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CN-122026381-A - Power distribution method, system, terminal equipment and medium for analyzing electric energy peak value

CN122026381ACN 122026381 ACN122026381 ACN 122026381ACN-122026381-A

Abstract

The invention discloses a power distribution method, a system, terminal equipment and a medium for analyzing an electric energy peak value. Based on the model, the node with the highest load is positioned, the history and real-time data of the node are analyzed, and the future load change of the node is predicted. And then combining the prediction data with a current model, constructing a test platform for simulating future period operation in a digital environment, setting a plurality of different regulation and control schemes for regulating energy storage or load in the test platform, and calculating the specific influence of each scheme on the whole network power flow one by one. Finally, the simulation results of all schemes are automatically compared, a scheme capable of reducing the overload risk of the line and balancing the whole network power flow is selected, and the scheme is directly converted into a control instruction and sent to field equipment for execution, so that the technical problem that other electric energy power flow is easy to cause congestion by using simple logic of a preset control instruction, and the problem is transferred or even expanded is solved.

Inventors

  • Sun Jingning
  • Li Zuwan
  • WANG HAILUN

Assignees

  • 海南美亚电能有限公司

Dates

Publication Date
20260512
Application Date
20260123

Claims (10)

  1. 1. A power distribution method for analyzing peaks of electrical energy, comprising: S1, constructing a power grid state model; s2, identifying peak load nodes in a power grid based on the power grid state model, and predicting the load change trend of at least one node; S3, constructing a virtual power grid environment based on the power grid state model and the load change trend, simulating a plurality of candidate power distribution strategies in the virtual power grid environment, and analyzing the influence degree of each strategy on power grid power flow distribution; and S4, selecting a strategy which minimizes the power flow congestion risk as a target power distribution strategy according to the influence degree analysis result of each strategy, and executing the strategy.
  2. 2. The method for power distribution for analyzing peak power according to claim 1, wherein said step S1 specifically includes: Step S11, topology structure data and equipment parameter data of a power grid are obtained; Step S12, determining state variables and measurement variables of the power grid according to the topological structure data and the equipment parameter data; step S13, establishing a mathematical model of power grid state estimation based on the state variables and the measured variables; and S14, initializing parameters of the mathematical model, and constructing the power grid state model.
  3. 3. The method for power distribution for analyzing peak power according to claim 1, wherein said step S2 specifically comprises: s21, extracting load data of each node in a set historical period and a current period from the power grid state model; S22, analyzing the load level and change of each node according to the extracted load data, and identifying the node with the load level exceeding the corresponding threshold value as a peak load node based on a preset peak value judging rule; step S23, calculating the load change trend of at least one peak load node in the future set period by a load prediction model based on the historical load sequence, the real-time load data and the environmental factors; And step S24, generating and outputting a data set containing the peak load node identification information and the corresponding load change trend prediction result.
  4. 4. A power distribution method for analyzing peak power according to claim 3, wherein step S23 specifically includes: step S231, collecting and integrating historical load sequence data, real-time load monitoring data and associated environmental factor data of the peak load node; Step S232, preprocessing and characteristic engineering are carried out on the integrated data, and time sequence characteristics, statistical characteristics and environmental characteristics related to load change are extracted; step S233, inputting the data subjected to the characteristic engineering treatment into a pre-trained load prediction model, and executing prediction calculation to obtain a load prediction sequence of the node in a future set period; And step S234, carrying out trend analysis on the load prediction sequence, and identifying and outputting the change direction, the change rate and the key turning points of the load along with time to form the load change trend.
  5. 5. The method for power distribution for analyzing peak power according to claim 1, wherein said step S3 specifically comprises: step S31, based on the power grid state model, importing the load change trend as a dynamic boundary condition in a future period, and constructing a virtual power grid environment for strategy simulation analysis; step S32, configuring at least two different candidate distribution strategies in the virtual power grid environment, wherein the candidate distribution strategies comprise control instructions for at least one of load, energy storage, distributed power supply and reactive compensation equipment; Step S33, aiming at each candidate distribution strategy, executing load flow calculation simulation in the virtual power grid environment, and simulating the steady state or dynamic running state of the power grid after the strategy is implemented; And step S34, extracting a power flow distribution result obtained by each simulation, calculating at least one index of the running state of the power grid, and evaluating and outputting the influence degree of each candidate distribution strategy on the power flow distribution of the power grid based on the index.
  6. 6. The method for analyzing peak power distribution according to claim 5, wherein step S33 specifically includes: Step S331, according to the candidate distribution strategy, adjusting operation parameters of controllable equipment in the virtual power grid environment; Step S332, based on the operation parameters, adopting a hybrid power flow simulation algorithm to automatically switch between the dynamic power flow and the steady-state power flow; step S333, circularly executing simulation according to time step length, and simulating a continuous operation process of the power grid within a set time length after strategy implementation; step S334, recording key operation state quantity of the power grid in the whole simulation process; And step 335, analyzing the running state quantity, and extracting characteristic indexes representing the steady state and dynamic process of the power grid as the running state of the power grid after the strategy is implemented.
  7. 7. The method of claim 6, wherein the step S332 specifically includes: a1, acquiring the operation parameters, initializing the mixed power flow simulation algorithm, and setting a switching threshold between dynamic power flow and steady-state power flow; A2, in the simulation process, calculating an index of the power grid state change rate, and comparing the index with the switching threshold; and A3, when the index exceeds the switching threshold, automatically calling the dynamic power flow to calculate, and when the index is lower than or equal to the switching threshold, automatically calling the steady-state power flow to calculate.
  8. 8. A system for applying the electrical power distribution method for analyzing peak electrical energy of any one of claims 1-7, comprising: The state modeling module is used for acquiring power grid operation data and constructing a power grid state model; the prediction analysis module is used for identifying peak load nodes in the power grid based on the power grid state model and predicting the load change trend of at least one node; The simulation evaluation module is used for constructing a virtual power grid environment based on the power grid state model and the load change trend, simulating various candidate power distribution strategies in the virtual power grid environment and analyzing the influence degree of each strategy on power grid power flow distribution; and the policy decision and execution module is used for selecting a policy which minimizes the risk of the flow congestion as a target power distribution policy according to the analysis result of the influence degree of each policy, and generating a control instruction for execution.
  9. 9. A terminal device comprising a memory, a processor and computer instructions stored in the memory and capable of running on the processor, the processor implementing the steps of the method of analysing peak power distribution according to any one of claims 1 to 7 when executing the computer program.
  10. 10. A computer readable storage medium having instructions stored thereon which, when run on a computer, cause the computer to perform the method of analysing electrical energy peak power distribution according to any one of claims 1 to 7.

