A power distribution network main demand response mode selection method, system, device and medium

Abstract

The application belongs to the field of power distribution network operation, and discloses a power distribution network leading demand response mode selection method, system, device and medium. The method comprises the following steps: generating a division result of a demand response trigger signal event according to an event demand judgment criterion of a power distribution network operation state; calculating priority index of various demand response trigger signal events to obtain priority index evaluation values; scoring feature index according to an evaluation criterion to obtain feature index scoring results, and summing the feature index scoring results to obtain a comprehensive coefficient; comparing and judging a power distribution network operation trigger signal comprehensive value to obtain a power distribution network operation event to be solved, so as to determine a power distribution network leading demand response mode. The power distribution network leading demand response mode selection method provided by the application comprehensively judges the operation problems in the power distribution network based on measured data, and realizes the selection of the demand response mode under the complex operation state of the power distribution network in combination with the proposed criterion.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of power distribution network operation, and in particular to a power distribution network dominant demand response mode selection method, system, device and medium. BACKGROUND

[0002] With the advancement of new power system construction, large-scale distributed energy such as photovoltaic and wind turbine is connected to the power distribution system, and the integration and interaction of source-grid-load-storage in the system is strengthened, but at the same time, the randomness and volatility of power distribution network operation are greatly increased. Since the connection of distributed source and load will affect the operation stability of the power distribution network, the power distribution network needs to regulate the regional adjustment resources for demand response to improve the operation level of the power distribution network. However, in the actual operation of the power distribution network, due to the diversity of operation problems, there are multiple demand response tasks, such as voltage out-of-limit control and reduction of network loss. The traditional power distribution network management is difficult to make global comprehensive judgment according to the real-time operation data of the power distribution network, and cannot efficiently select the demand response mode. The current power distribution network management urgently needs a more scientific demand response mode selection method to improve the scientificity and effectiveness of decision-making in power distribution network operation management.

[0003] Currently, there are studies on demand response strategies for power distribution network operation. The common method is to establish corresponding demand response strategies for controllable loads such as electric vehicle charging stations, large industrial users with energy storage, and air conditioning clusters, to improve the regulation and control capability and operation flexibility of the power distribution network. The current research on demand response strategies for power distribution network operation focuses on the regulation and control strategies of various controllable resources under a single demand response mode. However, these strategies often lack flexibility and cannot effectively respond to multiple types of demand response needs generated in the operation of the power distribution network. There is still a lack of efficient methods for selecting multiple types of operation problems in the operation of the power distribution network based on real-time data. If a more scientific demand response mode selection method is not proposed for the operation of the power distribution network, it will affect the efficiency of the operation and management of the power distribution network, leading to a decrease in user satisfaction and economic losses, and restricting the further construction and development of the new power system.

[0004] Therefore, how to provide a power distribution network dominant demand response mode selection method, system, device and medium is a problem to be solved at present. SUMMARY

[0005] The embodiments of the present application provide a power distribution network dominant demand response mode selection method, system, device and medium to solve the problem that it is difficult to make global comprehensive judgment according to real-time operation data of the power distribution network in the prior art.

[0006] The following presents a simplified summary of some aspects of the disclosed embodiments in order to provide a basic understanding of such embodiments. This summary is not an extensive overview of the embodiments and is intended neither to identify key / critical elements of the embodiments nor to delineate the scope of the embodiments. Its sole purpose is to present some concepts of the embodiments in a simplified form as a prelude to the more detailed description that is presented later.

[0007] According to a first aspect of embodiments of the present application, there is provided a power distribution grid dominant demand response mode selection method.

[0008] In one embodiment, the power distribution grid dominant demand response mode selection method comprises:

[0009] obtaining power distribution grid real-time operation monitoring data, obtaining power distribution grid operation states according to predefined power distribution grid operation trigger signal trigger condition criteria, and generating demand response trigger signal event division results according to power distribution grid operation state event demand judgment criteria;

[0010] calculating priority index indicators of various demand response trigger signal events, obtaining priority index evaluation values, and performing priority evaluation on various demand response trigger signal events based on the priority index evaluation values;

[0011] defining evaluation criteria of feature indicators based on the evaluation results, scoring the feature indicators according to the evaluation criteria, obtaining feature indicator scoring results, and obtaining a comprehensive coefficient by summing the feature indicator scoring results;

[0012] calculating weight coefficients of the feature indicators based on the comprehensive coefficient, and comparing and judging power distribution grid operation trigger signal comprehensive values according to the weight coefficients to obtain power distribution grid operation events to be solved, so as to determine the power distribution grid dominant demand response mode.

[0013] In one embodiment, the obtaining power distribution grid real-time operation monitoring data, obtaining power distribution grid operation states according to predefined power distribution grid operation trigger signal trigger condition criteria, and generating demand response trigger signal event division results according to power distribution grid operation state event demand judgment criteria comprises:

[0014] obtaining power distribution grid real-time operation monitoring data, extracting data information of various demand response trigger signal events from the power distribution grid real-time operation monitoring data, and obtaining power distribution grid operation states according to predefined power distribution grid operation trigger signal trigger condition criteria;

[0015] defining judgment criteria of various demand response trigger signal events based on the data information of various demand response trigger signal events, and obtaining trigger signals corresponding to various demand response trigger signal events;

[0016] A set of power distribution network nodes is generated based on the trigger signal, and a division of the operation state of the power distribution network is implemented based on the set of power distribution network nodes.

[0017] In one embodiment, the demand response trigger signal event includes voltage out-of-limit, network loss, grid frequency, line overload, and peak shaving;

[0018] The characteristic indicators included in the priority indicator include an influence range indicator, a duration indicator, a change amplitude indicator, a loss cost indicator, and a node access load indicator.

