Multi-objective optimization scheduling method and system for post-disaster recovery of power grid

Abstract

The invention provides a multi-objective optimization scheduling method and system for power grid post-disaster recovery, and relates to the technical field of power grid optimization scheduling. According to a scanning result and the load responsivity of a power distribution unit in a scheduling instruction, the scheduling load constraint amount of a power distribution load of a power grid energy consumption side is marked; determining a cooperative scheduling index of a power grid energy consumption side when the power grid recovers after the disaster; on the basis of the load disturbance information and the load recovery efficiency of a power grid line after the power distribution network is damaged by various levels of disasters, verifying power balance constraints corresponding to load nodes of a plurality of sites during post-disaster recovery of the power grid to obtain a power utilization verification sequence; and controlling the automatic scheduling sequence of the power grid energy consumption side when the power grid recovers after the disaster based on the cooperative scheduling index and the power consumption verification sequence, and carrying out load optimization on the power grid energy consumption side. According to the invention, each load node can be accurately scanned in the post-disaster recovery process of the large-scale power grid, so that the recovery efficiency is improved, and the recovery time delay is reduced to ensure the stability of the power grid.

Description

Technical Field

[0001] The present application relates to the technical field of power grid optimization and dispatching, and more specifically, to a multi-objective optimization and dispatching method and system for post-disaster power grid recovery. Background Art

[0002] Grid optimization and dispatching refers to the rational allocation of power resources in the grid through optimization algorithms and dispatching strategies during grid operation or post-disaster recovery to maximize power supply stability, economy, reliability and environmental benefits. In the context of post-disaster recovery of the grid, optimization and dispatching are particularly important, which involves comprehensive dispatching of power supply and load distribution in the grid based on multiple objectives such as load demand, equipment status, recovery capability and priority of each node in the grid.

[0003] However, the existing multi-objective optimization scheduling method for post-disaster power grid recovery lacks accurate load scanning and resilience assessment mechanisms when dealing with large-scale power grid recovery, and cannot effectively handle complex multi-site, multi-objective scheduling tasks, making load allocation and priority scheduling in the power grid recovery process inflexible and responsive, resulting in long post-disaster recovery time, uneven power supply recovery, and high power grid operation risks, thus affecting the overall stability and recovery efficiency of the power grid. Therefore, how to accurately scan each load node in the post-disaster recovery process of a large-scale power grid to improve recovery efficiency and reduce recovery delay to ensure power grid stability is a difficult problem faced by the industry. Summary of the invention

[0004] The present application provides a multi-objective optimization scheduling method and system for power grid post-disaster recovery, which can accurately scan each load node during large-scale power grid post-disaster recovery to improve recovery efficiency and reduce recovery delay to ensure power grid stability.

[0005] In a first aspect, the present application provides a multi-objective optimization scheduling method for power grid post-disaster recovery, the scheduling method comprising the following steps:

[0006] Responding to the dispatching instruction for post-disaster recovery of the power grid issued by the large-scale power grid security center, scanning the distribution load on the power grid energy consumption side in the large-scale power grid, and marking the dispatching load constraint of the distribution load on the power grid energy consumption side according to the scanning result and the load responsiveness of the distribution unit in the dispatching instruction;

[0007] Collect capacity configuration features corresponding to multiple sites when the power grid is restored after a disaster, and determine the coordinated dispatch index of the power grid energy consumption side when the power grid is restored after a disaster based on the load responsiveness in the capacity configuration features and the energy dispatch load level of the multiple sites when the power grid is restored after a disaster;

[0008] Control the load configuration amount of energy distribution during grid energy supply scheduling, and extract the load disturbance information of energy loads of multiple energy-consuming sides when responding to energy distribution. Based on the load disturbance information and the load recovery efficiency of the grid lines after the distribution network is damaged by various levels of disasters, verify the power balance constraints corresponding to the load nodes of multiple sites during post-disaster grid recovery, and obtain a power verification sequence;

[0009] Based on the coordinated dispatch index and the power consumption verification sequence, the automatic dispatch order of the power grid energy consumption side is controlled during the post-disaster recovery of the power grid, and the load on the power grid energy consumption side is optimized.

[0010] In this embodiment, the coordinated dispatching index of the power grid energy consumption side during power grid post-disaster recovery is determined based on the load responsiveness in the capacity configuration feature and the energy dispatching load level of multiple sites during power grid post-disaster recovery, specifically including:

[0011] extracting load responsiveness from the capacity configuration characteristics;

[0012] Determining energy discrete quantities of multiple sites when the power grid is restored after a disaster based on the load responsiveness;

[0013] Determine the energy allocation information of the power grid energy consumption side when the power grid is restored after a disaster;

[0014] The coordinated dispatching index of the energy consumption side of the power grid during post-disaster power grid recovery is determined according to the energy discrete quantity and the energy allocation information.

[0015] In this embodiment, extracting load disturbance information of energy loads of multiple energy consumption sides when responding to energy allocation specifically includes:

[0016] Determine the load priority for each energy-consuming side when allocating energy;

[0017] Determine the load aggregation amount on the energy consumption side of the power grid according to the priority of all loads;

[0018] The load disturbance information of the energy load when the energy consumption side responds to the energy distribution is determined according to the load aggregation amount.

