CN110429585B - Black-start recovery grid planning algorithm - Google Patents
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Abstract
The invention relates to a black-start net rack recovery planning algorithm, and belongs to the technical field of power system operation. The method is carried out in a mode of combining an breadth-first algorithm and a Dijkstra algorithm. Firstly, selecting a power supply point with self-starting capability and maximum capacity as a black-start power supply in a determined target area to be recovered, searching a recovery path from the black-start power supply to each alternative started power supply by adopting a breadth-first algorithm, selecting 4 optimal initial-stage small systems of the black-start according to a priority weight function calculation result, and then performing overall recovery on the grid frame to be recovered and the power supply of the target area by adopting a Dijkstra algorithm according to a shortest weight path principle. When the power grid has large-scale power failure, the method can quickly provide an optimal recovery scheme for black start recovery, improve the efficiency and success rate of the black start recovery of the power grid, and reduce the social and economic losses caused by long-term power failure.
Description
Technical Field
The invention relates to a black-start net rack recovery planning algorithm, and belongs to the technical field of power system operation.
Background
Along with various intelligent technologies continuously apply to the field of power production, the safety and stability level of a power system is greatly improved, but because the scale of an interconnection system is increasingly large, the loads are diversified due to the wide application of various novel power equipment, the operation mode of the system is undoubtedly more complicated, in addition, the large-scale interconnection of a power grid, the potential hidden dangers of the power system are more and more, and the risk of occurrence of a large power failure accident exists constantly. In the face of the development trend that the structure and the characteristics of the modern power system are more complex, when the power system faces various internal and external interferences, the major power failure accident still cannot be completely avoided. When the power grid has a blackout and the system cannot be recovered through an external power supply, the net rack needs to be recovered by black start. Normally, the black start path recovery mainly comprises a black start small system forming phase and a network reconstruction phase. In the stage of forming the small black-start system, a power supply point with the existing self-starting capacity, large installed capacity and good regulation capacity is required to be selected for self-starting, a safe, reliable and quick recovery path is selected to drive a power supply with large installed capacity, the power supply is operated in parallel to form a small dual-power system, in the stage of reconstructing the grid frame, the optimal recovery path is required to be sequentially calculated for the designated target power supply in the area and is sequentially recovered, the power generation capacity of the power grid in the area is expanded, and the regulation capacity of the grid frame is improved. In order to obtain a more scientific recovery scheme, multiple factors including power point self-starting capability, power point installed capacity, power point priority, line length, line voltage level, recovery operation times, node importance and the like need to be considered and comprehensively evaluated. For various reasons, the power supply characteristics, the power grid structure and the grid operation modes of different regions are completely different, and the guidance in formulating the black start scheme is also different, so that how to design the black start path optimization method suitable for different grid structures also becomes a hotspot problem in the black start process.
Disclosure of Invention
The invention aims to provide a black start recovery grid planning algorithm aiming at the defects of the existing black start recovery method and the specific grid characteristics, and comprehensively considers various factors. And calculating the safest, most reliable and fastest recovery path in the designated area, and improving the efficiency and success rate of black start recovery.
The technical scheme adopted by the invention is as follows: a black start recovery grid planning algorithm comprises the following steps:
step1: firstly, selecting a power supply point with self-starting capability and maximum generating capacity as a black-start power supply in a determined target area to be recovered,
step2: searching a recovery path from the black-start power supply to each alternative started power supply by adopting a breadth-first algorithm, and selecting 4 optimal paths according to a priority function calculation result to form an optimal 4 small system scheme at the initial stage of the black-start;
step3: and respectively recovering the net racks to be recovered and the power supply of 4 initial small systems in the target area by adopting a Dijkstra algorithm and a shortest weighted path principle to form 4 complete black start recovery schemes.
The three steps specifically comprise the following steps:
step1: in the target area self-starting power supply list, a black-start unit with the largest capacity is automatically selected as a black-start power supply, and the adopted target function is as follows:
wherein w is the number of black start power sources,
capacity of the i-th power supply point with self-starting capability, f 1 The selected black start power supply point.