[0019] In one embodiment, the calculation formula of the priority indicator of the demand response trigger signal event is:

[0020] G i = ω1Z i + ω2T i + ω3C i + ω4A i + ω5B i i∈Q;

[0021] In the formula, G i is the priority indicator of the demand response trigger signal event occurring at the i node; Z i is the influence range of the demand response trigger signal event occurring at the i node; T i is the duration of the demand response trigger signal event occurring at the i node; C i is the importance of the load accessed by the i node; A i is the change amplitude of the demand response trigger signal event occurring at the i node; B i is the loss cost of the demand response trigger signal event occurring at the i node; ω1, ω2, ω3, ω4, and ω5 are weight coefficients corresponding to each characteristic indicator; and Q is the set of power distribution network nodes with trigger signals.

[0022] In one embodiment, the evaluation criteria of the characteristic indicators are defined based on the evaluation results, and the characteristic indicators are scored according to the evaluation criteria to obtain characteristic indicator score results, which include:

[0023] The characteristic indicators included in the priority indicator are calculated based on the evaluation results, and the evaluation criteria of the characteristic indicators are defined based on the characteristic indicator calculation results;

[0024] The characteristic indicators are scored based on the evaluation criteria of the characteristic indicators to obtain characteristic indicator score results, so as to realize standardization and unification of the characteristic indicators.

[0025] In one embodiment, the weight coefficient of the feature index is calculated based on the comprehensive coefficient, and the power distribution network operation event to be solved is obtained by comparing and judging the comprehensive values of the power distribution network operation trigger signals according to the weight coefficient, so as to determine the dominant demand response mode of the power distribution network, including:

[0026] The evaluation criterion based on the feature index and the weight coefficient of the feature index calculated by the comprehensive coefficient are used to calculate the comprehensive value of the trigger signal corresponding to the demand response trigger signal event;

[0027] The comprehensive values of the trigger signals are compared and judged, and the demand response trigger signal event corresponding to the maximum trigger signal comprehensive value is selected as the power distribution network operation event to be solved in the preset period, so as to determine the dominant demand response mode of the power distribution network.

[0028] In one embodiment, the calculation formula of the weight coefficient of the feature index is:

[0029]

[0030] In the formula, S i represents the comprehensive coefficient of the feature index; Z i represents the influence range of the demand response trigger signal event occurring at the i node; T i represents the duration of the demand response trigger signal event occurring at the i node; C i represents the importance of the load connected to the i node; A i represents the change amplitude of the demand response trigger signal event occurring at the i node; B i represents the loss cost of the demand response trigger signal event occurring at the i node; ω1, ω2, ω3, ω4 and ω5 are weight coefficients corresponding to respective feature indexes.

[0031] According to a second aspect of the embodiment of the present application, a power distribution network dominant demand response mode selection system is provided.

[0032] In one embodiment, the power distribution network dominant demand response mode selection system comprises:

[0033] A trigger signal judgment and event division module is configured to obtain real-time operation monitoring data of the power distribution network, obtain the operation state of the power distribution network according to the trigger condition criterion of the predefined power distribution network operation trigger signal, and generate the division result of the demand response trigger signal event according to the event demand judgment criterion of the power distribution network operation state;

[0034] A trigger signal priority evaluation module is configured to calculate the priority index of each type of demand response trigger signal event, obtain the priority index evaluation value, and perform priority evaluation on each type of demand response trigger signal event based on the priority index evaluation value;

[0035] The priority index score calculation module is configured to define an evaluation criterion for the characteristic index based on the evaluation result, score the characteristic index according to the evaluation criterion, obtain a characteristic index score result, and sum the characteristic index score result to obtain a comprehensive coefficient;

[0036] The index weight coefficient calculation module is configured to calculate a weight coefficient of the characteristic index based on the comprehensive coefficient, compare and judge the power distribution network operation trigger signal comprehensive value according to the weight coefficient, and obtain a power distribution network operation event to be solved to determine a dominant demand response mode of the power distribution network.

[0037] In one embodiment, the trigger signal judgment and event division module includes a trigger signal definition module, a trigger signal generation module, and a trigger signal event division module, wherein,

[0038] The trigger signal definition module is configured to obtain real-time operation monitoring data of the power distribution network, extract data information of various demand response trigger signal events from the real-time operation monitoring data of the power distribution network, and obtain a power distribution network operation state according to a predefined trigger condition criterion of the power distribution network operation trigger signal.

[0039] The trigger signal generation module is configured to define a judgment criterion of various demand response trigger signal events based on the data information of the various demand response trigger signal events, and obtain a trigger signal corresponding to the various demand response trigger signal events.

[0040] The trigger signal event division module is configured to generate a power distribution network node set based on the trigger signal, and divide the power distribution network operation state based on the power distribution network node set.

[0041] In one embodiment, the demand response trigger signal events include voltage out-of-limit, network loss, power grid frequency, line overload, and peak shaving and valley filling.

[0042] The characteristic index contained in the priority index includes an influence range index, a duration index, a change amplitude index, a loss cost index, and a node access load index.

[0043] In one embodiment, the calculation formula of the priority index of the demand response trigger signal event is:

[0044] G i = ω1Z i + ω2T i + ω3C i + ω4A i + ω5B i i ∈ Q.

[0045] In the formula, G i is the priority index of the demand response trigger signal event occurring at the i node; Z ian influence range of the demand response trigger signal event occurring at the i-th node; T i a duration of the demand response trigger signal event occurring at the i-th node; C i an importance of the load connected to the i-th node; A i a variation range of the demand response trigger signal event occurring at the i-th node; B i a loss cost of the demand response trigger signal event occurring at the i-th node; ω1, ω2, ω3, ω4 and ω5 are weight coefficients corresponding to the respective characteristic indexes; and Q is a set of distribution network nodes with trigger signals.

