CN-121984021-A - New energy power system optimization method considering transient frequency safety constraint

CN121984021ACN 121984021 ACN121984021 ACN 121984021ACN-121984021-A

Abstract

The invention belongs to the technical field of power systems, and relates to a new energy power system optimization method considering transient frequency safety constraint. The method comprises the following key steps of S1, constructing a frequency dynamic model of an electric power system, determining a nonlinear expression of a maximum frequency deviation constraint, S2, converting the nonlinear expression into a linear approximation form through variable replacement, S3, substituting the linear approximation obtained in S2 into an original frequency minimum point constraint to obtain a second order cone constraint SOC constraint form, S4, integrating the second order cone constraint into a frequency constraint optimization model, combining the second order cone constraint with other constraints, and solving an objective function by using a CPLEX business solver to obtain an optimization scheme. By implementing the method, the device and the system, the frequency constraint optimization problem can be solved rapidly on the premise of not increasing the complexity of the model, the frequency stability of the power system under large disturbance is improved, and the method and the system are suitable for the scenes of power generation scheduling, standby planning and the like.

Inventors

YU LINLIN
SHAO HONGBO
YAN XINTONG
ZHAO YABO
JIA PENG
CHENG YUMING
CHEN SHUYU
MAO YUBIN
ZHANG LIHUA
DING DONG
WANG CHUANJIE

Assignees

国网河南省电力公司经济技术研究院

Dates

Publication Date: 20260505
Application Date: 20251231

Claims (7)

1. The new energy power system optimization method considering transient frequency safety constraint is characterized by comprising the following key steps: s1, constructing a power system frequency dynamic model, and determining a nonlinear expression of maximum frequency deviation constraint; s2, converting the nonlinear expression into a linear approximation form through variable replacement, simplifying the constraint of the lowest frequency point into a single-input single-output model at a critical point, and deriving an analytical expression of y with respect to x through analysis LambertW functions, and approximating the relationship with a linear function y=alpha x+beta; S3, substituting the linear approximation obtained in the S2 into the original frequency minimum point constraint to obtain a second order cone constraint SOC constraint form; and S4, integrating the second order cone constraint into a frequency constraint optimization model, and then combining the second order cone constraint with other constraints, and solving an objective function by using a CPLEX business solver to obtain an optimization scheme.
2. The new energy power system optimization method taking into account transient frequency security constraints according to claim 1, wherein the frequency dynamic model in S1 is represented by the following differential equation: Where Δf (t) is the frequency deviation, Δp PFR (t) is the Primary Frequency Regulated (PFR) power, H is the system inertia time constant, D P is the load damping, and Δp L is the power disturbance.
3. The new energy power system optimization method considering transient frequency security constraints of claim 2, wherein the primary frequency response process is modeled as a piecewise linear function, the functional expression being as follows: Where t DB is the time for the frequency deviation to reach the dead band, R PFR is the PFR capacity, t PFR is the PFR lead time, Is the rate of the PFR ramp up.
4. The new energy power system optimization method considering transient frequency security constraint according to claim 1, wherein the nonlinear expression of the maximum frequency deviation constraint in S1 is: Where f m is the frequency floor predefined limit and Δf DB is the frequency dead band.
5. The method for optimizing the new energy power system taking the transient frequency security constraint into consideration as claimed in claim 3 or 4, wherein the step S2 is specifically to introduce three new variables x, y and z, and obtain the non-linear expression of x, y and z by replacing the variable with the non-linear expression of S1 as follows: z=f m +Δf DB wherein x and y are related by a critical point analysis, z is a constant, and the derivative of y tends to be at a limit of-; converting a nonlinear expression of the maximum frequency deviation constraint into an expression of x, y and z, wherein the expression is a single-input single-output model, and the expression is as follows: Converting the equation of x, y, z into an equation comprising LambertW functions: argument of Lambert W function The method is close to the point of-e -1 , Referring to the classical expansion formula of the Lambert W function near the branching point, there is an approximate expansion for the close variables: e u ≈1+u(u→0) The method can obtain: y and x have a linear relationship under certain conditions, and the relationship is as follows: y=αx+β Where α and β are parameters of a linear function, which can be estimated by a weighted least squares method, the weights can be evenly distributed or determined from the frequency of occurrence of the corresponding x values, once determined, α and β are considered constant within the optimization framework.
6. The method for optimizing a new energy power system taking into account transient frequency safety constraints as defined in claim 5, wherein said S3 is specifically a nonlinear expression of substituting a linear relationship between y and x into a maximum frequency deviation constraint, said expression being as follows: 2HC PFR α 2 ≥(ΔP L -(β+Δf DB )D P ) 2 the second order cone constraints are specifically expressed as: 。
7. The method for optimizing the new energy power system taking the transient frequency security constraint into consideration of claim 6, wherein the other constraints in S4 are a system inertia constraint, a PFR capacity constraint, a PFR climbing rate constraint, a unit output constraint and a disturbance constraint.