Step2: and searching the shortest path from the selected black start power supply point to all selectable started power supplies in the net rack by adopting a breadth-first algorithm. As shown in fig. 2, the paths in the graph are all bidirectional, the light-colored paths represent paths that have network topology but are not searched by the algorithm, the thick black arrows represent planned paths, and the thin black arrow paths represent the step of exploring paths. Firstly, adding a black start power supply node 0 into a queue, starting circular search, deleting the black start power supply node 0 from the queue, changing adjacent nodes of the black start power supply node 0 into power supply point nodes 1 and 2, adding a power supply point node 5 into the queue, and assigning a value of 0 in a side; remove node 2 from the queue and examine its neighbors 0 and 1, finding both marked, add neighboring power supplies 3 and 4 to the queue, mark them and assign them to edge 2, respectively; deleting the node 5 from the queue, adding the power supply point node 3 adjacent to the node into the queue, and checking that the adjacent nodes 0 and 3 of the node 5 are marked; remove node 3 from the queue and check that its neighbors 2, 4, 5 have all been marked; node 4 is removed from the queue and its neighbors 3 and 2 are examined and found to have been marked. And marking paths from the black start power supply point to all target power supply points by optimizing the path of the topology taking the black start power supply point as a fixed starting point.
And step3: and (3) calculating the weight of each path in the step (2) by adopting a priority weight function, wherein the smaller the function value is, the better the priority of the path is, and selecting 4 optimal paths as initial small system stage sub-schemes of different alternative schemes. The priority value objective function for selecting the optimal small system path to be selected is as follows:
wherein f is y Priority evaluation value, L, of paths corresponding to different activated power supplies x,y Represents the distance length from the black start power supply point node x to the started power supply point node y, S y The capacity of the started power supply point is shown, and R represents the number of nodes from the black start power supply point node x to the started power supply point node y.
And 4, step 4: storing the importance of each node in a vector C for calling the weighted path length formula calculated in step 5, wherein the node importance vector C is as follows:
C＝{c 1 ,c 2 ,...c j ...,c n }
wherein n is the number of nodes in the net rack.
And 5: and (3) taking four started power supplies in the four schemes determined in the steps 2 and 3 as algorithm starting points, respectively calculating the optimal path of each target power supply point to be started in the area by using a Dijkstra algorithm, wherein the optimal path in the algorithm is a weighted optimal path. The formula for calculating the weighted path length of the candidate nodes in each step is as follows:
wherein Q j The weighted path length of the next node j to be selected is the node in the net rack including the variable power supply point, the power supply point and the switch station, L i,j Indicating in each calculation stepPath length from start node i to destination node j, C j Representing the importance value of the target node j.
After the above operations, a weighted grid structure as shown in fig. 3 can be obtained. Through Dijkstra algorithm, based on a small system formed in the previous period, wherein {0,2} nodes are respectively a black start power supply point node and a started power supply point node, restoring from a node 2, adding the node 2 into a tree, and adding nodes 4 and 8 into a priority queue; deleting node 8 from the priority queue, adding edges 2-8 to the tree, and adding node 7 to the priority queue; deleting node 4 from the priority queue, adding edges 2-4 to the tree, adding node 5 to the priority queue, and disabling edges 4-7; deleting node 7 from the priority queue, adding edges 8-7 to the tree, adding node 3 to the priority queue, and failing edges 7-5; deleting node 1 from the priority queue, adding edge 5-1 to the tree, and failing edge 1-3; node 6 is removed from the priority queue and edges 3-6 are added to the tree. The algorithm is shown in fig. 4. And the spanning tree path is the black start recovery path.
And 6: after the optimal path of each started power supply point is determined by a Dijkstra algorithm, each started power supply needs to be recovered according to a certain sequence. The order is determined by the priority of the power supply points determined in advance, and the power supply points are restored from high to low in sequence according to the priority values. The vector H storing the priority values of each activated power supply is:
H＝{h 1 ,h 2 ,...,h t }
where t is the number of activated power supplies.
And 7: when target power supply points to be recovered in a fragment are recovered through a Dijkstra algorithm, when some nodes are included in a recovery path of a recovered power supply point, the nodes need to be removed from the recovery path of the next target power supply point, namely, the recovery nodes are not repeated, and recovery is directly started from the nodes which are not recovered in a set path.
