基于模糊TOPSIS方法的变压器维修策略

变压器维修策略的决策是一种涉及到量化指标和定性分析指标共存的混合多属性指标的决策问题.运用模糊理想解法(fuzzy TOPSIS)建立了变压器维修策略的模糊综合评价分析模型,来解决含有混合多属性指标决策问题.这种方法不仅可以对多台变压器的运行情况进行监视,通过利用计算相对贴近度来确定变压器的运行状态,进而确定变压器的维修策略,而且还可以通过专家系统对1台变压器的多种维修策略进行直接的判断与确定,通过精确的实数型指标值、区间数型的指标值和模糊数的指标值进行分类判断,给出多种维修策略下的取值情况,进而分析比较各个相对贴近度的大小,做出排序,决定选取哪种维修策略.通过实例验证此方法具有良好的决策效果.

基于熵权TOPSIS法的火电厂选址综合决策

目前火电厂选址的综合评价方法主要依赖专家评判确定指标权重,主观性强、评分标准难以准确把握及合理运用。本文针对以上不足,将基于熵权的TOPSIS法应用于火电厂选址的综合决策,通过运用熵权法客观确定了选址评价体系各指标的权重,并构造了理想解与负理想解,以方案指标向量靠近理想解、远离负理想解来判断确定方案的优劣,同时结合实例说明了应用熵权TOPSIS法进行火电厂选址综合评价的具体过程,并验证了基于熵权TOPSIS法的科学性和可行性。

低频减载方案基础集的设计及TOPSIS多属性决策

针对目前电力系统低频减载方案设计中基础方案集合过小、方案各性能指标相互矛盾难以决策的问题,提出了一种新的方案基础集设计方法及基于TOPSIS的方案决策方法。新的方案基础集设计方法根据低频减载方案的构成及参数特性的分析,确定了各参数取值集合的计算方法,并按方案的构成形式将各参数取值集合进行有机组合,最终形成方案的基础集。所设计的基础方案集合域大,并且可通过集合的设定值直接决策,避免传统决策中因性能指标冲突而难以决策的缺点,具有强的实用性。另外根据低频减载方案决策问题的特性,并结合优化理论中的TOPSIS多属性决策方法(MADM),提出了基于TOPSIS的方案决策方法。该方法可对基础方案集中的各方案的评价指标给出综合定量评估,解决了以往方案决策过程中方案各指标相互矛盾、难以筛选最优方案的问题。最后给出了算例分析,证明了所提理论方法的有效性和实用性。

基于改进TOPSIS法和德尔菲——熵权综合权重法的电网规划方案综合决策方法

针对目前电网规划方案综合决策问题中客观数据利用不充分和权重分配不合理的问题,提出一种基于改进TOPSIS法和德尔菲—熵权综合权重法相结合的电网规划方案综合决策方法。首先,根据电网规划的发展特点和基本属性,构建了考虑安全、效益、成本和适应性的电网规划SECA综合评价指标体系。其次,应用博弈论模型得到德尔菲—熵权综合权重计算方法。然后,引入绝对理想点以及投影法对TOPSIS法进行改进,并采用改进TOPSIS—德尔菲—熵权组合评价进行电网规划方案评估。最后,利用实际算例验证了该方法的有效性。TOPSIS法与综合权重法相结合充分利用了客观数据全部信息,并且同时具备了TOPSIS法简单实用、可操作性强以及综合权重法主客观均衡的优势。

基于TOPSIS算法的电力通信网关键节点识别

电力通信网某些关键节点对于网络安全可靠运行有着重要意义。为识别关键节点,提出一种基于TOPSIS(Technique for Order Preference by Similarity to an Ideal Solution,TOPSIS)算法识别电力通信网关键节点的方法。首先构建节点重要度评价体系,将每个节点看作一个方案,将评价指标看作方案属性,将主观赋权法中的层次分析法和客观赋权法中的熵权法相结合,求得综合权重。然后给每个评价指标赋权。最后采用多属性决策的方法求得节点重要度,根据重要度值的大小识别出关键节点。采用某省实际电网进行检验,仿真证明,相对于现有其他算法,该算法能更准确地识别关键节点,验证了该方法的实用性和有效性。

Power Aggregation Operators of Simplified Neutrosophic Sets and Their Use in Multi-attribute Group Decision Making

The simplified neutrosophic set(SNS) is a useful generalization of the fuzzy set that is designed for some practical situations in which each element has different truth membership function, indeterminacy membership function and falsity membership function. In this paper, we develop a series of power aggregation operators called simplified neutrosophic number power weighted averaging(SNNPWA) operator, simplified neutrosophic number power weighted geometric(SNNPWG) operator, simplified neutrosophic number power ordered weighted averaging(SNNPOWA) operator and simplified neutrosophic number power ordered weighted geometric(SNNPOWG) operator. We present some useful properties of the operators and discuss the relationships among them. Moreover, an approach to multiattribute group decision making(MAGDM) within the framework of SNSs is developed by the above aggregation operators.Finally, a practical application of the developed approach to deal with the problem of investment is given, and the result shows that our approach is reasonable and effective in dealing with uncertain decision making problems.

