Optimization of a battery energy storage system using particle swarm optimization for stand-alone microgrids

The main challenge in integrating a Battery Energy Storage System (BESS) into a microgrid is to evaluate an optimum size of BESS to prevent the microgrid from instability and system collapse. The installation of BESS at a random size or non-optimum size can increase in cost, system losses and larger BESS capacity. Thus, this paper proposes the new method to evaluate an optimum size of BESS at minimal total BESS cost by using particle swarm optimization (PSO)-based frequency control of the stand-alone microgrid. The research target is to propose an optimum size of BESS by using the PSO method-based frequency control in order to prevent the microgrid from instability and system collapse after the loss of the utility grid (e.g., blackout or disasters) and minimize the total cost of BESS for 15 years installation in the microgrid. Then, the economical performance of BESS with modern different storage technologies is investigated and compared in the typical microgrid. Results show that the optimum size of BESS-based PSO method can achieve higher dynamic performance of the system than the optimum size of BESS-based analytic method and the conventional size of BESS. In terms of BESS economical performance with modern storage technologies, the installation of the polysulfide–bromine BESS is likely to be more cost-effective than the installation of the vanadium redox BESS for 15 years installation in the typical microgrid. It is concluded that the proposed PSO method-based frequency control can improve significantly power system stability, grid security, and planning flexibility for the microgrid system. At the same time, it can fulfill the frequency control requirements with a high economic profitability.     

适用于工业园区的微电网系统能量管理

为了提高微电网系统输出特性,满足工业园区并网要求,提出一种基于功率预测、前馈控制的微电网系统能量管理策略。通过功率预测,高效控制微电网系统输出功率,跟踪厂区负荷;基于前馈控制的储能波动平抑,有效平滑系统输出,并提高电池应用效率。在RTDS实时仿真平台上,结合能量管理器,搭建微电网系统硬件在环测试平台,MW级风光储微电网系统工程的长期稳定运行验证了所提算法的有效性和稳定性。     

基于改进二进制蝙蝠算法的独立型微网容量优化配置

该文围绕独立型风/光/柴/储微网的容量优化配置展开研究,以微网系统供电可靠性为约束条件,同时考虑微网经济性、环保性和可再生能源利用率3个指标,以加权后的年均综合费用最小为优化目标,构建微网容量优化配置的非线性整数规划模型。针对连续优化算法直接用于求解离散优化模型而导致的局部最优问题,该文提出一种改进的二进制蝙蝠算法(improved binary bat algorithm,IBBA),将差分进化(differential evolution,DE)算法的变异、交叉、选择操作与二进制蝙蝠算法(binary bat algorithm,BBA)相结合,增强BBA的全局寻优能力。算例结果表明,IBBA求解得到的配置结果在精度和稳定性上均优于遗传算法(genetic algorithm,GA)、粒子群算法(particle swarm optimization,PSO)和DE算法。     

Multi-stage Frequency Control of a Microgrid in the Presence of Renewable Energy Units

The integration of distributed generations such as photovoltaic and wind as well as large load variations leads to the significant issue of frequency stability problem. This paper presents a multi-stage frequency control for microgrids. Energy storage systems such as BESSs are selected as a flexible and fast-response device for this application. In the first stage, a PI control method based on PSO for the BESS is applied in order to minimize the frequency deviations. Moreover, in contingency modes, in which the BESS with the optimized PI control application cannot stabilize the system due to the unbalanced situation of supply and demand, fast reaction of the central control system operator is necessary in order to protect the network from collapse. Hence, in the second stage of the control, a Fuzzy-logic frequency controller as a smart controller is designed. This controller proposes solutions through power level change such as load shedding in a short time to rescue the network from instability. The proposed method is validated by a set of simulations on a representative microgrid. The effectiveness of the proposed multi-stage control is illustrated through the comparison to the one-stage controller without the Fuzzy-logic part.     

