Locally Minimum Storage Regenerating Codes in Distributed Cloud Storage Systems

In distributed cloud storage systems, inevitably there exist multiple node failures at the same time. The existing methods of regenerating codes, including minimum storage regenerating(MSR) codes and minimum bandwidth regenerating(MBR) codes, are mainly to repair one single or several failed nodes, unable to meet the repair need of distributed cloud storage systems. In this paper, we present locally minimum storage regenerating(LMSR) codes to recover multiple failed nodes at the same time. Specifically, the nodes in distributed cloud storage systems are divided into multiple local groups, and in each local group(4, 2) or(5, 3) MSR codes are constructed. Moreover, the grouping method of storage nodes and the repairing process of failed nodes in local groups are studied. Theoretical analysis shows that LMSR codes can achieve the same storage overhead as MSR codes. Furthermore, we verify by means of simulation that, compared with MSR codes, LMSR codes can reduce the repair bandwidth and disk I/O overhead effectively.

Towards Implementation of Smart Grid: An Updated Review on Electrical Energy Storage Systems

A smart grid will require, to greater or lesser degrees, advanced tools for planning and operation, broadly accepted communications platforms, smart sensors and controls, and real-time pricing. The smart grid has been described as something of an ecosystem with constantly communication, proactive, and virtually self-aware. The use of smart grid has a lot of economical and environmental advantages;however it has a downside of instability and unpredictability introduced by distributed generation (DG) from renewable energy into the public electric systems. Variable energies such as solar and wind power have a lack of stability and to avoid short-term fluctuations in power supplied to the grid, a local storage subsystem could be used to provide higher quality and stability in the fed energy. Energy storage systems (ESSs) would be a facilitator of smart grid deployment and a “small amount” of storage would have a “great impact” on the future power grid. The smart grid, with its various superior communications and control features, would make it possible to integrate the potential application of widely dispersed battery storage systems as well other ESSs. This work deals with a detailed updated review on available ESSs applications in future smart power grids. It also highlights latest projects carried out on different ESSs throughout all around the world.

Smart Inverter Functionality Testing for Battery Energy Storage Systems

Variable distributed energy resources (DERs) such as photovoltaic (PV) systems and wind power systems require additional power resources to control the balance between supply and demand. Battery energy storage systems (BESSs) are one such possible resource for providing grid stability. It has been proposed that decentralized BESSs could help support microgrids (MGs) with intelligent control when advanced functionalities are implemented with variable DERs. One key challenge is developing and testing smart inverter controls for DERs. This paper presents a standardized method to test the interoperability and functionality of BESSs. First, a survey of grid-support standards prevalent in several countries was conducted. Then, the following four interoperability functions defined in IEC TR 61850-90-7 were tested: the specified active power from storage test (INV4), the var-priority Volt/VAR test (VV) and the specified power factor test (INV3) and frequency-watt control (FW). This study then out-lines the remaining technical issues related to basic BESS smart inverter test protocols.

Segment Storage System:基于P2P的网络存储服务(英文)

Segment Storage System(S3)是一种基于P2P模型的网络存储服务,它具有高可用性、可靠性和持久性的特点。S3继承了P2P网络的优点并且摒弃了诸如文件时效性和不稳定性等缺点。S3的目标是提供一种高质量的网络存储服务。文章是对S3的设计架构的一个概览。

Battery Energy Storage System and Demand Response Based Optimal Virtual Power Plant Operation

With certain controllability of various distribution energy resources (DERs) such as battery energy storage system (BESS), demand response (DR) and distributed generations (DGs), virtual power plant (VPP) can suitably regulate the powers access to the distribution network. In this paper, an optimal VPP operating problem is used to optimize the charging/discharging schedule of each BESS and the DR scheme with the objective to maximize the benefit by regulating the supplied powers over daily 24 hours. The proposed solution method is composed of an iterative dynamic programming optimal BESS schedule approach and a particle swarm optimization based (PSO-based) DR scheme approach. The two approaches are executed alternatively until the minimum elec-tricity cost of the whole day is obtained. The validity of the proposed method was confirmed with the obviously decreased supplied powers in the peak-load hours and the largely reduced electricity cost.

