CN119765520A - A distributed photovoltaic voltage coordinated control method for distribution network based on dynamic partitioning - Google Patents
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Abstract
本发明提供一种基于动态分区的配电网分布式光伏电压协同控制方法，属于配电网分布式光伏电压协同控制技术领域；本发明通过动态分区和设计一致性变量，实现对不同节点越限程度的灵活应对，提升电压控制的协调性和整体效果，解决了分布式光伏接入引起的配电网电压越限问题，采用的技术方案为：根据配电网线路参数计算每个节点的电压灵敏度和电气距离；构建动态分区指标；根据某一节点对分区内其他节点的影响情况来选择主导节点；设立动态分区目标函数，利用遗传算法进行分区求解，每隔一小时分区一次，输出分区结果并计算各分区内主导节点；本发明应用于配电网分布式光伏电压协同控制。
The present invention provides a distributed photovoltaic voltage coordinated control method for a distribution network based on dynamic partitioning, and belongs to the technical field of distributed photovoltaic voltage coordinated control for distribution networks; the present invention realizes flexible response to the over-limit degree of different nodes through dynamic partitioning and designing consistency variables, improves the coordination and overall effect of voltage control, and solves the voltage over-limit problem of the distribution network caused by distributed photovoltaic access. The technical scheme adopted is: calculating the voltage sensitivity and electrical distance of each node according to the line parameters of the distribution network; constructing dynamic partitioning indicators; selecting a dominant node according to the influence of a certain node on other nodes in the partition; establishing a dynamic partitioning objective function, using a genetic algorithm to perform partitioning solution, partitioning once every hour, outputting the partitioning results and calculating the dominant nodes in each partition; the present invention is applied to the distributed photovoltaic voltage coordinated control of the distribution network.
Description
Technical Field
The invention provides a distributed photovoltaic voltage cooperative control method of a power distribution network based on dynamic partitioning, and belongs to the technical field of distributed photovoltaic voltage cooperative control of power distribution networks.
Background
Along with the establishment and the use of more and more distributed photovoltaic power generation fields in recent years, more and more photovoltaic power generation capacity is connected into a power distribution network, but the randomness and the intermittence of the photovoltaic power generation can lead to frequent voltage fluctuation and frequent voltage out-of-limit conditions, particularly, the phenomenon that the voltage of the power distribution network is higher in low-load period and high illumination intensity is remarkable, and the phenomenon that the voltage of the power distribution network is lower in night under the conditions that the user load is larger and the photovoltaic power is not output is needed to be regulated and controlled.
The voltage regulation method adopted at present comprises the steps of adding a voltage regulator and a reactive compensation device, but the added devices are difficult to respond to voltage fluctuation caused by photovoltaic power generation in real time, the regulation range is limited, and the voltage requirement under high-proportion distributed photovoltaic access cannot be met; with large-scale access of distributed photovoltaic, partial nodes in a power distribution network are easy to generate voltage out-of-limit phenomenon, the existing control method is difficult to effectively cope with voltage fluctuation, and the traditional partition control strategy lacks flexibility especially under the condition that different node out-of-limit severity degree is inconsistent.
The method adopts disposable partition without considering the randomness of the photovoltaic output and the dynamic change of the load, the voltage deviation of different nodes is dynamic change, the power balance degree change among the partitions can be caused, the fixed partition scheme can not adapt to the running condition of the power distribution network which is dynamically changed, the method is difficult to dynamically adjust according to the voltage adjustment requirement of different nodes, the control resource distribution is uneven, and partial nodes can not effectively eliminate the problem of voltage overrun due to insufficient adjustment capability.
In addition, the consistency variable is designed by adopting the reactive or active utilization rate of the distributed photovoltaic, particularly the node voltage is controlled by adjusting the output force of the distributed power supply through consistency protocol convergence, the purpose of the method is to enable the reactive or active utilization rate of the distributed photovoltaic to approach consistency, however, the influence of different nodes on the voltage is not considered to be different, the voltage regulating effect of the photovoltaic inverters is difficult to be exerted to the maximum extent, the problem of insufficient coordination exists in the cooperative control of the plurality of photovoltaic inverters, the voltage regulating contribution degree of each inverter cannot be fully utilized to achieve agreement, and the voltage control effect is poor.
