针对蚁群算法求解配电网重构问题时搜索时间过长、易陷入局部最优解等问题,提出了一种基于序优化理论和模糊控制理论改进的蚁群算法应用于配电网重构。通过加入模糊规则,结合序优化思想,在信息素更新环节提出了分阶段按序更新策略,扩大解空间的探索;将Prim算法应用于搜索环节,直接得到辐射型可行解,大大减少了构造解的时间;结合模糊理论提出了多目标的目标函数,有利于得出高质量的解。选取IEEE33节点配电系统作为算例验证了算法的有效性和优越性。

New energ y acce ss t he power distribution system on the large scale, increases the uncertainties of the operating parameters of power system. There are two aspects to the key issue of achieving the new energy grid system stable operation:establishing reasonable optimization model of photovoltaic power generation grid-connected system, and providing the voltage limit interval and system rational "carrying capacity" based on stable operation conditions. Therefore, we put forward the application of the interval optimization algorithm for realizing the operation parameter optimization of PV grid-connected system. The power source capacity of the photovoltaic power grid node was used as the objective function, and the distribution network node voltage and branch power characteristics as the constraint conditions, a nonlinear model of the interval optimization was created in regard to the photovoltaic power generation system. The deterministic model transformation of objective function and constraint condition using the interval possibility and interval order relationship were completed. Two nested interval optimization functions were established in order to achieve the minimum node voltage fluctuations and the minimum network active power loss. The interval boundary function of the active capacity and the node voltage as the constraint condition. It sets up the optimization model of multi-node PV grid-connected system was used to combine the active power inequality constraints and the regulation of PV grid-connected. The optimal solution of robustness was obtained. The simulation of IEEE 33 node power distribution system had the best effect to improve the voltage of the end node of the distribution network. The voltage of the end node was enhanced by 3.3% - 11.8%, with the optimal range of the end node voltage lower boundary [9.8277, 9.8367], the accuracy of node voltage lower boundary being from -5% to -1.72% the optimal range of active power loss being [131.6576, 143.4365] with the reduction of the active power loss by 63.8% - 66.8% compared with no PV grid-connected system. The first-end power optimization interval was [30.446, 354.59], achieving the active power maximum adjustment peak 354.59kW, which provided the reliability of the operation for the photovoltaic power grid-connected system. The method had the characteristics of high precision and fast convergence suitable for improving the condition of the voltage at the end of the rural distribution network. The PV grid-connected configuration scheme could be provided by utilizing the interval optimization method, which could provide an important theoretical basis for the future power distribution network reconstruction.

Due to the random feature of wind power,the access of large numbers of wind turbines brings high uncertainties to the reactive power optimization of distribution network.In order to improve the adaptability of reactive power optimization to the wind turbines,this paper proposes a new model for multi-objective reactive power optimization of distribution systems integrated with wind power based on scenario analysis under multiple load levels.Two indexes,including net savings and nodes voltage deviation,are synthetically considered in the model.Through fuzzing of the two indexes,the maximum fuzzy satisfaction index method is used to transform the multi-objective optimization problem into a single objective problem,which is then solved by the adaptive genetic algorithm.By using a 33-bus testing system as an example,the capacitor switching,power loss,node voltage and net savings are analyzed with the proposed algorithm under different scenarios and three load levels,including maximum load,normal and minimum load.The case study shows that the proposed model and method can effectively improve the voltage profile of distribution system and significantly reduce the power loss,and can be applied to the reactive power optimization of distribution system integrated with wind power generators under multiple load levels.

In view of the nonlinear and non-stationary characteristics of wind power time series,this paper presents a modified ensemble empirical mode decomposition (MEEMD)-sample entropy (SE)-ARMA wind power ultra short term combined forecasting model.The white noise signal added in the EEMD decomposition is changed to two groups positive and negative white noise signal which have the equal absolute value,and the EMD steps of the decomposition process of MEEMD is improved with the endpoint extension and three piecewise Hermite interpolation,forming a modified EEMD decomposition algorithm (MEEMD).The wind power time series is decomposed into a series of complex wind power generation by MEEMD-SE,and the ARMA forecasting model is built for each different sub sequence,and the final wind power forecast value is obtained.Through numerical analysis and comparison with other forecasting models,the results show that the MEEMD-SE-ARMA combination forecasting model can effectively improve the accuracy of the ultra short term forecasting of wind power generation.

