A method and device for multi-level scheduling and collaborative recovery of network provinces and regions

Abstract

This invention discloses a multi-level dispatching and coordinated recovery method for power grids, provinces, and regions. It includes proposing a power grid recovery safety risk assessment index based on line recovery reliability under typhoon disasters; constructing a full-stage coordinated recovery optimization model for multi-level dispatching and coordinated recovery considering recovery safety risks; and proposing a multi-level dispatching and coordinated recovery method for power grids, provinces, and regions after a province-wide power outage during a typhoon. This invention also discloses a multi-level dispatching and coordinated recovery device for implementing the above recovery method. By assessing the risk of power grid recovery safety, this invention effectively avoids additional control costs caused by recovery safety risks. Compared to power system recovery methods that only consider transmission and distribution coordination, the method in this invention also considers recovery safety risks, choosing to perform recovery later to avoid additional control costs caused by secondary power outages during typhoon passage. This invention has faster black start and load recovery speeds, thus achieving higher net benefits in power system recovery.

Description

Technical Field

[0001] This invention relates to the field of power systems, specifically to a method and apparatus for multi-level dispatch and coordinated recovery of power grid, provincial, and local areas. Background Technology

[0002] Existing research has explored numerous power system recovery strategies after large-scale power outages, making significant contributions to the rapid recovery of power systems. However, in terms of multi-level dispatch coordinated recovery, research on a framework for multi-level dispatch coordinated recovery at the grid, provincial, and municipal levels is lacking. Specifically, existing research only explores transmission and distribution coordinated recovery, which in practice corresponds to provincial and municipal dispatch respectively. In reality, a province-wide power outage also involves grid dispatch, and the jurisdiction of dispatch at the grid, provincial, and municipal levels differs, with grid information not being bidirectionally shared. Therefore, how to coordinate dispatch at the grid, provincial, and municipal levels to achieve rapid recovery after a province-wide power outage is an urgent problem to be solved. Regarding multi-stage coordinated recovery, research on full-stage power grid recovery strategies under a multi-level dispatch coordinated recovery framework at the grid, provincial, and municipal levels is lacking. Most existing studies do not consider the full-stage recovery of the three stages: black start, network reconfiguration, and load restoration, which may lead to difficulties in coordinating recovery strategies at different stages. Furthermore, there is a lack of research on methods for assessing the safety risks of power grid recovery under typhoon disasters. Existing research either uses uncertainty handling methods or simply uses Monte Carlo sampling to simulate the safety risks of node and line recovery failures. In fact, the damage rate of power lines under typhoon disasters is related to wind speed, which also means that the safety risks of restoring each power line are different at different times, and the control costs are also different. Summary of the Invention

[0003] The main technical problem addressed by this invention is to provide a multi-level coordinated restoration method for power grid, province, and local governments that offers fast restoration speed and high net benefits after restoration, while considering the safety risks of power grid restoration. Another objective of this invention is to provide a multi-level coordinated restoration device for power grid, province, and local governments.

[0004] The technical solution adopted in this invention is as follows:

[0005] In a first aspect, the present invention provides a multi-level scheduling and collaborative recovery method for network provinces and regions, comprising the following steps:

[0006] Establish a power grid restoration safety risk assessment index based on line restoration reliability under typhoon disasters;

[0007] Based on the power grid restoration safety risk assessment indicators, a multi-level dispatching model for full-stage collaborative restoration of power grid, provincial and local governments was established to address restoration safety risks.

[0008] Based on the multi-level scheduling and full-stage collaborative recovery optimization model of the grid, province and locality, a multi-level scheduling and collaborative recovery scheme of the grid, province and locality after a major power outage in the province under a typhoon scenario is obtained.

[0009] Based on the aforementioned multi-level grid-province-regional dispatching collaborative recovery scheme, the power grid recovery strategy of multi-level grid-province-regional dispatching is carried out collaboratively for recovery.

[0010] The establishment of a power grid restoration safety risk assessment index based on line restoration reliability under typhoon disasters includes the following steps:

[0011] The temporal-spatial wind speed distribution of a typhoon is obtained by the vector sum of its moving wind speed and circulation wind speed.

[0012] Based on the temporal-spatial wind speed distribution of the typhoon, the data is corrected according to micro-topographic factors to obtain wind speed data for each line at each time step. The tower failure rate is calculated based on the wind speed data for each line at each time step, thereby obtaining the power supply reliability of the line. Finally, the recovery safety risk assessment index is calculated.

[0013] The typhoon's moving wind speed and circulation wind speed are calculated based on the Masae Miyazaki model and the Rankine model:

[0014]

[0015]

[0016] In the formula, Let be the moving wind speed of the l-th line at time t; The wind speed at which the typhoon center moves at time t; This represents the distance between the typhoon center and the l-th line at time step t; The radius of the typhoon's maximum wind speed at time step t; Let be the circulation wind speed of the typhoon along the l-th line at time t. The maximum wind speed of the typhoon at time t;

[0017] in,

[0018] In the formula, and (x) l,t ,y l,t (x) represents the latitude and longitude coordinates of the typhoon center and the l-th line at time step t, respectively. l,t ,y l,t R represents the average latitude and longitude coordinates of the first and last nodes of the line; E This is the average radius of the Earth.

[0019] The process of obtaining wind speed data for each time step along each typhoon route, based on the typhoon's temporal-spatial wind speed distribution and corrected for micro-topographical factors, includes:

[0020] Obtain the wind speed vector and v of the l-th line at time step t. l,t :

[0021]

[0022] In the formula: k l This is the terrain correction factor for the l-th route; and These are the moving wind speed and the circulating wind speed, respectively.

[0023] R l,t To determine the power supply reliability of the grid line l at time t, assuming all towers on the same transmission line are of the same type, the reliability assessment theory of series systems R is referenced. l,t The calculation formula is:

[0024]

[0025] In the formula, Let be the tower failure rate of line l at time t; The number of towers for line l;

[0026] The reliability of the power supply of the line The calculation formula is:

[0027]

[0028] In the formula, Let a be the design wind speed for line l. l The tower failure rate model coefficient for line l is taken as 0 to 0.4;

[0029] The restoration safety risk assessment index for line l is defined as follows:

[0030]

[0031] In the formula, c SR,l,t The unit safety risk control cost for the l-th line at time step t;

[0032] Define power grid restoration safety risk assessment indicators The sum of the safety risk assessment indicators for the restoration of each line:

[0033]

[0034] In the formula, N line denoted as the total number of power grid lines; T represents the total number of recovery time steps.

[0035] The network-province-region multi-level scheduling full-stage collaborative recovery optimization model has a multi-layer structure, including a middle-layer sub-model, an upper-layer sub-model, and a lower-layer sub-model.

[0036] The intermediate sub-model is used to formulate the recovery strategy for network surveys;

[0037] The upper-level sub-model is used to formulate the provincial-level recovery strategy;

[0038] The upper-level sub-model is used to formulate the recovery strategy for the geological survey.

[0039] The intermediate sub-model uses the provincial adjustment recovery net income f. SD Maximize the objective function; f SD Based on the revenue from the restoration of generating units by the provincial dispatch center Provincial Dispatch Restoration Load Revenue Provincial grid restoration benefits and the cost of restoring security risk control It is confirmed that its expression is:

[0040]

[0041]

[0042]

[0043]

[0044] In the formula, To restore the net revenue per unit of power generation at the nth node of the provincial power grid; The restored generating power of the generator at the nth node of the provincial dispatch center; The net revenue per unit load restored to the nth node of the provincial power dispatch system; Δt represents the restored load power of the nth node of the provincial dispatch center; Δt is the time interval between adjacent restoration steps. and The net revenue was restored for both provincial regulation points and line units; and These represent the number of nodes and lines in the provincial dispatch center, respectively. and These are the recovery status variables for the nth node and the lth line of the provincial dispatch center, respectively. A value of 1 and 0 indicate that the line has been restored and has not been restored, respectively. and These are the provincial regulation point connectivity index and the shortest node connectivity distance index, respectively. This refers to the line's power transmission capacity.

