Double-Layer-Optimizing Method of Hybrid Energy Storage Microgrid Based on Improved Grey Wolf Optimization

To reduce the comprehensive costs of the construction and operation of microgrids and to minimize the power fluctuations caused by randomness and intermittency in distributed generation,a double-layer optimizing configuration method of hybrid energy storage microgrid based on improved grey wolf optimization(IGWO)is proposed.Firstly,building a microgrid system containing a wind-solar power station and electric-hydrogen coupling hybrid energy storage system.Secondly,the minimum comprehensive cost of the construction and operation of the microgrid is taken as the outer objective function,and the minimum peak-to-valley of the microgrid’s daily output is taken as the inner objective function.By iterating through the outer and inner layers,the system improves operational stability while achieving economic configuration.Then,using the energy-self-smoothness of the microgrid as the evaluation index,a double-layer optimizing configuration method of the microgrid is constructed.Finally,to improve the disadvantages of grey wolf optimization(GWO),such as slow convergence in the later period and easy falling into local optima,by introducing the convergence factor nonlinear adjustment strategy and Cauchy mutation operator,an IGWO with excellent global performance is proposed.After testing with the typical test functions,the superiority of IGWO is verified.Next,using IGWO to solve the double-layer model.The case analysis shows that compared to GWO and particle swarm optimization(PSO),the IGWO reduced the comprehensive cost by 15.6%and 18.8%,respectively.Therefore,the proposed double-layer optimizationmethod of capacity configuration ofmicrogrid with wind-solar-hybrid energy storage based on IGWO could effectively improve the independence and stability of the microgrid and significantly reduce the comprehensive cost.

Hybrid Petri Nets for Modeling and Analysis of Microgrid Systems

Hybrid Petri nets(HPNs) are widely used to describe and analyze various industrial hybrid systems that have both discrete-event and continuous discrete-time behaviors. Recently,many researchers attempt to utilize them to characterize power and energy systems. This work proposes to adopt an HPN to model and analyze a microgrid that consists of green energy sources. A reachability graph for such a model is generated and used to analyze the system properties.

Optimal Sizing of Solar/Wind Hybrid Off-Grid Microgrids Using an Enhanced Genetic Algorithm

This paper presents a method for optimal sizing of an off-grid hybrid microgrid (MG) system in order to achieve a certain load demand. The hybrid MG is made of a solar photovoltaic (PV) system, wind turbine (TW) and energy storage system (ESS). The reliability of the MG system is modeled based on the loss of power supply probability (SPSP). For optimization, an enhanced Genetic Algorithm (GA) is used to minimize the total cost of the system over a 20-year period, while satisfying some reliability and operation constraints. A case study addressing optimal sizing of an off-grid hybrid microgrid in Nigeria is discussed. The result is compared with results obtained from the Brute Force and standard GA methods.

Research on Distributed Cooperative Control Strategy of Microgrid Hybrid Energy Storage Based on Adaptive Event Triggering

Distributed collaborative control strategies for microgrids often use periodic time to trigger communication,which is likely to enhance the burden of communication and increase the frequency of controller updates,leading to greater waste of communication resources.In response to this problem,a distributed cooperative control strategy triggered by an adaptive event is proposed.By introducing an adaptive event triggering mechanism in the distributed controller,the triggering parameters are dynamically adjusted so that the distributed controller can communicate only at a certain time,the communication pressure is reduced,and the DC bus voltage deviation is effectively reduced,at the same time,the accuracy of power distribution is improved.The MATLAB/Simulink modeling and simulation results prove the correctness and effectiveness of the proposed control strategy.

Research and practice of designing hydro/ photovoltaic hybrid power system in microgrid

Small-hydro power station is often used in remote areas beside a river,but it doesn't match electricity demand so well,especially in dry seasons. A photovoltaic (PV) system with battery is a suitable option to complement the electricity gap. In this paper,a new structure of megawatt-class PV system integrating battery at DC-bus (DC: direct current) is proposed to be used in hydro/PV hybrid power system,and 4 main designing considerations and several key equipments are discussed. In 2011,a 2 MWp PV station with the proposed structure was built up in Yushu,China. From stability analysis,the station shows a strong stability under load cut-in/off and solar irradiance's fluctuation.

Modeling and Simulation of a Hybrid Energy Storage System for Residential Grid-Tied Solar Microgrid Systems

Present-day power conversion and conditioning systems focus on transferring energy from a single type of power source into a single type of load or energy storage system (ESS). While these systems can be optimized within their specific topology (e.g. MPPT for solar applications and BMS for batteries), the topologies are not easily adapted to accept a wide range of power flow operating conditions. With a hybrid approach to energy storage and power flow, a system can be designed to operate at its most advantageous point, given the operating conditions. Based on the load demand, the system can select the optimal power source and ESS. This paper will investigate the feasibility of combining two types of power sources (main utility grid and photovoltaics (PV)) along with two types of ESS (ultra-capacitors and batteries). The simulation results will show the impact of a hybrid ESS on a grid-tied residential microgrid system performance under various operating scenarios.

