CN115224729A - Distributed power supply peak regulation dynamic control method - Google Patents

Distributed power supply peak regulation dynamic control method Download PDF

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CN115224729A
CN115224729A CN202210848852.0A CN202210848852A CN115224729A CN 115224729 A CN115224729 A CN 115224729A CN 202210848852 A CN202210848852 A CN 202210848852A CN 115224729 A CN115224729 A CN 115224729A
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peak shaving
peak
power
power supply
cluster
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CN115224729B (en
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李宏伟
徐晴
宋蕙慧
王仕韬
罗兴
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State Grid Corp of China SGCC
State Grid of China Technology College
Shandong Electric Power College
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State Grid Corp of China SGCC
State Grid of China Technology College
Shandong Electric Power College
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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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply
    • 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
    • H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
    • H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
    • 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
    • H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
    • 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
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]

Abstract

The application provides a peak regulation dynamic control method for a distributed power supply, which comprises the following steps: determination of peak shaving performance index gamma j J =1 \ 82304; based on said γ in each peak regulation period j Sorting the peak shaving priority of DG units participating in power grid peak shaving in each power supply cluster, and controlling each power supply cluster to carry out power grid peak shaving in the peak shaving period according to the sorting result; at each evaluation period, based on the gamma j Evaluating the peak shaving performance of DG units participating in power grid peak shaving in each power supply cluster, updating a peak shaving prohibition list according to the evaluation result and determining the next evaluation periodAnd the DG units are internally involved in power grid peak shaving, wherein each evaluation period comprises at least one peak shaving period. The dynamic control method for peak shaving of the distributed power supply can reasonably sort and evaluate DG units in a distributed power supply cluster, establishes a multi-dimensional self-updating mechanism, and can more accurately perform peak shaving of the distributed power supply.

Description

Distributed power supply peak regulation dynamic control method
Technical Field
The application belongs to the technical field of power system control, and particularly provides a peak shaving dynamic control method for a distributed power supply.
Background
With the gradual expansion of the scale of the power grid, the non-uniformity of power supply and load exists in different areas and time periods, the mismatching of power supply and demand will cause the problems of insufficient or excessive electric energy, etc., which not only causes the waste of energy, but also may cause impact on the power grid system due to the overlarge peak-valley difference of power flow, and increases the risk of equipment failure.
In order to avoid the problems, the peak-valley of the electric load is adjusted by economic means such as adjusting the price of electricity, and the peak regulation of the power grid can be realized by actively adjusting the power supply. In recent years, with the great development of green energy technologies such as photovoltaic power generation and wind power generation, distributed photovoltaic/wind power generation units and other DG units increasingly participate in power grid peak shaving, and support is provided for determining stable and efficient operation of a power grid.
In practical application, DG units distributed in different regions are generally integrated into a plurality of power clusters, each power cluster includes a different number of DG units, and after receiving a power grid peak shaving task, different power clusters autonomously control each internal DG unit to perform power grid peak shaving. Obviously, whether the corresponding DG unit can be reasonably selected and regulated inside each power supply cluster to participate in power grid peak shaving or not directly determines the overall peak shaving effect of the distributed power supply.
At present, various power grid peak regulation evaluation and sequencing methods exist, for example, a comprehensive evaluation value calculation and sequencing method based on an integrated weighting method is proposed in patent CN 112258222A: firstly, considering the economy of photovoltaic participation power grid auxiliary service, designing 6 evaluation indexes, then determining objective weight and subjective weight based on an entropy weight method and a characteristic value method respectively, carrying out combined weighting on the evaluation indexes based on an integrated weighting method to obtain a comprehensive evaluation value, and finally sequencing the photovoltaic based on the obtained comprehensive evaluation value, thereby providing basis for selecting the photovoltaic participation power grid scheduling, but the method only adopts the characteristic value method to carry out subjective weighting, and has certain limitation; and then, the photovoltaics are directly sorted according to the obtained comprehensive evaluation value, and an objective and effective sorting method is lacked.
Also, for example, spring generator et al proposes a priority ranking scheme of user participation in power grid peak shaving based on an improved TOPSIS method (user-side power grid peak shaving mechanism [ J ] based on priority ranking, science and technology and engineering, 2020,20 (30): 12436-12442.) by taking the minimum power consumption cost of a user as a target function, designing through multiple indexes, determining the index weight based on an entropy weight method, and applying the improved TOPSIS method to obtain the priority ranking of the users participating in peak shaving in each round, thereby finally determining a list of the users participating in peak shaving, wherein 4 designed peak shaving evaluation indexes cannot comprehensively reflect the advantages and disadvantages of the performance of the users participating in power grid peak shaving, and lack of evaluation indexes of dimensions such as regulation rate, response rate, regulation precision and the like; and then, the index weight is determined only by adopting an entropy weight method, and the operation is unilateral.
In addition, in the two schemes, the DG units or users participating in the grid auxiliary service cannot be subjected to high-quality elimination according to the obtained comprehensive evaluation sequencing result, a reasonable control and dynamic updating scheme for each DG unit or user cannot be further provided, the distributed DG units which are not beneficial to aggregation and scheduling cannot be removed in time, and low cluster scheduling efficiency and unsustainable development are easily caused.
