CN116505518A - Power grid fault control method, device and storage medium - Google Patents
Power grid fault control method, device and storage medium Download PDFInfo
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Abstract
The invention discloses a power grid fault control method, a device and a storage medium. Wherein the method comprises the following steps: obtaining a plurality of fault scenes according to the operation mode of the target power grid and preset faults; respectively carrying out risk assessment on the multiple fault scenes to obtain a system risk value of the target power grid under the multiple fault scenes; under the condition that the system risk value is larger than a preset risk threshold value, determining multiple types of candidate control measures corresponding to multiple fault scenes, wherein the multiple types of candidate control measures respectively comprise at least one candidate control measure; determining a plurality of control measure combinations based on control measure performance indexes respectively corresponding to the plurality of types of candidate control measures; and obtaining a target control measure based on the plurality of control measure combinations, wherein the target control measure is a group of control measures with the minimum control cost in the plurality of control measure combinations. The invention solves the technical problems of low accuracy and high control cost of power grid fault control of the power grid auxiliary decision-making system in the related technology.
Description
Technical Field
The invention relates to the field of intelligent power grid control, in particular to a power grid fault control method, a power grid fault control device and a storage medium.
Background
The dynamic behavior and the instability mode characteristics of the interconnected large-scale urban power grid are increasingly complex, various safety risk problems are interwoven, and various potential safety hazards can occur simultaneously. On the one hand, various auxiliary decisions for solving different security risk problems consider the same power system, which is generally implemented by an energy control center through a dispatch plan, and share one control channel. On the other hand, various auxiliary decision functions for solving different security risk problems may give contradictory measures or stable and effective adjustment measures for a certain class of security. In addition, the operation mode of the full-clean energy power grid and the uncertainty of occurrence of serious faults are increased, the risks of mismatching of an offline emergency control strategy and expansion of accidents exist under the serious faults, and the safe operation of the power grid cannot be ensured by means of the actions of the protection device and the self-installation device alone. The problems that the consideration of the power grid fault control factors is incomplete exist in the scheme, adverse effects on safety and stability of other types can be possibly caused, and the power grid fault control accuracy is low and the operation risk is high.
In view of the above problems, no effective solution has been proposed at present.
Disclosure of Invention
The embodiment of the invention provides a power grid fault control method, a device and a storage medium, which are used for at least solving the technical problems of low power grid fault control accuracy and high control cost of a power grid auxiliary decision-making system in the related technology.
According to an aspect of the embodiment of the present invention, there is provided a power grid fault control method, including: obtaining a plurality of fault scenes according to the operation mode of the target power grid and preset faults; respectively carrying out risk assessment on the multiple fault scenes to obtain a system risk value of the target power grid under the multiple fault scenes; under the condition that the system risk value is larger than a preset risk threshold value, determining multiple types of candidate control measures corresponding to the multiple fault scenes, wherein the multiple types of candidate control measures respectively comprise at least one candidate control measure; determining a plurality of control measure combinations based on control measure performance indexes respectively corresponding to the plurality of types of candidate control measures; and obtaining a target control measure based on the plurality of control measure combinations, wherein the target control measure is a group of control measures with the minimum control cost in the plurality of control measure combinations.
According to another aspect of the embodiment of the present invention, there is also provided a power grid fault control device, including: the first acquisition module is used for obtaining a plurality of fault scenes according to the operation mode of the target power grid and preset faults; the second acquisition module is used for respectively carrying out risk assessment on the plurality of fault scenes to obtain a system risk value of the target power grid under the plurality of fault scenes; the first determining module is used for determining multiple types of candidate control measures corresponding to the multiple fault scenes under the condition that the system risk value is greater than a preset risk threshold, wherein the multiple types of candidate control measures respectively comprise at least one candidate control measure; the second determining module is used for determining a plurality of control measure combinations based on control measure performance indexes respectively corresponding to the plurality of types of candidate control measures; and the third acquisition module is used for obtaining a target control measure based on the plurality of control measure combinations, wherein the target control measure is a group of control measures with the minimum control cost in the plurality of control measure combinations.
According to another aspect of the embodiments of the present invention, there is also provided a non-volatile storage medium storing a plurality of instructions adapted to be loaded by a processor and to perform any one of the above-described grid fault control methods.
In the embodiment of the invention, a plurality of fault scenes are obtained according to the operation mode of the target power grid and preset faults; respectively carrying out risk assessment on the multiple fault scenes to obtain a system risk value of the target power grid under the multiple fault scenes; under the condition that the system risk value is larger than a preset risk threshold value, determining multiple types of candidate control measures corresponding to the multiple fault scenes, wherein the multiple types of candidate control measures respectively comprise at least one candidate control measure; determining a plurality of control measure combinations based on control measure performance indexes respectively corresponding to the plurality of types of candidate control measures; based on the combination of the plurality of control measures, the target control measure is obtained, wherein the target control measure is a group of control measures with the minimum control cost in the combination of the plurality of control measures, and the aim of determining a control strategy which is applicable to various power grid fault scenes and has the minimum control cost is fulfilled, so that the technical effects of improving the accuracy of power grid fault control and reducing the cost of fault control are realized, and the technical problems of low accuracy of power grid fault control and high control cost in a power grid auxiliary decision-making system in the related art are solved.
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The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the drawings:
FIG. 1 is a schematic diagram of a grid fault control method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an alternative grid fault control method according to an embodiment of the present invention;
FIG. 3 is a flow chart illustrating an alternative grid fault control method implementation in accordance with an embodiment of the present invention;
fig. 4 is a schematic diagram of a grid fault control device according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
At present, the extra-high voltage alternating current/direct current power grid bears the heavy duty of large-scale long-distance transmission of clean energy, and has huge transmission capacity and remarkable economic and social benefits. However, even if a disaster event occurs with small probability, once the extra-high voltage alternating current/direct current transmission system is stopped due to the disaster, the load and the power output loss caused by the safety and stability problem or the prevention and control measures of the power transmission and receiving end power grid become a large probability event, and serious accidents of large-area power failure are possibly caused. Therefore, it is highly necessary to effectively and efficiently evaluate the impact of catastrophe on the running risk of a full clean energy grid in order to guide the taking of corresponding prevention and control measures from the point of view of grid planning, grid infrastructure, grid operation and dispatch operation for effective evasion and countermeasures.
The dynamic behavior and the instability mode characteristics of the interconnected large-scale urban power grid are increasingly complex, various safety risk problems are interwoven, and various potential safety hazards can occur simultaneously. On the one hand, various auxiliary decisions for solving different security risk problems consider the same power system, which is generally implemented by an energy control center through a dispatch plan, and share one control channel. On the other hand, various auxiliary decision functions for solving different security risk problems may give contradictory measures or stable and effective adjustment measures for a certain class of security. In addition, the operation mode of the full-clean energy power grid and the uncertainty of occurrence of serious faults are increased, the risks of mismatching of an offline emergency control strategy and expansion of accidents exist under the serious faults, and the safe operation of the power grid cannot be ensured by means of the actions of the protection device and the self-installation device alone. The problems that the consideration of the power grid fault control factors is incomplete exist in the scheme, adverse effects on safety and stability of other types can be possibly caused, and the power grid fault control accuracy is low and the operation risk is high. Thus, there is a need to consider coordinated optimization between a variety of security risk issues in the auxiliary decision calculation. And finally obtaining a unified auxiliary decision control strategy by summarizing and evaluating various security risk auxiliary decision information.
According to an embodiment of the present invention, there is provided a method embodiment of grid fault control, it being noted that the steps shown in the flowchart of the figures may be performed in a computer system, such as a set of computer executable instructions, and that, although a logical sequence is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than what is shown herein.
Fig. 1 is a flowchart of a power grid fault control method according to an embodiment of the present invention, as shown in fig. 1, the method includes the steps of:
step S102, obtaining a plurality of fault scenes according to the operation mode of the target power grid and preset faults.
Optionally, the preset faults are various, and may include, but not limited to, three-phase short circuit faults, inter-phase short circuit faults, single-phase grounding faults, direct current blocking faults, new energy off-grid faults, and the like. The operation modes are various, and can include, but are not limited to, maintenance operation modes, maximum and minimum load and startup modes, summer operation modes, winter operation modes, annual operation modes and the like. Through the mode, a plurality of preset faults are combined with the operation modes of the power grid, and a plurality of different fault scenes of the target power grid under different operation modes are obtained.