Description

Power distribution method, system, terminal equipment and medium for analyzing electric energy peak value Technical Field The invention relates to the technical field of electric energy distribution, in particular to a power distribution method, a system, terminal equipment and a medium for analyzing electric energy peaks. Background When the electric energy reaches a peak, the power grid bears huge pressure, and the original distribution line can be overloaded or unbalanced. The power flow direction is optimized rapidly by re-distributing the power, surplus power is scheduled to an emergency area, the key node pressure is relieved, and the overload damage or power failure risk of equipment is avoided. The method not only improves the instantaneous bearing capacity and the power supply reliability of the power grid, but also promotes clean energy consumption, and is a key emergency measure for guaranteeing the electricity safety and realizing the coordination of the source network. When the monitoring system finds that the electricity load of a certain area exceeds a preset safety threshold value during the current power distribution, one or more control instructions preset by engineers are automatically triggered. These instructions are typically simple logic to "if zone a is overloaded, close a standby line switch that connects zone B," and call power from zone B to zone a. However, when the system executes the preset control command, the current power supply capacity of the zone B, the residual capacity of the power transmission channel and the overall operation conditions of other adjacent zones are not calculated and evaluated. Therefore, in the complicated real power grid distribution, other electric energy flow congestion is easily caused by using simple logic of a preset control instruction, so that the problem is transferred and even expanded. Disclosure of Invention The invention aims to provide a power distribution method, a system, terminal equipment and a medium for analyzing an electric energy peak value, so as to solve the technical problems that other electric energy flow congestion is easily caused by simple logic using a preset control instruction, and the problem is transferred or even enlarged. The technical scheme of the invention is realized as follows: the invention provides a method for analyzing peak power distribution of electric energy, which comprises the following steps: S1, constructing a power grid state model; s2, identifying peak load nodes in a power grid based on the power grid state model, and predicting the load change trend of at least one node; S3, constructing a virtual power grid environment based on the power grid state model and the load change trend, simulating a plurality of candidate power distribution strategies in the virtual power grid environment, and analyzing the influence degree of each strategy on power grid power flow distribution; and S4, selecting a strategy which minimizes the power flow congestion risk as a target power distribution strategy according to the influence degree analysis result of each strategy, and executing the strategy. The further technical scheme is that the step S1 specifically includes: Step S11, topology structure data and equipment parameter data of a power grid are obtained; Step S12, determining state variables and measurement variables of the power grid according to the topological structure data and the equipment parameter data; step S13, establishing a mathematical model of power grid state estimation based on the state variables and the measured variables; and S14, initializing parameters of the mathematical model, and constructing the power grid state model. The further technical scheme is that the step S2 specifically includes: s21, extracting load data of each node in a set historical period and a current period from the power grid state model; S22, analyzing the load level and change of each node according to the extracted load data, and identifying the node with the load level exceeding the corresponding threshold value as a peak load node based on a preset peak value judging rule; step S23, calculating the load change trend of at least one peak load node in the future set period by a load prediction model based on the historical load sequence, the real-time load data and the environmental factors; And step S24, generating and outputting a data set containing the peak load node identification information and the corresponding load change trend prediction result. The further technical scheme is that the step S23 specifically includes: step S231, collecting and integrating historical load sequence data, real-time load monitoring data and associated environmental factor data of the peak load node; Step S232, preprocessing and characteristic engineering are carried out on the integrated data, and time sequence characteristics, statistical characteristics and environmental characteristics related to load change are extrac