基于自适应虚拟惯性的微电网动态频率稳定控制策略

微电网作为分布式电源的有效载体,通过分布式电源并联连接形成独立电网。而微电网中传统下垂控制的输出频率动态响应速度快,在负荷频繁波动下易受到较大扰动。为了提高微电网频率的动态稳定性,文中提出了一种基于自适应虚拟惯性的同步发电机的控制策略,该方法模拟同步发电机的行为,构造频率变化率与虚拟惯性的关系,自适应改变虚拟同步发电机控制的惯性,从而提高微电网系统抗干扰能力和过载能力。相比于传统的交替惯性方法,所构造的自适应惯性算法不需要采样频率微分项,避免了引入系统噪声,同时实现了惯量的平滑灵活调节,具有较强的鲁棒性。另外,利用李雅普诺夫稳定理论分析了所提算法的收敛性和稳定性。仿真和实验结果表明所提方法提升了微电网频率的动态稳定性,从而验证了所提控制策略的可行性和有效性。     

兼顾新能源消纳与频率电压支撑的电池储能系统优化规划

随着新能源发电占比的逐步提升,电力系统消纳新能源发电的难度和压力增大,电网的频率和电压稳定性面临巨大挑战。通过在电网中配置电池储能系统,不仅可以提升新能源的消纳能力,还可以提升系统频率和电压的支撑能力。因此,研究电池储能系统优化规划方法,考虑储能在电力系统正常运行时用于新能源消纳,在紧急情况下对频率和电压进行快速支撑,从而提高储能利用率,降低系统成本。建立了考虑新能源消纳的电池储能系统协同规划模型,可得到输电网中集中式电池储能系统和配电网中分布式电池储能系统的选址定容结果。提出了一种兼顾频率和电压支撑的电池储能系统规划方法,分别对储能位置、无功功率容量、有功功率容量和能量容量进行优化规划。综合考虑储能的多重功能,构建其支撑系统调频调压的约束,建立了兼顾新能源消纳与频率电压支撑的电池储能系统优化规划模型,得到电池储能系统的最终选址定容结果。基于IEEE 24节点输电网和IEEE 33节点配电网设计算例系统进行仿真分析,验证了所提方法的有效性。     

基于改进粒子群算法的多能微网多目标优化调度

为实现多能微网内部能源的灵活调用,减轻系统碳排放压力,文中提出了一种基于改进粒子群(particle swarm optimization, PSO)算法的多能微网多目标优化调度方法。建立了冷热电气多能微网模型,分析系统能源耦合机理并对设备进行数学建模;以微网运行成本与环境成本最小为目标,构建多能微网多目标优化调度模型;提出一种改进PSO算法,通过调整主要参数的迭代规则,并采用自适应粒子寻优策略加快收敛速度,提升寻优效果;仿真结果表明：与传统方法相比,所提基于改进PSO算法的多目标优化调度方法能够有效提升算法收敛速度、降低系统综合成本,兼顾其运行的经济性与环境友好性。     

液态金属电池储能系统在光氢耦合微电网中的优化配置

液态金属电池是一种新型电池,其与氢储能共同构成的综合储能系统可以很好地满足微电网的需求。首先为该综合储能系统设计了一套以经济性最优为原则的调度方案,使两种储能装置协调配合,共同平抑并网光伏电能的功率波动。其次,仿真计算该调度方案下的液态金属电池配置成本、微电网年利润、电池预期使用寿命、电池容量不足的天数等指标,并利用这4项指标构建液态金属电池储能系统性能的综合评价模型。最后,以某光氢耦合微电网为例,利用上述模型对不同容量液态金属电池的性能进行评价,得出了电池的最优配置容量。     

基于100%绿色能源供电目标的海岛微电网群容量优化配置

针对常规化石燃料机组在解决海岛供能时带来的环境污染问题,该文以100%的可再生能源发电满足海岛负荷需求为目标,探讨基于100%绿色能源供电的海岛微电网群优化配置问题。首先,构建由不同功能类型的微电网组成的海岛微电网群,并制定其100%可再生能源供电的运行规则和相应的协调控制策略;然后,根据蓄电池、抽水蓄能电站的运行特性提出以储能装置运行成本最小化为目标的运行成本动态优化策略,以使总成本最小化;最后,通过NSGA-Ⅱ算法求解不同场景下的容量优化配置模型,并分析可再生能源发电和负荷波动的不确定性对优化配置结果的影响。算例结果表明,所提的海岛微电网群优化配置模型能够在满足经济可靠性的要求下,实现100%绿色能源供电的目标,为发展"生态友好型"海岛微电网提供工程参考。     

