Distributed new energy dynamic management and control method, system, equipment and medium

Abstract

The invention belongs to the field of power distribution network voltage control, and discloses a distributed new energy dynamic management and control method, system, device and medium, and the method comprises the steps: calculating a source load feature matching index value and a capacity matching index value based on the pre-obtained day-ahead and intra-day transformer area source load power and uncontrollable source load data, and determining the transformer area response priority; determining a regulation and control operation mode of each transformer area according to a transformer area response priority ranking result; correspondingly matching a resource time sequence response model of each transformer area based on the regulation and control operation mode, and calculating a resource time sequence response sequence of each transformer area by using the resource time sequence response model; calculating a voltage out-of-limit risk value of the transformer area based on the resource time sequence response sequence under different regulation and control operation modes; and according to the voltage out-of-limit risk index value, judging the voltage out-of-limit risk of the transformer area, and outputting a risk-free response result. According to the invention, by closely combining the transformer area source load characteristics with the power distribution system regulation and control requirements, the admitting ability of the power distribution network to new energy is improved.

Description

Technical Field

[0001] The present invention relates to the field of voltage control in distribution networks, and in particular to a method, system, equipment and medium for dynamic control of distributed new energy. Background Art

[0002] The penetration rate of renewable energy in distribution networks continues to increase, and its random volatility interacts with the uncertainty of power users' behavior, resulting in increasingly complex operating conditions of distribution networks. Traditional distribution networks are affected by "closed-loop design and open-loop operation", and their flexible regulation capabilities are difficult to adapt to the increasingly complex power supply and demand regulation needs of distribution networks. With the development of power electronics technology, a new form of flexible interconnection that realizes inter-grid power exchange and regulation capabilities has become a key solution to cope with the absorption of renewable energy.

[0003] At present, there have been some studies on the regulation of flexible interconnected distribution systems. Usually, centralized, distributed, and hierarchical control methods are used to solve the complex regulation of power grids in areas with a high proportion of new energy. However, there are various schemes between and within power grids in areas with a high proportion of new energy. The control variables and interest targets of different regions are coupled and intertwined. The existing methods have not yet fully considered the impact of the uncertainty of the above factors on the ability of resource mutual assistance. It is difficult to achieve coordination and cooperation between different stakeholders, and it is difficult to give full play to the coordination capacity of source and load resources. Summary of the invention

[0004] The embodiments of the present invention provide a distributed new energy dynamic control method, system, device and medium to solve the above-mentioned technical problems in the prior art.

[0005] In order to have a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended to be a general review, nor is it intended to identify key / important components or to delineate the scope of protection of these embodiments. Its only purpose is to present some concepts in a simple form as a preface to the detailed description that follows.

[0006] According to a first aspect of an embodiment of the present invention, a distributed new energy dynamic control method is provided.

[0007] In one embodiment, a distributed new energy dynamic management and control method includes:

[0008] Based on the pre-acquired day-ahead and day-intraday source-load power and uncontrollable source-load data, the source-load feature matching index value and capacity matching index value are calculated, and the similarity and autonomy of the substations are evaluated to determine the substation response priority;

[0009] According to the response priority ranking results of the substations, the control operation mode of each substation is determined; the resource timing response model of each substation is matched based on the control operation mode, and the resource timing response order of each substation is calculated using the resource timing response model;

[0010] Based on the resource timing response order under different control operation modes, combined with the pre-acquired daily voltage data of the substation, the substation voltage over-limit risk value is calculated; according to the voltage over-limit risk index value, the substation voltage over-limit risk is judged and the risk-free response result is output.

[0011] In one embodiment, the calculation of the source-load characteristic matching index value and the capacity matching index value based on the pre-acquired day-ahead and day-intraday source-load power and uncontrollable source-load data of the substation area, and the evaluation of the substation area similarity and autonomy capability, and the determination of the substation area response priority includes:

[0012] Obtain the source load power and uncontrollable source load data of the station area on the day before and within the day; calculate the source load characteristic matching index value and the capacity matching index value respectively through the source load characteristic matching index calculation formula and the capacity matching index calculation formula;

[0013] Based on the matching index value of the source-load characteristics of the substation, the matching situation of the source and load of the substation at different times is judged, and the similarity of the substation is analyzed;

[0014] According to the similarity results of different substations, adjacent substations are aggregated to obtain substation clusters;

[0015] Based on the capacity matching index value and cluster of the substation area, the self-consumption capacity of the source load in the substation area is judged, and the autonomous capacity of the substation area is analyzed;

[0016] According to the autonomous capability of the substation, the autonomous response priority of the substation is determined, and the autonomous response priority result of the substation is obtained.

[0017] In one embodiment, the source-load characteristic matching index calculation formula is:

[0018]

[0019] In the formula, λ i represents the source-load characteristic matching index value of the substation, m represents the number of substations in substation cluster i, P PVj,k represents the sum of the photovoltaic output of the ith area at the kth time, P Lj,k represents the sum of load power consumption of the ith area at the kth moment, and j represents the jth device in the ith area.

[0020] In one embodiment, the capacity matching index calculation formula is:

[0021]

[0022] Where η i represents the capacity matching index value of the ith cluster, P PVmax,i represents the sum of the maximum photovoltaic output of the ith cluster, T ESdIndicates the energy storage charging time, T ESc Indicates the discharge duration, P ESmax,i represents the sum of the maximum storage capacity of the cluster in the ith area, P Lmax,i It represents the sum of the maximum power consumption of all loads in the ith substation cluster.

[0023] In one embodiment, determining the control operation mode of each substation according to the substation response priority sorting result includes:

[0024] If the capacity matching index value η i ≤0.4, the substation control operation mode is the substation mutual assistance mode;

[0025] If the capacity matching index value is 0.4<η i ≤0.8, the control and operation mode of the substation is the substation priority autonomy and then mutual assistance mode;

[0026] If the capacity matching index value is 0.8<η i ≤1, the substation control operation mode is the substation autonomy mode.