Disclosure of Invention
In order to solve the above problems in the prior art, an object of the present application is to provide a distributed power peak regulation dynamic control method. The embodiment of the application can be realized by the following technical scheme:
a peak regulation dynamic control method for a distributed power supply comprises the following steps:
s1: determination of peak shaving performance index gamma j ,j＝1...4；
S2: at each peak regulation period based on said gamma j Sequencing the peak shaving priority of DG units participating in power grid peak shaving in each power supply cluster, and controlling each power supply cluster to carry out power grid peak shaving in the peak shaving period according to the sequencing result;
s3: at each evaluation period, based on the gamma j Evaluating peak shaving performances of DG units participating in power grid peak shaving in each power supply cluster, updating a peak shaving forbidding list according to evaluation results, and determining the DG units participating in power grid peak shaving in the next evaluation period, wherein each evaluation period comprises at least one peak shaving period.
Preferably, said γ is j Comprises the following steps:
Figure BDA0003754079040000021
wherein ,vreal 、v stand 、Δt real 、Δt stand 、Δp max 、Δp real 、Δp target The actual power change rate, the standard power change rate, the actual response time, the standard response time, the maximum adjustable power, the actual peak-load output and the target peak-load output of the DG unit, respectively, are delta P max The maximum adjustable power of the power cluster in which the DG unit is located.
Further, in step S2, the peak shaving priorities of the DG units in each power cluster participating in the peak shaving of the power grid are sorted, specifically, the following steps are performed for each power cluster:
s11: obtaining an evaluation matrix A of DG units participating in power grid peak shaving in the power supply cluster,
Figure BDA0003754079040000022
wherein M is the number of DG units participating in power grid peak shaving in the power supply cluster, a ij The jth peak shaving performance index gamma of the ith DG unit participating in power grid peak shaving j The calculated value of (a);
s12: determining a combined weight w of peak shaver performance indicators of the power supply cluster based on j ，
w j ＝s 1 w 1j +s 2 w 2j ,j＝1...4，
wherein ,w1j 、w 2j Are respectively gamma j Corresponding objective and subjective weights, s 1 、s 2 Are respectively w 1j 、w 2j The weight coefficient of (a);
s13: based on the A and w j And carrying out peak shaving priority sequencing on the M DG units participating in the power grid peak shaving of the power supply cluster.
Further, the objective weight w 1j Is determined by the following steps:
firstly, standardizing the evaluation matrix A to obtain a standardized evaluation matrix
Figure BDA0003754079040000023
wherein
Figure BDA0003754079040000024
Is a pair of ij Values after normalization processing;
second, obtaining A * Probability matrix P = (P) ij ) M×4, wherein
Figure BDA0003754079040000031
Third, calculating gamma j Information entropy e of j ，
Figure BDA0003754079040000032
The fourth step, calculate gamma j Information utility value of G j ，
G j ＝1-e j ，j＝1...4；
The fifth step, calculate gamma j Objective weight w of 1j ，
Figure BDA0003754079040000033
Further, the subjective weight w 2j Is determined by the following steps:
firstly, constructing a judgment matrix Y of peak regulation performance indexes based on an analytic hierarchy process,
Figure BDA0003754079040000034
wherein any element y kj Represents gamma k And gamma j A quantitative scale of importance for making the comparison determination;
secondly, calculating a consistency index CI of Y,
Figure BDA0003754079040000035
wherein ,λmax The largest characteristic root of Y;
thirdly, a consistency test is performed on Y based on the following formula
Figure BDA0003754079040000036
Wherein, RI is an average random consistency index, if Y passes consistency check, the next step is executed, otherwise, the first step is returned to reconstruct Y;
the fourth step, calculate gamma j Subjective weight w of 2j ，
Figure BDA0003754079040000037
wherein ,α1j 、α 2j 、α 3j The arithmetic mean weight, the geometric mean weight, and the eigenvalue weight of Y, respectively.
Specifically, step S13 further includes the steps of:
firstly, normalizing A to obtain a normalized evaluation matrix B = (B) ij ) M×4, wherein
Figure BDA0003754079040000041
Secondly, calculating a weighted evaluation matrix R,
Figure BDA0003754079040000042
thirdly, calculating the positive ideal solution R of the power supply cluster + And negative ideal solution R - ，
Figure BDA0003754079040000043
wherein ,rj + ＝max[r 1j ，r 2j ，...r Mj ]，r j - ＝min[r 1j ，r 2j ，...r Mj ]；
Fourthly, calculating the closeness indexes of M DG units
Figure BDA0003754079040000047
Figure BDA0003754079040000044
wherein ,
Figure BDA0003754079040000045
the fifth step is based on
Figure BDA0003754079040000048
i =1.. M orders the peak shaver priorities of M DG units.
Specifically, step S3 further includes performing the following steps for each power cluster:
s31: calculating the compliance gamma of M DG units participating in power grid peak shaving in the power supply cluster i ，
Figure BDA0003754079040000046
Wherein L is the number of peak regulation periods contained in the evaluation period, gamma 1，i，l 、γ 2，i，l 、γ 3，i，l Respectively is the performance evaluation index gamma of the ith DG unit participating in the peak shaving of the power grid in the l peak shaving period of the evaluation period 1 、γ 2 、γ 3 The calculated value of (a);
s32: calculating the degree M of the practice of M DG units participating in power grid peak regulation in the power cluster i ，
Figure BDA0003754079040000051
wherein γ4，i，l The performance evaluation index gamma of the ith DG unit participating in power grid peak shaving in the l peak shaving period of the evaluation period 4 The calculated value of (a);
s33: evaluating M DG units participating in power grid peak shaving in the power supply cluster according to the compliance and the convention;
s34: updating the forbidden peak list, including i And M i Any DG unit which does not meet the corresponding qualified standard is placed into a peak regulation forbidding list, and the DG unit which meets the shifting-out condition in the peak regulation forbidding list is shifted out of the peak regulation forbidding listA list of peaks;
s35: and determining DG units participating in power grid peak shaving in the next evaluation period according to the evaluation result and the updated forbidden peak shaving list.
