减小直流母线电压跌落,增强系统鲁棒性。

面向季节性短时高峰负荷的虚拟配电馈线功能架构及协同配置

传统线路增容方式面对季节性短时高峰负荷时存在线路整体利用率低、紧急功率支撑能力差等问题。因此,文中以功能虚拟化为核心,研究了传统配电馈线与储能元件融合的虚拟配电馈线功能架构,利用双端储能元件搭建虚拟电能传输通道,以应对季节性短时高峰负荷、延缓传统线路增容改造工程,并在非高峰时期提供紧急功率支撑和辅助服务功能,提高储能元件整体利用率。为充分挖掘虚拟配电馈线的灵活传输和紧急功率支撑潜力,提出了配电网线路增容优化配置模型,在保证经济性和满足高峰负荷需求的前提下,优化虚拟配电馈线储能配置。算例研究表明,虚拟配电馈线能够有效延缓传统线路增容改造工程、应对季节性短时高峰负荷;对于线路负荷增长较稳定、线路长度较长和设计延缓增容年限较短的配电区域,虚拟配电馈线的优势更加凸显。

风储锁相弹性耦合下的系统次同步振荡抑制技术

通过虚拟刚度建立储能与风电机组锁相间的弹性连接关系是高效抑制锁相环诱发次同步振荡的关键。以机械振动力学为基础,该文首先在风电机组锁相与储能虚拟同步机之间建立相位弹性耦合关系,并定义虚拟锁相刚度。其次,引入虚拟锁相刚度,建立风储弹性系统的两自由度运动模型,分析风电机组相位的幅频响应特性,并基于固定点理论,优化设计风储间整体刚度和阻尼。再次,提出虚拟锁相刚度控制策略,将其嵌入储能虚拟同步机控制系统中,并与虚拟惯量、阻尼环节构建风储弹性耦合控制系统结构。最后,搭建风储高渗透并网仿真系统,验证增设虚拟锁相刚度后,风电机组锁相环诱发的次同步振荡能够得到有效抑制,显著提升系统的稳定性。

基于NSGA-Ⅱ的飞轮-火电联合二次调频最优负荷分配策略

为了在提升飞轮-火电联合二次调频性能的同时控制调频成本、减少飞轮损耗,面向飞轮-火电联合系统,提出一种考虑自动发电控制(AGC)指令及电网频率偏差的基于多目标遗传算法的负荷分配策略。该策略以电网调频偏差、飞轮-火电出力能量和、飞轮损耗为三层最小化目标,考虑火电机组爬坡率及其负荷备用、飞轮荷电状态及其功率等约束条件,基于改进的非支配排序遗传算法(NSGA-Ⅱ),通过AGC功率指令变化速度及频率偏差动态调整飞轮与火电出力权重系数,以频率偏差及其变化方向调整飞轮虚拟下垂、惯性系数,求解飞轮-火电出力比例、飞轮下垂系数和飞轮惯性系数。结合中国宁夏某电厂飞轮储能系统辅助火电机组调频现场AGC指令等历史数据,在双区域两机系统模型上进行仿真实验,结果表明该负荷分配策略有效地减小了火电二次调频偏差和调节时间,提升了调频性能,同时也有效地控制了系统出力能量及飞轮损耗。

基于光储联合系统的电网分段恢复策略

当前新能源大量引入至电力系统,为了使其代替传统的水电、燃气机组作为黑启动电源,文中研究了基于光储联合系统的电网分段恢复策略。首先,根据光储系统的结构和控制方式,提出由储能系统建立稳定的并网母线线电压,光伏系统分步并网的启动方式;其次,为了增强光伏发电系统的惯性阻尼支撑,提出在光伏系统逆变器侧加入虚拟同步控制;最后,在待启动机组和系统负荷并网过程中,利用储能系统配置附加阻尼控制器抑制电网黑启动产生的次同步振荡,保证电网稳定恢复。在PSCAD/EMTDC中搭建光储联合系统黑启动的电磁暂态仿真模型并进行分析,结果表明系统恢复过程中母线线电压偏差不超过0.65%、系统频率偏差不超过1%,满足黑启动要求,验证了文中所提启动策略的可行性。

