CN110808612A - Method for evaluating operation flexibility of power distribution system with high-proportion distributed power supply - Google Patents

Method for evaluating operation flexibility of power distribution system with high-proportion distributed power supply Download PDF

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CN110808612A
CN110808612A CN201911189987.5A CN201911189987A CN110808612A CN 110808612 A CN110808612 A CN 110808612A CN 201911189987 A CN201911189987 A CN 201911189987A CN 110808612 A CN110808612 A CN 110808612A
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flexibility
load
voltage fluctuation
power distribution
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韩春成
鹿丽
贺欢
徐大利
祝湘博
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State Grid Corp of China SGCC
State Grid Liaoning Electric Power Co Ltd
Northeast Electric Power University
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State Grid Corp of China SGCC
Northeast Dianli University
State Grid Liaoning Electric Power Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers

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Abstract

A method for evaluating the operation flexibility of a power distribution system with a high-proportion distributed power supply belongs to the technical field of evaluation of the operation flexibility of the power distribution system. According to the method, relevant factors influencing the operation flexibility are analyzed, the load scene is divided based on the improved fuzzy C-means clustering algorithm from the power distribution network voltage constraint, a calculation method of the operation flexibility quantitative evaluation index considering the load scene probability is provided, and the operation flexibility evaluation of the power distribution system with the high-proportion DG is realized in the aspects of space and time. The index can reflect the flexibility state and change of the system during operation, and the energy storage device plays a role in improving the operation flexibility of the power distribution system.

Description

Method for evaluating operation flexibility of power distribution system with high-proportion distributed power supply
Technical Field
The invention belongs to the technical field of evaluation of operation flexibility of a power distribution system, and particularly relates to an evaluation method of operation flexibility of a power distribution system with a high-proportion distributed power source.
Background
With the spread of renewable energy, access of a Distributed Generation (DG) to a power distribution system is becoming a necessary trend. The ability of power distribution systems to cope with the effects of uncertainty resulting from DG randomness, fluctuating contribution, has become the focus of current attention. The operation flexibility is an important index for measuring the capability of the system to cope with uncertainty factors, and the distribution system can accept a higher proportion of DGs only if the distribution system has sufficient operation flexibility, so that the research and evaluation of the operation flexibility of the distribution system containing the higher proportion of DGs have important significance.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: an evaluation method for the operational flexibility of a power distribution system with a high percentage of distributed power sources is provided for determining the operational flexibility of the power distribution system so that the power distribution system can accommodate a higher percentage of DGs.
The method for evaluating the operation flexibility of the power distribution system with the high-proportion distributed power supply comprises the following steps which are sequentially carried out,
firstly, establishing a power distribution system operation flexibility index simulation model containing a high-proportion distributed power supply by utilizing Matlab software, and inputting power distribution network parameters, distributed power supply output constraint conditions and original data of a load sample into the simulation model;
collecting original data of load samples every day in selected days at equal time intervals, carrying out clustering analysis on the original data of the load samples by adopting an improved fuzzy C-means clustering algorithm, dividing scenes according to the optimal clustering number, wherein the scene number is the same as the optimal clustering number, and respectively obtaining the proportion of each load scene and the load volatility index of each scene in a sampling time period;
obtaining voltage fluctuation values of each node under each scene through load flow calculation, wherein the voltage fluctuation values of the nodes are divided into an increasing direction and a decreasing direction, and the adequacy of the upward voltage fluctuation of the nodes and the adequacy of the downward voltage fluctuation of the nodes are respectively obtained according to the voltage fluctuation values of the nodes and a node flexibility adequacy formula;
selecting a time scale, calculating and obtaining the voltage fluctuation value of each node at each moment according to the load flow in an operation period, judging the voltage fluctuation direction, calculating and obtaining the flexibility value of each node and the system operation flexibility value respectively according to the flexibility index formula of the node and the system flexibility index formula at any moment, and outputting;
and step five, classifying and screening out the nodes with insufficient system operation flexibility and the moments with insufficient system operation flexibility according to the output node flexibility values, the system operation flexibility values and the set threshold values.
The power distribution network parameters in the first step comprise a node power distribution system type and a distributed power source type of an access node.
The output constraint conditions of the distributed power supply in the first step comprise power balance constraint, voltage safety constraint and energy storage constraint.
And the raw data of the load samples in the second step comprises the percentage of each load model.
