CN-122026445-A - ALK-PEM series-parallel system control method and device based on wind and light fluctuation

CN122026445ACN 122026445 ACN122026445 ACN 122026445ACN-122026445-A

Abstract

The specification provides an ALK-PEM series-parallel system control method and device based on wind and light fluctuation. The method comprises the steps of determining a total power target value to be distributed of a target electrolytic cell series-parallel system according to input power of an external fluctuation power supply, constructing a corresponding particle coding sequence according to the number of electrolytic cell units, carrying out iterative optimization processing on the particle coding sequence according to operation physical boundary parameters by using a preset particle swarm optimization model, determining target particle position information, determining start-stop state combination and power distribution proportion of each electrolytic cell unit in the target electrolytic cell series-parallel system according to the target particle position information by using a preset power distribution rule, and determining operation power values of each electrolytic cell unit in the target electrolytic cell series-parallel system according to the start-stop state combination, the power distribution proportion and the total power target value to be distributed. Therefore, the accurate determination of the total power target value to be distributed according to the input power of the external fluctuating power supply is realized, and the technical defect of power response lag is overcome.

Inventors

WANG GUANGCHUN
ZHOU ZUXU
LEI ZHENYUAN
LIU JUN
HAN WENJIE
WANG JIE

Assignees

中电建新能源集团股份有限公司

Dates

Publication Date: 20260512
Application Date: 20260410

Claims (10)

