Evaluation of Multi-Temporal-Spatial Scale Adjustment Capability and Cluster Optimization Operation Method for Distribution Networks with Distributed Photovoltaics

Themassive integration of high-proportioned distributed photovoltaics into distribution networks poses significant challenges to the flexible regulation capabilities of distribution stations.To accurately assess the flexible regulation capabilities of distribution stations,amulti-temporal and spatial scale regulation capability assessment technique is proposed for distribution station areas with distributed photovoltaics,considering different geographical locations,coverage areas,and response capabilities.Firstly,the multi-temporal scale regulation characteristics and response capabilities of different regulation resources in distribution station areas are analyzed,and a resource regulation capability model is established to quantify the adjustable range of different regulation resources.On this basis,considering the limitations of line transmission capacity,a regulation capability assessment index for distribution stations is proposed to evaluate their regulation capabilities.Secondly,considering different geographical locations and coverage areas,a comprehensive performance index based on electrical distance modularity and active power balance is established,and a cluster division method based on genetic algorithms is proposed to fully leverage the coordination and complementarity among nodes and improve the active power matching degree within clusters.Simultaneously,an economic optimization model with the objective of minimizing the economic cost of the distribution station is established,comprehensively considering the safety constraints of the distribution network and the regulation constraints of resources.This model can provide scientific guidance for the economic dispatch of the distribution station area.Finally,case studies demonstrate that the proposed assessment and optimization methods effectively evaluate the regulation capabilities of distribution stations,facilitate the consumption of distributed photovoltaics,and enhance the economic efficiency of the distribution station area.

Designing ultrastable P2/O3-type layered oxides for sodium ion batteries by regulating Na distribution and oxygen redox chemistry

P2/O3-type Ni/Mn-based layered oxides are promising cathode materials for sodium-ion batteries(SIBs)owing to their high energy density.However,exploring effective ways to enhance the synergy between the P2 and 03 phases remains a necessity.Herein,we design a P2/O3-type Na_(0.76)Ni_(0.31)Zn_(0.07)Mn_(0.50)Ti_(0.12)0_(2)(NNZMT)with high chemical/electrochemical stability by enhancing the coupling between the two phases.For the first time,a unique Na*extraction is observed from a Na-rich O3 phase by a Na-poor P2 phase and systematically investigated.This process is facilitated by Zn^(2+)/Ti^(4+)dual doping and calcination condition regulation,allowing a higher Na*content in the P2 phase with larger Na^(+)transport channels and enhancing Na transport kinetics.Because of reduced Na^(+)in the O3 phase,which increases the difficulty of H^(+)/Na^(+) exchange,the hydrostability of the O3 phase in NNZMT is considerably improved.Furthermore,Zn^(2+)/Ti^(4+)presence in NNZMT synergistically regulates oxygen redox chemistry,which effectively suppresses O_(2)/CO_(2) gas release and electrolyte decomposition,and completely inhibits phase transitions above 4.0 V.As a result,NNZMT achieves a high discharge capacity of 144.8 mA h g^(-1) with a median voltage of 3.42 V at 20 mA g^(-1) and exhibits excellent cycling performance with a capacity retention of 77.3% for 1000 cycles at 2000 mA g^(-1).This study provides an effective strategy and new insights into the design of high-performance layered-oxide cathode materials with enhanced structure/interface stability forSIBs.

Research on Short-Term Load Forecasting of Distribution Stations Based on the Clustering Improvement Fuzzy Time Series Algorithm

An improved fuzzy time series algorithmbased on clustering is designed in this paper.The algorithm is successfully applied to short-term load forecasting in the distribution stations.Firstly,the K-means clustering method is used to cluster the data,and the midpoint of two adjacent clustering centers is taken as the dividing point of domain division.On this basis,the data is fuzzed to form a fuzzy time series.Secondly,a high-order fuzzy relation with multiple antecedents is established according to the main measurement indexes of power load,which is used to predict the short-term trend change of load in the distribution stations.Matlab/Simulink simulation results show that the load forecasting errors of the typical fuzzy time series on the time scale of one day and one week are[−50,20]and[−50,30],while the load forecasting errors of the improved fuzzy time series on the time scale of one day and one week are[−20,15]and[−20,25].It shows that the fuzzy time series algorithm improved by clustering improves the prediction accuracy and can effectively predict the short-term load trend of distribution stations.