[0046] In one embodiment, the priority index score calculation module comprises an evaluation criterion definition module and a characteristic index score calculation module, wherein,

[0047] The evaluation criterion definition module is configured to calculate the characteristic indexes contained in the priority indexes based on the evaluation results, and define evaluation criteria of the characteristic indexes based on the calculation results of the characteristic indexes.

[0048] The characteristic index score calculation module is configured to score the characteristic indexes based on the evaluation criteria of the characteristic indexes, to obtain a characteristic index score result, so as to realize standardization and unification of the characteristic indexes.

[0049] In one embodiment, the index weight coefficient calculation module comprises a comprehensive value calculation module and a demand response mode determination module, wherein,

[0050] The comprehensive value calculation module is configured to calculate the weight coefficients of the characteristic indexes based on the evaluation criteria of the characteristic indexes and comprehensive coefficients, and calculate comprehensive values of trigger signals corresponding to the demand response trigger signal events.

[0051] The demand response mode determination module is configured to compare and judge the comprehensive values of the trigger signals, select a demand response trigger signal event corresponding to a maximum trigger signal comprehensive value as a distribution network operation event to be solved in a preset time period, and determine a dominant demand response mode of the distribution network.

[0052] In one embodiment, the calculation formula of the weight coefficients of the characteristic indexes is as follows:

[0053]

[0054] In the formula, S i denotes a comprehensive coefficient of the characteristic indexes; Z i an influence range of the demand response trigger signal event occurring at the i-th node; T i a duration of the demand response trigger signal event occurring at the i-th node; C i an importance of the load connected to the i-th node; A iThe change range of the demand response trigger signal event occurring for the i node; B i The loss cost of the demand response trigger signal event occurring for the i node; ω1, ω2, ω3, ω4, and ω5 are weight coefficients corresponding to each feature index.

[0055] According to a third aspect of the embodiments of the present application, a computer device is provided.

[0056] In one embodiment, the computer device comprises a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0057] According to a fourth aspect of the embodiments of the present application, a computer readable storage medium is provided.

[0058] In one embodiment, the computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the above method.

[0059] The technical solutions provided by the embodiments of the present application can include the following beneficial effects:

[0060] 1. The power distribution network dominant demand response mode selection method provided by the present application comprehensively judges the operation problems in the power distribution network based on measured data, and realizes the selection of demand response modes under complex operation states of the power distribution network in combination with the proposed criteria.

[0061] 2. The present application takes into account the source and load power characteristics and the spatial and temporal distribution characteristics, proposes five types of demand side response events of the power distribution network, including voltage out-of-limit events, network loss events, grid frequency events, line overload events, and peak clipping and valley filling events, and formulates alternative modes of multi-dimensional demand response of the power distribution network.

[0062] 3. The present application considers the operation characteristic analysis of the power distribution network considering the interaction between distributed energy and load, and realizes comprehensive evaluation of demand response events through priority index calculation of trigger signal nodes of various events, fully excavating the characteristics of demand response in terms of influence range, duration, change range, loss cost, and node load.

[0063] 4. The present application can dynamically adapt to the changes in the operation state of the power distribution network through multi-dimensional judgment of demand side response events, more accurately reflects the operation environment and demand changes of the power distribution network in actual application, and through systematic priority evaluation and comprehensive analysis, can comprehensively evaluate and optimize demand response strategies, effectively improving the response speed and processing capacity for emergencies; the power distribution network dominant demand response mode selection method provided by the present application has a wide range of applications and can be applied to the field of power systems, improving the efficiency and flexibility of demand response decision-making for power distribution network operation in power systems.

[0064] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application, as claimed. BRIEF DESCRIPTION OF DRAWINGS

[0065] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and serve to explain the principles of the application, in which, like reference numerals designate corresponding parts throughout the several views.

[0066] Figure 1 is a flow chart of a power distribution network dominant demand response mode selection method according to an exemplary embodiment;

[0067] Figure 2 is a schematic block diagram of a power distribution network dominant demand response mode selection system according to an exemplary embodiment;

[0068] Figure 3 is a structural schematic diagram of a computer device according to an exemplary embodiment;

[0069] Figure 4 is an implementation schematic diagram of a power distribution network dominant demand response mode selection method according to an exemplary embodiment;

[0070] Figure 5 is a demand response trigger signal event division schematic diagram in a power distribution network dominant demand response mode selection method according to an exemplary embodiment;

[0071] Figure 6 is a priority feature index schematic diagram in a power distribution network dominant demand response mode selection method according to an exemplary embodiment;

[0072] Figure 7 is a priority feature index corresponding weight coefficient change trend schematic diagram in a power distribution network dominant demand response mode selection method according to an exemplary embodiment;

[0073] Figure 8 is a power distribution network operation event decision to be solved schematic diagram in a power distribution network dominant demand response mode selection method according to an exemplary embodiment. DETAILED DESCRIPTION

[0074] The following description and accompanying drawings fully illustrate specific embodiments described herein to enable those skilled in the art to practice them. Some embodiments may include or substitute parts and features of other embodiments. The scope of the embodiments herein encompasses the entire scope of the claims and all available equivalents thereof. Throughout this document, the terms “first,” “second,” etc., are used only to distinguish one element from another without requiring or implying any actual relationship or order between the elements. Indeed, a first element can also be referred to as a second element, and vice versa. Furthermore, the terms “comprising,” “including,” or any other variations thereof are intended to cover non-exclusive inclusion, such that a structure, apparatus, or device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a structure, apparatus, or device. Without further limitation, an element defined by the phrase “comprising one…” does not exclude the presence of other identical elements in the structure, apparatus, or device that includes said element. The various embodiments described herein are presented in a progressive manner, with each embodiment focusing on its differences from other embodiments; similar or identical parts between embodiments can be referred to interchangeably.

