CN-122026527-A - Wind-solar heat storage multi-energy system optimal scheduling method based on self-adaptive dynamic programming

CN122026527ACN 122026527 ACN122026527 ACN 122026527ACN-122026527-A

Abstract

The invention relates to the technical field of energy optimal scheduling, and particularly provides a wind-solar-thermal storage multi-energy system optimal scheduling method based on self-adaptive dynamic planning. The method is characterized in that the coupling effect of heat conduction hysteresis-form difference of rotor thermal stress is reversely utilized, namely, the hot air risk trend quantification is completed through the form deviation of the node virtual temperature and a reference sequence, then risk adjustment coefficients, battery polarization impedance and charge constraint items are extracted under the power adjustment working condition, and battery suppression weights are calculated through normalization and feature fusion. The system automatically distributes scheduling instructions to the battery and the photo-thermal power station by embedding dynamic weights into a quadratic programming objective function. The invention takes 'radial temperature field deduction-thermal expansion stress prediction-shape deviation quantification' as a judging basis, eliminates the dead zone of single-point threshold value on heat conduction hysteresis, ensures the precision and response speed under second-level rolling optimization, and realizes the collaborative optimization of rotor thermal shock inhibition, battery aging delay and unit climbing cost.

Inventors

AN YI
ZHANG JIALE
ZHANG SHUYU
LI CHENCHEN
WANG WUCHEN
ZHANG SONGCAI
LIANG CHUNHUI

Assignees

长春工程学院

Dates

Publication Date: 20260512
Application Date: 20260413

Claims (10)

1. The wind-solar-thermal storage multi-energy system optimal scheduling method based on self-adaptive dynamic programming is characterized by comprising the following steps of: in the optimal scheduling of energy sources, the node temperature, the steam temperature, the battery current and the battery residual capacity of the rotor are obtained; acquiring an initial temperature of the node by performing attenuation analysis of shutdown start-up on the node temperature, correcting the initial temperature of the node by using the environment temperature to acquire a corrected temperature of the node, and performing recursive fusion analysis on the corrected temperature by using the steam temperature to acquire a virtual temperature of the node; Acquiring a predicted value of the expansion stress according to the distribution difference of the virtual temperature of the node; Obtaining a polarization voltage difference by analyzing the polarization loss of the battery; acquiring a battery impedance reference item through the difference between the polarized voltage difference and the battery current, and acquiring a charge constraint item based on attenuation penalty of the residual electric quantity of the battery; the method comprises the steps of calculating a feature fusion value of a risk adjustment coefficient, a battery impedance reference item and a charge constraint item normalization value, obtaining a battery inhibition weight, constructing an operation loss evaluation function, taking the battery inhibition weight as the weight of a battery power item in the operation loss evaluation function, and optimizing scheduling of an energy system according to output of the operation loss evaluation function, wherein the operation loss evaluation function comprises a battery power item and a photo-thermal power station power change item.
2. The optimal scheduling method for the wind-solar-thermal storage multi-energy system based on the adaptive dynamic programming according to claim 1, wherein the initial temperature obtaining method comprises the following steps: Judging the current shutdown starting state through a preset threshold value, judging cold start when the shutdown time length is larger than or equal to the preset threshold value, judging hot start when the shutdown time length is smaller than the preset threshold value, and carrying out attenuation analysis on the node through the shutdown time length to acquire the initial temperature of the node.
3. The method for optimizing and scheduling the wind-solar-thermal storage multi-energy system based on the adaptive dynamic programming according to claim 2, wherein the method for acquiring the attenuation analysis comprises the following steps: And obtaining the attenuation analysis result of the shutdown time length on the node temperature cooling based on the feature fusion of the natural cooling temperature and the environment temperature.
4. The optimal scheduling method for the wind-solar-thermal storage multi-energy system based on the adaptive dynamic programming according to claim 1, wherein the method for acquiring the node correction temperature comprises the following steps: Calculating the difference between the ambient temperature at the current moment and the predicted temperature of the surface of the rotor, weighting by using preset temperature weights to obtain a temperature correction difference at the current moment, correcting the initial temperature according to the temperature correction difference, and obtaining the corrected temperature at the current moment.
5. The method for optimizing and scheduling the wind-solar-thermal storage multi-energy system based on the adaptive dynamic programming according to claim 1, wherein the method for acquiring the node virtual temperature comprises the following steps: and carrying out weighted fusion according to a preset weighting coefficient based on the correction temperature of each node at the previous moment and the steam temperature at the current moment, and carrying out recursive analysis to obtain the node virtual temperature of each node at different moments.
6. The method for optimizing and scheduling the wind-solar-thermal storage multi-energy system based on the adaptive dynamic programming according to claim 1, wherein the method for acquiring the expansion stress predicted value comprises the following steps: And correcting by a material adjustment coefficient based on the difference between the node virtual temperature average values of all the node virtual temperature values at the current moment and the node virtual temperature of the boundary node of the rotor to obtain an expansion stress predicted value of the rotor.
7. The optimal scheduling method for the wind-solar-thermal storage multi-energy system based on the adaptive dynamic programming according to claim 1, wherein the acquiring method for the risk adjustment coefficient comprises the following steps: The method comprises the steps of obtaining a coupling matrix according to the difference between the expansion stress predicted value of a rotor and a preset reference value at different moments, obtaining all path tracks through dynamic path searching of the coupling matrix, obtaining the minimum value of all the maximum values according to the maximum value of all the path tracks, normalizing the minimum value to obtain a trend deviation value of a control period, and obtaining a risk adjustment coefficient at the current moment through negative correlation analysis weighted on the trend deviation value.
8. The adaptive dynamic programming-based optimal scheduling method for the wind-solar-thermal storage multi-energy system according to claim 1, wherein the method for acquiring the polarization voltage difference comprises the following steps: and analyzing the polarization loss of lithium ions in the electrode material according to the difference among the voltage of the energy storage battery, the open-circuit voltage and the internal resistance voltage, and obtaining the polarization voltage difference of the battery.
9. The adaptive dynamic programming-based optimal scheduling method for the wind-solar-thermal storage multi-energy system according to claim 1, wherein the method for correcting the attenuation of the residual battery power comprises the following steps: And based on the difference between the residual electric quantity of the battery and a preset threshold value, performing exponential decay punishment of over-charge and over-discharge of the battery to obtain a charge constraint item.
10. The adaptive dynamic programming-based optimal scheduling method for a wind-solar-thermal storage multi-energy system according to claim 1, wherein the operation loss evaluation function comprises: Wherein, the Representing the result of the running loss evaluation function of the current control period; battery inhibit weights representing the current control period; Representing the battery power solved by the current control period; representing a preset smoothing coefficient, which in this embodiment takes a value of 100; the power change rate of the photo-thermal power station for the current control period is represented.