[0019] In this embodiment, based on the load disturbance information and the load recovery efficiency of the power grid line after the distribution network is damaged by various levels of disasters, the power balance constraints corresponding to the load nodes of multiple sites during the post-disaster recovery of the power grid are verified, and the power consumption verification sequence is obtained, which specifically includes:

[0020] Determine the load recovery efficiency of the power grid lines after the distribution network is damaged by disasters of various levels;

[0021] Determine the load nodes of multiple sites when the power grid is restored after a disaster;

[0022] Determine, according to the load disturbance information, the power balance corresponding to the load nodes of the multiple sites when the power grid is restored after a disaster;

[0023] The power consumption on the energy consumption side is calibrated according to the load recovery efficiency, the load node and the power balance amount to obtain an electric verification sequence.

[0024] In this embodiment, the automatic dispatching sequence of the power grid energy consumption side when controlling the power grid post-disaster recovery based on the coordinated dispatching index and the power consumption verification sequence specifically includes:

[0025] Determine the resilience index of the power grid energy consumption side when the power grid is restored after a disaster according to the coordinated dispatch index;

[0026] Determine the dispatch response characteristics of the power grid energy consumption side when the power grid is restored after a disaster according to the power consumption verification sequence;

[0027] The load dispatch index of the power grid energy consumption side when the power grid is restored after a disaster is determined according to the resilience index and the dispatch response characteristics, and the load dispatch index is sorted according to the load dispatch index to obtain an automatic dispatch order of the power grid energy consumption side when the power grid is restored after a disaster.

[0028] In this embodiment, the load disturbance information refers to load changes and fluctuations caused by energy allocation, load adjustment, and execution of response instructions during the power grid dispatching process.

[0029] In this embodiment, the power consumption verification sequence refers to a calibration sequence of the power consumption of each node during power grid recovery.

[0030] In this embodiment, the load configuration amount refers to the specific power supply amount allocated to meet the power demand of each site or region during the power grid dispatching process.

[0031] In this embodiment, the capacity configuration feature refers to a set of key parameters related to the power supply capacity of each site in the power grid during post-disaster recovery or daily operation.

[0032] In a second aspect, the present application provides a multi-objective optimization scheduling system for power grid post-disaster recovery, which is used to execute a multi-objective optimization scheduling method for power grid post-disaster recovery, and the scheduling system includes:

[0033] A load marking module is used to respond to the dispatching instructions for post-disaster recovery of the power grid issued by the large-scale power grid security center, scan the distribution load on the power grid energy consumption side in the large-scale power grid, and mark the dispatching load constraint of the distribution load on the power grid energy consumption side according to the scanning results and the load responsiveness of the distribution units in the dispatching instructions;

[0034] A collaborative dispatching module is used to collect capacity configuration features corresponding to multiple sites when the power grid is restored after a disaster, and determine the collaborative dispatching index of the power grid energy consumption side when the power grid is restored after a disaster based on the load responsiveness in the capacity configuration features and the energy dispatching load level of multiple sites when the power grid is restored after a disaster;

[0035] A power verification module is used to control the load configuration amount of energy distribution during power grid energy supply scheduling, and extract the load disturbance information of energy loads of multiple energy consumption sides when responding to energy distribution. Based on the load disturbance information and the load recovery efficiency of the power grid line after the distribution network is damaged by various levels of disasters, the power balance constraints corresponding to the load nodes of multiple sites during the post-disaster recovery of the power grid are verified to obtain a power consumption verification sequence;

[0036] The automatic dispatching module is used to control the automatic dispatching sequence of the power grid energy consumption side during post-disaster power grid recovery based on the coordinated dispatching index and the power consumption verification sequence, and to optimize the load on the power grid energy consumption side.

[0037] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects:

[0038] By responding to the dispatching instruction of post-disaster recovery of the power grid issued by the large-scale power grid security center, the distribution load on the power grid energy consumption side in the large-scale power grid is scanned, and the dispatching load constraint of the distribution load on the power grid energy consumption side is marked according to the scanning result and the load responsiveness of the distribution unit in the dispatching instruction; the capacity configuration characteristics corresponding to multiple sites when the power grid is recovered after the disaster are collected, and the coordinated dispatching index of the power grid energy consumption side when the power grid is recovered after the disaster is determined based on the load responsiveness in the capacity configuration characteristics and the energy dispatching load level of multiple sites when the power grid is recovered after the disaster; the load configuration amount of energy distribution during power grid energy supply dispatching is controlled, and the load disturbance information of energy loads on multiple energy consumption sides when responding to energy distribution is extracted; based on the load disturbance information and the load recovery efficiency of the power grid line after the distribution network is damaged by various levels of disasters, the power balance constraints corresponding to the load nodes of multiple sites when the power grid is recovered after the disaster are verified to obtain a power verification sequence; based on the coordinated dispatching index and the power verification sequence, the automatic dispatching order of the power grid energy consumption side when the power grid is recovered after the disaster is controlled, and the load on the power grid energy consumption side is optimized.

[0039] It can be seen that in this application, first, by responding to the post-disaster recovery dispatching instruction of the power grid and scanning the distribution load on the power grid energy consumption side, the recovery demand and dispatching constraints of each load can be accurately identified, ensuring the rationality and efficiency of load dispatching during the power grid recovery process, optimizing the allocation of power resources, and reducing the load overload or imbalance that may occur during the recovery process; collecting the capacity configuration characteristics of multiple sites and combining the load responsiveness and energy dispatching load level, the overall coordinated dispatching capability of the power grid during post-disaster recovery can be more accurately evaluated to ensure that the power grid recovery in various regions can be coordinated. Controlling the load configuration amount of energy distribution during power grid energy supply dispatching and extracting load disturbance information can identify the load change trend of each energy consumption side in real time. By analyzing the load disturbance information, the power grid load dispatching strategy can be optimized, the real-time and stability of power grid recovery can be improved, and power grid fluctuations caused by excessive load changes can be avoided. By verifying the power balance constraint based on the load disturbance information and the recovery efficiency of the power grid line, it can ensure that the power supply and demand of each load node are balanced, and the unstable factors in the power grid recovery process are reduced. Combined with the coordinated dispatching index and the power verification sequence, the automatic dispatching sequence control can dynamically adjust the power supply restoration sequence of each load node, thereby optimizing the load distribution on the power consumption side of the power grid. It improves the flexibility and efficiency of power grid restoration, ensures that important nodes are restored first during the power restoration process, and avoids waste of system resources and unnecessary delays in the restoration process.