Design scheme for fast charging station for electric vehicles with distributed photovoltaic power generation

The demand for fast charging is increasing owing to the rapid expansion of the market for electric vehicles. In addition, the power generation technology for distributed photovoltaic has matured. This paper presents a design scheme for a fast charging station for electric vehicles equipped with distributed photovoltaic power generation system taking the area with certain conditions in Beijing as an example construction site. The technical indexes and equipment lectotype covering the general framework and subsystems of the charging station are determined by analyzing the charging service demand of fast charging stations. In this study, the layout of the station is developed and the operation benefits of the station is analyzed. The design scheme realizes the design objective of "rationalization, modularization and intelligentization" of the fast charging station and can be used as reference for the construction of a fast charging network in urban area.

Distributed power allocation over indoor multi-pico stations

A low-complexity distributed power allocation algorithm is proposed to reduce the interference and improve the transmitting rate of edge users. Different scenarios are considered and user experience of indoor communication is promoted. The simulation results prove the effectiveness of our algorithm. The proposed power control scheme ensures that more users can achieve their required rate and the fairness of different users is improved. Besides, more than 5096 energy can be saved without loss in outage ability, and energy efficiency is also promoted. In addition, the proposed algorithm can be extended to scenarios that the required rates of pico stations can be changed periodically.

Comparative Study on Distributed Waste Pyrolysis Cold Emission Energy Station and Incineration Power Generation

The proper terminal disposal of organic solid waste such as domestic waste is a worldwide issue.Landfill covers a large area,with limited capacity,and a single landfill will be filled one day;incineration is costly to build and operate.These methods all need to transfer and centralized treatment,and secondary pollution is difficult to control,against the purification law of the nature."NIMBY effect"is very serious,and the social cost of treatment is increasing,becoming a heavy financial burden."The Distributed Waste Pyrolysis Cold Emission Energy Station"developed by Hunan Zhongzhou Energy-Saving Technology Co.,Ltd.overcomes these disadvantages and constructs a more appropriate environmental economic industrial chain for the treatment of organic solid waste such as urban and rural household waste.Based on its technical characteristics,this paper compares it with waste incineration power generation project in the aspects of secondary pollution control,treatment effect,energy utilization,investment and operation economy,etc.

Location and Capacity Determination Method of Electric Vehicle Charging Station Based on Simulated Annealing Immune Particle Swarm Optimization

As the number of electric vehicles(EVs)continues to grow and the demand for charging infrastructure is also increasing,how to improve the charging infrastructure has become a bottleneck restricting the development of EVs.In other words,reasonably planning the location and capacity of charging stations is important for development of the EV industry and the safe and stable operation of the power system.Considering the construction and maintenance of the charging station,the distribution network loss of the charging station,and the economic loss on the user side of the EV,this paper takes the node and capacity of charging station planning as control variables and the minimum cost of system comprehensive planning as objective function,and thus proposes a location and capacity planning model for the EV charging station.Based on the problems of low efficiency and insufficient global optimization ability of the current algorithm,the simulated annealing immune particle swarm optimization algorithm(SA-IPSO)is adopted in this paper.The simulated annealing algorithm is used in the global update of the particle swarm optimization(PSO),and the immune mechanism is introduced to participate in the iterative update of the particles,so as to improve the speed and efficiency of PSO.Voronoi diagram is used to divide service area of the charging station,and a joint solution process of Voronoi diagram and SA-IPSO is proposed.By example analysis,the results show that the optimal solution corresponding to the optimisation method proposed in this paper has a low overall cost,while the average charging waiting time is only 1.8 min and the charging pile utilisation rate is 75.5%.The simulation comparison verifies that the improved algorithm improves the operational efficiency by 18.1%and basically does not fall into local convergence.