The invention has the beneficial effects that: when the power grid has large-scale power failure, the method can quickly provide an optimal recovery scheme for black start recovery, improve the efficiency and success rate of the black start recovery of the power grid, and reduce the social and economic losses caused by long-term power failure.
Drawings
FIG. 1 is a flow chart of a black start scheme generation algorithm;
FIG. 2 is a breadth first algorithm path trajectory diagram;
FIG. 3 is a Dijkstra algorithm weighted connectivity graph;
FIG. 4 is a Dijkstra algorithm net rack formation connectivity graph;
FIG. 5 is a one-time wiring diagram of a water filter zone system;
FIG. 6 is a diagram of a small system recovery scheme in the early stage of a water filtration zone;
figure 7 is a filter bank black start scheme path diagram.
Detailed Description
In order to make the objects, technical solutions and features of the present invention more apparent, the present invention will be described in further detail with reference to the following embodiments and drawings.
Example 1: as shown in fig. 1, the implementation process of the present invention can be divided into three major steps:
step1: firstly, selecting a power supply point with self-starting capability and maximum capacity as a black-start power supply in a determined target area to be recovered,
step2: searching a recovery path from the black-start power supply to each alternative started power supply by adopting a breadth-first algorithm, and selecting 4 optimal paths according to a priority function calculation result to form an optimal 4 small system scheme at the initial stage of the black-start;
and step3: and respectively recovering the net racks to be recovered and the power supply of 4 initial small systems in the target area by adopting a Dijkstra algorithm and a shortest weight path principle to form 4 alternative black start recovery schemes.
Further, the specific content of step1 is as follows:
taking the water filtering zone of the Yangjiang network as an example, the zone graph is shown in figure 5, and the name and capacity statistics of each power supply point are shown in table 1.
TABLE 1 statistical table of power supply point capacity
According to the formula:
wherein w is the number of black start power sources,
capacity of the i-th power supply point with self-starting capability, f 1 The selected black start power supply point.
And selecting a channel power station as a black start power point by a calculation formula and a power point capacity statistical table.
Further, the specific steps of step2 are as follows:
step 2.1: and searching paths from the selected black start power supply point to all selectable started power supplies in the net rack by adopting a breadth-first algorithm. Step1 shows that the Mingriver power station is used as a black start power supply. And performing first-layer diffusion on the node, selecting the node directly connected with the node as a six-storeroom center transformer, performing second-layer diffusion at the moment, and sequentially searching a sheet horse transformer substation, a Guden switching station, a self-foundation river power station, an old-nest river four-stage power station, an old-nest river three-stage power station, a 35kV old-nest transformer substation and a 35kV Lai Mao transformer substation which are directly connected with the six-storeroom center transformer. The third layer of diffusion is a sheet Ma He three-level power station connected with a sheet horse power transformation station, a maorehe power station, a Jin Man river power station, a boundary-separated river secondary power station connected with a Gudon switch station, a thatch power station and a silver slope river power station directly connected with a 35kV old nest power substation, and a 35kV Shangjiang power substation connected with a 35kV Lai Mao power substation. The fourth layer of diffusion is a Sun Zu river power station connected with a 35kV Shangjiang substation.
Step 2.2: and (3) substituting the target node parameters determined in the step (2.1) into an evaluation function for recovering the priority of the started unit as follows, and evaluating the priority of the nodes of the started unit, wherein the evaluation function for the priority is as follows:
wherein f is y Priority evaluation value, L, of paths corresponding to different activated power supplies x,y Represents the distance length from the black start power supply point node x to the started power supply point node y, S y The capacity of the started power supply point is shown, and R represents the number of nodes from the black start power supply point node x to the started power supply point node y.
