CN110795692A - A method for evaluating the operating status of active distribution network - Google Patents
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Abstract
一种主动配电网运行状态评估方法，包括：构建主动配电网运行状态评估指标体系；评估指标的一致化处理；确定优化组合权重；对各评价对象的运行状态进行距离综合评价，给出各评估对象综合运行状态的相对优劣顺序；属性区间综合评估：利用属性区间算法对主动配电网运行状态进行分析时需要构建属性测度区间矩阵，再利用级别特征值法确定最终评估等级。本发明的优点是：1、构建了表征主动配电网运行状态的评估指标体系；2、采用最小二乘优化组合基于层次分析法的主观权重和基于变异系数法的客观权重；3、利用属性区间算法，充分考虑了主动配电网运行状态中的模糊性特点，考虑了完整隶属度信息，最后得到的各指标综合评估结果科学有效。
An active distribution network operating state evaluation method, comprising: constructing an active distribution network operating state evaluation index system; uniform processing of evaluation indexes; determining optimal combination weights; The relative order of the comprehensive operation status of each evaluation object; comprehensive evaluation of attribute interval: when using the attribute interval algorithm to analyze the operation state of the active distribution network, it is necessary to construct an attribute measurement interval matrix, and then use the level eigenvalue method to determine the final evaluation level. The advantages of the invention are: 1. An evaluation index system is constructed to characterize the operating state of the active distribution network; 2. The least squares optimization is used to combine the subjective weight based on the AHP method and the objective weight based on the coefficient of variation method; 3. Use the attribute The interval algorithm fully considers the ambiguity characteristics of the active distribution network operating state, and considers the complete membership information. The final comprehensive evaluation result of each index is scientific and effective.
Description
技术领域technical field
本发明涉及一种基于组合权重、距离综合评价和属性区间算法的主动配电网运行状态评估方法，属电气工程领域。The invention relates to an active distribution network operation state evaluation method based on combined weight, distance comprehensive evaluation and attribute interval algorithm, and belongs to the field of electrical engineering.
背景技术Background technique
当今社会的发展离不开电力，迫切需要实现配电网的自愈控制以满足电力用户对配电网供电日趋增高的要求，而掌握配电网的运行状态是其实现自愈控制的前提。The development of today's society is inseparable from electricity, and it is urgent to realize the self-healing control of the distribution network to meet the increasing demands of power users on the power supply of the distribution network.
自愈控制可以赋予主动配电网(Active Distribution Network,ADN)更强的自愈能力，使其始终运行在一种良好的状态。主动配电网的运行状态会受其所处的环境影响，而其运行环境非常复杂，影响因素众多。表征配电网运行状态的指标非常多，为了达到通过运行状态评估导向合理控制策略的目标，首先需要针对主动配电网运行的特点，建立合理的评估指标体系、指标模型和评估方法，实现对主动配电网运行状态的评估，这是进行自愈控制的前提和关键内容。Self-healing control can endow Active Distribution Network (ADN) with stronger self-healing ability, so that it always runs in a good state. The operating state of the active distribution network will be affected by its environment, and its operating environment is very complex and there are many influencing factors. There are many indicators that characterize the operation state of the distribution network. In order to achieve the goal of guiding a reasonable control strategy through the evaluation of the operation state, it is first necessary to establish a reasonable evaluation index system, index model and evaluation method according to the characteristics of the active distribution network operation. The evaluation of active distribution network operation status is the premise and key content of self-healing control.