Step S104, performing risk assessment on the multiple fault scenes to obtain a system risk value of the target power grid under the multiple fault scenes.
Optionally, the system risk value is used for indicating the operation condition of the target power grid, and for an operation scene that the system risk value of the target power grid is larger and larger than a preset risk threshold value, corresponding control measures need to be formulated to better cope with faults occurring in the operation process of the power grid, so that the operation risk of the power grid faults is reduced.
In an optional embodiment, the performing risk assessment on the multiple fault scenarios to obtain a system risk value of the target power grid under the multiple fault scenarios includes: acquiring at least one safety and stability problem corresponding to the multiple fault scenes respectively and a safety and stability margin corresponding to the at least one safety and stability problem respectively; determining fault consequences corresponding to the multiple fault scenes respectively based on at least one safety stability problem corresponding to the multiple fault scenes respectively and a safety stability margin corresponding to the at least one safety stability problem respectively; acquiring fault occurrence probabilities respectively corresponding to the multiple fault scenes; and obtaining the system risk value based on the fault result and the fault occurrence probability which are respectively corresponding to the plurality of fault scenes.
Alternatively, the safety margin range may be, but is not limited to, [ -100, +100], and the calculation formula of the level segmentation conversion result according to the safety margin is as follows:
wherein eta is a safety and stability evaluation margin of the percentile; alpha 1 、α 2 、……、α 6 Is a piecewise conversion coefficient, and alpha 1 ＜α 2 ＜α 3 ＜α 4 ＜α 5 ＜α 6 ＜0。
Optionally, the segmentation conversion results calculated according to various safety stability margins are weighted to obtain the fault results corresponding to the fault scene, and the specific formula is as follows:
wherein M is the number of types of safety and stability problems to be considered; lambda (lambda) m A weighting coefficient for the m-th class safety and stability problem;the segmentation reduction results are calculated according to the margin of the m-th type safety and stability problem.
Wherein R is a system risk value; ρ i For the probability of the occurrence of scene i,ψ i as a fault result of the fault scenario i, S T Is a fault scene set composed of the plurality of fault scenes.
Through the mode, when the risk value of the target power grid operation system is determined, various safety and stability problems corresponding to various fault scenes and corresponding safety and stability margins in the operation process of the target power grid are considered, and the fault result of the fault scenes is determined on the basis. And because of the different occurrence probabilities of the fault scenes, the occurrence probabilities of the fault scenes are considered when the system risk value is calculated, and the fault results of the fault scenes are weighted and summed according to the occurrence probabilities of the fault scenes, so that the system risk value of the target power grid is more accurate and reliable.
Step S106, under the condition that the system risk value is larger than a preset risk threshold, determining multiple types of candidate control measures corresponding to the multiple fault scenes, wherein the multiple types of candidate control measures respectively comprise at least one candidate control measure.
Alternatively, the multiple types of candidate control measures may include, but are not limited to, generator active regulation control measures, load regulation control measures, direct current regulation control measures, generator reactive regulation control measures, preventive control measures of capacitor or reactor switching, and the like.
By the method, when candidate control measures are determined, various types of control measures such as generator active adjustment, generator reactive adjustment, load adjustment, capacitor/reactor switching, starting, line switching and direct current adjustment are considered, so that the control measures which can adapt to various different fault scenes are obtained, the power grid can better cope with various possible running faults, and the running stability and reliability of the target power grid are enhanced.
Optionally, the priorities of the different types of control measures are different when they are executed, so that the auxiliary decision should support step-by-step decision optimization according to the priority order of the different types of control measures. And when the same type of effective control measures are all adjusted, switching to the control measure for adjusting the next priority. The priority control sequence of the multiple types of control measures is realized by setting corresponding adjustment costs for the different types of control measures. In general, the active power of the conventional unit is preferably adjusted in consideration of the maximum requirement of the new energy consumption, wherein the conventional unit can include, but is not limited to, a gas unit, a thermal power unit, a hydroelectric unit and the like. The hydroelectric generating set is preferably regulated due to low cost and high regulating speed, and pumped storage is as little as possible. The load control adopts a pull-up sequence list, a transfer measure is adopted preferentially, and then the adjustment quantity is issued to the regional dispatching center according to the sequence list. And firstly, adjusting the switching of the capacitive reactance device when the voltage is out of limit, and considering the adjustment of reactive power of the unit when the overvoltage is serious. The measures of generator start-stop and transformer tap adjustment are less adopted.
Step S108, based on the control measure performance indexes respectively corresponding to the multiple types of candidate control measures, determining multiple control measure combinations.
Optionally, the control measure performance index may include, but is not limited to: the performance indexes of the active power adjustment control measures, the load adjustment control measures, the direct current adjustment control measures, the reactive power adjustment control measures and the prevention control measures of the switching of the capacitor or the reactor of the generator.
In an alternative embodiment, the determining a plurality of control measure combinations based on the control measure performance indexes respectively corresponding to the plurality of candidate control measures includes: under the condition that the system risk value is determined to be greater than a preset risk threshold, determining a control measure sequence table corresponding to each of the multiple types of candidate control measures based on the control measure performance indexes corresponding to each of the multiple types of candidate control measures, wherein the at least one candidate control measure included in the control measure sequence table is arranged according to the sequence from the large control measure performance index score to the small control measure performance index score; and determining the combination of the plurality of control measures according to the control measure sequence list corresponding to the plurality of candidate control measures.
Optionally, if the risk value of the target power grid system is greater than the preset risk threshold, the fault risk of the target power grid is indicated. At the moment, comprehensive risk control performance indexes (i.e. control measure performance indexes) of various candidate control measures for various high-risk safety and stability problems in various risk scenes are calculated, various candidate control measures are respectively ordered according to the comprehensive risk control performance indexes to form an effective control measure sequence table, and the combination of target power grid control measures is determined on the basis of the effective control measure sequence table.
In an optional embodiment, the determining the control measure sequence table corresponding to each of the multiple types of candidate control measures based on the control measure performance indexes corresponding to each of the multiple types of candidate control measures includes: based on the performance index of the control measure corresponding to any type of candidate control measure in the multiple types of candidate control measures, the control measure sequence list corresponding to any type of candidate control measure is determined in the following manner: determining a control measure performance index score of the at least one candidate control measure included in the any one type of candidate control measure; determining a first candidate control measure with the control measure performance index score being greater than or equal to 0 in the at least one candidate control measure; and sorting the first candidate control measures according to the control measure performance index scores to obtain the control measure sequence list corresponding to any type of candidate control measures.
In an optional embodiment, the sorting the first candidate control according to the control measure performance index score to obtain the control measure sequence table corresponding to the candidate control measure of any type includes: determining a second candidate control measure with the highest control measure performance index score and other candidate control measures except the second candidate control measure in the plurality of first candidate control measures when the plurality of first candidate control measures are provided; calculating a ratio between the other candidate control measure and the second candidate control measure; determining a third candidate control measure with the ratio larger than a preset threshold value in the plurality of first candidate control strategies; and sorting the third candidate control according to the performance index scores of the control measures to obtain a control measure sequence list corresponding to any type of candidate control measure.
Optionally, in the case that the control measure performance index is the generator active adjustment control measure performance index, filtering the generator active adjustment control measure performance index I from the optional generator active increase or decrease preventive control measure gpk An optional control measure less than or equal to 0 and according to I gpk Sequencing the rest optional control measures from the big order to the small order to obtain the generatorActive adjustment measure position table GS 1 If GS 1 Non-empty, then from GS 1 Well knockout I gpk /I gp.max An optional control measure smaller than the set value, wherein I gp.max For GS 1 All optional control measures I gpk Is the maximum value of (a).
Optionally, in the case that the control measure performance index is a load adjustment control measure performance index, filtering the load adjustment control measure performance index from the optional load increase or decrease preventive control measure to drop I lk An optional control measure less than or equal to 0 and according to I lk The rest optional control measures are ordered from big to small to obtain a load adjustment measure order table LS 1 If LS 1 Non-empty, then from LS 1 Well knockout I lk /I l.max An optional control measure smaller than the set value, wherein I l.max Is LS 1 All optional control measures I lk Is the maximum value of (a).