Taking Jin Man river power station as an example, node x from black-start power source listening river power station to started power source Jin Man river power station needs to pass through six-depot central substation nodes and Gudeng switch station nodes as shown in fig. 5, so that the value of m is 2. Meanwhile, the length of the six listening wires in FIG. 5 is 24.862km, the length of the six ancient wires is 63.97km, and the length of the Jin Gu wires is 10.056km. Therefore, the distance from the power point of the black-start visiting river to the power station of the started Jin Man river is as follows: l is x,y ＝24.862+63.97+10.056＝98.888km
Started Jin Man capacity S of river power station y Referring to FIG. 5, which shows 42MW, the priority rating of the power point Jin Manhe is:
the black start power supply point nodes x of the other power supply points are all the power supply points of the Yanghe, and the calculation steps are the same as the above, so that the priority evaluation function values of all started power supply units in the six-library central area are obtained as shown in the table 2:
TABLE 2 priority evaluation calculation Table
The smaller the evaluation function value of the priority calculated in the above table is, the higher the priority is. Four started power supply points with higher priority are selected as target nodes to form 4 different black start small system generation schemes as shown in figure 6, and the other schemes are eliminated due to the fact that the priority evaluation values are small.
Further, the specific steps of step3 are as follows:
step 3.1: storing the importance of each node in a vector for calling the weighted path length formula calculated in step3.2, wherein the node importance vector is as follows:
C＝{c 1 ,c 2 ,...c j ...,c n }
wherein n is the number of nodes in the net rack. When the node is a power supply or a switching station, c j Is 1, when j is 110kV power conversion point, c j Is 0.5, when j is a 35kV substation, c j Is 0.2. The node importance values are shown in table 3:
TABLE 3 statistical table of node importance
Step 3.2: after the small black start system is formed, a target power supply point in a region needs to be recovered through a Dijkstra algorithm, an optimal path in the algorithm is a weighted optimal path, and the weighted path length of each edge needs to be initialized when the optimal path is calculated. The method specifically comprises the following steps: after an initial small system is formed, a whole black start grid of a district is generated through a Dijkstra algorithm, a Jin Man river power station with the highest priority evaluation function value is used as a started power supply point, the initial small system formed in the calculation example is a [ a visiting river power station, a six-warehouse center substation, a Gudon switch station, a Jin Man river power station ], based on the system, dijkstra algorithm optimization is carried out, and the weight of a node directly connected with the formed initial small system is calculated. As can be seen from fig. 7, the initial small system includes a listening river power station and a Jin Man river power station, dijkstra algorithm path optimization takes a started power supply Jin Man river power station in the small system as a starting point, and a formula for calculating the weighted path length of each step of the alternative nodes is as follows:
wherein Q is j The weighted path length of the next node j to be selected is the node in the net rack including the variable power supply point, the power supply point and the switch station, L i,j Represents the path length from the starting node i to the target node j in each step of calculation, c j Representing the importance value of the target node j. For example, as shown in fig. 5, the distance from the i 35kV Lai Mao substation as the starting node to the j 35kV shangjiang substation as the target node is 17km, and the importance of the j 35kV shangjiang substation as the target node is 0.2. Therefore, the weighted path length from the transformer substation at the initial node i 35kV Lai Mao to the transformer substation at the target node j 35kV shangjiang is as follows:
/>
the weighted path lengths of the edges are as in table 4:
TABLE 4 weighted Path statistics Table
Step 3.3: after the optimal path of each started power supply point is determined by a Dijkstra algorithm, each started power supply needs to be recovered according to a certain sequence. The order is determined by the priority of the power supply points determined in advance, and the power supply points are restored from high to low in sequence according to the priority values. The vector H storing the priority values of each activated power supply is:
H＝{h 1 ,h 2 ,...,h t }
where t is the number of activated power supplies.
In this example, the sequence is restored from large to small according to the capacity of the power supply point, and finally the block black start scheme path diagram shown in fig. 7 is formed.
Step 3.4: when target power supply points to be recovered in a fragment are recovered through a Dijkstra algorithm, when some nodes are included in a recovery path of a recovered power supply point, the nodes need to be removed from the recovery path of the next target power supply point, namely, the recovery nodes are not repeated, and recovery is directly started from the nodes which are not recovered in the path. For example, in a scenario where the small system is [ a listening river hydropower station — a golden river hydropower station ], the restoration path for the target power supply point to be a maor river hydropower station is: a listening river hydropower station-a six-storeroom center transformer-a ancient switch station-Jin Man river hydropower station-a maor river hydropower station; the recovery path of the old honeycomb river four-stage hydropower station with the target power supply point is as follows: listening river hydropower station-six storehouses center change-ancient switch station-Jin Man river hydropower station-old nest river four-level hydropower station. However, the path of the Ma Russian river hydropower station is recovered before the path of the old nest river four-level hydropower station, the nodes listen to the river hydropower station, the six-reservoir center station, the Guden switch station and the Jinman river hydropower station are recovered, and the paths are overlapped, so that the recovered nodes are not repeated, and the old nest river four-level hydropower station is directly recovered.