基于坐标旋转虚拟阻抗的微电网控制与性能分析

微电网中系统阻抗不平衡和复阻抗特性、电源和负载位置复杂性等因素严重影响了系统功率分配的准确性、稳定性和动态性能。提出了基于坐标旋转虚拟阻抗的孤岛微电网控制策略,采用坐标旋转虚拟阻抗闭环改善微电网的阻抗特性,基于电压幅值和频率下垂控制实现系统功率分配,带前馈补偿的电压外环控制和电流内环控制保证了系统的稳态和暂态性能。建立了完整的微电网小信号动态模型,并在此基础上分析了坐标旋转虚拟阻抗对整个微电网性能的影响。算例仿真验证了小信号动态建模分析的准确性,证明了该方法能够改进功率解耦和分配的准确性,提高微电网控制的稳定性和动态性能。     

基于模型预测控制混合储能系统的直流微电网韧性提升策略

受可再生能源出力波动、负荷变化、故障以及非计划性脱网等事件的影响,直流微电网将面临不同时间尺度的动态功率不平衡问题.直流微电网运行韧性体现了系统在高频/小干扰事件与低频/极端事件下的快速响应、减少性能损失并尽快恢复的能力.提出了一种基于有限控制集模型预测控制的混合储能系统的直流微电网运行韧性提升策略.为完善直流微电网韧性评价体系,首先提出了量化直流微电网运行韧性的方法.其次,建立混合储能系统离散预测模型,设计代价函数以及不同控制目标之间的权重系数,最大化功率型与能量型储能系统的优势,实现了基于局部信号的快速充放电与能量自动恢复控制.最后,通过多种干扰事件算例,验证所提出的韧性提升方法的可行性与有效性.     

考虑储能电池参与一次调频技术经济模型的容量配置方法

规模间歇电源并网引起的电网频率问题,导致对引入储能辅助调频的研究越发迫切。提出一种考虑储能电池参与一次调频技术经济模型的容量配置方法。阐述了储能电池功率和容量设计的通用方法;通过分析储能电池在调频运行过程中的成本和效益,基于全寿命周期理论,运用净现值法结合仿真模型构建储能电池参与一次调频的技术经济模型;设计了一种储能电池参与一次调频的充放电策略,在此基础上,考虑受风电出力波动影响的电网综合负荷,从与之对应的电网频率信号波动特性出发,在确定的电网调频及储能电池运行要求约束下,得出调频效果最优、经济性最优以及两者综合最优目标下的储能电池容量配置方案。仿真结果表明了该方法的合理性及有效性。本研究有助于推动储能电池在辅助调频服务上的示范与工程化应用。     

Battery energy storage system for frequency support in microgrids and with enhanced control features for uninterruptible supply of local loads

This paper proposes a battery energy storage system (BESS) to support the frequency control process within microgrids (MG) with high penetration of renewable energy sources (RES). The solution includes features that enhance the system’s stability and security of supply. The BESS can operate connected to MG or islanded and the transition between the two states is seamlessly coordinated by an original method. The BESS active power response is governed by an improved frequency controller on two layers, namely primary and secondary. It responds to frequency deviations by combining a conventional droop control method with a virtual inertia function to improve the system’s stability. The proposed BESS may also compensate the power of the local loads, so that the MG frequency transients can be reduced and, depending on the remaining inverter capacity, voltage support in the point of common coupling with the MG may be provided. If the MG power quality degrades in terms of the voltage and frequency, the BESS and the local load are disconnected from the MG and continue operating islanded. The BESS is reconnected to the MG after a smoothly resynchronization of the local voltage with the MG, without disturbing the local loads supply. Simulation and experimental results assesses the proposed control solutions.     

基于线性自抗扰控制的微网逆变器时-频电压控制策略

微网是一个非线性、强耦合、多约束、负载扰动大的系统,传统比例-积分(PI)双环控制已经无法满足需求,自抗扰技术通过补偿扰动可使微网逆变控制系统的性能显著改善。据此,文中提出了基于线性自抗扰控制(LADRC)的微网逆变器时-频电压控制策略。为了提高微网逆变器的抗扰性能和动态性能,在时域上,设计和分析了dq轴解耦环节、带电容电流反馈的降维扩张状态观测器以及线性状态误差反馈控制律;为了提高微网逆变器在各谐波频率处的跟踪精度和抗扰性能,分析了时域LADRC系统的频率响应特性,并据此设计和分析了频域上的实部/虚部解耦环节和时-频域LADRC策略。最后,针对工作在孤岛模式下的微网逆变器,对所提策略进行了实验验证。实验结果表明,与PI双环控制对比,基于LADRC的微网逆变器时-频电压控制策略具有更好的解耦、抗扰、动态性能,并能精确控制谐波电压以达到抑制谐波的效果。     