The proportion formula of the load scene in the second step is as follows:
Hh＝ph/p
in the formula, HhIn a ratio of phP is the total number of raw load samples contained in the h-th typical load scenario.
The load fluctuation indexes of the scene in the second step are as follows:
Figure BDA0002293321580000021
in the formula: ebn SIs a load fluctuation index; n-1, 2, …, q-1; t is the period of sampling samples; pcIs the total system load;
Figure BDA0002293321580000022
the clustering center of the b scene in the (n + 1) th sampling period in the S iteration;
Figure BDA0002293321580000023
meaning of cluster center of the b-th scene at the S-th iteration of the nth sampling period.
The adequacy formula of the node voltage fluctuation in the third step is as follows:
Figure BDA0002293321580000024
Figure BDA0002293321580000025
in the formula: h is the optimal clustering number; hjThe proportion of the j typical load scene; f+ BFC,iIs a margin for voltage fluctuations upward of the node; f- BFC,iIs a margin for node-down voltage fluctuations; delta Ui +Is the per unit value of the increased voltage fluctuation value; delta Ui -Is the per unit value of the voltage fluctuation value reduction.
The flexibility index formula of the node is as follows:
Figure BDA0002293321580000031
in the formula: pr represents the probability; i isBFC,iIs the flexibility index of the node i; t is the period of sampling samples; delta URi,t +The voltage at the node i at the time t is a per unit value of the upward fluctuation amount; delta URi,t -Is a section at time tVoltage fluctuation amount per unit value at point i, F+ BFC,iIs a margin for upward voltage fluctuation at node i; f- BFC,iIs a sufficient margin for the voltage fluctuation downwards at node i.
The system operation flexibility index formula is as follows:
Figure BDA0002293321580000032
in the formula: pr represents the probability; i isSFC,tExpressing the system flexibility index at the time t; n is the number of nodes of the power distribution system; delta URi,t +The voltage at the node i at the time t is a per unit value of the upward fluctuation amount; delta URi,t -Is the per unit value of the voltage fluctuation at the node i at the time t, F+ BFC,iIs a margin for upward voltage fluctuation at node i; f- BFC,i -Is a sufficient margin for the voltage fluctuation downwards at node i.
Through the design scheme, the invention can bring the following beneficial effects:
according to the method, relevant factors influencing the operation flexibility are analyzed, the load scene is divided based on the improved fuzzy C-means clustering algorithm from the power distribution network voltage constraint, a calculation method of the operation flexibility quantitative evaluation index considering the load scene probability is provided, and the operation flexibility evaluation of the power distribution system with the high-proportion DG is realized in the aspects of space and time. The index can reflect the flexibility state and change of the system during operation, and the energy storage device plays a role in improving the operation flexibility of the power distribution system.
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The invention is further described with reference to the following figures and detailed description:
fig. 1 is a block flow diagram of a method for evaluating the operation flexibility of a power distribution system including a high-ratio distributed power source according to the present invention.
Fig. 2 is a photovoltaic power generation and net load diagram under a typical sunny normal condition of a certain area in the method for evaluating the operation flexibility of the power distribution system with the high-proportion distributed power supply.
Fig. 3 is a photovoltaic power generation and net load diagram under a condition that the photovoltaic of a certain area is doubled in a typical sunny day in the method for evaluating the operation flexibility of the power distribution system with the high-proportion distributed power supply.
Fig. 4 is a structural diagram of an IEEE33 node power distribution system in an embodiment of the method for evaluating the operational flexibility of a power distribution system with a high-ratio distributed power source according to the present invention.
FIG. 5 is a graph of the photovoltaic power generation and wind power generation output test results in an embodiment of the method for evaluating the operation flexibility of a power distribution system with a high-proportion distributed power source of the present invention.
FIG. 6 is a graph showing I of different nodes in an embodiment of the method for evaluating the operation flexibility of a power distribution system with a high-ratio distributed power supply according to the present inventionBFC,iAnd (5) distribution diagram.
FIG. 7 is a schematic diagram of an embodiment of a method for evaluating the operational flexibility of a power distribution system with high-ratio distributed power sources according to the present invention at different times ISFC,tAnd (5) distribution diagram.
FIG. 8 shows I before and after energy storage access in an embodiment of the method for evaluating the operation flexibility of a power distribution system with a high-proportion distributed power supply according to the present inventionBFC,iCompare the figures.