The algorithm takes the more important water filter area power grid in the power grid across the Yangjiang river as an example, and by applying the algorithm, a reasonable path recovery scheme is provided for black start recovery, the recovery efficiency and the success rate are improved, and the algorithm has important significance for the emergency recovery process of the power grid.
While the present invention has been described in detail with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, and various changes can be made without departing from the spirit and scope of the present invention.
Claims (2)
1. A black start recovery grid planning algorithm is characterized in that: the method comprises the following steps:
step1: firstly, selecting a power supply point with self-starting capability and maximum generating capacity as a black-start power supply in a determined target area to be recovered;
step2: searching a recovery path from the black-start power supply to each alternative started power supply by adopting a breadth-first algorithm, and selecting 4 optimal paths according to a priority function calculation result to form an optimal 4 small system scheme at the initial stage of the black-start;
step3: respectively recovering 4 initial small system net racks to be recovered and power supplies of a target area by adopting a Dijkstra algorithm and a shortest weighted path principle to form 4 complete black start recovery schemes;
the specific steps of Step2 are as follows:
step2.1 searches the shortest path from the selected black start power supply point to all the selectable started power supplies in the net rack by adopting an breadth-first algorithm;
step2.2 adopts a priority weight function to calculate the weight of each path in Step2.1, the path with smaller function value has better priority, 4 optimal paths are selected as initial small system stage sub-schemes of different alternative schemes, and the priority value target function of the optimal small system path to be selected is as follows:
wherein f is y Preference evaluation values, L, for paths corresponding to different activated power supplies x,y Represents the distance length from the black start power node x to the started power node y, S y The capacity of the started power supply point is represented, and R represents the number of nodes from a black start power supply point node x to a started power supply point node y;
the specific steps of Step3 are as follows:
step3.1 stores the importance of each node in a vector C for the Step3.2 to call by the weighted path length calculation formula, the node importance vector C is:
C＝{c 1 ,c 2 ,...c j ...,c n }
wherein n is the number of nodes in the net rack;
step3.2, four started power supplies in the four schemes determined by Step2 are used as algorithm starting points, the Dijkstra algorithm is used for calculating the optimal path of each target power supply point to be started in the area respectively, the optimal path in the algorithm is a weighted optimal path, and the formula for calculating the weighted path length of each Step of the alternative nodes is as follows:
wherein Q is j The weighted path length of the next node j to be selected is the node in the net rack including the variable power supply point, the power supply point and the switch station, L i,j Represents the path length from the starting node i to the target node j in each step of calculation, C j Representing the importance value of the target node j;
step3.3 determines the optimal path of each started power supply point through Dijkstra algorithm, and then needs to recover each started power supply according to a specific sequence, wherein the specific sequence is determined by the priority of the power supply points determined in advance, and the power supply points recover from high to low in sequence according to the priority value, and the vector H for storing the priority value of each started power supply is as follows:
H＝{h 1 ,h 2 ,...,h t }
wherein t is the number of started power supplies;
when the target power supply point to be recovered in the fragment area is recovered by the Step3.4 through the Dijkstra algorithm, when some nodes are included in the recovery path of the recovered power supply point, the nodes need to be removed from the recovery path of the next target power supply point, namely the recovery nodes are not repeated, and the recovery is directly started from the nodes which are not recovered in the path.
2. The black start net rack recovery planning algorithm according to claim 1, wherein: the specific content of Step1 is as follows:
in the target area self-starting power supply list, a black-start unit with the largest capacity is automatically selected as a black-start power supply, and the adopted target function is as follows:
wherein w is the number of black start power sources,
capacity of the i-th power supply point with self-starting capability, f 1 The selected black start power supply point. />
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