CN-121984027-A - Power grid control method and system

CN121984027ACN 121984027 ACN121984027 ACN 121984027ACN-121984027-A

Abstract

The invention belongs to the technical field of comprehensive energy system planning, and particularly relates to a power grid control method and system. The power grid control method comprises the following steps of setting constraint conditions of new energy power generation, adjustable power load, electrolytic hydrogen production and energy storage, predicting safety parameters through tide calculation, determining an objective function, constructing a corresponding relation between a punishment function and a threshold crossing value of the safety parameters, carrying out optimization solution on a solution variable through an intelligent algorithm to obtain an optimal variable for realizing the objective function, executing the optimal variable, and judging whether the safety parameters are out of limit in real time in the executing process. The hydrogen capacity of the electrolytic hydrogen production and the energy storage capacity constraint of the energy storage device and the power grid safety constraint are fully considered, and the safety stability of the hydrogen production device, the adjustable power load and the electrochemical energy storage device and the economical efficiency of the system operation are ensured through the hydrogen, the adjustable power load and the capacity constraint of electrochemical energy storage and the power flow constraint.

Inventors

GENG XIANFU
LIU WEI
ZHAO DONGSHENG
SUN GANG
WANG JIAOBO
GAO HONGJIAN

Assignees

中国石油化工股份有限公司
中国石油化工股份有限公司中原油田分公司

Dates

Publication Date: 20260505
Application Date: 20241029

Claims (10)

1. The power grid control method is characterized by comprising the following steps of: S1, setting constraint conditions of a new energy power generation device A, an adjustable power load device B, an electrolysis hydrogen production device C and an energy storage device D in a prediction period, and initializing a solving variable, wherein the solving variable comprises the power generation of the A, the load power of the B, the hydrogen production power of the C and the charging/discharging power of the D; S2, predicting safety parameters through load flow calculation according to the public power grid, the historical data of A-D and the solving variables in the initialized population in the S1, wherein the safety parameters comprise the load flow of each branch, the voltage of each node, the power grid loss, the hydrogen capacity of C, the energy storage capacity of D and the load energy of B; S3, determining an objective function based on the optimal active power and the lowest cost of the power grid operation, and constructing a corresponding relation between a penalty function and an out-of-limit value of a safety parameter based on the safety operation of the power grid and each device; S4, under the constraint conditions of the fitness function and the penalty function, optimizing and solving the solving variables through an intelligent algorithm according to the objective function to obtain and execute the optimal variables for realizing the objective function; And S5, judging whether the safety parameters are out of limit in real time in the execution process, if not, continuing to execute, and if so, returning to the step S2 to carry out optimization solution on the solution variables in the residual prediction period according to the real-time data.
2. The grid control method according to claim 1, wherein the maximum power generated in the prediction period is obtained as the constraint condition of the new energy power generation device a by a prediction algorithm using the power generation data of the new energy power generation device corresponding to the historical meteorological data.
3. The power grid control method according to claim 1, wherein the constraint conditions of the adjustable electric load device B, the electrolytic hydrogen production device C and the energy storage device D are determined as the sectional constraint conditions based on a change curve of load power of the adjustable electric load with load energy generated by the adjustable electric load device, a change curve of hydrogen production power of the electrolytic hydrogen production device with hydrogen capacity in the device, and a change curve of charge/discharge power of the energy storage device with energy storage capacity, respectively.
4. The grid control method of claim 3, wherein the segment constraint of the adjustable electrical load device B is that the load power of B is a constant value Y 1 when the load energy of B is 0~X 1 , is 0~Y 2 when the load energy of B is raised to X 1 ～X 2 , wherein Y 1 ＞Y 2 , and is 0 when the load energy of B is continued to be raised to X 2 ～X max .
5. The power grid control method as set forth in claim 3, wherein the sectional constraint condition of said electrolytic hydrogen production device C is that the hydrogen production power of C is a constant value Z 1 when the hydrogen capacity is 0~V 1 , is 0~Z 2 when the hydrogen capacity is raised to V 1 ～V 2 , wherein Z 1 ＞Z 2 , and is 0 when the hydrogen capacity is continued to be raised to V 2 ～V max .
6. The method of claim 3, wherein the segment constraint condition of the energy storage device D is that when the energy storage capacity is 0~E 1 , the discharging power of D is a constant value W 1 , the charging power is a constant value W 2 , wherein W 1 ＜W 2 , when the energy storage capacity is increased to E 1 ～E 2 , the discharging power of D is a value of 0~W 3 , the charging power is a value of 0~W 4 , wherein W 1 ＜W 3 ,W 4 ＜W 2 , when the energy storage capacity is increased to E 2 ～E 3 , the discharging power of D is a value of 0~W 3 , the charging power is a value of 0~W 5 , wherein W 5 ＜W 4 , and when the energy storage capacity is increased to E 3 ～E max , the discharging power of D is a value of 0~W 3 , and the charging power is 0.
7. The grid control method according to claim 1, wherein the expression of the objective function Y is: P Gridi ＝f(Pnei j ,Pesi j ,Pldi j ,Phi j ) The power generation system comprises a power generation device, a power generation device and a power generation device, wherein Pnei j is the power generation power of a new energy power generation device in the ith and the jth, pesi j is the discharge power of an energy storage device in the ith and the jth, pldi j is the load power of an adjustable power load device in the ith and the jth, phi j is the hydrogen generation power of an electrolytic hydrogen generation device in the ith and the jth, P Gridi is the active power of a public power grid, P Gridi is obtained by power flow calculation by taking the operating power of the new energy power generation device, the energy storage device, the adjustable power load device and the electrolytic hydrogen generation device as parameters, eta is the hydrogen generation efficiency of the electrolytic hydrogen generation device, c Hydrogen gas is the hydrogen price, and c Electric power j is the time-sharing price of the power grid.
8. The grid control method of claim 1, wherein the penalty function is expressed as: Wherein f (P bij ) is the maximum current-carrying capacity function of the j-th hour of the line i, f (U ij ) is the voltage threshold function of the j-th hour of the node i, f (P lossj ) is the system grid loss threshold function of the j-th hour, f (V ij ) is the hydrogen capacity threshold function of the j-th hour of the i-th set of electrolytic water hydrogen production device, f (E ij ) is the capacity threshold function of the j-th hour of the i-th set of energy storage device, f (T ij ) is the load energy threshold function of the j-th hour of the i-th set of adjustable power load device, and k 1 、k 2 ………k 6 are the linear proportion coefficients of the threshold values respectively.
9. The grid control method of claim 1, wherein the fitness function is: P=C-Y Wherein Y is an objective function, and C is a value which is an order of magnitude greater than Y; Converting the constraint solving objective function P into an unconstrained solving objective function F through a punishment function: F=G×P where f is a penalty function.
10. The power grid control system is characterized by comprising a data acquisition module, a calculation module and a control instruction issuing module, wherein the data acquisition module is used for collecting real-time data, historical data and weather prediction information of a power grid, a new energy power generation device A, an adjustable power load device B, an electrolysis hydrogen production device C and an energy storage device D; the calculation module is used for setting constraint conditions of A-D in a prediction period, initializing a population, and carrying out optimization solution on solution variables including power generation power of A, load power of B, hydrogen production power of C and charging/discharging power of D, calculating prediction safety parameters according to historical data of a power grid, A-D and the solution variables in the initialization population through power flow, wherein the safety parameters comprise power flow of each branch, voltage of each node, power grid loss, hydrogen capacity of C, energy storage capacity of D and load energy of B; The control instruction issuing module is used for issuing control instructions of optimal variables, judging whether safety parameters are out of limit in real time in the process of executing the control instructions by the system, if not, continuing to execute the control instructions, and if so, returning to the calculation module to carry out optimal solution on solution variables in the residual prediction period again according to real-time data.