基于模糊控制的电池储能系统辅助AGC调频方法

针对AGC控制中火电机组响应时滞长、机组爬坡速率低的问题,提出了一种基于模糊控制策略的电池储能系统(Battery Energy Storage System,BESS)辅助AGC调频方法。该方法以区域控制偏差(Area Control Error,ACE)及其变化率作为模糊控制器的输入量,BESS的参考功率变化量作为输出量,根据系统的运行状态调节BESS输出功率,辅助火电机组改善电网的动态调频性能。基于Matlab/Simulink平台的仿真结果表明,BESS能够迅速响应负荷扰动,减小了系统频率偏差和联络线功率偏差,降低了系统的超调作用,有助于提高电网AGC调频能力和增强系统的稳定性。     

孤岛运行模式下微网的稳定控制仿真分析

为了更好地分析微网系统的稳定特性及影响因素,基于PSCAD／EMTDC建立了孤岛微网系统的动态仿真模型,针对微网恒频恒压控制、高周切机、切负荷控制等措施下的系统特性进行仿真试验,结果显示：孤岛运行时微网系统整体稳定性较差,系统抗扰动能力弱,当系统发生扰动或故障时,须保证充裕的旋转备用容量或采取快速稳定控制措施才能保持系统稳定运行。同时提出了相应改进措施及建议。     

微电网储能系统下垂协调控制与母线电压控制策略

针对风光互补微电网内风力发电系统和光伏发电系统运行特性,提出采用蓄电池储能系统(Battery Energy Storage System,BESS)与超级电容储能系统(Super Capacitor Energy Storage System,SCESS)下垂协调控制策略基础上对微电网母线电压采用对应的控制策略,进而优化无功功率控制,以此进一步提高对微电网内负荷供电的稳定性。文中对微电网模式切换过程,加以控制策略理论分析,再通过PSCAD/EMTDC仿真软件,验证文中所提出控制策略的有效性及可行性。     

考虑需求响应影响的含分布式电源的配电网多目标协调规划

分析了考虑需求响应影响的含分布式电源(DG)的配电网多目标协调规划问题,建立了以DG综合投资成本(包括DG安装及运行维护成本、购电综合成本、需求响应运行成本、网络损耗成本和环境效益)最小为目标的模型,综合考虑网络系统安全约束和需求响应运行约束条件,实现DG位置和容量的协调规划。利用自适应粒子群算法对IEEE33节点系统进行求解,算例结果表明,该模型能有效提高可再生能源的利用率,提升含DG的配电网规划的经济性。     

基于RT-LAB的储能系统离网运行控制策略研究

微网离网运行时,要求电压和频率稳定。针对风电和光伏的间歇性波动以及负载的频繁投切特性,微网需要储能系统平衡有功和无功功率。本文首先基于RTLAB搭建了储能系统离网运行实验平台,然后在传统的V/f单环控制基础上,对比分析了电感电流内环和电容电流内环两种双环控制方法,改进了传统的恒压恒频控制,该控制策略有更好的抗负载电流扰动特性。最后在matlab/simulink环境下进行了仿真,并且在RTLAB平台上进行了半实物仿真验证,结果表明了提出控制策略的有效性。     

A particle swarm optimization for economic dispatch with nonsmooth cost functions

This work presents a new approach to economic dispatch (ED) problems with nonsmooth cost functions using a particle swarm optimization (PSO) technique. The practical ED problems have nonsmooth cost functions with equality and inequality constraints that make the problem of finding the global optimum difficult using any mathematical approaches. A modified PSO (MPSO) mechanism is suggested to deal with the equality and inequality constraints in the ED problems. A constraint treatment mechanism is devised in such a way that the dynamic process inherent in the conventional PSO is preserved. Moreover, a dynamic search-space reduction strategy is devised to accelerate the optimization process. To show its efficiency and effectiveness, the proposed MPSO is applied to test ED problems, one with smooth cost functions and others with nonsmooth cost functions considering valve-point effects and multi-fuel problems. The results of the MPSO are compared with the results of conventional numerical methods, Tabu search method, evolutionary programming approaches, genetic algorithm, and modified Hopfield neural network approaches.