[0040] In summary, the technical solution adopted in this application can accurately scan each load node during the post-disaster recovery of a large-scale power grid, so as to improve the recovery efficiency and reduce the recovery delay to ensure the stability of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0042] Figure 1 is a flow chart of a multi-objective optimization scheduling method for post-disaster power grid recovery provided by the present application;

[0043] Figure 2 is an exemplary flow chart for determining a power verification sequence provided by the present application;

[0044] Figure 3 is an exemplary flow chart of the automatic dispatching sequence of the power grid energy consumption side when controlling the power grid post-disaster recovery provided by the present application;

[0045] Figure 4 It is a module structure diagram of the multi-objective optimization dispatching system for post-disaster power grid recovery provided in this application. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical scheme and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments and drawings. The schematic implementation modes and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention. It should be noted that the present invention is already in the actual development and use stage.

[0047] Embodiment 1: In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. Figure 1 As shown in FIG. 1 , this figure is an exemplary flow chart of a multi-objective optimization scheduling method for post-disaster recovery of a power grid according to this embodiment of the present application, and the scheduling method includes the following steps:

[0048] In step S1, in response to the dispatching instruction for post-disaster recovery of the power grid issued by the large-scale power grid security center, the distribution load on the power grid energy consumption side in the large-scale power grid is scanned, and the dispatching load constraint of the distribution load on the power grid energy consumption side is marked according to the scanning results and the load responsiveness of the distribution units in the dispatching instruction.

[0049] In specific implementation, key power data including power, current, voltage, etc. are collected in real time through smart meters, distribution monitoring terminals and distributed energy management systems deployed on each energy consumption side (such as residential areas, industrial parks and commercial areas). The device transmits the collected data to the central dispatching and control system of the power grid to form a load distribution diagram on the energy consumption side. The dispatching system analyzes the load adjustment capacity of each energy consumption side in combination with the load responsiveness of the distribution units mentioned in the dispatching instructions. Load responsiveness is an important indicator reflecting the flexibility of regulation. The load adjustment range and adjustment speed need to be evaluated during calculation. By setting the constraint threshold, the distribution load on each energy consumption side is marked as different dispatching load constraints, including the maximum allowable load, the minimum allowable load and the flexible adjustment interval. In this process, it is also necessary to combine the actual operating conditions of the post-disaster power grid equipment, such as the repair progress of the line and the availability of the distribution facilities, to ensure that the marking of the constraint quantity is consistent with the actual capacity of the current power grid. Finally, the system generates a load constraint report, and the dispatching load constraint quantity is read from the load constraint report, which will not be repeated here.

[0050] It should be noted that in this application, the dispatching instruction for post-disaster recovery of the power grid refers to the directive operation plan issued by the power grid security center to quickly restore the stability of power grid operation and power supply capacity after the power grid suffers a natural disaster or an emergency; the distribution load on the power consumption side of the power grid in a large-scale power grid refers to the total power demand consumed by various types of power-consuming equipment, users or systems distributed on the power consumption side in the large-scale power grid in the distribution network. This includes the load demand of industrial, commercial and residential users; load responsiveness refers to the index of the flexibility and ability of the power consumption side of the power grid to adjust its power demand after receiving the dispatching instruction; the dispatching load constraint refers to the dispatching range and restriction conditions set for the power consumption side distribution load in the power grid dispatching process to ensure the stable operation of the system and the balance of supply and demand. It includes the maximum allowable value, the minimum allowable value and the range of flexible adjustment of the load, which are usually determined based on the actual operating capacity of the power grid equipment, the user load responsiveness and the dispatching demand. The dispatching load constraint is used to guide load distribution and adjustment decisions to prevent power grid operation risks caused by load overload or improper adjustment, while ensuring the safety and efficiency of power supply under post-disaster recovery or special working conditions.

[0051] In step S2, the capacity configuration characteristics corresponding to multiple sites when the power grid is restored after a disaster are collected, and the coordinated scheduling indicators of the power grid energy consumption side when the power grid is restored after a disaster are determined based on the load responsiveness in the capacity configuration characteristics and the energy scheduling load levels of the multiple sites when the power grid is restored after a disaster.

[0052] In specific implementation, the collection of capacity configuration features corresponding to multiple sites during post-disaster power grid recovery can be implemented in the following ways: the site's monitoring system (such as a SCADA system) can be used to collect the site's capacity configuration data in real time, including the rated capacity of the transformer, spare capacity, equipment load rate, and distributed energy access capacity. At the same time, combined with the status monitoring system of the on-site equipment, the equipment integrity and availability data of each site after the disaster, such as line damage and the operating status of the substation equipment, are obtained. The collected capacity configuration features are uploaded to the central dispatching and control platform using the data communication network. In the platform, the data of each site is classified, summarized, and cleaned to form a capacity feature report, that is, the capacity configuration features are obtained.

[0053] It should be noted that, in this application, the capacity configuration characteristics refer to a set of key parameters related to the power supply capacity of each site in the power grid during post-disaster recovery or daily operation.