Optionally, in the case that the control measure performance index is a dc adjustment control measure performance index, filtering the dc adjustment control measure performance index I from the optional dc adjustment preventive control measure dck An optional control measure less than or equal to 0 and according to I dck The rest optional control measures are sequenced from the big order to the small order to obtain a DC adjustment measure sequence table DCS 1 If DCS 1 Non-empty, then from DCS 1 Well knockout I dck /I dc.max An optional control measure smaller than the set value, wherein I dc.max Is DCS 1 All optional control measures I dck Is the maximum value of (a).
Optionally, in the case that the performance index of the control measure is the performance index of the reactive power adjustment control measure of the generator, the performance index I of the reactive power adjustment control measure of the generator is filtered out from the preventive control measure of the increase or decrease of the reactive power output of the generator gqk Optional control measure of 0 or less, filtering out the performance index I of the preventive control measure of the capacitor or the reactor switching from the preventive control measure of the optional capacitor/reactor switching xk Not more than 0Selecting control measures, uniformly sequencing the rest preventive control measures for increasing or decreasing reactive power output of the optional generator and the preventive control measures for switching of the optional capacitor/reactor according to the sequence from the large to the small of the comprehensive risk performance indexes to obtain a reactive power regulation measure sequence table QS 1 If QS is 1 Non-empty, then the QS is again 1 Well knockout I gqk /I gq.x.max Or I xk /I gq.x.max An optional control measure smaller than the set value, wherein I gq.x.max Is QS 1 All optional control measures I gqk And I xk Is the maximum value of (a).
In an alternative embodiment, the determining a plurality of control measure combinations according to the control measure sequence table corresponding to each of the plurality of candidate control measures includes: determining an adjusting space of at least one candidate control measure corresponding to each of the multiple types of candidate control measures based on the preset index adjusting precision corresponding to each of the multiple types of candidate control measures; determining the splitting number corresponding to the at least one candidate control measure respectively corresponding to the multiple types of candidate control measures based on the adjusting space; based on the splitting quantity, obtaining a new control measure sequence table corresponding to each of the multiple types of candidate control measures, wherein the control measure performance index scores between the split control measures corresponding to one candidate control measure in the new control measure sequence table are in an arithmetic sequence; according to the candidate control measures included in the new control measure sequence list corresponding to the multiple types of candidate control measures respectively, arranging and combining to obtain a combined sequence list, wherein the control strategy combinations included in the combined sequence list are arranged according to the order of the control cost from small to large; and combining the control strategies arranged in a preset number in the combined sequence table as a plurality of control measure combinations.
Optionally, the control measure performance indexes corresponding to the multiple types of candidate control measures respectively include: under the conditions of the performance indexes of the active adjustment control measures of the generator, the performance indexes of the load adjustment control measures, the performance indexes of the direct current adjustment control measures, the performance indexes of the reactive adjustment control measures of the generator and the performance indexes of the preventive control measures of the switching of the capacitor or the reactor, the control measure sequence list is updated according to the set precision split control measures to obtain a new control measure sequence list, and enumeration combination is carried out aiming at candidate control measures included in the new control measure sequence list to obtain a combined sequence list.
Optionally, for the generator active adjustment control measure, according to the set generator active adjustment precision epsilon g.p Respectively aiming at the measure sequence table GS 1 Active power adjustment measures of each generator, meter and adjustable space delta P thereof g Dividing it into 1 or more adjusting measures which are ordered from small to large according to the adjustment amount and uniformly changed, and according to the adjustment amount in GS 1 Sequentially adding the decomposed adjustment measure sequences into a new generator active adjustment measure sequence table GS' 1 Is a kind of medium.
Optionally, for the load adjustment control measure, the accuracy ε is adjusted according to the set load l Respectively for LS 1 Each load adjustment measure of (1) meter and its adjustable space delta P l Dividing it into 1 or more adjusting measures which are ordered from small to large according to the adjustment amount and uniformly changed, and according to the adjustment amount in LS 1 Sequentially adding the decomposed adjustment measure sequences into a new load adjustment measure sequence table LS' 1 Is a kind of medium.
Optionally, for the dc adjustment control measure, the accuracy epsilon is adjusted according to the set dc power dc Respectively for DCS 1 Each direct current adjustment measure in (1) meter and adjustable space delta P thereof g Dividing it into 1 or more adjusting measures which are ordered from small to large according to the adjustment amount and uniformly changed, and according to the adjusting measures in DCS 1 Sequentially adding the decomposed adjustment measure sequences into a new DC adjustment measure sequence table DCS 1 'in'.
Optionally, for reactive power adjustment control measures of the generator, the reactive power adjustment precision epsilon of the generator is set according to the setting g.q Respectively for QS 1 Reactive power regulation measure of each generator, meter and adjustable space delta Q thereof g Decomposing it into 1 or more pieces which are ordered from small to large according to adjustment amount and uniformly changedRespectively for QS 1 Each capacitor/reactor switching measure is decomposed into 1 or more reactive power adjustment quantity difference absolute value and epsilon which are sequentially increased according to the number of capacitor/reactor switching groups and adjacent two adjustment measures according to reactive power adjustment direction g.q The minimum absolute value of the difference between the two is adjusted in QS according to the reactive power adjustment of the generator and the switching of the capacitor/reactor 1 Sequentially adding the adjustment measure sequences obtained after decomposition into a new reactive adjustment measure sequence table QS' 1 Is a kind of medium.
Alternatively, for ranking in GS 1 The first generator active power regulation measures convert it into [ int (|Δp) g |/ε g.p +0.5)+1]The adjustment amounts are in an arithmetic progression such that the adjustment amount of the 1 st adjustment is 0 and the adjustment amount of the 2 nd adjustment is DeltaP g /int(|ΔP g |/ε g.p +0.5), and so on; for the remaining generator active power regulation measures, they are each converted into int (|Δp) g |/ε g.p +0.5) adjustment measures whose adjustment amounts are in an arithmetic progression such that the adjustment amount of the 1 st adjustment measure is Δp g /int(|ΔP g |/ε g.p +0.5), the adjustment amount of the 2 nd adjustment measure is 2ΔP g /int(|ΔP g |/ε g.p +0.5), and so on; for ordering at LS 1 The first load regulation measure in the middle converts it into [ int (|Δp) l |/ε l +0.5)+1]The adjustment amounts are in an arithmetic progression such that the adjustment amount of the 1 st adjustment is 0 and the adjustment amount of the 2 nd adjustment is DeltaP l /int(|ΔP l |/ε l +0.5), and so on; for the remaining load regulation measures, they are each converted into int (|Δp) l |/ε l +0.5) adjustment measures whose adjustment amounts are in an arithmetic progression such that the adjustment amount of the 1 st adjustment measure is Δp l /int(|ΔP l |/ε l +0.5), the adjustment amount of the 2 nd adjustment measure is 2ΔP l /int(|ΔP l |/ε l +0.5), and so on; for sequencing at DCS 1 Direct current regulation measures of the first middle position are used for converting the direct current regulation measures into the direct current regulation measuresChange to [ int (|Δp) g |/ε dc +0.5)+1]The adjustment amounts are in an arithmetic progression such that the adjustment amount of the 1 st adjustment is 0 and the adjustment amount of the 2 nd adjustment is DeltaP g /int(|ΔP g |/ε dc +0.5), and so on; for the remaining dc regulation measures, they are each converted into int (|Δp) g |/ε dc +0.5) adjustment measures whose adjustment amounts are in an arithmetic progression such that the adjustment amount of the 1 st adjustment measure is Δp g /int(|ΔP g |/ε dc +0.5), the adjustment amount of the 2 nd adjustment measure is 2ΔP g /int(|ΔP g |/ε dc +0.5), and so on; if ordered in QS 1 The first reactive power regulation is the generator reactive power regulation, which is then converted into [ int (|Δq) g |/ε g.q +0.5)+1]The adjustment amounts are equal-difference series adjustment measures, so that the adjustment amount of the 1 st adjustment measure is 0 and the adjustment amount of the 2 nd adjustment measure is DeltaQ g /int(|ΔQ g |/ε g.q +0.5), and so on; for the remaining reactive power regulation measures of the generator, they are each converted into int (|Δq) g |/ε g.q +0.5) adjustment measures whose adjustment amounts are in an arithmetic progression such that the adjustment amount of the 1 st adjustment measure is Δq g /int(|ΔQ g |/ε g.q +0.5), the adjustment amount of the 2 nd adjustment measure is 2ΔQ g /int(|ΔQ g |/ε g.q +0.5), and so on; for the rest capacitor/reactor switching measures, the adjustment quantity of the first adjustment measure is set as the capacitor or reactor of the corresponding group number, otherwise, the capacitor or reactor is arranged in QS sequence 1 The first capacitor/reactor switching measure is set to 0, the first regulating measure is set to the corresponding group number of capacitors or reactors for the rest of the capacitor/reactor switching measures, and the rest of the generator reactive power regulating measures are respectively converted into int (|DeltaQ) g |/ε g.q +0.5) adjustment measures whose adjustment amounts are in an arithmetic progression such that the adjustment amount of the 1 st adjustment measure is Δq g /int(|ΔQ g |/ε g.q +0.5), 2 nd adjustment measureThe adjustment amount is 2 delta Q g /int(|ΔQ g |/ε g.q +0.5), and so on.