当前，主动配电网相关的研究热点主要集中在分布式能源接入规划、电能质量监测装置、主动调度、控制和优化投资、经济效益等方向，关于运行状态综合评估方法的研究成果较少。申请号为201810885635的发明专利提出一种主动配电网电能质量综合评估方法，其主要思路仅仅针对主动配电网的电能质量问题的综合评估；申请号为201810013969的发明专利提出一种基于TOPSIS法的含分布式电源的主动配电网可靠性评估方法，但其对主动配电网除可靠性外的运行状态指标没有提及；申请号为201711023109的发明专利提出一种基于效用函数的主动配电网运行态势评价方法，但其权重确定方法仍是主观性较强的单一层次分析法来确定权重。本发明专利针对各种影响主动配电网运行状态多指标、多属性、模糊性的特点以及传统评估权重确定主观性过强的问题进行了研究，建立了主动配电网运行状态评估指标体系，分别从配电网运行状态的内部对象相对优劣性和具体指标等级两个角度，优化组合了主客观权重，并采用距离综合评价法和属性区间算法对主动配电网运行状态进行了综合评估，并通过雷达图给出所有评估对象的各项指标的评估结果。At present, the research hotspots related to active distribution network mainly focus on distributed energy access planning, power quality monitoring devices, active scheduling, control and optimization of investment, economic benefits, etc., and there are few research results on comprehensive evaluation methods of operating conditions. The invention patent with the application number 201810885635 proposes a comprehensive evaluation method for the power quality of the active distribution network, the main idea of which is only for the comprehensive evaluation of the power quality problems of the active distribution network; The reliability evaluation method of the active distribution network with distributed power generation, but it does not mention the operating state indicators of the active distribution network except reliability; the invention patent application number 201711023109 proposes a utility function-based active distribution network. However, the weight determination method is still a single AHP with strong subjectivity to determine the weight. The patent of the present invention studies the characteristics of multiple indicators, multi-attributes and ambiguity affecting the operation state of the active distribution network and the problem that the determination of the traditional evaluation weight is too subjective, and establishes an evaluation index system for the operation state of the active distribution network. From the perspectives of the relative pros and cons of the internal objects of the distribution network operation state and the specific index level, the subjective and objective weights are optimized and combined, and the distance comprehensive evaluation method and the attribute interval algorithm are used to comprehensively evaluate the active distribution network operation state. , and the evaluation results of each index of all evaluation objects are given through radar charts.
发明内容SUMMARY OF THE INVENTION
本发明要克服现有技术的上述缺点，提供一种主动配电网运行状态评估方法。The present invention aims to overcome the above shortcomings of the prior art, and provides a method for evaluating the operating state of an active distribution network.
本发明实现含分布式电源(Distributed Generation,DG)接入的主动配电网运行状态评估，需要对配电网运行的基础数据进行处理，并计算合理的组合权重值。不仅给出评价对象的各项运行状态指标的等级，还给出各评价对象的综合运行状态的相对优劣顺序。设计一个针对主动配电网运行状态多层次、模糊性强的特点以及传统配电网运行状态评价方法中权重系数的确定主观性过强的问题的评估方法。The invention realizes the evaluation of the active distribution network operation state including distributed generation (DG) access, and needs to process the basic data of the distribution network operation and calculate a reasonable combined weight value. It not only gives the grades of various operating state indicators of the evaluation objects, but also gives the relative order of relative merits of the comprehensive operating states of each evaluation object. An evaluation method is designed to deal with the multi-level and strong ambiguity of active distribution network operating state and the problem that the determination of the weight coefficient in the traditional distribution network operating state evaluation method is too subjective.
本发明为实现上述目的，分别提出了基于层次分析法(AHP)-变异系数法和距离综合评价法的主动配电网运行状态综合评价方法和基于最小二乘和属性区间算法的主动配电网运行状态综合评价模型。In order to achieve the above purpose, the present invention proposes a comprehensive evaluation method of active distribution network operation state based on Analytic Hierarchy Process (AHP)-variation coefficient method and distance comprehensive evaluation method, and an active distribution network based on least squares and attribute interval algorithm. Comprehensive evaluation model of operating status.
一种主动配电网运行状态评估方法，包括如下步骤：A method for evaluating the operating state of an active distribution network, comprising the following steps:
1、构建主动配电网运行状态评估指标体系：以系统性、客观性、科学性、实用性的指标体系构建原则为依据，对主动配电网运行状态进行划分，具体划分为紧急状态、需恢复状态、异常状态、正常状态和优化状态这五种运行状态，从安全性、可靠性、优质性、经济性、适应性和网络性六个方面对目标主动配电网运行状态健康与否进行评估以反映其健康程度的状态特征，构建其运行状态的评估指标体系；1. Construct the evaluation index system of active distribution network operation state: Based on the construction principles of systematic, objective, scientific and practical index system, the operation state of active distribution network is divided into emergency state, need The five operating states of recovery state, abnormal state, normal state and optimization state, from six aspects of safety, reliability, quality, economy, adaptability and network, to determine whether the target active distribution network is healthy or not. Evaluate to reflect the state characteristics of its health, and construct an evaluation index system for its operating state;
2、评估指标的一致化处理：各项评估指标中，数据类型、量纲和指标值的变化区间各不相同，含有“极大型”、“极小型”、“居中型”不同特征指标，需将各指标项进行无量纲化和统一化处理，将各指标项都统一转化为“极大型”指标，更改原始数据矩阵中相应的数值；2. Consistent processing of evaluation indicators: Among the evaluation indicators, the data types, dimensions and index values vary in different ranges, including “extremely large”, “extremely small” and “intermediate” characteristic indicators. Perform dimensionless and unified processing on each index item, convert each index item into a "large-scale" index uniformly, and change the corresponding value in the original data matrix;
对于“极小型”指标，令For a "very small" indicator, let
x*＝xmax-x (1)x * = x max -x (1)
对于“居中型”指标，令For a "centered" indicator, let
式中：x为评估指标原始值，x*为一致化处理后的评估指标值，xmin、xmax和xopt分别为评估指标x的允许最小值、允许最大值和理想值；In the formula: x is the original value of the evaluation index, x * is the evaluation index value after uniform processing, x min , x max and x opt are the allowable minimum value, allowable maximum value and ideal value of the evaluation index x, respectively;
3、确定优化组合权重：分别采用层次分析法，即AHP法和变异系数法计算得到主观权重和客观权重，再分别通过基于客观修正主观的组合权重方法和最小二乘优化法对两权重向量进行组合，获得组合权重；3. Determine the optimal combination weight: The AHP method and the coefficient of variation method are used to calculate the subjective weight and the objective weight, respectively, and then the two weight vectors are calculated by the combination weight method based on objective correction and the least square optimization method respectively. Combine, get combined weight;
步骤301，用AHP法获得主观指标权重：AHP法根据专家意见给出两两指标之间的重要性比较，根据指标之间的相对重要性，构建出判断矩阵；在判断矩阵构建好后，需对其进行一致性检验，检验结果由公式(3)得出：Step 301, use the AHP method to obtain the weight of the subjective indicators: the AHP method provides the importance comparison between the two indicators according to the expert opinion, and constructs a judgment matrix according to the relative importance between the indicators; after the judgment matrix is constructed, it needs to be The consistency test is carried out, and the test result is obtained by formula (3):
式中：CI表示一致性检验结果值，λmax表示判断矩阵的最大特征值，n表示判断矩阵的阶数；In the formula: CI represents the consistency test result value, λ max represents the maximum eigenvalue of the judgment matrix, and n represents the order of the judgment matrix;
步骤302，用变异系数法获得客观指标权重：变异系数法直接利用实际数据中的信息，通过数学工具计算得到指标的权重，其核心为对标准偏差越大的指标分配越大的权重；由于评价指标体系中各指标项的量纲不同，需用变异系数来衡量其取值的差异程度，各指标项的变异系数如公式(4)所示：Step 302: Obtain the weight of the objective index by the coefficient of variation method: the coefficient of variation method directly uses the information in the actual data, and calculates the weight of the index through mathematical tools. The dimensions of each indicator item in the indicator system are different, and the coefficient of variation is needed to measure the degree of difference in their values. The coefficient of variation of each indicator item is shown in formula (4):
式中：Bi表示第i个指标项的变异系数，
步骤303，基于客观修正主观的组合权重计算：利用客观赋权法的优势进行主观赋权法劣势的修正，使得组合权重能兼顾主、客观权重的各自优势；根据各指标项的标准差，通过公式(5)确定相邻指标项的重要性之比：Step 303: Calculate the combined weight based on the objective correction subjective: use the advantages of the objective weighting method to correct the disadvantages of the subjective weighting method, so that the combined weight can take into account the respective advantages of the subjective and objective weights; Formula (5) determines the ratio of the importance of adjacent index items:
式中：ri表示第i项指标的重要性专家赋值，si-1为第i-1项指标的标准差；In the formula: ri represents the importance expert assignment of the i -th indicator, and s i-1 is the standard deviation of the i-1-th indicator;