基于混合两阶段鲁棒的多微网合作优化运行

针对微网独立运行时面临运行成本高,受可再生能源出力和多能负荷功率不确定性影响大等问题,提出一种基于混合两阶段鲁棒优化的多微网合作运行方法。首先,为了应对源荷双重不确定性挑战,在传统两阶段鲁棒优化基础上,提出一种基于多场景数据的最恶劣概率场景驱动的混合两阶段鲁棒优化方法,并采用可并行计算列与约束生成(column and constraint generation,C&CG)算法来提高求解效率。然后,在建立的多微网点对点分布式能源交易系统框架上,根据纳什谈判理论构造多微网合作成本最小化问题和收益分配问题,并提出一种耦合可并行计算C&CG的交替方向乘子法进行求解。最后,根据各微网不同的贡献率,设计一种基于点对点电能交易贡献度的非对称纳什谈判机制来分配各微网的合作收益。算例结果表明,所提方法能兼顾系统的鲁棒性、经济性和隐私性,并实现每个微网公平合理的收益分配。

基于有限时间观测器的光储系统母线电压互补滑模控制

针对光储直流微网混合储能系统易受能源间歇性输入、负载随机性扰动以及功率流向切换等干扰,会造成母线电压波动、系统功率失稳等问题,提出一种基于有限时间观测器的互补滑模控制(FTESO+CSMC)策略.首先,根据混合储能元件的高低频特性,对系统差额功率进行电流等效分配.然后,设计有限时间扩张状态观测器,对系统受到的总扰动进行观测,并将扰动观测值作为前馈项输入互补滑模控制器中,对系统扰动进行补偿,保证系统状态在有限时间内达到收敛,提高了系统的快速性和抗扰性,并根据Lyapunov理论证明了控制系统的稳定性.最后,基于MATLAB仿真平台,对多种模拟工况进行仿真,仿真结果表明,相较于传统控制策略,本文所提控制具有更快的响应速度以及更好的抗扰性能.

事件触发改进一致性算法的孤岛混合微电网并联互联变流器分布式协调控制策略

在交直流混合微电网中,并联互联变流器(parallel bidirectional power converters,BPCs)可以实现大容量的功率传输,以满足新型电力系统在空间上的供需匹配。如何在占用更少资源的同时协调控制BPCs实现功率的比例共享,是交直流混合微电网中BPCs控制的研究难点。因此,该文设计了一种针对BPCs的事件触发改进一致性协调控制策略。以归一化下垂控制为基础,提出了改进的比例功率一致性算法,实现BPCs间高精度比例功率共享。在此之上,基于BPCs比例功率误差建立事件触发改进一致性算法,并预设触发函数的预判阈值,从而降低系统在稳定状态下的通信次数。最后进行仿真对比分析,结果表明该文提出的方法相比基本一致性算法通信量减少98.35%;同时,与现有控制策略相比,该文提出的方法有着更好的控制性能。

电-氢混合储能型多微电网系统有功功率均衡控制方法

在多电-氢微电网并联运行的交流系统中,采用传统控制方法的逆变器会受到输出线路阻抗差异所产生的影响产生较大环流,甚至无法实现有功功率的合理分配,考虑到系统中电压偏差与有功功率间的关系,对多微电网的有功功率分配问题进行分析研究.首先,构建含光伏、燃料电池、电解槽、蓄电池的电-氢混合储能微电网交流系统模型;其次,根据反下垂控制中有功功率与电压间的关系,构造考虑电压偏差的反下垂控制,并为使额定有功功率自适应调节,提出基于功率跟随控制的反下垂控制方法;最后,在多电-氢微电网并联运行的系统中,对本文所提方法进行RT-LAB半实物实验验证及与其他方法的对比验证.实验结果显示:基于本文所提控制方法的系统稳定后功率分配的准确度达97.50%,母线电压的精准度达99.86%,环流大小的范围约为[−3.0,3.0]A,均优于其余方法.