[0045]

[0046]

[0047]

[0048] In the formula, and These are the sets of provincial grid nodes that contain and do not contain node n, respectively. The binary coefficients for connectivity between nodes i and j are denoted by 1, where a value of 1 indicates that nodes i and j are connected. Let i be the shortest connected distance between nodes i and j; This represents the upper limit of the transmission power that line l can carry; Let be the number of times the shortest electrical path connecting nodes i and j passes through line l; where, This is called the weighted power flow betweenness of line l;

[0049] The constraints of the mid-level sub-model include black start constraints, network reconfiguration constraints, load recovery constraints, active power balance constraints, and power flow constraints.

[0050] The black start constraint is specifically as follows:

[0051]

[0052]

[0053]

[0054]

[0055]

[0056]

[0057] In the formula, This refers to the startup time of a non-blackout power supply. This refers to the time required for a non-black-start power supply to reach its rated power from startup. The power required for starting a non-black start power supply; This refers to the rated power of a non-black start power supply. and These are the upper and lower limits of the startup time for a non-black start power supply; and These are binary variables reflecting the startup status of non-black start power supplies and black start power supplies, respectively, with 1 indicating that it has been started; This refers to the startup time of the black-start power supply; This is the set of lines connected to node n in the provincial data transfer.

[0058] The network reconstruction constraints are specifically as follows:

[0059]

[0060]

[0061]

[0062] In the formula, This is a binary variable representing the recovery status of line l, where 1 indicates that recovery has been achieved. This represents the set of lines connected to line p; The set of lines connected to node n;

[0063] The load recovery constraint is specifically as follows:

[0064]

[0065]

[0066]

[0067] In the formula, and These represent the restored load power and the load power to be restored at node n, respectively. This refers to the set of nodes containing non-flexible loads. This is a binary variable representing the load recovery status of node n, where 1 indicates that the node's load has begun to recover.

[0068] The active power balance constraint is specifically as follows:

[0069]

[0070] In the formula, The power supply for black start-up; and These are the charging and discharging power of the energy storage device at provincial regulation point n, respectively. This represents the interaction power between the provincial dispatch center and the grid dispatch center. A positive value indicates that the provincial dispatch center provides power to the grid dispatch center, while a negative value indicates that the provincial dispatch center requests power support from the grid dispatch center.

[0071] The upper-level sub-model uses the net profit f from network survey recovery. WD Maximize the objective function; f WD Revenue from unit power generation restored by grid dispatch Network adjustment and grid restoration revenue And the cost of network restoration and security risk control It is confirmed that its expression is:

[0072]

[0073]

[0074]

[0075] In the formula, To restore the net revenue per unit of power generation of the nth node in the grid dispatching system; This represents the restored generating power of the generator at the nth node of the network dispatching system. and The net revenue was restored for network regulation points and line units, respectively. and These represent the number of nodes and lines in the network survey, respectively. and These are the recovery status variables for the nth node and the lth line in the network survey, respectively. A value of 1 and 0 indicate that the network has recovered and has not recovered, respectively. and These are the network adjustment point connectivity index and the shortest node connectivity distance index, respectively. Their specific expressions are as follows: and The expression is similar; This is an indicator of the transmission power capacity of a line, and its specific expression is the same as... The expression is similar;

[0076] The constraints of the upper-level sub-model include black-start constraints, network reconfiguration constraints, active power balance constraints, and power flow constraints. The black-start and network reconfiguration constraints of the upper-level sub-model are similar to those of the middle-level sub-model, respectively. The active power balance constraints are as follows:

[0077]

[0078] In the formula, This refers to the power that the power grid borrows from other provinces. This represents the interaction power between the grid dispatch center and the provincial dispatch center. A positive value indicates that the grid dispatch center provides power to the provincial dispatch center, while a negative value indicates that the grid dispatch center requests power support from the provincial dispatch center.

[0079] The lower-level sub-model uses the ground survey to recover net revenue. Maximize the objective function; Net revenue based on regional dispatch load recovery The benefits of the geological survey network restoration and the cost of restoring safety risk control It is confirmed that its expression is:

[0080]

[0081]

[0082]

[0083] In the formula, Let d be the number of nodes in the d-th local survey. Let n be the unit load recovery revenue of the d-th local adjustment point n; The load recovery power of the d-th ground control point n at time step t; The unit penalty cost is the difference between the load power restored by the d-th regional dispatch and the load power expected to be restored by the provincial dispatch. and These are the recovery status variables for the d-th dispatch center, the n-th node, and the l-th line, respectively. Values ​​of 1 and 0 indicate that the line has been restored and has not been restored, respectively. and Let be the connectivity index of the d-th adjustment point and the shortest connectivity distance index of the node, respectively. Their specific expressions are as follows: and The expression is similar; This is an indicator of the transmission power capacity of a line, and its specific expression is the same as... The expression is similar;

[0084] The constraints of the lower-level sub-model include network reconfiguration constraints, load recovery constraints, active power balance constraints, and power flow constraints. The network reconfiguration and load recovery constraints of the lower-level sub-model are similar to those of the middle-level sub-model, respectively. The active power balance constraints are as follows:

[0085]

[0086] In the formula, and These are the charging and discharging powers of the energy storage device at the d-th ground control point n, respectively. This represents the interaction power between the d-th regional dispatch center and the superior provincial dispatch center. A positive value indicates that the regional dispatch center provides power to the provincial dispatch center, while a negative value indicates that the regional dispatch center requests power support from the provincial dispatch center.

[0087] Conditional Value at Risk (CVaR) is used to modify the three-layer sub-model to address uncertainties in wind speed and load forecasting; the objective function f of the modified three-layer sub-model is... SD,rev f WD,rev and They are respectively:

[0088]

[0089]

[0090]

[0091] In the formula, and The CVaR of the provincial survey, the network survey, and the d-th regional survey are respectively; γ SD γ WD and These are the risk weight coefficients for the provincial survey, the network survey, and the d-th regional survey, respectively.

[0092] CVaR is defined as the average loss of a portfolio over a given investment period when the risk of loss exceeds the Value at Risk (VaR) at a given confidence level. Converting the average loss into a return function yields the formula for calculating CVaR.

[0093]

[0094]

[0095]

[0096] In the formula, and These are the VaR values ​​for provincial, network, and regional surveys, respectively; N SCE The number of random scenes; and These represent the probabilities of the nth scenario occurring in the provincial survey, network survey, and local survey, respectively. These represent taking the larger value within the parentheses; and The confidence levels are given for the provincial survey, the national survey, and the regional survey, respectively. and Let be the net recovery benefit after considering CVaR in the nth random scenario of provincial, network, and regional surveys, respectively, with the specific expressions as follows:

[0097]

[0098]

[0099]

[0100] In the formula, and These are the additional control unit prices generated by the typhoon wind speed forecast errors of the provincial, national, and regional dispatch centers, respectively. and These are the additional control unit prices generated by load forecasting errors at the provincial, grid, and regional dispatching levels, respectively. and These represent the typhoon wind speed prediction errors at time t for the lth line of the provincial, national, and regional dispatch systems, respectively. and These represent the load forecasting errors at time step t for the nth node of the provincial, grid, and regional dispatch centers, respectively.

[0101] The method of collaboratively restoring the power grid recovery strategy based on the multi-level dispatching scheme of the grid, province, and locality includes:

[0102] Collect the load power prediction matrix of each local dispatch center at each time step, construct the provincial dispatch center's initial recovery optimization sub-model, and solve to obtain the initial full-stage recovery strategy of the 220kV transmission network under the jurisdiction of the provincial dispatch center.

[0103] Based on the initial full-stage recovery strategy of the 220kV transmission network under the jurisdiction of the provincial dispatch center, the provincial dispatch center transmits the guaranteed recovery time step to the grid dispatch center; at the same time, the provincial dispatch center transmits all the guaranteed recovery time step matrix and load power matrix to each local dispatch center.

[0104] Solve the upper-level sub-model; add a bottom-line recovery constraint for the network-province coupling node based on the upper-level sub-model, and then solve the upper-level sub-model to obtain the black start and network recovery strategy of the 500kV transmission network under the jurisdiction of the grid dispatching department;

[0105] Based on the black start and grid restoration strategy of the 500kV transmission network under the jurisdiction of the grid dispatch center, the grid dispatch center will feed back the final restoration time step matrix and the unit power matrix available at each time step to the provincial dispatch center.