[0075] The terms "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer" used in this document to indicate orientations or positional relationships are based on the orientations or positional relationships shown in the accompanying drawings. They are used solely for the convenience of describing the document and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. In the description herein, unless otherwise specified and limited, the terms "installed," "connected," and "linked" should be interpreted broadly. For example, they can refer to mechanical or electrical connections, or internal connections between two elements; they can be direct connections or indirect connections through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms according to the specific circumstances.

[0076] In this document, unless otherwise stated, the term "multiple" means two or more.

[0077] In this article, the character " / " indicates that the objects before and after it are in an "or" relationship. For example, A / B means: A or B.

[0078] In this article, the term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0079] It should be understood that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order constraint on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the diagram may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0080] The modules in the apparatus or system of this application can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0081] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0082] Figure 1 An embodiment of the distribution network dominant demand response mode selection method of the present invention is shown.

[0083] In this optional embodiment, the method for selecting the dominant demand response mode of the distribution network includes:

[0084] Step S101: Obtain real-time operation monitoring data of the distribution network, obtain the operation status of the distribution network according to the predefined triggering condition criteria of the distribution network operation triggering signal, and generate the division result of the demand response triggering signal event according to the event demand judgment criteria of the distribution network operation status.

[0085] Step S103: Calculate the priority index of various demand response trigger signal events, obtain the priority index evaluation value, and evaluate the priority of various demand response trigger signal events based on the priority index evaluation value.

[0086] Step S105: Define the evaluation criteria for the feature indicators based on the evaluation results, score the feature indicators according to the evaluation criteria, obtain the feature indicator score results, and sum the feature indicator score results to obtain the comprehensive coefficient.

[0087] Step S107: Calculate the weight coefficient of the characteristic index based on the comprehensive coefficient, and compare and judge the comprehensive value of the distribution network operation trigger signal according to the weight coefficient to obtain the distribution network operation event to be resolved, so as to clarify the dominant demand response mode of the distribution network.

[0088] In this optional embodiment, the steps of acquiring real-time operation monitoring data of the distribution network, obtaining the operation status of the distribution network according to predefined triggering condition criteria for distribution network operation triggering signals, and generating the division result of demand response triggering signal events according to the event demand judgment criteria of the distribution network operation status include: acquiring real-time operation monitoring data of the distribution network, extracting data information of various demand response triggering signal events from the real-time operation monitoring data of the distribution network, and obtaining the operation status of the distribution network according to predefined triggering condition criteria for distribution network operation triggering signals; defining judgment criteria for various demand response triggering signal events based on the data information of various demand response triggering signal events, and obtaining the triggering signals corresponding to various demand response triggering signal events; generating a distribution network node set based on the triggering signals, and dividing the operation status of the distribution network based on the distribution network node set.

[0089] In this optional embodiment, the demand response triggering signal events include voltage over-limit, network loss, grid frequency, line overload, and peak shaving and valley filling; the priority index includes characteristic indicators such as impact range index, duration index, change magnitude index, loss cost index, and node access load index.

[0090] In this optional embodiment, the priority index of the demand response trigger signal event is calculated using the following formula:

[0091] G i =ω1Z i +ω2T i +ω3C i +ω4A i +ω5B i i∈Q;

[0092] In the formula, G i Z is the priority indicator for demand response trigger signal events occurring at node i; i The scope of influence of the demand response trigger signal event occurring at node i; T i The duration of the demand response trigger signal event occurring at node i; C i The importance of the load connected to the i-node; A i B represents the magnitude of the change in the demand response trigger signal event occurring at node i; i ω1, ω2, ω3, ω4 and ω5 are the weighting coefficients corresponding to each characteristic index; Q is the set of distribution network nodes with trigger signals.

[0093] In this optional embodiment, the step of defining the evaluation criteria for feature indicators based on the evaluation results and scoring the feature indicators according to the evaluation criteria to obtain the feature indicator scoring results includes: calculating the feature indicators contained within the priority indicators based on the evaluation results and defining the evaluation criteria for the feature indicators based on the feature indicator calculation results; and scoring the feature indicators based on the evaluation criteria to obtain the feature indicator scoring results, so as to achieve standardization and unification of feature indicators.

[0094] In this optional embodiment, the step of calculating the weight coefficients of characteristic indicators based on comprehensive coefficients and comparing and judging the comprehensive values ​​of distribution network operation trigger signals according to the weight coefficients to obtain the distribution network operation events to be resolved, so as to clarify the distribution network-dominant demand response mode, includes: calculating the weight coefficients of characteristic indicators based on the evaluation criteria of characteristic indicators and comprehensive coefficients, and calculating the comprehensive value of the trigger signal corresponding to the demand response trigger signal event; comparing and judging the comprehensive values ​​of the trigger signals, and selecting the demand response trigger signal event corresponding to the largest comprehensive value of the trigger signal as the distribution network operation event to be resolved under the preset time period, so as to clarify the distribution network-dominant demand response mode.

[0095] In this optional embodiment, the formula for calculating the weight coefficient of the feature index is:

[0096]

[0097] In the formula, S i Z represents the comprehensive coefficient of the characteristic index. i The scope of influence of the demand response trigger signal event occurring at node i; T i The duration of the demand response trigger signal event occurring at node i; C i The importance of the load connected to the i-node; A i B represents the magnitude of the change in the demand response trigger signal event occurring at node i; i ω1, ω2, ω3, ω4 and ω5 are the weighting coefficients corresponding to each feature index.

[0098] Figure 2 An embodiment of the distribution network dominant demand response mode selection system of the present invention is shown.