Preferably, step S3 further comprises the steps of:
counting integrity N of all DG units in the power supply cluster g And moving DG units with integrity level 0 out of the power cluster, wherein
Figure BDA0003754079040000052
G is the number of DG units in the power cluster.
The distributed power supply peak regulation dynamic control method provided by the embodiment of the application at least has the following beneficial effects:
(1) The method comprises the steps of comprehensively considering performance parameters of multiple aspects of a power supply cluster and distributed DG units in the power supply cluster, and establishing peak regulation performance indexes, so that the reasonability of peak regulation priority sequencing on the DG units in the power supply cluster is ensured, starting from 4 aspects of peak regulation precision, response rate and the like, and improving the overall peak regulation performance and effect;
(2) Aiming at the actual task completion condition of the DG unit participating in the power grid peak shaving, a unified peak shaving evaluation standard is provided, a three-dimensional dynamic evaluation system is constructed, and the peak shaving performance, the peak shaving precision and the historical peak shaving condition of the DG unit participating in the power grid peak shaving can be comprehensively and objectively evaluated from three aspects of compliance, practice degree and integrity degree;
(3) A self-updating mechanism of DG units in the distributed power supply cluster is established, peak regulation permission of the DG units participating in the cluster peak regulation task is reserved or cancelled by combining the obtained three-dimensional evaluation result, effective control of the DG units in the distributed power supply cluster and good completion of the peak regulation task by the cluster are facilitated, the overall peak regulation capability of the power supply cluster is timely updated based on conditions such as the cancellation of the peak regulation permission, and reasonable distribution of the peak regulation task with the cluster as a unit is facilitated.
Drawings
Fig. 1 is a flowchart of a distributed power peak shaving dynamic control method according to an embodiment of the present application;
fig. 2 is a schematic flowchart of evaluating peak shaving performance of DG units according to an embodiment of the present application;
fig. 3 to fig. 5 are weight conditions of peak shaving performance indexes of three power clusters in different peak shaving cycles in embodiment 1, respectively;
fig. 6 (a) to 6 (c) respectively show the overall peak shaving precision obtained by the three power clusters of embodiment 1 in different peak shaving cycles according to different weighting conditions;
fig. 7 (a) to 7 (c) are respectively the overall response rates obtained by the three power clusters of embodiment 1 in different peak shaving periods according to different empowerment conditions;
fig. 8 (a) to 8 (c) are the overall regulation rates obtained by the three power clusters of example 1 according to different weighting conditions in different peak regulation periods, respectively;
fig. 9 (a) to 9 (c) are respectively the compliance and the compliance of the respective DG units participating in the peak shaving at the end of one evaluation period for the three power clusters of example 1;
fig. 10 is a comparison of the total peak shaving accuracy under the conditions where the prohibition period is set and where the prohibition period is not set.
Detailed Description
Hereinafter, the present application will be further described based on preferred embodiments with reference to the drawings.
In addition, various components on the drawings are enlarged or reduced for convenience of understanding, but this is not intended to limit the scope of the present application.
Singular references also include plural references and vice versa.
In the description of the embodiments of the present application, it should be noted that if the terms "upper", "lower", "inner", "outer", etc. are used for indicating the orientation or positional relationship based on the orientation or positional relationship shown in the drawings or the orientation or positional relationship which is usually arranged when the products of the embodiments of the present application are used, the description is only for convenience and simplicity, but the indication or suggestion that the referred device or element must have a specific orientation, be constructed in a specific orientation and be operated, and thus, the application cannot be construed as being limited. Moreover, the terms first, second, etc. may be used in the description to distinguish between different elements, but these should not be limited by the order of manufacture or by importance to be understood as indicating or implying any particular importance, and their names may differ from their names in the detailed description of the application and the claims.
The terminology used in the description is for the purpose of describing the embodiments of the application and is not intended to be limiting of the application. It is also to be understood that, unless otherwise expressly stated or limited, the terms "disposed," "connected," and "connected" are intended to be open-ended, i.e., may be fixedly connected, detachably connected, or integrally connected; they may be mechanically coupled, directly coupled, indirectly coupled through intervening media, or interconnected between two elements. The specific meaning of the above terms in the present application will be specifically understood by those skilled in the art.
The application provides a peak regulation dynamic control method for a distributed power supply, which comprises the following steps:
s1: determination of peak shaving performance index gamma j ,j＝1…4；
S2: at each peak regulation period based on said gamma j Sequencing the peak shaving priority of DG units participating in power grid peak shaving in each power supply cluster, and controlling each power supply cluster to carry out power grid peak shaving in the peak shaving period according to the sequencing result;
s3: at each evaluation period, based on the gamma j Evaluating peak shaving performances of DG units participating in power grid peak shaving in each power supply cluster, updating a peak shaving forbidding list according to evaluation results, and determining the DG units participating in power grid peak shaving in the next evaluation period, wherein each evaluation period comprises at least one peak shaving period.