[0106] Solve the lower-level sub-model; add provincial and local coupling node bottom-line recovery constraints on the lower-level sub-model, and then solve the lower-level sub-model to obtain the network reconfiguration and load recovery strategies of the 110kV distribution networks under the jurisdiction of each dispatching authority;

[0107] Based on the network reconfiguration and load restoration strategies of the 110kV distribution networks under the jurisdiction of each dispatch center, each dispatch center feeds back the load power matrix of their actual restoration at each time step to the provincial dispatch center;

[0108] After receiving feedback from the grid dispatch and the local dispatch, the provincial dispatch center adds constraints on the available generating power of the grid dispatch and the actual restored load power of the local dispatch to the intermediate-level sub-model, and continues to solve the intermediate-level sub-model to obtain the final full-stage recovery strategy of the 220kV transmission network under the jurisdiction of the provincial dispatch center.

[0109] On the other hand, the present invention also provides a multi-level scheduling and collaborative recovery device for network provinces and regions, including a risk assessment module, a model building module, a scheme formulation module and a strategy recovery module;

[0110] The risk assessment module is used to establish a power grid restoration safety risk assessment index based on line restoration reliability under typhoon disasters;

[0111] The model building module establishes a multi-level scheduling, full-stage collaborative recovery optimization model for power grid, province, and local governments to address recovery security risks, based on power grid recovery security risk assessment indicators.

[0112] The scheme formulation module, based on the multi-level scheduling and full-stage collaborative recovery optimization model of the grid, province and locality, obtains the multi-level scheduling and collaborative recovery scheme of the grid, province and locality after a major power outage in the province under the typhoon scenario;

[0113] The strategy recovery module, based on the multi-level grid-province-regional dispatch collaborative recovery scheme, performs collaborative recovery of the power grid recovery strategy of the multi-level grid-province-regional dispatch.

[0114] Beneficial effects:

[0115] This invention conducts a risk assessment of power grid restoration safety. Based on the typhoon's movement path, it obtains the temporal-spatial wind speed distribution of the typhoon at different times in different regions. When the wind speed is too high, the restoration safety risk is significant, and forcibly restoring lines will cause secondary power outages. Therefore, risk assessment of power grid restoration safety effectively avoids the additional control costs caused by restoration safety risks. Furthermore, a three-level optimization model for multi-level dispatch and full-stage collaborative restoration is established in provinces and regions with low restoration safety risks. Based on the optimization model, a multi-level dispatch and collaborative restoration method is proposed. The multi-level dispatch and collaborative restoration method includes the coordination of grid dispatch, provincial dispatch, and regional dispatch during the power system restoration process. Grid dispatch can restore from the bottom up with the help of provincial dispatch, and provincial dispatch can also provide power support from the top down with the power generation already restored by grid dispatch. Compared with power system restoration methods that only consider transmission and distribution coordination, the method in this invention also considers restoration safety risks, choosing to restore later to avoid additional control costs caused by secondary power outages during typhoon passage. This invention has faster black start and load restoration speeds, thus achieving higher net benefits of power system restoration. Attached Figure Description

[0116] Figure 1 This is a schematic diagram of the overall process of the present invention;

[0117] Figure 2 This is a diagram of the actual power grid topology of a province in China.

[0118] Figure 3 A map showing the typhoon wind speed and recovery safety risk for each route at each time point;

[0119] Figure 4 Diagram of the 500kV grid restoration strategy for grid commissioning;

[0120] Figure 5 Diagram showing the 110kV grid restoration strategy for partial geological surveys;

[0121] Figure 6 For network power saving interaction strategy diagram;

[0122] Figure 7 This is a diagram showing the provincial load recovery strategy for regional surveys #43 and #299. Detailed Implementation

[0123] This invention proposes a multi-level scheduling and collaborative recovery method for network, province, and region, such as... Figure 1 As shown, the implementation process includes the following detailed steps:

[0124] Step 1: Establish a power grid restoration safety risk assessment index based on line restoration reliability under typhoon disasters.

[0125] During typhoon conditions, the China Typhoon Path website provides historical temporal and spatial data and forecasts for typhoons, but wind speed information is limited to the typhoon center and its wind circle. After a province-wide power outage, the distances of the power grid lines from the typhoon center vary across the province. To assess the reliability and safety risks of power restoration, it is necessary to know the wind speed data for each line at various time points. The wind speed of each line depends on a circle centered on the typhoon center. Therefore, this invention obtains the temporal and spatial wind speed distribution of the typhoon based on the vector sum of moving wind speed and circulating wind speed, and corrects for it by considering micro-topographical factors, thereby obtaining more accurate wind speed data for each line at each time point.

[0126] First, the moving wind speed and circulation wind speed of the typhoon are obtained according to the Miyazaki Masayoshi model and the Rankine model, respectively, as shown in equations (1)-(2).

[0127]

[0128]

[0129] In the formula, Let be the moving wind speed of the l-th line at time t; The wind speed at which the typhoon center moves at time t; This represents the distance between the typhoon center and the l-th line at time step t; The radius of the typhoon's maximum wind speed at time step t; Let be the typhoon circulation wind speed of the l-th line at time t; The maximum wind speed of the typhoon at time t. The specific expression is shown in equation (3):

[0130]

[0131] In the formula, and (x) l,t ,y l,t (x) represents the latitude and longitude coordinates of the typhoon center and the l-th line at time step t, respectively. l,t ,y l,t Take the average latitude and longitude coordinates of the first and last nodes of the route; R E This is the average radius of the Earth.

[0132] Based on the moving wind speed and the circulating wind speed, and considering the influence of the terrain on the wind speed, the wind speed vector and v of the l-th line at time step t can be obtained. l,t As shown in equation (4):

[0133]

[0134] In the formula: k l This is the terrain correction factor for the l-th route; and These are the moving wind speed and the circulation wind speed, respectively. The moving wind speed is in the same direction as the typhoon's movement; the circulation wind speed has an inward deflection angle between its direction and the counterclockwise tangential direction of the circular symmetrical line, which is generally taken as an approximation of 20°.

[0135] Because typhoon paths can shift, wind speeds vary in the same area at different times, and even between different areas at the same time. When wind speeds are excessively high, the risk of power restoration is significant, and forcibly restoring power lines could cause secondary power outages, leading to unnecessary control costs. Therefore, this invention assesses the risk of power restoration safety using a line restoration reliability index based on tower failure rates.

[0136] First, define R. l,t Let R be the power supply reliability of the grid line l at time t. Since a transmission line usually has multiple towers, assuming that the towers of the same line are of the same type, then R is defined according to the reliability assessment theory of series systems. l,t For equation (5):

[0137]

[0138] In the formula, Let be the tower failure rate of line l at time t; The number of poles and towers for line l.

[0139] During typhoon weather, the failure rate of transmission line towers will increase significantly with the increase of the wind speed they are subjected to. The faults of transmission lines are mostly manifested as structural failures such as tower collapse and tower breakage. v obtained from equation (4) l,t and the design wind speed of line l The relevant curve can be fitted by an exponential curve function, as shown in equation (6).

[0140]

[0141] In the formula, a l The tower failure rate model coefficient for line l is generally taken as 0 to 0.4.

[0142] Based on this, the restoration safety risk assessment index for line l is defined as shown in equation (7), and the restoration safety risk assessment index for the power grid is further defined. The sum of the safety indicators for each line is shown in (8).

[0143]

[0144]

[0145] In the formula, c SR,l,t The unit safety risk control cost for the l-th line at time step t; N line denoted as the total number of power grid lines; T represents the total number of recovery time steps.

[0146] Step 2: Based on the power grid restoration safety risk assessment indicators, establish a multi-level dispatching full-stage collaborative restoration optimization model for power grid, province and local governments to restore safety risks.

[0147] The middle-level sub-model uses provincial adjustment to restore net income f SD Maximize the objective function f SD Revenue from the restoration of generating units by the provincial dispatch center Provincial Dispatch Restoration Load Revenue Provincial grid restoration benefits and the cost of restoring security risk control Related to. SD , and The expressions are shown in equations (9)-(12) respectively. The expression is shown in equation (7).