基于滑模变结构的混合微电网接口变换器双向下垂控制

由于混合微电网中的交直流子网具有不同的动态特性,当系统发生负荷突变时,会在双向接口变换器(bidirectional interface converter, BIC)两侧子网间产生功率波动,使交流母线频率和直流母线电压动态响应变差,为此提出了基于分数阶滑模控制器(fractional order sliding mode controller, FOSMC)的双向下垂控制策略。将具有鲁棒性强、响应速度快和抗干扰能力强的滑模变结构控制引入到BIC的控制中,得到改进型的分数阶滑模控制器,以改善系统的暂态响应过程。通过Matlab/Simulink平台搭建了仿真模型,在多种工况下验证了该控制策略的有效性。与传统双向下垂控制相比,该控制算法可以在保证系统原有稳态特性的同时,加快整个系统的响应速度,抑制暂态过程中BIC传输功率的瞬间波动,减小功率波动对交直流子网母线的反作用,提高整个系统的动态性能和抗扰动性能。

基于混合储能的交直流混联微电网功率分级协调控制策略

针对交直流混联微电网孤岛运行时,仅靠互联变流器协调网间功率无法有效缓解系统频率与电压波动,且单一蓄电池储能难以适用多场景功率需求的问题,提出利用超级电容和蓄电池混合储能的交直流混联微电网功率协调控制策略。将混合储能作为储能子网连接在直流母线上,优先采用超级电容平抑交直流子网内功率波动,提出以储能荷电状态来划分五种工作模式的改进混合储能控制策略。兼顾超级电容快速响应特性和减少互联变流器的频繁起动,根据直流子网电压和交流子网频率波动程度,提出功率自治和功率互济工况的两级分层协调控制策略。通过设计混合储能处于不同工作模式的网间功率互济场景,仿真证明了所提混合储能和互联变流器协调控制策略能够平抑各子网负荷功率波动。

基于多目标协调的混合储能功率自适应分配方法

混合储能具有良好的功率可控特性,在孤岛微网中常被用作功率缓冲器,补偿分布式电源和负荷多变的功率潮流.围绕储能的功率响应问题,本文设计了混合储能的功率控制方案,并提出了一种基于多目标协调的子单元功率自适应分配方法.首先基于对母线功率供求平衡关系的分析,设计了主从并联型储能功率控制方案.其次利用积分器的“时空调零”特性,实现了子单元的功率自主分配;基于此,考虑了不同荷电状态(SOC)下储能最大充放电功率的差异,设计了子单元的SOC分层管理和多目标功率协调策略.仿真结果表明,所提策略实现的功率分配效果满足子单元的功率响应特性;随着超级电容SOCscn偏移加深,所提策略对SOCscn的优化能力越强,初始SOCscn为97%时能提高10.10%的优化性能,这保障了超级电容作为电压源的功率输出能力;所提策略降低了超级电容常态下的蓄电池的输出深度,蓄电池的最大功率深度降低了46.70%,这提高了蓄电池的使用寿命.

基于神经网络的微电网交错并联变换器的改进自抗扰控制

针对混合储能微电网在负载突变、扰动加入等多种复杂工况下引起的用电端降压接口的电压质量降低的问题,文章设计了一种以改进线性自抗扰为主要控制器,以BP神经网络为辅助参数优化算法的闭环控制策略。首先,根据六路交错并联变换器的电路拓扑建立时域下的数学模型,并对系统总扰动进行重构,将总扰动分解为模型未知扰动和外界扰动,分别利用观测器进行估计,形成了改进线性自抗扰控制,提高系统的扰动观测能力和观测精度;其次,为使系统获得控制参数的实时优化能力,引入BP神经网络,对控制器参数进行实时整定;最后,搭建了混合微电网六路交错并联变换器的数字仿真模型和半实物仿真模型进行验证,并与PI,LADRC进行了比较。结果显示,所提控制策略不仅具备优异的输出电压质量,而且使系统获得了更好的稳定性与鲁棒性。

基于改进鲸鱼算法的混合储能系统容量优化配置

针对微电网中使用可再生能源的高随机性和间歇性等特征,提出了一种混合储能系统容量优化配置方法。该方法以混合储能系统成本最低、平抑可再生能源功率波动效果最优与电网联络线利用率最高为目标,通过建立混合储能容量优化配置模型并采用改进鲸鱼优化算法对所建立的模型进行求解得到最优混合储能系统容量优化配置。最终对比传统鲸鱼优化算法和传统粒子群算法来验证改进鲸鱼算法可以更合理地配置混合储能系统的容量,使可再生能源功率波动的平抑效果提高,同时也使微网联络线利用率变高,保证微电网可靠、经济地运行,进而实现资源的合理利用。