FIG. 9 shows I before and after energy storage access in an embodiment of the method for evaluating the operation flexibility of a power distribution system with a high-proportion distributed power supply according to the present inventionSFC,tAnd (5) distribution diagram.
Detailed Description
1. Factors affecting operational flexibility:
1.1 distributed Power supply
When a high proportion of DG is connected to a power distribution system, the power flow distribution of the system can change dramatically. Fig. 2 is a typical sunny solar photovoltaic power generation and net load actual measurement curve in aesculus of a certain area, fig. 3 is a typical sunny solar photovoltaic power generation and net load actual measurement curve in aesculus of the area, it can be seen that the fluctuation of net load is reduced by the access fluctuation DG at the initial moment, but the peak clipping effect is achieved by the access high-proportion DG, an obvious valley occurs in the net load mode, the fluctuation is increased, and therefore the requirement for operation flexibility is increased.
The DG output is uncertain and variable under the influence of natural environmentThe characteristic of sex. At a particular time scale Δ T, the DG output sequence PGi at node i is PGi ═ PDi1，PGi2...PGik...PGiT}. At time k, the output fluctuation value of DG may be expressed as Δ PDGik＝ΔPDGik+1-ΔPDGikThe DG force has two directions of increase and decrease, i.e. Δ PDGikThe positive and negative values of (a) correspond to the upward and downward flexibility of the power distribution system, respectively.
The DG output fluctuation sequence delta PGi at each moment can be obtained through calculation:
Figure BDA0002293321580000051
the magnitude of the delta PGi reflects the fluctuation degree of the DG output, and the larger the value of the delta PGi, the stronger the DG output fluctuation at the moment is, and the larger the probability that the insufficient operation flexibility of the power distribution system occurs is. Setting the maximum DG output fluctuation quantity which can be borne by the power distribution system as delta Pmax, and adopting a DG output fluctuation sequence delta PDGiComparison with Δ Pmax screens out periods of insufficient operating flexibility of the power distribution system and quantifies its severity.
1.2 load side
The load is divided into controllable load and uncontrollable load. In certain situations, the power distribution system may increase the flexibility of the system by adjusting controllable loads to respond to power fluctuations within the system, while uncontrollable loads may consume system flexibility resources.
The load characteristics of the power distribution system are characterized by typical load scenes, and the method has important significance for evaluating the operation flexibility of the power distribution system with the distributed power supply. At present, various researches on typical scene selection methods are carried out, the invention refers to an improved fuzzy C-means clustering algorithm, collects q load data with equal time intervals every day in p days for clustering analysis, and divides the load data into h scenes according to the optimal clustering number h. Where the load data sample X may be represented as:
Figure BDA0002293321580000052
in the formula: m is 1,2, …,p，n＝1,2,…,q；xmnThe load of the nth sample point on the mth day.
The cluster centers for h scenes are represented as:
Figure BDA0002293321580000053
wherein b is 1,2, …, h; s (s is more than or equal to 1, s belongs to N) is the iteration step number, and s is 1 initially.
Assuming that clustering division is completed when the iteration step number is S ═ S, h load typical scenes are obtained, and if the number of original load samples included in the h type of typical load scene is phThe proportion of the H-th load typical scene is Hh＝ph/p。
The fluctuation characteristics of the load typical scene can be reflected by adopting the load fluctuation indexes of the scene in the sampling time period. The index reflects the fluctuation degree of a typical scene of the load, and the larger the numerical value is, the larger the fluctuation of the load in the scene is; conversely, the smaller. Load fluctuation index Ebn SComprises the following steps:
Figure BDA0002293321580000061
in the formula:
Figure BDA0002293321580000062
is a load fluctuation index; n-1, 2, …, q-1; t is the period of sampling samples; pcIs the total system load;
Figure BDA0002293321580000063
the clustering center of the b scene in the (n + 1) th sampling period in the S iteration;meaning of cluster center of the b-th scene at the S-th iteration of the nth sampling period.
1.3 energy storage device
The energy storage device is an important component of the power distribution system, and can absorb redundant power when the output of the distributed power supply is higher than the load requirement; on the contrary, when the distributed output is lower than the load demand, the stored energy can release electric energy, namely the energy storage device can well stabilize the DG output and the fluctuation of the load. The energy storage in the discharge state can provide uplink flexibility by increasing discharge power, or provide downlink flexibility by reducing discharge and even reverse charge; the energy storage in the charging state can provide uplink flexibility by reducing charging and even reverse discharging, or provide downlink flexibility by increasing charging power.