[0054] In this embodiment, the coordinated dispatching index of the power grid energy consumption side during power grid post-disaster recovery is determined based on the load responsiveness in the capacity configuration feature and the energy dispatching load level of multiple sites during power grid post-disaster recovery, which can be specifically determined in the following manner, namely:

[0055] extracting load responsiveness from the capacity configuration characteristics;

[0056] Determining energy discrete quantities of multiple sites when the power grid is restored after a disaster based on the load responsiveness;

[0057] Determine the energy allocation information of the power grid energy consumption side when the power grid is restored after a disaster;

[0058] The coordinated dispatching index of the energy consumption side of the power grid during post-disaster power grid recovery is determined according to the energy discrete quantity and the energy allocation information.

[0059] In the specific implementation, first, obtain the grid load data from the real-time monitoring system of each site (such as SCADA system, smart meter), record the actual load demand (such as power, energy consumption) and the maximum adjustable load of each site, compare the load response in different time periods, and evaluate the load adjustment ability during the post-disaster recovery period. Load responsiveness = ΔP / Δt, where ΔP represents the load adjustment amount (the increase or decrease in load), and Δt is the time required for load adjustment. This calculation can output a load responsiveness value for each site, reflecting the flexibility and efficiency of load adjustment after the site receives the dispatch instruction. Then, determine the actual load demand and theoretical load demand (such as normal load during post-disaster recovery) of each site. Assume that the load demand of each site is P 需求 , the maximum adjustable load is P 可调 , the energy discrete quantity represents the difference between the demand of each site and its regulation capacity, which can be calculated by the following formula: Among them, P 需求，i is the load demand of site i, P 可调，i is the load regulation capability of site i. The value usually ranges between 0 and 1, where 0 indicates no difference and 1 indicates that the demand is completely mismatched or cannot be regulated. Finally, an optimization algorithm (such as linear programming or genetic algorithm) can be used for energy allocation. According to the discrete amount of energy at the site, the amount of energy that needs to be supplemented is determined. The specific calculation method is, E 调配，i =Energy Discrete i ×P 需求，i , where the calculation represents the amount of energy that site i needs to adjust to balance its actual load demand and regulation capacity; the energy dispatch process is optimized through the linear programming algorithm to ensure the overall supply and demand balance of the power grid. Assume that the total dispatch capacity of the power grid is P 总调度 , we can set the objective function, Through the constraint conditions, it is ensured that each site will not exceed its maximum adjustment range during the dispatch process. Finally, the load responsiveness and energy discreteness are combined by weighted summation to form a coordinated dispatch index. The formula is: coordinated dispatch index i = load responsiveness i × energy discreteness i. For all sites, the total coordinated dispatch index is calculated.

[0060] It should be noted that, in this application, energy discrete quantity refers to the degree of difference between the energy demand of each site in the power grid and its regulation capacity; energy dispatch information refers to the energy allocation plan formulated in the process of power grid dispatch to ensure the balance of supply and demand and stable operation of the system, based on the energy demand, load response capability and available resources of each site; load responsiveness refers to the indicator of the ability of the power grid energy-consuming side (such as each site, user or equipment) to adjust its power demand when receiving the power grid dispatch instruction; energy dispatch load level refers to the load regulation level or priority set by the power grid when dispatching, according to the load demand and power grid operation status of different sites or regions; collaborative dispatch index refers to the indicator used to measure and optimize the coordination and cooperation capabilities between multiple sites or regions during the power grid dispatch process.

[0061] In step S3, the load configuration amount of energy distribution during grid energy supply scheduling is controlled, and load disturbance information of energy loads of multiple energy-consuming sides when responding to energy distribution is extracted. Based on the load disturbance information and the load recovery efficiency of the grid lines after the distribution network is damaged by various levels of disasters, the power balance constraints corresponding to the load nodes of multiple sites during post-disaster grid recovery are verified to obtain a power consumption verification sequence.

[0062] In specific implementation, the load configuration amount of energy distribution during the control of power grid energy supply dispatching can be implemented in the following way, namely: first, by collecting real-time load data of each site in the power grid, the power demand of each site is determined. Then, the load response capability of each site is considered, that is, the load range that can be adjusted after receiving the dispatching instruction. Sites with strong load response capability can adjust the load quickly, while sites with weak response capability require more energy support. Then, the dispatching system calculates the load configuration amount of each site according to the total power supply capacity of the power grid. Through optimization algorithms (such as linear programming), the dispatching system ensures that the load demand of each site is met while avoiding power supply overload. Priority is given to sites with high load demand or those that are critical to power grid recovery to ensure that key areas have sufficient power supply. Among them, the dispatching system will also monitor the operating status of the power grid in real time, dynamically adjust the load configuration amount, and ensure the stable operation of the power grid. Finally, through accurate load configuration, it is ensured that the load demand of the power grid during post-disaster recovery or peak period is effectively managed and met.

[0063] It should be noted that in this application, the load allocation refers to the specific amount of power supply allocated to meet the power demand of each site or region during the power grid dispatching process. The load allocation is reasonably allocated based on factors such as the load demand, response capability, priority of each site and the power supply capacity of the power grid.

[0064] In an optional embodiment of the present application, load optimization on the power grid energy consumption side includes optimizing power grid resources, for example, optimizing power grid resources of the power grid according to a pre-configured resource allocation optimization model. The resource allocation optimization model is constructed based on a comprehensive loss index and an emergency resource information set, and the comprehensive loss index is determined based on a partition risk assessment model and power grid load data.