Description

New energy power system optimization method considering transient frequency safety constraint Technical Field The invention belongs to the technical field of power systems, and relates to a new energy power system optimization method considering transient frequency safety constraint. Background With the aggravation of global energy crisis and the increasing of environmental pollution, the great development of new energy sources such as wind energy, solar energy and the like has become the necessary trend of the development of electric power systems. However, the dynamic characteristics of the power system are deeply changed by the access of high-proportion new energy, and the optimized operation of the system is severely challenged. The system inertia level is remarkably reduced, and the new energy units are usually connected with the grid through a power electronic converter, and are difficult to provide physical rotational inertia unlike the traditional synchronous generator. With the improvement of the permeability of new energy, the equivalent inertia of the power system is greatly reduced, so that the disturbance rejection capability of the system is weakened. The risk of frequency stability increases when high power disturbances (e.g., generator tripping, dc blocking) occur, the frequency change rate (RoCoF) of the low inertia system is faster and the frequency Nadir (Nadir) is lower. If the frequency deviation exceeds the safety threshold, a low frequency load shedding (UFLS) will be triggered and even a system crash will be caused. The limitation of the traditional optimization method is that the traditional power system optimization operation (such as unit combination and economic dispatch) usually only considers steady-state power balance, or only adopts simplified static frequency constraint, so that transient frequency dynamic under large disturbance is difficult to accurately reflect. In the existing optimization method considering transient frequency safety constraint, the maximum frequency deviation constraint presents high nonlinearity and non-convexity. In order to solve the problem, the prior art adopts piecewise linearization (introducing a large number of binary variables to increase the calculation burden) or adopts an intelligent algorithm (difficult to ensure global optimum and long calculation time), and is difficult to meet the double requirements of real-time scheduling of a large power grid on calculation efficiency and precision. Therefore, a new energy power system optimizing operation method capable of accurately describing frequency dynamic characteristics under large disturbance and solving efficiently is needed, so that the economy of system operation is improved on the premise of ensuring frequency safety. Disclosure of Invention In order to achieve the above purpose, the invention provides a new energy power system optimization method considering transient frequency safety constraint. The method has high precision, strong adaptability and easy solution to the problem of frequency constraint optimization. By studying the analytical expressions of the lowest frequency points, we have found that highly nonlinear expressions can be accurately approximated as linear expressions by variable substitution within the actual system parameters. This approximation can be used to construct a second order cone constraint that can be efficiently processed by a commercial solver. Compared with the prior art, the method provides a global and accurate approximation on the premise of not increasing the complexity of the optimization model. The technical scheme adopted by the invention is that the new energy power system optimization method taking the transient frequency safety constraint into consideration comprises the following key steps: s1, constructing a power system frequency dynamic model, and determining a nonlinear expression of maximum frequency deviation constraint; s2, converting the nonlinear expression into a linear approximation form through variable replacement, simplifying the constraint of the lowest frequency point into a single-input single-output model at a critical point, and deriving an analytical expression of y with respect to x through analysis LambertW functions, and approximating the relationship with a linear function y=alpha x+beta; S3, substituting the linear approximation obtained in the S2 into the original frequency minimum point constraint to obtain a second order cone constraint SOC constraint form; and S4, integrating the second order cone constraint into a frequency constraint optimization model, and then combining the second order cone constraint with other constraints, and solving an objective function by using a CPLEX business solver to obtain an optimization scheme. Further, the frequency dynamic model in S1 is represented by the following differential equation: Where Δf (t) is the frequency deviation, Δp PFR (t) is the Primary Frequency Regulated (P