根据式(5)计算所得的ri值，利用公式(6)计算获得其组合权重vi；利用公式(7)依次计算获得第i-1，i-2，...，3，2项指标的组合权重：According to the ri value calculated by formula (5), use formula (6) to calculate and obtain its combined weight v i ; use formula (7) to calculate and obtain the i -1, i-2, ..., 3, 2th items in turn Combination weights of indicators:
vi-1＝ri×vi (7)v i-1 =r i ×v i (7)
式中：vi、vi-1表示第i项、第i-1项指标的客观修正主观的组合权重，其中k∈[s,m]，s∈[2,m]；In the formula: vi and vi -1 represent the objective modified subjective combination weights of the i-th and i -1th indicators, where k∈[s,m], s∈[2,m];
步骤304，利用遗传函数算法对主客观权重进行最小二乘优化组合，编写其适应度函数，即最小二乘法优化模型，如公式(8)所示：Step 304, using the genetic function algorithm to perform the least squares optimization combination on the subjective and objective weights, and write its fitness function, that is, the least squares optimization model, as shown in formula (8):
式中：H(W)为约束函数，wi为第i项指标最小二乘优化后的综合权重值，Ui和U’i分别为第i项指标的主观权重值和客观权重值，x* ij为一致化处理后的第i项指标第j个评估时刻的数据；In the formula: H(W) is the constraint function, w i is the comprehensive weight value of the ith index after least squares optimization, U i and U' i are the subjective weight value and objective weight value of the ith index respectively, x * ij is the data of the jth evaluation moment of the i-th indicator after the consistent processing;
4、对各评价对象的运行状态进行距离综合评价：给出各评估对象综合运行状态的相对优劣顺序；4. Carry out a comprehensive distance evaluation of the operating state of each evaluation object: give the relative order of relative merits of the comprehensive operating state of each evaluation object;
步骤401，构造规划化评价矩阵：由公式(2)得到的一致化指标值，得到一致化变换后的数据矩阵如公式(9)所示：Step 401, constructing a planning evaluation matrix: from the consistent index value obtained by formula (2), the data matrix after consistent transformation is obtained as shown in formula (9):
X*＝(x* ij)m×n (9)X * = (x * ij ) m×n (9)
式中：X*表示一致化变换后的数据矩阵；In the formula: X * represents the data matrix after uniform transformation;
通过公式(10)、(11)对数据矩阵X*进行处理，得到规划化评价矩阵：The data matrix X * is processed by formulas (10) and (11), and the planning evaluation matrix is obtained:
Y*＝(y* ij)m×n (11)Y*=(y * ij ) m×n (11)
式中：y* ij为规划化处理后的第i项指标第j个评估时刻的数据，Y*表示规划化后的数据矩阵；In the formula: y * ij is the data of the i-th index at the j-th evaluation time after the planning process, and Y * represents the planned data matrix;
步骤402，构造加权规划化评价矩阵：将步骤303得到的基于客观修正主观的组合权重与规划化评价矩阵结合，得到加权规划化矩阵，如式(12)所示：Step 402, construct a weighted planning evaluation matrix: combine the combination weights based on the objective correction subjective obtained in step 303 with the planning evaluation matrix to obtain a weighted planning matrix, as shown in formula (12):
zij＝vi×y* ij (12)z ij =v i ×y * ij (12)
式中：zij为加权规划化后的第i项指标第j个评估时刻的数据；In the formula: z ij is the data at the jth evaluation time of the i-th indicator after weighted programming;
步骤403，确定评价参考样本：选取最优样本与最差样本作为参考样本，与指标一致化处理相对应，如公式(13)所示，将指标最大值作为最佳样本点的值、指标最小值作为最差样本点的值：Step 403, determine the evaluation reference sample: select the optimal sample and the worst sample as the reference sample, corresponding to the index consistency processing, as shown in formula (13), the maximum index value is taken as the value of the best sample point, and the index is the smallest. value as the value of the worst sample point:
式中：Z+为所有指标项的最佳样本，Z-为所有指标项的最差样本；
步骤404，确定各评估对象与样本的相对距离并计算最优接近度：如公式(15)、(16)所示，分别计算各指标实际值与最佳参考对象的相对距离，以及与最差参考对象的相对距离：Step 404: Determine the relative distance between each evaluation object and the sample and calculate the optimal proximity: as shown in formulas (15) and (16), calculate the relative distance between the actual value of each index and the best reference object, and the worst The relative distance of the reference object:
式中：
由公式(17)，计算每个评估对象与最佳参考对象的相对接近度：From formula (17), calculate the relative proximity of each evaluation object to the best reference object:
式中：Ci为第i个指标项的最优接近度；In the formula: C i is the optimal proximity of the ith index item;
最后，根据最优接近度对所有评估对象进行排序，得到优劣顺序；Finally, sort all the evaluation objects according to the optimal proximity to get the order of pros and cons;
