为了提高阀门智能控制的工作效率与阀门的智能化、数字化,该研究对阀门智能控制进行了研究,设计了基于信息技术的阀门智能控制系统,包括CAN通信接口、单元控制器和阀门智能控制器节点三大部分,采用微控制器技术,实现了智能阀门的数字控制和智能控制;利用CAN总线技术,构建两级总线智能阀门控制系统,实现智能阀门的集中控制;设计了阀门远程控制的软件系统,利用了 PLC中央处理器及远程控制模块的方式,实现了阀门的远程操作,最后利用自适应控制算法,实现阀门参数的自整定,在此基础上依据系统的响应,进而实现阀门参数的自校正;实验表明,该研究的系统在进行阀门位置定位测试时,定位误差均低于10％,并且在进行智能阀门远程控制响应时间测试时,在系统迭代次数为900次时,响应时间为60s,相对较低,可见该研究的系统定位精度较高,响应速度较快,性能较好.

当前,对电力系统输电通道的风险评估手段以规则方法为主,往往对输电线路结构本身的特征考虑较少.基于KNN、决策树和SVM模型,提出了一种融合改进SMOTE与Stacking的机器学习算法,实现了对输电通道中树线放电因子的风险评估预测,该算法能较好地解决数据集没有明确正常样本数据,且异常样本类型分布不平衡的问题.通过与Bagging集成算法、融合SMOTE与Stacking算法对比,验证了所提算法的有效性与先进性,为后续输电通道其他因子基于机器学习的风险评估奠定了基础.

As for the reactive power compensation device capacity judgment at the low end of traditional 500 kV substation is relied only experience and without systematic calculation method,in this paper,the comprehensive allocation for the low end compensation capacity of 500 kV substation is determined by way of analysis and comparison.On the basis of the reactive power flow situation and existing allocation condi-tion of the reactive power compensation in 500 kV grid in Jiangsu Province,the practical method of the re-active power compensation allocation for 500 kV substation is proposed from such three aspects as reactive power local compensation and hierarchical partitioning equilibrium,the reason of installing reactive power compensation device for 500 kV substation and the limit compensation capacity for the busbar voltage of 500 kV substation operating within reasonable range.The simulation calculation is made with the simpli-fied simulation model which is set up in power system analysis software package(PSASP).The three meth-ods are analyzed and compared with combination of actual case so to provide reference for the plan and de-sign of substation

大规模分布式电源的并网给潮流计算中拉丁超立方抽样法的应用带来了新的问题.为解决分布式电源的累积分布函数较难获得以及相关性控制中相关系数矩阵非正定两个问题,提出了一种基于修正相关系数矩阵的改进拉丁超立方抽样法.该方法可根据离散数据,进行分层抽样得到样本,并采用正定谱分解法修正使得相关系数矩阵都能进行Cholesky分解,修正速度快误差小,毫秒级的速度便可使误差达到10-4.采用IEEE 33和PG&E69两个节点系统,验证了修正算法的准确性和有效性.仿真结果表明该方法计算速度快,在采样与输出变量的准确性和收敛性方面都要优于蒙特卡罗.

An algorithm for probabilistic load flow considering the correlation between input variables was proposed.A Gaussian mixture model (GMM) was established by the algorithm to represent non-Gaussian input variables in the system.On such a basis,a Gaussian component combination method (GCCM) was introduced and the marginal distribution of any output variable was directly obtained from multiple weighted least square runs (WLS).A study was also carried out to reduce the number of trials by limiting the number of Gaussian components.The simulation and error analysis on IEEE-30 test system indicated that GMM had the features of high fitting precision and wide applicability.The results obtained from the proposed method are identical to that of MCS and the computational efficiency is obviously improved.The effectiveness and the accuracy are proved to be closely related to operation times of WLS.

