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.

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.

A Secure Microgrid Data Storage Strategy with Directed Acyclic Graph Consensus Mechanism

The wide application of intelligent terminals in microgrids has fueled the surge of data amount in recent years.In real-world scenarios,microgrids must store large amounts of data efficiently while also being able to withstand malicious cyberattacks.To meet the high hardware resource requirements,address the vulnerability to network attacks and poor reliability in the tradi-tional centralized data storage schemes,this paper proposes a secure storage management method for microgrid data that considers node trust and directed acyclic graph(DAG)consensus mechanism.Firstly,the microgrid data storage model is designed based on the edge computing technology.The blockchain,deployed on the edge computing server and combined with cloud storage,ensures reliable data storage in the microgrid.Secondly,a blockchain consen-sus algorithm based on directed acyclic graph data structure is then proposed to effectively improve the data storage timeliness and avoid disadvantages in traditional blockchain topology such as long chain construction time and low consensus efficiency.Finally,considering the tolerance differences among the candidate chain-building nodes to network attacks,a hash value update mechanism of blockchain header with node trust identification to ensure data storage security is proposed.Experimental results from the microgrid data storage platform show that the proposed method can achieve a private key update time of less than 5 milliseconds.When the number of blockchain nodes is less than 25,the blockchain construction takes no more than 80 mins,and the data throughput is close to 300 kbps.Compared with the traditional chain-topology-based consensus methods that do not consider node trust,the proposed method has higher efficiency in data storage and better resistance to network attacks.

Distributed Cooperative Control of Battery Energy Storage Systems in DC Microgrids

The control of battery energy storage systems(BESSs)plays an important role in the management of microgrids.In this paper,the problem of balancing the state-ofcharge(SoC)of the networked battery units in a BESS while meeting the total charging/discharging power requirement is formulated and solved as a distributed control problem.Conditions on the communication topology among the battery units are established under which a control law is designed for each battery unit to solve the control problem based on distributed average reference power estimators and distributed average unit state estimators.Two types of estimators are proposed.One achieves asymptotic estimation and the other achieves finite time estimation.We show that,under the proposed control laws,SoC balancing of all battery units is achieved and the total charging/discharging power of the BESS tracks the desired power.A simulation example is shown to verify the theoretical results.

Optimal configuration for photovoltaic storage system capacity in 5G base station microgrids

Base station operators deploy a large number of distributed photovoltaics to solve the problems of high energy consumption and high electricity costs of 5G base stations.In this study,the idle space of the base station’s energy storage is used to stabilize the photovoltaic output,and a photovoltaic storage system microgrid of a 5G base station is constructed.Aiming at the capacity planning problem of photovoltaic storage systems,a two-layer optimal configuration method is proposed.The inner layer optimization considers the energy sharing among the base station microgrids,combines the communication characteristics of the 5G base station and the backup power demand of the energy storage battery,and determines an economic scheduling strategy for each photovoltaic storage system with the goal of minimizing the daily operation cost of the base station microgrid.The outer model aims to minimize the annual average comprehensive revenue of the 5G base station microgrid,while considering peak clipping and valley filling,to optimize the photovoltaic storage system capacity.The CPLEX solver and a genetic algorithm were used to solve the two-layer models.Considering the construction of the 5G base station in a certain area as an example,the results showed that the proposed model can not only reduce the cost of the 5G base station operators,but also reduce the peak load of the power grid and promote the local digestion of photovoltaic power.

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.

Dynamic Economic Dispatch for Microgrids Including Battery Energy Storage

Microgrids integrate distributed renewable energy resources, controllable loads and energy storage in a more economic and reliable fashion. Battery energy storage units are essential for microgrid operation, which make microgird become a strong coupling system in the time domain. Hence, the traditional methods of static dispatch are no longer suitable for microgrids. This paper proposes a dynamic economic dispatch method for microgrids. Considering microgrid as a discrete time system, the dynamic economic dispatch is to find the optimal control strategy for the system in finite time period. Based on this idea, the dynamic economic dispatch model for microgrids is established, and then the corresponding dynamic programming algorithm is designed. Finally, an example of microgrid is given, and the dynamic economic dispatch results are compared with that of the static dispatch. The comparison confirms the effectiveness of the proposed dynamic dispatch method.

Microgrid Design Including Fuzzy Logic Controlled Storage System

Smart grid design and structures are somehow depending on the way of designing and operating Microgrids. In this research a unique design of microgrid is proposed as in medium tension isolated power distribution system contains diesel generation unit and photovoltaic generation. Storage system is a part of the control strategy to reduce the diesel usage and to maintain the balance between generation and demand which might be disturbed due to the presence of PV system. Fuzzy logic control scheme has been chosen compared with conventional controller to be the main controller for both the diesel unit and storage system. Promising result has been found by digital simulation using Matlab Simulink proving the possibility of reducing the dependency on fossil fueled generators and increase the utilization of renewable energy.