[0065] In an optional embodiment of the present application, the process of constructing the partition risk assessment model includes:

[0066] Determine key statistical features in each preset time period, wherein the key statistical features may include statistical features such as variance, average value, difference between maximum and minimum values ​​of various historical power parameter values ​​in the time period, health status of each power grid device, various statistical features of various environmental parameters in the time period, and quantitative values ​​of all geographic information features, such as altitude, slope, land use type, terrain classification index, digital elevation and other information;

[0067] A Bayesian network model is used as a partition risk assessment model, wherein the partition risk assessment model takes key statistical features of each time period as input;

[0068] Use structural learning algorithms to build the structure of the Bayesian network to represent the conditional dependencies between key statistical features and manually add known physical or engineering constraints;

[0069] The partition risk assessment model outputs an estimated probability of failure occurring in each time period according to the key statistical characteristics of the time period; it iteratively optimizes the parameters of each conditional probability table in the Bayesian network by using the maximum likelihood estimation or Bayesian estimation method for each time period;

[0070] In an optional embodiment of the present application, the resource demand ratio Bi is calculated according to the following formula:

[0071]

[0072] Wherein, i represents the serial number mark of each power grid partition; Ri represents the estimated resource demand mark in the i-th power grid partition, and the estimated resource demand Ri=a1×Li+a2×Ni+a3×Ri; wherein a1, a2 and a3 are all preset proportional coefficients; wherein Li represents the real-time power load mark of the i-th power grid partition; Ni represents the number mark of the key power facilities in the i-th power grid partition; FPi represents the failure probability mark of the i-th power grid partition estimated by the partition risk assessment model; Bi represents the resource demand ratio mark in the i-th power grid partition.

[0073] The grid loss index Wherein, a4 and a5 are preset proportional coefficients, and Ltotal is the total load of all grid partitions.

[0074] In an optional embodiment of the present application, the resource allocation optimization model is constructed by minimizing the target optimization function M as the optimization target, and taking the first constraint condition and the second constraint condition as the constraint condition set:

[0075] The expression of the objective optimization function M of the resource allocation optimization model is: M = ∑ i (Si×(1-xi)+Pi×xi); where Pi is the cost of allocating emergency resources to the i-th grid partition; xi represents the allocation ratio variable set for each grid partition; the total amount of emergency resources is 1.

[0076] In this embodiment, extracting load disturbance information of energy loads of multiple energy consumption sides when responding to energy allocation can be specifically implemented by the following steps:

[0077] Determine the load priority for each energy-consuming side when allocating energy;

[0078] Determine the load aggregation amount on the energy consumption side of the power grid according to the priority of all loads;

[0079] The load disturbance information of the energy load when the energy consumption side responds to the energy distribution is determined according to the load aggregation amount.

[0080] In the specific implementation, first of all, it is necessary to determine the load priority of each energy-consuming side in the power grid according to its load demand, importance and recovery priority, including: load demand, larger load demand may have higher priority, especially in the early stage of power grid recovery, focus on power supply to large load areas. Restoration importance, some key facilities (such as hospitals, government agencies, etc.) have higher priority in the post-disaster recovery process. Response capability, energy-consuming sides with strong load response capability may have higher priority in scheduling because they can quickly adjust the load and relieve the pressure on the power grid. Then, each energy-consuming side is classified according to priority, and the total load required for each type of energy-consuming side in a specific time period is calculated. Load aggregation is the result of weighted summation of the load demand of each energy-consuming side, ensuring that the power grid can reasonably allocate energy and avoid excessive load concentration. Finally, the load demand of each energy-consuming side is merged through load aggregation, and the load adjustment range that each energy-consuming side can accept is determined based on these aggregated loads. The load adjustment range refers to the range in which the power grid can adjust the load of each energy-consuming side according to the dispatching instructions. For example, if the load aggregation of a certain site is large, the load of the site can be adjusted within a certain range to respond to the demand fluctuation of the power grid by reducing the load. Collect the real-time load data, load response capability and dispatch instructions of each site. Then evaluate the load adjustment range of each site, simulate the fluctuations that may occur during the load change process, consider factors such as response lag and load concentration, and obtain the load disturbance information of the energy load when the energy consumption side responds to energy distribution.

[0081] It should be noted that, in this application, load priority refers to the priority of load adjustment determined during the grid dispatching process according to the load demand, importance and contribution to the stability or recovery of the grid on each energy consumption side; load aggregation refers to the total load obtained by merging or aggregating the load demands of multiple energy consumption sides according to certain rules during the grid dispatching process; load disturbance information refers to the load changes and fluctuations caused by energy allocation, load adjustment and the execution of response instructions during the grid dispatching process.

[0082] Preferably, in this embodiment, reference Figure 2 As shown, this figure is an exemplary flow chart for determining a power verification sequence in an embodiment of the present application. In this embodiment, based on the load disturbance information and the load recovery efficiency of the power grid line after the distribution network is damaged by various levels of disasters, the power balance constraints corresponding to the load nodes of multiple sites during the post-disaster recovery of the power grid are verified, and the power verification sequence is obtained. Specifically, the following steps can be used to implement it:

[0083] First, in step S31, the load recovery efficiency of the power grid line after the distribution network is damaged by disasters of various levels is determined;

[0084] Secondly, in step S32, the load nodes of multiple sites when the power grid is restored after a disaster are determined;

[0085] Then, in step S33, the power balance amounts corresponding to the load nodes of the multiple sites when the power grid is restored after a disaster are determined according to the load disturbance information;

[0086] Finally, in step S34, the power consumption on the energy consumption side is calibrated according to the load recovery efficiency, the load nodes and the power balance amount to obtain an electric verification sequence.