Linguistic Single-Valued Neutrosophic Power Aggregation Operators and Their Applications to Group Decision-Making Problems

Linguistic single-valued neutrosophic set(LSVNS)is a more reliable tool,which is designed to handle the uncertainties of the situations involving the qualitative data.In the present manuscript,we introduce some power aggregation operators(AOs)for the LSVNSs,whose purpose is to diminish the influence of inevitable arguments about the decision-making process.For it,first we develop some averaging power operators,namely,linguistic single-valued neutrosophic(LSVN)power averaging,weighted average,ordered weighted average,and hybrid averaging AOs along with their desirable properties.Further,we extend it to the geometric power AOs for LSVNSs.Based on the proposed work;an approach to solve the group decision-making problems is given along with the numerical example.Finally,a comparative study and the validity tests are present to discuss the reliability of the proposed operators.

Power Aggregation Operators and Similarity Measures Based on Improved Intuitionistic Hesitant Fuzzy Sets and their Applications to Multiple Attribute Decision Making

Intuitionistic hesitant fuzzy set(IHFS)is amixture of two separated notions called intuitionistic fuzzy set(IFS)and hesitant fuzzy set(HFS),as an important technique to cope with uncertain and awkward information in realistic decision issues.IHFS contains the grades of truth and falsity in the formof the subset of the unit interval.The notion of IHFS was defined by many scholars with different conditions,which contain several weaknesses.Here,keeping in view the problems of already defined IHFSs,we will define IHFS in another way so that it becomes compatible with other existing notions.To examine the interrelationship between any numbers of IHFSs,we combined the notions of power averaging(PA)operators and power geometric(PG)operators with IHFSs to present the idea of intuitionistic hesitant fuzzy PA(IHFPA)operators,intuitionistic hesitant fuzzy PG(IHFPG)operators,intuitionistic hesitant fuzzy power weighted average(IHFPWA)operators,intuitionistic hesitant fuzzy power ordered weighted average(IHFPOWA)operators,intuitionistic hesitant fuzzy power ordered weighted geometric(IHFPOWG)operators,intuitionistic hesitant fuzzy power hybrid average(IHFPHA)operators,intuitionistic hesitant fuzzy power hybrid geometric(IHFPHG)operators and examined as well their fundamental properties.Some special cases of the explored work are also discovered.Additionally,the similarity measures based on IHFSs are presented and their advantages are discussed along examples.Furthermore,we initiated a new approach to multiple attribute decision making(MADM)problem applying suggested operators and a mathematical model is solved to develop an approach and to establish its common sense and adequacy.Advantages,comparative analysis,and graphical representation of the presented work are elaborated to show the reliability and effectiveness of the presented works.

Clustering Analysis of Black-start Decision-making with a Large Group of Decision-makers

The optimization of black-start decision-making plays an important role in the rapid restoration of a power system after a major failure/outage.With the introduction of the concept of smart grids and the development of real-time communication networks,the black-start decision-makers are no longer limited to only one or a few power system experts such as dispatchers,but rather a large group of professional people in practice.The overall behaviors of a large decision-making group of decision-makers/experts are more complicated and unpredictable.However,the existing methods for black-start decision-making cannot handle the situations with a large group of decision-makers.Given this background,a clustering algorithm is presented to optimize the black-start decision-making problem with a large group of decision-makers.Group decision-making preferences are obtained by clustering analysis,and the final black-start decision-making results are achieved by combining the weights of black-start indexes and the preferences of the decision-making group.The effectiveness of the proposed method is validated by a practical case.This work extends the black-start decision-making problem to situations with a large group of decision-makers.

Apply to the Micro Grid Data Limit Learning Algorithm

More and more microgrid projects are put into operation and completed, and the load data are becoming more and more multidimensional and massive. This requires effective classification of load data. Most of the traditional processing methods are based on neural network to classify the grid data. However, with the development of microgrid, the traditional neural network algorithm is having a hard time meeting the requirement of the classification and operation of massive microgrid data. In this paper, the back propagation neural network (BPNN) algorithm is parallelized based on the traditional reverse neural network algorithm. Multiple algorithms are applied for data learning, for example, the combined application of extreme learning algorithm and simulated annealing algorithm, artificial fish swarm algorithm and other evolutionary algorithms. The input variables in BPNN are optimized in the network training process. After adding the algorithm fitness evaluation function, the combined algorithm of improved back propagation neural network algorithm came out. It is most in line with the real-time data of power grid by means of root mean square error. This result could provide data support and theoretical basis for load management, microgrid optimization, energy storage management and electricity price modeling of microgrid.