In an alternative embodiment, the ranking and combining the candidate control measures included in the new control measure sequence table corresponding to each of the multiple types of candidate control measures to obtain a combined sequence table includes: according to the candidate control measures included in the new control measure sequence list respectively corresponding to the multiple types of candidate control measures, arranging and combining to obtain a first number of control measure combinations; determining the active injection total amount of the first number of control measure combinations to the target power grid respectively; determining whether the first number of control measure combinations meet a preset power condition according to the total active injection amount of the first number of control measure combinations to the target power grid; and based on the control measure combination meeting the preset power condition in the first number of control combinations, obtaining the combination sequence table.
Optionally, according to the set step length, on the premise of meeting the adjustment limit value of the candidate control measures, a control scheme is generated by enumerating the combination based on the new control measure sequence table, and a combination sequence table is obtained. The specific method comprises the following steps: from GS ', respectively' 1 、LS′ 1 、DCS′ 1 And QS' 1 The optional precaution control measure beginning sequence number ordered first in (n) is selected for enumerating the combination min (n gs ,n 1 ) Active power adjustment measure, min (n ls ,n 2 ) Individual load regulation measures, min (n) dcs ,n 3 ) The direct current regulation measures and min (n qs ,n 4 ) Reactive power adjustment measures are adopted, enumeration combination is carried out on the 4 measures, and min (n) gs ,n 1 )×min(n ls ,n 2 )×min(n dcs ,n 3 )×min(n qs ,n 4 ) A combination of control measures, wherein n gs 、n ls 、n dcs 、n qs GS ', respectively' 1 、LS′ 1 、DCS 1 'and QS' 1 The number of optional preventive control measures, n 1 、n 2 、n 3 、n 4 Respectively set forEnumeration combination of the maximum value of the number of active power adjustment measures, load adjustment measures, direct current adjustment measures and reactive power adjustment measures of the generator calculated by the risk control decision; then, for each control measure combination, calculating the active injection total quantity delta P of the control measure combination to the power grid in If [ f 0 +ΔP in f 0 /(KP sum.0 )]Greater than f ul Or less than f ll Wherein f 0 And P sum.0 Respectively, the sum of the frequency and the load active power of the power grid in the state after the adjustment measures are implemented, K is the power frequency static characteristic coefficient of the power grid, and the control measure combination is removed, f ul Scoring an upper limit value, f, of a frequency performance index in a state after a preset adjustment measure is implemented ll A lower limit value of a frequency performance index score in a state after a preset adjustment measure is implemented; finally, the rest control measure combinations are ordered according to the order of the control cost from small to large, and the control measure combination sequence table GLDCQS for risk assessment is obtained according to the order of the adjustment amount from small to large for the control measure combinations with the same control cost 1 。
Optionally, taking the risk scene set with the system risk value larger than the threshold value as a risk scene set F to be subjected to preventive control td (i.e., a set of target failure scenarios) based on GLDCQS 1 Top of the middle orderA plurality of control measure combinations are obtained, and each control measure combination in the plurality of control measure combinations is combined with F td Each fault scene in (1) is combined to generate common +.>Risk evaluation example of power grid after control measure combination implementation is considered, wherein N is as follows td For the upper limit of the risk evaluation example number submitted to the cluster computing platform for processing at one time, n gldcq Is GLDCQS 1 The number of measures, n ftd Is F td The number of the fault scenes in the system is combined in the GLDCQS according to control measures 1 In the order of (a)The generated examples are sequenced to form a scheduling queue, and the scheduling queue is submitted to a cluster system for parallel calculation of risk evaluation examples.
Step S110, obtaining a target control measure based on the plurality of control measure combinations, wherein the target control measure is a group of control measures with the minimum control cost in the plurality of control measure combinations.
In an alternative embodiment, the obtaining the target control measure based on the combination of the plurality of control measures includes: obtaining a target fault scene set based on the fault scenes with the system risk value larger than the preset risk threshold value in the multiple fault scenes; and carrying out iterative optimization calculation by taking the minimum system risk value, the minimum control cost and the maximum new energy consumption as objective functions according to the plurality of control measures and the objective fault scene set to obtain the objective control measures.
By the method, when the target power grid control strategy is determined, the target control measures are taken as targets of minimum system risk value, minimum control cost and maximum new energy consumption, and the obtained target control measures comprehensively consider the problems of system risk, control cost, new energy consumption and the like, so that the power grid operation, fault treatment and other works are more economical and reliable.
Optionally, the control cost minimum objective function is as follows:
Wherein Sc, com is a conventional deterministic control measure set composed of preset deterministic control measures included in one control measure combination of a plurality of control measure combinations; sc, new is an uncertainty control measure (the set comprises new energy unit control, load control and the like) composed of preset uncertainty control measures included in a control measure combination; ST is a high-risk scene set composed of high-risk scenes included in the plurality of failure scenes; c (C) pk The unit active force adjustment cost of the active control measure k in one control measure combination; c (C) qk The reactive power control method is characterized in that the reactive power control method is a unit reactive power output adjustment cost of reactive power control measure k in a control measure combination, and if the reactive power adjustment cost is ignored, the reactive power adjustment cost can be set to be 1; p (P) k An adjusted active force for active control measure k; q (Q) k Reactive output after adjustment for reactive control measure k;active force before adjustment for deterministic active control measure k; />Reactive power output before adjustment for deterministic reactive power control measure k; lambda (lambda) i For the probability of occurrence of the fault scenario i, +.>C pj The unit active force adjustment cost of the uncertainty active control measure j in one control measure combination; p (P) j An adjusted active force that is an uncertainty active control measure j; / >The active force is the active force before the adjustment of the uncertain active control measure j in the fault scene i.
Optionally, the system risk minimum objective function is as follows:
wherein R is a system risk value; ρ i For the probability of occurrence of the failure scenario i,ψ i is the consequence of the failure scenario i.
Optionally, the new energy consumption maximum objective function is as follows:
wherein P is j And the active power output of the new energy unit j in the target power grid is obtained.
Optionally, constraints involved in the iterative optimization calculation include, but are not limited to: load flow balance constraint, conventional unit climbing rate constraint, control measure output constraint and the like.
Optionally, the formula corresponding to the above-mentioned load flow balance constraint is expressed as follows:
in the formula, S, t epsilon S N ，i∈S T ；S N Collecting all nodes of a target power grid system; p (P) s,i 、Q s,i 、The active power output, the reactive power output, the active load output and the reactive load output of the node i in the fault scene i are respectively; v (V) s,i 、θ s,i The voltage amplitude and the voltage phase angle of the node s in the fault scene i are respectively; y is Y st,i 、α st,i The amplitude and phase angle of the node admittance matrix in the fault scene i are respectively.
Optionally, in the conventional unit hill climbing rate constraint, the hill climbing constraint rate refers to an output that the unit can increase or decrease in a unit time (1 min), where the output that the unit can increase in a unit time is called an up-slope rate (ramp-up), and vice versa is called a down-slope rate (ramp-down). The climbing rate constraint considering the previous moment can be expressed as:
Wherein S is P.G A conventional set of units included in the target power grid; p (P) n ' is the output of the conventional unit n at the previous moment;the power rise of the conventional unit n is limited, and the value of the power rise is equal to the ascending slope speed multiplied by the time interval (such as 15 min);the power drop of the conventional unit n is limited, and the value of the power drop is equal to the down-climbing speed multiplied by a time interval (such as 15 min).