1.4 time scale
The response characteristics of various schedulable resources of the power distribution system are closely related to the time characteristics, so that the selection of the time scale has a great influence on the evaluation of the operation flexibility of the power distribution system. The measurement of the operation flexibility of the power distribution system needs to be established under a certain time scale, and the value range of the time scale delta t is as follows: Δ t ═ 1min,5min,30min,1h }.
2. Evaluation index for operation flexibility of power distribution system
When a high-proportion distributed power supply is connected into a power distribution system, the main cause of system uncertainty is that the fluctuation of the output of the distributed power supply increases the phenomenon that the power of the system is unbalanced, so that the voltage of a system node changes, and further serious consequences such as voltage out-of-limit are caused. The ability of the node to tolerate voltage fluctuation reflects the operation flexibility of the power distribution system, and the operation flexibility of the power distribution system is evaluated spatially by adopting a node flexibility adequacy index; and evaluating the operation flexibility of the power distribution system in time by adopting a system flexibility adequacy index.
2.1 node flexibility adequacy index
The node voltage fluctuation is divided into two directions of increasing and decreasing, which are respectively marked as delta Ui +And Δ Ui -. The adequacy expression of the voltage fluctuation which the node can bear under the condition of considering the load scene and the system safe operation constraint is as follows:
Figure BDA0002293321580000071
Figure BDA0002293321580000072
in the formula: h is the optimal clustering number; hjThe proportion of the j typical load scene; f+ BFC,iIs a margin for voltage fluctuations upward of the node; f- BFC,iIs a margin for node-down voltage fluctuations; delta Ui +Is the per unit value of the increased voltage fluctuation value; delta Ui -Is the per unit value of the voltage fluctuation value reduction.
The node flexibility adequacy index is the probability that the node voltage fluctuation quantity does not exceed the voltage fluctuation adequacy range in a certain operation period T, and can reflect the operation flexibility condition of each node of the power distribution system. The calculation method is as follows:
Figure BDA0002293321580000073
in the formula: pr represents the probability; i isBFC,iIs the flexibility index of the node i; t is the period of sampling samples; delta URi,t +The voltage at the node i at the time t is a per unit value of the upward fluctuation amount; delta URi,t -Is the per unit value of the voltage fluctuation at the node i at the time t, F+ BFC,iIs a margin for upward voltage fluctuation at node i; f- BFC,iIs a sufficient margin for the voltage fluctuation downwards at node i.
2.2 System flexibility adequacy index
The system operation flexibility adequacy index can reflect the whole operation flexibility condition of the power distribution system at each moment, can be represented by the probability that the voltage fluctuation amount of each node at the moment t does not exceed the voltage fluctuation adequacy range, and the larger the index is, the more sufficient the system operation flexibility is. The calculation method is as follows:
in the formula: pr represents the probability; i isSFC,tExpressing the system flexibility index at the time t; n is the number of nodes of the power distribution system; delta URi,t +The voltage at the node i at the time t is a per unit value of the upward fluctuation amount; delta URi,t -Is the per unit value of the voltage fluctuation at the node i at the time t, F+ BFC,iIs a margin for upward voltage fluctuation at node i; f- BFC,iIs a sufficient margin for the voltage fluctuation downwards at node i.
Node flexibility adequacy index IBFC,iAnd the system operation flexibility adequacy index can be divided into 4 types according to the values thereof, as shown in table 1.
TABLE 1
Figure BDA0002293321580000081
2.3 constraint Condition
(1) Power balance constraint
For a node containing a distributed power supply, the power balance equation is:
Figure BDA0002293321580000082
in the formula: pGiIs the active power of node i; qGiIs the reactive power of node i; pLiIs the active load of node i; qLiReactive load of node i; delta PiActive change of a distributed power supply is node i; delta QiIs the reactive change of the distributed power supply of the node i; u shapeiIs the voltage at node i; u shapejIs the voltage at node j; gijConductance between nodes i and j; b isijIs the susceptance between nodes i and j; thetaijIs the phase angle difference between nodes i and j.
For nodes without distributed power sources, the power balance equation is:
Figure BDA0002293321580000083
(2) voltage safety constraints
Figure BDA0002293321580000091
In the formula: u shapei minIs the lower voltage limit at node i; u shapeiIs the voltage at node i; u shapei maxIs the upper voltage limit at node i.
