Multi-Time Scale Optimal Scheduling of a Photovoltaic Energy Storage Building System Based on Model Predictive Control

Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance.

Intelligent Fractional-Order Controller for SMES Systems in Renewable Energy-Based Microgrid

An autonomous microgrid that runs on renewable energy sources is presented in this article.It has a supercon-ducting magnetic energy storage(SMES)device,wind energy-producing devices,and an energy storage battery.However,because such microgrids are nonlinear and the energy they create varies with time,controlling and managing the energy inside them is a difficult issue.Fractional-order proportional integral(FOPI)controller is recommended for the current research to enhance a standalone microgrid’s energy management and performance.The suggested dedicated control for the SMES comprises two loops:the outer loop,which uses the FOPI to regulate the DC-link voltage,and the inner loop,responsible for regulating the SMES current,is constructed using the intelligent FOPI(iFOPI).The FOPI+iFOPI parameters are best developed using the dandelion optimizer(DO)approach to achieve the optimum performance.The suggested FOPI+iFOPI controller’s performance is contrasted with a conventional PI controller for variations in wind speed and microgrid load.The optimal FOPI+iFOPI controller manages the voltage and frequency of the load.The behavior of the microgrid as a reaction to step changes in load and wind speed was measured using the proposed controller.MATLAB simulations were used to evaluate the recommended system’s performance.The results of the simulations showed that throughout all interruptions,the recommended microgrid provided the load with AC power with a constant amplitude and frequency.In addition,the required load demand was accurately reduced.Furthermore,the microgrid functioned incredibly well despite SMES and varying wind speeds.Results obtained under identical conditions were compared with and without the best FOPI+iFOPI controller.When utilizing the optimal FOPI+iFOPI controller with SMES,it was found that the microgrid performed better than the microgrid without SMES.

Multi-timescale robust dispatching for coordinated automatic generation control and energy storage

The increasing penetration of renewable energy into power grids is reducing the regulation capacity of automatic generation control(AGC).Thus,there is an urgent demand to coordinate AGC units with active equipment such as energy storage.Current dispatch decision-making methods often ignore the intermittent effects of renewable energy.This paper proposes a two-stage robust optimization model in which energy storage is used to compensate for the intermittency of renewable energy for the dispatch of AGC units.This model exploits the rapid adjustment capability of energy storage to compensate for the slow response speed of AGC units,improve the adjustment potential,and respond to the problems of intermittent power generation from renewable energy.A column and constraint generation algorithm is used to solve the model.In an example analysis,the proposed model was more robust than a model that did not consider energy storage at eliminating the effects of intermittency while offering clear improvements in economy and efficiency.

考虑时变线阻的多储能SOC稳定均衡控制策略

在直流微电网中,由于线路阻抗大小差异的复杂化,难以保证各储能单元之间达到荷电状态(state-of-charge,SOC)均衡。为此,提出一种考虑时变线阻的SOC均衡改进控制策略。首先,通过线路阻抗和SOC幂指数构造的平衡因子来修正控制系数,提高SOC的辨识度。同时,利用输出电流来约束平衡因子,提高系统的抗扰能力。在SOC均衡之后,SOC平衡因子G变为1,此时依赖线路阻抗信息但不受线路阻抗变化影响,可平稳地保持电流分配。并且结合输出电流构造的电压补偿环节有效地解决了母线电压质量和SOC均衡控制效果之间的矛盾。其次,针对基于SOC均衡的改进控制策略易受恒功率负载影响的问题,利用混合势函数理论进行建模,得到稳定性判据,有利于保障系统的稳定运行。最后,仿真结果表明,所提出的改进下垂控制能够有效地消除线路阻抗的影响,提高电流分配精度,实现SOC均衡,并验证了在各种突发扰动及极端情况下所提控制策略的有效性和正确性。

基于二阶一致性算法的电池储能系统SOC均衡及功率分配策略

为延长电池储能系统的整体寿命,需保持储能系统中各单元的荷电状态(state of charge,SOC)均衡。为此,提出一种基于二阶一致性算法的改进下垂控制策略,通过指数函数嵌套变化系数,实现不同容量储能单元快速SOC均衡。在SOC均衡的基础上设计二次控制策略,在一定通信时延下实现频率、电压恢复和有功、无功功率合理分配。最后,以4台储能单元组成的电池储能系统为算例进行仿真,验证了所提控制策略的有效性,SOC能够快速收敛达到均衡状态,频率、电压能够恢复到额定值,有功、无功功率能够按照相应下垂系数比例进行分配。