Wet Oxidation of Al_x Ga_(1-x)As/GaAs Distributed Bragg Reflectors

The wet oxidation of AlGaAs with high Al content in a distributed Bragg reflectors （DBR） is studied by scanning electron microscopy （SEM） and transmission electron microscopy （TEM）. Some voids distribute along the oxide/GaAs interfaces due to the stress induced by the wet oxidation of the AlGaAs layers. These voids decrease the shrinkage of the Al2O3 layers to 8% instead of the theoretical 20% when compared to the unoxidized AlGaAs layers. With the extension of oxidation time, the reactants are more completely transported to the front interface and the products are more completely transported out along the porous interfaces. As a result,the oxide quality is better.

Effect of uneven noise source and/or station distribution on estimating the azimuth anisotropy of surface waves

With the development of the dense array,the surface wave velocity and azimuthal anisotropy under the array can be directly obtained by beamforming the noise cross-correlation functions(NCFs). However, the retrieval of the Green’s function by cross-correlating the seismic noise requires that the noise source has a uniform distribution. For the case with uneven noise source, the azimuthal dependence on the sources in the expression for the spatial coherence function, which corresponds to the NCF in the time domain,has the same form as the azimuthal dependence of the surface wave velocity in weakly anisotropic media. Therefore, the uneven noise source will affect the surface wave anisotropy extraction. In this study, three passive seismic methods, i.e.,beamforming, SPAC(spatial autocorrelation), and NCF, are compared to demonstrate that an uneven source distribution and uneven station distribution have equivalent effects on the outcome from each method. A beamforming method is proposed to directly extract the velocity and azimuthal anisotropy of surface waves. The effect of uneven noise source and/or station distribution on estimating the azimuth anisotropy of surface waves was investigated using data from the ChinArray Phase Ⅱ. A method for correcting the apparent anisotropy in beamforming results caused by an uneven station distribution is suggested.

基于Floyd算法的5G基站区域储能分配策略

由于5G集中在人群密集区域配置,需要的基站数量多且能耗大,因此,运营商需要支付的购电成本很多。为了降低运营商的购电成本,本文提出一种基于Floyd算法的5G基站区域储能分配策略。首先,将供电网络中的5G基站区域储电站等效为一系列节点,并根据节点之间的距离信息计算出传输损失率矩阵;其次,对各节点的储能情况进行分析,并根据其储能情况将节点分为供能节点与需求节点;最后,基于Floyd算法来合理调配该储能网络中的能量。仿真结果表明,在不引入外部供电和引入外部供电两种情况下,本文所提出的系统在运行2 a或150 d后分别达到稳定状态,系统不再需要额外从公用电网购电,减轻了电网供电压力的同时,降低了运营商的购电成本。

A Method for Rapidly Determining the Optimal Distribution Locations of GNSS Stations for Orbit and ERP Measurement Based on Map Grid Zooming and Genetic Algorithm

Designing the optimal distribution of Global Navigation Satellite System(GNSS)ground stations is crucial for determining the satellite orbit,satellite clock and Earth Rotation Parameters(ERP)at a desired precision using a limited number of stations.In this work,a new criterion for the optimal GNSS station distribution for orbit and ERP determination is proposed,named the minimum Orbit and ERP Dilution of Precision Factor(OEDOP)criterion.To quickly identify the specific station locations for the optimal station distribution on a map,a method for the rapid determination of the selected station locations is developed,which is based on the map grid zooming and heuristic technique.Using the minimum OEDOP criterion and the proposed method for the rapid determination of optimal station locations,an optimal or near-optimal station distribution scheme for 17 newly built BeiDou Navigation Satellite System(BDS)global tracking stations is suggested.To verify the proposed criterion and method,real GNSS data are processed.The results show that the minimum OEDOP criterion is valid,as the smaller the value of OEDOP,the better the precision of the satellite orbit and ERP determination.Relative to the exhaustive method,the proposed method significantly improves the computational efficiency of the optimal station location determination.In the case of 3 newly built stations,the computational efficiency of the proposed method is 35 times greater than that of the exhaustive method.As the number of stations increases,the improvement in the computational efficiency becomes increasingly obvious.