[0027] In one embodiment, matching the resource timing response model of each area based on the control operation mode, and calculating the resource timing response order of each area using the resource timing response model includes:

[0028] If the substation control operation mode is the substation mutual assistance mode, the resource time series response model introduces a price-dominated game mechanism to balance multiple types of substations;

[0029] If the substation control operation mode is the substation priority autonomy and then mutual assistance mode, the resource timing response model is an adjustable model and an unadjustable model within the substation, and based on the consistency constraint conditions, different types of resource response orders are obtained;

[0030] If the substation control operation mode is the substation autonomous mode, the resource timing response model is the photovoltaic uncertain timing model and the load response uncertain timing model, and based on the substation's new energy acceptance capacity and voltage safety constraints, different types of resource response orders are obtained.

[0031] In one embodiment, the resource timing response model corresponding to the mutual assistance mode of the substation area is:

[0032] f1=maxF

[0033]

[0034]

[0035] In the formula, F represents the profit after the strategy of the cluster participating in the game is applied, S represents the cluster of substations participating in the game, Ω represents the power mutual assistance strategy of the substation cluster, Si represents the i-th cluster participating in the game, Ω i,k represents the kth strategy of the ith cluster, F i,k represents the benefit obtained by the i-th cluster using the k-th strategy, P i represents the power values ​​of the ith cluster, P a represents the power boundary value of the ith station cluster, u a represents the node voltage in the ith cluster, r i,a Indicates the power value provided by the i-th cluster, P j represents the power values ​​of the j-th cluster, P b represents the power boundary value of the j-th cluster, u b represents the node voltage in the jth substation cluster; t b,j represents the power value received by the jth cluster; G represents the multi-station game model, C ia represents the consistency constraint corresponding to the ith node a, C bj represents the consistency constraint corresponding to node b in area j, t b,j represents the power value provided by the j-th substation cluster, and f1 represents the objective function corresponding to control mode 1;

[0036] The resource timing response model corresponding to the area priority autonomy and mutual assistance mode is:

[0037] f2=min(P PV -P L -P ES )

[0038]

[0039] In the formula, u a represents the node voltage in the ith cluster, u b represents the node voltage in the jth cluster, P PV Indicates the photovoltaic output in the area, P L Indicates the power demand of the internal load in the substation, P ES Indicates the energy storage charging / discharging power in the station area, where charging is a positive value and discharging is a negative value, x i represents the power value of the ith station, x a represents the power boundary of the ith station, x j represents the power boundary of the jth station, x b represents the power boundary of the jth substation, and f2 represents the objective function corresponding to control mode 2;

[0040] The resource timing response model corresponding to the station area autonomy mode is:

[0041] f3=maxΣSPV,i ;

[0042]

[0043] P PV,i =S PVmax,i γ PV,i +δ PV,i,t ;

[0044] P L,i =P L,i +δ L,i,t ;

[0045] In the formula, S PV,i Represents photovoltaic access capacity; S PVmax,i represents the photovoltaic installed capacity of the ith cluster; γ PV,i represents the load type of the i-th area; δ PV,i Indicates the fluctuation deviation of photovoltaic output; δ L,i Indicates load power fluctuation deviation, P PV,i represents the active power output of the ith photovoltaic power station in the area, Q PV,i represents the i-th photovoltaic reactive power output in the substation, P L,i represents the power demand of the ith load in the substation, δ PV,i,t represents the ith photovoltaic active power deviation in the substation, δ L,i,t represents the active power deviation of the i-th load in the substation, and f3 represents the objective function corresponding to control mode 3.

[0046] In one embodiment, the voltage over-limit risk value calculation formula of the substation is:

[0047]

[0048] In the formula, Indicates the voltage over-limit risk index value of the substation area, Q PV represents the PV reactive power supply value of cluster i in the substation, Q L Represents the reactive power demand value of cluster i in the substation.

[0049] According to a second aspect of an embodiment of the present invention, a distributed new energy dynamic management and control system is provided.

[0050] In one embodiment, the distributed new energy dynamic management and control system includes:

[0051] The substation autonomous priority determination module is used to calculate the source-load characteristic matching index value and the capacity matching index value based on the pre-acquired day-ahead and intra-day substation source-load power and uncontrollable source-load data, and evaluate the substation similarity and autonomous capability to determine the substation response priority;

[0052] The module for determining the resource timing response of each substation is used to determine the control operation mode of each substation according to the result of the substation response priority sorting; the resource timing response model of each substation is matched based on the control operation mode, and the resource timing response order of each substation is calculated using the resource timing response model;

[0053] The substation dynamic management and control module is used to calculate the substation voltage over-limit risk value based on the resource timing response order under different control operation modes, combined with the pre-acquired substation daily voltage data; according to the voltage over-limit risk indicator value, the substation voltage over-limit risk is judged and a risk-free response result is output.

[0054] In one embodiment, the station autonomous priority determination module includes: a data acquisition and index calculation module, a similarity analysis module, a station cluster division module, an autonomous capability analysis module and a station autonomous priority acquisition module.

[0055] The data acquisition and index calculation module is used to obtain the source load power and uncontrollable source load data of the day-ahead and intra-day areas; the source load characteristic matching index value and the capacity matching index value are calculated respectively through the source load characteristic matching index calculation formula and the capacity matching index calculation formula;

[0056] The similarity analysis module is used to determine the matching situation of the source and load of the substation at different times based on the source-load characteristic matching index value of the substation, and analyze the similarity of the substation;

[0057] The substation cluster division module is used to aggregate adjacent substations according to the similarity results of different substations to obtain substation clusters;

[0058] The autonomous capacity analysis module is used to determine the self-consumption capacity of the source load in the substation based on the substation capacity matching index value and the substation cluster, and analyze the autonomous capacity of the substation;

[0059] The substation autonomous priority acquisition module is used to determine the substation autonomous response priority according to the substation autonomous capability and obtain the substation autonomous response priority result.