Disclosure of Invention
The invention realizes flexible treatment of different node out-of-limit degrees through dynamic partitioning and design of consistency variables, improves coordination and overall effect of voltage control, and solves the problem of out-of-limit voltage of a power distribution network caused by distributed photovoltaic access.
Calculating voltage sensitivity and electrical distance of each node according to the line parameters of the power distribution network;
Step two, constructing dynamic partition indexes;
Selecting a dominant node according to the influence condition of a certain node on other nodes in the partition;
setting up a dynamic partition objective function, wherein the expression is as follows:
;
Wherein, lambda 1 and lambda 2 are respectively weight factors, and lambda 1+λ2 =1 is satisfied to adjust the partition result, and alpha and beta are respectively the in-region coupling degree and the interval dispersion degree;
then carrying out partition solving by utilizing a genetic algorithm, partitioning once every other hour, outputting a partitioning result and calculating dominant nodes in each partition;
Step five, after voltage out-of-limit occurs, counting voltage deviation values of out-of-limit nodes, and then calculating reactive power adjustment power of each distributed photovoltaic in the power distribution network and weight coefficients of photovoltaic nodes in the partition according to the partition result in the step four;
Step six, responding reactive power regulation of the distributed photovoltaics in each partition through a consistency algorithm result;
And seventhly, if the reactive power regulation resources of the distributed photovoltaic of each partition are exhausted, an active regulation method is adopted, and the distributed photovoltaic responds according to the consistency regulation method in the step six.
The method for calculating the voltage sensitivity of each node in the first step is as follows:
The active and reactive-voltage sensitivity matrixes are adopted for expression, and the expression is as follows:
;
Wherein V 0 is the voltage of the head end node of the line, S P,ij is the active-voltage sensitivity between the ith node and the jth node, S Q,ij is the reactive-voltage sensitivity between the ith grid-connected point and the jth grid-connected point, R i and X i are the resistance and reactance values of the ith section of line respectively;
The method for calculating the electrical distance comprises the following steps:
The electrical distance is calculated by using the voltage sensitivity, and the calculation formula of the electrical distance between the nodes i and j is as follows:
;
Wherein S P,im is the active-voltage sensitivity between the ith node and the mth node, S P,jm is the active-voltage sensitivity between the jth node and the mth node, S Q,im is the reactive-voltage sensitivity between the ith node and the mth node, and S Q,jm is the reactive-voltage sensitivity between the jth node and the mth node.
The specific method for constructing the dynamic partition index in the second step comprises the following steps:
And respectively calculating the intra-area coupling degree alpha and the interval dispersion degree beta of the distributed photovoltaic node, wherein the calculation formula is as follows:
;
;
Wherein N is the number of partitions, A is the node set of partition x, and L ave,x is the average distance of partition x.
The specific method for selecting the dominant node in the third step is as follows:
The dominant node delta x is selected according to the influence condition of the node on other nodes in the partition, and the selection is based on the following calculation formula:
;
Wherein S P,jj is the active-voltage sensitivity of the jth node to itself, and S Q,jj is the reactive-voltage sensitivity of the jth node to itself.
The specific method for dynamic partition division in the fourth step is as follows:
step 4.1, drawing a network topological graph according to an actual power distribution network;
step 4.2, converting each node and branch of the network topological graph into chromosome codes of a genetic algorithm:
The length of the chromosome coding vector is equal to the total branch number of the distribution topology, 0 and 1 elements are used for representing the partition relation between the branch and the node, 0 represents that the nodes at two ends of the branch are not in the same partition, and 1 represents that the nodes at two ends of the branch are in the same partition;
Step 4.3, inputting the number of individuals required by a genetic algorithm, the maximum genetic algebra, generation gap coefficients, cross probability, mutation probability and partition index weight coefficients;
step 4.4, randomly encoding the chromosome to generate an initial population:
obtaining a partition scheme by decoding the chromosome, and calculating individual fitness by using a partition evaluation index;
Step 4.5, selecting, crossing and mutating to obtain a child population, calculating the fitness of the child population, inserting the child into the parent to obtain a new population, and outputting a partitioning result after the maximum genetic algebra is reached;
And 4.6, after the partition result is obtained, selecting dominant nodes of each partition through a calculation formula in the second step.