[0087] In the specific implementation, first, it is necessary to evaluate the line damage of the distribution network during the post-disaster recovery process. Disasters of different levels may cause different degrees of line damage, which in turn affects the load recovery capacity of the power grid lines. According to the level of the disaster and the degree of damage to the line, the dispatching system determines the load recovery efficiency of each line. Then, in the post-disaster recovery process, the load nodes of the power grid refer to the key areas or sites in the power grid that need power supply. The load demand and recovery status of these sites directly affect the efficiency and stability of power grid recovery. Through the post-disaster assessment, the dispatching system determines the sites that need to be restored first and uses them as load nodes. The power supply of these load nodes will be allocated according to priority to ensure that the key areas are restored as soon as possible. Then, after determining the load nodes, the dispatching system needs to calculate the power balance of each load node based on the load disturbance information. The power balance reflects the difference between the power supply demand and the actual supply of the load nodes in the power grid. The load disturbance information provides the load fluctuations of each energy-consuming side when responding to energy distribution. The dispatching system calculates the actual power demand of the load node through this information, and combines the load recovery efficiency of the post-disaster line to evaluate the power balance status of each load node in the power grid. Finally, based on the load recovery efficiency, the demand of the load nodes and the power balance, the dispatching system calibrates the power consumption on the energy consumption side. By adjusting the power supply of each load node of the power grid, it ensures that the power demand of each site and the power supply capacity of the power grid are balanced during the post-disaster recovery process, thereby avoiding overload or insufficient power supply. The calibrated power consumption will form a power verification sequence.

[0088] It should be noted that in this application, load recovery efficiency refers to the efficiency and degree of restoring load carrying capacity and power supply capacity of power grid lines or distribution networks after damage from disasters of various levels during the post-disaster recovery of the power grid; load nodes refer to specific locations or areas in the power grid that require power supply; power balance refers to the difference between the power demand and actual supply of a specific area or node during the operation of the power grid. A positive value indicates that the actual power supply capacity of the area or node exceeds the load demand and there is surplus power. A negative value indicates that the power supply capacity of the area or node is insufficient to meet the load demand and there is a power gap; the power consumption verification sequence refers to the calibration sequence of the power consumption of each node during the power grid restoration.

[0089] In step S4, the automatic dispatching sequence of the power grid energy consumption side during post-disaster power grid recovery is controlled based on the coordinated dispatching index and the power consumption verification sequence, and the load on the power grid energy consumption side is optimized.

[0090] Preferably, in this embodiment, reference Figure 3 As shown, this figure is an exemplary flow chart of the automatic dispatching sequence of the power grid energy consumption side when controlling the power grid post-disaster recovery in an embodiment of the present application. In this embodiment, the automatic dispatching sequence of the power grid energy consumption side when controlling the power grid post-disaster recovery based on the collaborative dispatching index and the power consumption verification sequence can be specifically implemented by the following steps:

[0091] First, in step S41, the resilience index of the power grid energy consumption side during post-disaster power grid recovery is determined according to the coordinated dispatch index;

[0092] Then, in step S42, the dispatch response characteristics of the power grid energy consumption side when the power grid is restored after a disaster are determined according to the power consumption verification sequence;

[0093] Finally, in step S43, the load dispatching index of the power grid energy consumption side when the power grid is restored after a disaster is determined according to the resilience index and the dispatching response characteristics, and the loads are sorted according to the load dispatching index to obtain an automatic dispatching order of the power grid energy consumption side when the power grid is restored after a disaster.

[0094] In the specific implementation, first, the power grid dispatching system needs to evaluate the post-disaster recovery capability of the power grid based on the coordinated dispatching index. The coordinated dispatching index integrates the response capabilities of each energy-consuming side of the power grid during the recovery process, including the load recovery rate, the load adjustment range and coordination of each node. By analyzing these indicators, the resilience index of each energy-consuming side can be determined. The resilience index reflects the rapid recovery capability and power distribution capability of each energy-consuming side during post-disaster recovery. For example, for areas carrying critical loads (such as hospitals, communication sites, etc.), their resilience index is usually high, while for ordinary residential areas, their resilience may be low. Through the evaluation of resilience, the power grid dispatching system can determine which areas or nodes should be restored to power supply first to ensure the stability and recovery efficiency of the power grid. Then, the power consumption verification sequence reflects the actual power consumption of each load node in the power distribution and dispatching process during the post-disaster recovery process. By analyzing the power consumption verification sequence, the dispatching system evaluates the dispatching response characteristics of each load node, that is, the response characteristics of each load node after receiving the dispatching instruction. These response characteristics include the speed of load change, the sensitivity of response, and the hysteresis in the adjustment process. For example, some load nodes may adjust their loads immediately after receiving the recovery command, while other nodes may have a delayed response or a small load adjustment. Finally, the power grid dispatching system combines the resilience indicators and dispatch response characteristics obtained in the first two steps to comprehensively analyze the performance of each load node in post-disaster recovery, and then determine the load dispatching indicators for post-disaster recovery of the power grid. Nodes with strong resilience and quick response will be given higher priority, while nodes with weak resilience and delayed response will be arranged in the subsequent recovery plan. The dispatching system sorts the load nodes according to these load dispatching indicators. The sorted result is the automatic dispatching order for post-disaster recovery of the power grid.

[0095] It should be noted that in this application, the resilience index refers to the ability index to measure the rapid restoration of load carrying capacity of each energy-consuming side or load node of the power grid during the post-disaster recovery of the power grid; the dispatch response characteristic refers to the response behavior and characteristics of the load node to the dispatch command after the power grid energy-consuming side receives the power grid dispatch command; the automatic dispatch order of the power grid energy-consuming side during the post-disaster recovery of the power grid refers to the priority order of power supply restoration of each load node automatically generated during the post-disaster recovery of the power grid based on factors such as the resilience, dispatch response characteristics and priority of each load node. This order determines which areas or nodes should be restored to power supply first in post-disaster recovery and which can be restored later to ensure the stability and recovery efficiency of the power grid.