[0060] In one embodiment, the source-load characteristic matching index calculation formula is:

[0061]

[0062] In the formula, λ i represents the source-load characteristic matching index value of the substation, m represents the number of substations in substation cluster i, P PVj,k represents the sum of the photovoltaic output of the ith grid area at the kth time, P Lj,k represents the sum of load power consumption of the ith area at the kth moment, and j represents the jth device in the ith area.

[0063] In one embodiment, the capacity matching index calculation formula is:

[0064]

[0065] Where η i represents the capacity matching index value of the ith cluster, P PVmax,i represents the sum of the maximum photovoltaic output of the ith cluster, T ESd Indicates the energy storage charging time, T ESc Indicates the discharge duration, P ESmax,i represents the sum of the maximum storage capacity of the cluster in the ith area, P Lmax,i It represents the sum of the maximum power consumption of all loads in the ith substation cluster.

[0066] In one embodiment, determining the control operation mode of each substation according to the substation response priority sorting result includes:

[0067] If the capacity matching index value η i ≤0.4, the substation control operation mode is the substation mutual assistance mode;

[0068] If the capacity matching index value is 0.4<η i ≤0.8, the control and operation mode of the substation is the substation priority autonomy and then mutual assistance mode;

[0069] If the capacity matching index value is 0.8<η i ≤1, the substation control operation mode is the substation autonomy mode.

[0070] In one embodiment, matching the resource timing response model of each area based on the control operation mode, and calculating the resource timing response order of each area using the resource timing response model includes:

[0071] If the substation control operation mode is the substation mutual assistance mode, the resource time series response model introduces a price-dominated game mechanism to balance multiple types of substations;

[0072] If the substation control operation mode is the substation priority autonomy and then mutual assistance mode, the resource timing response model is an adjustable model and an unadjustable model within the substation, and based on the consistency constraint conditions, different types of resource response orders are obtained;

[0073] If the substation control operation mode is the substation autonomous mode, the resource timing response model is the photovoltaic uncertain timing model and the load response uncertain timing model, and based on the substation's new energy acceptance capacity and voltage safety constraints, different types of resource response orders are obtained.

[0074] According to a third aspect of an embodiment of the present invention, a computer device is provided.

[0075] In some embodiments, the computer device includes 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.

[0076] According to a fourth aspect of embodiments of the present invention, a computer-readable storage medium is provided.

[0077] In one embodiment, the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0078] The technical solution provided by the embodiment of the present invention may have the following beneficial effects:

[0079] The present invention closely combines the source-load characteristic matching index of the substation area with the control demand of the distribution system, selects different control operation modes according to different source-load characteristic index values, integrates various control schemes between and within substations, reduces the degree of mutual coupling between regional control variables and interest targets, ensures that the distribution system's ability to accept new energy is maximized, and reduces network losses caused by power interaction; the proposed substation autonomous capacity differentiation evaluation method can automatically update the substation operation boundary according to the substation's own operating status, fully explore the substation's multi-type resource control potential within an acceptable range, realizes accurate evaluation of controllable resources, and helps to improve the implementation efficiency of distribution substation resource management; the proposed The proposed distribution station area mode selection method solves the interest conflicts between different stations and the diversity of user demand within the station area through the mutual assistance strategy game of station area clusters, and balances the impact of random distribution of high-proportion distributed renewable energy through multi-resource regulation, which significantly improves the distribution system's acceptance level of distributed renewable energy, reduces the impact of source-load uncertainty on the regulation of flexible interconnected stations, and improves the multi-resource flexibility of flexible interconnected stations; only the power and voltage information of the station area needs to be collected to evaluate the station's response capability, and the computing workload is not greatly increased, which improves the matching performance of resources between stations and within the station area, ensures the safe operation needs of the distribution station area, and improves the distribution network's acceptance of renewable energy.

[0080] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0082] Figure 1 is a flow chart of a distributed new energy dynamic control method according to an exemplary embodiment;

[0083] Figure 2is a structural block diagram of a distributed new energy dynamic management and control system according to an exemplary embodiment;

[0084] Figure 3 The figure is a schematic diagram showing the structure of a computer device according to an exemplary embodiment.

[0085] Figure 4 It is a control flow chart of improving the consumption of new energy in a flexible interconnected power distribution system in a substation according to an exemplary embodiment;

[0086] Figure 5 A flexible interconnected power distribution system architecture with multiple stakeholders is shown according to an exemplary embodiment;

[0087] Figure 6 A control architecture of a flexible interconnected power distribution system in a substation is shown according to an exemplary embodiment;

[0088] Figure 7 is a flow chart of selecting a substation control operation mode according to an exemplary embodiment;

[0089] Figure 8 It is a flow chart of a management and control algorithm for improving the new energy consumption of a flexible interconnected distribution system in an area according to an exemplary embodiment. DETAILED DESCRIPTION

[0090] The following description and accompanying drawings fully illustrate the specific embodiments of this article so that those skilled in the art can practice them. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. The scope of the embodiments of this article includes the entire scope of the claims, as well as all available equivalents of the claims. Herein, the terms "first", "second", etc. are only used to distinguish one element from another, without requiring or implying any actual relationship or order between these elements. In fact, the first element can also be called the second element, and vice versa. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that the structure, device or equipment including a series of elements includes not only those elements, but also other elements that are not explicitly listed, or also include elements inherent to such structure, device or equipment. In the absence of more restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the structure, device or equipment including the elements. Each embodiment is described in a progressive manner herein, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the embodiments can be referred to each other.

[0091] The terms "longitudinal", "lateral", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc. in this document indicate the orientation or position relationship based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing this document and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In the description of this document, unless otherwise specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a mechanical connection or an electrical connection, it can also be the internal communication of two elements, it can be a direct connection, or it can be an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0092] As used herein, the term "plurality" means two or more than two, unless otherwise specified.

[0093] In this document, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B means: A or B.

