Comprehensive Evaluation of Distributed PV Grid-Connected Based on Combined Weighting Weights and TOPSIS-RSR Method

To effectively quantify the impact of distributed photovoltaic(PV)access on the distribution network,this paper proposes a comprehensive evaluation method of distributed PV grid connection combining subjective and objective combination of assignment and technique for order preference by similarity to an ideal solution(TOPSIS)—rank sum ratio(RSR)(TOPSIS-RSR)method.Based on the traditional distribution network evaluation system,a comprehensive evaluation system has been constructed.It fully considers the new development requirements of distributed PV access on the environmental friendliness and absorptive capacity of the distribution grid and comprehensively reflects the impact of distributed PV grid connection.The analytic hierarchy process(AHP)was used to determine the subjective weights of the primary indicators,and the Spearman consistency test was combined to determine the weights of the secondary indicators based on three objective assignment methods.The subjective and objective combination weights of each assessment indicator were calculated through the principle of minimum entropy.Calculate the distance between the indicators to be evaluated and the positive and negative ideal solutions,the relative closeness ranking,and qualitative binning by TOPSIS-RSR method to obtain the comprehensive evaluation results of different scenarios.By setting up different PV grid-connected scenarios and utilizing the IEEE33 node simulation algorithm,the correctness and effectiveness of the proposed subject-object combination assignment and integrated assessment method are verified.

Synergetic optimization operation method for distribution network based on SOP and PV

The integration of distributed generation brings in new challenges for the operation of distribution networks,including out-of-limit voltage and power flow control.Soft open points(SOP)are new power electronic devices that can flexibly control active and reactive power flows.With the exception of active power output,photovoltaic(PV)devices can provide reactive power compensation through an inverter.Thus,a synergetic optimization operation method for SOP and PV in a distribution network is proposed.A synergetic optimization model was developed.The voltage deviation,network loss,and ratio of photovoltaic abandonment were selected as the objective functions.The PV model was improved by considering the three reactive power output modes of the PV inverter.Both the load fluctuation and loss of the SOP were considered.Three multi-objective optimization algorithms were used,and a compromise optimal solution was calculated.Case studies were conducted using an IEEE 33-node system.The simulation results indicated that the SOP and PVs complemented each other in terms of active power transmission and reactive power compensation.Synergetic optimization improves power control capability and flexibility,providing better power quality and PV consumption rate.

Predictive value of red blood cell distribution width and hematocrit for short-term outcomes and prognosis in colorectal cancer patients undergoing radical surgery

BACKGROUND Previous studies have reported that low hematocrit levels indicate poor survival in patients with ovarian cancer and cervical cancer,the prognostic value of hematocrit for colorectal cancer(CRC)patients has not been determined.The prognostic value of red blood cell distribution width(RDW)for CRC patients was controversial.AIM To investigate the impact of RDW and hematocrit on the short-term outcomes and long-term prognosis of CRC patients who underwent radical surgery.METHODS Patients who were diagnosed with CRC and underwent radical CRC resection between January 2011 and January 2020 at a single clinical center were included.The short-term outcomes,overall survival(OS)and disease-free survival(DFS)were compared among the different groups.Cox analysis was also conducted to identify independent risk factors for OS and DFS.RESULTS There were 4258 CRC patients who underwent radical surgery included in our study.A total of 1573 patients were in the lower RDW group and 2685 patients were in the higher RDW group.There were 2166 and 2092 patients in the higher hematocrit group and lower hematocrit group,respectively.Patients in the higher RDW group had more intraoperative blood loss(P<0.01)and more overall complications(P<0.01)than did those in the lower RDW group.Similarly,patients in the lower hematocrit group had more intraoperative blood loss(P=0.012),longer hospital stay(P=0.016)and overall complications(P<0.01)than did those in the higher hematocrit group.The higher RDW group had a worse OS and DFS than did the lower RDW group for tumor node metastasis(TNM)stage I(OS,P<0.05;DFS,P=0.001)and stage II(OS,P=0.004;DFS,P=0.01)than the lower RDW group;the lower hematocrit group had worse OS and DFS for TNM stage II(OS,P<0.05;DFS,P=0.001)and stage III(OS,P=0.001;DFS,P=0.001)than did the higher hematocrit group.Preoperative hematocrit was an independent risk factor for OS[P=0.017,hazard ratio(HR)=1.256,95%confidence interval(CI):1.041-1.515]and DFS(P=0.035,HR=1.194,95%CI:1.013-1.408).CONCLUSION A higher preoperative RDW and lower hematocrit were associated with more postoperative complications.However,only hematocrit was an independent risk factor for OS and DFS in CRC patients who underwent radical surgery,while RDW was not.