[0148]

[0149]

[0150]

[0151]

[0152] In the formula, To restore the net revenue per unit of power generation at the nth node of the provincial power grid; The restored generating power of the generator at the nth node of the provincial dispatch center; The net revenue per unit load restored to the nth node of the provincial power dispatch system; Δt represents the restored load power of the nth node of the provincial dispatch center; Δt is the time interval between adjacent restoration steps. and The net revenue was restored for both provincial regulation points and line units; and These represent the number of nodes and lines in the provincial dispatch center, respectively. and These are the recovery status variables for the nth node and the lth line of the provincial dispatch center, respectively, with values ​​of 1 and 0 indicating that the system has recovered and has not recovered, respectively. and These are the provincial regulation point connectivity index and the shortest node connectivity distance index, respectively, and their specific expressions are shown in equations (13)-(14); The line carrying power transmission capacity index is expressed in Equation (15).

[0153]

[0154]

[0155]

[0156] In the formula: and These are the sets of provincial grid nodes that contain and do not contain node n, respectively. The binary coefficients for connectivity between nodes i and j are denoted by 1, where a value of 1 indicates that nodes i and j are connected. The shortest connection distance between nodes i and j can be represented by the sum of the line reactance of the shortest path; This represents the upper limit of the transmission power that line l can carry; Let be the number of times the shortest electrical path connecting nodes i and j passes through line l. This is called the weighted power flow betweenness of line l.

[0157] The constraints of the mid-level sub-model include black start constraints, network reconfiguration constraints, load recovery constraints, active power balance constraints, and power flow constraints.

[0158] The black start constraints are shown in equations (16)-(21). Equation (16) reflects the relationship between the restored power generation and time of the non-black start power source; Equation (17) expresses the cold and hot start time constraints of the non-black start power source; Equation (18) indicates that the necessary condition for the recovery of the non-black start power source is that the node it is located in has been restored; Equations (19)-(20) respectively indicate that the black start power source can be started immediately after the disaster and that the node it is located in can be restored immediately; Equation (21) indicates that the line connected to the node where the black start power source is located can be restored after its start.

[0159]

[0160]

[0161]

[0162]

[0163]

[0164]

[0165] In the formula, This refers to the startup time of a non-blackout power supply. This refers to the time required for a non-black-start power supply to reach its rated power from startup. The power required for starting a non-black start power supply; This refers to the rated power of a non-black start power supply. and These are the upper and lower limits of the startup time for a non-black start power supply; and These are binary variables reflecting the startup status of non-black start power supplies and black start power supplies, respectively, with 1 indicating that it has been started; This refers to the startup time of the black-start power supply; This is the set of lines connected to node n in the provincial data transfer.

[0166] The network reconfiguration constraints are shown in equations (22)-(24). Equation (22) indicates that the provincial regulation point and the line will not lose power again after restoration, and the prerequisite for line restoration is that an adjacent line has been restored in the previous time step; Equation (23) indicates that the sufficient condition for a line to be restored is that both of its two ends are restored; Equation (24) indicates that the necessary condition for a node to be restored is that at least one line connected to it has been restored.

[0167]

[0168]

[0169]

[0170] In the formula, This is a binary variable representing the recovery status of line l, where 1 indicates that recovery has been achieved. This represents the set of lines connected to line p; This is the set of lines connected to node n.

[0171] The load recovery constraints are shown in equations (25)-(27). Equation (25) indicates that the load connected to node n can only be recovered after the node is recovered; Equation (26) indicates the relationship between load recovery power and load recovery state, and also reflects the discreteness of load recovery (i.e., after a node is recovered, all its subordinate loads are recovered); Equation (27) indicates the load recovery state constraint for non-flexible loads.

[0172]

[0173]

[0174]

[0175] In the formula, and These represent the restored load power and the load power to be restored at node n, respectively. This refers to the set of nodes containing non-flexible loads. This is a binary variable representing the load recovery status of node n, where 1 indicates that the node's load has begun to recover.

[0176] To ensure frequency stability during the recovery process, the power grid under the jurisdiction of the provincial dispatch center needs to meet the active power balance constraint, as shown in equation (28). It should be noted that during typhoon disasters, photovoltaic power plants have no output due to cloudy and rainy weather, and since typhoon wind speeds usually exceed the typhoon cutoff wind speed, wind power plants also have no output. Therefore, the active power balance constraint shown in equation (28) does not include wind power and photovoltaic power output.

[0177]

[0178] In the formula, The power supply for black start-up; and These represent the charging and discharging power of the energy storage device at node n, respectively. This represents the interaction power between the provincial dispatch center and the grid dispatch center. A positive value indicates that the provincial dispatch center provides power to the grid dispatch center, while a negative value indicates that the provincial dispatch center requests power support from the grid dispatch center.

[0179] The 500kV grid under the jurisdiction of the grid dispatch center is typically not directly connected to loads, but it has large non-black-start generating units. Furthermore, the grid dispatch center can perform black starts by borrowing power from neighboring provinces; therefore, nodes coupled with neighboring provinces can be considered black-start nodes. In this context, the upper-level sub-model uses the grid dispatch center's net recovery benefit f. WD Maximize the objective function f WD Revenue from unit power generation restored by grid dispatch Network adjustment and grid restoration revenue And the cost of network restoration and security risk control Related to. WD , and The expressions are shown in equations (29)-(31) respectively. The expression is shown in equation (7).

[0180]

[0181]

[0182]

[0183] In the formula, To restore the net revenue per unit of power generation of the nth node in the grid dispatching system; This represents the restored generating power of the generator at the nth node of the network dispatching system. and The net revenue was restored for network regulation points and line units, respectively. and These represent the number of nodes and lines in the network survey, respectively. and These are the recovery status variables for the nth node and the lth line in the network survey, respectively, with values ​​of 1 and 0 indicating that the network has recovered and has not recovered, respectively. and These are the network adjustment point connectivity index and the shortest node connectivity distance index, respectively, and their specific expressions are similar to those of equations (13)-(14); The line carrying power transmission capacity index is expressed in a similar way to equation (15).

[0184] The constraints of the upper-level sub-model include black start constraints, network reconfiguration constraints, active power balance constraints, and power flow constraints. Among them, the black start constraints and network reconfiguration constraints are similar to equations (16)-(21) and (22)-(24), respectively; the active power balance constraints are shown in equation (32).

[0185]

[0186] In the formula, This refers to the power that the power grid borrows from other provinces. This represents the interaction power between the grid dispatch center and the provincial dispatch center. A positive value indicates that the grid dispatch center provides power to the provincial dispatch center, while a negative value indicates that the grid dispatch center requests power support from the provincial dispatch center.

[0187] The 110kV distribution network under the jurisdiction of the regional dispatch center typically lacks large-scale non-black-start power sources. Therefore, the regional dispatch center usually does not include the black-start phase, and it needs to meet the load restoration needs of the provincial dispatch center as much as possible. Furthermore, since there is no wind or solar power output during typhoon disasters, the regional dispatch center can assist with black-start through energy storage power stations. In this context, taking the d-th regional dispatch center as an example, the lower-level sub-model uses the regional dispatch center's net recovery revenue... Maximize the objective function. Net income from load recovery Revenue from space frame restoration and the cost of restoring security risk control related. and The expressions are shown in equations (33)-(35) respectively. The expression is shown in equation (7).

[0188]

[0189]

[0190]

[0191] In the formula, Let d be the number of nodes in the d-th local survey. Let n be the unit load recovery revenue of the d-th local adjustment point n; The load recovery power of the d-th ground control point n at time step t; The unit penalty cost is the difference between the load power restored by the d-th regional dispatch and the load power expected to be restored by the provincial dispatch. and These are the recovery status variables for the d-th dispatch center, the n-th node, and the l-th line, respectively. Values ​​of 1 and 0 indicate that the line has been restored and has not been restored, respectively. and These are the connectivity index of the d-th adjustment point and the shortest connectivity distance index of the node, respectively. Their specific expressions are similar to those in equations (13)-(14). The line carrying power transmission capacity index is expressed in a similar way to Equation (15).

[0192] The constraints of the lower-level sub-model include network reconfiguration constraints, load recovery constraints, active power balance constraints, and power flow constraints. Among them, the network reconfiguration constraints and load recovery constraints are similar to equations (22)-(24) and (25)-(27), respectively; the active power balance constraints are shown in equation (36).

[0193]

[0194] In the formula, and These are the charging and discharging powers of the energy storage device at the d-th ground control point n, respectively. This represents the interaction power between the d-th regional dispatch center and the superior provincial dispatch center. A positive value indicates that the regional dispatch center provides power to the provincial dispatch center, while a negative value indicates that the regional dispatch center requests power support from the provincial dispatch center.