Wind Power Flow Optimization and Control System Based on Rapid Energy Storage

风电功率的间歇与波动致使电场容量可信度低、可调度性差；同时易引起局部电网的电压不稳、频率波动，影响了系统的电能质量及稳定性。针对此现象，将超级电容器与蓄电池组成快速储能装置，用于风电的潮流优化控制。采用三重双向直流变换电路控制储能元件间的功率流动；采用四象限交直流变换电路控制储能与电网间的能量交换。提出基于超级电容器电压低频波动抑制的功率分配方法，可显著减少蓄电池的充放次数；提出基于储能元件荷电状态的储能能量调整规则，可避免储能元件的过充和频繁深度放电，以优化其功率调节能力。实验结果表明，系统可实现2种储能元件的优势互补，能有效平滑调节风电注入电网的有功功率，并实时补偿控制风电接入点的无功功率。

考虑SOC优化设定的电-氢混合储能系统的运行优化

针对含电-氢混合储能的源网荷储系统,为提高新能源的消纳水平并降低系统运行成本,提出了考虑SOC优化设定的电-氢混合储能系统的运行优化方法,实现系统的日前-实时优化调度。首先提出了大容量储能系统SOC优化设定的方法,以确定储能系统日前的始末SOC优化设定值。随后,基于双延迟深度确定性策略梯度算法,提出了一种日前-实时优化调度模型训练方法。结合储能SOC的优化设定值和日前运行数据,建立了源-网-荷-储系统的实时优化调度模型,实现日前和实时综合优化调度。最后,通过算例分析验证了所提运行优化方法的有效性。结果表明,大容量储能系统的SOC优化设定方法可以有效提高系统收益,日前-实时优化调度模型则在日前优化调度的基础上减少了预测误差带来的影响。

LSTM-EKF算法实现储能集装箱电芯SOC的优化估计

储能集装箱是锂电池储能电站的核心设备,每个集装箱由数千只电芯串并联构成。因此,对集装箱电芯锂电池荷电状态(state of charge,SOC)的准确估计成为表征储能电站运行最核心最基础的参数,并且为辅助新能源高效并网,储能系统的工作状态也会相应地呈现随机性、波动性和不确定性,这对电芯状态估计的准确度提出了更高的要求。为此,首先基于基尔霍夫定律建立Thevenin电池模型,根据安时积分法列出系统的状态和观测方程,并且将其状态和观测方程作为扩展卡尔曼滤波(extended Kalman filtering,EKF)算法的研究对象。然后利用EKF算法对估计值电池SOC更新迭代,再将EKF算法中得到的卡尔曼矩阵和状态变量更新误差值以及UDDS工况下的电池数据,作为长短期记忆(long short-term memory,LSTM)神经网络算法的训练数据集,由此完成LSTM-EKF联合算法,实现对储能集装箱电芯SOC的优化估计。该文所提LSTM-EKF算法可将电芯SOC的误差值降低到1%以下。最后对优化算法在储能电站安全运行与监控平台中的应用情况进行介绍。

基于储能SOC的源网荷微网功率调控设计研究

为提高微网中微元的消纳能力和降低传统储能配备成本,设计了一种等效储能装置,其与传统储能蓄电池和超级电容组合成三能源混合储能。为合理地响应微电网内功率需求,提出了一种基于传统储能SOC(荷电状态)的三能源混合储能输出功率的模糊控制策略,同时对超级电容SOC进行优化研究。仿真表明,采用本设计的等效储能装置和模糊控制器有利于实现系统内有功平衡,改善了系统频率稳定性。