With the growing scale of new energy, new energy power contribute often exhibit a strong correlation, traditional random flow algorithm for strong correlation random variables was considered less. A method of probabilistic power flow algorithm based on semi-variable and Gram-Charlier series expansion was proposed in this paper. According node voltage and branch current expectations and sensitivity matrix, with wind power output, load changes, forced outages and generator fault lines and other uncertainties considered, load and conventional generators, wind turbine output and each node injection power of each order half invariant were calculated. Probability density function and probability distribution function were obtained by Gram-Charlier series expansion. IEEE-30 node test shows that the algorithm can reflect the uncertainty of large-scale new energy accessing to the system, and probability density function can be simplified to the semi-invariant algebra. Greatly reduce the computation time and it has a good convergence.

With the continuous increase of the proportion of distributed generations (DG) in distribution grids, power systems face more and more challenges, such as the increase of uncertainty and the change of grid structure.The conventional load flow calculation method is unable to deal with such a great number of uncertainties in grids.In order to solve this problem, a probabilistic load flow calculation method based on the imperialist competitive algorithm (ICA) is proposed, which can easily take into account all kinds of topology structures, different DG penetration levels and multiple constraint conditions of complicated networks, with good convergence as well.Moreover, for the purpose of improving the searching ability and convergence rate of the algorithm, a clone evolution operator is introduced in ICA.The modified IEEE-33 distribution system is used for simulation and the results are compared with those obtained via Monte Carlo simulation (MCS).It is found that the proposed method is of high precision and great practical value.

综合考虑风电出力的随机波动、负荷的变化、发电机的强迫停运及线路的故障等各种不确定情况,针对大规模新能源接人电网产生随机扰动,对非线性蒙特卡罗法进行线性化处理,得到节点电压及支路潮流的概率分布.采用IEEE-30节点算例,基于提出的随机潮流算法研究了大规模风电接入对电网电压越限率和潮流分布的影响.结果表明,风电场接入点附近电压和支路功率随机波动范围明显增加,所提算法能反映大规模新能源接人下系统的不确定性和多个新能源电站出力相关性,为电力系统规划和决策人员提供有价值的信息.

面对各种智能算法在优化问题的应用中出现的问题,提出一种基于量子计算和混沌局部搜索的布谷鸟算法.混沌局部搜索采用切比雪夫映射产生的混沌数列,以产生的新最优个体替代原始最优个体,并利用量子旋转门更新其余个体,达到更快收敛并跳出局部解的效果.以随机最优潮流问题作为修正布谷鸟算法的应用场景,考虑分布式电源和负荷的随机性,建立随机最优潮流的机会约束模型,机会约束的处理采取修正变量上下限的方式.以IEEE33节点为算例,对比了4种不同智能算法的计算结果和收敛情况,验证了修正的布谷鸟算法在随机最优潮流中收敛速度快,收敛结果好,稳定性好的特点.

A probabilistic load flow method considering the correlation between input variables based on improved Monte Carlo simulation ( MCS) is proposed . Regarding the behaviors of diversity and randomness for variable input , the method establishes the Gaussian mixture model ( GMM ) for variable input and performs parameter estimation by the use of measured data . Uniform design sampling ( UDS) is introduced to improve the sampling efficiency , and correlated samples are generated by marginal transformation and Cholesky decomposition . Moreover , multi‐linearization is applied to reduce the truncated error as well as time consumption . The simulation results of IEEE 30‐bus and IEEE 118‐bus test system verify the effectiveness , accuracy and practicability of the proposed method .

为更好地应对大功率区外来电对电网调度和安全稳定运行的影响,在分析了江苏电网区外来电现状的基础上,从发用电平衡面临新的压力、省内电源调节压力增大和发电利用小时数偏低等方面研究了内外电源协调运行面临的主要问题,提出了调节义务分摊机制和辅助服务补偿机制等内外电源协调运行机制.

为了研究沿海地区密集型大规模风电场出力特性以及相互关联性,以江苏沿海大规模风电为例,基于EMS系统中的实测风电出力数据,对风电场之间的有功出力相关性、概率分布、月最大出力进行了分析,研究了风电场的有功出力波动情况,并探讨了风电有功出力对江苏电网综合负荷、调峰的影响.对于分布式新能源利用率的提高和调度运行的优化具有重要意义.