[0094] In this article, the term "and / or" is a description of the association relationship between objects, indicating that three relationships may exist. For example, A and / or B means: A or B, or, A and B.

[0095] It should be understood that, although the various steps in the flow chart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the figure may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0096] Each module in the device or system of the present application can be implemented in whole or in part by software, hardware, or a combination thereof. The above modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to the above modules.

[0097] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0098] Figure 1An embodiment of a distributed new energy dynamic control method of the present invention is shown.

[0099] In this optional embodiment, the distributed new energy dynamic management and control method includes:

[0100] Step S101, based on the pre-acquired day-ahead and day-intraday source-load power and uncontrollable source-load data, calculate the source-load characteristic matching index value and the capacity matching index value, evaluate the similarity and autonomy of the substations, and determine the substation response priority;

[0101] Step S103, determining the control operation mode of each substation according to the response priority ranking result of the substation; matching the resource timing response model of each substation based on the control operation mode, and calculating the resource timing response order of each substation using the resource timing response model;

[0102] Step S105, based on the resource timing response order under different control operation modes, combined with the pre-acquired daily voltage data of the substation, calculate the substation voltage over-limit risk value; according to the voltage over-limit risk indicator value, judge the substation voltage over-limit risk, and output a risk-free response result.

[0103] In this optional embodiment, the calculation of the source-load characteristic matching index value and the capacity matching index value based on the pre-acquired day-ahead and day-intraday area source-load power and uncontrollable source-load data, and the evaluation of the area similarity and autonomy capability, and the determination of the area response priority include:

[0104] Obtain the source load power and uncontrollable source load data of the station area on the day before and within the day; calculate the source load characteristic matching index value and the capacity matching index value respectively through the source load characteristic matching index calculation formula and the capacity matching index calculation formula;

[0105] Based on the matching index value of the source-load characteristics of the substation, the matching situation of the source and load of the substation at different times is judged, and the similarity of the substation is analyzed;

[0106] According to the similarity results of different substations, adjacent substations are aggregated to obtain substation clusters;

[0107] Based on the capacity matching index value and cluster of the substation area, the self-consumption capacity of the source load in the substation area is judged, and the autonomous capacity of the substation area is analyzed;

[0108] According to the autonomous capability of the substation, the autonomous response priority of the substation is determined, and the autonomous response priority result of the substation is obtained.

[0109] In this optional embodiment, the source-load characteristic matching index calculation formula is:

[0110]

[0111] In the formula, λi represents the source-load characteristic matching index value of the substation, m represents the number of substations in substation cluster i, P PVj,k represents the sum of the photovoltaic output of the ith area at the kth time, P Lj,k represents the sum of load power consumption of the ith area at the kth moment, and j represents the jth device in the ith area.

[0112] In this optional embodiment, the capacity matching index calculation formula is:

[0113]

[0114] Where η i represents the capacity matching index value of the ith cluster, P PVmax,i represents the sum of the maximum photovoltaic output of the ith cluster, T ESd Indicates the energy storage charging time, T ESc Indicates the discharge duration, P ESmax,i represents the sum of the maximum storage capacity of the cluster in the ith area, P Lmax,i It represents the sum of the maximum power consumption of all loads in the ith substation cluster.

[0115] In this optional embodiment, determining the control operation mode of each substation according to the substation response priority sorting result includes:

[0116] If the capacity matching index value η i ≤0.4, the substation control operation mode is the substation mutual assistance mode;

[0117] If the capacity matching index value is 0.4<η i ≤0.8, the control and operation mode of the substation is the substation priority autonomy and then mutual assistance mode;

[0118] If the capacity matching index value is 0.8<η i ≤1, the substation control operation mode is the substation autonomy mode.

[0119] In this optional embodiment, matching the resource timing response model of each substation based on the control operation mode, and calculating the resource timing response order of each substation using the resource timing response model includes:

[0120] If the substation control operation mode is the substation mutual assistance mode, the resource time series response model introduces a price-dominated game mechanism to balance multiple types of substations;

[0121] If the substation control operation mode is the substation priority autonomy and then mutual assistance mode, the resource timing response model is an adjustable model and an unadjustable model within the substation, and based on the consistency constraint conditions, different types of resource response orders are obtained;

[0122] If the substation control operation mode is the substation autonomous mode, the resource timing response model is the photovoltaic uncertain timing model and the load response uncertain timing model, and based on the substation's new energy acceptance capacity and voltage safety constraints, different types of resource response orders are obtained.

[0123] In this optional embodiment, the resource timing response model corresponding to the station area mutual assistance mode is:

[0124] f1=maxF

[0125]

[0126]

[0127] In the formula, F represents the profit after the strategy of the cluster participating in the game is applied, S represents the cluster of substations participating in the game, Ω represents the power mutual assistance strategy of the substation cluster, S i represents the i-th cluster participating in the game, Ω i,k represents the kth strategy of the ith cluster, F i,k represents the benefit obtained by the i-th cluster using the k-th strategy, P i represents the power values ​​of the ith cluster, P a represents the power boundary value of the ith cluster, u a represents the node voltage in the ith cluster, r i,a Indicates the power value provided by the i-th cluster, P j represents the power values ​​of the j-th cluster, P b represents the power boundary value of the j-th cluster, u b represents the node voltage in the jth substation cluster; t b,j represents the power value received by the jth cluster; G represents the multi-station game model, C ia represents the consistency constraint corresponding to the ith node a, C bj represents the consistency constraint corresponding to node b in area j, t b,j represents the power value provided by the j-th substation cluster, and f1 represents the objective function corresponding to control mode 1;

[0128] The resource timing response model corresponding to the area priority autonomy and mutual assistance mode is:

[0129] f2=min(P PV -P L -P ES )

[0130]