[0195] CVaR is defined as the average loss of an investment portfolio over a given investment period when the risk loss is higher than the Value at Risk (VaR) at a given confidence level. Taking the mid-level recovery sub-model as an example, considering that the objective function is to maximize the recovery return, the average loss is converted into a return function, and the CVaR solution formula is shown in equation (37).

[0196]

[0197] In the formula, and These are CVaR and VaR, respectively; N SCE The number of random scenes; Let n be the probability of the nth scenario occurring. Indicates taking 0 and The larger value; For a given confidence level; The net recovery benefit after considering CVaR in the nth random scenario is the net recovery benefit of the provincial dispatch center minus the control costs caused by the uncertainty of wind speed forecast and load forecast. The specific expression is shown in Equation (38):

[0198]

[0199] In the formula, and These are the additional control unit prices generated by typhoon wind speed prediction errors and load prediction errors, respectively. and These represent the typhoon wind speed prediction error and load prediction error at time step t for the l-th line and n-th node of the provincial dispatching system.

[0200] Based on this, by introducing the risk weight coefficient γ SD The objective function f of the middle-layer sub-model after CVaR correction is obtained. SD,rev As shown in equation (39). Similarly, the risk weight coefficient γ of the network survey and the d-th local survey is introduced. WD and CVaR values ​​based on network survey and the d-th local survey and The objective function f obtained after CVaR correction of the upper and lower sub-models is obtained. WD,rev and As shown in equations (40)-(41) respectively.

[0201]

[0202]

[0203]

[0204] Step 3: Based on the multi-level scheduling full-stage collaborative recovery optimization model of the grid, province and locality, obtain the multi-level scheduling collaborative recovery scheme of the grid, province and locality after a major power outage in the province under the typhoon scenario. Based on the multi-level scheduling collaborative recovery scheme of the grid, province and locality, carry out collaborative recovery of the power grid recovery strategy of the multi-level scheduling of the grid, province and locality.

[0205] Based on the respective functions and jurisdictions of the multi-level dispatching systems (grid, province, and prefecture), each level only possesses grid and load information within its own jurisdiction. However, a subordinate relationship exists between higher and lower-level dispatching systems; that is, the grid dispatching system can request information from the provincial dispatching system, and the provincial dispatching system can request information from the prefecture dispatching system. Against this backdrop, based on the aforementioned three-layer recovery optimization sub-model for multi-level dispatching, a collaborative recovery optimization method for multi-level dispatching systems (grid, province, and prefecture) after a province-wide major power outage is proposed. The specific steps are as follows:

[0206] Step 31, Provincial Transfer Direction Each regional dispatch center collects the power prediction matrix of the load to be restored at each time step:

[0207] Based on this, the provincial dispatch center does not consider power interaction with the grid dispatch center, i.e., it performs independent recovery. It constructs an optimization sub-model for the initial recovery of the provincial dispatch center and solves the initial full-stage recovery strategy of the 220kV transmission network under the jurisdiction of the provincial dispatch center.

[0208] Step 32: Based on the initial full-stage recovery strategy for the 220kV transmission network under the provincial dispatch center obtained in Step 1, the provincial dispatch center will... The guaranteed recovery time-step matrix for each network-province coupled node:

[0209] The data was transmitted to the network survey team; simultaneously, the provincial survey team transmitted all of it. The guaranteed recovery time-step matrix of each province-level coupled node And the load power matrix that the provincial dispatch center expects local dispatch centers to restore at each time step. It is transmitted to various local survey centers.

[0210] Step 33: Solve the upper-level sub-model. This is because the network dispatch center receives the network-province coupled node backup recovery time-step matrix transmitted from the provincial dispatch center. Therefore, based on the upper sub-model, the grid-province coupling node bottom-line recovery constraint shown in equation (42) is added. That is, if the node cannot be recovered before the bottom-line recovery time of the provincial dispatch, then after the bottom-line recovery time, the node can be used as a black start power source node to help the grid dispatch recover from bottom to top. Then, by solving the upper sub-model, the black start and grid recovery strategies of the 500kV transmission network under the jurisdiction of the grid dispatch can be obtained.

[0211]

[0212] Step 34: Based on the black start and grid restoration strategies for the 500kV transmission network under the jurisdiction of the grid dispatching authority obtained in Step 3, the grid dispatching authority will... The final recovery time step matrix of each network province coupled node:

[0213] And the unit power matrix available for grid dispatch at each time step. Feedback was sent to the provincial survey center.

[0214] Step 35: Solve the lower-level sub-model. This is because the regional survey receives the provincial-regional coupling node backup recovery time-step matrix transmitted from the provincial survey. Therefore, based on the lower-level sub-model, the provincial-local coupling node guaranteed recovery constraint shown in Equation (43) is added. That is, if the node cannot be recovered before the provincial dispatch guaranteed recovery time, then after the guaranteed recovery time, the node can be used as a black start power supply node to help the local dispatch restore the network structure from top to bottom. Then, by solving the lower-level sub-model, the network reconfiguration and load recovery strategies of the 110kV distribution network under the jurisdiction of each dispatch can be obtained.

[0215]

[0216] In the formula, Let be the binary variable representing the recovery state of the d-th local and provincial dispatching nodes at time step t.

[0217] Step 36: Based on the network reconfiguration and load restoration strategies of the 110kV distribution networks under the jurisdiction of each dispatching station obtained in Step 5, each dispatching station will determine the actual load power matrix restored at each time step. Feedback has been sent to the provincial survey center.

[0218] Step 37: The provincial survey receives feedback from the network survey and the regional survey. and Subsequently, based on the intermediate-level sub-model, the available generating power constraints of the grid dispatching system and the actual restored load power constraints of the local dispatching system, as shown in equations (44)-(45), are added. Continuing to solve the intermediate-level sub-model yields the final full-stage recovery strategy for the 220kV transmission network under the jurisdiction of the provincial dispatching system. Specifically, the available generating power constraints of the grid dispatching system and the actual restored load power constraints of the local dispatching system are as follows:

[0219]

[0220]

[0221] In the formula, This refers to the generating capacity of the unit that the grid dispatch can provide at time step t.

[0222] This invention uses a real power grid from a province in China for example analysis, and its structure diagram is shown below. Figure 2 As shown in the figure. In this example system, there are power grids with three voltage levels: 500kV, 220kV, and 110kV, which are managed by the national grid dispatch center, the provincial dispatch center, and the regional dispatch center, respectively. Two regional dispatch distribution networks are shown in the figure for illustration. The restoration of 110kV and below substations and lines is not considered for the time being. It is assumed that after the 110kV substation is restored, the grid structure and loads of its subordinate voltage levels can be connected to the grid.

[0223] Based on the typhoon's path, the wind speed of each power grid line at each time step can be calculated using the typhoon's time-space wind speed distribution model, and thus the recovery safety risk of each line at each time step can be determined. Figure 3 The typhoon wind speeds and recovery safety risks for each route at each time step are given. Figure 3It is known that as the typhoon moves and its central wind speed and wind circle radius change, the typhoon wind speed on the same line at different time steps, and even on different lines at the same time step, will vary. A more detailed analysis will be conducted using lines #232-379, #37-38, #15-286, and #10-11 as examples. Specifically, line #232-379 is located at the typhoon's landfall point. Around time step 11, the typhoon's wind circle center is closest to this line, therefore, the wind speed on this line reaches 29.1 m / s, exceeding the line's design wind speed of 23.5 m / s, thus posing a 7% risk of recovery. Line #37-38 is located inland, far from the typhoon's path, therefore its wind speed remains below 11.2 m / s, posing no risk of recovery. Line #15-286 is located in the middle of the typhoon's path. At point #10, the typhoon passed through the line roughly between time steps 18 and 33. Due to the overlap between the typhoon's wind circle and the line, there were two peak wind speeds, with the highest reaching 34.5 m / s, corresponding to a recovery safety risk of 32.1%. Lines #10-11 were located at the end of the typhoon's path, with a maximum wind speed of 32.4 m / s. However, because they are 500kV lines with a design wind speed of 27 m / s, higher than 200kV lines, their recovery safety risk was only 4.6%. In summary, the typhoon temporal-spatial wind speed distribution model proposed in this invention can accurately calculate line wind speeds and assess recovery safety risks.