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.

Short-term Distributed Energy Resource Scheduling for a DC Microgrid

A microgrid is associated with a low voltage distribution power network and inherits small modular generation systems and loads that have certain coordinated functions to provide the solution to supply premium power to remote or specific areas. Similar to conventional power systems, the energy management of distributed generation resources (DERs) is carried out to minimize the operation cost and maximize benefit of installation of DERS in a microgrid. This paper presents the process of implementing the short-term DER scheduling function for a dc microgrid. The optimal scheduling results for two operation modes are then reported.

Convex decomposition of concave clouds for the ultra-short-term power prediction of distributed photovoltaic system

Concave clouds will cause miscalculation by the power prediction model based on cloud ieatures for distributed photovoltaic （PV） plant. The algorithm for decomposing concave cloud into convex images is proposed. Adopting minimum polygonal approximation （MPP） to demonstrate the contour of concave cloud, cloud features are described and the subdivision lines of convex decomposition for the concave clouds are determined by the centroid point scattering model and centroid angle func- tion, which realizes the convex decomposition of concave cloud. The result of MATLAB simulation indicates that the proposed algorithm can accurately detect cloud contour comers and recognize the concave points. The proposed decomposition algorithm has advantages of less time complexity and decomposition part numbers compared to traditional algorithms. So the established model can make the convex decomposition of complex concave clouds completely and quickly, which is available for the existing prediction algorithm for the ultra-short-term power output of distributed PV system based on the cloud features.

BIPV模式在工业厂房屋顶的应用研究

中国大力推进分布式光伏发电的同时,存在许多工业厂房屋顶无法满足光伏发电系统安装条件的问题,这极大制约了光伏发电技术的推广。由于传统的光伏发电系统是直接附着在建筑物屋顶,即采用的是BAPV模式,这会导致因需增加建筑物的承载力而增加建设成本的情况出现,从而制约了分布式光伏发电的应用,而将光伏发电系统与建筑集成的光伏建筑一体化(BIPV)模式可有效解决此类问题。针对BIPV模式和BAPV模式对工业厂房钢结构的影响进行了研究,并根据实际案例对这两种模式下的光伏发电系统建设、维护成本进行了分析。研究结果表明:1)BIPV模式相较于BAPV模式可以减少工业厂房钢结构屋顶恒荷载,对于轻微超限的项目可以省去加固成本,对于超限明显的项目可以减少加固成本。2)在同等建设条件下,BIPV模式相较于BAPV模式可以减少屋顶建设成本;并且从中长期来看,相较于BAPV模式,BIPV模式平均1万m^(2)的厂房可以减少126万建设维护成本。

Short-term prediction of photovoltaic power generation based on LMD-EE-ESN with error correction

Considering the instability of the output power of photovoltaic(PV)generation system,to improve the power regulation ability of PV power during grid-connected operation,based on the quantitative analysis of meteorological conditions,a short-term prediction method of PV power based on LMD-EE-ESN with iterative error correction was proposed.Firstly,through the fuzzy clustering processing of meteorological conditions,taking the power curves of PV power generation in sunny,rainy or snowy,cloudy,and changeable weather as the reference,the local mean decomposition(LMD)was carried out respectively,and their energy entropy(EE)was taken as the meteorological characteristics.Then,the historical generation power series was decomposed by LMD algorithm,and the hierarchical prediction of the power curve was realized by echo state network(ESN)prediction algorithm combined with meteorological characteristics.Finally,the iterative error theory was applied to the correction of power prediction results.The analysis of the historical data in the PV power generation system shows that this method avoids the influence of meteorological conditions in the short-term prediction of PV output power,and improves the accuracy of power prediction on the condition of hierarchical prediction and iterative error correction.

Availability, Performance and Reliability Evaluation for PV Distributed Generation

Nowadays, renewable energy resources play an important role in replacing conventional energy resources such as fossil fuel by integrating solar, wind and geothermal energy. Photovoltaic energy is one?of?the very promising renewable energy resources which grew rapidly in the past few years, it can be used to produce electric energy through photovoltaic process. The primary objective of the research proposed in this paper is to facilitate the increasing penetration levels of PV systems in the electric distribution networks. In this work, the PV module electrical model is presented based on the mathematical equations and was implemented on MATLAB to simulate the non-linear characteristics I-V and P-V curves with variable input parameters which are irradiance and temperature based on Riyadh region. In addition, the reliability evaluation of distribution networks, including distributed generators of solar photovoltaic (PV) with varying output power capacity is presented also. The Monte Carlo simulation algorithm is applied to test the distribution network which is RBTS Bus 2 and the same has been conducted on the original case of distribution network substation 7029 which is located at KSA Riyadh. The two distribution networks have been modified to include the PV’s distributed generators. The distributed generators contribute to supply a part of the load during normal mode and supply the entire load during component failure or failure of grid operation supply. The PV stochastic models have been used to simulate the randomness of these resources. Moreover, the study shows that the implementation and integration of renewable resources as distributed generations have improved the reliability of the distribution networks.