Optionally, the control measure output constraint, that is, the output of each type of adjustable measure must be within the allowable maximum and minimum output ranges, and the corresponding formula is as follows:
wherein S is P An active adjustable measure set consisting of active adjustable control measures in a control measure combination; s is S Q A reactive adjustable measure set consisting of reactive adjustable control measures in a control measure combination; p (P) k An adjusted active force which is an active adjustable measure k; q (Q) k The reactive power output is adjusted by the reactive power adjustable measure k; P k the upper and lower limits of the output of the active adjustable measure k are respectively set; />Q k The upper and lower limits of the reactive power adjustable measure k are respectively adopted. Wherein, for the active power adjustable measures of the unit,wherein (1)> The upper and lower limits of the active output of the unit k are respectivelyNew energy unit->The maximum and minimum values of the output in all the scenes are respectively. Random load of electric automobile and the like > P k The maximum and minimum loads in all scenes are respectively.
In an optional embodiment, the performing iterative optimization calculation according to the plurality of control measures and the target fault scene set with a minimum system risk value, a minimum control cost and a maximum new energy consumption as objective functions to obtain the target control measure includes: converting the control cost minimum objective function and the new energy consumption maximum objective function into constraint conditions; and according to the plurality of control measures and the target fault scene set, taking the minimum system risk value as an objective function, carrying out iterative optimization calculation on the constraint condition that the output power of a new energy unit included in the target power grid is larger than a preset power threshold and the system risk value of the target power grid is smaller than the preset risk threshold, so as to obtain the target control measure.
Alternatively, the multi-objective optimization problem requires the decision maker to choose under each conflicting objective, screening out the appropriate tradeoff. The epsilon constraint method is widely adopted, one objective function in the multiple objective functions is used as a main objective function for optimization, other objective functions are used as constraint conditions and added into the model, and the Pareto solution of the original multi-objective optimization problem is obtained through calculation by controlling the value range of the objective functions in the constraint conditions. The method is adopted to convert the multi-objective prevention control optimization problem into a single-objective prevention control optimization problem.
Optionally, the objective of the minimum preventive control cost is taken as an objective function, and the explanation of the corresponding variables is the same as that described above, and is not repeated here.
Optionally, the control cost of converting the target with the maximum new energy consumption into the new energy unit is greater than the inequality constraint condition of the conventional unit, so that the conventional unit participates in control before the new energy unit. The conventional unit is adjusted preferentially to ensure that the system risk is within an acceptable risk range, and if no feasible solution exists, the system risk is controlled by the power output limit of the new energy unit. The corresponding formula is expressed as follows:
wherein C is pj The unit active output control cost of the jth new energy unit; c (C) pk The unit active output control cost of the kth conventional unit is set;and controlling the cost for the maximum unit active output in the conventional unit.
Optionally, the target with the minimum system risk is converted into an inequality constraint condition that the system risk is less than or equal to a certain threshold value, so as to ensure that the system risk is within an acceptable risk range.
Wherein R is a system risk value; ρ i For the probability of occurrence of the failure scenario i,ψ i for the fault consequences of the fault scenario i +.>Is an acceptable upper limit of system risk values.
Through the steps S102 to S110, the aim of determining the control strategy which is applicable to various power grid fault scenes and has the minimum control cost can be fulfilled, so that the technical effects of improving the power grid fault control accuracy and reducing the fault control cost are realized, and the technical problems of low power grid fault control accuracy and high control cost of a power grid auxiliary decision-making system in the related technology are solved.
Based on the foregoing embodiment and the optional embodiments, an optional implementation manner is provided in the present invention, and fig. 2 is a flowchart of an optional power grid fault control method according to an embodiment of the present invention, as shown in fig. 2, where the method includes:
step S1: and combining an operation mode considering the uncertainty of the source network load and the expected faults to generate a plurality of fault scenes to form a fault scene set.
Step S2: and performing risk assessment on each scene in the fault scene set, and calculating a system risk value.
Step S3: and judging whether the system risk value is larger than a threshold value, if so, entering a step S4, otherwise, exiting.
Step S4: and calculating comprehensive risk control performance indexes (namely control measure performance indexes) of various candidate control measures on various high-risk safety and stability problems under various risk scenes.
Step S5: the candidate control measures are respectively sequenced according to the comprehensive risk control performance index to form an effective control measure sequence list, and the specific method is as follows:
step S51, filtering the generator active adjustment control measure performance index I from the optional generator active increase or decrease preventive control measure under the condition that the control measure performance index is the generator active adjustment control measure performance index gpk An optional control measure less than or equal to 0 and according to I gpk Sequencing the rest optional control measures from big to small to obtain a generator active adjustment measure sequence table GS 1 If GS 1 Non-empty, then from GS 1 Well knockout I gpk /I gp.max An optional control measure smaller than the set value, wherein I gp.max For GS 1 All optional control measures I gpk Is the maximum value of (a).
Step S52, in control ofFiltering the load adjustment control measure performance index from the optional load increase or decrease preventive control measure under the condition that the measure performance index is the load adjustment control measure performance index lk An optional control measure less than or equal to 0 and according to I lk The rest optional control measures are ordered from big to small to obtain a load adjustment measure order table LS 1 If LS 1 Non-empty, then from LS 1 Well knockout I lk /I l.max An optional control measure smaller than the set value, wherein I l.max Is LS 1 All optional control measures I lk Is the maximum value of (a).
Step S53, filtering the DC adjustment control measure performance index I from the optional DC adjustment preventive control measure in case the control measure performance index is the DC adjustment control measure performance index dck An optional control measure less than or equal to 0 and according to I dck The rest optional control measures are sequenced from the big order to the small order to obtain a DC adjustment measure sequence table DCS 1 If DCS 1 Non-empty, then from DCS 1 Well knockout I dck /I dc.max An optional control measure smaller than the set value, wherein I dc.max Is DCS 1 All optional control measures I dck Is the maximum value of (a).
Step S54, filtering the reactive power adjustment control measure performance index I from the optional preventive control measure for increasing or decreasing the reactive power output of the generator under the condition that the control measure performance index is the reactive power adjustment control measure performance index of the generator gqk Optional control measure of 0 or less, filtering out the performance index I of the preventive control measure of the capacitor or the reactor switching from the preventive control measure of the optional capacitor/reactor switching xk Optional control measures smaller than or equal to 0, and uniformly sequencing the rest optional generator reactive power output increasing or decreasing preventive control measures and optional capacitor/reactor switching preventive control measures according to the sequence from large to small of the comprehensive risk performance indexes to obtain a reactive power adjustment measure sequence table QS 1 If QS is 1 Non-empty, then the QS is again 1 Well knockout I gqk /I gq.x.max Or I xk /I gq.x.max An optional control measure smaller than the set value, wherein I gq.x.max Is QS 1 All optional control measures I gqk And I xk Is the maximum value of (a).
Step S6: the control measures are split according to the set precision, the measure sequence list in the step S5 is updated, and a new control measure sequence list is obtained, and the specific method is as follows:
Step S61, adjusting the precision epsilon according to the set generator active power g.p Respectively aiming at the measure sequence table GS 1 Active power adjustment measures of each generator, meter and adjustable space delta P thereof g Dividing it into 1 or more adjusting measures which are ordered from small to large according to the adjustment amount and uniformly changed, and according to the adjustment amount in GS 1 Sequentially adding the decomposed adjustment measure sequences into a new generator active adjustment measure sequence table GS' 1 Is a kind of medium.
Step S62, adjusting the precision epsilon according to the set load l Respectively for LS 1 Each load adjustment measure of (1) meter and its adjustable space delta P l Dividing it into 1 or more adjusting measures which are ordered from small to large according to the adjustment amount and uniformly changed, and according to the adjustment amount in LS 1 Sequentially adding the decomposed adjustment measure sequences into a new load adjustment measure sequence table LS' 1 Is a kind of medium.
Step S63, adjusting the precision epsilon according to the set direct current power dc Respectively for DCS 1 Each direct current adjustment measure in (1) meter and adjustable space delta P thereof g Dividing it into 1 or more adjusting measures which are ordered from small to large according to the adjustment amount and uniformly changed, and according to the adjusting measures in DCS 1 Sequentially adding the decomposed adjustment measure sequences into a new DC adjustment measure sequence table DCS 1 'in'.