[0096] In addition, it should be noted that in this application, load optimization is performed on the energy consumption side of the power grid. First, the dispatching system needs to collect real-time power consumption data of each load node of the power grid, including load demand, load response characteristics, resilience indicators, etc. These data are collected by sensors and smart meters, and analyzed in real time to evaluate the power consumption of each node; based on the collected data, the dispatching system formulates adjustment strategies according to the load priority, recovery capability and response characteristics of each load node. For load nodes that are restored first, their load carrying capacity will be optimized by increasing the power supply or adjusting the dispatching order; on the basis of ensuring the stability of the power grid, the system uses an optimization algorithm to reasonably distribute the load of each node of the power grid. The adjusted load optimization plan will be reflected in the power grid dispatching system in real time to ensure that while meeting the recovery requirements, load overload or underload is avoided. After the load optimization plan is implemented, the system will continuously monitor the changes in the power grid load and make dynamic adjustments according to the actual situation to continuously optimize the load distribution on the energy consumption side of the power grid.

[0097] It can be seen that in this application, first, by responding to the post-disaster recovery dispatching instruction of the power grid and scanning the distribution load on the power grid energy consumption side, the recovery demand and dispatching constraints of each load can be accurately identified, ensuring the rationality and efficiency of load dispatching during the power grid recovery process, optimizing the allocation of power resources, and reducing the load overload or imbalance that may occur during the recovery process; collecting the capacity configuration characteristics of multiple sites and combining the load responsiveness and energy dispatching load level, the overall coordinated dispatching capability of the power grid during post-disaster recovery can be more accurately evaluated to ensure that the power grid recovery in various regions can be coordinated. Controlling the load configuration amount of energy distribution during power grid energy supply dispatching and extracting load disturbance information can identify the load change trend of each energy consumption side in real time. By analyzing the load disturbance information, the power grid load dispatching strategy can be optimized, the real-time and stability of power grid recovery can be improved, and power grid fluctuations caused by excessive load changes can be avoided. By verifying the power balance constraint based on the load disturbance information and the recovery efficiency of the power grid line, it can ensure that the power supply and demand of each load node are balanced, and the unstable factors in the power grid recovery process are reduced. Combined with the coordinated dispatching index and the power verification sequence, the automatic dispatching sequence control can dynamically adjust the power supply restoration sequence of each load node, thereby optimizing the load distribution on the power consumption side of the power grid. It improves the flexibility and efficiency of power grid restoration, ensures that important nodes are restored first during the power restoration process, and avoids waste of system resources and unnecessary delays in the restoration process.

[0098] In summary, the technical solution adopted in this application can accurately scan each load node during the post-disaster recovery of a large-scale power grid, so as to improve the recovery efficiency and reduce the recovery delay to ensure the stability of the power grid.

[0099] Embodiment 2: This application provides a multi-objective optimization scheduling system for power grid post-disaster recovery, referring to Figure 4 As shown, this figure is a schematic diagram of a scheduling system according to this embodiment of the present application, and the scheduling system includes:

[0100] The load marking module 100 is used to respond to the dispatching instruction of the post-disaster recovery of the power grid issued by the large-scale power grid security center, scan the distribution load on the power grid energy consumption side in the large-scale power grid, and mark the dispatching load constraint of the distribution load on the power grid energy consumption side according to the scanning result and the load responsiveness of the distribution unit in the dispatching instruction;

[0101] The collaborative dispatching module 200 is used to collect the capacity configuration characteristics corresponding to the multiple sites when the power grid is restored after a disaster, and determine the collaborative dispatching index of the power grid energy consumption side when the power grid is restored after a disaster based on the load responsiveness in the capacity configuration characteristics and the energy dispatching load level of the multiple sites when the power grid is restored after a disaster;

[0102] The power verification module 300 is used to control the load configuration amount of energy distribution during power grid energy supply scheduling, and extract the load disturbance information of energy loads of multiple energy consumption sides when responding to energy distribution, and verify the power balance constraints corresponding to the load nodes of multiple sites during post-disaster power grid recovery based on the load disturbance information and the load recovery efficiency of the power grid lines after the distribution network is damaged by various levels of disasters, so as to obtain a power consumption verification sequence;

[0103] The automatic dispatching module 400 is used to control the automatic dispatching sequence of the power grid energy consumption side during post-disaster power grid recovery based on the coordinated dispatching index and the power consumption verification sequence, and to optimize the load on the power grid energy consumption side.

[0104] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A multi-objective optimization scheduling method for power grid post-disaster recovery, characterized in that: The scheduling method comprises the following steps: Responding to the dispatching instruction for post-disaster recovery of the power grid issued by the large-scale power grid security center, scanning the distribution load on the power grid energy consumption side in the large-scale power grid, and marking the dispatching load constraint of the distribution load on the power grid energy consumption side according to the scanning result and the load responsiveness of the distribution unit in the dispatching instruction; Collect capacity configuration features corresponding to multiple sites when the power grid is restored after a disaster, and determine the coordinated dispatch index of the power grid energy consumption side when the power grid is restored after a disaster based on the load responsiveness in the capacity configuration features and the energy dispatch load level of the multiple sites when the power grid is restored after a disaster; Control the load configuration amount of energy distribution during grid energy supply scheduling, and extract the load disturbance information of energy loads of multiple energy-consuming sides when responding to energy distribution. Based on the load disturbance information and the load recovery efficiency of the grid lines after the distribution network is damaged by various levels of disasters, verify the power balance constraints corresponding to the load nodes of multiple sites during post-disaster grid recovery, and obtain a power verification sequence; Based on the coordinated dispatch index and the power consumption verification sequence, the automatic dispatch order of the power grid energy consumption side is controlled during the post-disaster recovery of the power grid, and the load on the power grid energy consumption side is optimized.