基于混合博弈的多微网-共享储能双层能量交易策略

为解决用户侧分布式储能运营方式单一、成本较高、利用率较低等问题,提出了兼具电能自营及储能共享模式的多微网-共享储能联合运行方式,从电力市场的角度出发,针对所提方式下的能量交易问题,考虑各微网间的利益冲突和信息不对称,提出了一种基于混合博弈的双层能量交易策略。首先,构建以上层共享储能运营商收益最大化、下层综合能源微网聚合体自身效益最大化为目标的主从博弈-双层能量交易模型;其次,引入综合能源微网聚合体中各成员间的合作博弈,使得综合能源微网聚合体中各成员间进行点对点交易,建立了共享储能运营商与综合能源微网聚合体混合博弈优化模型,并基于纳什谈判理论,将综合能源微网间合作博弈转化为聚合体效益最大化与合作收益分配2个子问题,使得合作收益能够在各成员中得到合理分配。然后,采用二分法与交互式乘子法相结合的方法对所构造的多目标优化问题进行求解。算例仿真结果表明,所提交易策略有效提升了综合能源微网聚合体的整体效益,并降低了对共享储能运营商的依赖,验证了所提策略的可行性与有效性。

混合能源直流微电网能源优化管控策略研究

混合能源直流微电网在快速跟踪负载方面具有较大优势,弥补了固体氧化物燃料电池(solidoxidefuelcell,SOFC)直流微电网功率跟踪缓慢的问题。现有能源管控策略重点关注能源分配,对系统效率、运行安全性和燃料亏空方面缺乏相关研究和成熟策略。为此,提出了一种混合能源直流微型电网能源优化管控策略。首先,搭建了混合SOFC直流微电网模型。其次,采用最优操作点(optimal operating points,OOPs)实现最大效率,然后采用平均电流控制模式保证稳定的电力供应。最后,设计了基于SOFC电流的时滞控制算法来避免燃料亏空。实验结果表明,所提出的能源优化管控策略具有时间响应迅速、输出效率高和热特性良好等优势。

基于子网优先级驱动的交直流混合微网集群双向互联变流器分散式控制策略

随着可再生能源渗透率的不断提高,交直流混合微电网集群逐渐成为新型电力系统的弹性解决方案。考虑到实际运行中各子电网优先级和电能质量需求存在差异,该文提出一种基于子网优先级驱动的交直流混合微网集群双向互联变流器分散式控制策略,以实现系统的弹性功率交互。首先,通过将归一化的交流频率和直流电压值作为子电网的状态偏差因子,以最小化全局总偏差因子为目标构建了用于交直流混合微电网集群的最优电力交换模型,该模型充分考虑了子电网的优先级指数和供电容量;其次,基于最优电力交换目标,提出用于双向互联变流器的准下垂控制策略,由于该策略中双向互联变流器仅需检测本地交流频率/直流电压的状态偏差因子,因此可以实现对交直流混合微电网集群整体偏差因子最小化的分散式最优功率自主协同控制;最后,构造了两个仿真实例,并利用半实物仿真系统验证了所提策略的有效性。

计及多重差异的交直流混合多能微网多时间尺度优化调度

近年来,可再生能源发电、热电联产、储能和电力电子变压器(PET)等技术发展迅速,有利于构建多能互补、清洁高效的交直流混合多能微网(MEMG),但不成熟的PET模型和复杂的不确定性为系统的优化调度带来了挑战。为此,首先构建了一种基于三级式PET的交直流混合MEMG结构,建立了包括PET在内的设备模型和不确定性模型;其次,提出了计及多重差异的MEMG多时间尺度优化调度策略,明确了日前-日内-实时三时间尺度调度的协调机制,其中,多重差异包含需求响应资源、系统调度目标和源荷预测精度在时间尺度上的差异,以及不同能量的响应特性差异;再次,建立了对应的多时间尺度优化调度模型,包括日前鲁棒机会约束优化模型、日内随机优化模型和实时分层滚动修正模型,并在日前调度中,改进了传统储能和电热耦合设备的备用模型,设计了基于PET的交直流系统备用共享机制,将调度模型转换为混合整数线性规划模型,给出了利用CPLEX求解器求解多时间尺度调度模型的步骤;最后,通过算例分析表明,所提调度策略可以通过逐级修正调度计划应对不确定性,且所设计备用方案兼具可靠性和灵活性。

Real-time Energy Management Method for Electric-hydrogen Hybrid Energy Storage Microgrids Based on DP-MPC

With the increasing presence of intermittent energy resources in microgrids,it is difficult to precisely predict the output of renewable resources and their load demand.In order to realize the economical operations of the system,an energy management method based on a model predictive control(MPC)and dynamic programming(DP)algorithm is proposed.This method can reasonably distribute the energy of the battery,fuel cell,electrolyzer and external grid,and maximize the output of the distributed power supply while ensuring the power balance and cost optimization of the system.Based on an ultra-shortterm forecast,the output power of the photovoltaic array and the demand power of the system load are predicted.The offline global optimization of traditional dynamic programming is replaced by the repeated rolling optimization in a limited period of time to obtain power values of each unit in the energy storage system.Compared with the traditional DP,MILP-MPC and the logic based real-time management method,the proposed energy management method is proved to be feasible and effective.