5、属性区间综合评估：利用属性区间算法对主动配电网运行状态进行分析时需要构建属性测度区间矩阵，其含义为主动配电网某一时刻的运行状态隶属某种等级的程度，再利用级别特征值法确定最终评估等级；5. Comprehensive evaluation of attribute interval: When using the attribute interval algorithm to analyze the operating state of the active distribution network, it is necessary to construct an attribute measurement interval matrix, which means that the operating state of the active distribution network at a certain time belongs to a certain level, and then use it. The final evaluation grade is determined by the grade eigenvalue method;
步骤501，构建评估样本对运行状态的属性测度区间矩阵，形式如式(18)所示：Step 501, construct the attribute measurement interval matrix of the evaluation sample to the running state, the form is as shown in formula (18):
式中：[μ(low)tk,μ(up)tk]为第t个时刻评估样本xi相对于第k种运行状态的属性测度区间，T表示评估时刻总数，K表示运行状态总数；μ(low)tk和μ(up)tk分别为t时刻隶属第k个状态的下界属性测度和上界属性测度；In the formula: [μ (low)tk , μ (up)tk ] is the attribute measurement interval of the evaluation sample x i at the t-th time relative to the k-th operating state, T represents the total number of evaluation moments, and K represents the total number of operating states; μ (low)tk and μ (up)tk are the lower bound attribute measure and the upper bound attribute measure of the kth state at time t, respectively;
步骤502，得到评估各对象各项指标的综合属性测度：求取上界属性测度与下界属性测度的平均值，得到评估样本xi属于第k种运行状态的综合属性测度；Step 502, obtaining a comprehensive attribute measure for evaluating each index of each object: obtaining the average value of the upper bound attribute measure and the lower bound attribute measure, and obtaining the comprehensive attribute measure that the evaluation sample x i belongs to the kth operating state;
步骤503，确定指标评估等级：运用级别特征值法，利用完整隶属度信息实现避免基于最大隶属度原则进行模糊评估时产生的失真隐患；Step 503, determine the index evaluation level: use the level eigenvalue method, and use the complete membership degree information to avoid the hidden distortion caused by the fuzzy evaluation based on the maximum membership degree principle;
步骤504，利用雷达图展示每一个被评估对象的各目标层指标的评估等级：在雷达图中，外圈实线表示所有评估对象在该目标层的最佳表现，内圈实现表示所有评估对象在该目标层的最差表现，中间阴影区域表示该评估时刻各目标层中的表现情况。Step 504, use the radar chart to display the evaluation level of each target layer index of each evaluated object: in the radar chart, the outer circle solid line represents the best performance of all evaluation objects in the target layer, and the inner circle realization represents all evaluation objects. The worst performance of the target layer, the middle shaded area represents the performance of each target layer at the evaluation time.
本发明的有益效果主要表现在：1、构建了表征主动配电网运行状态的评估指标体系；2、采用最小二乘优化组合基于层次分析法的主观权重和基于变异系数法的客观权重；3、利用属性区间算法，充分考虑了主动配电网运行状态中的模糊性特点，考虑了完整隶属度信息，最后得到的各指标综合评估结果科学有效。The beneficial effects of the invention are mainly manifested in: 1. constructing an evaluation index system to characterize the operation state of the active distribution network; 2. adopting the least squares optimization to combine the subjective weight based on the analytic hierarchy process and the objective weight based on the coefficient of variation method; 3 . Using the attribute interval algorithm, fully considering the fuzziness in the active distribution network operating state, and considering the complete membership information, the final comprehensive evaluation results of each index are scientific and effective.
附图说明Description of drawings
图1是本发明方法的具体实施流程图。Fig. 1 is the specific implementation flow chart of the method of the present invention.
图2是本发明的主动配电网运行状态评估指标体系图。FIG. 2 is a system diagram of the evaluation index system of the active distribution network operation state of the present invention.
图3a～图3h是本发明的主动配电网运行状态评估雷达图，其中图3a是评估样本1的雷达图显示，图3b是评估样本2的雷达图显示，图3c是评估样本3的雷达图显示，图3d是评估样本4的雷达图显示，图3e是评估样本5的雷达图显示，图3f是评估样本6的雷达图显示，图3g是评估样本7的雷达图显示图3h是评估样本8的雷达图显示。Figures 3a to 3h are the radar charts of the active distribution network operating state evaluation according to the present invention, wherein Figure 3a is the radar chart display of the evaluation sample 1, Figure 3b is the radar chart display of the evaluation sample 2, and Figure 3c is the radar chart of the
具体实施方式Detailed ways
下面结合实施例及附图对本发明作进一步的详细说明，但本发明的实施方式不限于此。实施例中本发明的实施流程图如附图1所示。The present invention will be further described in detail below with reference to the embodiments and the accompanying drawings, but the embodiments of the present invention are not limited thereto. In the embodiment, the flow chart of the implementation of the present invention is shown in FIG. 1 .