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.

A novel coordinated control strategy considering power smoothing for a hybrid photovoltaic/battery energy storage system

This work presents a novel coordinated control strategy of a hybrid photovoltaic/battery energy storage(PV/BES) system. Different controller operation modes are simulated considering normal, high fluctuation and emergency conditions. When the system is grid-connected, BES regulates the fluctuated power output which ensures smooth net injected power from the PV/BES system. In islanded operation, BES system is transferred to single master operation during which the frequency and voltage of the islanded microgrid are regulated at the desired level. PSCAD/EMTDC simulation validates the proposed method and obtained favorable results on power set-point tracking strategies with very small deviations of net output power compared to the power set-point. The state-of-charge regulation scheme also very effective with SOC has been regulated between 32% and 79% range.

Research on Multi-Objective Optimization Model of Industrial Microgrid Considering Demand Response Technology and User Satisfaction

In the process of wind power,coal power,and energy storage equipment participating in the operation of industrial microgrids,the stable operation of wind-storage industrial microgrids is guaranteed by considering demand response technology and user satisfaction.This paper firstly sorts out the status quo of microgrid operation optimization,and determines themain requirements for user satisfaction considering three types of load characteristics,demand response technology,power consumption benefit loss,user balance power purchase price and wind power consumption evaluation indicators in the system.Secondly,the operation architecture of the windstorage industrialmicrogrid is designed,and themulti-objective optimizationmodel of the wind-storage industrial microgrid is established with the comprehensive operating cost and user satisfaction as the target variables,and the corresponding solution method is mentioned.Finally,a typical wind-storage industrial microgrid is selected for simulation analysis,and the results showthat,(1)Considering the demand response technology,the comprehensive operating cost of the wind-storage industrial microgrid per day is 5292.63 yuan,the user satisfaction index is 0.953,and the wind power consumption rate reaches 100%.(2)By setting four scenarios,it highlights that the grid-connected operation mode is superior to the off-grid operation mode.Considering the demand response technology,the load curve can be optimized,and the time-of-use electricity price can be fully used to coordinate the operation of each unit,which enhances the wind power consumption capacity.The compromise solution of the system comprehensive operating cost and user satisfaction under the confidence level of 0.95 is obtained,namely(5343.22,0.94).(3)The frontier curve shows that in the process of model solving,it is impossible to optimize any sub-objective by changing the control variables,which proves that there is a close relationship between the comprehensive operating cost of the system and the confidence level,which can provide effective guidance for the optimal operation of industrial microgrids.

Optimal Design of Grid-Connected Microgrid System for Cold Chain Logistics Centre in China

The growing interest in energy conservation has inspired companies to seek alternatives to highly polluting fuel electricity generation. This study designed an optimised solar wind power generation system to fulfil the energy requirement of a cold chain logistics centre. This study first conducted a thorough analysis of the clarity indicators and daily temperature positions of the cold chain logistics centre, determined the average daily electricity demand, and proposed an effective design scheme. The energy simulation software, RETScreen 8.0, was used to determine the scale of solar photovoltaic and wind power projects that meet the expected energy needs of the cold chain logistics centre. The results indicated that the estimated annual total energy demand was 833689.2 kWh. The annual power generation of 6 kW from solar photovoltaic projects and 150 kW from wind power projects was found to be enough to meet the expected electricity demand. Solar photovoltaic power generation and wind power generation account for 2.44% and 97.56%, respectively. The hybrid energy system achieved a 96.6% reduction in carbon emissions and provides a reasonable payback period of 6.1 years and an electricity generation of 904368.674 kWh per year. The feasibility of the project and the calculated period of investment return are very reasonable. Therefore, this hybrid renewable energy system provides reliable power by combining energy sources.

考虑移动氢能存储的港口多能微网两阶段分布鲁棒优化调度

为有效应对海上风电固有的间歇及波动性给港口多能微网带来的不确定性风险,提出一种考虑移动氢能存储的港口多能微网两阶段分布鲁棒优化调度模型。首先,结合Wasserstein距离实现风电出力概率分布模糊集的精确刻画,并通过非参数核密度估计拟合海上风电预测误差概率分布,获得不同置信水平下风电出力区间及场景。其次,分析氢能船舶、汽车等移动氢能存储资源对间歇性风电出力的能源存储潜力,并结合用能心理、交通属性差异,将两者分别建模为激励型、价格型需求响应,实现港口移动氢能存储灵活性资源的高效聚合。再次,针对含移动氢能存储的港口多能微网,构建基于概率分布模糊集的日前-日内两阶段分布鲁棒优化调度模型,并运用线性决策规则与强对偶理论将其转换为混合整数线性规划模型求解。最后,基于海上风电实测数据进行仿真验证。结果证明,移动氢能存储可显著提升港口多能微网的低碳灵活性,所提模型在兼顾港口多能微网经济性的同时,可进一步保证风电不确定性风险下的鲁棒性。

