A Two-Layer Fuzzy Control Strategy for the Participation of Energy Storage Battery Systems in Grid Frequency Regulation

To address the frequency fluctuation problem caused by the power dynamic imbalance between the power system and the loadwhen a large number of newenergy sources are connected to the grid,a two-layer fuzzy control strategy is proposed for the participation of the energy storage battery system in FM.Firstly,considering the coordination of FM units responding to automatic power generation control commands,a comprehensive allocation strategy of two signals under automatic power generation control commands is proposed to give full play to the advantages of two FM signals while enabling better coordination of two FM units responding to FM commands;secondly,based on the grid FM demand and battery FM capability,a double-layer fuzzy control strategy is proposed for FM units responding to automatic power generation control commands in a coordinated manner under dual-signal allocation mode to precisely allocate the power output depth of FM units,which can control the fluctuation of frequency deviation within a smaller range at a faster speed while maintaining the battery charge state;finally,the proposed Finally,the proposed control strategy is simulated and verified inMatlab/Simulink.The results show that the proposed control strategy can control the frequency deviation within a smaller range in a shorter time,better stabilize the fluctuation of the battery charge level,and improve the utilization of the FM unit.

Distributed Power Control for Energy Conservation in Hybrid Cellular Network with Device-to-Device Communication

Device-to-Device(D2D) communication has been proposed as a promising implementation of green communication to benefit the existed cellular network.In order to limit cross-tier interference while explore the gain of short-range communication,we devise a series of distributed power control(DPC) schemes for energy conservation(EC)and enhancement of radio resource utilization in the hybrid system.Firstly,a constrained opportunistic power control model is built up to take advantage of the interference avoidance methodology in the presence of service requirement and power constraint.Then,biasing scheme and admission control are added to evade ineffective power consumption and maintain the feasibility of the system.Upon feasibility,a non-cooperative game is further formulated to exploit the profit in EC with minor influence on spectral efficiency(SE).The convergence of the DPC schemes is validated and their performance is confirmed via simulation results.

Distributed generator-based distribution system service restoration strategy and model-free control methods

The rapid growth of distributed generator(DG)capacities has introduced additional controllable assets to improve the performance of distribution systems in terms of service restoration.Renewable DGs are of particular interest to utility companies,but the stochastic nature of intermittent renewable DGs could have a negative impact on the electric grid if they are not properly handled.In this study,we investigate distribution system service restoration using DGs as the primary power source,and we develop an effective approach to handle the uncertainty of renewable DGs under extreme conditions.The distribution system service restoration problem can be described as a mixed-integer second-order cone programming model by modifying the radial topology constraints and power flow equations.The uncertainty of renewable DGs will be modeled using a chance-constrained approach.Furthermore,the forecast errors and noises in real-time operation are solved using a novel model-free control algorithm that can automatically track the trajectory of real-time DG output.The proposed service restoration strategy and model-free control algorithm are validated using an IEEE 123-bus test system.

Distributed energy storage node controller and control strategy based on energy storage cloud platform architecture

Based on the energy storage cloud platform architecture,this study considers the extensive configuration of energy storage devices and the future large-scale application of electric vehicles at the customer side to build a new mode of smart power consumption with a flexible interaction,smooth the peak/valley difference of the load side power,and improve energy efficiency.A plug and play device for customer-side energy storage and an internet-based energy storage cloud platform are developed herein to build a new intelligent power consumption mode with a flexible interaction suitable for ordinary customers.Based on the load perception of the power grid,this study aims to investigate the operating state and service life of distributed energy storage devices.By selecting an integrated optimal control scheme,this study designs a kind of energy optimization and deployment strategy for stratified partition to reduce the operating cost of the energy storage device on the client side.The effectiveness of the system and the control strategy is verified through the Suzhou client-side distributed energy storage demonstration project.

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.

