CN110504689B - Power system load flow calculation method based on cloud calculation technology - Google Patents
Power system load flow calculation method based on cloud calculation technology Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
Abstract
The invention relates to the technical field of computers, in particular to a power system load flow calculation method based on a cloud calculation technology, which comprises the following steps: A) importing power system data, and dividing a power system into a plurality of areas; B) dividing the voltage level into a plurality of subnets; C) sequentially taking the load flow calculation of each sub-network as a task; D) e, verifying the sub-networks in the area, if the sub-networks pass the verification, entering the step E, otherwise, replacing the load flow calculation method, and returning to the step C; E) and (4) jointly solving and verifying all the areas, finishing the load flow calculation of the power system if the verification is passed, and replacing the load flow calculation method to perform the load flow calculation again if the verification is not passed. The substantial effects of the invention are as follows: by means of cloud computing, load flow computing of each regional power grid can be conducted in parallel, and load flow computing efficiency is greatly improved.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a power system load flow calculation method based on a cloud calculation technology.
Background
Cloud computing (cloud computing) is one type of distributed computing, and means that a huge data computing processing program is decomposed into countless small programs through a network "cloud", and then the small programs are processed and analyzed through a system consisting of a plurality of servers to obtain results and are returned to a user. In the early stage of cloud computing, simple distributed computing is adopted, task distribution is solved, and computing results are merged. Thus, cloud computing is also known as grid computing. By the technology, tens of thousands of data can be processed in a short time, so that strong network service is achieved. Load flow calculation is an electromechanical term, and refers to the calculation of the distribution of active power, reactive power and voltage in a power network under the conditions of given power system network topology, element parameters, power generation parameters and load parameters. The tidal current calculation is a calculation for determining steady-state operation state parameters of each part of the power system according to the given power grid structure, parameters and operation conditions of elements such as a generator and a load. Typically given operating conditions there are power at each source and load point in the system, pivot point voltage, voltage at the balance point and phase angle. The operating state parameters to be solved comprise voltage amplitude and phase angle of each bus node of the power grid, power distribution of each branch circuit, power loss of the network and the like. And the load flow calculation of the power grid can be completed quickly in a cloud calculation mode. When the load flow calculation is carried out, the regional power grids are combined after the load flow calculation is carried out on the regional power grids, and whether the load flow calculation result is correct or not is checked. By adopting a cloud computing mode, parallel computing of each sub-network can be realized, and the efficiency of load flow computing is improved.
Chinese patent CN109800944A, published 2019, 5, 24, a dispatcher load flow calculation method based on cloud calculation, for the traditional dispatcher load flow, the method can automatically allocate the calculation resources of the dispatcher load flow according to the user information, support multi-user operation without influencing each other, and can push different load flow calculation results according to the user information; the cloud terminal concentrates information such as power flow out-of-limit, overloading and transfer concerned by a dispatcher on a main picture, and the inquiry and operation are integrated in the same main picture, so that the functions of equipment operation, calculation result check and the like can be facilitated when a power flow calculation function is used, and the use habit better conforms to the application requirement of off-line calculation and the use habit of a user, so that the method is perfect as the function of power flow calculation. But the method can not solve the problem that the load flow calculation of the sub-network cannot be basically completed at the same time due to poor cloud calculation task distribution coordination, so that the waiting time is long.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the current technical problem of low power grid load flow calculation efficiency is solved. The cloud computing technology-based power system load flow computing method efficiently using the cloud computing parallel computing technology is provided.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows: a power system load flow calculation method based on a cloud calculation technology comprises the following steps: A) importing data of an electric power system, and dividing the electric power system into a plurality of areas according to geographical areas; B) dividing each region into a plurality of subnets according to voltage levels; C) sequentially taking the load flow calculation of each sub-network as a task, and calculating by a cloud computing system; D) e, jointly solving and verifying the sub-networks in the region, if the load flow calculation result passes the verification, entering the step E, otherwise, replacing the load flow calculation method, and returning to the step C; E) and (4) jointly solving and verifying all the regions, if the verification is passed, completing the load flow calculation of the power system, and if the verification is not passed, selecting a partial region replacement load flow calculation method to perform the load flow calculation again.
Preferably, in step B, the method for dividing the subnets comprises: and processing the node with the changed voltage level as a power supply or a load, wherein the power node is input to the sub-network as the power supply, and the node which acquires power from the sub-network is used as the load.
Preferably, in step C, load flow calculation is performed on each sub-network in sequence according to the voltage levels of the sub-networks from low to high.
Preferably, the plurality of subnets divided in the step B use the areas in each subnet, which are connected in the topology, as independent power flow calculation tasks, so that each subnet divides a plurality of independent power flow calculation tasks, and the independent power flow calculation tasks are used as tasks of the cloud computing system and input into the cloud computing system for calculation.
Preferably, tasks belonging to the same subnet are simultaneously input or are input to the cloud computing system in close proximity for computing.