In order to improve the accuracy of the ultra short term forecasting model of wind power, original wind power time series are decomposed and reconstructed by wavelet transform to get corresponding high frequency sequences and low -frequency sequences. The corresponding autoregressive moving average model is established according to different sequences,as well as the Lagrangian multiplier test is mainly used to verify whether there is a Lagrangian multiplier effect,so as to establish the corresponding autoregressive conditional heteroskedasticity model or generalized autoregressive conditional heteroscedasticity model.The final forecasting results are obtained through the linear superposition and combination. Through the case study and the comparison with the forecasting results of several other forecasting models,the consequences show that the combination model of wavelet transform and time series can effectively improve the accuracy of the ultra short term forecasting model of wind power.

ABSTRACT:In order to mine the deep information contained in the wind power big data and explore the law of the wind farm operation and offer guidance for the practical wind farm operation in a scientific, proper, and economical way, the research on the wind power farm operation data analysis is done in this paper. With the operation data of the SCADA system of the wind turbine generator as the main research target,with analysis of the power big data as the basic train of thought,and econometrics and statistics as the main research method,this paper proposes the level structure of wind power farm data analysis,and summarizes the classification frame structure and analyzes the performance characteristics of the various parame-ters of the wind turbine generator and verifies the necessity of research in the current hot points in the wind power sector based on the data analysis.

为降低风力发电厂并网后对电网稳定性和波动性的影响,风力发电功率的特性分析和预测显得十分重要。论文针对影响风力发电功率的气象因素,引用主成分分析和逐步回归分析2种方法,明确了风速和最低温度与发电功率的因果关系。在进行发电功率预测中以风速作为主因变量的条件,应用指数平滑模型、ARIMA模型、组合预测3种方法分别对风力发电功率进行了预测。组合预测是将前两种预测方法的优点进行组合,使预测结果的精确度得到进一步的提高。

分布式电源是一种分散配置在配电系统中的小规模发电系统，在推进美丽乡村建设中必将起到重要的作用。分析了户用风光互补系统建设的独立系统结构、并网系统结构、光伏发电并网的实现方式和并网控制系统、分布式电源运行监测系统、分布式光伏最大输出功率跟踪系统、分布式电源并网系统的电能质量问题、分布式电源与电网电源互补储热系统、分布式电源在农网应用实例等问题，指出发展分布式电源是推进美丽乡村建设的有效途径。

The magnetically controlled reactor in the wind farm had a slow reaction speed, it could not meet the requirements of fast reactive power compensation in the wind farm. In order to solve the prob-lem, a scheme of quick response magnetically controlled reactor which took advantage of improved wind-ing structure as well as the quick response principle was presented. The steady state operation process and steady state parameters were analyzed, and the quick response time expression was given. The simu-lation results showed that the current tracking speed of the quick response magnetically controlled reactor was quick, it could meet tracking time requirements of the fast reactive power dynamic compensation de-vice in the wind farm.

<span id="ChDivSummary" name="ChDivSummary" class="abstract-text">目前,对农村电网负荷的数据记录研究较少,农村电网的负荷记录仪器研究开发也较少,不利于农村电力系统的长期发展。针对农村电网负荷记录的问题,利用单片机技术,设计一种可应用于农村电网负荷实时记录的仪器。通过对仪器的仿真调试,使仪器达到数据记录的设计要求;通过在南疆第一师供电线路的负荷记录试验,结果表明:线路通电1h后,负荷由0变化至7 000kVA;当线路在送电后4h内,负荷变化至17 000kVA,达到带负荷运行状态;测量结果在一定时间内与线路电压、电流的变化值相同,得到的测量结果较为准确,满足农村电力系统的负荷记录。</span>

风力发电由于其清洁性、波动性、随机性及不稳定性,向电网输送绿色电能的同时也对电网的可靠运行造成了一定的冲击,因此风电发电量预测的准确性对电网科学合理调度、安全稳定运行具有至关重要的作用。以大数据分析、多学科交叉融合为背景,以负荷预测为基础理论,利用计量经济学分析方法对风电场月发电量数据进行分析、建模和预测。对辽宁地区某49.5 MW风电场月发电量数据进行收集整理,利用计量经济学分析软件EVIEWS对采样数据进行分析,并采用SARIMA模型对风电场月发电量数据进行拟合和预测,达到了较好的预测效果。

人才培养模式改革是提高高等教育质量的重要保证.在国家建设农村智能电网、电力企业对高技能型人才需求急剧的背景下,沈阳农业大学积极开展农电专业高技能型人才培养模式建设.以适应电力企业需求、提高就业质量和就业率为目标,以教学团队建设、实践教学条件建设等为基础,构建了“教、学、做、研”一体化高技能型人才培养模式,并取得了良好效果.