Fully distributed control to coordinate charging efficiencies for energy storage systems

This study proposes a novel fully distributed coordination control(DCC) strategy to coordinate charging efficiencies of energy storage systems(ESSs). To realize this fully DCC strategy in an active distribution system(ADS) with high penetration of intermittent renewable generation, a two-layer consensus algorithm is proposed and applied. It collects global information in the first layer and achieves pinning-based DCC in the second layer. Basic objectives of the proposed DCC for ESSs are: à to coordinate the ESSs and improve efficiency using associated marginal charging costs(MCCs) in a fully distributed manner; ` to reduce local power mismatch and power transmission losses; ′ to adapt to unintentional communication topology changes. The effectiveness and adaptability of the proposed DCC approach are both validated by simulation results.

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.

Assessing impacts of energy storage on resilience of distribution systems against hurricanes

This paper develops a comprehensive framework to analyze the impact of energy storage on improving the resilience of distribution systems against hurricanes.This paper first develops a spatio-temporal model of progressing hurricane when making landfall that can be used to anticipate outage scenarios caused by the gust-wind speed.An optimization model is then developed for optimizing the operation of distribution systems during hurricane that captures both pre-outage and post-outage network operation constraints.Numerical simulations are performed on the modified IEEE 33-bus distribution system with real hurricane data in Houston to demonstrate the effectiveness of the proposed model.

Multi-Threat Real-Time Separating System

This paper describes a multi-threat real-time separating system for broadband anti-radiation missile seeker. It presents a method, with a dual-port memory as comparer, to perform PF and PW hardware real-time separation and to determine the time-of-arrival (TOA) by use of sequential difference histogram (SDIF). The method has been applied to practice, which has achieved good results.

Storage capacity allocation strategy for distribution network with distributed photovoltaic generators

Distributed photovoltaic generators(DPGs) have been integrated into the medium/low voltage distribution network widely. Due to the randomness and fluctuation of DPG, however, the distribution and direction of power flow changed frequently some days. Therefore, more attention is needed to ensure the safe operation of the distribution network. The installation of energy storage systems(ESSs) can help the network withstand thefluctuations caused by DPG. Based on the discrete Fourier transform method, this paper presents an ESS capacity allocation strategy for the medium/low voltage distribution network with DPG. The reliability scenario models are created via Latin hypercube sampling with Cholesky decomposition and scenario reduction. Numerical results show that the proposed strategy can reduce the power flow fluctuation with less ESS capacity, and increase the penetration capacity of DPG in the distribution network while maintaining the quality of the power supply.

Optimal planning of energy storage system in active distribution system based on fuzzy multi-objective bi-level optimization

A fuzzy multi-objective bi-level optimization problem is proposed to model the planning of energy storage system(ESS) in active distribution systems(ADS). The proposed model enables us to take into account how optimal operation strategy of ESS in the lower level can affect and be affected by the optimal allocation of ESS in the upper level. The power characteristic model of micro-grid(MG)and typical daily scenarios are established to take full consideration of time-variable nature of renewable energy generations(REGs) and load demand while easing the burden of computation. To solve the bi-level mixed integer problem, a multi-subgroup hierarchical chaos hybrid algorithm is introduced based on differential evolution(DE) and particle swarm optimization(PSO). The modified IEEE-33 bus benchmark distribution system is utilized to investigate the availability and effectiveness of the proposed model and the hybrid algorithm. Results indicate that the planningmodel gives an adequate consideration to the optimal operation and different roles of ESS, and has the advantages of objectiveness and reasonableness.

Multi-objective short-term scheduling of active distribution networks for benefit maximization of DisCos and DG owners considering demand response programs and energy storage system

This paper proposes a multi-objective benefit function for operation of active distribution systems considering demand response program(DRP)and energy storage system(ESS).In the active distribution system,active network management(ANM)is applied so that the distribution system equipment is controlled in real-time status based on the real-time measurements of system parameters(voltages and currents).The multi-objective optimization problem is solved using e-constraint method,and a fuzzy satisfying approach has been employed to select the best compromise solution.Two different objective functions are considered as follows:benefit maximization of distribution company(DisCo);benefit maximization of distributed generation owner(DGO).To increase the benefits and efficient implementation of distributed generation(DG),DGO has installed battery as energy storage system(ESS)in parallel with DG unit.Consequently,DGO decides for the battery charging/discharging.DisCo has the ability to exchange energy with the upstream network and DGO.Also,DisCo focuses to study the effect of demand response program(DRP)on total benefit function and consequently its influence on the load profile has been discussed.This model is successfully applied to a 33-bus radial distribution network.