Step S64, according to the set reactive power adjustment precision epsilon of the generator g.q Respectively for QS 1 Reactive power regulation measure of each generator, meter and adjustable space delta Q thereof g Decomposing it into 1 or more pieces which are ordered from small to large according to adjustment amount and are allUniform adjustment measures for QS 1 Each capacitor/reactor switching measure is decomposed into 1 or more reactive power adjustment quantity difference absolute value and epsilon which are sequentially increased according to the number of capacitor/reactor switching groups and adjacent two adjustment measures according to reactive power adjustment direction g.q The minimum absolute value of the difference between the two is adjusted in QS according to the reactive power adjustment of the generator and the switching of the capacitor/reactor 1 Sequentially adding the adjustment measure sequences obtained after decomposition into a new reactive adjustment measure sequence table QS' 1 Is a kind of medium.
Step S65, for ranking in GS 1 The first generator active power regulation measures convert it into [ int (|Δp) g |/ε g.p +0.5)+1]The adjustment amounts are in an arithmetic progression such that the adjustment amount of the 1 st adjustment is 0 and the adjustment amount of the 2 nd adjustment is DeltaP g /int(|ΔP g |/ε g.p +0.5), and so on; for the remaining generator active power regulation measures, they are each converted into int (|Δp) g |/ε g.p +0.5) adjustment measures whose adjustment amounts are in an arithmetic progression such that the adjustment amount of the 1 st adjustment measure is Δp g /int(|ΔP g |/ε g.p +0.5), the adjustment amount of the 2 nd adjustment measure is 2ΔP g /int(|ΔP g |/ε g.p +0.5), and so on; for ordering at LS 1 The first load regulation measure in the middle converts it into [ int (|Δp) l |/ε l +0.5)+1]The adjustment amounts are in an arithmetic progression such that the adjustment amount of the 1 st adjustment is 0 and the adjustment amount of the 2 nd adjustment is DeltaP l /int(|ΔP l |/ε l +0.5), and so on; for the remaining load regulation measures, they are each converted into int (|Δp) l |/ε l +0.5) adjustment measures whose adjustment amounts are in an arithmetic progression such that the adjustment amount of the 1 st adjustment measure is Δp l /int(|ΔP l |/ε l +0.5), the adjustment amount of the 2 nd adjustment measure is 2ΔP l /int(|ΔP l |/ε l +0.5), and so on; for sequencing at DCS 1 The direct current adjusting measure of the first middle position,converts it into [ int (|ΔP) g |/ε dc +0.5)+1]The adjustment amounts are in an arithmetic progression such that the adjustment amount of the 1 st adjustment is 0 and the adjustment amount of the 2 nd adjustment is DeltaP g /int(|ΔP g |/ε dc +0.5), and so on; for the remaining dc regulation measures, they are each converted into int (|Δp) g |/ε dc +0.5) adjustment measures whose adjustment amounts are in an arithmetic progression such that the adjustment amount of the 1 st adjustment measure is Δp g /int(|ΔP g |/ε dc +0.5), the adjustment amount of the 2 nd adjustment measure is 2ΔP g /int(|ΔP g |/ε dc +0.5), and so on; if ordered in QS 1 The first reactive power regulation is the generator reactive power regulation, which is then converted into [ int (|Δq) g |/ε g.q +0.5)+1]The adjustment amounts are equal-difference series adjustment measures, so that the adjustment amount of the 1 st adjustment measure is 0 and the adjustment amount of the 2 nd adjustment measure is DeltaQ g /int(|ΔQ g |/ε g.q +0.5), and so on; for the remaining reactive power regulation measures of the generator, they are each converted into int (|Δq) g |/ε g.q +0.5) adjustment measures whose adjustment amounts are in an arithmetic progression such that the adjustment amount of the 1 st adjustment measure is Δq g /int(|ΔQ g |/ε g.q +0.5), the adjustment amount of the 2 nd adjustment measure is 2ΔQ g /int(|ΔQ g |/ε g.q +0.5), and so on; for the rest capacitor/reactor switching measures, the adjustment quantity of the first adjustment measure is set as the capacitor or reactor of the corresponding group number, otherwise, the capacitor or reactor is arranged in QS sequence 1 The first capacitor/reactor switching measure is set to 0, the first regulating measure is set to the corresponding group number of capacitors or reactors for the rest of the capacitor/reactor switching measures, and the rest of the generator reactive power regulating measures are respectively converted into int (|DeltaQ) g |/ε g.q +0.5) adjustment measures whose adjustment amounts are in an arithmetic progression such that the adjustment amount of the 1 st adjustment measure is Δq g /int(|ΔQ g |/ε g.q +0.5), 2 nd adjustmentThe adjustment amount of the measure is 2 delta Q g /int(|ΔQ g |/ε g.q +0.5), and so on.
Step S7: according to the set step length, on the premise of meeting the adjustment limit value of the candidate control measures, a control scheme is generated by enumerating the combination based on the new control measure sequence table, and a combination sequence table is obtained. The specific method comprises the following steps:
from GS ', respectively' 1 、LS′ 1 、DCS 1 'and QS' 1 The optional precaution control measure beginning sequence number ordered first in (n) is selected for enumerating the combination min (n gs ,n 1 ) Active power adjustment measure, min (n ls ,n 2 ) Individual load regulation measures, min (n) dcs ,n 3 ) The direct current regulation measures and min (n qs ,n 4 ) Reactive power adjustment measures are adopted, enumeration combination is carried out on the 4 measures, and min (n) gs ,n 1 )×min(n ls ,n 2 )×min(n dcs ,n 3 )×min(n qs ,n 4 ) A combination of control measures, wherein n gs 、n ls 、n dcs 、n qs GS ', respectively' 1 、LS′ 1 、DCS 1 'and QS' 1 The number of optional preventive control measures, n 1 、n 2 、n 3 、n 4 Respectively setting maximum values of the number of the power generator active adjustment measures, the load adjustment measures, the direct current adjustment measures and the reactive power adjustment measures which are used for enumeration combination of risk control decision calculation; then, for each control measure combination, calculating the active injection total quantity delta P of the control measure combination to the power grid in If [ f 0 +ΔP in f 0 /(KP sum.0 )]Greater than f ul Or less than f ll Wherein f 0 And P sum.0 Respectively, the sum of the frequency and the load active power of the power grid in the state after the adjustment measures are implemented, K is the power frequency static characteristic coefficient of the power grid, and the control measure combination is removed, f ul Scoring an upper limit value, f, of a frequency performance index in a state after a preset adjustment measure is implemented ll A lower limit value of a frequency performance index score in a state after a preset adjustment measure is implemented;finally, the rest control measure combinations are ordered according to the order of the control cost from small to large, and the control measure combination sequence table GLDCQS for risk assessment is obtained according to the order of the adjustment amount from small to large for the control measure combinations with the same control cost 1 。
Step S8: parallel risk assessment is carried out on each scene under each control scheme, and the specific method is as follows:
taking a risk scene set with a system risk value larger than a threshold value as a risk scene set F needing preventive control td (i.e., a set of target failure scenarios) based on GLDCQS 1 The control measure combinations with the forefront order in the middle are obtained to obtain a plurality of control measure combinations, and each control measure combination in the plurality of control measure combinations is combined with F td Each scene in (a) is combined to generate a common Risk evaluation example of power grid after control measure combination implementation is considered, wherein N is as follows td For the upper limit of the risk evaluation example number submitted to the cluster computing platform for processing at one time, n gldcq Is GLDCQS 1 The number of measures, n ftd Is F td The number of the scenes is combined in the GLDCQS according to the control measures 1 And (3) sequencing the generated examples to form a scheduling queue, and submitting the scheduling queue to a cluster system for parallel calculation of risk evaluation examples.
Determining target control measures (shown in figure 3) from a plurality of control measure combinations by adopting a parallel computing mode, wherein in the parallel computing process, the system risk of all fault scenes of at least one control measure combination is less than or equal to a risk threshold valueAnd stopping the calculation of all the remaining calculation examples, and combining the control measures which are the most forward with the ranking number and have the system risks of all the calculation examples less than or equal to the threshold value as the comprehensive decision measure for prevention control.
Step S8: and comprehensively comparing the system risks of the control schemes, selecting the control scheme with the minimum cost, which ensures the system risk to be within an acceptable range, and ending.