Description

Power grid control method and system Technical Field The invention relates to the technical field of comprehensive energy system planning, in particular to a power grid control method and system. Background At present, the power grid system gradually turns to the emerging industries of power grid power generation, new energy power generation, power load, hydrogen production by electrolysis of water and the like from the traditional power grid power generation and power load production, and the power grid is changed into a novel power system integrating source power grid and load storage from the traditional power grid and load structure. Currently, for the control of an electric power system, a public power grid mainly considers wind power photovoltaic power generation, electrochemical energy storage and the like, and a regional comprehensive energy demonstration park mainly considers wind power photovoltaic power generation, electrochemical energy storage, steam heat supply and the like. A control method for public power grid and comprehensive energy demonstration park power grid mainly aims at power grid safety, heat supply network safety and economic operation. The published application publication number CN117408471A of the application published in 1 month of 2024 discloses a comprehensive energy park variable constraint multi-target optimization control method and system, a mathematical model is built for various energy devices of a park comprehensive energy system, constraint targets and related constraint conditions are then established, the efficiency of an energy storage battery and the photovoltaic output are predicted according to weather and equipment conditions, related constraints are timely adjusted, and finally the constraint targets and the constraint targets are solved through Cplex, so that the comprehensive energy system multi-target optimization planning is perfected, and the running stability of the comprehensive energy system is improved on the basis of ensuring economy, environmental protection and renewable energy power generation. However, in recent years, enterprises gradually construct novel power systems (as shown in fig. 1) which are integrated with power grid power generation, wind power photovoltaic power generation, electrochemical energy storage, adjustable power load, non-adjustable power load, water electrolysis hydrogen production and the like, and control objects of the novel power systems are more than those of public power grids and comprehensive energy demonstration parks, and control objects of the novel power systems are more complex. In order to ensure safe, economical and efficient operation of the novel power grid, the capacity constraints of hydrogen, adjustable power load and electrochemical energy storage are required to be prioritized, and the power grid safety constraints are considered. When the above problems are considered, it is necessary to solve the power of the power generation/load of a plurality of types of control objects (wind photovoltaic power generation, electrochemical energy storage, adjustable electric load, hydrogen production by electrolysis of water, etc.). The solved variable is large in scale and huge, and each time of solving, various safety constraints are needed to be considered and stability calculation of the power load is needed, and the stability calculation is mainly carried out on power flow calculation to determine that node voltage, branch power flow, network loss and the like are not out of limit. Thus, the prior art lacks a control method that efficiently and stably optimizes multiple objectives for a new power system. Disclosure of Invention The invention aims to provide a power grid control method, which solves the problem that the existing control method cannot realize efficient and stable multi-objective optimization on a novel power system. The second object of the present invention is to provide a power grid control system, which solves the problem that the existing control system cannot realize efficient and stable multi-objective optimization for a novel power system. In order to solve the technical problems, the technical scheme of the power grid control method of the invention is as follows: A method of grid control, comprising the steps of: S1, setting constraint conditions of a new energy power generation device A, an adjustable power load device B, an electrolysis hydrogen production device C and an energy storage device D in a prediction period, and initializing a solving variable, wherein the solving variable comprises the power generation of the A, the load power of the B, the hydrogen production power of the C and the charging/discharging power of the D; S2, predicting safety parameters through load flow calculation according to the public power grid, the historical data of A-D and the solving variables in the initialized population in the S1, wherein the safety parameters comprise the load flow of each br