Power grid primary frequency modulation control model based on large compressed air energy storage power generation

Abstract

The invention discloses a power grid primary frequency modulation control model based on large-scale compressed air energy storage power generation, which is used for carrying out key technical research by adopting a research method combining current situation investigation, theoretical analysis, simulation calculation, database establishment, numerical simulation, test verification, development of process parameters and summarization and induction. And finally, an own compressed air energy storage technology is formed and popularized to practical engineering application. Through the complex heat exchange system, the turbine system, the heat storage system, the compression system and the like which are complex in characteristics and mutually coupled, the influence on the power grid in different operation modes of energy storage and energy release is studied and mastered, through theoretical research and numerical simulation, the response time of the energy storage power station is shortened as much as possible, the fastest load response speed is achieved, and the energy storage and energy release efficiency is improved. And requirements of power grid frequency modulation and peak regulation are satisfied.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy storage frequency modulation control, and particularly to a primary frequency modulation control model for power grids based on large-scale compressed air energy storage power generation. Background Art

[0002] New energy storage is an important technology and basic equipment for building a new power system, an important support for achieving the goals of carbon peak and carbon neutrality, and also an important field for fostering new domestic energy business forms and seizing new international strategic high points. The research on the coordinated control method of large-scale compressed air energy storage power stations is one of the key factors for promoting the development of new energy storage technologies.

[0003] Generally, the analog quantity control of large unit generator sets mainly focuses on the automatic control of the operation of the main engine equipment and its auxiliary equipment. The purpose of the control is to enable the unit to automatically adapt to the changes in working conditions and operate under safe and economic conditions. Its control objects include load, pressure, temperature, flow, etc.

[0004] The coordinated control system is the main body of analog quantity control. When designing the coordinated control system, the main considerations are the stability and disturbance problems in regulation. Its basic idea is to design the regulation control system as a feedback regulation system with feedforward, which takes the disturbance quantity as the coarse adjustment and the regulated quantity as the fine adjustment, mainly coordinating the various systems of the unit generator set, balancing and coordinating the dynamic ratio between the unit energy and the electrical load, jointly adapting to the needs of the external load, and at the same time ensuring the safe and economic stable operation of the unit. With the continuous increase of the capacity of generator sets, in addition to putting forward higher requirements for the quality of the analog quantity control system, the power grid also introduces AGC (Automatic Generation Control) and primary frequency modulation functions. Through the improvement of system functions, the unit can be better stabilized, which is beneficial to the safe operation of the power grid.

[0005] Solve the problem of intelligent control of large-scale compressed air energy storage power stations, adopt a reasonable control strategy, realize the coordinated control between the heat exchanger and the compressor, between multi-stage compressors, between the heat exchanger and the expander, and between multi-stage expanders in a 300M-level compressed air energy storage power station, form a unique operation mode of the compressed air energy storage power station, and improve the operation stability, flexibility and economy of the power station. Summary of the Invention

[0006] Based on the technical problems existing in the background art, the present invention proposes a primary frequency modulation control model for power grids based on large-scale compressed air energy storage power generation.

[0007] A primary frequency modulation control model for power grids based on large-scale compressed air energy storage power generation proposed by the present invention includes the following steps:

[0008] System Initialization and Data Acquisition

[0009] S1: Initialize system parameters; set the target frequency range for primary frequency regulation and determine the operating constraints of the system;

[0010] S2: Collect real-time data;

[0011] Obtain real-time frequency fluctuation data from the power grid; obtain key operating parameters from the main control system of the CAES power station, including: gas storage tank pressure and temperature, compressor / expander power, heat exchanger thermal power, outlet gas flow rate and temperature;

[0012] S3: Preprocess data;

[0013] Denoise and handle outliers of the collected data, and convert it into a standardized value to meet the input requirements of the control model.

[0014] Furthermore, establish a primary frequency regulation control model, including:

[0015] S1: Frequency deviation detection module

[0016] Real-time monitor the power grid frequency deviation Δf: Δf = factual - frated; determine the magnitude and rate of change of the frequency deviation, and evaluate the frequency regulation demand;

[0017] S2: Dynamic response control model

[0018] According to the frequency deviation Δf, calculate the required power adjustment amount ΔP: ΔP = K·Δf; where K is the regulation coefficient of the primary frequency regulation system;

[0019] S3: Compressed air energy storage system model

[0020] Establish a dynamic power distribution model: adjust the expander power to supplement the power missing from the power grid; adjust the compressor power to reduce the load or maintain energy storage balance; introduce the gas storage tank state constraint: Pexpansion + Pcompression ≤ Ptotal energy storage; ensure that the gas storage tank pressure and capacity are within a safe range;

[0021] S4: Optimize the frequency regulation response time

[0022] Establish a fast response control module to reduce the equipment start-stop time and power adjustment lag; use model predictive control to predict the frequency change trend and adjust the power output.