A PI+R Control Scheme Based on Multi-Agent Systems for Economic Dispatch in Isolated BESSs

Battery energy storage systems(BESSs)are widely used in smart grids.However,power consumed by inner impedance and the capacity degradation of each battery unit become particularly severe,which has resulted in an increase in operating costs.The general economic dispatch(ED)algorithm based on marginal cost(MC)consensus is usually a proportional(P)controller,which encounters the defects of slow convergence speed and low control accuracy.In order to solve the distributed ED problem of the isolated BESS network with excellent dynamic and steady-state performance,we attempt to design a proportional integral(PI)controller with a reset mechanism(PI+R)to asymptotically promote MC consensus and total power mismatch towards 0 in this paper.To be frank,the integral term in the PI controller is reset to 0 at an appropriate time when the proportional term undergoes a zero crossing,which accelerates convergence,improves control accuracy,and avoids overshoot.The eigenvalues of the system under a PI+R controller is well analyzed,ensuring the regularity of the system and enabling the reset mechanism.To ensure supply and demand balance within the isolated BESSs,a centralized reset mechanism is introduced,so that the controller is distributed in a flow set and centralized in a jump set.To cope with Zeno behavior and input delay,a dwell time that the system resides in a flow set is given.Based on this,the system with input delays can be reduced to a time-delay free system.Considering the capacity limitation of the battery,a modified MC scheme with PI+R controller is designed.The correctness of the designed scheme is verified through relevant simulations.

Data-driven Predictive Voltage Control for Distributed Energy Storage in Active Distribution Networks

Integration of distributed energy storage(DES)is beneficial for mitigating voltage fluctuations in highly distributed generator(DG)-penetrated active distribution networks(ADNs).Based on an accurate physical model of ADN,conventional model-based methods can realize optimal control of DES.However,absence of network parameters and complex operational states of ADN poses challenges to model-based methods.This paper proposes a data-driven predictive voltage control method for DES.First,considering time-series constraints,a data-driven predictive control model is formulated for DES by using measurement data.Then,a data-driven coordination method is proposed for DES and DGs in each area.Through boundary information interaction,voltage mitigation effects can be improved by interarea coordination control.Finally,control performance is tested on a modified IEEE 33-node test case.Case studies demonstrate that by fully utilizing multi-source data,the proposed predictive control method can effectively regulate DES and DGs to mitigate voltage violations.

State-of-charge Balance Control and Safe Region Analysis for Distributed Energy Storage Systems with Constant Power Loads

This paper presents a fully distributed state-of-charge balance control (DSBC) strategy for a distributed energy storage system (DESS). In this framework, each energy storage unit (ESU) processes the state-of-charge (SoC) information from its neighbors locally and adjusts the virtual impedance of the droop controller in real-time to change the current sharing. It is shown that the SoC balance of all ESUs can be achieved. Due to virtual impedance, voltage deviation of the bus occurs inevitably and increases with load power. Meanwhile, widespread of the constant power load (CPL) in the power system may cause instability. To ensure reliable operation of DESS under the proposed DSBC, the concept of the safe region is put forward. Within the safe region, DESS is stable and voltage deviation is acceptable. The boundary conditions of the safe region are derived from the equivalent model of DESS, in which stability is analyzed in terms of modified Brayton-Moser's criterion. Both simulations and hardware experiments verify the accuracy of the safe region and effectiveness of the proposed DSBC strategy.

A Clustering-tree Topology Control Based on the Energy Forecast for Heterogeneous Wireless Sensor Networks

How to design an energy-efficient algorithm to maximize the network lifetime in complicated scenarios is a critical problem for heterogeneous wireless sensor networks (HWSN). In this paper, a clustering-tree topology control algorithm based on the energy forecast (CTEF) is proposed for saving energy and ensuring network load balancing, while considering the link quality, packet loss rate, etc. In CTEF, the average energy of the network is accurately predicted per round (the lifetime of the network is denoted by rounds) in terms of the difference between the ideal and actual average residual energy using central limit theorem and normal distribution mechanism, simultaneously. On this basis, cluster heads are selected by cost function (including the energy, link quality and packet loss rate) and their distance. The non-cluster heads are determined to join the cluster through the energy, distance and link quality. Furthermore, several non-cluster heads in each cluster are chosen as the relay nodes for transmitting data through multi-hop communication to decrease the load of each cluster-head and prolong the lifetime of the network. The simulation results show the efficiency of CTEF. Compared with low-energy adaptive clustering hierarchy (LEACH), energy dissipation forecast and clustering management (EDFCM) and efficient and dynamic clustering scheme (EDCS) protocols, CTEF has longer network lifetime and receives more data packets at base station. © 2014 Chinese Association of Automation.