Fig. 1 is a flowchart of a peak shaving dynamic control method for a distributed power supply according to an embodiment of the present application, in the method, first, performance parameters of multiple aspects of a power supply cluster and each distributed DG unit in the power supply cluster are considered comprehensively to establish a peak shaving performance index; then, dynamically sequencing peak shaving priority according to peak shaving performance indexes of DG units in each power supply cluster and carrying out power grid peak shaving according to sequencing results; and the dynamic sequencing and peak shaving are repeatedly executed in each peak shaving period until the end point of one evaluation period is reached, and then multi-dimensional evaluation is carried out according to peak shaving performances of the DG units in a plurality of peak shaving periods contained in the evaluation period so as to determine the DG units qualified to participate in the power grid peak shaving in the next evaluation period.
The following describes steps S1 to S3 in detail with reference to the drawings and embodiments.
Step S1 for determining a peak shaver Performance index γ j ，j＝1...4。
The peak regulation performance index is a basis for calculating and evaluating the peak regulation capability and the peak regulation performance of each distributed DG unit in the power supply cluster, and the proper selection of the peak regulation performance index directly influences the control and regulation effects of the DG units participating in peak regulation based on the peak regulation performance index, so that parameters influencing the power grid peak regulation should be comprehensively considered in multiple dimensions when the peak regulation performance index is selected, and the rationality of subsequent evaluation and control is ensured. The peak shaving performance index in the examples of the present application is explained in detail below.
γ 1 The adjustment rate of the DG unit is used for measuring the speed of the DG unit for carrying out peak shaving according to the peak shaving instruction.
In particular, the amount of the solvent to be used,
Figure BDA0003754079040000071
wherein vreal 、v stand The real power change rate and the standard power change rate of the DG unit are respectively.
In some specific embodiments, v real Can be obtained by the following formula:
Figure BDA0003754079040000072
in the formula te 、t s Are respectively at the topStarting and ending time of a peak regulation period, p e 、p s The output power at the beginning and end of the last peak-shaving period respectively.
In some preferred embodiments, γ 1 The maximum value of (A) is 1.5, and values exceeding 1.5 are calculated as 1.5. In other preferred embodiments, γ 1 The maximum value of (A) is 1.2, and values exceeding 1.2 are all calculated according to 1.2.
The significance of setting the peak shaving performance index upper limit is that the evaluation of the peak shaving performance of the DG unit needs to be comprehensively considered from multiple dimensions, rather than considering only the performance of a certain aspect. In the process of peak shaving of the power grid, factors such as the regulation rate, the stability and the continuity of the DG units are mutually influenced in a coupling manner, and the regulation rate is excessively increased unilaterally, so that adverse impact on the power grid can be caused, the load of a single DG unit can be increased, the loss and the fault probability of the unit can be increased, the service life of the unit can be reduced, and the performance of the whole power supply cluster can be influenced. Therefore, from the perspective of overall performance of the power cluster, and by referring to performance standards of power grid peak shaving in different regions, reasonable adjusting speed intervals are set for each DG unit, and the situation that the DG units excessively pursue a certain index to cause other bad results and excessive investment can be effectively avoided.
γ 2 For the response rate of a DG unit, the speed of the DG unit responding to the peak shaving instruction can be measured by comparing the actual response time of the DG unit with the standard response time.
In particular, the amount of the solvent to be used,
Figure BDA0003754079040000073
wherein ,Δtreal 、Δt stand The actual response time and the standard response time of the DG unit are respectively (the response time refers to the time for the DG unit to reliably span out an adjustment dead zone consistent with the adjustment direction on the basis of the original force output point after the peak regulation instruction is sent out by the power grid).
In some specific embodiments, Δ t real May be determined based on the actual response time of the DG unit in the last peak shaver cycle.
In the examples of the present application, γ 2 Configured as a very large index (i.e., the shorter the response time, the larger the index), in order to avoid that some DG units have too long response time and thus the calculated value of the index becomes negative, and in order to avoid too large an influence on the calculation of the subsequent compliance, it is necessary to apply to gamma 2 A reasonable lower limit is set. To this end, in some preferred embodiments, γ 2 The minimum limit of (2) is 0.1, and all values below 0.1 are calculated as 0.1.
γ 3 The adjustable capacity of a DG unit is used for measuring the proportion of the maximum adjustable power of one DG unit in a power supply cluster in which the DG unit is positioned.
In particular, the amount of the solvent to be used,
Figure BDA0003754079040000081
wherein Δpmax Is the maximum adjustable power (the maximum adjustable power of DG unit based on original output point after receiving peak regulation instruction), Δ P max The maximum adjustable power of the power cluster in which the DG unit is located, specifically, the maximum adjustable power of each DG unit of the power cluster in which the DG unit is located.
γ 4 The peak shaving precision of the DG unit is used for measuring the reliability and the peak shaving precision of one DG unit for finishing the peak shaving task.
In particular, the amount of the solvent to be used,
Figure BDA0003754079040000082
wherein Δpreal 、Δp target The actual peak shaver output and the target peak shaver output of the DG unit are respectively.
In some embodiments, and v real And Δ t real Similarly,. DELTA.p real 、Δp taraet May be determined based on actual data of the last peak shaver period.