[0131] In the formula, u a represents the node voltage in the ith cluster, ub represents the node voltage in the jth cluster, P PV Indicates the photovoltaic output in the area, P L Indicates the power demand of the internal load in the substation, P ES Indicates the energy storage charging / discharging power in the station area, where charging is a positive value and discharging is a negative value, x i represents the power value of the ith station, x a represents the power boundary of the ith station, x j represents the power boundary of the jth station, x b represents the power boundary of the jth substation, and f2 represents the objective function corresponding to control mode 2;

[0132] The resource timing response model corresponding to the station area autonomy mode is:

[0133] f3=maxΣS PV,i ;

[0134]

[0135] P PV,i =S PVmax,i γ PV,i +δ PV,i,t ;

[0136] P L,i =P L,i +δ L,i,t ;

[0137] In the formula, S PV,i Represents photovoltaic access capacity; S PVmax,i represents the photovoltaic installed capacity of the ith cluster; γ PV,i represents the load type of the i-th area; δ PV,i Represents the fluctuation deviation of photovoltaic output, which obeys the normal distribution; δ L,i It represents the load power fluctuation deviation, which obeys the normal distribution, P PV,i represents the active output of the ith photovoltaic power station in the area, Q PV,i represents the i-th photovoltaic reactive power output in the substation, P L,i represents the power demand of the i-th load in the substation, δ PV,i,t represents the ith photovoltaic active power deviation in the substation, δ L,i,t represents the active power deviation of the i-th load in the substation, and f3 represents the objective function corresponding to control mode 3.

[0138] In this optional embodiment, the calculation formula of the voltage over-limit risk value of the substation is:

[0139]

[0140] In the formula, Indicates the voltage over-limit risk index value of the substation area, Q PV represents the PV reactive power supply value of cluster i in the substation, Q L represents the reactive power demand value of the cluster i in the substation area. The greater the risk index value of the substation voltage exceeding the limit, the more reactive power balance can be achieved in the substation cluster. It is necessary to reduce the substation cluster boundary restrictions, recalculate the response order, and recalculate the substation voltage over-limit risk index.

[0141] Figure 2 An embodiment of a distributed new energy dynamic control system of the present invention is shown.

[0142] In this optional embodiment, the distributed new energy dynamic management and control system includes:

[0143] The substation autonomous priority determination module 201 is used to calculate the source-load characteristic matching index value and the capacity matching index value based on the pre-acquired substation source-load power and uncontrollable source-load data before and during the day, and evaluate the substation similarity and autonomous capability to determine the substation response priority;

[0144] The substation resource timing response determination module 203 is used to determine the control operation mode of each substation according to the substation response priority sorting result; match the resource timing response model of each substation based on the control operation mode, and calculate the resource timing response order of each substation using the resource timing response model;

[0145] The substation dynamic management and control module 205 is used to calculate the substation voltage over-limit risk value based on the resource timing response order under different control operation modes, combined with the pre-acquired substation daily voltage data; according to the voltage over-limit risk indicator value, the substation voltage over-limit risk is judged and a risk-free response result is output.

[0146] In this optional embodiment, the station area autonomous priority determination module includes: a data acquisition and index calculation module, a similarity analysis module, a station area cluster division module, an autonomous capability analysis module and a station area autonomous priority acquisition module

[0147] The data acquisition and index calculation module is used to obtain the source load power and uncontrollable source load data of the day-ahead and intra-day areas; the source load characteristic matching index value and the capacity matching index value are calculated respectively through the source load characteristic matching index calculation formula and the capacity matching index calculation formula;

[0148] The similarity analysis module is used to determine the matching situation of the source and load of the substation at different times based on the source-load characteristic matching index value of the substation, and analyze the similarity of the substation;

[0149] The substation cluster division module is used to aggregate adjacent substations according to the similarity results of different substations to obtain substation clusters;

[0150] The autonomous capacity analysis module is used to determine the self-consumption capacity of the source load in the substation based on the substation capacity matching index value and the substation cluster, and analyze the autonomous capacity of the substation;

[0151] The substation autonomous priority acquisition module is used to determine the substation autonomous response priority according to the substation autonomous capability and obtain the substation autonomous response priority result.

[0152] In this optional embodiment, the source-load characteristic matching index calculation formula is:

[0153]

[0154] In the formula, λ i represents the source-load characteristic matching index value of the substation, m represents the number of substations in substation cluster i, P PVj,k represents the sum of the photovoltaic output of the ith grid area at the kth time, P Lj,k represents the sum of load power consumption of the ith area at the kth moment, and j represents the jth device in the ith area.

[0155] In this optional embodiment, the capacity matching index calculation formula is:

[0156]

[0157] Where η i represents the capacity matching index value of the ith cluster, P PVmax,i represents the sum of the maximum photovoltaic output of the ith cluster, T ESd Indicates the energy storage charging time, T ESc Indicates the discharge duration, P ESmax,i represents the sum of the maximum storage capacity of the cluster in the ith area, P Lmax,i It represents the sum of the maximum power consumption of all loads in the ith substation cluster.

[0158] In this optional embodiment, determining the control operation mode of each substation according to the substation response priority sorting result includes:

[0159] If the capacity matching index value η i ≤0.4, the substation control operation mode is the substation mutual assistance mode;

[0160] If the capacity matching index value is 0.4<η i ≤0.8, the control and operation mode of the substation is the substation priority autonomy and then mutual assistance mode;

[0161] If the capacity matching index value is 0.8<η i ≤1, the substation control operation mode is the substation autonomy mode.

[0162] In this optional embodiment, matching the resource timing response model of each substation based on the control operation mode, and calculating the resource timing response order of each substation using the resource timing response model includes:

[0163] If the substation control operation mode is the substation mutual assistance mode, the resource time series response model introduces a price-dominated game mechanism to balance multiple types of substations;

[0164] If the substation control operation mode is the substation priority autonomy and then mutual assistance mode, the resource timing response model is an adjustable model and an unadjustable model within the substation, and based on the consistency constraint conditions, different types of resource response orders are obtained;

[0165] If the substation control operation mode is the substation autonomous mode, the resource timing response model is the photovoltaic uncertain timing model and the load response uncertain timing model, and based on the substation's new energy acceptance capacity and voltage safety constraints, different types of resource response orders are obtained.