Preferably, when the task is input into the cloud computing system for computing, the task is distributed to the server nodes of the plurality of cloud computing systems, and the distributed server nodes basically complete the computing of the task at the same time.
Preferably, when the task is input into the cloud computing system for computing, the task is distributed to the server nodes of the plurality of cloud computing systems, and the distributed server nodes basically complete the computing of the task at the same time; periodically and randomly copying an allocated computing task, allocating the copied computing task to other server nodes for computing, and comparing whether the results returned by the two server nodes which compute the same computing task are consistent; if the results are not consistent, redistributing the two same computing tasks to the other two server nodes until the execution results of the two server nodes which are simultaneously distributed to the two same computing tasks are the same, and taking the consistent execution result as the execution result of the computing task; and counting comparison results of the latest execution results, and giving an alarm if the consistency rate is lower than a set threshold. The task is copied and distributed to the two server nodes for calculation, the calculation results of the two nodes can be verified, and the accuracy of the calculation results is improved.
Preferably, the calculation time consumption of two server nodes which calculate the same calculation task is compared, and the calculation time consumption is proportional to the reciprocal of the calculation time consumption allocated to the two server nodes when the calculation task is subsequently allocated. The calculation of the time consumption of the same task has a more accurate result for evaluating the calculation power of the server nodes, and the ratio of the calculation power of the two servers can be improved, so that the proportion of the tasks subsequently distributed to the two server nodes is more reasonable.
Preferably, the method for distributing the tasks to the server nodes of the plurality of cloud computing systems comprises the following steps: the server nodes are arranged according to the sequence of the load rates from low to high, and the server nodes are sequentially selected until the computing power of the selected server nodes meets the requirement of completing an independent load flow computing task within a set threshold time t. By setting the latest completion time t, the load flow calculation of all regional power grids is completed within the time t, and the load flow calculation of each regional power grid is basically completed at the same time, so that long-time waiting before checking can be avoided.
The substantial effects of the invention are as follows: through the cloud computing mode, the load flow computing of each regional power grid can be performed in parallel, after the regional power grids are combined, the load flow at the joint is checked to pass, the load flow computing task can be completed, and the load flow computing efficiency is greatly improved.
Drawings
FIG. 1 is a flow diagram of an embodiment.
Detailed Description
The following provides a more detailed description of the present invention, with reference to the accompanying drawings.
The first embodiment is as follows:
a power flow calculation method of an electric power system based on a cloud computing technology, as shown in fig. 1, the embodiment includes the following steps: A) and importing data of the power system, and dividing the power system into a plurality of areas according to the geographical area. And a small number of tie lines are arranged between the power grid areas, and the division areas are divided on the tie lines.
B) Each zone is divided into several sub-networks according to the voltage class. Each region is divided into sub-networks according to different voltage grades, and clear voltage change nodes are arranged between the sub-networks. The power node is input to the sub-network as a power source, and the node which acquires power from the sub-network is used as a load.
C) And sequentially taking the load flow calculation of each sub-network as a task according to the sequence of the voltage levels of the sub-networks from low to high, and calculating by using a cloud computing system. And for each sub-network, the areas connected in topology are used as independent load flow calculation tasks, each sub-network is divided into a plurality of independent load flow calculation tasks, the independent load flow calculation tasks are used as tasks of the cloud calculation system, and the tasks belonging to the same sub-network are simultaneously input or are closely input into the cloud calculation system for calculation. When the task is input into the cloud computing system for computing, the task is distributed to the server nodes of the plurality of cloud computing systems, and the distributed server nodes basically complete the computing of the task at the same time. The method for distributing the tasks to the server nodes of the cloud computing systems comprises the following steps: the server nodes are arranged according to the sequence of the load rates from low to high, and the server nodes are sequentially selected until the computing power of the selected server nodes meets the requirement of completing an independent load flow computing task within a set threshold time t. By setting the latest completion time t, the load flow calculation of all regional power grids is completed within the time t, and the load flow calculation of each regional power grid is basically completed at the same time, so that long-time waiting before checking can be avoided.
D) And E, carrying out combined solution verification on the subnets in the region, entering the step E if the load flow calculation result passes the verification, otherwise, replacing the load flow calculation method, and returning to the step C. The load flow calculation method comprises a Newton-Raphson method, a rapid decomposition method and load flow calculation methods of optimization algorithms such as a genetic algorithm, an artificial neural network and a fuzzy algorithm, which are disclosed in the prior art and are not described in detail herein. Different load flow calculation methods have different adaptability, so that the load flow calculation accuracy can be improved by replacing the load flow algorithm.
E) And (4) jointly solving and verifying all the regions, if the verification is passed, completing the load flow calculation of the power system, and if the verification is not passed, selecting a partial region replacement load flow calculation method to perform the load flow calculation again.