基于改进SOC幂指数下垂控制的混合储能能量均衡策略

为了抑制微电网电压波动、消纳不平衡功率,针对直流微电网中的锂电池和超级电容混合储能系统,提出一种改进SOC幂指数的下垂控制能量管理方法。该方法不仅改进了传统下垂控制电流均衡度差和会导致电压偏差的缺点,还采用阻抗在线检测法量化线路电阻值,消除了其对储能输出电流均衡度的影响,并通过二次控制对下垂控制所引起的直流母线电压偏移进行补偿。基于Matlab/Simulink仿真平台搭建了光储直流微电网仿真系统模型,检验了所搭直流微电网的电压稳定效果,并验证了改进SOC幂指数下垂控制方法相对于传统下垂控制方法的优越性。

基于FSBB变换器的直流微电网SOC平衡控制策略

针对直流微电网工作时易出现储能单元SOC不平衡的现象,提出一种基于四开关BuckBoost(FSBB)变换器的直流微电网SOC平衡控制策略。使用四开关Buck-Boost变换器替换双向DC/DC变换器与蓄电池相联,既保证功率可以双向流通,又提高储能单元动态响应能力和抗干扰能力;设计了一种基于储能单元SOC平衡的改进下垂控制策略,将蓄电池SOC函数与下垂系数相结合,使各储能单元在充放电过程中按SOC值分配输出电流,实现储能单元SOC平衡和单元间电流合理分配;同时负载跳变时保持母线电压稳定,实现不同模式的平滑切换与功率分配,且无需互联通信,降低系统设计成本。在MATLAB/Simulink中搭建仿真模型,验证了所提控制策略的正确性和可行性。

风电波动平抑下考虑SOC均衡及收益的电池储能功率分配策略

针对电池储能(battery energy storage system,BESS)平抑风电波动过程中电池单元荷电状态(state of charge,SOC)均衡性较差且未考虑风储净收益的问题,提出了风电波动平抑下考虑SOC均衡及收益的BESS功率分配策略。首先,建立综合考虑售电收益、弃风惩罚、缺电惩罚及BESS运行成本等多个因素的风电并网指令优化模型,以并网指令波动率、电池组SOC标准差等多个因素为约束条件,提出改进算术优化算法(improved arithmetic optimization algorithm,IAOA)求解该优化模型。然后,将BESS划分为两个电池组,设计了BESS双层功率分配方法(double-layer power allocation method,DPAM),上层将BESS充放电指令分配给两个电池组,下层根据最大充放电功率原则或新型SOC均衡原则将电池组充放电指令分配给各自的电池单元。最后,通过仿真对所提策略进行了验证。仿真结果表明:IAOA加快了寻优速度,提高了寻优精度;DPAM提升了电池组内电池单元SOC的均衡速度,改善了均衡程度;提出的功率分配策略进一步降低了风电并网波动率,同时提高了风储系统净收益。

孤岛微电网不同尺寸DESUs的SoC均衡方案

为实现孤岛微电网中不同尺寸(容量和电压)分布式储能单元(Distributed Energy Storage Units,DESUs)的荷电状态(State of Charge,SoC)均衡,提出一种基于P-ω下垂控制的改进型控制方案,在无需中央控制器和通信的前提下实现不同尺寸DESUs的SoC均衡,延长DESUs的使用寿命。在分析传统下垂控制原理和SoC的基础上,阐明所提方案实现不同尺寸DESUs的SoC均衡机理。仿真和实验结果说明:所提方案能够消除尺寸参数差异对SoC均衡的影响,通过SoC均衡因子的调节实现不同负荷下不同尺寸DESUs的SoC均衡。

广域分布式储能系统分层控制和SOC均衡控制研究

为了实现广域范围内分布式储能的统一灵活调控,本文研究基于储能云端控制器架构的分布式储能分层分区控制策略。中间层“分布式储能节点控制器”是核心环节,其接收上层云端调度信息实现对下层储能模块SOC的均衡控制,以解决储能电池过度充/过放电问题,从而提高蓄电池储能系统及电网运行可靠性。在传统均衡控制基础上,本文首先改进了一种荷电均衡控制方法,利用SOC差值修正中间层控制系数最可提高荷电均衡速度;为进一步提高荷电均衡速度和防止储能模块功率越限,本文提出了一种基于SOC差值的反正切函数均衡控制策略。最后,通过仿真验证了所提控制方法的正确性和可行性。