一种主动配电网运行状态评估方法，包括以下步骤：A method for evaluating the operating state of an active distribution network, comprising the following steps:
1、构建主动配电网运行状态评估指标体系：以系统性、客观性、科学性、实用性的指标体系构建原则为依据，对主动配电网运行状态进行划分，具体划分为紧急状态、需恢复状态、异常状态、正常状态和优化状态这五种运行状态，从安全性、可靠性、优质性、经济性、适应性和网络性六个方面对目标主动配电网运行状态健康与否进行评估以反映其健康程度的状态特征，构建其运行状态的评估指标体系；1. Construct the evaluation index system of active distribution network operation state: Based on the construction principles of systematic, objective, scientific and practical index system, the operation state of active distribution network is divided into emergency state, need The five operating states of recovery state, abnormal state, normal state and optimization state, from six aspects of safety, reliability, quality, economy, adaptability and network, to determine whether the target active distribution network is healthy or not. Evaluate to reflect the state characteristics of its health, and construct an evaluation index system for its operating state;
具体到实施例中，构建的主动配电网运行状态评估指标体系如附图2所示；其评估体系基础层中，安全性指标包括过电压、低电压和过负荷，可靠性指标包括故障概率和失负荷风险，优质性包括电压偏差和馈线功率因素，经济性指标有网络损耗率，适应性包括负荷孤立供电能力、无功缺额和线路装接容量，网络性包括被攻击频率、攻击严重程度和信息传输漏洞；Specifically in the embodiment, the constructed active distribution network operating state evaluation index system is shown in Figure 2; in the basic layer of the evaluation system, the safety index includes overvoltage, low voltage and overload, and the reliability index includes failure probability and load loss risk, quality includes voltage deviation and feeder power factor, economic index includes network loss rate, adaptability includes load isolation power supply capacity, reactive power shortage and line installation capacity, network quality includes attack frequency, attack severity and information transmission vulnerabilities;
2、评估指标的一致化处理：各项评估指标中，数据类型、量纲和指标值的变化区间各不相同，含有“极大型”、“极小型”、“居中型”不同特征指标，需将各指标项进行无量纲化和统一化处理，将各指标项都统一转化为“极大型”指标，更改原始数据矩阵中相应的数值；对于“极小型”指标，转化方法如式(1)所示，对于“居中型”指标，转化方法如式(2)所示；2. Consistent processing of evaluation indicators: Among the evaluation indicators, the data types, dimensions and index values vary in different ranges, including “extremely large”, “extremely small” and “intermediate” characteristic indicators. Perform dimensionless and unified processing on each index item, transform each index item into a "large-scale" index uniformly, and change the corresponding value in the original data matrix; for the "very-small" index, the conversion method is as shown in formula (1) As shown, for the "center type" index, the transformation method is shown in formula (2);
实施例中，经一致化处理后得到的待评估电能质量指标数据如表1所示；In the embodiment, the power quality index data to be evaluated obtained after the unification processing is shown in Table 1;
3、确定优化组合权重：分别采用层次分析法，即AHP法和变异系数法计算得到主观权重和客观权重，再分别通过基于客观修正主观的组合权重方法和最小二乘优化法对两权重向量进行组合，获得组合权重；3. Determine the optimal combination weight: The AHP method and the coefficient of variation method are used to calculate the subjective weight and the objective weight, respectively, and then the two weight vectors are calculated by the combination weight method based on objective correction and the least square optimization method respectively. Combine, get combined weight;
步骤301，用AHP法获得主观指标权重：AHP法根据专家意见给出两两指标之间的重要性比较，根据指标之间的相对重要性，构建出判断矩阵；在判断矩阵构建好后，需对其进行一致性检验，检验结果由公式(3)得出；Step 301, use the AHP method to obtain the weight of the subjective indicators: the AHP method provides the importance comparison between the two indicators according to the expert opinion, and constructs a judgment matrix according to the relative importance between the indicators; after the judgment matrix is constructed, it needs to be Consistency test is carried out on it, and the test result is obtained by formula (3);
表1一致化后各个时刻的评估指标值Table 1. Evaluation index values at each moment after unification
步骤302，用变异系数法获得客观指标权重：变异系数法直接利用实际数据中的信息，通过数学工具计算得到指标的权重，其核心为对标准偏差越大的指标分配越大的权重；由于评价指标体系中各指标项的量纲不同，需用变异系数来衡量其取值的差异程度，各指标项的变异系数如公式(4)所示；Step 302: Obtain the weight of the objective index by the coefficient of variation method: the coefficient of variation method directly uses the information in the actual data, and calculates the weight of the index through mathematical tools. The dimensions of each indicator item in the indicator system are different, and the coefficient of variation is needed to measure the degree of difference in their values. The coefficient of variation of each indicator item is shown in formula (4);