1. An ALK-PEM series-parallel system control method based on wind and light fluctuation is characterized by comprising the following steps: Acquiring the input power of an external fluctuation power supply and the operation parameters of a target electrolytic cell series-parallel system, wherein the operation parameters comprise the number of each electrolytic cell unit and corresponding operation physical boundary parameters; Determining a total power target value to be distributed of the target electrolytic tank series-parallel system according to the input power of the external fluctuation power supply; constructing corresponding particle coding sequences according to the number of the electrolytic tank units; Performing iterative optimization processing on the particle coding sequence according to the running physical boundary parameters by using a preset particle swarm optimization model to determine target particle position information, wherein the iterative optimization processing process comprises the steps of dynamically adjusting search step length by adopting a linearly decreasing inertia weight adjustment strategy and performing optimization processing by taking a multi-objective function as an evaluation criterion; Determining the start-stop state combination and the power distribution proportion of each electrolytic cell unit in the target electrolytic cell series-parallel system according to the target particle position information by utilizing a preset power distribution rule; and determining the operation power value of each electrolytic cell unit in the target electrolytic cell series-parallel system according to the start-stop state combination, the power distribution proportion and the total power target value to be distributed.
2. The method of claim 1, wherein the performing iterative optimization on the particle encoded sequence according to the running physical boundary parameters using a preset particle swarm optimization model to determine target particle location information comprises: Determining the initial position of each particle in the particle swarm according to the particle coding sequence and the operation physical boundary parameter; determining the current cost value of each particle according to the current position of each particle and the multi-objective function; according to the current cost value, determining individual target positions of each particle and group target positions of the particle group; Determining the group center position of the particle swarm according to the individual target positions of all the particles; determining a current inertia weight parameter according to the current iteration times, a preset iteration stop threshold value and a linearly decreasing inertia weight adjustment strategy; determining an updated position of each particle according to the individual target position, the group center position and the current inertia weight parameter; And repeatedly executing the steps of determining the current cost value to determine the update position until the iteration times reach the preset iteration stop threshold value, and obtaining the target particle position information according to the group target position.
3. The method of claim 2, wherein determining the current cost value of each particle based on the current location of each particle and the multi-objective function comprises: Determining the running state and the distribution power value of each electrolytic cell unit according to the current position of each particle and the running physical boundary parameters of each electrolytic cell unit; Determining evaluation values of evaluation factors in the multi-objective function according to the running state, the distributed power value and the total power target value to be distributed, wherein the evaluation factors comprise a power tracking factor, a start-stop factor, a hydrogen production efficiency factor and an electric energy quality factor; And according to the evaluation value of each evaluation factor and the preset weight corresponding to each evaluation factor, carrying out fusion calculation by utilizing the multi-objective function, and determining the current cost value of each particle.
4. A method according to claim 3, wherein the determining, by using a preset power distribution rule, a start-stop state combination and a power distribution ratio of each cell unit in the target electrolytic cell series-parallel system according to the target particle position information includes: Determining the running state of each electrolytic cell unit according to the target particle position information and a preset state switching threshold value, and obtaining the start-stop state combination; determining the basic operation power of each electrolytic cell unit in an open state according to the start-stop state combination and the operation physical boundary parameters corresponding to each electrolytic cell unit; determining the residual power to be distributed according to the total power target value to be distributed and the sum of the basic operation power; according to a proportion distribution criterion in a preset power distribution rule, determining the optimized incremental power corresponding to each electrolytic cell unit according to the numerical proportion relation among elements in the target particle position information and the residual power to be distributed; and according to constraint correction criteria in the preset power distribution rule, the climbing rate limit and the power operation range corresponding to each electrolytic cell unit are corrected to the sum of the basic operation power and the optimized incremental power, and the power distribution proportion corresponding to each electrolytic cell unit is determined.
5. The method of claim 4, wherein determining the operating power value for each cell unit in the target cell series-parallel system based on the start-stop state combination, the power distribution ratio, and the total power target to be distributed comprises: determining a target electrolytic cell unit in an open state according to the start-stop state combination; Determining the lower limit value of the operation power corresponding to each target electrolytic cell unit according to the operation physical boundary parameters; Determining the residual total power to be distributed according to the difference between the sum of the running power lower limit values and the total power target value to be distributed; Performing incremental allocation calculation on the total power to be allocated by using the power allocation proportion corresponding to each target electrolytic cell unit to obtain an additional power allocation value corresponding to each target electrolytic cell unit; And determining the operation power value of each electrolytic cell unit according to the start-stop state combination, the operation power lower limit value corresponding to each target electrolytic cell unit and the additional power distribution value.
6. The method of claim 5, wherein determining the total power to be allocated target value of the target electrolytic cell series-parallel system based on the external fluctuating power supply input power comprises: obtaining conversion efficiency corresponding to the input power of the external fluctuation power supply and auxiliary machine operation power consumption of the target electrolytic tank series-parallel system; Determining a preliminary power value according to the conversion efficiency of the current transformation for the input power of the external fluctuation power supply; And determining the total power target value to be distributed according to the difference between the primary power value and the auxiliary machine operation power consumption.
7. The method of claim 6, wherein after said determining the operating power value for each cell unit in said target cell series-parallel system based on said start-stop state combination, said power distribution ratio, and said total power to be distributed target value, said method further comprises: Determining modulation control parameters of power conversion equipment corresponding to each electrolytic tank unit according to the operation power value corresponding to each electrolytic tank unit; determining a direct current output current of the power conversion device according to the modulation control parameter; and driving each electrolytic tank unit to carry out electrolytic hydrogen production treatment according to the direct current output current.
8. The method of claim 1, wherein after the obtaining the external fluctuating power supply input power and the operating parameters of the target electrolyzer series-parallel system, the method further comprises: and acquiring the dynamic hydrogen price of the current hydrogen market associated with the target electrolytic tank series-parallel system through a communication interface.
9. ALK-PEM series-parallel system control device based on scene fluctuation, characterized by comprising: The system comprises a data acquisition module, a target electrolytic cell series-parallel system and a control module, wherein the data acquisition module is used for acquiring the input power of an external fluctuation power supply and the operation parameters of the target electrolytic cell series-parallel system, wherein the operation parameters comprise the number of electrolytic cell units and corresponding operation physical boundary parameters; The total power determining module is used for determining a total power target value to be distributed of the target electrolytic tank series-parallel system according to the input power of the external fluctuating power supply; The sequence determining module is used for constructing a corresponding particle coding sequence according to the number of the electrolytic tank units; The position information determining module is used for carrying out iterative optimization processing on the particle coding sequence according to the running physical boundary parameters by utilizing a preset particle swarm optimization model to determine target particle position information, wherein the iterative optimization processing process comprises the steps of dynamically adjusting search step length by adopting a linearly decreasing inertia weight adjustment strategy and carrying out optimization processing by taking a multi-objective function as an evaluation criterion; The start-stop distribution determining module is used for determining the start-stop state combination and the power distribution proportion of each electrolytic cell unit in the target electrolytic cell series-parallel system according to the target particle position information by utilizing a preset power distribution rule; And the power distribution module is used for determining the operation power value of each electrolytic cell unit in the target electrolytic cell series-parallel system according to the start-stop state combination, the power distribution proportion and the total power target value to be distributed.
10. A computer readable storage medium, having stored thereon computer instructions which, when executed by a processor, implement the steps of the method of any of claims 1 to 8.