[0099] In this optional embodiment, the distribution network dominant demand response mode selection system includes:

[0100] The trigger signal judgment and event division module 201 is used to acquire real-time operation monitoring data of the distribution network, obtain the operation status of the distribution network according to the predefined trigger condition criteria of the distribution network operation trigger signal, and generate the division result of the demand response trigger signal event according to the event demand judgment criteria of the distribution network operation status.

[0101] The trigger signal priority evaluation module 203 is used to calculate the priority index of various demand response trigger signal events, obtain the priority index evaluation value, and evaluate the priority of various demand response trigger signal events based on the priority index evaluation value.

[0102] The priority indicator scoring calculation module 205 is used to define the evaluation criteria for the characteristic indicators based on the evaluation results, score the characteristic indicators according to the evaluation criteria, obtain the characteristic indicator scoring results, and sum the characteristic indicator scoring results to obtain the comprehensive coefficient.

[0103] The indicator weight coefficient calculation module 207 is used to calculate the weight coefficient of the characteristic indicator based on the comprehensive coefficient, and compare and judge the comprehensive value of the distribution network operation trigger signal according to the weight coefficient to obtain the distribution network operation event to be resolved, so as to clarify the dominant demand response mode of the distribution network.

[0104] In this optional embodiment, the trigger signal judgment and event division module 201 includes a trigger signal definition module (not shown in the figure), a trigger signal generation module (not shown in the figure), and a trigger signal event division module (not shown in the figure). The trigger signal definition module is used to acquire real-time operation monitoring data of the distribution network, extract data information of various demand response trigger signal events from the real-time operation monitoring data, and obtain the distribution network operation status according to predefined triggering condition criteria for distribution network operation trigger signals. The trigger signal generation module is used to define judgment criteria for various demand response trigger signal events based on the data information of various demand response trigger signal events, and obtain the trigger signals corresponding to various demand response trigger signal events. The trigger signal event division module is used to generate a distribution network node set based on the trigger signals, and to divide the distribution network operation status based on the distribution network node set.

[0105] In this optional embodiment, the demand response triggering signal events include voltage over-limit, network loss, grid frequency, line overload, and peak shaving and valley filling; the priority index includes characteristic indicators such as impact range index, duration index, change magnitude index, loss cost index, and node access load index.

[0106] In this optional embodiment, the priority index of the demand response trigger signal event is calculated using the following formula:

[0107] G i =ω1Zi +ω2T i +ω3C i +ω4A i +ω5B i i∈Q;

[0108] In the formula, G i Z is the priority indicator for demand response trigger signal events occurring at node i; i The scope of influence of the demand response trigger signal event occurring at node i; T i The duration of the demand response trigger signal event occurring at node i; C i The importance of the load connected to the i-node; A i B represents the magnitude of the change in the demand response trigger signal event occurring at node i; i ω1, ω2, ω3, ω4 and ω5 are the weighting coefficients corresponding to each characteristic index; Q is the set of distribution network nodes with trigger signals.

[0109] In this optional embodiment, the priority indicator scoring calculation module 205 includes an evaluation criterion definition module (not shown in the figure) and a feature indicator scoring module (not shown in the figure). The evaluation criterion definition module is used to calculate the feature indicators contained in the priority indicators based on the evaluation results, and define the evaluation criteria for the feature indicators based on the feature indicator calculation results. The feature indicator scoring module is used to score the feature indicators based on the evaluation criteria for the feature indicators, and obtain the feature indicator scoring results, so as to achieve standardization and unification of the feature indicators.

[0110] In this optional embodiment, the indicator weight coefficient calculation module 207 includes a comprehensive value calculation module (not shown in the figure) and a demand response mode determination module (not shown in the figure). The comprehensive value calculation module is used to calculate the weight coefficient of the characteristic indicator based on the evaluation criteria and comprehensive coefficient of the characteristic indicator, and to calculate the comprehensive value of the trigger signal corresponding to the demand response trigger signal event. The demand response mode determination module is used to compare and judge the comprehensive values ​​of the trigger signals, and select the demand response trigger signal event corresponding to the largest comprehensive value of the trigger signal as the distribution network operation event to be resolved under the preset time period, so as to determine the dominant demand response mode of the distribution network.

[0111] In this optional embodiment, the formula for calculating the weight coefficient of the feature index is:

[0112]

[0113] In the formula, S i Z represents the comprehensive coefficient of the characteristic index. iThe scope of influence of the demand response trigger signal event occurring at node i; T i The duration of the demand response trigger signal event occurring at node i; C i The importance of the load connected to the i-node; A i B represents the magnitude of the change in the demand response trigger signal event occurring at node i; i ω1, ω2, ω3, ω4 and ω5 are the weighting coefficients corresponding to each feature index.

[0114] The following is a detailed description of the method for selecting the dominant demand response mode of the distribution network provided by the present invention.

[0115] like Figure 4 As shown, the methods for selecting the dominant demand response mode in a distribution network include:

[0116] The acquired real-time operation monitoring data of the distribution network is analyzed and calculated. Based on the triggering conditions of distribution network operation triggering signals, the operating status of distribution network nodes (equivalent to real-time operating voltage, network loss, current, etc.) is obtained. Simultaneously, based on the demand judgment criteria for various events in distribution network operation (equivalent to demand response triggering signal events), such as... Figure 5 As shown, the classification results of five types of events are obtained: voltage over-limit, network loss, grid frequency, line overload, and peak shaving and valley filling.

[0117] Based on the data information related to the voltage over-limit events during the acquired time period, the trigger signal for the voltage over-limit events is determined.

[0118] The criteria for determining the voltage over-limit event trigger signal D1 are as follows:

[0119]

[0120] In the formula: V i V is the monitored voltage value of node i; min The set lower limit value for node voltage; V max The upper limit value for the node voltage is set.

[0121] Based on the data information related to network loss events acquired during the time period, the trigger signals for network loss events are determined.