Energy-based robust controller design for flexible spacecraft

This paper presents a class of non-model-based position controllers for a kind of flexible spacecraft. With the controllers, one can achieve not only the closed-loop stability of the original distributed parameter system, but also the asymptotic stability of the truncated system, which is obtained through representing the deflection of the appendage by an arbitrary finite number of flexible modes. The system dynamics are not explicitly involved in the controller design and stability proof. Instead, only a very basic system energy relationship of the flexible spacecraft is utilized. The controllers possess several remarkable advantages over the traditional model-based ones. Numerical simulations are carried out on a kind of spacecraft with one flexible appendage and satisfactory results are obtained.

Network security protection technology for a cloud energy storage network controller

As part of the ongoing information revolution,smart power grid technology has become a key focus area for research into power systems.Intelligent electrical appliances are now an important component of power systems,providing a smart power grid with increased control,stability,and safety.Based on the secure communication requirements of cloud energy storage systems,this paper presents the design and development of a node controller for a cloud energy storage network.The function division and system deployment processes were carried out to ensure the security of the communication network used for the cloud energy storage system.Safety protection measures were proposed according to the demands of the communication network,allowing the system to run safely and stably.Finally,the effectiveness of the system was verified through a client-side distributed energy storage demonstration project in Suzhou,China.The system was observed to operate safely and stably,demonstrating good peak-clipping and valley filling effects,and improving the system load characteristics.

Distributed Control System Retrofit for 200 MW Units of Thermal Power Plant

This paper introduces GKS-9000 Distributed Control System (DCS)developed by Nanjing Automation Research Institute (NARI) and its application in DCS retrofit project of indigenous 200 MW units and its feature.

考虑光储协调的配电网多阶段就地-分布式电压控制策略

针对高渗透率光伏并网点附近线路的电压越限问题,基于对含分布式电源配电网的功率调压原理的分析,提出了考虑光储协调的多阶段电压控制方法。采用切比雪夫多项式滤波方法改进基于一致性原理迭代的分布式控制方式,有效加快了分布式控制的收敛速度;提出了多阶段就地-分布式电压控制策略,包括光伏逆变器就地无功补偿的阶段Ⅰ调压、全网光伏逆变器分布式无功调节的阶段Ⅱ调压、全网储能一致性分布式有功调节的阶段Ⅲ调压。以改进的某实际55节点中压配电系统为算例进行仿真,验证了所提多阶段就地-分布式电压控制策略的有效性和优越性。

多轴分布式电驱动车辆电液复合制动控制研究

针对多轴分布式电机驱动车辆电液复合制动中易出现的车辆制动抖动问题,提出了一种建压阶段电机制动力修正策略和一种基于前馈-反馈的协调控制策略,分别在建压阶段和其他阶段通过协调复合制动力来解决制动抖动的问题。针对防抱死控制系统与电机制动系统共同作用时的制动矛盾,提出了一种基于PID控制的ABS控制策略,主要通过改变电机制动力来解决制动矛盾的问题。通过TruckSim、Matlab/Simulink及AMESim联合仿真验证,制动冲击度在建压阶段下降了20.66%,在电机退出阶段下降了92.59%,驾驶感觉得到明显改善。而ABS控制策略也可在保证理想滑移率的同时完成制动能量回收;结合整车制动试验,表明协调控制策略在保证制动效果良好的同时实现了制动能量回收,效果显著。