[0166] It should be supplemented that, the present invention, for the flexible interconnected distribution system of substations, constructs substation source-load characteristic matching indicators and capacity matching indicators, determines the power mutual assistance of substations and the priority of autonomy within the substations; comprehensively considers the above-mentioned substation matching indicators, clarifies the transmission power between substations, combines the response characteristics of different types of resources, calculates the adjustable capacity under different operating modes within each substation, and determines the regulation and control operation mode of each substation; based on the resource timing response model under different regulation and control operation modes, and according to the fluctuation of new energy output and switching uncertainty, reserves the real-time power adjustment space of the interconnection line, reduces the risk of uncertainty factors to the safe operation of the distribution network through the substation voltage over-limit risk indicator, and realizes the improvement of the new energy absorption capacity of the distribution network.

[0167] The operating status of the substation in the present invention is affected by multiple factors such as photovoltaic output characteristics and user electricity consumption behavior. In order to clarify the source-load characteristic indicators of the substation and the interaction between the substations, this embodiment records the daily source and load status information of the substation at a frequency of 1 hour / time; because the voltage change is shorter than the capacity matching adjustment time scale, in order to track the substation voltage changes in a timely manner, this embodiment needs to collect the substation voltage information with a high proportion of random source and load access at a frequency of 15 minutes / time.

[0168] It should be noted that the source-load characteristic matching index is based on the obtained daily substation source load power and uncontrollable source load data to judge the matching situation of the source and load in the substation in different time sections, which is used to describe the substation mutual assistance capacity; if the source-load characteristic matching index value is closer to 1, the source-load characteristic matching index value is larger, the source-load curve is closer, the matching ability of the source and load is stronger, and the similarity of the source-load curve is higher; the capacity matching index value is based on the obtained daily substation source load power and uncontrollable source load data to judge the self-absorption capacity of the source load in the substation; if the capacity matching index value is larger, the substation’s internal self-absorption capacity is stronger, the autonomy is stronger, and the substation’s autonomy priority is higher.

[0169] The control operation mode of the substation is divided into three cases based on the results of the substation autonomous response priority, and each case satisfies the consistency constraint; when the substation autonomous response priority is the lowest, that is, the substation autonomous response priority is a1, the substation selects substation control operation mode 1, that is, the substation mutual assistance mode. Under this substation mutual assistance mode, the substation clusters are allocated power between clusters with the goal of maximizing the consumption of new energy and maximizing the benefits of each cluster. Except for the uncontrollable data obtained by the substation, all other sources and loads participate in the control; when the substation autonomous response priority is medium, that is, The substation's autonomous response priority is a2, the substation selects substation regulation mode 2, the substation selects the substation priority autonomy followed by mutual assistance mode, priority autonomy followed by mutual assistance, under this substation priority autonomy, the substation conducts substation autonomy with the goal of maximizing new energy consumption, and only sources and loads that do not participate in the substation content volume matching participate in regulation; when the substation's autonomous response priority is the highest, that is, the substation's autonomous response priority is a3, the substation selects substation regulation mode 3, the substation selects the substation autonomy mode, under which the substation only conducts local autonomy and does not participate in inter-substation regulation.

[0170] The resource timing response model is divided according to the substation regulation and operation mode; when the substation chooses the substation mutual assistance mode, the resource timing response model introduces a price-dominated game mechanism to balance the interests of multiple types of substations; when the substation chooses the substation priority autonomy and then mutual assistance mode, the resource timing response model includes adjustable models and non-adjustable models within the substation, and uses consistency conditions as constraints to obtain the response order of different types of resources; when the substation chooses the substation autonomy mode, the resource timing response model includes photovoltaic uncertain timing model and load response uncertain timing model, and takes the maximum substation new energy acceptance capacity as the goal, and takes voltage not exceeding the limit as a safety constraint to obtain the response order of different types of resources.

[0171] The substation voltage over-limit risk value takes 20%-40% of the photovoltaic output as the reactive power compensation capacity. The larger the voltage over-limit risk index value, the more the substation reactive power can meet the local balance and reduce the reactive power transfer between substations, thereby reducing the substation cluster voltage over-limit risk. At the same time, it can conduct risk assessment on the resource response results to ensure that under the premise of maximizing the new energy absorption capacity, the reactive power transfer between substations is reduced as much as possible, thereby reducing the cluster substation voltage over-limit risk.

[0172] It should be noted that the source-load characteristic matching indicators of different substations can be compared to analyze the source-load matching situation of different substations throughout the day; when the source-load characteristic matching values ​​of adjacent substations are similar and interconnected, they are divided into the same substation cluster, and then the substation cluster is divided into response priorities according to the capacity matching indicators.

[0173] like Figure 5 As shown in the figure, when the substations with similar source-load matching characteristics are aggregated, clusters of substations with similar source-load characteristics can be obtained. The aggregation feasible domain of similar substation clusters is calculated as:

[0174]

[0175] Where P agg is the aggregate power boundary, P (i) is the adjustable power boundary of the ith cluster, p j is the power boundary of the jth substation in the i-th substation cluster.

[0176] For example, the present invention provides a distributed new energy dynamic control method application including: obtaining real-time vehicle information such as the initial charging capacity and expected charging time of electric vehicles connected to the distribution network; constructing graded quantitative indicators of response speed and response capacity of different electric vehicles based on the obtained user battery capacity, expected charging time and other information; calculating the comprehensive voltage regulation capacity of electric vehicles of different types and with different initial charging capacities based on the graded combination results of response speed and response capacity; aggregating the obtained voltage regulation capabilities of each electric vehicle to obtain an electric vehicle cluster with similar comprehensive voltage regulation capabilities; characterizing the adjustable capacity boundary of the electric vehicle cluster to obtain a voltage regulation feasible domain based on the obtained single electric vehicle regulation capabilities within the cluster; establishing a mapping relationship between the voltage change amount and the cluster voltage regulation amount based on the effect of different cluster voltage regulation feasible domains on the distribution network voltage regulation, and constructing a voltage regulation criterion to realize voltage adaptive regulation.