[0023] Furthermore, the specific steps of the control process include:

[0024] S1: Frequency deviation analysis

[0025] According to the magnitude and rate of change of the real-time frequency deviation Δf, trigger the frequency regulation strategy in stages: small deviation: complete fine-tuning by adjusting the expander output; large deviation: start the compressor or other auxiliary systems to participate in frequency regulation;

[0026] S2: Power Allocation and Coordination Control

[0027] Call the primary frequency regulation power allocation model to calculate the power adjustment values of the expander and compressor: Expander power adjustment: P_expansion = P_reference + ΔP; Compressor power adjustment (triggered when the gas storage pressure exceeds the upper limit): P_compression = P_reference - ΔP;

[0028] S3: Dynamic Adjustment of Heat Exchanger

[0029] Adjust the heat balance of the heat exchanger according to the changes in the powers of the expander and compressor to maintain the stable temperature of the outlet gas;

[0030] S4: Real-time Feedback and Control Optimization

[0031] Use feedback control to adjust the real-time power output of the expander and compressor, reducing the system response lag; Combine real-time data to update the control parameters and optimize the frequency modulation effect.

[0032] Furthermore, fault handling and safety protection include:

[0033] S1: Abnormal State Detection

[0034] Detect abnormal conditions such as compressor and expander overload, overpressure or overheating of the gas storage tank;

[0035] S2: Protection Measures

[0036] In case of faults or overlimits, quickly cut off the relevant equipment and switch to the standby system.

[0037] Furthermore, model verification and optimization include:

[0038] S1: Simulation Test

[0039] Simulate the power grid frequency fluctuation scenario on the digital simulation platform to test the dynamic response performance of the frequency modulation control model;

[0040] S2: Performance Optimization

[0041] Optimize the model parameters (such as the regulation coefficient K, feedback gain, etc.) according to the test results.

[0042] Furthermore, application and actual operation include:

[0043] S1: Real-time Deployment

[0044] Integrate the frequency modulation control model into the main control system of the CAES power station for real-time operation;

[0045] S1: System Monitoring and Maintenance

[0046] Use the online monitoring system to track the operation of the frequency modulation model and maintain and update the model in a timely manner.

[0047] The beneficial effects of the present invention are as follows:

[0048] The 350MW compressed air energy storage power generation unit includes a complex heat exchange system, a turbine system, a heat storage system, a compression system, etc. Its characteristics are complex and mutually coupled. By studying and mastering the impact on the power grid under different operating modes of energy storage and energy release, through theoretical research and numerical simulation, the response time of the energy storage power station is shortened as much as possible to achieve the fastest load response speed and meet the requirements of power grid frequency modulation and peak shaving. Description of the Drawings

[0049] Figure 1 It is a flowchart of a primary frequency modulation control model for the power grid based on large-scale compressed air energy storage power generation proposed by the present invention. Detailed Implementation Modes

[0050] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments.

[0051] A primary frequency modulation control model for the power grid based on large-scale compressed air energy storage power generation includes the following steps:

[0052] System initialization and data acquisition

[0053] S1: Initialize system parameters; set the target frequency range for primary frequency modulation and determine the operating constraint conditions of the system;

[0054] S2: Real-time data acquisition;

[0055] Obtain real-time frequency fluctuation data from the power grid; obtain key operating parameters from the main control system of the CAES power station, including: the pressure and temperature of the gas storage tank, the power of the compressor / expander, the heat power of the heat exchanger, the outlet gas flow rate and temperature;

[0056] S3: Data preprocessing;

[0057] Denoise and process the collected data and convert it into a standardized value to meet the input requirements of the control model.

[0058] During the research and preparation stage, query and collect similar research results at home and abroad, and combine the previous design experience of the compressed air energy storage power station of the project team to complete the research on the performance parameters of the main equipment in the compressed air system and form a summary analysis of the research results.