步骤303，基于客观修正主观的组合权重计算：利用客观赋权法的优势进行主观赋权法劣势的修正，使得组合权重能兼顾主、客观权重的各自优势；根据各指标项的标准差，通过公式(5)确定相邻指标项的重要性之比；Step 303: Calculate the combined weight based on the objective correction subjective: use the advantages of the objective weighting method to correct the disadvantages of the subjective weighting method, so that the combined weight can take into account the respective advantages of the subjective and objective weights; Formula (5) determines the ratio of the importance of adjacent index items;
根据式(5)计算所得的ri值，利用公式(6)计算获得其组合权重vi；利用公式(7)依次计算获得第i-1，i-2，...，3，2项指标的组合权重；According to the ri value calculated by formula (5), use formula (6) to calculate and obtain its combined weight v i ; use formula (7) to calculate and obtain the i -1, i-2, ..., 3, 2th items in turn The combined weight of the indicator;
步骤304，利用遗传函数算法对主客观权重进行最小二乘优化组合，编写其适应度函数，即最小二乘法优化模型，如公式(8)所示；Step 304, using the genetic function algorithm to perform the least squares optimization combination on the subjective and objective weights, and write its fitness function, that is, the least squares optimization model, as shown in formula (8);
实施例中，经步骤3处理后得到的各指标组合权重结果如表2所示；In the embodiment, the weight result of each index combination obtained after being processed in
表2主动配电网运行状态评估二级指标综合权重Table 2 Comprehensive weights of secondary indicators for active distribution network operation status evaluation
4、对各评价对象的运行状态进行距离综合评价：给出各评估对象综合运行状态的相对优劣顺序；4. Carry out a comprehensive distance evaluation of the operating state of each evaluation object: give the relative order of relative merits of the comprehensive operating state of each evaluation object;
步骤401，构造规划化评价矩阵：由公式(2)得到的一致化指标值，得到一致化变换后的数据矩阵如公式(9)所示；Step 401, constructing a planning evaluation matrix: the consistent index value obtained by formula (2), the obtained data matrix after consistent transformation is shown in formula (9);
通过公式(10)、(11)对数据矩阵X*进行处理，得到规划化评价矩阵；The data matrix X * is processed by formulas (10) and (11) to obtain a planning evaluation matrix;
步骤402，构造加权规划化评价矩阵：将步骤303得到的基于客观修正主观的组合权重与规划化评价矩阵结合，得到加权规划化矩阵，如式(12)所示；Step 402, construct a weighted planning evaluation matrix: combine the combination weights based on the objective correction subjective obtained in step 303 with the planning evaluation matrix to obtain a weighted planning matrix, as shown in formula (12);
步骤403，确定评价参考样本：选取最优样本与最差样本作为参考样本，与指标一致化处理相对应，如公式(13)所示，将指标最大值作为最佳样本点的值、指标最小值作为最差样本点的值；Step 403, determine the evaluation reference sample: select the optimal sample and the worst sample as the reference sample, corresponding to the index consistency processing, as shown in formula (13), the maximum index value is taken as the value of the best sample point, and the index is the smallest. value as the value of the worst sample point;
步骤404，确定各评估对象与样本的相对距离并计算最优接近度：如公式(15)、(16)所示，分别计算各指标实际值与最佳参考对象的相对距离，以及与最差参考对象的相对距离；由公式(17)，计算每个评估对象与最佳参考对象的相对接近度；最后，根据最优接近度对所有评估对象进行排序，得到优劣顺序；Step 404: Determine the relative distance between each evaluation object and the sample and calculate the optimal proximity: as shown in formulas (15) and (16), calculate the relative distance between the actual value of each index and the best reference object, and the worst The relative distance of the reference object; according to formula (17), calculate the relative proximity of each evaluation object and the best reference object; finally, sort all the evaluation objects according to the optimal proximity to obtain the superior and inferior order;
实施例中，经步骤4处理后得到的各评估时刻主动配电网运行状态距离综合评价优劣顺序结果如表3所示；In the embodiment, after the processing in step 4, the results of the comprehensive evaluation of the pros and cons of the active distribution network operating state distance at each evaluation time are shown in Table 3;
表3主动配电网运行状态距离综合评价评估结果Table 3. Evaluation results of comprehensive evaluation of operating state distance of active distribution network