The peak shaving performance index determined in step S1 is described in detail above, and after the peak shaving performance index is determined, as shown in fig. 1, each power supply cluster is controlled to perform peak shaving priority ranking in each peak shaving period through step S2, and power grid peak shaving is performed according to the ranking result.
In an embodiment of the present application, for each power supply cluster, the peak shaver priority ranking is performed by:
s11: obtaining an evaluation matrix A of DG units participating in power grid peak shaving in the power cluster,
Figure BDA0003754079040000083
wherein M is the number of DG units participating in power grid peak shaving in the power supply cluster, a ij The jth peak shaving performance index gamma of the ith DG unit participating in the peak shaving of the power grid j The calculated value of (a);
s12: determining a combined weight w of peak shaver performance indicators of the power supply cluster based on j ，
w j ＝s 1 w 1j +s 2 w 2j ，j＝1...4，
wherein ,w1j 、w 2j Are respectively gamma j Corresponding objective and subjective weights, s 1 、s 2 Are respectively w 1j 、w 2j The weight coefficient of (a);
s13: based on the A and w j And carrying out peak shaving priority sequencing on the M DG units participating in the power grid peak shaving of the power supply cluster.
In some specific embodiments, an evaluation matrix a of DG units in the power cluster, which are involved in power grid peak shaving, is first constructed through step S11, and for a power cluster including M DG units, a is an M × 4 matrix. Obviously, if the sorting operation is performed at the beginning of each peaking cycle, each element a of the above-mentioned evaluation matrix ij The calculation should be performed based on the peak shaving performance index of the last peak shaving period, (especially, for the first peak shaving period, the historical data a of each DG unit can be used ij Assigned an initial value). Each element a of the evaluation matrix ij The obtaining method is described in detail above, and is not described herein again.
In some embodiments, evaluation matrix A is obtained byStep S12 of respectively calculating the peak regulation performance index gamma of the power supply cluster j Objective weight w of 1j And subjective weight w 2j And finally weighted and superposed to generate the combined weight w j 。w 1j Based on entropy weight method generation, w 2j Generated based on an analytic hierarchy process. The following detailed description of w 1j And w 2j The method of (1).
In some embodiments of the present application, w 1j The method is generated based on an entropy weight method, the entropy weight method distributes objective weight according to the information quantity contained in the information theory calculation index, the objective weight is calculated by the attribute numerical value of the evaluation object, and the discrimination between the evaluation objects can be improved. In particular, w 1j Is generated by the following steps:
firstly, standardizing the evaluation matrix A to obtain a standardized evaluation matrix
Figure BDA0003754079040000091
wherein
Figure BDA0003754079040000092
Is a to a ij Values after normalization processing;
second, obtaining A * Probability matrix P = (P) ij ) M×4, wherein
Figure BDA0003754079040000093
Third, calculating gamma j Information entropy e of j ，
Figure BDA0003754079040000094
The fourth step, calculate gamma j Information utility value of G j ，
C j ＝1-e j ，j＝1...4；
The fifth step, calculate gamma j Objective weight w of 1j ，
Figure BDA0003754079040000095
In some embodiments of the present application, w 2j The method is generated based on an analytic hierarchy process, the analytic hierarchy process hierarchically organizes complex indexes into a form of pairwise comparison between the indexes, analysis and research are facilitated, the importance degree of a certain index can be well reflected through the generated subjective weight, and a reference result expected by people is given in an evaluation result. In particular, w 2j The method comprises the following steps:
firstly, constructing a judgment matrix Y of peak regulation performance indexes based on an analytic hierarchy process,
Figure BDA0003754079040000096
wherein any element y kj Represents gamma k And gamma j A quantitative scale of importance for making the comparison determination;
secondly, calculating a consistency index CI of Y,
Figure BDA0003754079040000101
wherein ,λmax The largest characteristic root of Y;
thirdly, the consistency of Y is checked based on the following formula
Figure BDA0003754079040000102
Wherein, RI is an average random consistency index, if Y passes consistency check, the next step is executed, otherwise, the first step is returned to reconstruct Y;
the fourth step, calculate gamma j Subjective weight w of 2j ，
Figure BDA0003754079040000103
wherein ,α1j 、α 2j 、α 3j The arithmetic mean weight, the geometric mean weight, and the eigenvalue weight of Y, respectively.
In the process of generating subjective weight by using an analytic hierarchy process, importance degrees of any two indexes can be compared, and pairwise comparison results are assigned by a 1-9 scale method, so that a judgment matrix Y is obtained; by the establishment mode of the judgment matrix, the judgment matrix Y is known to be a positive and inverse matrix, and the maximum characteristic root lambda exists max (ii) a After the judgment matrix passes consistency check, 3 methods of an arithmetic mean method, a geometric mean method and a characteristic value method are adopted to calculate subjective weight alpha 1j 、α 2j 、α 3j And calculating the average value to finally obtain the subjective weight w 2j . Wherein, the indexes are assigned pairwise and the value is alpha by a 1-9 scale method 1j 、α 2j 、α 3j The determination method is a conventional technical means used in the analytic hierarchy process, and is not described herein again.
Respectively obtaining w through the steps 1j and w2j Then the weighted superposition is carried out to the peak shaving performance indexes to obtain the combined weight w of the peak shaving performance indexes of the power supply cluster j . Weight coefficient s 1 、s 2 The different weight coefficients represent different emphasis tendencies for objective versus subjective weights, which can be determined based on the performance of the power cluster and its containing units of DGs.