[0059] Furthermore, establish a primary frequency modulation control model, including:

[0060] S1: Frequency deviation detection module

[0061] Real-time monitor the grid frequency deviation Δf: Δf = f_actual - f_rated; Determine the magnitude and rate of change of the frequency deviation, and evaluate the frequency regulation demand;

[0062] S2: Dynamic response control model

[0063] According to the frequency deviation Δf, calculate the required power adjustment amount ΔP: ΔP = K·Δf; where K is the regulation coefficient of the primary frequency regulation system;

[0064] S3: Compressed air energy storage system model

[0065] Establish a dynamic power distribution model: Adjust the power of the expander to supplement the power missing from the grid; Adjust the power of the compressor to reduce the load or maintain energy storage balance; Introduce the state constraint of the gas storage tank: P_expansion + P_compression ≤ P_total_energy_storage; Ensure that the pressure and capacity of the gas storage tank are within the safe range;

[0066] S4: Optimize the frequency regulation response time

[0067] Establish a fast response control module to reduce the start-stop time of equipment and the power adjustment lag; Use model predictive control to predict the frequency change trend and adjust the power output.

[0068] Furthermore, the specific steps of the control process include:

[0069] S1: Frequency deviation analysis

[0070] According to the magnitude and rate of change of the real-time frequency deviation Δf, trigger the frequency regulation strategy in stages: Small deviation: Complete the fine adjustment by adjusting the output of the expander; Large deviation: Start the compressor or other auxiliary systems to participate in frequency regulation;

[0071] S2: Power distribution and coordinated control

[0072] Call the primary frequency regulation power distribution model to calculate the power adjustment values of the expander and the compressor: Expander power adjustment: P_expansion = P_reference + ΔP; Compressor power adjustment (triggered when the gas storage pressure exceeds the upper limit): P_compression = P_reference - ΔP;

[0073] S3: Dynamic adjustment of the heat exchanger

[0074] According to the changes in the power of the expander and the compressor, adjust the heat balance of the heat exchanger to maintain the stable temperature of the outlet gas;

[0075] S4: Real-time feedback and control optimization

[0076] Use feedback control to adjust the real-time power output of the expander and the compressor to reduce the system response lag; Combine real-time data to update the control parameters and optimize the frequency regulation effect.

[0077] Process system research, based on a non-supplementary combustion compressed air energy storage power generation system, analyzes the working characteristics of core equipment such as compressors, heat exchangers, thermal energy storage tanks, gas storage reservoirs, and expanders, as well as the thermodynamic processes of the entire system and the coupling relationships between them, according to the compression link, heat exchange link, thermal energy storage link, gas storage link, and expansion link, using a research method that combines theoretical analysis, numerical simulation, and experimental research. System parameter optimization is carried out according to specific boundary conditions, such as boundary parameters of gas storage reservoir volume, maximum and minimum allowable pressures, generator set capacity, grid low valley and peak operation durations, etc., and the principle design of the system is completed.

[0078] Furthermore, fault handling and safety protection include:

[0079] S1: Abnormal state detection

[0080] Detect abnormal situations such as compressor and expander overload, overpressure or overheating of the gas storage tank;

[0081] S2: Protection measures

[0082] In case of faults or overlimits, quickly cut off relevant equipment and switch to the standby system.

[0083] Furthermore, model verification and optimization include:

[0084] S1: Simulation test

[0085] Simulate the grid frequency fluctuation scenario on the digital simulation platform and test the dynamic response performance of the frequency modulation control model;

[0086] S2: Performance optimization

[0087] Optimize model parameters (such as regulation coefficient K, feedback gain, etc.) according to the test results.

[0088] Model development, based on the theoretical analysis of thermodynamics and heat transfer, studies and establishes the calculation models of the thermal performance of key equipment, including the calculation models of compressors, heat exchangers, thermal energy storage tanks, gas storage reservoirs, expanders, etc., completes the development of the simulation system, and conducts in-depth research on the operation laws of the system under various working conditions.

[0089] Furthermore, application and actual operation include:

[0090] S1: Real-time deployment

[0091] Integrate the frequency modulation control model into the main control system of the CAES power station and run it in real time;

[0092] S1: System monitoring and maintenance

[0093] Use the online monitoring system to track the operation of the frequency modulation model and maintain and update the model in a timely manner.

[0094] During the project implementation stage, relying on the demonstration project, integrating research results, providing the system design of the coordinated and AGC load control system for the non-supplementary combustion compressed air energy storage power station, completing relevant design work, researching effective ways to improve system efficiency, reduce project cost, and achieve grid connection at parity.

[0095] The above are only the preferred specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, making equivalent substitutions or changes should be covered within the protection scope of the present invention.