In the fifth step, after the voltage is out of limit, the voltage deviation value of each out-of-limit node is counted, and the calculation formula is as follows:
;
Wherein U ref is reference voltage, K is an out-of-limit node set, and U k is a real-time voltage value of a voltage out-of-limit node;
According to the zoning result in the step four, calculating reactive power adjustment power delta Q i (t) of each distributed photovoltaic, wherein the calculation formula is as follows:
;
Wherein w i is the weight coefficient of the distributed photovoltaic leading node and other nodes, eta i (t) is the voltage regulation contribution degree of the photovoltaic node i at the moment t, and Q i,max is the maximum reactive power output of the distributed photovoltaic i;
The weight coefficient of the photovoltaic nodes in the partition is calculated, and the calculation formula is as follows:
;
wherein S PV,i is the grid-connected capacity of the ith distributed photovoltaic, and m is the number of distributed photovoltaic nodes in the partition.
The consistency algorithm adopted in the step six is specifically:
Each node bears voltage fluctuation according to the voltage regulation contribution degree, and finally achieves the following consistency:
;
Where η dom (t) and η i (t) are voltage adjustment contribution degrees at the time of a dominant node and at the time of other nodes respectively, Δu dom (t) and Δu i (t) are voltage deviation degrees at the time of the dominant node and at the time of other nodes respectively, Δq dom (t) and Δq i (t) are reactive adjustment power at the time of the dominant node and at the time of other nodes respectively, w dom and w i are weight coefficients at the dominant node and at the time of other nodes respectively, and Q dom,max and Q i,max are maximum reactive adjustment margins at the dominant node and at the time of other nodes respectively.
The specific method for responding to reactive power regulation in the step six is as follows:
Step 6.1, determining an adjacent matrix in each partition according to the network topology of the power distribution network, wherein the expression is as follows:
;
Wherein d ij represents the communication weight between the nodes i and j, the n multiplied by n matrix is a square matrix, the rows and columns are n elements, and n is the number of nodes of the power distribution network;
And 6.2, calculating the communication weight d ij between the nodes i and j, wherein the calculation formula is as follows:
;
Where s ij = 1 if there is communication between nodes i and j, otherwise s ij=0,Ni is the number of nodes i;
And 6.3, according to a consistency protocol, iteratively updating the voltage regulation contribution degree of the distributed photovoltaic in the partition according to the following formula:
;
Where η i (k) represents the reactive voltage regulation contribution of the photovoltaic node i, and k is the sampling time.
The active power adjusting method adopted in the step seven comprises the following specific steps:
step 7.1, calculating the active regulation power of each distributed photovoltaic:
;
Wherein w i is the weight coefficient of the distributed photovoltaic leading node and other nodes, ρ i (t) is the voltage regulation contribution degree, and ΔP i (t) is the active power regulation quantity of each distributed photovoltaic response participating in voltage management;
and 7.2, according to a consistency protocol, iteratively updating the voltage regulation contribution degree of the distributed photovoltaic in the partition according to the following formula:
;
Wherein ρ i (k) represents the reactive voltage regulation contribution degree of the photovoltaic node i, and k is the sampling time;
and 7.3, responding to active regulation by a distributed photovoltaic in each partition through a consistency algorithm result, and bearing voltage fluctuation by each node according to a voltage regulation contribution degree, wherein consistency is finally achieved, and the expression of consistency is as follows:
;
Wherein ρ dom (t) and ρ i (t) are voltage regulation contribution degrees of the dominant node and other nodes respectively, Δu dom (t) and Δu i (t) are voltage deviation degrees of the dominant node and other nodes at time t respectively, Δp dom (t) and Δp i (t) are active regulation power of the dominant node and other nodes at time t respectively, w dom is a weight coefficient of the dominant node, and P dom,max and P i,max are maximum active regulation margins of the dominant node and other nodes respectively.
Compared with the prior art, the distributed photovoltaic voltage cooperative control method for the power distribution network has the advantages that the nodes with different voltage sensitivity degrees are dynamically partitioned, so that control resources of the photovoltaic inverters can be distributed in a targeted mode, the response capability to voltage fluctuation of different areas is improved, the inefficiency response of a global control strategy on local problems is avoided, the flexibility of voltage control is improved, the adjustment capability of each inverter is reasonably distributed by utilizing the voltage adjustment contribution degree, the resource distribution is optimized, the voltage adjustment effect is maximized, the problem that part of nodes are excessively adjusted or are insufficient in adjustment is solved, the control efficiency is improved, meanwhile, the cooperative work of a plurality of photovoltaic inverters is realized, the coordination among all nodes in the system is enhanced, the integral effect of voltage adjustment is improved, and the voltage stability of the power distribution network under the condition of large-scale photovoltaic access is ensured.