工程博弈论-工程优化决策中的博弈思想、原理及应用

实际工程优化决策问题中经常会面临多决策主体、多决策目标以及不确定性等复杂场景,常规的优化决策方法有较大局限性.受钱学森先生名著《工程控制论》的启发,将工程决策问题中应用博弈论基本概念、建模方法、求解算法并考虑复杂工程技术条件进行决策的理论称为“工程博弈论”.本文简要介绍了博弈论的基本理论,并阐释了工程博弈论“以均衡协调冲突”的基本思想.在此基础上分别介绍了不确定性决策问题的非合作工程博弈原理、多目标决策问题的合作工程博弈原理和多主体决策问题的演化工程博弈原理及其在能源电力系统中的部分典型工程应用.本文希望通过对相关进展的介绍可以吸引更多的研究者进入这一领域,共同完善工程博弈论的相关基础理论和方法,使之在更多的领域中得到更广泛的应用.

基于绿电减排量互认的建筑虚拟电厂电-碳双层协同决策机制

在“双碳”背景下,电-碳多政策并举和多市场并存局面带来了电能环境权益重复奖惩的问题。针对该问题,提出了基于减排量等效的绿色电力-国家核证自愿减排量(CCER)互认方法,将绿色电力的环境权益统一归属至用户侧,并以建筑主体为研究对象对互认方法进行验证。首先,依据减排特性差异,将建筑分为强制性建筑、减排性建筑、零碳建筑3类,以建筑虚拟电厂为CCER互认的代理。其次,针对建筑虚拟电厂内部CCER分配问题,提出了基于Shapley值法的分配方法,以保证分配的公平和合理性。然后,针对建筑主体面临的电-碳协同决策问题,提出了基于能源共享原则的电-碳双层协同交易机制,并基于主从博弈理论构建双层决策模型,结合供需比概念对模型进行凸化。最后,通过算例仿真验证了互认方法的可行性及电-碳双层协同决策机制的有效性。

女性就业、家庭决策权及其幸福感

经济赋权是增进女性获得感、安全感和幸福感,实现共同富裕的重要措施。使用2017年中国综合社会调查数据(CGSS),采用OLS模型,实证检验女性就业参与对其幸福感的影响及作用机制。研究表明:有薪酬的劳动力市场就业参与对女性幸福感存在显著的积极影响,已就业参与女性较未就业参与女性的幸福感明显更高。该结论在利用处理效应模型(TEM)和拓展回归模型(ERM)尽可能缓解内生性问题,以及进行一系列稳健性检验后,仍然成立。异质性分析表明,对于性别分工观念平等、性别就业价值观念平等以及配偶在业的女性,其就业参与的幸福效应更强。机制分析表明,家庭决策权是女性就业参与提升其幸福感的重要渠道。已就业参与女性在父母奉养、子女教养和家用支出分配等方面拥有决策权的概率,分别是未就业参与女性的1.514倍、1.471倍和1.276倍。拓展分析表明,与未就业参与相比,非正规就业参与、正规就业参与均能有效提升女性幸福感。因此,增进女性福祉,既要鼓励女性有薪酬的劳动力市场就业,又要发展并规范非正规就业劳动力市场,还要树立平等的性别观念。

食品安全风险监测计划何以高效决策?——基于组织规范构造的视角

食品安全风险监测计划决策的时效性、科学性乃至执行效率,往往受制于相关政府职能部门的组织机构建制水平。有必要基于组织规范构造的视角,围绕所涉政府职能部门的权责配置与职权行使事项,来系统性约束和保障其机构能力。一方面,应针对专有权责与共有权责来设定其权责配置规范,以彰显相应职能部门在该类决策过程中的差异性决策设计与多元化决策考量。另一方面,应针对监测计划设置与监测信息传递来设定其职权行使规范,以厘清相应职能部门在该类决策过程中的内部决策定位与外部决策整合。最终尝试依托复合决策维度中、决策要素驱动下的协同履职,来明晰实现高效决策的可行规范进路。