MILP formulations for highway petrol station replenishment in initiative distribution mode

To investigate highway petrol station replenishment in initiative distribution mode,this paper develops a mixed-integer linear programming(MILP)model with minimal operational costs that includes loading costs,unloading costs,transport costs and the costs caused by unpunctual distribution.Based on discrete representation,the working day is divided into equal time intervals,and the truck distribution process is decomposed into a pair of tasks including driving,standby,rest,loading and unloading.Each truck must execute one task during a single interval,and the currently executing task is closely related to the preceding and subsequent tasks.By accounting for predictive time-varying sales at petrol stations,real-time road congestion and a series of operational constraints,the proposed model produces the optimal truck dispatch,namely,a detailed task assignment for all trucks during each time interval.The model is tested on a real-world case of a replenishment system comprising eight highway petrol stations,one depot,one garage and eight trucks to demonstrate its applicability and accuracy.

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.

多级A/O工艺设计及其在应急污水处理工程中的应用

为有效缓解资阳市第二污水处理厂现状处理能力不足导致的污水溢流问题,改善周边水生态环境,新建了规模为5000 m 3/d的应急污水处理工程。该工程采用“多级A/O+磁混凝沉淀”组合工艺,对其中的多级A/O工艺段进行了深化设计,并对本项目的实际运行效果进行了分析。深化设计结果表明,多级A/O反应器级数宜采用2级,流量分配比宜为7∶3,污泥回流比宜为100%。运行期间的监测数据表明,出水指标均满足《四川省岷江、沱江流域水污染物排放标准》(DB51/2311-2016),其中的COD Cr、TP和TN的去除率分别为96.6%、97.6%和87.2%。通过设置初段硝化液回流,充分发挥初级缺氧池的脱氮能力,使多级A/O工艺的脱氮效率得到了强化。该项目采用的组合工艺简单有效,出水效果好,为城市溢流污水的高标准排放提供了一种更优选择。

Design of a Level-3 electric vehicle charging station using a 1-MW solar system via the distributed maximum power point tracking technique

Solar power is mostly influenced by solar irradiation,weather conditions,solar array mismatches and partial shading conditions.Therefore,before installing solar arrays,it is necessary to simulate and determine the possible power generated.Maximum power point tracking is needed in order to make sure that,at any time,the maximum power will be extracted from the photovoltaic system.However,maximum power point tracking is not a suitable solution for mismatches and partial shading conditions.To overcome the drawbacks of maximum power point tracking due to mismatches and shadows,distributed maximum power point tracking is util-ized in this paper.The solar farm can be distributed in different ways,including one DC-DC converter per group of modules or per module.In this paper,distributed maximum power point tracking per module is implemented,which has the highest efficiency.This technology is applied to electric vehicles(EVs)that can be charged with a Level 3 charging station in<1 hour.However,the problem is that charging an EV in<1 hour puts a lot of stress on the power grid,and there is not always enough peak power reserve in the existing power grid to charge EVs at that rate.Therefore,a Level 3(fast DC)EV charging station using a solar farm by implementing distributed maximum power point tracking is utilized to address this issue.Finally,the simulation result is reported using MATLAB®,LTSPICE and the System Advisor Model.Simulation results show that the proposed 1-MW solar system will provide 5 MWh of power each day,which is enough to fully charge~120 EVs each day.Additionally,the use of the proposed photovoltaic system benefits the environment by removing a huge amount of greenhouse gases and hazardous pollutants.For example,instead of supplying EVs with power from coal-fired power plants,1989 pounds of CO_(2) will be eliminated from the air per hour.