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。

基于储能有功功率与OLTC协调的配电网电压控制

高比例光伏系统接入配电网会引起电压越限,传统无功电压调整方案在高阻抗比配网中失效,利用储能系统有功功率实现电压控制的技术方案被广泛采用,但现有技术方案中的储能系统在电压控制过程中可能产生过度充放电问题。针对这些问题,提出了一种基于储能有功功率与有载调压变压器(on-loadtapchanger,OLTC)协调的配电网电压控制策略。在分析光伏接入对配电网电压影响的基础上,利用测量得到的电压数据控制储能有功功率,实现对接入节点电压水平的快速调控;同时在OLTC控制环节加入储能荷电状态参考量,利用节点电压信息与储能荷电状态共同控制OLTC分接头动作,实现对配电网整体电压水平调控的同时避免了储能系统过度充放电。最后在IEEE 13节点系统中进行仿真验证,结果表明所提策略能够解决配电网内电压越限问题,避免储能系统过度充放电,从而延长储能系统的使用寿命,实现对配电网内资源的合理利用。

高比例分布式可再生能源交直流混合配电网运行调控:科学问题与技术框架

随着分布式可再生能源发电与中低压直流组网技术的快速发展,未来配电网必然向复杂的交直流混合形态演进,其运行调控技术面临许多新的挑战。在高比例分布式可再生能源交直流混合配电网(HR-HDN)运行调控技术发展需求分析的基础上,提炼出HR-HDN运行调控技术的3个科学问题,并以多类型可控设备协同、源-网-荷-储高度互动化和市场化需求为研究主线,从稳定控制、故障主动防御与恢复、电力市场机制辅助调控以及“平台+数据”数字化集成调控4个方面,提出了HR-HDN的运行调控技术框架。最后,对HR-HDN运行调控关键技术的未来发展进行了展望。

基于分布式协同控制技术的分散式无功补偿技术方案研究

结合实际工程的应用实例从分散式无功补偿方案的提出、分布式协同吸收方案的理论、具体工程方案的设计进行简单的论述。结合线路开通后的实际运行工况,利用设置于正线的能量回馈吸收装置实现了分散式无功补偿,该方案可减少或完全取消设置于主变电所侧的SVG容量,充分开发和利用了能馈吸收装置的能力,节约了工程投资,实现了既定设计目标。

超导磁储能装置提高柔性直流配电系统稳定性的研究

柔性直流配电系统中定功率控制的换流器具有恒功率负载特性,会降低系统阻尼,对系统的稳定性产生不利影响。针对该问题,在直流配电系统中加入超导磁储能SMES(superconducting magnetic energy storage)装置来提高系统的稳定性。推导了柔性直流配电系统的反馈控制模型,采用频域分析法研究了换流器恒功率负载特性对系统稳定性的影响,并结合数学模型和频域分析,指出SMES装置能够为电网提供正阻尼,增大了系统开环传递函数在剪切频率处的相位裕度,从而改善了系统稳定性。为防止超导磁体两端电压过高,SMES装置与直流配电网连接的DC/DC换流器需具备一定的电压调节性能,因此研究了采用模块化多电平DC/DC换流器DC-MMC(modular multilevel DC/DC converter)的SMES装置,通过调节子模块个数灵活设置换流器电压变比,在实现换流器能量双向流动的同时控制超导磁体两端电压,以保护储能装置。最后通过时域仿真波形验证了采用DC-MMC的SMES装置在提高柔性直流配电系统稳定性方面的可行性和有效性。

考虑电压-无功调节的台区互联装置规划方法

伴随分布式能源广泛接入低压配电网,其对配电网运行灵活性和消纳能力的要求不断提高。利用低压柔性互联装置将独立运行的低压配电台区分区互联,避免传统电压调节和无功补偿装置频繁动作。考虑到柔性互联装置造价昂贵,协同传统电压-无功调节装置,文中提出低压柔性互联装置的选址定容规划方法。首先,分析低压柔性互联装置拓扑和运行方式,建立其潮流模型。其次,建立低压柔性互联装置优化配置的双层规划模型,上层规划以年综合费用最小为目标,下层规划考虑电压-无功协调控制时间序列模型,以运行成本和电压偏差最小为目标,基于粒子群优化算法和混合整数二阶锥规划算法交替求解,得出配电系统最优柔性互联方案和最优运行方式。最后,在IEEE 33节点系统上进行实例分析,验证该双层规划算法的有效性。结果表明,所提方法能有效减少柔性互联装置的过度布置,同时减少由分布式能源频繁波动造成的运行成本。将模型凸化并线性化的方法明显提高了求解效率。