Example two:
in this embodiment, on the basis of the first embodiment, generation and allocation of the cloud computing task in step C are further improved, specifically:
c') sequentially taking the load flow calculation of each sub-network as tasks according to the sequence of the voltage levels of the sub-networks from low to high, and calculating by using the cloud computing system. And for each sub-network, the areas connected in topology are used as independent load flow calculation tasks, each sub-network is divided into a plurality of independent load flow calculation tasks, the independent load flow calculation tasks are used as tasks of the cloud calculation system, and the tasks belonging to the same sub-network are simultaneously input or are closely input into the cloud calculation system for calculation. When a task is input into a cloud computing system for computing, the task is distributed to a plurality of server nodes of the cloud computing system, and the distributed server nodes basically complete the computing of the task at the same time; periodically and randomly copying an allocated computing task, allocating the copied computing task to other server nodes for computing, and comparing whether the results returned by the two server nodes which compute the same computing task are consistent; if the results are not consistent, redistributing the two same computing tasks to the other two server nodes until the execution results of the two server nodes which are simultaneously distributed to the two same computing tasks are the same, and taking the consistent execution result as the execution result of the computing task; and counting comparison results of the latest execution results, and giving an alarm if the consistency rate is lower than a set threshold. The task is copied and distributed to the two server nodes for calculation, the calculation results of the two nodes can be verified, and the accuracy of the calculation results is improved.
Comparing the calculation time consumption of two server nodes which calculate the same calculation task, and enabling the reciprocal of the calculation time consumption allocated to the two server nodes to be proportional to the calculation time consumption when the calculation task is subsequently allocated. The calculation of the time consumption of the same task has a more accurate result for evaluating the calculation power of the server nodes, and the ratio of the calculation power of the two servers can be improved, so that the proportion of the tasks subsequently distributed to the two server nodes is more reasonable.
The above-described embodiments are only preferred embodiments of the present invention, and are not intended to limit the present invention in any way, and other variations and modifications may be made without departing from the spirit of the invention as set forth in the claims.
Claims (7)
1. A power flow calculation method of an electric power system based on a cloud computing technology is characterized in that,
the method comprises the following steps:
A) importing data of an electric power system, and dividing the electric power system into a plurality of areas according to geographical areas;
B) dividing each region into a plurality of subnets according to voltage levels;
C) sequentially taking the load flow calculation of each sub-network as a task, and calculating by a cloud computing system;
D) e, jointly solving and verifying the sub-networks in the region, if the load flow calculation result passes the verification, entering the step E, otherwise, replacing the load flow calculation method, and returning to the step C;
E) performing combined solution verification on all the regions, if the verification is passed, completing load flow calculation of the power system, and if the verification is not passed, selecting a partial region replacement load flow calculation method to perform load flow calculation again;
the plurality of sub-networks divided in the step B take the areas in each sub-network which are connected in the topological mode as independent load flow calculation tasks, so that each sub-network is divided into a plurality of independent load flow calculation tasks which are used as the tasks of the cloud computing system and input into the cloud computing system for calculation;
when a task is input into a cloud computing system for computing, the task is distributed to a plurality of server nodes of the cloud computing system, and the distributed server nodes basically complete the computing of the task at the same time;
periodically and randomly copying an allocated computing task, allocating the copied computing task to other server nodes for computing, and comparing whether the results returned by the two server nodes which compute the same computing task are consistent;
if the results are not consistent, redistributing the two same computing tasks to the other two server nodes until the execution results of the two server nodes which are simultaneously distributed to the two same computing tasks are the same, and taking the consistent execution result as the execution result of the computing task;
and counting comparison results of the latest execution results, and giving an alarm if the consistency rate is lower than a set threshold.
2. The power flow calculation method based on the cloud computing technology as recited in claim 1,
in step B, the method for dividing the subnets comprises:
and processing the node with the changed voltage level as a power supply or a load, wherein the power node is input to the sub-network as the power supply, and the node which acquires power from the sub-network is used as the load.
3. The power flow calculation method based on the cloud computing technology according to claim 1 or 2,
and step C, sequentially carrying out load flow calculation on each sub-network according to the sequence of the voltage levels of the sub-networks from low to high.
4. The power flow calculation method based on the cloud computing technology as recited in claim 1,
and simultaneously inputting or closely inputting tasks belonging to the same subnet into the cloud computing system for computing.
5. The power flow calculation method based on the cloud computing technology as recited in claim 1,
when the task is input into the cloud computing system for computing, the task is distributed to the server nodes of the plurality of cloud computing systems, and the distributed server nodes basically complete the computing of the task at the same time.
6. The power flow calculation method based on the cloud computing technology as recited in claim 1,
comparing the calculation time consumption of two server nodes calculating the same calculation task, and enabling the task data amount distributed by the two server nodes to be proportional to the reciprocal of the calculation time consumption when the calculation task is subsequently distributed.
7. The power flow calculation method based on the cloud computing technology as recited in claim 1,
the method for distributing the tasks to the server nodes of the cloud computing systems comprises the following steps:
the server nodes are arranged according to the sequence of the load rates from low to high, and the server nodes are sequentially selected until the computing power of the selected server nodes meets the requirement of completing an independent load flow computing task within a set threshold time t.
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