[0224] Figure 4 The restoration strategy for the 500kV network under the jurisdiction of the network dispatching department is given, where yellow backgrounds indicate black-start nodes, and the numbers in parentheses indicate the restoration time steps of the black-start nodes. Figure 4 It is known that the neighboring province's coupling nodes acted as black-start power sources after the province-wide blackout, with the grid dispatch center borrowing power from neighboring provinces for black-start operations. Nodes 4, 12, and 18 were successfully restored by the provincial dispatch center in the first time step; therefore, these nodes also became black-start nodes for the grid dispatch center from the second time step onwards, with the provincial dispatch center assisting the grid dispatch center in restoring the network structure from the bottom up. In the first four time steps, 87.2% of the 500kV network lines had been restored. The remaining lines #13-14, #18-19, #16-17, #8-9, #13-16, and #118-12 were restored in time steps 23, 24, 32, 36, 38, and 43, respectively. This is because these pink-marked lines are located in the typhoon's path; if restored too early, they could cause secondary power outages when the typhoon passes through them due to the higher safety risks, resulting in significant control costs. Furthermore, since the nodes at both ends of these lines had already been restored via other green lines, the restoration of these lines was not urgent. Therefore, by delaying the restoration of these lines until a time when the safety risk is lower, the control costs during the restoration process can be effectively reduced, thereby increasing the net benefits of restoration.

[0225] The following analysis examines the 220kV grid restoration strategies under the jurisdiction of the provincial dispatch center. Since the province comprises 16 cities, the restoration strategies for four typical cities are selected for demonstration: RZ11 (which lacks a black-start power source and is far from the typhoon's path), YT6 (which lacks a black-start power source and is located in the typhoon's path), JN1 (which has a black-start power source and is far from the typhoon's path), and QD2 (which has a black-start power source and is located in the typhoon's path). Their grid restoration strategies are shown in Table 1. As shown in Table 1, RZ11, lacking a black start power source, only received assistance from node 233 of WF7 to restore the first node 223 at step 9, and the network structure restoration for that city was completed at step 13. JN1 has a black start power source located at node 360, and its geographical location is far from the typhoon path, so its restoration safety risk is low, and the network structure of that city was successfully restored at step 7. YT6 itself does not have a black start power source, but the black start power source node 374 of the adjacent city WH10 is connected to node 12 of that city, so it can use the black start power source of WH10 to restore the network structure. However, YT6 is located at the end of the typhoon path, and in order to reduce the additional control costs caused by restoration safety risks, node 11 was not restored until step 43. Similarly, QD2 is located in the middle of the typhoon path, and it restores the network structure through black start power source node 377, and node 14 was not restored until step 39 due to restoration safety risks.

[0226] Table 1. Specific restoration strategies for the 16 cities and prefectures of the provincial 220kV power grid.

[0227]

[0228] Each 220kV node is connected to a 110kV grid under the jurisdiction of the local dispatch center. This invention uses the 110kV grids under nodes 79 and 299 as examples to illustrate the local dispatch center's restoration strategy. Figure 5 As shown. For Dispatch 79, since the Provincial Dispatch only restores the Provincial-Local Coupled Node 79 in the 5th time step, Dispatch 79 cannot assist in its restoration from top to bottom through the Provincial Dispatch. Therefore, Dispatch 79 uses the energy storage devices of nodes 17 and 18 as black start power sources for grid restoration, and the grid restoration is completed after 4 time steps. For Dispatch 299, the Provincial Dispatch restores the Provincial-Local Coupled Node 299 in the second time step. Therefore, Dispatch 299 can start from the second time step, using the Provincial-Local Coupled Node 1 as a black start power source, and assist in its restoration from top to bottom through the Provincial Dispatch.

[0229] Table 2 presents the provincial dispatch's guaranteed recovery time step and the actual recovery time step for each node in the 500kV grid. As shown in Table 2, 83.3% of the 500kV nodes were restored before the provincial dispatch's guaranteed recovery time step, meaning the grid was restored by borrowing power from neighboring provinces through coupling nodes. Nodes 4, 5, 12, 18, 23, and 28 were restored through the provincial dispatch's guaranteed recovery. This demonstrates that after the provincial dispatch reports node recovery information to the grid dispatch, the grid dispatch can formulate a guaranteed recovery strategy based on its own grid recovery status. For nodes that are relatively remote and cannot be restored in time, the grid dispatch can use the provincial dispatch's guaranteed recovery to achieve bottom-up assistance in grid recovery.

[0230] Table 2. Provincial Dispatch Baseline Recovery Time Steps and Actual Network Dispatch Recovery Time Steps for Each Node of the 500kV Power Grid

[0231]

[0232] Figure 6 A strategy for saving network interaction power is presented. Figure 6 As can be seen, during the initial optimization, the provincial dispatch center reports the power it hopes the grid dispatch center will support, as shown by the red curve in the figure. After receiving the provincial dispatch center's backup node recovery strategy, the grid dispatch center formulates its black start strategy and feeds back the provincial dispatch center the upper limit of the power generation it can provide, as shown by the blue curve in the figure. After receiving the grid dispatch center's upper limit of power generation information, the provincial dispatch center uses it as the boundary condition of the secondary optimization model and determines the final grid-province interactive power strategy, as shown by the green curve in the figure. Figure 6 The network-province interactive power iteration strategy can achieve network-province collaborative recovery through information exchange.

[0233] Regarding the provincial-local collaborative recovery strategy, taking the geological surveys 43 and 299 as examples, the following is given: Figure 7 The provincial load recovery strategy is shown. Figure 7 It can be seen that Dispatch 43 did not restore any load in the first 7 time steps because the provincial dispatch only restored node 43 in the 7th time step. After the 6th time step, Dispatch 43 began to try its best to meet the load power restoration requirements of the provincial dispatch. However, due to the dispersion of the load, the power restored by Dispatch 43 after the restoration of the feeder may not completely match the requirements of the provincial dispatch. Similarly, it can be seen that Dispatch 299 did not restore any load in the first 2 time steps. In the 3rd and 4th time steps, since the distribution network structure of Dispatch 299 has not been fully restored, the load that can be restored is relatively small. In the 5th time step and thereafter, the network structure of Dispatch 299 is fully restored, so it can completely match the load restoration requirements of the provincial dispatch.

[0234] To verify the effectiveness of the proposed multi-level grid-province-region coordinated recovery model, the method of this invention was compared with method A, which only considers provincial-region coordination (i.e., does not consider assisting grid dispatch in recovery, nor does it consider the support power of grid dispatch). The comparison results are shown in Table 3. Table 3 shows that, in terms of the net recovery benefit of grid dispatch and provincial dispatch, the method of this invention is 2.7% and 0.34% higher than method A, respectively. This is because this invention considers grid-province coordination; grid dispatch can recover from the bottom up with the help of provincial dispatch, while provincial dispatch can also provide power support from the top down using the power already recovered by grid dispatch. In contrast, method A's grid dispatch does not have provincial dispatch for bottom-up recovery, resulting in a slower recovery speed and less restored unit power generation; provincial dispatch, without power support from grid dispatch, can only rely on its own black-start units to restore non-black-start units, resulting in even less restored load.

[0235] Table 3 Comparison of recovery benefits between the method proposed in this invention and method A

[0236]

[0237] To verify the effectiveness of the restoration safety risk assessment proposed in this invention, the restoration benefits of the method of this invention are compared with those of method B, which does not consider restoration safety risk (i.e., the objective function does not consider restoration safety risk, but the control cost caused by restoration safety risk is calculated after solving the problem). The results are shown in Table 4. Table 4 shows that the power generation restoration benefits and load restoration benefits of the grid dispatch and provincial dispatch systems of this invention are basically equal. However, in terms of grid restoration benefits, the method of this invention is less than that of method B. This is because method B does not consider restoration safety risk and only considers grid restoration from the perspective of node and line importance. However, correspondingly, some lines are located in the typhoon path, such as lines 53, 69, and 71. The method of this invention chooses to restore them later, while method B restores them earlier. This may lead to secondary power outages during the typhoon's passage, generating additional control costs. Therefore, the grid dispatch and provincial dispatch control costs of method B are higher than those of the method of this invention, resulting in lower net restoration benefits for grid dispatch and provincial dispatch systems for method B.