Survey on Anonymity in Unstructured Peer-to-Peer Systems

Although anonymizing Peer-to-Peer （P2P） networks often means extra cost in terms of transfer efficiency, many systems try to mask the identities of their users for privacy consideration. By comparison and analysis of existing approaches, we investigate the properties of unstructured P2P anonymity, and summarize current attack models on these designs. Most of these approaches are path-based, which require peers to pre-construct anonymous paths before transmission, thus suffering significant overhead and poor reliability. We also discuss the open problems in this field and propose several future research directions.

A multi agent-based optimal control method for combined cooling and power systems with thermal energy storage

Combined cooling,heating and power(CCHP)systems have been considered as a potential energy saving technology for buildings due to their high energy efficiency and low carbon emission.Thermal energy storage(TES)can improve the energy efficiency of CCHP systems,since they reduce the mismatch between the energy supply and demand.However,it also increases the complexity of operation optimization of CCHP systems.In this study,a multi-agent system(MAS)-based optimal control method is proposed to minimize the operation cost of CCHP systems combined with TES.Four types of agents,i.e.,coordinator agents,building agents,energy management agents and optimization agents,are implemented in the MAS to cooperate with each other.The operation optimization problem is solved by the genetic algorithm.A simulated system is utilized to validate the performance of the proposed method.Results show that the operation cost reductions of 10.0%on a typical summer day and 7.7%on a typical spring day are achieved compared with a rule-based control method.A sensitivity analysis is further performed and results show that the optimal operation cost does not change obviously when the rated capacity of TES exceeds a threshold.

计及故障维修与网络重构的灾后配电网综合调度策略

当前,灾后配电网负荷恢复与故障维修多是独立考虑,缺乏有效联动,且没有合理计及包含故障维修时间及新能源出力的不确定性在内的双重因素影响。为此,提出一种灾后配电网维修恢复联合调度策略。首先,提出灾后配电网两阶段求解框架,第一阶段求解故障维修计划及网络重构问题,第二阶段解决移动式储能系统参与下的灾后配电网源荷协同调度问题。其次,构建移动式储能系统与维修人员的调度模型,量化分析移动式储能系统时空转移模型及能量模型,同时基于维修人员的时空转移特性,建立故障维修及网络重构模型。在此基础上,以恢复运行成本最小化为目标,分别采用离散鲁棒与连续鲁棒处理故障维修时间与新能源出力的不确定性,构建灾后配电网综合调度模型。最后,采用改进IEEE 33节点配电网进行仿真测试。结果表明,所提调度策略能够显著降低负荷失电率,减少停电损失。此外,两阶段算法在显著提升求解速度的同时能够保证求解精度,具有可行性和合理性。

基于多元储能的分布式能源系统优化调度方法研究

为进一步构建清洁低碳、经济节能的供能系统,研究建立了含风、光以及多元储能的分布式能源系统,针对北京某办公园区,采用DeST预测用户负荷以及当地风、光条件。以经济性、节能性和环保性三方面的综合效益最大为目标,提出一种自适应优化运行策略,分别采用穷举搜索法和遗传算法对系统优化调度方案进行优化。同时,采用以电定热运行策略作为对照,对比分析几种不同运行策略下系统的综合效益。结果表明:传统以电定热运行模式下的综合效益平均值为0.41;而在自适应优化运行策略下,使用遗传算法得到的调度方案,其综合效益平均值可达0.5,穷举搜索法得到的运行方案,其综合效益平均值可达0.51。

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。

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。

光伏波动平抑下改进K-means的电池储能动态分组控制策略

针对电池储能系统(battery energy storage system,BESS)进行光伏波动平抑时寿命损耗高及荷电状态(state of charge,SOC)一致性差的问题,提出了光伏波动平抑下改进K-means的BESS动态分组控制策略。首先,采用最小最大调度方法获取光伏并网指令。其次,设计了改进侏儒猫鼬优化算法(improved dwarf mongoose optimizer,IDMO),并利用它对传统K-means聚类算法进行改进,加快了聚类速度。接着,制定了电池单元动态分组原则,并根据电池单元SOC利用改进K-means将其分为3个电池组。然后,设计了基于充放电函数的电池单元SOC一致性功率分配方法,并据此提出BESS双层功率分配策略,上层确定电池组充放电顺序及指令,下层计算电池单元充放电指令。对所提策略进行仿真验证,结果表明,所设计的IDMO具有更高的寻优精度及更快的寻优速度。所提BESS平抑光伏波动策略在有效平抑波动的同时,降低了BESS运行寿命损耗并提高了电池单元SOC的均衡性。

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。