After the evaluation matrix a of the power supply cluster and the combined weight of the peak shaving performance index are obtained, the M DG units of the power supply cluster participating in the grid peak shaving may be subjected to peak shaving priority ranking in step S13. The steps of peak shaver prioritization are described in detail below.
In some embodiments of the present application, peak shaving priority ranking is performed by a TOPSIS ranking method, which is to construct a positive ideal solution and a negative ideal solution according to each input index of an evaluation object, calculate euclidean distances between each evaluation object and the positive ideal solution and the negative ideal solution, respectively, and finally evaluate and rank the evaluation objects according to closeness to the positive ideal solution. As a common multi-attribute decision making method and a sequencing method, the TOPSIS method has the advantages of not only having intuitive geometric significance, but also fully utilizing data. Specifically, the peak shaver prioritization comprises the following steps:
firstly, normalizing A to obtain a normalized evaluation matrix B = (B) ij ) M×4, wherein
Figure BDA0003754079040000104
Specifically, in the embodiment of the present application, all of the 4 peak shaving performance indexes are maximum-type indexes.
Secondly, calculating a weighted evaluation matrix R,
Figure BDA0003754079040000111
thirdly, calculating the positive ideal solution R of the power supply cluster + And negative ideal solution R - ，
Figure BDA0003754079040000112
wherein ,rj + ＝max[r 1j ，r 2j ，...r Mj ]，r j - ＝min[r 1j ，r 2j ，...r Mj ]；
Fourthly, calculating the closeness indexes of M DG units
Figure BDA0003754079040000117
Figure BDA0003754079040000113
wherein ,
Figure BDA0003754079040000114
the fifth step is based on
Figure BDA0003754079040000118
i =1 \ 8230and M sorts the peak shaving priority of M DG units.
In this embodiment, as shown in fig. 1, when each peak shaving period starts, the above sorting operation is performed on each power source cluster, and then each DG unit participating in the power grid peak shaving is controlled to perform the power grid peak shaving in the peak shaving period based on the above sorting result.
Step S3 will be described in detail below.
In some embodiments of the present application, step S3 further comprises performing the following steps for each power cluster:
s31: calculating the compliance gamma of M DG units participating in power grid peak shaving in the power supply cluster i ，
Figure BDA0003754079040000115
Wherein L is the number of peak regulation periods contained in the evaluation period, and gamma 1，i，l 、γ 2，i，l 、γ 3，i，l Respectively is the performance evaluation index gamma of the ith DG unit participating in the peak shaving of the power grid in the l peak shaving period of the evaluation period 1 、γ 2 、γ 3 The calculated value of (a);
s32: calculating the degree M of the practice of M DG units participating in power grid peak shaving in the power supply cluster i ，
Figure BDA0003754079040000116
wherein γ4，i，l The performance evaluation index gamma of the ith DG unit participating in power grid peak shaving in the l peak shaving period of the evaluation period 4 The calculated value of (a);
s33: evaluating M DG units participating in power grid peak regulation in the power source cluster according to the compliance and the convention degree;
s34: updating the peak shaver forbidden list, including i And M i Any DG unit which does not meet the corresponding qualified standard is placed into a peak regulation forbidding list, and the DG unit which meets the shifting-out condition in the peak regulation forbidding list is shifted out of the peak regulation forbidding list;
s35: and determining DG units participating in power grid peak shaving in the next evaluation period according to the evaluation result and the updated forbidden peak shaving list.
In the embodiment of the application, one evaluation period comprises a plurality of peak shaving periods, and at the end of each evaluation period, the performance of DG units participating in grid peak shaving in each power supply cluster in the evaluation period is evaluated by calculating the compliance and the practice degree of the DG units according to the peak shaving performance index values of the plurality of peak shaving periods in the evaluation period.
After the above-mentioned compliance degree and convention degree are obtained, the DG units that do not meet the compliance standard are further shifted into the peak regulation prohibition list, and the DG units that have met the shift-out condition are shifted out of the peak regulation prohibition list (specifically, the shift-out condition may be that a prohibition period set when the DG units are shifted into the peak regulation prohibition list expires), thereby implementing the update of the peak regulation prohibition list. Furthermore, the DG unit that moves out of the forbidden list may be given the average evaluation result of other DG units of the power cluster where it is located, so that it participates in the power grid peak shaving and peak shaving priority ranking again.
And finally, determining a DG unit participating in power grid peak shaving in the next evaluation period according to the evaluation result and the updated peak shaving prohibition list.
In some preferred embodiments of the present application, step S3 further comprises the steps of:
counting integrity N of all DG units in the power supply cluster g And shifting the DG unit with integrity level 0 out of the circuitA source cluster of
Figure BDA0003754079040000121
G is the number of DG units in the power cluster.
Through the steps, the DG units with bad records of multiple power grid peak shaving in one power supply cluster can be removed from the power supply cluster, the power supply cluster is regarded as an uncontrollable DG unit, and the power supply cluster completely loses the qualification of participating in power grid peak shaving.
Fig. 2 is a flowchart illustrating the evaluation of peak shaving performance of DG units according to an embodiment of the present application.
Example 1
The present embodiment is used for performing peak shaving dynamic control on three distributed power supply clusters, and the control method used is described in detail above.