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The invention is further described below with reference to the accompanying drawings:
fig. 1 is a flow chart of steps of a distributed photovoltaic voltage cooperative control method of a power distribution network.
Detailed Description
The invention provides a distributed photovoltaic voltage cooperative control method of a power distribution network based on dynamic partition, which is based on a distributed photovoltaic dynamic partition dividing method and utilizes a consistency principle to realize active and reactive voltage cooperative control of the distributed photovoltaic, and can dynamically partition according to the severity degree of out-of-limit of different nodes, utilize voltage regulation contribution degree to construct consistency variables, optimize and adjust active and reactive power distribution in real time, realize effective suppression of out-of-limit voltage, ensure safe and stable operation of the power distribution network, simultaneously promote electric energy quality and provide technical support for sustainable development of an electric power system.
The invention provides a distributed photovoltaic voltage cooperative control method of a power distribution network based on dynamic partition, which specifically comprises the following control steps:
Calculating the voltage sensitivity of each node according to the line parameters of the power distribution network, wherein the active and reactive-voltage sensitivity matrix expression is as follows:
(1);
Wherein V 0 is the voltage of the head end node of the line, S P,ij is the active-voltage sensitivity between the ith node and the jth node, S Q,ij is the reactive-voltage sensitivity between the ith grid-connected point and the jth grid-connected point, and R i and X i are the resistance and reactance values of the ith line respectively.
Calculating an electrical distance by using the voltage sensitivity, wherein the electrical distance between the nodes i and j is as follows:
(2);
Wherein S P,im is the active-voltage sensitivity between the ith node and the mth node, S P,jm is the active-voltage sensitivity between the jth node and the mth node, S Q,im is the reactive-voltage sensitivity between the ith node and the mth node, and S Q,jm is the reactive-voltage sensitivity between the jth node and the mth node;
And step two, constructing dynamic partition indexes. The method comprises the steps of calculating the intra-zone coupling degree alpha and the inter-zone dispersion degree beta of the distributed photovoltaic node, wherein the calculation formulas are shown in a formula (3) and a formula (4) respectively:
(3);
(4);
wherein N is the number of partitions, A is the node set of partition x, L ave,x is the average distance of partition x, and the calculation formula is 。
Defining a dominant node, selecting the dominant node delta x according to the influence condition of the node on other nodes in the partition, and selecting the dominant node delta x according to the following formula:
(5);
Wherein S P,jj is the active-voltage sensitivity of the jth node to itself, S Q,jj is the reactive-voltage sensitivity of the jth node to itself;
Setting a dynamic partition objective function:
;
wherein, lambda 1 and lambda 2 are weight factors respectively, and lambda 1+λ2 =1 is satisfied, so that the partition result can be adjusted.
And carrying out partition solving by using a genetic algorithm, partitioning once every other hour, outputting a partition result and calculating dominant nodes in each partition.
The specific method for dynamic partition division is as follows:
and 4.1, drawing a network topological graph according to an actual power distribution network.
And 4.2, converting each node and branch based on the network topology diagram into the coding of the chromosome of the genetic algorithm. The length of the chromosome coding vector is equal to the total branch number of the distribution topology, the partition relation between the branch and the node is represented by 0 and 1 elements, 0 represents that the nodes at two ends of the branch are not in the same partition, and 1 represents that the nodes at two ends of the branch are in the same partition.
And 4.3, inputting parameters such as the number of individuals required by a genetic algorithm, the maximum genetic algebra, generation gap coefficients, crossover probability, mutation probability, partition index weight coefficients and the like.
And 4.4, randomly encoding the chromosome to generate an initial population. And obtaining a partition scheme by decoding the chromosome, and calculating individual fitness by using a partition evaluation index.
And 4.5, selecting, crossing, mutating and the like to obtain a child population, calculating the fitness of the child population, and inserting the child into the parent to obtain a new population. And after the maximum genetic algebra is reached, outputting a partitioning result.