Impact of PV Distributed Generation on Loop Distribution Network

The rapid spreading of the Photovoltaic (PV) Systems as Distributed Generation (DG) in medium and low voltage networks created many effects and changes on the existing power system networks. In this work, two methods have been used and applied to determine the optimal allocation and sizing of the PV to be installed as DGs (ranging from 250 kW up to 3 MW). The first one is to determine the location according to the maximal power losses reduction over the feeder. The second one is by using the Harmony Search Algorithm which is claimed to be a powerful technique for optimal allocation of PV systems. The results of the two techniques were compared and found to be nearly closed. Furthermore, investigation on the effects on the feeder in terms of voltage levels, power factor readings, and short circuit current levels has been done. All calculations and simulations are conducted by using the MATLAB Simulation Program. Some field calculations and observations have been expended in order to substantiate the research findings and validation.

An Augmented Jacobian Method for Power Flow Analysis of Weakly Looped Distribution Systems with PV Buses

A power flow analysis method for weakly looped distribution systems with PV buses is proposed in this paper. The proposed method is computationally more efficient and more robust compared with the conventional compensation methods. The robustness is achieved by embedding the boundary conditions of loops and PV buses into the Jacobian matrix. The computational efficiency is achieved by the carefully designed factorization of Jacobian matrix. Test results on a 33 bus system are presented.

Research on Multi-Scale Modeling of Grid-Connected Distributed Photovoltaic Power Generation

The complexity of distribution network model mainly depends on the model scale of grid-connected distributed photovoltaic (PV) power generation. Therefore, the simulation performance of multi-scale PV model is the key factor of the simulation accuracy in the specific operating scenarios of distribution network. In this paper, a multi-scale model of grid connected PV distributed generation system is proposed based on the mathematical model of grid-connected distributed PV power generation. It is analyzed that differences of simulation performance, such as adaptability of simulation step size, accuracy of output and the effect on voltage profile of distribution network, between PV models with different scales in IEEE 33 node example. Simulation results indicate that the multi-scale model is effective in improving the accuracy and efficiency of simulation under different operating conditions of distribution network.

考虑分布式光伏发电特性的CHPV组合优化调度

近年来光伏装机容量逐年提升,为进一步提高光伏的消纳能力,满足居民的电热需求,本文首先分析分布式光伏的发电特性,提出一种由微型热电联供机组和光伏机组的组合机组,简称CHPV组合,构建以运行成本最低为目标的CHPV组合优化模型,采用K-means聚类方法对某地一年的光伏数据进行聚类,生成3个典型的光伏出力场景并代入CHPV组合优化模型中,采用Cplex对本文所提模型进行仿真验证。结果表明,本文所构建的CHPV组合可有效满足居民不同季节下的电热需求和提高光伏的消纳能力。

Short-Term Kinematics of the Adria Plate and Space-Time Distribution of Major Peri-Adriatic Earthquakes

Seismic activity is quite strong in the peri-Adriatic zones, whereas the internal part of the Adria plate is almost aseismic. This pattern suggests that Adria is a solid block that interacts with the surrounding belts, trying to move roughly northward. Each major earthquake in a peri-Adriatic zone triggers the acceleration of the decoupled Adria sector, which induces a perturbation of the stress/strain fields in the still blocked boundaries of the plate. Step by step, the displacement of Adria involves more and more northern zones to finally reach the northern front of the plate (eastern Southern Alps). This interpretation seems to be compatible with the time patterns of seismic activity in the main peri-Adriatic zones since 1600 A.D., which may suggest repeated northward migrations of seismic crises. Each supposed migrating sequence involves major earthquakes in most zones. The main features of the first 4 seismic sequences (1600-1930) are used to get insights into possible regularities in the progressive activations of the peri-Adriatic zones. This information and the main features of the ongoing migrating sequence (since 1931) are then used to tentatively recognize the peri-Adriatic zones where the occurrence of next major earthquakes may be most likely.