为了实现对并网型光伏电站调度,提出了一种基于集合经验模态能分解(EEMD)与BP神经网络的短期光伏出力的组合预测模型。利用集合经验模态分解将光伏出力序列分解,得到本征模函数分量IMF和剩余分量Res,降低序列的非平稳性。采用游程检验法优化因IMF分量数量多造成的建模过程复杂的问题,针对优化后的分量分别建立相应的BP神经网络预测模型。利用该方法对额定容量为40 k W的光伏系统进行预测,并与EMD-BP神经网络和传统的BP神经网络模型进行比较分析。结果表明,所提出的方法有效地提高了预测精度。

选择适当的智能变电站过程层组网方式,采用虚拟局域网技术对过程层交换机进行合理的VLAN划分,可大大提高交换机的使用效能,避免产生网络阻塞.介绍了智能变电站系统基本结构和组网技术,研究了智能变电站的过程层网络拓扑结构,并根据VLAN技术,探讨了网络的VLAN划分方案,同时结合工程实例提出了220 kV智能变电站具体的组网方案及VLAN划分实现方式.通过220 kV马山变电站的实例应用证明,独立星型双单网方式及基于端口的VLAN划分能有效地保证智能变电站过程层网络数据传输的实时性和可靠性.

在不同辐照强度和光伏电池温度、有无旁路二极管条件下,利用光伏软件PVsyst对多晶硅光伏电池组件及其单体电池的反向特性进行了研究,对不同旁路二极管数量、局部电池不同阴影率条件下的光伏组件输出特性进行了仿真.基于辐照强度、电池温度、旁路二极管对光伏组件及其电池反向特性的影响,对旁路二极管和局部电池阴影率对光伏组件发电性能的影响进行了分析.研究结果表明:当光伏电池加反向恒定电压时,随辐照强度、电池温度升高,流过电池的电流逐渐升高;当无旁路二极管的光伏组件加反向电压时,随反向电压升高,电流升高缓慢,当带旁路二极管的光伏组件加反向电压时,旁路二极管导通,电流急剧升高;当光伏组件局部电池被遮挡时随旁路二极管数量增加,光伏组件功率损失逐渐减小,当光伏组件无旁路二极管时随光伏组件局部电池阴影率升高,光伏组件输出功率持续下降.

Power flow calculation of power system is the basis of the operation and planning or implementation of a variety of academic research. With intermittent, random power output of wind generators and other evenly distributed power systems included in the calculation of the power active power flow, the probabilistic load flow is most widely used, which can effectively take great enhancement of the operating parameters or variables of uncertainty of the power grid into consideration after connecting the intermittent, random distributed power supply to the distribution network. However, due to the basically similar trend of the size of wind speed change within a region, which explains the existence of the strong correlation between the location of the wind power generators. The existing probabilistic load flow calculation research cannot effectively deal with questions about the relevance of wind speed random variables, which leads to lower efficiency of the probabilistic load flow computation and the lower accuracy of the results, and influences the correctness of a variety of research conclusion in the power system, or even endangers the power system security and reliable operation. In order to resolve the above problems, the rank correlation coefficient in statistics describing the correlation of wind speed random variables has been put forward to improve the accuracy of probabilistic load flow calculation. In the process of sampling of the wind speed, load and so on, the use of the Latin hypercube importance sampling technique based on the traditional Monte Carlo simulation method of random sampling has been proposed to improve the efficiency of the probabilistic load flow computation. To verify the effectiveness of proposed method (referred to as CMCS-LIS method), on the basis of the IEEE33 bus system and coupled with utilizing MATLAB software to compile the computer program simulation tests were carried out. Simulation results revealed that the proposed method could flexibly deal with the correlation between wind speed and other random variables and boost computational efficiency. Furthermore, it has a good reference value in engineering application.