线损水平与电网类型密切相关,单纯以实际线损率作为考核标准来评价不同电网的线损水平有失科学性。为了建立科学合理的线损水平评价方法,构建了考虑电网结构、设备参数、电网运行和用电结构等电网特征的线损评价指标体系,建立了所有指标的数学模型。在各个底层指标评价值的基础上采用层次分析法分析得到线损评价综合值。对电网线损评价值与实际线损率分别进行排序,通过分析排序的差异客观评价地区电网的线损水平。通过IEEE-14算例仿真分析了典型指标对线损率的影响;以江苏电网为例进行了线损水平评价。结果表明:所提出的典型指标能够反映不同电网特征对地区电网线损的影响,该方法为电网线损水平评估提供了量化计算依据,可广泛应用于评估各省、市或县级电网的线损现状,解决评估降损空间这一难题。

建立了一种考虑尾流效应和地形因素的实际大型风电场综合模型.在此基础上,分析比较了3种随机潮流算法(MCS、线性MCS和半不变量法).在半不变量法中,提出了一种新的基于蒙特卡罗抽样技术的方法,解决了风电场出力的半不变量难以用数值方法求解的困难.依托IEEE-30节点系统进行随机潮流计算,对比分析了风电场接入前后及负荷变化对系统潮流的影响,从计算精度和耗时两个方面比较分析了3种算法各自的特点,利用潮流计算结果得到了表征系统静态安全性能的各项评估指标.

随着江苏特高压电网的不断发展,区外来电的可靠性对保障地区供电具有重要意义.特高压直流等大规模区外来电在受端电网需要各个省级电网支撑和分担,当双极闭锁等情况损失的电量需要进行分摊,电网潮流重新分布.以实际发生的锦苏直流闭锁历史事件为背景,分析了区外来电失去后本地电源的响应特性和外省电源的支撑特性,对于应对区外来电损失后的潮流控制提供借鉴.

通信技术是输电线路在线监测数据可靠传输的关键.然而在部分偏远地区,公网通信条件较差,未铺设光纤,专网部署成本过高,通信方式成为输电线路业务发展的主要技术瓶颈.针对这一问题,文章将北斗卫星短报文技术应用在输电线路在线监测系统中,在现场布置一体化通信系统,主站系统采用多指挥机扩展并联方式,并通过增加消息队列和确认重发机制来提高通信的可靠性,实现了状态监测数据的实时回传.文章相关研究很好地解决了偏远地区数据传输问题,实现了输电线路在线监测装置数据的无线接入.

输电线路状态监测业务是一个系统工程,涉及监测选点设计、通信方案设计、数据安全、技术选型及安装设计等多个环节.在设计环节,急需系统的、典型化的设计方案作为指导依据.文中重点探讨了输电线路状态监测系统在不同设计阶段的设计深度,并根据状态监测技术发展及应用现状,提出状态监测选点设计指导原则、典型状态监测通信设计方案、状态监测设备的安装设计建议.总结了各种通信方案的技术特点和关键技术指标计算方法,并提出状态监测业务及各种典型通信方案的适用范围和选择依据,为工程设计提供参考依据.

静止无功补偿器(Static Var Compensator,SVC)作为一种常用的无功补偿设备,当电压变化时能快速、平滑地调节[1],有效解决负荷所产生的无功冲击,明显改善电网电压波动,提高系统功率因数[2].同时,SVC还能做到分相补偿[3],对于三相不平衡负荷及冲击负荷有较强的适应性[4].

随着智能电网技术的发展，输电线路在线监测得到了广泛应用。然而在数据采集选点、通信技术应用、电源取能及储能技术方面仍旧缺乏统一的技术原则。基于此，文章从输电线路各类在线监测装置数据采集选点、通信技术及组网方式、能量采集和能量存储技术等方面开展了研究，提出优选方案用于指导输电线路在线监测系统规范建设。