(3) Restraint of stored energy
Figure BDA0002293321580000092
In the formula, Pess,minThe minimum value of the energy storage rated power is obtained; pessRated power for energy storage; pess,maxThe maximum value of the rated power of the stored energy; eess,minIs the minimum value of the rated capacity of the stored energy; eessRated capacity for energy storage; eess,maxIs the maximum value of the rated capacity of the energy storage.
2.4 evaluation method for operation flexibility of power distribution system with high proportion distributed power supply:
under the condition of considering the operation flexibility constraint, the invention solves the operation flexibility index, and the steps shown in figure 1 are as follows:
(1) and inputting original data such as power distribution network parameters, distributed power output, load samples and the like.
(2) Clustering load scenes by adopting an improved fuzzy C-means clustering algorithm, and calculating HhAnd Ebn S。
(3) Performing load flow calculation, and optimizing the flexibility of the node FBFCAnd (6) performing calculation.
(4) Selecting a proper time scale, and calculating to obtain delta U at each moment according to the load flow in an operation periodRiAnd judging the direction, and respectively calculating the index I of sufficient flexibility of each node according to the formulas (7) and (8)BFC,iAnd a system flexibility index ISFC,t。
(5) And outputting the calculation result, and ending.
3. Specific examples are as follows:
the embodiment of the invention adopts an improved IEEE33 node power distribution system to evaluate the operation flexibility of the power distribution system with a high-proportion distributed power supply, and the structure diagram of a topological network is shown in figure 4. The distributed power supply takes photovoltaic power generation and wind power generation as examples, 1 distributed photovoltaic power generation access node 5 of 1MW, 1 distributed wind power generation access node 2 of 1MW, 1 distributed wind power generation access node 20 of 0.6MW, 1 distributed wind power generation access node 33 of 0.5MW, and the working range of node voltage is [0.95,1.05 ]]. The reference power was 10MW and the reference voltage was 12.66 kV. The maximum fluctuation of wind power generation and photovoltaic power generation is limited to 0.2 MW. The photovoltaic power generation and wind power generation output test results are shown in fig. 5. Load typical scene sequence ratio sum Ebn SAs shown in table 1. Typical load scene coefficients and photovoltaic and wind turbine data are shown in table 2. Typical load scenario parameters are shown in table 3.
TABLE 2
Figure BDA0002293321580000101
TABLE 3
Figure BDA0002293321580000102
From the data in Table 2, F can be calculated according to equation (5)+ BFCIs 0.013, F is calculated according to the formula (6)- BFCIs 0.02. Calculating the flexibility index I of each node in one operation period according to the load flowBFC,iThe distribution of (2) is shown in fig. 6. As can be seen from fig. 6, I at the access node (node 5, node 20, node 33) of the distributed power supply and its neighboring nodesBFCLow; i at node 18 and node 33 at the end of the lineBFCLow; indicating that the operational flexibility of these nodes is severely inadequate. Since node 33 is both an end-of-line node and an access point for distributed power, IBFCThe situation of insufficient minimum operation flexibility is the most serious; closer to balancing node IBFCThe higher the value, the more flexibility. In addition, I of different nodesBFC,iDistribution of each phaseMeanwhile, the characteristic that the operation flexibility distribution of the power distribution system has spatiality is explained. In conclusion, the access of a high-proportion distributed power supply to a power distribution system can cause the serious shortage of operation flexibility at the tail end of a line and the access position of the distributed power supply, and further cause the occurrence of load shedding or wind and light abandoning phenomena; the closer to the balance node, the more sufficient the operation flexibility; node flexibility index IBFC,iCan select the not enough node of operation flexibility, and then evaluate distribution system's operation flexibility from the space perspective.