[0122] The criteria for determining the network loss event trigger signal D2 are as follows:

[0123]

[0124] In the formula: P ij,loss P represents the network power loss value on the line between node i and node j; th,loss This is the upper limit for the line network loss that is set.

[0125] Based on the data information related to the power grid frequency events during the acquired time period, the trigger signals of the power grid frequency events are determined.

[0126] The criteria for determining the power grid frequency event trigger signal D3 are as follows:

[0127]

[0128] In the formula: f is the monitoring frequency value of the system; f min The lower limit of the system frequency is set; f max This is the maximum system frequency setting.

[0129] Based on the data information related to the line overload events during the acquired time period, the trigger signal of the line overload event is determined.

[0130] The criteria for determining the line overload event trigger signal D4 are as follows:

[0131]

[0132] In the formula: I ij I represents the monitored current value on the line between node i and node j; th The set safety threshold for line current is generally the line's rated current.

[0133] Based on the data information involved in the peak shaving and valley filling events during the acquired time period, the trigger signals of the peak shaving and valley filling events are determined.

[0134] The criteria for determining the peak shaving and valley filling event trigger signal D5 are as follows:

[0135]

[0136] In the formula: P i P represents the actual load connected to node i; i,base The baseline load for node i; P th The threshold value set for the difference between the two.

[0137] Based on the judgment criteria for various event demands in the above-mentioned distribution network operation, corresponding trigger signals are obtained, which are used to classify the operating states of distribution network nodes. The expression is as follows:

[0138]

[0139] In the formula: Q is the set of distribution network nodes with trigger signals; N is the set of distribution network nodes without trigger signals.

[0140] Priority indices are calculated for trigger signal nodes of various events in the regional power distribution network to obtain priority index evaluation values ​​for trigger signal nodes of various events.

[0141] Considering that the impact, duration, magnitude of change, cost of loss, and characteristics of the occurrence nodes differ after the occurrence of five types of events—voltage exceeding limits, network losses, grid frequency, line overload, and peak shaving and valley filling—such as… Figure 6 As shown, the trigger signals of various events are prioritized based on these characteristic indicators.

[0142] The above priority indicator G i The calculation method is as follows:

[0143] G i =ω1Z i +ω2T i +ω3C i +ω4A i +ω5B i i∈Q;

[0144] Where: G i Z is the priority indicator for demand response trigger signal events occurring at node i; i The scope of influence of the demand response trigger signal event occurring at node i; T i The duration of the demand response trigger signal event occurring at node i; C i The importance of the load connected to the i-node; A i B represents the magnitude of the change in the demand response trigger signal event occurring at node i; i The cost of the demand response trigger signal event occurring at node i; ω1, ω2, ω3, ω4, and ω5 are the weighting coefficients corresponding to each feature index. The larger the value, the greater the influence of the corresponding index, such as... Figure 7 As shown, and satisfying ω1+ω2+ω3+ω4+ω5=1.

[0145] A unified standard is established for the impact range, duration, magnitude of change, loss cost, and the characteristics of the occurrence node included in the priority indicators. Evaluation criteria for each indicator are obtained, and the impact range indicator within the priority indicators is scored to achieve standardization and unification.

[0146] Calculate the impact range index:

[0147]

[0148] In the formula: Z i N is an indicator of the scope of influence. affected,i N represents the number of affected devices or users. total,iThis represents the total number of devices or users within the region.

[0149] The evaluation criteria for the impact range indicator are as follows, where z1, z2, and z3 are the judgment thresholds for this indicator, which are determined by the control personnel based on the power grid operation requirements:

[0150]

[0151] The duration metrics within the priority metrics are scored to achieve standardization and uniformity.

[0152] Calculate the duration index:

[0153] T i =t end -t start ;

[0154] In the formula: T i For duration indicators; t end N is the time when the event ends. total,i This refers to the time when the event occurred.

[0155] The evaluation criteria for the duration indicator are as follows, where t1, t2, and t3 are the judgment thresholds for this indicator, which are determined by the management personnel based on the power grid operation requirements:

[0156]

[0157] The importance of node access load within the priority index is scored to achieve standardization and unification.

[0158] The importance of node access load is calculated as follows:

[0159]

[0160] In the formula: C i P is an indicator of the importance of the load connected to the node. vital,i P is an important load connected to the i-node. total,i This represents the total load connected to node i.

[0161] The evaluation criteria for the importance indicators of node access loads are as follows, where c1, c2, and c3 are the judgment thresholds for these indicators, which are determined by the management personnel based on the power grid operation requirements:

[0162]

[0163] The variation range indicators within the priority indicators are scored to achieve standardization and uniformity.

[0164] Calculate the magnitude of change index:

[0165]

[0166] In the formula: A i V is an indicator of the magnitude of change. i,t,max V i,t,min Let P be the maximum and minimum values ​​of the monitored voltage at node i during time period t. ij,loss,t,max P ij,loss,t,min Let f be the maximum and minimum network power loss during time period t between node i and node j, respectively. i,t,max f i,t,min Let I be the maximum and minimum values ​​of the system monitoring frequency during time period t at node i. ij,t,max I ij,t,min P represents the maximum and minimum monitored current values ​​of the line between node i and node j during time period t. i,t,max P i,t,min These represent the maximum and minimum values ​​of the access load at node i during time period t, respectively.

[0167] The evaluation criteria for the change range index are as follows, where a1, a2, and a3 are the judgment thresholds for this index, which are determined by the control personnel based on the power grid operation requirements:

[0168]

[0169] The loss cost indicators within the priority indicators are scored to achieve standardization and uniformity.

[0170] The evaluation criteria for the loss cost indicator are as follows, where b1, b2, and b3 are the judgment thresholds for this indicator, which are determined by the management personnel based on the power grid operation requirements:

[0171]

[0172] The weight coefficients for the scope of impact, duration, magnitude of change, cost of loss, and the characteristics of the occurrence node are calculated to obtain the weight coefficients for each indicator.