基于CRITIC-TOPSIS的配电站房运行状态评估

实现配电站房运行状态的准确评估对确保电力系统的稳定运行有着重要的意义。针对目前评估方法主观性过强的问题,提出了一种基于CRITIC-TOPSIS的配电站房运行状态评估方法。基于压力-状态-响应(PSR)框架的思维模式,建立科学合理的配电站房运行状态评估指标体系,采用CRITIC赋权法确定各评价指标的权重,减少评价过程中的主观性,建立CRITIC-TOPSIS评价模型,利用综合接近度评估配电站房相对运行状态,并确定状态等级;引入禀赋效应来根据决策者的心理行为对评价结果进行调整,并对配电站房状态情况进行优劣排序;根据某地区配电站房实际运行数据进行实例分析,所得评价结果具有客观性和合理性。

A^(2)O-MBBR+反硝化深床滤池工艺用于污水处理厂提标扩能

宜宾市杨湾污水处理厂处理规模由6×10^(4)m^(3)/d扩容至12×10^(4)m^(3)/d,出水水质提升至《四川省岷江、沱江流域水污染物排放标准》(DB 51/2311-2016)。针对用地受限和排洪暗渠从厂区中间穿过的实际情况,从工艺选择、总图和构筑物布置角度优化设计。污水处理采用“A^(2)O-MBBR-反硝化深床滤池”工艺;二期生化池和二沉池布置在排洪暗渠上方;加大生化池有效水深和滤池滤层厚度;二次提升泵井、反硝化深床滤池及配套设施集约化组合布置。实际运行效果显示,出水COD、BOD_(5)、NH_(3)^(-)N、TP、TN、SS平均值分别为8.37、2.87、0.08、0.15、5.29、2.56 mg/L,稳定达到排放标准。

基于BPSO-IRS算法的智能值守机器人资源调度方法研究

针对电网区域内多配电站的巡检,单一值守机器人无法满足区域协调能力且会造成众多资源的浪费,云机器人可以实现资源共享提升巡检效率,以优化系统负载均衡、各类资源利用率均衡和系统能耗为目标,提出了云架构的资源调度系统。搭建资源调度数学模型,结合物理机的几种重要参数建立面向不同目标的数学模型。创建两种不同类型的RVM服务虚拟机:初始放置与增量放置。在云端初始创建服务虚拟机时产生的资源分配问题,可以借鉴PSO算法采用BPSO算法进行放置;在工作环境中对于虚拟机数量不足需要增加虚拟机个数时的分配问题,采用IRS算法进行分配。最后利用设计仿真实验,对比OpenStack原生的LFF调度算法,对BPSO-IRS算法优越性进行验证。

西门子分布式I/O系统在矿用电铲上的应用

西门子PLC系统主机架可通过扩展机架和分布式I/O两种方式完成对原PLC系统的扩展。目前电铲常用的扩展机架的方式在实际生产过程中会出现信号线松动和信号不稳定等情况,导致故障率较高。针对当前情况,提出了分布式I/O方案来扩展PLC系统的I/O模块,减少了控制电缆的数量,完成了程序的标准化、模块化、智能化,降低了故障率。

混凝沉淀-气浮-ABR-AA/O-MBR工艺处理垃圾中转站渗滤液的试验研究

垃圾中转站运行过程中产生的垃圾渗滤液含有大量的悬浮固体、油脂、有机物、盐分、氮类等污染物,其水质复杂且波动性大,易造成环境污染。针对浙江省某垃圾中转站渗滤液的水量和水质特点,采用混凝沉淀-气浮-ABR-AA/O-MBR工艺进行试验研究。其中,混凝沉淀-气浮物化处理单元能有效去除渗滤液中的悬浮固体和油脂等,而ABR-AA/O生物处理单元则能有效去除有机物、氨氮和总氮等。试验结果表明:进水中的COD_(Cr)、NH_(4)^(+)-N、TN和SS浓度分别为15130~20540、278.0~413.0、289.0~437.0和4330~6317 mg/L,出水中的COD_(Cr)、NH_(4)^(+)-N、TN和SS浓度分别为134~313、0.4~0.9、46.4~65.1和8~14 mg/L,平均去除率分别为98.72%、99.81%、84.91%和99.79%,满足《污水排入城镇下水道水质标准》(GB/T 31962—2015)的要求。综合来看,此工艺具有良好的技术适应性和产业化前景。