基于SOC均衡的分布式电池储能系统协同控制策略

研究分布式电池储能系统的优化控制方法以及电池荷电状态(SOC)均衡策略,提出基于SOC均衡的协同控制策略。利用多智能体系统(MAS)理论,实现电池储能系统的协同控制,并采用多智能体分布式算法,实现功率指令的自适应分配,进而实现SOC动态均衡。针对传统多智能体算法收敛速度较慢的问题,提出一种基于模型预测控制(MPC)的分布式算法,利用MPC对传统多智能体算法进行优化,提高收敛速度。最后利用实际储能功率数据进行仿真,验证了所提策略的有效性和算法在收敛速度上的优势。

考虑SOC均衡的直流微网储能系统控制策略研究

在直流微电网中分布式储能系统起着稳定母线电压、维持系统功率平衡的关键作用。针对多个储能单元中荷电状态(SOC)不同会造成过充或者过放,从而影响系统稳定性的问题,提出一种改进SOC均衡下垂控制策略。首先,将储能装置的下垂系数与SOC嵌套反正切函数联系,充分利用反正切函数和幂函数的优点。其次引入变加速因子,在SOC差异较小时进一步加快均衡速度。同时,为了解决均衡过程中引起的母线电压偏差问题,在上述改进控制策略基础上增加二次电压补偿环节,使用一致性电压均衡器减少母线电压的波动。最后搭建了直流微网储能系统的仿真模型。仿真结果验证了所提控制策略可以动态实现SOC快速均衡,并有效维持了微网内功率平衡和母线电压稳定。

考虑SOC均衡的储能电站一次调频协同控制方法

针对多个储能电站参与一次调频的稳定运行问题,提出一种考虑荷电状态(SOC)均衡需求的储能电站协同调频控制策略。首先,建立含多个储能电站的区域电网调频控制模型,并分析储能电站参与一次调频的基本控制规律。其次,根据系统调频动作区和死区内的净功率变化,对不同工作阶段区间调频功率与SOC均衡功率的互补耦合特性进行分析,论证储能SOC均衡控制与调频需求协同响应的可行性,在此基础上设计储能的协同调频控制策略,并给出关键控制参数的设计方法。本文方法在改善分布式储能电站调频效果的同时,减小了储能电站SOC越限风险,使得其频率支撑能力更加稳定。最后,搭建典型区域电网模型,结合不同频率波动工况进行仿真验证,结果表明所提控制策略可以有效改善频率质量,在不增加系统调频负担的前提下实现多个储能电站的荷电状态均衡。

Model Predictive Control Strategy for Residential Battery Energy Storage System in Volatile Electricity Market with Uncertain Daily Cycling Load

This paper presents a control strategy for residential battery energy storage systems,which is aware of volatile electricity markets and uncertain daily cycling loads.The economic benefits of energy trading for prosumers are achieved through a novel modification of a conventional model predictive control(MPC).The proposed control strategy guarantees an optimal global solution for the applied control action.A new cost function is introduced to model the effects of volatility on customer benefits more effectively.Specifically,the newly presented cost function models a probabilistic relation between the power exchanged with the grid,the net load,and the electricity market.The probabilistic calculation of the cost function shows the dependence on the mathematical expectation of market price and net load.Computational techniques for calculating this value are presented.The proposed strategy differs from the stochastic and robust MPC in that the cost is calculated across the market price and net load variations rather than across model constraints and parameter variations.

过载储能系统SoC快速均衡控制与分布式功率分配策略

储能系统过载时,保证荷电状态(state of charge, SoC)均衡并提升其调节不平衡功率的能力是目前亟待解决的问题。为提高过载储能系统的能量利用率,提出了基于SoC快速一致的功率分配策略与离散时间分布式控制方法。首先,利用分布式算法使其他储能电池跟踪到不平衡功率的平均值;然后,给出各储能电池的输出功率或输入功率的表达式,设计基于周期时变控制和多采样率控制的分布式平均一致算法,并给出平均一致算法的最优收敛率。理论分析表明,所提功率分配方案能够实现SoC快速一致,与已有功率分配方案相比,所提方法提升了储能系统对电网不平衡功率的调节能力。最后,通过仿真实验验证了所提方法的有效性。