[0173] First, the scores of the five indicators are summed to obtain the comprehensive coefficient S. i :

[0174] S i =Z i +T i +C i +A i +B i ;

[0175] The weighting coefficients for each indicator are calculated as follows:

[0176]

[0177] The obtained comprehensive values ​​of the corresponding event trigger signals are compared and judged. Based on the priority index of the trigger signals of each event at different nodes calculated above, the final distribution network operation events to be resolved in this time period are obtained. "Evaluation criteria" refers to the criteria for calculating each part of the priority index; while "evaluation principle" here refers to an evaluation principle for comparing the comprehensive priority values.

[0178] When multiple events occur due to a valid trigger signal, only one event can be responded to and processed in the current time period. The calculation of the combined values ​​d1, d2, d3, d4, and d5 for various event trigger signals is as follows:

[0179]

[0180] In the formula: d1, d2, d3, d4, and d5 correspond to the combined values ​​of trigger signals under voltage over-limit, network loss, grid frequency, line overload, and peak shaving and valley filling events, respectively; Q is the set of distribution network nodes with trigger signals; D1 is the voltage over-limit event trigger signal; D2 is the network loss event trigger signal; D3 is the grid frequency event trigger signal; D4 is the line overload event trigger signal; and D5 is the peak shaving and valley filling event trigger signal.

[0181] The event corresponding to the largest calculated comprehensive value of the event trigger signal is selected as the distribution network operation event to be resolved in that time period, such as... Figure 8 As shown, that is:

[0182] max{d1,d2,d3,d4,d5};

[0183] In the formula: d1, d2, d3, d4, and d5 correspond to the combined values ​​of trigger signals under voltage over-limit, network loss, power grid frequency, line overload, and peak shaving and valley filling events, respectively.

[0184] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 3 As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores static and dynamic information data. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements the steps in the above method embodiments.

[0185] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the computer device to which the present invention is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0186] In addition, the present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0187] In addition, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0188] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0189] This invention is not limited to the structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this invention is limited only by the appended claims.

Claims

1. A method for selecting the dominant demand response mode in a distribution network, characterized in that, The method includes: The system acquires real-time operation monitoring data of the distribution network, obtains the operation status of the distribution network based on the predefined triggering condition criteria of the distribution network operation triggering signal, and generates the division results of the demand response triggering signal events according to the event demand judgment criteria of the distribution network operation status. Calculate the priority index of various demand response trigger signal events, obtain the priority index evaluation value, and evaluate the priority of various demand response trigger signal events based on the priority index evaluation value; Evaluation criteria for characteristic indicators are defined based on the evaluation results, and the characteristic indicators are scored according to the evaluation criteria to obtain the characteristic indicator scoring results. The comprehensive coefficient is obtained by summing the characteristic indicator scoring results. The weight coefficients of characteristic indicators are calculated based on the comprehensive coefficients, and the comprehensive values ​​of the distribution network operation trigger signals are compared and judged based on the weight coefficients to obtain the distribution network operation events to be resolved, so as to clarify the dominant demand response mode of the distribution network. The process of acquiring real-time operation monitoring data of the distribution network, obtaining the distribution network operation status based on predefined triggering condition criteria for distribution network operation triggering signals, and generating the division results of demand response triggering signal events according to the event demand judgment criteria of the distribution network operation status includes: Acquire real-time operation monitoring data of the distribution network, extract data information of various demand response trigger signal events from the real-time operation monitoring data of the distribution network, and obtain the operation status of the distribution network according to the predefined triggering condition criteria of the distribution network operation trigger signal; Based on the data information of various demand response trigger signal events, the judgment criteria for various demand response trigger signal events are defined, and the trigger signals corresponding to various demand response trigger signal events are obtained. A set of distribution network nodes is generated based on trigger signals, and the operation status of the distribution network is divided based on the set of distribution network nodes; The demand response triggering signal events include voltage over-limit, network loss, grid frequency, line overload, and peak shaving and valley filling; The priority index includes characteristic indicators such as the scope of influence, duration, magnitude of change, cost of loss, and node access load.

2. The method for selecting the dominant demand response mode of a distribution network according to claim 1, characterized in that, The formula for calculating the priority index of the demand response trigger signal event is as follows: G i =ω1Z i +ω2T i +ω3C i +ω4A i +ω5B i i∈Q; In the formula, G i Z is the priority indicator for demand response trigger signal events occurring at node i; i The scope of influence of the demand response trigger signal event occurring at node i; T i The duration of the demand response trigger signal event occurring at node i; C i The importance of the load connected to the i-node; A i B represents the magnitude of the change in the demand response trigger signal event occurring at node i; i ω1, ω2, ω3, ω4 and ω5 are the weighting coefficients corresponding to each characteristic index; Q is the set of distribution network nodes with trigger signals.

3. The method for selecting the dominant demand response mode of a distribution network according to claim 1, characterized in that, The evaluation criteria for defining characteristic indicators based on the evaluation results, and the scoring of characteristic indicators according to the evaluation criteria, to obtain the characteristic indicator scoring results include: Based on the evaluation results, the characteristic indicators contained within the priority indicators are calculated, and the evaluation criteria for the characteristic indicators are defined based on the calculation results. The characteristic indicators are scored based on the evaluation criteria of the characteristic indicators to obtain the characteristic indicator score results, so as to achieve the standardization and unification of the characteristic indicators.