[0177] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 3As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store static information and dynamic information data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the steps in the above method embodiment are implemented.

[0178] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0179] In addition, the present invention also provides a computer device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiment when executing the computer program.

[0180] In addition, the present invention further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in the above method embodiment are implemented.

[0181] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present 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 memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0182] The present invention is not limited to the structures which have been described above and shown in the drawings, and various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A distributed new energy dynamic control method, characterized in that: The distributed new energy dynamic control method includes: Based on the pre-acquired day-ahead and day-intraday source-load power and uncontrollable source-load data, the source-load feature matching index value and capacity matching index value are calculated, and the similarity and autonomy of the substations are evaluated to determine the substation response priority; According to the response priority ranking results of the substations, the control operation mode of each substation is determined; the resource timing response model of each substation is matched based on the control operation mode, and the resource timing response order of each substation is calculated using the resource timing response model; Based on the resource timing response order under different control operation modes, combined with the pre-acquired daily voltage data of the substation, the substation voltage over-limit risk value is calculated; according to the voltage over-limit risk index value, the substation voltage over-limit risk is judged and the risk-free response result is output.

2. The distributed new energy dynamic control method according to claim 1 is characterized in that: The calculation of the source-load characteristic matching index value and the capacity matching index value based on the pre-acquired day-ahead and day-intraday source-load power and uncontrollable source-load data of the substation area, and the evaluation of the substation area similarity and autonomy capability, and the determination of the substation area response priority include: Obtain the source load power and uncontrollable source load data of the station area on the day before and within the day; calculate the source load characteristic matching index value and the capacity matching index value respectively through the source load characteristic matching index calculation formula and the capacity matching index calculation formula; Based on the matching index value of the source-load characteristics of the substation, the matching situation of the source and load of the substation at different times is judged, and the similarity of the substation is analyzed; According to the similarity results of different substations, adjacent substations are aggregated to obtain substation clusters; Based on the capacity matching index value and cluster of the substation area, the self-consumption capacity of the source load in the substation area is judged, and the autonomous capacity of the substation area is analyzed; According to the autonomous capability of the substation, the autonomous response priority of the substation is determined, and the autonomous response priority result of the substation is obtained.

3. The distributed new energy dynamic control method according to claim 2 is characterized in that: The source-load characteristic matching index calculation formula is: In the formula, λ i represents the source-load characteristic matching index value of the substation, m represents the number of substations in substation cluster i, P PVj,k represents the sum of the photovoltaic output of the ith grid area at the kth time, P Lj,k represents the sum of load power consumption of the ith area at the kth moment, and j represents the jth device in the ith area.

4. The distributed new energy dynamic control method according to claim 2 is characterized in that: The capacity matching index calculation formula is: Where η i represents the capacity matching index value of the ith cluster, P PVmax,i represents the sum of the maximum photovoltaic output of the ith cluster, T ESd Indicates the energy storage charging time, T ESc Indicates the discharge duration, P ESmax,i represents the sum of the maximum storage capacity of the cluster in the ith area, P Lmax,i It represents the sum of the maximum power consumption of all loads in the ith substation cluster.

5. The distributed new energy dynamic control method according to claim 1 is characterized in that: Determining the control operation mode of each substation according to the substation response priority sorting result includes: If the capacity matching index value η i ≤0.4, the substation control operation mode is the substation mutual assistance mode; If the capacity matching index value is 0.4<η i ≤0.8, the control and operation mode of the substation is the substation priority autonomy and then mutual assistance mode; If the capacity matching index value is 0.8<η i ≤1, the substation control operation mode is the substation autonomy mode.

6. The distributed new energy dynamic control method according to claim 5 is characterized in that: The resource timing response model of each substation is matched based on the control operation mode, and the resource timing response order of each substation is calculated by using the resource timing response model, including: If the substation control operation mode is the substation mutual assistance mode, the resource time series response model introduces a price-dominated game mechanism to balance multiple types of substations; If the substation control operation mode is the substation priority autonomy and then mutual assistance mode, the resource timing response model is an adjustable model and an unadjustable model within the substation, and based on the consistency constraint conditions, different types of resource response orders are obtained; If the substation control operation mode is the substation autonomous mode, the resource timing response model is the photovoltaic uncertain timing model and the load response uncertain timing model, and based on the substation's new energy acceptance capacity and voltage safety constraints, different types of resource response orders are obtained.