基于数据驱动的分布式光伏发电功率预测方法研究进展

从综述的角度,以分布式光伏系统为对象,分析了功率预测技术的发展情况、存在的难点以及主要影响因素,梳理了应用数据驱动方法实现功率准确预测的技术路线。再以空间相关性、历史出力功率以及气象等影响因素为切入点,梳理了光伏系统数据驱动的功率预测研究现状,分析其相应的数据增强、时空图信息以及特征融合的手段,讨论了技术的优缺点。最后给出了功率预测数据驱动方法研究方向和发展建议。

含电动汽车和光伏的配电网演化动态博弈调度策略

针对大规模电动汽车的无序充电行为可能导致电网出现的三相不平衡问题,基于演化动态博弈模型,提出一种考虑三相负荷平衡和光伏消纳的电动汽车充电调度策略。首先,基于电动汽车接入时段的主观性以及光伏出力和负荷的不确定性,引入游牧集群和定居集群之间的演化动态博弈方程;然后,考虑用户侧和电网侧双方利益关系,设计以最小化电动汽车充电费用、三相负荷不平衡度和无功需求为目标的调度优化模型;最后,通过对某商业区配电网算例进行仿真求解,对比分析三相有功曲线、三相无功曲线以及荷电状态曲线的变化趋势。算例结果表明,该调度策略可有效降低三相不平衡度,满足无功补偿的需求以及改善用户充电成本。

基于PVsyst和Simulink的建筑主动配电系统光伏仿真设计

设计建筑主动配电系统一般需要先建立“源、网、荷、储”各系统模型,再对其进行仿真模拟,最终实现优化控制。光伏系统是建筑主动配电系统中“源”的重要组成部分,根据光伏电池的数学模型,在PVsyst和Simulink仿真平台中建立基于扰动观察法最大功率点跟踪(MPPT)的建筑主动配电系统光伏仿真模型,最后用实际工程案例进行验证。

An Introduction to Distribution-Level Solar Energy

Solar energy has been widely used in power generation.With the development of solar energy,the distributed photovoltaic power generation and the distributed grid-connected PV systems become the center of attention.This paper provided a brief introduction to distribution-level solar energy.Firstly,the development of solar energy was analyzed,and the distributed photovoltaic power generation was discussed.Secondly,the distributed grid-connected PV systems and basic theory of photovoltaic solar channel were analyzed.In order to ensure PV power is connected to grid stably and reliably,some related aspects such as the establishment of mathematical model for solar photovoltaic cell,the analysis of I-V characteristics of solar photovoltaic cell,and the tracking of its maximum power point(MPPT)to control the behaviour of the DC/DC converter were discussed.Finally,a simulation model was necessary to be established by using PSCAD/EMTDC function module to verify and simulate the mathematical model and control strategies,and some suggestions were put forward for the sustainable development of solar energy.

基于RPC的光储接入牵引供电系统协调控制方法

为将光伏发电接入牵引供电系统进行有效利用,同时兼顾牵引供电系统电能质量改善及列车再生制动能量回收利用,提出了一种基于铁路功率调节器的光储系统接入牵引供电系统的协调控制方法.首先,搭建基于铁路功率调节器的光储系统接入牵引供电拓扑结构,并对其电能质量补偿机理进行理论分析;在此基础上,充分考虑光储系统的运行条件以及列车牵引、制动、空载或惰行工况,提出光储系统接入牵引供电的联合协调控制方法,实现了“光+储+荷”三者间的协调控制、牵引供电系统负序的动态补偿以及谐波的有效抑制;在RT-Lab实时仿真系统中建立了基于铁路功率调节器的光伏接入牵引供电系统仿真模型,并结合实际光照和牵引工况数据验证本文所提出的系统结构以及协调控制方法的有效性.结果表明:本文所提出的系统结构以及协调控制方法能够实现牵引供电系统中光储系统的有效接入,再生制动能量回收率提升至86.7%,功率因数提升6.4%,对谐波特别是高次谐波含有率有较大改善,满足光伏电能高效消纳及综合利用、电能质量动态综合补偿、再生制动能量回收多重需求.

矩形管道PV/T集热器在企业中应用的实验研究

设计并构建基于矩形集热管道的光伏光热系统,将该系统与工厂原有的余热回收系统相结合,扩大太阳能的应用领域,提高PV/T组件的热效率与电效率。利用COMSOL软件对PV/T组件温度场仿真分析,得到光伏板及集热管道温度的具体变化情况,并与实验结果相验证,实现热能与电能的协调控制。搭建1000块PV/T板,环境温度24℃左右时,每日可将100m3水池升温18.6℃,用于工厂冬季供暖和居民生活用水,该PV/T组件最大热效率为44.1%,每日发电量约为741KWh,用于提供余热回收系统在用电高峰时耗电,相当于每日共节约357.7kg标准煤。该系统兼具了节能和环保的作用,促进了企业可持续发展,充分体现了光伏光热系统在工业企业实施的可行性,为双碳目标的实现做出贡献。