For the parallel computing method, in terms of prevention control decision taking into account multiple types of safety constraints, firstly, aiming at transient, dynamic and static 11 types of safety stability problems, the influences of generator active adjustment, generator reactive adjustment, direct current power adjustment, load adjustment and capacitor/reactor switching measures on different safety stability problems and different safety stability modes are comprehensively considered, and comprehensive control performance indexes of the multiple types of measures are calculated. On the basis, a method of decomposition coordination-cluster enumeration-loop iteration is adopted to carry out preventive control optimization decision, transient and dynamic safety and stability control decision is preferentially solved, on the basis, the problem of static safety control decision is solved, and coordination of the transient and dynamic safety and stability control decision is realized through loop iteration; in the transient dynamic decision, the optional adjustment measures of contradiction between transient, dynamic safety and stability comprehensive performance indexes and static safety comprehensive performance indexes are removed, and in the subsequent static decision, the adjustment direction of the previous auxiliary decision is considered, so that the subsequent auxiliary decision adjustment is ensured not to conflict with the previous auxiliary decision adjustment. In each stage, the adjustment measures which are subjected to queuing screening according to the control performance indexes are enumerated and combined according to types, and the cluster computing platform is combined to rapidly evaluate the safety and stability after the enumeration and combination measures are implemented, so that the decision scheme which meets all the fault safety and stability and has low control cost is obtained in an iterative manner.
The control performance index based on the adjustment measure can provide a search direction for the optimization decision; the comprehensive control performance index of the multiple types of safety and stability based on the adjustment measures can coordinate the control decisions of the multiple types of safety and stability; the calculation strategy of the transient state and dynamic safety and stability control decision priority and 'decomposition coordination and cyclic iteration' with the static safety and stability control decision can be adopted to solve the problems that the transient state and dynamic safety and stability control performance indexes based on the participation factors are different in meaning from the static safety and stability control performance indexes based on the sensitivity and cannot be uniformly sequenced; the candidate measures for enumeration combination can be greatly reduced by adopting sequencing, screening and mutual exclusion elimination based on control performance indexes, and the calculation speed of comprehensive optimization decision can be improved by adopting a cluster calculation platform to perform safe and stable quantitative evaluation on the adjustment measures of enumeration combination. According to the processing capacity estimation of the current cluster computing platform of the power grid dispatching center in the province level and above in China, the method is applied, and in most cases, the online preventive control auxiliary decision taking account of transient, dynamic and static multi-type safety and stability constraints can be calculated within 3 minutes.
For on-line safety and stability prevention control, the calculation speed is a problem to be considered, and when the potential safety and stability hazard occurs in the power grid, adjustment measures need to be given as soon as possible. Scene analysis by discretizing a random vector with a continuous probability distribution into a set of scenes, while reflecting the probability characteristics of the uncertainty variable, will generate a large number of scenes when the system contains multiple uncertainty quantities. The scene clustering or reduction is carried out at the expense of calculation precision, and on the premise of meeting the calculation precision requirement, the reduced scene set still brings excessive model scale and excessive calculation burden.
In order to fully utilize the powerful computing capability of the cluster computing platform, an enumeration parallel mode is adopted to replace a serial iteration process, so that the computing efficiency is improved, as shown in the following figure. For the calculation example which does not meet the requirement of system safety and stability, a plurality of adjustment schemes are formed on the management nodes of the cluster computing platform. And issuing the adjustment schemes to all the computing nodes, and simultaneously carrying out safety and stability evaluation of all the adjustment schemes on the computing units of all the computing nodes. And after the calculation is finished, uploading the calculation result to the management node. And the management node comprehensively compares the calculation results of all the calculation nodes, and finally selects the minimum cost adjustment mode for ensuring the safety and stability margin of the system to be within an acceptable range.
In this embodiment, a power grid fault control device is further provided, and the device is used to implement the foregoing embodiments and preferred embodiments, and is not described in detail. As used below, the terms "module," "apparatus" may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
According to an embodiment of the present invention, there is further provided an embodiment of an apparatus for implementing the above-mentioned power grid fault control method, and fig. 4 is a schematic structural diagram of a power grid fault control apparatus according to an embodiment of the present invention, as shown in fig. 4, where the above-mentioned power grid fault control apparatus includes: a first acquisition module 400, a second acquisition module 402, a first determination module 404, a second determination module 406, a third acquisition module 408, wherein:
the first obtaining module 400 is configured to obtain a plurality of fault scenarios according to an operation mode of the target power grid and a preset fault;
the second obtaining module 402 is connected to the first obtaining module 400, and is configured to perform risk assessment on the multiple fault scenarios, so as to obtain a system risk value of the target power grid under the multiple fault scenarios;
the first determining module 404 is connected to the second obtaining module 402, and configured to determine multiple types of candidate control measures corresponding to the multiple fault scenarios when it is determined that the system risk value is greater than a preset risk threshold, where the multiple types of candidate control measures include at least one candidate control measure respectively;
the second determining module 406, coupled to the first determining module 404, is configured to determine a plurality of control measure combinations based on control measure performance indicators corresponding to the plurality of candidate control measures, respectively;
The third obtaining module 408 is connected to the second determining module 406, and is configured to obtain a target control measure based on the combination of the plurality of control measures, where the target control measure is a group of control measures with the smallest control cost among the combination of the plurality of control measures.
In the embodiment of the invention, by arranging the first acquisition module 400, the second acquisition module 402, the first determination module 404, the second determination module 406 and the third acquisition module 408, the aim of determining the control strategy which is applicable to various power grid fault scenes and has the minimum control cost is achieved, so that the technical effects of improving the accuracy of power grid fault control and reducing the fault control cost are realized, and the technical problems of low accuracy of power grid fault control and high control cost of a power grid auxiliary decision system in the related art are further solved.
It should be noted that each of the above modules may be implemented by software or hardware, for example, in the latter case, it may be implemented by: the above modules may be located in the same processor; alternatively, the various modules described above may be located in different processors in any combination.
It should be noted that, the first obtaining module 400, the second obtaining module 402, the first determining module 404, the second determining module 406, and the third obtaining module 408 correspond to steps S102 to S110 in the embodiment, and the modules are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to the disclosure of the foregoing embodiments. It should be noted that the above modules may be run in a computer terminal as part of the apparatus.
It should be noted that, the optional or preferred implementation manner of this embodiment may be referred to the related description in the embodiment, and will not be repeated herein.
The above-mentioned power grid fault control device may further include a processor and a memory, where the above-mentioned first obtaining module 400, second obtaining module 402, first determining module 404, second determining module 406, third obtaining module 408, etc. are stored as program modules in the memory, and the processor executes the above-mentioned program modules stored in the memory to implement corresponding functions.
The processor comprises a kernel, the kernel accesses the memory to call the corresponding program module, and the kernel can be provided with one or more than one. The memory may include volatile memory, random Access Memory (RAM), and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM), among other forms in computer readable media, the memory including at least one memory chip.
According to an embodiment of the present application, there is also provided an embodiment of a nonvolatile storage medium. Optionally, in this embodiment, the nonvolatile storage medium includes a stored program, where the device where the nonvolatile storage medium is located is controlled to execute any one of the power grid fault control methods when the program runs.
Alternatively, in this embodiment, the above-mentioned nonvolatile storage medium may be located in any one of the computer terminals in the computer terminal group in the computer network or in any one of the mobile terminals in the mobile terminal group, and the above-mentioned nonvolatile storage medium includes a stored program.
Optionally, the program controls the device in which the nonvolatile storage medium is located to perform the following functions when running: obtaining a plurality of fault scenes according to the operation mode of the target power grid and preset faults; respectively carrying out risk assessment on the multiple fault scenes to obtain a system risk value of the target power grid under the multiple fault scenes; under the condition that the system risk value is larger than a preset risk threshold value, determining multiple types of candidate control measures corresponding to the multiple fault scenes, wherein the multiple types of candidate control measures respectively comprise at least one candidate control measure; determining a plurality of control measure combinations based on control measure performance indexes respectively corresponding to the plurality of types of candidate control measures; and obtaining a target control measure based on the plurality of control measure combinations, wherein the target control measure is a group of control measures with the minimum control cost in the plurality of control measure combinations.
According to an embodiment of the present application, there is also provided an embodiment of a processor. Optionally, in this embodiment, the processor is configured to run a program, where any one of the power grid fault control methods is executed when the program runs.
According to an embodiment of the present application, there is also provided an embodiment of a computer program product adapted to perform a program initialized with the steps of any one of the grid fault control methods described above when executed on a data processing device.