5、属性区间综合评估：利用属性区间算法对主动配电网运行状态进行分析时需要构建属性测度区间矩阵，其含义为主动配电网某一时刻的运行状态隶属某种等级的程度，再利用级别特征值法确定最终评估等级；5. Comprehensive evaluation of attribute interval: When using the attribute interval algorithm to analyze the operating state of the active distribution network, it is necessary to construct an attribute measurement interval matrix, which means that the operating state of the active distribution network at a certain time belongs to a certain level, and then use it. The final evaluation grade is determined by the grade eigenvalue method;
步骤501，构建评估样本对运行状态的属性测度区间矩阵，形式如式(18)所示；Step 501, construct the attribute measurement interval matrix of the evaluation sample to the running state, the form is as shown in formula (18);
步骤502，得到评估各对象各项指标的综合属性测度：求取上界属性测度与下界属性测度的平均值，得到评估样本xi属于第k种运行状态的综合属性测度；Step 502, obtaining a comprehensive attribute measure for evaluating each index of each object: obtaining the average value of the upper bound attribute measure and the lower bound attribute measure, and obtaining the comprehensive attribute measure that the evaluation sample x i belongs to the kth operating state;
实施例中，主动配电网各评估时刻在“紧急”、“需恢复”、“异常”、“正常”和“优化”这五个综合状态的评估综合属性测度如表4所示；In the embodiment, the evaluation comprehensive attribute measures of the five comprehensive states of "emergency", "recovery required", "abnormal", "normal" and "optimized" at each evaluation time of the active distribution network are shown in Table 4;
步骤503，确定指标评估等级：运用级别特征值法，利用完整隶属度信息实现避免基于最大隶属度原则进行模糊评估时产生的失真隐患；Step 503, determine the index evaluation level: use the level eigenvalue method, and use the complete membership degree information to avoid the hidden distortion caused by the fuzzy evaluation based on the maximum membership degree principle;
实施例中，主动配电网在各评估时刻的准则层评估指标计算结果和运行状态辨识结果分别如表5，表6所示；In the embodiment, the calculation result of the criterion layer evaluation index and the operation state identification result of the active distribution network at each evaluation time are shown in Table 5 and Table 6 respectively;
步骤504，利用雷达图展示每一个被评估对象的各目标层指标的评估等级：在雷达图中，外圈实线表示所有评估对象在该目标层的最佳表现，内圈实现表示所有评估对象在该目标层的最差表现，中间阴影区域表示该评估时刻各目标层中的表现情况；Step 504, use the radar chart to display the evaluation level of each target layer index of each evaluated object: in the radar chart, the outer circle solid line represents the best performance of all evaluation objects in the target layer, and the inner circle realization represents all evaluation objects. The worst performance of the target layer, the middle shaded area represents the performance of each target layer at the evaluation moment;
表4主动配电网综合状态评估综合属性测度Table 4. Comprehensive attribute measurement of comprehensive state evaluation of active distribution network
表5准则层评估指标计算结果Table 5 Calculation results of evaluation indicators at the criterion level
表6主动配电网运行状态辨识结果Table 6 Identification results of active distribution network operating state
步骤504，利用雷达图表现每一个被评估对象各目标层指标的评估等级：在雷达图中，外圈实线表示所有评估对象在该目标层的最佳表现，内圈实现表示所有评估对象在该目标层的最差表现，中间阴影区域表示该评估时刻在各目标层中的表现情况；In step 504, the evaluation level of each target layer index of each evaluated object is represented by the radar chart: in the radar chart, the solid line in the outer circle represents the best performance of all the evaluation objects in the target layer, and the inner circle indicates that all the evaluation objects are in the target layer. The worst performance of the target layer, the middle shaded area represents the performance of each target layer at the evaluation moment;
实施例中，待评估样本时刻1至时刻8中，主动配电网在安全性、可靠性、优质性、经济性、适应性和网络性六个目标层的综合评价结果的雷达图显示依次如附图3a～附图3h所示。In the embodiment, from time 1 to time 8 of the sample to be evaluated, the radar charts of the comprehensive evaluation results of the active distribution network in the six target layers of safety, reliability, quality, economy, adaptability and network are shown in the order as follows: Figures 3a to 3h are shown.
本说明书实施例所述的内容仅仅是对发明构思的实现形式的列举，本发明的保护范围不应当被视为仅限于实施例所陈述的具体形式，本发明的保护范围也及于本领域技术人员根据本发明构思所能够想到的等同技术手段。The content described in the embodiments of the present specification is only an enumeration of the realization forms of the inventive concept, and the protection scope of the present invention should not be regarded as limited to the specific forms stated in the embodiments, and the protection scope of the present invention also extends to those skilled in the art. Equivalent technical means that can be conceived by a person based on the inventive concept.
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