[0238] Table 4 Comparison of recovery benefits between the method proposed in this invention and method B

[0239]

[0240] Furthermore, based on the same inventive concept, this invention also provides a multi-level grid-province-regional dispatching collaborative recovery device, including a risk assessment module, a model building module, a scheme formulation module, and a strategy recovery module. The risk assessment module is used to establish a grid recovery safety risk assessment index based on line recovery reliability under typhoon disasters. The model building module, based on the grid recovery safety risk assessment index, establishes a full-stage collaborative recovery optimization model for multi-level grid-province-regional dispatching for recovery safety risks. The scheme formulation module, based on the full-stage collaborative recovery optimization model, obtains a multi-level grid-province-regional dispatching collaborative recovery scheme after a province-wide power outage under a typhoon scenario. The strategy recovery module, based on the multi-level grid-province-regional dispatching collaborative recovery scheme, performs collaborative recovery of the grid recovery strategy for multi-level grid-province-regional dispatching.

[0241] Following a typhoon, the risk assessment module calculates wind speed data for each power line at various time points, determines tower failure rates based on this data, and then assesses the power supply reliability of the lines. Finally, it calculates restoration safety risk assessment indicators. For areas with low restoration risk, the model building module constructs a multi-level dispatching three-tiered restoration optimization sub-model, specifying the respective dispatching methods for the grid, province, and local governments. Based on the multi-level dispatching three-tiered restoration optimization sub-model and the respective dispatching methods, the scheme formulation module proposes a multi-level dispatching coordinated restoration optimization scheme for the entire province after a major power outage. According to this scheme, the strategy restoration module performs coordinated restoration of the power grid restoration strategy across the multi-level dispatching system.

[0242] This invention also provides a computer-readable storage medium for storing one or more programs, the programs including instructions that, when executed by a computing device, cause the computing device to perform the methods described in this invention.

[0243] The present invention provides a computing device comprising: one or more processors, one or more memories, and one or more programs, wherein the one or more programs are stored in the one or more memories and configured to be executed by the one or more processors, and the one or more programs include methods for performing embodiments of the present invention.

[0244] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention can be implemented using various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0245] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0246] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0247] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0248] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the invention.

[0249] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A multi-level scheduling and collaborative recovery method for network provinces and regions, characterized in that: Includes the following steps: Establish a power grid restoration safety risk assessment index based on line restoration reliability under typhoon disasters; Based on the power grid restoration safety risk assessment indicators, a multi-level dispatching full-stage collaborative restoration optimization model for power grid, province and locality is established for restoring safety risks. The multi-level dispatching full-stage collaborative restoration optimization model has a multi-layer structure, including a middle-level sub-model, an upper-level sub-model and a lower-level sub-model. The intermediate sub-model is used to formulate the recovery strategy for network surveys; The upper-level sub-model is used to formulate the provincial-level recovery strategy; The lower-level sub-model is used to formulate the recovery strategy for the geological survey; The middle-level sub-model uses provincial adjustment to restore net income. Maximize the objective function; Based on the revenue from the restoration of generating units by the provincial dispatch center Provincial Dispatch Restoration Load Revenue Provincial grid restoration benefits and the cost of restoring security risk control It is confirmed that its expression is: ； ； ； ； In the formula, To restore the net revenue per unit of power generation at the nth node of the provincial power grid; The restored generating power of the generator at the nth node of the provincial dispatch center; The net revenue per unit load restored to the nth node of the provincial power dispatch system; The restored load power of the nth node of the provincial dispatch center; The time interval between adjacent recovery steps; and The net revenue was restored for both provincial regulation points and line units; and These represent the number of nodes and lines in the provincial dispatch center, respectively. and These are the recovery status variables for the nth node and the lth line of the provincial dispatch center, respectively. A value of 1 and 0 indicate that the line has been restored and has not been restored, respectively. and These are the provincial regulation point connectivity index and the shortest node connectivity distance index, respectively. This refers to the line's power transmission capacity. ； ； ； In the formula, and These are the sets of provincial grid nodes that contain and do not contain node n, respectively. The binary coefficients for connectivity between nodes i and j are denoted by 1, where a value of 1 indicates that nodes i and j are connected. Let i be the shortest connected distance between nodes i and j; This represents the upper limit of the transmission power that line l can carry; Let be the number of times the shortest electrical path connecting nodes i and j passes through line l; where, This is called the weighted power flow betweenness of line l; Based on the multi-level scheduling and full-stage collaborative recovery optimization model of the grid, province and locality, a multi-level scheduling and collaborative recovery scheme of the grid, province and locality after a major power outage in the province under a typhoon scenario is obtained. Based on the aforementioned multi-level grid-province-regional dispatching collaborative recovery scheme, the power grid recovery strategy of multi-level grid-province-regional dispatching is carried out collaboratively for recovery.

2. The multi-level scheduling and collaborative recovery method for network, province, and region as described in claim 1, characterized in that: The establishment of a power grid restoration safety risk assessment index based on line restoration reliability under typhoon disasters includes the following steps: The temporal-spatial wind speed distribution of a typhoon is obtained by the vector sum of its moving wind speed and circulation wind speed. Based on the temporal-spatial wind speed distribution of the typhoon, the data is corrected according to micro-topographic factors to obtain wind speed data for each line at each time step. The tower failure rate is calculated based on the wind speed data for each line at each time step, thereby obtaining the power supply reliability of the line. Finally, the recovery safety risk assessment index is calculated.

3. The multi-level scheduling and collaborative recovery method for network, province, and region as described in claim 2, characterized in that: The typhoon's moving wind speed and circulation wind speed were calculated based on the Masae Miyazaki model and the Rankine model: ； ； In the formula, Let be the moving wind speed of the l-th line at time t; The wind speed at which the typhoon center moves at time t; This represents the distance between the typhoon center and the l-th line at time step t; The radius of the typhoon's maximum wind speed at time step t; Let be the circulation wind speed of the typhoon along the l-th line at time t. The maximum wind speed of the typhoon at time t; in, ; In the formula, ( , )and( , () are the latitude and longitude coordinates of the typhoon center and the l-th line at time step t, respectively. , () represents the average latitude and longitude coordinates of the first and last nodes of the line; This is the average radius of the Earth.

4. The multi-level scheduling and collaborative recovery method for network, province, and region as described in claim 3, characterized in that: Based on the temporal-spatial wind speed distribution of the typhoon, the data is corrected according to micro-topographic factors to obtain wind speed data for each time step along each route, including: Obtain the wind speed vector of the l-th line at time step t. : ； In the formula: This is the terrain correction factor for the l-th route; and These are the moving wind speed and the circulating wind speed, respectively. To assess the power supply reliability of the grid line l at time t, assuming all towers on the same transmission line are of the same type, the reliability assessment theory for series systems is referenced. The calculation formula is: ； In the formula, Let be the tower failure rate of line l at time t; The number of towers for line l; The reliability of the power supply of the line The calculation formula is: ； In the formula, The design wind speed for line l, The tower failure rate model coefficient for line l is taken as 0 to 0.4; The restoration safety risk assessment index for line l is defined as follows: ； In the formula, The unit safety risk control cost for the l-th line at time step t; Define power grid restoration safety risk assessment indicators The sum of the safety risk assessment indicators for the restoration of each line: ； In the formula, denoted as the total number of power grid lines; T represents the total number of recovery time steps.

5. The multi-level scheduling and collaborative recovery method for network, province, and region according to claim 1, characterized in that: The constraints of the mid-level sub-model include black start constraints, network reconfiguration constraints, load recovery constraints, active power balance constraints, and power flow constraints. The black start constraint is specifically as follows: ； ； ； ； ； ； In the formula, This refers to the startup time of a non-blackout power supply. This refers to the time required for a non-black-start power supply to reach its rated power from startup. ; The power required for starting a non-black start power supply; This refers to the rated power of a non-black start power supply. and These are the upper and lower limits of the startup time for a non-black start power supply; and These are binary variables reflecting the startup status of non-black start power supplies and black start power supplies, respectively, with 1 indicating that it has been started; This refers to the startup time of the black-start power supply; This is the set of lines connected to node n in the provincial data transfer. The network reconstruction constraints are specifically as follows: ； ； ； In the formula, This is a binary variable representing the recovery status of line l, where 1 indicates that recovery has been achieved. This represents the set of lines connected to line p; The set of lines connected to node n; The load recovery constraint is specifically as follows: ； ； ； In the formula, and These represent the restored load power and the load power to be restored at node n, respectively. This refers to the set of nodes containing non-flexible loads. This is a binary variable representing the load recovery status of node n, where 1 indicates that the node's load has begun to recover. The active power balance constraint is specifically as follows: ； In the formula, The power supply for black start-up; and These are the charging and discharging power of the energy storage device at provincial regulation point n, respectively. This represents the interaction power between the provincial dispatch center and the grid dispatch center. A positive value indicates that the provincial dispatch center provides power to the grid dispatch center, while a negative value indicates that the provincial dispatch center requests power support from the grid dispatch center.