With the rapid development of information technology, agricultural knowledge and data have seen explosive growth in the internet. It has become a major problem facing the field of agricultural informatization to realize the precise pushing of agricultural information. This paper proposes an agricultural knowledge-oriented self-adaption decision-making model, the AKDM (agriculture knowledge decision-making model), which actively collects knowledge and information in the internet using Agent software, and performs reasoning, analyzing and result delivering based on the information collected, and finally giving instructions on knowledge pushing. The result showed it was possible to realize the self-adaption decision-making with regard to agricultural knowledge by converting agricultural knowledge into a cluster of faith, will and intention and guiding information pushing behavior by the relations of decision-making and reasoning among them. Thus, the experiment in this paper provides a feasible model for the intelligent personalized pushing of agricultural information.

Wind power prediction is very important to improve the power quality and the safe operation of power sys -tem.The ultra short-term prediction of wind power data is carried out in a wind farm in Chifeng of Inner Mongola based on time series analysis , and the ARMA ( Autoregressive Moving Average ) model of time series is built through the stationary test of data.Through ARCH effect of the residual of ARMA model by Lagrange Multiplier (LM), the corresponding ARMA-GARCH model is set up .Through the comparison of the wind power prediction by using ARMA model , ARMA-ARCH model and ARMA-GARCH model respectively , ARMA-GARCH model possesses higher accura-cy on the residual sequence of the data with the long term correlation .

Voltage is an important assessment criterion of power quality. The low voltage phenomena (LVP) frequently appeared in the power distribution network especially at the rural areas of China, which had been key technical problem to be solved by the local departments of State Grid Corporation of China (SGCC). However, LVP happened mostly at the end of the rural medium voltage distribution system in the peak season, by which the electric power consumption of farming and farmers were seriously affected, and also lay behind the development of agricultural economy.Insufficient primary voltage of the distribution transformer was the main cause of rural low voltage phenomena. Increasing rural substation sites or the conductor section could also improve the power quality, but the investment cycle was too long and the rate of return lower. It is not suitable for large-scale popularization and application in rural areas. The thesis presented a synthesized optimal dynamic compensation method for low voltage in the whole electric power line, which was adopted practically and led in Xifeng medium voltage distribution network of Liaoning. First, based on the line voltage-regulation theory with voltage regulator and the terminal voltage monitored by feeder terminal unit (FTU), the voltage level of the whole electric power line was up to the national criteria with the power on-load tapping voltage regulator controlled by the remote host computer. In the meantime, at the basis of reactive power flow of the head line, and with the constraint condition of voltage in the nodes of reactive power compensators installed, the reactive compensation commands were sent by the remote host computer. The total reactive power capacity was 440 kvar (kilovolt ampere reactive) in each node of compensators,in which 50 kvar was as static compensation and the other as dynamic separated into 4 groups. According to the output of reactive power tide at the transformer substation, 1 static and 4 set of dynamic capacitor banks were composed of 17 different combinations in every compensation node, which was optimized for grouping parallel capacitor switch by the remote host computer based on the principle of reactive balance. Finally the national supervision standards of reactive power dynamic balance were reached after above computerized dynamic adjusting measures taken in the whole experimental power grid. The experimental results showed that the line power factor increased to 0.99 from 0.97 under the maximum power flow after the synthesized compensation implementation, and 10KV line active power loss rate decreased by 6 percent compared with before, and distribution transformer primary qualified voltage rate rose to 100% from original 22%. In the paper, several theories and methods of wireless communication and computer control and line-automation were integrated into the practical application example of comprehensive voltage compensation, which effectively improved the voltage level and fluctuating range, the qualified voltage rate and the power loss rate in the rural low and medium voltage distribution network.It has good reference value of engineering. The proposed methods also come up with new solutions for the intelligent development of reactive power compensation of rural substation.

目前,我国广大的农业生产经营者由于在信息分析、信息处理等方面的能力匮乏,导致农业生产技术发展与互联网发展速度不匹配,大量散布在互联网中的农业信息资源无法有效到达信息需求者手中.本文讨论并分析了农业信息推送服务可以针对不同的受众人群,采用多种手段和方式,将大量的农业科技信息、农产品供销信息等农业信息传播给用户,个性化农业信息推送服务模式可以较好的促进农业信息化的发展,给农业经济带来促进作用.