Specifically, the number of DG units and the total adjustable power included in the three power clusters in this embodiment are listed in table 1:
table 1 example 1 power clustering situation
Figure BDA0003754079040000122
In this embodiment, taking 1 peak regulation period every 15 minutes, table 2 shows the peak regulation tasks of each power supply cluster in 51 th, 52 th, 53 th and 54 th peak regulation periods:
TABLE 2 distributed Power Cluster Peak shaving tasks
Figure BDA0003754079040000131
Fig. 3 to 5 respectively show the weighting of the peak shaving performance indexes of the three power supply clusters in the peak shaving period.
Table 3 shows the sequencing results of the DG units participating in the grid peak shaving in the power cluster 1 in the above-mentioned peak shaving cycles:
TABLE 3 comparison of the control sequences of the individual DG units of Cluster 1
Figure BDA0003754079040000132
And according to the sequencing result, each power supply cluster sequentially calls each DG unit to carry out power grid peak regulation in each peak regulation period according to the peak regulation task received by each power supply cluster.
Fig. 6 (a) to 6 (c) respectively show the overall peak shaving accuracy obtained by the three power supply clusters according to different weighting conditions in the peak shaving period.
Fig. 7 (a) to 7 (c) respectively show the overall response rates of the three power clusters in the peak shaving period according to different empowerment conditions.
Fig. 8 (a) to 8 (c) respectively show the overall regulation rates obtained by the three power supply clusters according to different weighting conditions during the peak shaving period.
In this embodiment, each 1 hour is taken as an evaluation period, that is, one evaluation period includes 4 peak shaving periods, and each DG unit participating in grid peak shaving in three power clusters is evaluated at the end of each evaluation period. Fig. 9 (a) to 9 (c) show the compliance and the compliance of the individual DG units participating in peak shaving at the end of the 13 th evaluation cycle (including 49 th, 50 th, 51 th, 52 th peak shaving cycles) for the three power clusters, respectively. Wherein the conformity and the trampling of both the degree of compliance and the degree of convention are set to 0.5.
As is clear from fig. 9 (a), since the DG unit numbered 17 in the power supply cluster 1 has a degree of accuracy of 0.47 and does not reach the set degree of accuracy of agreement, the peak regulation permission is temporarily canceled according to the evaluation result, the DG unit is moved to the peak regulation prohibited list, and the prohibited period is set to 2 evaluation periods, that is, 8 scheduling periods, and the DG unit is not allowed to participate in the peak regulation from the 53 th scheduling period to the 60 th scheduling period. Meanwhile, the DG units that have satisfied the shift-out condition need to be shifted out of the peak shaver prohibiting list, so as to update the peak shaver prohibiting list. And finally, determining a DG unit participating in power grid peak shaving in the next evaluation period according to the updated forbidden peak shaving list.
After the DG units participating in the power peak shaving are changed, the total adjustable power of the power cluster needs to be updated again, and the peak shaving task allocation needs to be performed again. In this embodiment, since the adjustable power of the 17 th DG unit removed from the power cluster 1 is 0.84, the total adjustable power of the power cluster 1 is changed from 24.86MW to 24.02MW, and the task allocation among the clusters is performed again, and the distribution comparison condition is shown in table 4:
TABLE 4 Peak shaving task assignment comparison
Figure BDA0003754079040000141
According to the task redistribution condition in table 4, each power supply cluster performs peak shaving according to the designated peak shaving task, and the total peak shaving precision is as shown in fig. 10 below. Further, if the number of times that a DG unit moves into the peak regulation forbidden list exceeds the upper limit of times, the DG unit is regarded as an uncontrollable DG unit, the DG unit is removed from the power cluster where the DG unit is located, and the DG unit completely loses the qualification of participating in power grid peak regulation.
As can be seen from fig. 10, a dynamic evaluation and self-updating mechanism is established in step S3, and through the three-dimensional evaluation and self-updating mechanism of compliance, convention degree and integrity degree, the elimination and control of DG units in a power supply cluster can be realized, so that the reasonable distribution of peak regulation tasks among clusters is further perfected, and the efficient and accurate completion of the total peak regulation task of the power grid is facilitated.
While the present invention has been described in detail and with reference to specific embodiments thereof, it will be apparent to one skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope thereof as defined in the appended claims.

Claims (8)

1. A peak regulation dynamic control method for a distributed power supply is characterized by comprising the following steps:
s1: determination of peak shaving performance index gamma j ,j＝1…4；
S2: at each peak regulationPeriod based on said γ j Sequencing the peak shaving priority of DG units participating in power grid peak shaving in each power supply cluster, and controlling each power supply cluster to carry out power grid peak shaving in the peak shaving period according to the sequencing result;
s3: at each evaluation period, based on the gamma j Evaluating peak shaving performances of DG units participating in power grid peak shaving in each power supply cluster, updating a peak shaving forbidding list according to evaluation results, and determining the DG units participating in power grid peak shaving in the next evaluation period, wherein each evaluation period comprises at least one peak shaving period.
2. The distributed power peak shaving dynamic control method according to claim 2, wherein the gamma is j The method specifically comprises the following steps:
Figure FDA0003754079030000011
wherein ,vreal 、v stand 、Δt real 、Δt stand 、Δp max 、Δp real 、Δp target The actual power change rate, the standard power change rate, the actual response time, the standard response time, the maximum adjustable power, the actual peak-shaving output force and the target peak-shaving output force of the DG unit are respectively delta P max The maximum adjustable power of the power cluster in which the DG unit is located.