FIG. 7 is a system flexibility index I for a time scale of 1hSFC,tDistribution of (2). As can be seen from the figure, the system flexibility index I at different momentsSFC,tThere is a large difference. According to ISFC,tThe distribution is known as I at times 7, 17, 18, 20SFC,tIf the value is too small, the system operation flexibility at the moment is seriously insufficient, and the overvoltage phenomenon can be caused, so that the system operation is seriously influenced; at times 6, 13, 16, 19ISFC,tThe value is small, and the system operation flexibility is insufficient. Comparing fig. 4 with the wind-solar distributed power output data, the following conclusions can be drawn: the running flexibility at the moment 6 is insufficient because the distributed photovoltaic power generation starts to output power; the main reason for the insufficient operational flexibility at the time points 7, 16, 17, 18 and 19 is that the output fluctuation of the distributed power supply is severe; the reason for insufficient operation flexibility at the time 13 is that the time is the peak time of distributed photovoltaic power generation output within the operation day, and nodes of a power imbalance or voltage line crossing phenomenon in the system are increased. To sum up, ISFC,tThe moment when the operation flexibility of the power distribution system is insufficient can be screened out, the severity of the moment can be quantified, and the distribution condition of the operation flexibility of the power distribution system can be evaluated from the time perspective.
Energy storage devices are respectively configured for the distributed photovoltaic power source at the node 5, the distributed wind power source at the node 20 and the node 33. Before and after the energy storage device is connected, I of partial nodeBFC,i，ISFC,tThe distribution is shown in fig. 8 and 9, respectively.
As can be seen from fig. 8, after the energy storage device session is connected, the node 5 with insufficient operational flexibility and the node with severely insufficient operational flexibility are operatedAt nodes 20, 33BFC,iThe operation flexibility of the nodes is increased to be sufficient from 0.71, 0.67 and 0.42 to 1, 1 and 0.96 respectively. As can be seen from fig. 9, after the energy storage device is connected, the times of insufficient operation flexibility and serious insufficiency are obviously reduced, and the operation flexibility of the power distribution system is effectively improved. In conclusion, the operation flexibility of the power distribution system can be obviously improved by accessing the energy storage device, and the energy storage device can be arranged according to the abundant condition of the operation flexibility in the system in the actual operation.
The invention provides an evaluation index and a method for the operation flexibility of a power distribution system by analyzing relevant influence factors of the operation flexibility, clustering and dividing a load scene by adopting an improved fuzzy C-means clustering algorithm and considering the space structure and the time scale of the power distribution system aiming at the power distribution system containing a high-proportion distributed power supply. By evaluating the flexibility of operation of the improved IEEE33 system, the following conclusions were made:
1) the evaluation index of the operation flexibility of the power distribution system provided by the invention can quantitatively evaluate the operation flexibility of the power distribution system and provides nodes and moments with insufficient system operation flexibility.
2) From the space perspective, the phenomenon of insufficient operation flexibility is easily generated by nodes accessed into the distributed power supply and nodes at the tail end of the line; from a time point of view, insufficient operational flexibility may easily occur at a time point when power fluctuation is severe.
3) The energy storage device is placed at the distributed power supply access position, so that the operation flexibility of the power distribution system can be obviously improved.
Through the analysis, Matlab simulation software is used for verifying the correctness and the effectiveness of the operation flexibility evaluation index provided by the invention, and the influence of energy storage on the improvement of the operation flexibility is preliminarily researched.

Claims (9)

1. The method for evaluating the operation flexibility of the power distribution system with the high-proportion distributed power supply is characterized by comprising the following steps: comprises the following steps which are sequentially carried out,
firstly, establishing a power distribution system operation flexibility index simulation model containing a high-proportion distributed power supply by utilizing Matlab software, and inputting power distribution network parameters, distributed power supply output constraint conditions and original data of a load sample into the simulation model;
collecting original data of load samples every day in selected days at equal time intervals, carrying out clustering analysis on the original data of the load samples by adopting an improved fuzzy C-means clustering algorithm, dividing scenes according to the optimal clustering number, wherein the scene number is the same as the optimal clustering number, and respectively obtaining the proportion of each load scene and the load volatility index of each scene in a sampling time period;
obtaining voltage fluctuation values of each node under each scene through load flow calculation, wherein the voltage fluctuation values of the nodes are divided into an increasing direction and a decreasing direction, and the adequacy of the upward voltage fluctuation of the nodes and the adequacy of the downward voltage fluctuation of the nodes are respectively obtained according to the voltage fluctuation values of the nodes and a node flexibility adequacy formula;
selecting a time scale, calculating and obtaining the voltage fluctuation value of each node at each moment according to the load flow in an operation period, judging the voltage fluctuation direction, calculating and obtaining the flexibility value of each node and the system operation flexibility value respectively according to the flexibility index formula of the node and the system flexibility index formula at any moment, and outputting;
and step five, classifying and screening out the nodes with insufficient system operation flexibility and the moments with insufficient system operation flexibility according to the output node flexibility values, the system operation flexibility values and the set threshold values.