6. The multi-level scheduling and collaborative recovery method for network provinces and regions according to claim 1, characterized in that: The upper-level sub-model uses network survey recovery net profit. Maximize the objective function; Revenue from unit power generation restored by grid dispatch , Network adjustment and grid restoration revenue And the cost of network restoration and security risk control It is confirmed that its expression is: ； ； ； In the formula, To restore the net revenue per unit of power generation of the nth node in the grid dispatching system; This represents the restored generating power of the generator at the nth node of the network dispatching system. and The net revenue was restored for network regulation points and line units, respectively. and These represent the number of nodes and lines in the network survey, respectively. and These are the recovery status variables for the nth node and the lth line in the network survey, respectively. A value of 1 and 0 indicate that the network has recovered and has not recovered, respectively. and These are the network adjustment point connectivity index and the shortest node connectivity distance index, respectively. Their specific expressions are as follows: and The expression is similar; This is an indicator of the transmission power capacity of a line, and its specific expression is the same as... The expression is similar; The constraints of the upper-level sub-model include black-start constraints, network reconfiguration constraints, active power balance constraints, and power flow constraints. The black-start and network reconfiguration constraints of the upper-level sub-model are similar to those of the middle-level sub-model, respectively. The active power balance constraints are as follows: ； In the formula, This refers to the power that the power grid borrows from other provinces. This represents the interaction power between the grid dispatch center and the provincial dispatch center. A positive value indicates that the grid dispatch center provides power to the provincial dispatch center, while a negative value indicates that the grid dispatch center requests power support from the provincial dispatch center.

7. The multi-level scheduling and collaborative recovery method for network, province, and region according to claim 1, characterized in that: The lower-level sub-model uses ground survey to recover net revenue. Maximize the objective function; Net revenue based on regional dispatch load recovery , Revenue from the restoration of the geological survey network and the cost of restoring safety risk control It is confirmed that its expression is: ； ； ； In the formula, Let d be the number of nodes in the d-th local survey. Let n be the unit load recovery revenue of the d-th local adjustment point n; The load recovery power of the d-th ground control point n at time step t; The unit penalty cost is the difference between the load power restored by the d-th regional dispatch and the load power expected to be restored by the provincial dispatch. and These are the recovery status variables for the d-th dispatch center, the n-th node, and the l-th line, respectively. Values ​​of 1 and 0 indicate that the line has been restored and has not been restored, respectively. and Let be the connectivity index of the d-th adjustment point and the shortest connectivity distance index of the node, respectively. Their specific expressions are as follows: and The expression is similar; This is an indicator of the transmission power capacity of a line, and its specific expression is the same as... The expression is similar; The constraints of the lower-level sub-model include network reconfiguration constraints, load recovery constraints, active power balance constraints, and power flow constraints. The network reconfiguration and load recovery constraints of the lower-level sub-model are similar to those of the middle-level sub-model, respectively. The active power balance constraints are as follows: ； In the formula, and These are the charging and discharging powers of the energy storage device at the d-th ground control point n, respectively. This represents the interaction power between the d-th regional dispatch center and the superior provincial dispatch center. A positive value indicates that the regional dispatch center provides power to the provincial dispatch center, while a negative value indicates that the regional dispatch center requests power support from the provincial dispatch center. Conditional Value at Risk (CVaR) is used to modify the three-layer sub-model to address uncertainties in wind speed and load forecasting; the objective function of the modified three-layer sub-model is... , and They are respectively: ； ； ； In the formula, , and These are the CVaRs of the provincial survey, the network survey, and the d-th regional survey, respectively. , and These are the risk weight coefficients for the provincial survey, the network survey, and the d-th regional survey, respectively. CVaR is defined as the average loss of a portfolio over a given investment period when the risk of loss exceeds the Value at Risk (VaR) at a given confidence level. Converting the average loss into a return function yields the formula for calculating CVaR. ； ； ； In the formula, , and These are the VaR values ​​for provincial, network, and regional surveys, respectively; N SCE The number of random scenes; , and These represent the probabilities of the nth scenario occurring in the provincial survey, network survey, and local survey, respectively. , , These represent taking the larger value within the parentheses; , and The confidence levels are given for the provincial survey, the national survey, and the regional survey, respectively. , and Let be the net recovery benefit after considering CVaR in the nth random scenario of provincial, network, and regional surveys, respectively, with the specific expressions as follows: ； ； ； In the formula, , and These are the additional control unit prices generated by the typhoon wind speed forecast errors of the provincial, national, and regional dispatch centers, respectively. , and These are the additional control unit prices generated by load forecasting errors at the provincial, grid, and regional dispatching levels, respectively. , and These represent the typhoon wind speed prediction errors at time t for the lth line of the provincial, national, and regional dispatch systems, respectively. , and These represent the load forecasting errors at time step t for the nth node of the provincial, grid, and regional dispatch centers, respectively.

8. The multi-level scheduling and collaborative recovery method for network provinces and regions according to claim 1, characterized in that: The method for coordinated recovery of the power grid based on the multi-level dispatching scheme of the grid, province, and locality includes: Collect the load power prediction matrix of each local dispatch center at each time step, construct the provincial dispatch center's initial recovery optimization sub-model, and solve to obtain the initial full-stage recovery strategy of the 220kV transmission network under the jurisdiction of the provincial dispatch center. Based on the initial full-stage recovery strategy of the 220kV transmission network under the jurisdiction of the provincial dispatch center, the provincial dispatch center transmits the guaranteed recovery time step to the grid dispatch center; at the same time, the provincial dispatch center transmits all the guaranteed recovery time step matrix and load power matrix to each local dispatch center. Solve the upper-level sub-model; add a bottom-line recovery constraint for the network-province coupling node based on the upper-level sub-model, and then solve the upper-level sub-model to obtain the black start and network recovery strategy of the 500kV transmission network under the jurisdiction of the grid dispatching department; Based on the black start and grid restoration strategy of the 500kV transmission network under the jurisdiction of the grid dispatch center, the grid dispatch center will feed back the final restoration time step matrix and the unit power matrix available at each time step to the provincial dispatch center. Solve the lower-level sub-model; add provincial and local coupling node bottom-line recovery constraints on the lower-level sub-model, and then solve the lower-level sub-model to obtain the network reconfiguration and load recovery strategies of the 110kV distribution networks under the jurisdiction of each dispatching authority; Based on the network reconfiguration and load restoration strategies of the 110kV distribution networks under the jurisdiction of each dispatch center, each dispatch center feeds back the load power matrix of their actual restoration at each time step to the provincial dispatch center; After receiving feedback from the grid dispatch and the local dispatch, the provincial dispatch center adds constraints on the available generating power of the grid dispatch and the actual restored load power of the local dispatch to the intermediate-level sub-model, and continues to solve the intermediate-level sub-model to obtain the final full-stage recovery strategy of the 220kV transmission network under the jurisdiction of the provincial dispatch center.

9. A recovery device applied to the network-province-region multi-level scheduling collaborative recovery method as described in claim 1, characterized in that: It includes a risk assessment module, a model building module, a solution development module, and a strategy recovery module; The risk assessment module is used to establish a power grid restoration safety risk assessment index based on line restoration reliability under typhoon disasters; The model building module establishes a multi-level scheduling, full-stage collaborative recovery optimization model for power grid, province, and local governments to address recovery security risks, based on power grid recovery security risk assessment indicators. The scheme formulation module, based on the multi-level scheduling and full-stage collaborative recovery optimization model of the grid, province and locality, obtains the multi-level scheduling and collaborative recovery scheme of the grid, province and locality after a major power outage in the province under the typhoon scenario; The strategy recovery module, based on the multi-level grid-province-regional dispatch collaborative recovery scheme, performs collaborative recovery of the power grid recovery strategy of the multi-level grid-province-regional dispatch.

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