3. The distributed power supply peak shaving dynamic control method according to claim 2, wherein in step S2, the peak shaving priorities of the DG units in each power supply cluster participating in the grid peak shaving are sorted, specifically, the following steps are performed for each power supply cluster:
s11: obtaining an evaluation matrix A of DG units participating in power grid peak shaving in the power supply cluster,
Figure FDA0003754079030000012
wherein M is the number of DG units participating in power grid peak shaving in the power supply cluster, a ij The jth peak shaving performance index gamma of the ith DG unit participating in the peak shaving of the power grid j The calculated value of (a);
s12: determining a combining weight w of a peak shaver performance index of the power cluster based on the following formula j ，
w j ＝s 1 w 1j +s 2 w 2j ,j＝1…4，
wherein ,w1j 、w 2j Are respectively gamma j Corresponding objective and subjective weights, s 1 、s 2 Are respectively w 1j 、w 2j The weight coefficient of (a);
s13: based on the A and w j And carrying out peak shaving priority sequencing on the M DG units participating in the power grid peak shaving of the power supply cluster.
4. The distributed power peak shaving dynamic control method according to claim 3, wherein the objective weight w 1j Is determined by the following steps:
firstly, standardizing the evaluation matrix A to obtain a standardized evaluation matrix
Figure FDA0003754079030000021
wherein
Figure FDA0003754079030000022
Is a pair of ij Values after normalization processing;
second, obtaining A * Probability matrix P = (P) ij ) M×4, wherein
Figure FDA0003754079030000023
Third, calculating gamma j Information entropy e of j ，
Figure FDA0003754079030000024
The fourth step, calculate gamma j Information utility value of G j ，
G j ＝1-e j ,j＝1...4；
The fifth step, calculate gamma j Objective weight w of 1j ，
Figure FDA0003754079030000025
5. The distributed power peak shaving dynamic control method according to claim 3, wherein the subjective weight w 2j Is determined by the following steps:
firstly, constructing a judgment matrix Y of peak regulation performance indexes based on an analytic hierarchy process,
Figure FDA0003754079030000026
wherein any element y kj Represents gamma k And gamma j Carrying out comparison to determine importance quantitative scale;
secondly, calculating a consistency index CI of Y,
Figure FDA0003754079030000027
wherein ,λmax The largest characteristic root of Y;
thirdly, carrying out consistency check on Y based on the following formula,
Figure FDA0003754079030000028
wherein, RI is an average random consistency index, if Y passes consistency check, the next step is executed, otherwise, the first step is returned to reconstruct Y;
the fourth step of calculating gamma j Subjective weight w of 2j ，
Figure FDA0003754079030000031
wherein ,α1j 、α 2j 、α 3j The arithmetic mean weight, the geometric mean weight, and the eigenvalue weight of Y, respectively.
6. The distributed power peak shaving dynamic control method according to claim 3, wherein the step S13 further comprises the steps of:
firstly, normalizing A to obtain a normalized evaluation matrix B = (B) ij ) M×4, wherein
Figure FDA0003754079030000032
Secondly, calculating a weighted evaluation matrix R,
Figure FDA0003754079030000033
thirdly, calculating the positive ideal solution R of the power supply cluster + And negative ideal solution R - ，
Figure FDA0003754079030000034
wherein ,
Figure FDA0003754079030000035
fourthly, calculating the closeness indexes of the M DG units
Figure FDA0003754079030000036
Figure FDA0003754079030000037
wherein ,
Figure FDA0003754079030000038
the fifth step is based on
Figure FDA0003754079030000039
i =1 \ 8230, and M sorts the peak shaving priority of M DG units.
7. The distributed power peak shaving dynamic control method according to claim 2, wherein the step S3 further comprises performing the following steps for each power cluster:
s31: calculating the compliance gamma of M DG units participating in power grid peak regulation in the power cluster i ，
Figure FDA00037540790300000310
Wherein L is the number of peak regulation periods contained in the evaluation period, gamma 1,i,l 、γ 2,i,l 、γ 3,i,l Respectively is the performance evaluation index gamma of the ith DG unit participating in the peak shaving of the power grid in the l peak shaving period of the evaluation period 1 、γ 2 、γ 3 The calculated value of (a);
s32: calculating the degree M of the practice of M DG units participating in power grid peak regulation in the power cluster i ，
Figure FDA0003754079030000041
wherein γ4,i,l The performance evaluation index gamma of the ith DG unit participating in power grid peak shaving in the l peak shaving period of the evaluation period 4 The calculated value of (a);
s33: evaluating M DG units participating in power grid peak shaving in the power supply cluster according to the compliance and the convention;
s34: updating the forbidden peak list, including i And M i Any DG unit which does not meet the corresponding qualified standard is placed in a peak regulation forbidden list, and the DG unit which meets the shifting-out condition in the peak regulation forbidden list is shifted out of the peak regulation forbidden list;
s35: and determining DG units participating in power grid peak shaving in the next evaluation period according to the evaluation result and the updated peak shaving prohibition list.
8. The distributed power peak shaving dynamic control method according to claim 7, wherein the step S3 further comprises the steps of:
counting integrity N of all DG units in the power supply cluster g And shifting out DG units with integrity of 0 from the power cluster, wherein
Figure FDA0003754079030000042
G is the number of DG units in the power cluster.
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