4. The method for selecting the dominant demand response mode of a distribution network according to claim 1, characterized in that, The process involves calculating the weighting coefficients of characteristic indicators based on comprehensive coefficients, and comparing and judging the comprehensive values ​​of distribution network operation trigger signals according to these weighting coefficients to obtain the distribution network operation events to be resolved, thereby clarifying the dominant demand response mode of the distribution network. The weight coefficients of the characteristic indicators are calculated based on the evaluation criteria and comprehensive coefficients of the characteristic indicators, and the comprehensive value of the trigger signal corresponding to the demand response trigger signal event is calculated. The comprehensive values ​​of the trigger signals are compared and judged, and the demand response trigger signal event corresponding to the largest comprehensive value of the trigger signal is selected as the distribution network operation event to be resolved under the preset time period, so as to clarify the dominant demand response mode of the distribution network.

5. The method for selecting the dominant demand response mode of a distribution network according to claim 4, characterized in that, The formula for calculating the weight coefficient of the feature index is as follows: In the formula, S i Z represents the comprehensive coefficient of the characteristic index. i The scope of influence of the demand response trigger signal event occurring at node i; T i The duration of the demand response trigger signal event occurring at node i; C i The importance of the load connected to the i-node; A i B represents the magnitude of the change in the demand response trigger signal event occurring at node i; i ω1, ω2, ω3, ω4 and ω5 are the weighting coefficients corresponding to each feature index.

6. A distribution network dominant demand response mode selection system, characterized in that, The system includes: The trigger signal judgment and event division module is used to acquire real-time operation monitoring data of the distribution network, obtain the operation status of the distribution network based on the predefined trigger condition criteria of the distribution network operation trigger signal, and generate the division result of the demand response trigger signal event according to the event demand judgment criteria of the distribution network operation status. The trigger signal priority evaluation module is used to calculate the priority index of various demand response trigger signal events, obtain the priority index evaluation value, and evaluate the priority of various demand response trigger signal events based on the priority index evaluation value. The priority indicator scoring calculation module is used to define the evaluation criteria for the characteristic indicators based on the evaluation results, score the characteristic indicators according to the evaluation criteria, obtain the characteristic indicator scoring results, and sum the characteristic indicator scoring results to obtain the comprehensive coefficient. The indicator weight coefficient calculation module is used to calculate the weight coefficient of the characteristic indicators based on the comprehensive coefficient, and compare and judge the comprehensive value of the distribution network operation trigger signal according to the weight coefficient to obtain the distribution network operation event to be resolved, so as to clarify the dominant demand response mode of the distribution network. The trigger signal judgment and event division module includes a trigger signal definition module, a trigger signal generation module, and a trigger signal event division module, wherein... The trigger signal definition module is used to acquire real-time operation monitoring data of the distribution network, extract data information of various demand response trigger signal events from the real-time operation monitoring data of the distribution network, and obtain the operation status of the distribution network according to the predefined trigger condition criteria of the distribution network operation trigger signal. The trigger signal generation module is used to define the judgment criteria for various demand response trigger signal events based on the data information of various demand response trigger signal events, and obtain the trigger signals corresponding to various demand response trigger signal events. The trigger signal event division module is used to generate a set of distribution network nodes based on trigger signals, and to divide the operating status of the distribution network based on the set of distribution network nodes; The demand response triggering signal events include voltage over-limit, network loss, grid frequency, line overload, and peak shaving and valley filling; The priority index includes characteristic indicators such as the scope of influence, duration, magnitude of change, cost of loss, and node access load.

7. The distribution network dominant demand response mode selection system according to claim 6, characterized in that, The formula for calculating the priority index of the demand response trigger signal event is as follows: G i =ω1Z i +ω2T i +ω3C i +ω4A i +ω5B i i∈Q; In the formula, G i Z is the priority indicator for demand response trigger signal events occurring at node i; i The scope of influence of the demand response trigger signal event occurring at node i; T i The duration of the demand response trigger signal event occurring at node i; C i The importance of the load connected to the i-node; A i B represents the magnitude of the change in the demand response trigger signal event occurring at node i; i ω1, ω2, ω3, ω4 and ω5 are the weighting coefficients corresponding to each characteristic index; Q is the set of distribution network nodes with trigger signals.

8. The distribution network dominant demand response mode selection system according to claim 6, characterized in that, The priority indicator scoring calculation module includes an evaluation criterion definition module and a feature indicator scoring module, wherein... The evaluation criteria definition module is used to calculate the characteristic indicators contained within the priority indicators based on the evaluation results, and to define the evaluation criteria for the characteristic indicators based on the calculation results of the characteristic indicators. The feature index scoring module is used to score feature indicators based on the evaluation criteria of feature indicators, and obtain feature index scoring results to achieve standardization and unification of feature indicators.

9. The distribution network dominant demand response mode selection system according to claim 6, characterized in that, The indicator weight coefficient calculation module includes a comprehensive value calculation module and a demand response mode definition module, wherein... The comprehensive value calculation module is used to calculate the weight coefficient of the characteristic indicators based on the evaluation criteria and comprehensive coefficient of the characteristic indicators, and to calculate the comprehensive value of the trigger signal corresponding to the demand response trigger signal event. The demand response mode identification module is used to compare and judge the comprehensive value of the trigger signals, select the demand response trigger signal event corresponding to the largest comprehensive value of the trigger signals as the distribution network operation event to be resolved under the preset time period, so as to identify the dominant demand response mode of the distribution network.

10. The distribution network dominant demand response mode selection system according to claim 9, characterized in that, The formula for calculating the weight coefficient of the feature index is as follows: In the formula, S i Z represents the comprehensive coefficient of the characteristic index. i The scope of influence of the demand response trigger signal event occurring at node i; T i The duration of the demand response trigger signal event occurring at node i; C i The importance of the load connected to the i-node; A i B represents the magnitude of the change in the demand response trigger signal event occurring at node i; i ω1, ω2, ω3, ω4 and ω5 are the weighting coefficients corresponding to each feature index.

11. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 5.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

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