异地独立董事与上市公司高质量发展——基于高铁通车与独立董事履职的视角

独立董事的尽责履职对推动上市公司高质量发展具有重要意义。文章以2004—2020年我国A股上市公司为样本,从独立董事履职的视角,对异地独立董事如何影响上市公司高质量发展进行了实证研究,并考察了高铁通车在其中的调节作用。研究发现,异地独立董事对上市公司高质量发展具有显著负向影响,高铁通车则有效缓解了这一影响。机制检验发现,异地独立董事因为监督、咨询和决策无效而不利于上市公司高质量发展,高铁通车则主要通过改善监督和咨询职能的发挥,缓解上述不利影响。进一步研究发现,高铁通车后不同背景特征的异地独立董事对上市公司高质量发展存在差异化影响。具体而言,高铁开通后,具有行业专长、学术背景、海外背景的异地独立董事比例与上市公司高质量发展显著正相关;而不论高铁是否开通,具有法律、财务背景的异地独立董事比例与上市公司高质量发展显著负相关。

新型电力系统中火电机组运营智慧决策系统

火电机组目前面对电力中长期合约市场、现货市场、辅助服务调峰调频市场,民用供热及工业供热等多种电热产品售卖途径,需要根据市场交易机制、运营成本及碳排放成本,在各种市场中优化分配有限的火电机组电热产品以获取最大利润。提出了火电机组运营智慧决策系统,采用通用开发平台,考虑了实时热电成本分摊、实时热电转换比、实时平衡利润比等,该智慧决策系统可以帮助火电企业实现实时的经营核算,并给出各级市场最优组合竞价策略及提供机组最佳运行方式。

超大型城市虚拟电厂的数字孪生框架设计及实践

超大型城市能源系统汇集了多种分布式能源资源(distributed energy resources,DER),包括具备不确定性的新能源发电单元(如光伏、风机),具备可调性的柔性用能单元(如空调、蓄冷)以及兼具充放功能的能源产消者(如电动汽车、储能),虚拟电厂(virtual power plant,VPP)已成为重塑上述DER生态关系并对其进行协同管控的有效途径。该文梳理了当前城市级VPP建设的目标与现状,明确了超大型城市VPP工程所面临的挑战,即对于由海量DER所诱发的多主体多目标高不确定性场景缺乏系统性的建模、仿真、推演、分析、决策与校核手段。为应对上述挑战,该文结合城市电网数字化整体架构与建设进程,提出了超大型城市VPP数字孪生技术框架,继而得以对城市能源系统的态势轨迹进行系统性地推演与分析;进一步,聚焦智能决策目标,探究了框架下的技术路径、关键技术、理论工具等。该框架已经助力临港新片区VPP工程示范落地,为城市级VPP建设提供参考。最后,展望了超大型城市下数字孪生VPP的研究方向与应用前景。

基于主从博弈的工业园区运营商与分布式光储用户购售电优化决策

随着分布式光伏大量接入园区用户侧,其随机性与波动性使得工业园区微电网下的能量管理愈发困难,储能为缓解上述问题提供了有效的手段。为实现园区用户侧新能源高效消纳及储能资源合理利用、兼顾多园区用户的利益诉求,提出一种基于主从博弈的工业园区运营商与分布式光储用户购售电优化模型。模型中利用工业园区用能运营商对多用户的能量进行统一管理,利用价格信息引导园区用户调整用电策略,利用分布式储能“低储高发”特性协调运营商与用户间的能量交互;并通过仿真算例验证所提方法的可行性和有效性。结果表明:基于主从博弈的工业园区运营商与分布式光储用户购售电优化决策,能够兼顾园区运营商和用户的经济性,促进新能源与储能的协同发展。

国内外无人机系统研究进展及应用

随着人工智能和无人机(Unmanned Aerial Vehicle,UAV)技术的深度融合,UAV已成为现代战争中的一把利器,各大军事强国均在竞相研发,力求在未来战争中占据制高点。概述了美国、中国、俄罗斯、英国和以色列等军事强国正在发展的UAV系统现状,总结了其最新研究进展和典型成果;在此基础上,从6个不同方面介绍了UAV系统作战所需的关键技术,并结合近年多场局部冲突中的UAV实战应用,梳理了其典型应用场景。旨在为UAV技术发展以及应用落地提供参考。

基于调和概率语言术语集的Power平均算子

实践发现现存概率语言Power平均算子在应用中存在概率信息丢失、计算过于繁琐等问题,针对这些问题,提出一种基于调和概率语言术语集的Power平均算子。结合新的基本运算法则与新的支撑度,给出新的概率语言Power平均算子、概率语言Power几何平均算子、概率语言Power加权平均算子、概率语言Power加权几何平均算子,同时论证分析了这几类新型算子的性质。最后通过实验数据,将提出的算子与现存算子进行对比分析,验证了所提算子的有效性与可行性。