7. The distributed new energy dynamic control method according to claim 6 is characterized in that: The resource timing response model corresponding to the mutual assistance mode of the substation area is: f1=maxF In the formula, F represents the profit after the strategy of the cluster participating in the game is applied, S represents the cluster of substations participating in the game, Ω represents the power mutual assistance strategy of the substation cluster, S i represents the i-th cluster participating in the game, Ω i,k represents the kth strategy of the ith cluster, F i,k represents the benefit obtained by the i-th cluster using the k-th strategy, P i represents the power values ​​of the ith cluster, P a represents the power boundary value of the ith cluster, u a represents the node voltage in the cluster of the ith substation, r i,a Indicates the power value provided by the i-th cluster, P j represents the power values ​​of the j-th cluster, P b represents the power boundary value of the j-th cluster, u b represents the node voltage in the jth substation cluster; t b,j represents the power value received by the jth cluster; G represents the multi-station game model, C ia represents the consistency constraint corresponding to the ith node a, C bj represents the consistency constraint corresponding to node b in area j, t b,j represents the power value provided by the j-th substation cluster, and f1 represents the objective function corresponding to control mode 1; The resource timing response model corresponding to the area priority autonomy and mutual assistance mode is: f2=min(P PV -P L -P ES ) In the formula, u a represents the node voltage in the ith cluster, u b represents the node voltage in the jth cluster, P PV Indicates the photovoltaic output in the area, P L Indicates the internal load power demand of the substation, P ES Indicates the energy storage charging / discharging power in the station area, where charging is a positive value and discharging is a negative value, x i represents the power value of the ith station, x a represents the power boundary of the ith station, x j represents the power boundary of the jth station, x b represents the power boundary of the jth substation, and f2 represents the objective function corresponding to control mode 2; The resource timing response model corresponding to the station area autonomy mode is: f3=maxΣS PV,i ; P PV,i =S PVmax,i c PV,i +d PV,i,t ; P L,i =P L,i +d L,i,t ; In the formula, S PV,i Represents photovoltaic access capacity; S PVmax,i represents the photovoltaic installed capacity of the ith cluster; γ PV,i represents the load type of the i-th area; δ PV,i Indicates the fluctuation deviation of photovoltaic output; δ L,i Indicates load power fluctuation deviation, P PV,i represents the active power output of the ith photovoltaic power station in the area, Q PV,i represents the i-th photovoltaic reactive power output in the substation, P L,i represents the power demand of the ith load in the substation, δ PV,i,t represents the ith photovoltaic active power deviation in the substation, δ L,i,t represents the active power deviation of the i-th load in the substation, and f3 represents the objective function corresponding to control mode 3.

8. The distributed new energy dynamic control method according to claim 1 is characterized in that: The calculation formula of the voltage over-limit risk value of the substation area is: In the formula, Indicates the voltage over-limit risk index value of the substation area, Q PV represents the PV reactive power supply value of cluster i in the substation, Q L Represents the reactive power demand value of cluster i in the substation.

9. A distributed new energy dynamic management and control system, characterized in that: The distributed new energy dynamic management and control system includes: The substation autonomous priority determination module is used to calculate the source-load characteristic matching index value and the capacity matching index value based on the pre-acquired day-ahead and intra-day substation source-load power and uncontrollable source-load data, and evaluate the substation similarity and autonomous capability to determine the substation response priority; The module for determining the resource timing response of each substation is used to determine the control operation mode of each substation according to the result of the substation response priority sorting; the resource timing response model of each substation is matched based on the control operation mode, and the resource timing response order of each substation is calculated using the resource timing response model; The substation dynamic management and control module is used to calculate the substation voltage over-limit risk value based on the resource timing response order under different control operation modes, combined with the pre-acquired substation daily voltage data; according to the voltage over-limit risk indicator value, the substation voltage over-limit risk is judged and a risk-free response result is output.

10. The distributed new energy dynamic management and control system according to claim 9 is characterized in that: The station area autonomy priority determination module includes: a data acquisition and index calculation module, a similarity analysis module, a station area cluster division module, an autonomy capability analysis module and a station area autonomy priority acquisition module The data acquisition and index calculation module is used to obtain the source load power and uncontrollable source load data of the day-ahead and intra-day areas; the source load characteristic matching index value and the capacity matching index value are calculated respectively through the source load characteristic matching index calculation formula and the capacity matching index calculation formula; The similarity analysis module is used to determine the matching situation of the source and load of the substation at different times based on the source-load characteristic matching index value of the substation, and analyze the similarity of the substation; The substation cluster division module is used to aggregate adjacent substations according to the similarity results of different substations to obtain substation clusters; The autonomous capacity analysis module is used to determine the self-consumption capacity of the source load in the substation based on the substation capacity matching index value and the substation cluster, and analyze the autonomous capacity of the substation; The substation autonomous priority acquisition module is used to determine the substation autonomous response priority according to the substation autonomous capability and obtain the substation autonomous response priority result.

11. The distributed new energy dynamic management and control system according to claim 10, characterized in that: The source-load characteristic matching index calculation formula is: In the formula, λ i represents the source-load characteristic matching index value of the substation, m represents the number of substations in substation cluster i, P PVj,k represents the sum of the photovoltaic output of the ith grid area at the kth time, P Lj,k represents the sum of load power consumption of the ith area at the kth moment, and j represents the jth device in the ith area.

12. The distributed new energy dynamic management and control system according to claim 10, characterized in that: The capacity matching index calculation formula is: Where η i represents the capacity matching index value of the ith cluster, P PVmax,i represents the sum of the maximum photovoltaic output of the ith cluster, T ESd Indicates the energy storage charging time, T ESc Indicates the discharge duration, P ESmax,i represents the sum of the maximum storage capacity of the cluster in the ith area, P Lmax,i It represents the sum of the maximum power consumption of all loads in the ith substation cluster.

13. The distributed new energy dynamic management and control system according to claim 9 is characterized in that: Determining the control operation mode of each substation according to the substation response priority sorting result includes: If the capacity matching index value η i ≤0.4, the substation control operation mode is the substation mutual assistance mode; If the capacity matching index value is 0.4<η i ≤0.8, the control and operation mode of the substation is the substation priority autonomy and then mutual assistance mode; If the capacity matching index value is 0.8<η i ≤1, the substation control operation mode is the substation autonomy mode.

14. The distributed new energy dynamic management and control system according to claim 9, characterized in that: The resource timing response model of each substation is matched based on the control operation mode, and the resource timing response order of each substation is calculated by using the resource timing response model, including: If the substation control operation mode is the substation mutual assistance mode, the resource time series response model introduces a price-dominated game mechanism to balance multiple types of substations; If the substation control operation mode is the substation priority autonomy and then mutual assistance mode, the resource timing response model is an adjustable model and an unadjustable model within the substation, and based on the consistency constraint conditions, different types of resource response orders are obtained; If the substation control operation mode is the substation autonomous mode, the resource timing response model is the photovoltaic uncertain timing model and the load response uncertain timing model, and based on the substation's new energy acceptance capacity and voltage safety constraints, different types of resource response orders are obtained.

15. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

16. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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