2. The method of claim 1, wherein the method comprises the steps of: the power distribution network parameters in the first step comprise a node power distribution system type and a distributed power source type of an access node.
3. The method of claim 1, wherein the method comprises the steps of: the output constraint conditions of the distributed power supply in the first step comprise power balance constraint, voltage safety constraint and energy storage constraint.
4. The method of claim 1, wherein the method comprises the steps of: and the raw data of the load samples in the second step comprises the percentage of each load model.
5. The method of claim 1, wherein the method comprises the steps of: the proportion formula of the load scene in the second step is as follows:
Hh＝ph/p
in the formula, HhIn a ratio of phP is the total number of raw load samples contained in the h-th typical load scenario.
6. The method of claim 1, wherein the method comprises the steps of: the load fluctuation indexes of the scene in the second step are as follows:
Figure FDA0002293321570000021
in the formula: ebn SIs a load fluctuation index; n-1, 2, …, q-1; t is the period of sampling samples; pcIs the total system load;
Figure FDA0002293321570000022
the clustering center of the b scene in the (n + 1) th sampling period in the S iteration;meaning of cluster center of the b-th scene at the S-th iteration of the nth sampling period.
7. The method of claim 1, wherein the method comprises the steps of: the adequacy formula of the node voltage fluctuation in the third step is as follows:
in the formula: h is the optimal clustering number; hjThe proportion of the j typical load scene; f+ BFC,iIs a margin for upward voltage fluctuation at node i; f- BFC,iIs a margin for the voltage fluctuation downwards at node i; delta Ui +Is the per unit value of the increased voltage fluctuation value; delta Ui -Is the per unit value of the voltage fluctuation value reduction.
8. The method of claim 1, wherein the method comprises the steps of: the flexibility index formula of the node is as follows:
Figure FDA0002293321570000026
in the formula: pr represents the probability; i isBFC,iIs the flexibility index of the node i; t is the period of sampling samples; delta URi,t +The voltage at the node i at the time t is a per unit value of the upward fluctuation amount; delta URi,t -Is the per unit value of the voltage fluctuation at the node i at the time t, F+ BFC,iIs a margin for upward voltage fluctuation at node i; f- BFC,iIs a sufficient margin for the voltage fluctuation downwards at node i.
9. The method of claim 1, wherein the method comprises the steps of: the system operation flexibility index formula is as follows:
Figure FDA0002293321570000031
in the formula: pr represents the probability; i isSFC,tExpressing the system flexibility index at the time t; n is the number of nodes of the power distribution system; delta URi,t +The voltage at the node i at the time t is a per unit value of the upward fluctuation amount; delta URi,t -Is the per unit value of the voltage fluctuation at the node i at the time t, F+ BFC,iIs a margin for upward voltage fluctuation at node i; f- BFC,iIs a sufficient margin for the voltage fluctuation downwards at node i.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116054282A (en) * 2022-11-25 2023-05-02 国网安徽省电力有限公司经济技术研究院 Active and reactive flexibility assessment method for public connection point of power distribution network and power transmission network

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107947165A (en) * 2017-11-30 2018-04-20 国网浙江省电力公司经济技术研究院 A kind of power distribution network flexibility evaluation method towards regulatory demand
CN110119889A (en) * 2019-04-26 2019-08-13 武汉大学 A kind of evaluation of power distribution network joint mobility and partition method

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107947165A (en) * 2017-11-30 2018-04-20 国网浙江省电力公司经济技术研究院 A kind of power distribution network flexibility evaluation method towards regulatory demand
CN110119889A (en) * 2019-04-26 2019-08-13 武汉大学 A kind of evaluation of power distribution network joint mobility and partition method

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
周光东;周明;孙黎滢;郭尊;谷纪亭;孙轶恺;: "含波动性电源的电力系统运行灵活性评价方法研究" *
彭春华;于蓉;孙惠娟;: "基于K-均值聚类多场景时序特性分析的分布式电源多目标规划" *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116054282A (en) * 2022-11-25 2023-05-02 国网安徽省电力有限公司经济技术研究院 Active and reactive flexibility assessment method for public connection point of power distribution network and power transmission network
CN116054282B (en) * 2022-11-25 2023-08-18 国网安徽省电力有限公司经济技术研究院 Active and reactive flexibility assessment method for public connection point of power distribution network and power transmission network

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