Claims

1. A primary frequency regulation control model for power grids based on large-scale compressed air energy storage power generation, characterized in that, It includes the following steps: System initialization and data acquisition S1: Initialize system parameters; Set the target frequency range for primary frequency regulation and determine the operating constraints of the system; S2: Real-time data acquisition; Obtain real-time frequency fluctuation data from the power grid; Obtain key operating parameters from the CAES power station master control system, including: gas storage tank pressure and temperature, compressor / expander power, heat exchanger thermal power, outlet gas flow rate and temperature; S3: Data preprocessing; Denoise and handle outliers of the acquired data, and convert them into standardized values to meet the input requirements of the control model.

2. The primary frequency regulation control model for a power grid based on large-scale compressed air energy storage power generation according to claim 1, establishing a primary frequency regulation control model, characterized in that, It includes: S1: Frequency deviation detection module Real-time monitor the grid frequency deviation Δf of a primary frequency regulation control model based on large-scale compressed air energy storage power generation: Δf = factual - frated; Determine the magnitude and change rate of the frequency deviation, and evaluate the frequency regulation demand; S2: Dynamic response control model According to the frequency deviation Δf of a primary frequency regulation control model based on large-scale compressed air energy storage power generation, calculate the required power adjustment amount ΔP of a primary frequency regulation control model based on large-scale compressed air energy storage power generation: ΔP = K·Δf; Where K of a primary frequency regulation control model based on large-scale compressed air energy storage power generation is the regulation coefficient of the primary frequency regulation system; S3: Compressed air energy storage system model Establish a dynamic power distribution model: adjust the expander power to supplement the power missing from the grid; Adjust the compressor power to reduce the load or maintain energy storage balance; Introduce the gas storage tank state constraint: Pexpansion + Pcompression ≤ Ptotal energy storage of a primary frequency regulation control model based on large-scale compressed air energy storage power generation; Ensure that the gas storage tank pressure and capacity are within the safe range; S4: Optimize the frequency regulation response time Establish a fast response control module to reduce the equipment start-stop time and power adjustment lag; Use model predictive control to predict the frequency change trend and adjust the power output.

3. The specific steps of the control process for a primary frequency regulation control model of a power grid based on large-scale compressed air energy storage power generation according to claim 2, characterized in that, It includes: S1: Frequency deviation analysis According to the magnitude and change rate of the real-time frequency deviation Δf of a primary frequency regulation control model based on large-scale compressed air energy storage power generation, hierarchically trigger the frequency regulation strategy: Small deviation: Complete fine-tuning by adjusting the expander output; Large deviation: Start the compressor or other auxiliary systems to participate in frequency regulation; S2: Power distribution and coordinated control Call the primary frequency regulation power distribution model to calculate the power adjustment values of the expander and compressor: Expander power adjustment: Pexpansion of a primary frequency regulation control model based on large-scale compressed air energy storage power generation = Pbenchmark + ΔP; Compressor power adjustment (triggered when the gas storage pressure exceeds the upper limit): Pcompression of a primary frequency regulation control model based on large-scale compressed air energy storage power generation = Pbenchmark - ΔP; S3: Heat exchanger dynamic adjustment According to the changes in the expander and compressor powers, adjust the heat balance of the heat exchanger to maintain the stable temperature of the outlet gas; 4. A primary frequency regulation control model for power grids based on large-scale compressed air energy storage power generation, fault handling and safety protection, characterized in that, S4: Real-time feedback and control optimization Use feedback control to adjust the real-time power outputs of the expander and compressor to reduce the system response lag; Combine real-time data to update the control parameters and optimize the frequency regulation effect. It includes: S1: Abnormal state detection Detect abnormal conditions such as compressor and expander overload, gas storage tank overpressure or overheating; S2: Protection measures In case of faults or overlimits, quickly cut off the relevant equipment and switch to the standby system.

5. A primary frequency regulation control model for power grids based on large-scale compressed air energy storage power generation, model verification and optimization, characterized in that Including: S1: Simulation test Simulate the power grid frequency fluctuation scenario on the digital simulation platform to test the dynamic response performance of the frequency regulation control model; S2: Performance optimization Optimize the model parameters (such as the regulation coefficient K, feedback gain, etc. of a primary frequency regulation control model based on large-scale compressed air energy storage power generation) according to the test results.

6. A primary frequency regulation control model for power grids based on large-scale compressed air energy storage power generation, when applied to actual operation, is characterized in that Including: S1: Real-time deployment Integrate the frequency regulation control model into the main control system of the CAES power station and run it in real time; S1: System monitoring and maintenance Use the online monitoring system to track the operation of the frequency regulation model and maintain and update the model.

Images