Optionally, the computer program product mentioned above, when executed on a data processing device, is adapted to perform a program initialized with the method steps of: obtaining a plurality of fault scenes according to the operation mode of the target power grid and preset faults; respectively carrying out risk assessment on the multiple fault scenes to obtain a system risk value of the target power grid under the multiple fault scenes; under the condition that the system risk value is larger than a preset risk threshold value, determining multiple types of candidate control measures corresponding to the multiple fault scenes, wherein the multiple types of candidate control measures respectively comprise at least one candidate control measure; determining a plurality of control measure combinations based on control measure performance indexes respectively corresponding to the plurality of types of candidate control measures; and obtaining a target control measure based on the plurality of control measure combinations, wherein the target control measure is a group of control measures with the minimum control cost in the plurality of control measure combinations.
The embodiment of the invention provides electronic equipment, which comprises a processor, a memory and a program stored on the memory and capable of running on the processor, wherein the program realizes the steps of any power grid fault control method when the processor executes the program.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed technology content may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the modules may be a logic function division, and there may be another division manner when actually implemented, for example, a plurality of modules or components may be combined or may be integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with respect to each other may be through some interface, module or indirect coupling or communication connection of modules, electrical or otherwise.
The modules described above as separate components may or may not be physically separate, and components shown as modules may or may not be physical modules, i.e., may be located in one place, or may be distributed over a plurality of modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist alone physically, or two or more modules may be integrated into one module. The integrated modules may be implemented in hardware or in software functional modules.
The integrated modules described above, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable non-volatile storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a non-volatile storage medium, including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of the embodiments of the present invention. And the aforementioned nonvolatile storage medium includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (11)
1. A power grid fault control method, comprising:
obtaining a plurality of fault scenes according to the operation mode of the target power grid and preset faults;
respectively carrying out risk assessment on the multiple fault scenes to obtain a system risk value of the target power grid under the multiple fault scenes;
under the condition that the system risk value is larger than a preset risk threshold value, determining multiple types of candidate control measures corresponding to the multiple fault scenes, wherein the multiple types of candidate control measures respectively comprise at least one candidate control measure;
determining a plurality of control measure combinations based on control measure performance indexes respectively corresponding to the plurality of types of candidate control measures;
and obtaining a target control measure based on the plurality of control measure combinations, wherein the target control measure is a group of control measures with the minimum control cost in the plurality of control measure combinations.
2. The method of claim 1, wherein the determining a plurality of control measure combinations based on control measure performance indicators corresponding to the plurality of types of candidate control measures, respectively, comprises:
under the condition that the system risk value is larger than a preset risk threshold, determining a control measure sequence table corresponding to each of the multiple types of candidate control measures based on the control measure performance indexes corresponding to each of the multiple types of candidate control measures, wherein at least one candidate control measure included in the control measure sequence table is arranged according to the sequence from the large control measure performance index score to the small control measure performance index score;
and determining the combination of the plurality of control measures according to the control measure sequence tables respectively corresponding to the plurality of types of candidate control measures.
3. The method according to claim 2, wherein determining the control measure sequence table corresponding to each of the plurality of types of candidate control measures based on the control measure performance indexes corresponding to each of the plurality of types of candidate control measures, comprises:
based on the control measure performance index corresponding to any type of candidate control measure in the multiple types of candidate control measures, the control measure sequence list corresponding to any type of candidate control measure is determined by the following method:
Determining a control measure performance index score for the at least one candidate control measure included in the any one type of candidate control measure;
determining a first candidate control measure with the control measure performance index score being greater than or equal to 0 in the at least one candidate control measure;
and sequencing the first candidate control measures according to the control measure performance index scores to obtain the control measure sequence list corresponding to any type of candidate control measures.
4. The method of claim 3, wherein the ranking the first candidate controls according to the control measure performance index score to obtain the control measure sequence table corresponding to the any type of candidate control measure includes:
determining a second candidate control measure with the highest control measure performance index score in the plurality of first candidate control measures and other candidate control measures except the second candidate control measure when the plurality of first candidate control measures are provided;
calculating a ratio between the other candidate control measure and the second candidate control measure;
determining a third candidate control measure with the ratio larger than a preset threshold value in the plurality of first candidate control strategies;
And sorting the third candidate control according to the control measure performance index score to obtain a control measure sequence table corresponding to any type of candidate control measure.
5. The method of claim 2, wherein determining a plurality of control measure combinations according to the control measure sequence tables respectively corresponding to the plurality of types of candidate control measures comprises:
determining an adjusting space of at least one candidate control measure corresponding to each of the multiple types of candidate control measures based on preset index adjusting precision corresponding to each of the multiple types of candidate control measures;
determining the splitting quantity corresponding to the at least one candidate control measure respectively corresponding to the multiple types of candidate control measures based on the adjusting space;
based on the splitting quantity, obtaining a new control measure sequence table corresponding to each of the multiple types of candidate control measures, wherein the control measure performance index scores between the split control measures corresponding to one candidate control measure in the new control measure sequence table are in an arithmetic sequence;
according to the candidate control measures included in the new control measure sequence list corresponding to the multiple types of candidate control measures respectively, arranging and combining to obtain a combined sequence list, wherein the control strategy combinations included in the combined sequence list are arranged according to the order of the control cost from small to large;
And combining the control strategies arranged in a preset number in the combined sequence table as a plurality of control measure combinations.
6. The method according to claim 5, wherein the ranking and combining the candidate control measures included in the new control measure ranking list according to the multiple types of candidate control measures respectively to obtain a combined ranking list includes:
according to the candidate control measures included in the new control measure sequence list respectively corresponding to the multiple types of candidate control measures, arranging and combining to obtain a first number of control measure combinations;
determining the active injection total amount of the first number of control measure combinations to the target power grid respectively;
determining whether the first number of control measure combinations meet a preset power condition or not according to the total active injection amount of the first number of control measure combinations to the target power grid;
and based on the control measure combinations meeting the preset power condition in the first number of control combinations, obtaining the combination sequence table.
7. The method of claim 1, wherein the deriving the target control measure based on the plurality of control measure combinations comprises:
Obtaining a target fault scene set based on the fault scenes with the system risk value larger than the preset risk threshold value in the multiple fault scenes;
and carrying out iterative optimization calculation by taking the minimum system risk value, the minimum control cost and the maximum new energy consumption as objective functions according to the plurality of control measures and the objective fault scene set to obtain the objective control measure.
8. The method of claim 7, wherein the performing iterative optimization calculation based on the plurality of control measures and the target fault scene set with a minimum system risk value, a minimum control cost, and a maximum new energy consumption as objective functions to obtain the target control measure comprises:
converting the minimum control cost objective function and the maximum new energy consumption objective function into constraint conditions;
and according to the plurality of control measures and the target fault scene set, taking the minimum system risk value as an objective function, carrying out iterative optimization calculation on the constraint condition that the output power of the new energy unit included in the target power grid is larger than a preset power threshold and the system risk value of the target power grid is smaller than the preset risk threshold, so as to obtain the target control measure.
9. The method according to any one of claims 1 to 8, wherein performing risk assessment on the plurality of fault scenarios respectively to obtain a system risk value of the target power grid under the plurality of fault scenarios includes:
acquiring at least one safety and stability problem corresponding to the multiple fault scenes respectively and safety and stability margin corresponding to the at least one safety and stability problem respectively;
determining fault consequences corresponding to the multiple fault scenes respectively based on at least one safety stability problem corresponding to the multiple fault scenes respectively and a safety stability margin corresponding to the at least one safety stability problem respectively;
acquiring fault occurrence probabilities corresponding to the multiple fault scenes respectively;
and obtaining the system risk value based on the fault result and the fault occurrence probability which are respectively corresponding to the multiple fault scenes.
10. A power grid fault control device, comprising:
the first acquisition module is used for obtaining a plurality of fault scenes according to the operation mode of the target power grid and preset faults;
the second acquisition module is used for respectively carrying out risk assessment on the multiple fault scenes to obtain a system risk value of the target power grid under the multiple fault scenes;
The first determining module is used for determining multiple types of candidate control measures corresponding to the multiple fault scenes under the condition that the system risk value is larger than a preset risk threshold, wherein the multiple types of candidate control measures respectively comprise at least one candidate control measure;
the second determining module is used for determining a plurality of control measure combinations based on control measure performance indexes respectively corresponding to the plurality of types of candidate control measures;
and the third acquisition module is used for obtaining a target control measure based on the plurality of control measure combinations, wherein the target control measure is a group of control measures with the minimum control cost in the plurality of control measure combinations.
11. A non-volatile storage medium, characterized in that it stores a plurality of instructions adapted to be loaded by a processor and to perform the grid fault control method according to any one of claims 1 to 9.
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