2. A multi-objective optimization scheduling method for post-disaster power grid recovery as claimed in claim 1, characterized in that: The coordinated dispatching index of the power grid energy consumption side during the power grid post-disaster recovery is determined based on the load responsiveness in the capacity configuration feature and the energy dispatching load level of multiple sites during the power grid post-disaster recovery, specifically including: extracting load responsiveness from the capacity configuration characteristics; Determining energy discrete quantities of multiple sites when the power grid is restored after a disaster based on the load responsiveness; Determine the energy allocation information of the power grid energy consumption side when the power grid is restored after a disaster; The coordinated dispatching index of the energy consumption side of the power grid during post-disaster power grid recovery is determined according to the energy discrete quantity and the energy allocation information.

3. A multi-objective optimization scheduling method for post-disaster power grid recovery as claimed in claim 1, characterized in that: Extracting load disturbance information of energy loads of multiple energy consumption sides when responding to energy allocation specifically includes: Determine the load priority for each energy-consuming side when allocating energy; Determine the load aggregation amount on the energy consumption side of the power grid according to the priority of all loads; The load disturbance information of the energy load when the energy consumption side responds to the energy distribution is determined according to the load aggregation amount.

4. A multi-objective optimization scheduling method for post-disaster power grid recovery according to claim 1, characterized in that: Based on the load disturbance information and the load recovery efficiency of the power grid lines after the distribution network is damaged by various levels of disasters, the power balance constraints corresponding to the load nodes of multiple sites during the post-disaster recovery of the power grid are verified, and the power consumption verification sequence obtained specifically includes: Determine the load recovery efficiency of the power grid lines after the distribution network is damaged by disasters of various levels; Determine the load nodes of multiple sites when the power grid is restored after a disaster; Determine, according to the load disturbance information, the power balance corresponding to the load nodes of the multiple sites when the power grid is restored after a disaster; The power consumption on the energy consumption side is calibrated according to the load recovery efficiency, the load node and the power balance amount to obtain an electric verification sequence.

5. A multi-objective optimization scheduling method for power grid post-disaster recovery as claimed in claim 1, characterized in that: The automatic dispatching sequence of the power grid energy consumption side when controlling the power grid post-disaster recovery based on the coordinated dispatching index and the power consumption verification sequence specifically includes: Determine the resilience index of the power grid energy consumption side when the power grid is restored after a disaster according to the coordinated dispatch index; Determine the dispatch response characteristics of the power grid energy consumption side when the power grid is restored after a disaster according to the power consumption verification sequence; The load dispatch index of the power grid energy consumption side when the power grid is restored after a disaster is determined according to the resilience index and the dispatch response characteristics, and the load dispatch index is sorted according to the load dispatch index to obtain an automatic dispatch order of the power grid energy consumption side when the power grid is restored after a disaster.

6. A multi-objective optimization scheduling method for post-disaster power grid recovery according to claim 1, characterized in that: The load disturbance information refers to the load changes and fluctuations caused by energy distribution, load adjustment and the execution of response instructions during the power grid dispatching process.

7. A multi-objective optimization scheduling method for post-disaster power grid recovery according to claim 1, characterized in that: The power consumption verification sequence refers to the calibration sequence of the power consumption of each node during power grid restoration.

8. A multi-objective optimization scheduling method for post-disaster power grid recovery according to claim 1, characterized in that: The load configuration refers to the specific power supply allocated to meet the power demand of each site or region during the power grid dispatching process.

9. A multi-objective optimization scheduling method for post-disaster power grid recovery according to claim 1, characterized in that: The capacity configuration characteristics refer to a set of key parameters related to the power supply capacity of each site in the power grid during post-disaster recovery or daily operation.

10. A multi-objective optimization scheduling system for power grid post-disaster recovery, used to execute a multi-objective optimization scheduling method for power grid post-disaster recovery as claimed in any one of claims 1 to 9, characterized in that: The dispatching system comprises: A load marking module is used to respond to the dispatching instructions for post-disaster recovery of the power grid issued by the large-scale power grid security center, scan the distribution load on the power grid energy consumption side in the large-scale power grid, and mark the dispatching load constraint of the distribution load on the power grid energy consumption side according to the scanning results and the load responsiveness of the distribution units in the dispatching instructions; A collaborative dispatching module is used to collect capacity configuration features corresponding to multiple sites when the power grid is restored after a disaster, and determine the collaborative dispatching index of the power grid energy consumption side when the power grid is restored after a disaster based on the load responsiveness in the capacity configuration features and the energy dispatching load level of multiple sites when the power grid is restored after a disaster; A power verification module is used to control the load configuration amount of energy distribution during power grid energy supply scheduling, and extract the load disturbance information of energy loads of multiple energy consumption sides when responding to energy distribution. Based on the load disturbance information and the load recovery efficiency of the power grid line after the distribution network is damaged by various levels of disasters, the power balance constraints corresponding to the load nodes of multiple sites during the post-disaster recovery of the power grid are verified to obtain a power consumption verification sequence; The automatic dispatching module is used to control the automatic dispatching sequence of the power grid energy consumption side during post-disaster power grid recovery based on the coordinated dispatching index and the power consumption verification sequence, and to optimize the load on the power grid energy consumption side.

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