Description

ALK-PEM series-parallel system control method and device based on wind and light fluctuation Technical Field The specification belongs to the technical field of renewable energy hydrogen production, and particularly relates to an ALK-PEM series-parallel system control method and device based on wind and light fluctuation. Background Along with the large-scale evolution of the hydrogen energy industry, a series-parallel system formed by heterogeneous electrolytic tanks becomes a core path for absorbing new fluctuation energy and taking account of large-scale hydrogen production, however, the existing control strategy lacks a cooperative scheduling mechanism aiming at the dynamic characteristic difference of the heterogeneous electrolytic tanks in the power distribution process, so that the system has the technical defects of limited adjustment range, delayed power response and the like when facing real-time power fluctuation. In view of the above problems, no effective solution has been proposed at present. Disclosure of Invention The specification provides an ALK-PEM series-parallel system control method and device based on wind and light fluctuation, which solve the technical problems of limited adjustment range and delayed power response of a system in the face of real-time power fluctuation caused by lack of dynamic characteristic cooperative scheduling in heterogeneous electrolytic tank series-parallel power distribution in the prior art. The specification provides an ALK-PEM series-parallel system control method based on wind and light fluctuation, which comprises the following steps: Acquiring the input power of an external fluctuation power supply and the operation parameters of a target electrolytic cell series-parallel system, wherein the operation parameters comprise the number of each electrolytic cell unit and corresponding operation physical boundary parameters; Determining a total power target value to be distributed of the target electrolytic tank series-parallel system according to the input power of the external fluctuation power supply; constructing corresponding particle coding sequences according to the number of the electrolytic tank units; Performing iterative optimization processing on the particle coding sequence according to the running physical boundary parameters by using a preset particle swarm optimization model to determine target particle position information, wherein the iterative optimization processing process comprises the steps of dynamically adjusting search step length by adopting a linearly decreasing inertia weight adjustment strategy and performing optimization processing by taking a multi-objective function as an evaluation criterion; Determining the start-stop state combination and the power distribution proportion of each electrolytic cell unit in the target electrolytic cell series-parallel system according to the target particle position information by utilizing a preset power distribution rule; and determining the operation power value of each electrolytic cell unit in the target electrolytic cell series-parallel system according to the start-stop state combination, the power distribution proportion and the total power target value to be distributed. In one embodiment, the performing iterative optimization processing on the particle coding sequence according to the running physical boundary parameter by using a preset particle swarm optimization model to determine target particle position information includes: Determining the initial position of each particle in the particle swarm according to the particle coding sequence and the operation physical boundary parameter; determining the current cost value of each particle according to the current position of each particle and the multi-objective function; according to the current cost value, determining individual target positions of each particle and group target positions of the particle group; Determining the group center position of the particle swarm according to the individual target positions of all the particles; determining a current inertia weight parameter according to the current iteration times, a preset iteration stop threshold value and a linearly decreasing inertia weight adjustment strategy; Determining the updating position of each particle by utilizing the quantum behavior optimizing criterion according to the individual target position, the group center position and the current inertia weight parameter; And repeatedly executing the steps of determining the current cost value to determine the update position until the iteration times reach the preset iteration stop threshold value, and obtaining the target particle position information according to the group target position. In one embodiment, the determining the current cost value of each particle according to the current position of each particle and the multi-objective function includes: Determining the running state and the distribution powe