Description

Wind-solar heat storage multi-energy system optimal scheduling method based on self-adaptive dynamic programming Technical Field The invention relates to the technical field of energy optimal scheduling, in particular to a wind-solar-thermal storage multi-energy system optimal scheduling method based on self-adaptive dynamic planning. Background In a novel power system taking new energy as a main body, a photo-thermal power station (CSP) has thermal power level schedulability and rotational inertia by virtue of a built-in heat storage and steam turbine generator unit, and becomes a basis for wind and light absorption, and electrochemical energy storage is in a millisecond response speed, such as a photoconduction shape, and stabilizes the random fluctuation of the new energy in parallel with the CSP. Therefore, an optimal scheduling method for the wind-solar heat storage multi-energy system gradually becomes a research hot spot. The existing scheduling technology only sets the fixed ramp rate to restrict the turbine output, but in actual operation, the rotor thermal stress peak value is obviously later than the power change due to radial heat conduction lag, the space-time dislocation is not only derived from the large mass thermal inertia of metal parts, but also is jointly influenced by multiple factors such as the temperature transient of main steam, the fluctuation of environment temperature, the electrochemical energy storage multiplying power characteristic and the like, the existing wind-solar heat storage system generally depends on the wall temperature or the SOC single-point threshold value at the current moment to trigger the power distribution, and because the battery polarization and the thermal stress response curve form are different, the optimization weight only depends on whether to exceed the limit or not rather than the future stress trend, the fixed battery suppression weight cannot accurately reflect the local evolution of the thermal risk, so that the response time lag is caused when the wind-solar heat storage multi-energy optimal scheduling is performed. Disclosure of Invention In order to solve the technical problem that the rotor thermal stress peak value is significantly later than the power change due to radial heat conduction lag, so that the optimization weight precision is reduced, and the response time is delayed in the process of wind-solar heat storage multi-energy optimization scheduling, the invention aims to provide a wind-solar heat storage multi-energy system optimization scheduling method based on self-adaptive dynamic programming, and the adopted technical scheme is as follows: The invention provides a wind-solar-thermal storage multi-energy system optimal scheduling method based on self-adaptive dynamic programming, which comprises the following steps: in the optimal scheduling of energy sources, the node temperature, the steam temperature, the battery current and the battery residual capacity of the rotor are obtained; acquiring an initial temperature of the node by performing attenuation analysis of shutdown start-up on the node temperature, correcting the initial temperature of the node by using the environment temperature to acquire a corrected temperature of the node, and performing recursive fusion analysis on the corrected temperature by using the steam temperature to acquire a virtual temperature of the node; Acquiring a predicted value of the expansion stress according to the distribution difference of the virtual temperature of the node; Obtaining a polarization voltage difference by analyzing the polarization loss of the battery; acquiring a battery impedance reference item through the difference between the polarized voltage difference and the battery current, and acquiring a charge constraint item based on attenuation penalty of the residual electric quantity of the battery; the method comprises the steps of calculating a feature fusion value of a risk adjustment coefficient, a battery impedance reference item and a charge constraint item normalization value, obtaining a battery inhibition weight, constructing an operation loss evaluation function, taking the battery inhibition weight as the weight of a battery power item in the operation loss evaluation function, and optimizing scheduling of an energy system according to output of the operation loss evaluation function, wherein the operation loss evaluation function comprises a battery power item and a photo-thermal power station power change item. Further, the method for acquiring the initial temperature comprises the following steps: Judging the current shutdown starting state through a preset threshold value, judging cold start when the shutdown time length is larger than or equal to the preset threshold value, judging hot start when the shutdown time length is smaller than the preset threshold value, and carrying out attenuation analysis on the node through the shutdown time length to acquire the i