And 4.6, after the partition result is obtained, selecting dominant nodes of each partition through a calculation formula in the second step.
Step five, after the voltage out-of-limit occurs, counting the voltage deviation value of each out-of-limit nodeWherein U ref is the reference voltage, K is the threshold-crossing node set, and U k is the real-time voltage value of the voltage threshold-crossing node.
Calculating reactive power regulation delta Q i (t) of each distributed photovoltaic according to the zoning result in the step four:
(6);
In the formula, w i is the weight coefficient of the distributed photovoltaic dominant node and other nodes, eta i (t) is the voltage regulation contribution degree of the photovoltaic node i at the moment t, and Q i,max is the maximum reactive power output of the distributed photovoltaic i.
The weight coefficient calculation formula of the photovoltaic nodes in the subareas is as follows:
(7);
wherein S PV,i is the grid-connected capacity of the ith distributed photovoltaic, and m is the number of distributed photovoltaic nodes in the partition.
Step six, the distributed photovoltaics in each partition respond to reactive power regulation through a consistency algorithm result, each node bears voltage fluctuation according to the voltage regulation contribution degree, and finally, consistency is achieved, and the expression of the consistency is as follows:
(8);
Where η dom (t) and η i (t) are voltage adjustment contribution degrees at the time of a dominant node and at the time of other nodes respectively, Δu dom (t) and Δu i (t) are voltage deviation degrees at the time of the dominant node and at the time of other nodes respectively, Δq dom (t) and Δq i (t) are reactive adjustment power at the time of the dominant node and at the time of other nodes respectively, w dom and w i are weight coefficients at the dominant node and at the time of other nodes respectively, and Q dom,max and Q i,max are maximum reactive adjustment margins at the dominant node and at the time of other nodes respectively.
And then reactive power adjustment is carried out based on consistency, and the specific steps are as follows:
Step 6.1, determining an adjacent matrix in each partition according to the network topology of the power distribution system D ij represents the communication weight between nodes i and j;
And 6.2, calculating the communication weight d ij between the nodes i and j, wherein the calculation formula is as follows:
(9);
Where s ij = 1 if there is communication between nodes i and j (i+.j), otherwise s ij=0,Ni is the number of nodes i.
And 6.3, according to a consistency protocol, iteratively updating the voltage regulation contribution degree of the distributed photovoltaic in the partition according to the following formula:
(10);
Where η i (k) represents the reactive voltage regulation contribution of the photovoltaic node i, and k is the sampling time.
And seventhly, if the reactive power regulation resources of the distributed photovoltaic of each partition are exhausted, an active regulation method is adopted, and the distributed photovoltaic responds according to the consistency regulation method.
The specific method for the distributed photovoltaic active power regulation comprises the following steps:
step 7.1, calculating the active regulation power of each distributed photovoltaic:
(11);
Where w i is the weight coefficient of the distributed photovoltaic dominant node and other nodes, ρ i (t) is the voltage regulation contribution, and Δp i (t) is the active power regulation amount responded to for each distributed photovoltaic participating in voltage management.
And 7.2, according to a consistency protocol, iteratively updating the voltage regulation contribution degree of the distributed photovoltaic in the partition according to the following expression:
(12);
Where ρ i (k) represents the reactive voltage regulation contribution of the photovoltaic node i, and k is the sampling time.
And 7.3, responding to active regulation by a distributed photovoltaic in each partition through a consistency algorithm result, and bearing voltage fluctuation by each node according to a voltage regulation contribution degree, wherein consistency is finally achieved, and the expression of consistency is as follows:
(13);
Wherein ρ dom (t) and ρ i (t) are voltage regulation contribution degrees of the dominant node and other nodes respectively, Δu dom (t) and Δu i (t) are voltage deviation degrees of the dominant node and other nodes at time t respectively, Δp dom (t) and Δp i (t) are active regulation power of the dominant node and other nodes at time t respectively, w dom is a weight coefficient of the dominant node, and P dom,max and P i,max are maximum active regulation margins of the dominant node and other nodes respectively.
It should be noted that the above embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that the technical solution described in the above embodiments may be modified or some or all of the technical features may be equivalently replaced, and these modifications or substitutions do not make the essence of the corresponding technical solution deviate from the scope of the technical solution of the embodiments of the present invention.
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