基于改进虚拟同步发电机的构网型并联储能逆变器控制研究

针对构网型变换器预同步过程时电力系统频率电压稳定性低导致变换器并网失败的问题,提出一种基于改进线性自抗扰控制(LADRC)的构网型变换器预同步控制策略。首先,采用无锁相环(PLL)控制策略,通过相位偏差的反馈控制对网侧电压的相位和幅值进行快速同步追踪,可避免因PLL精度较低和响应速度慢而引起的电力系统稳定性降低的问题。在此基础上,在有功频率支路模块的角频率输出端引入LADRC,这可以有效解决预同步控制过程中变换器输出电压频率存在过冲的问题,从而确保构网型变换器预同步控制顺利进行最终实现成功并网。最后,在MATLAB/Simulink仿真平台中搭建基于改进LADRC的构网型变换器预同步控制模型并进行仿真验证,结果表明所提控制策略可以有效抑制系统频率震荡,并能够加速系统预同步进程,确保构网型变换器安全运行最终实现成功并网,仿真结果验证了所提方法的有效性。

虚拟直流电机荷电状态均衡控制

新型电力系统的惯性低,虚拟直流电机控制可以加强系统惯性和阻尼。多储能变换器应该考虑荷电状态(State of charge,SOC)均衡问题,提高系统稳定性。针对虚拟直流电机控制的多储能SOC均衡问题,利用直流电机机端电压和电枢电流的下垂特性,提出引入SOC离差及变均衡系数的变电枢电阻控制;针对下垂引起的电压偏移问题,采用虚拟直流电机转速补偿,用母线电容瞬时功率替代传统虚拟直流电机控制中电压PI控制,给定系统功率需求,减少比例积分环节个数。以两台蓄电池为例,在Simulink中进行仿真,并与参考文献的变电枢电阻函数对比可知,所提控制策略可抑制直流母线电压跌落,调节SOC均衡过程,提高其均衡速度和精度。

考虑车网互动的园区电网动态双层能量管理策略

为解决大量接入的清洁能源出力波动和充电场内汽车数量的随机变化给电网能量管理带来的困难,提出一种园区电网双层优化控制策略.上层基于模型预测控制技术建立风光储集成动态优化模型,综合应用园区电池储能系统和电动汽车(EV)电池储能系统参与电网能量平衡.下层则考虑同时满足EV车主对EV的充电需求和上层能量调度的车网互动管理需求,制定园区电网内停车场的EV有序充放电策略.仿真算例验证表明:所提策略能将分散园区各处的EV储能集成为统一虚拟储能,扩展园区电网储能系统,增加可再生分布式电源的消纳与园区电网的经济效益.

基于强化学习的含分布式风-光-储虚拟电厂优化调度

将大量小规模的分布式风电、光伏发电和储能等单元并网的一种有效手段是将它们通过能源聚合商聚合之后参与虚拟电厂(VPP)的优化调度,然而VPP调度中心常难以对能源聚合商的总体出力特性进行精确的建模及预测,给传统的集中式VPP优化调度模式带来挑战。针对含分布式风-光-储单元的VPP,提出一种基于强化学习的交互式优化调度模型。VPP调度中心通过与各聚合商的在线信息交互,逐步学习得到VPP中各类单元的聚合出力及VPP对大电网的购售电量决策。该优化模型采用深度确定性策略梯度(DDPG)算法求解。基于真实新能源出力数据的仿真算例验证了该方法的有效性。与线性规划求解器得到的传统集中式调度结果对比,表明本所提法有助于改善VPP运行总效益,尤其是提高新能源利用率。