考虑保供电需求的光储微电网优化配置及电能质量评估

针对用户日益迫切的保供电需求以及光伏出力与负荷用电的随机性、波动性引发的电能质量的问题,建立了考虑保供电需求的光储微电网双层优化模型,并对规划配置的微电网电能质量进行评估。该模型以等效净负荷标准差和弃光率最小为上层优化目标,以微电网有功功率损耗最小为下层优化目标,以储能满足保供电负荷的保供电需求作为附加约束条件,采用遗传算法求解。然后设计源、网、荷三类指标,采用组合赋权法确定各指标权重,实现对微电网电能质量的综合评估。最后以改进的IEEE-33系统验证了所提模型的有效性。结果表明考虑保供电需求后能够提高微电网电能质量,并在一定范围内保供电负荷越大时越能提高微电网电能质量和用户满意度。

计及分布式储能的微电网群经济调度

为提高微电网群调度效率、减少微电网运行成本,首先构建了计及分布式储能的微电网群优化调度模型。该模型以包含风、光、储的3个子微网和网侧储能所构成的交流微电网作为调度对象。在满足功率平衡等约束条件下,对负荷侧储能充放电次数和单位时间内充放电功率进行限制;在考虑主网分时电价、系统发电成本,网侧储能放电成本条件下,采用遗传算法进行求解,得到计及分布式储能的微电网群经济调度方案,最终得到优化后的经济成本。算例计算结果表明,该运行调度模型可有效提高微电网群经济效益,从而验证了该模型的有效性。

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.

含共享储能的数据中心微网群分布式优化调度

多个数据中心微网可联合成微网群以实现不同数据中心微网的资源联动和能量互补。首先,建立了含共享储能的数据中心微网群运行模型,考虑了不同数据中心微网间的功率交互、数据负载交互、碳配额交互及共享储能容量使用权分配等耦合约束。其次,提出了考虑时变容量使用权和旋转备用服务的共享储能容量分配与运行策略,以进一步提高共享储能的效能。然后,采用高斯混合模型对数据中心微网内可再生发电的预测误差概率分布进行精确拟合,并结合机会约束处理预测误差的不确定性。最后,通过交替方向乘子法实现各个数据中心微网的独立求解,并引入动态乘子更新策略和预测-矫正因子以提高算法的收敛性。所提模型与方法的有效性在仿真中得到验证。

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。

基于模糊神经网络的微电网荷储协调智能控制方法

针对传统比例-积分-微分(proportional integral derivative,PID)控制和模型论控制方法难以应对新型电力系统背景下微电网面临的运行场景复杂多变的问题,提出了基于模糊神经网络的微电网荷储协调智能控制方法。首先确定了微电网模糊控制输入及输出变量,以平抑净负荷波动及减少储能充放电频次为目的,将微电网控制经验总结成模糊规则表,采用神经网络深度学习算法修正模糊控制模型的隶属度函数中心、宽度和输出权重来提高模型的自适应能力,从而制定了可调控负荷和储能的功率控制系数;进而针对模糊神经网络控制输出的负荷调控需求量在各可调控负荷间分配的问题,提出了基于灵活性供给指标排序的负荷调控优先级选择方法,最终完成了微电网系统储能单元和可调控负荷控制策略的制定。某典型微电网系统算例仿真结果表明,所提方法制定的各可调控负荷与储能控制策略能在避免储能频繁和过度充放电的同时,在并网状态下有效减弱并网功率对上级电网造成的随机扰动,在孤岛状态下能够有效平抑系统功率波动,提升系统运行稳定性。

基于IGDT的含广义储能的独立直流微网日前优化调度

微电网的能量管理与优化调度作为构建新型电力系统的重要环节,提高其可再生能源的消纳水平、降低源荷不确定性风险以及优化系统运行成本具有重要意义。因此,文中提出一种基于信息间隙决策理论(information gap decision theory,IGDT)的含广义储能的独立直流微电网日前优化调度模型。首先,构建含超级电容的混合储能系统,以降低蓄电池运行成本,将具备虚拟储能特性的柔性负荷与混合储能相结合,形成广义储能,充分发挥微电网系统内灵活性资源特性;其次,考虑系统风光荷不确定性,引入IGDT模型,在确定性模型基础上建立风险规避策略下的鲁棒模型和风险投机策略下的机会模型,从2种决策角度追求降低风险与最大化收益;最后,基于算例仿真分析,证明该调度策略在降低微电网运行成本的基础上可量化不确定性因素对系统调度决策的影响,验证了模型的有效性和可参考性。