Green electricity hydrogen production coupling coal chemical industry integrated energy management system

Abstract

The invention discloses a green electricity hydrogen production coupling coal chemical industry integrated energy management system, which is used for integrated management of a wind power generation subsystem, a photovoltaic power generation subsystem, an energy storage subsystem, a hydrogen production subsystem and a coal chemical industry subsystem, and comprises a day-ahead data prediction unit used for obtaining predicted values of the subsystems in a future preset time period; the intra-day data real-time monitoring unit is used for collecting the actual value of each subsystem at the current time point; the day-ahead scheduling unit is used for optimizing and generating a day-ahead scheduling instruction according to the predicted value by taking the minimum full-cycle hydrogen production cost as a day-ahead objective function; the intra-day rolling optimization unit is used for generating an intra-day scheduling instruction by taking minimization of real-time wind and light abandoning power as an intra-day objective function and combining energy storage subsystem capacity out-of-limit early warning and hydrogen demand quantity deviation feedback according to the actual value; and the control execution unit is used for converting the day-ahead scheduling instruction and the intra-day scheduling instruction into equipment control signals. Through the system, the wind and light abandoning rate is effectively reduced, and the hydrogen production cost is reduced.

Description

Technical Field

[0001] The present invention relates to the field of new energy and chemical technology, and more particularly to an integrated energy management system for green electricity hydrogen production coupled with coal chemical industry. Background Art

[0002] With the rapid development of new energy technologies, the proportion of wind and photovoltaic power generation in the energy mix has gradually increased. However, due to the intermittent and volatile nature of wind and solar resources, their large-scale grid integration poses challenges to grid stability. Furthermore, the coal chemical industry, a traditional industry with high energy consumption and carbon emissions, faces an urgent need for energy conservation, emission reduction, and transformation and upgrading.

[0003] Existing systems combine renewable energy hydrogen production with coal chemical processing, but these systems suffer from extensive energy management, insufficient coordination among multiple energy sources, high wind and solar curtailment rates, low hydrogen production efficiency, and high costs. For example, some systems fail to fully consider the forecast accuracy of wind and solar power generation, the response speed of energy storage systems, and the operating characteristics of hydrogen production equipment. This results in inadequate energy scheduling, impacting the overall performance and profitability of the system.

[0004] Therefore, achieving coordinated and optimized scheduling of wind and solar power generation, energy storage, hydrogen production and coal chemical systems, improving the capacity to absorb new energy, reducing the rate of wind and solar power abandonment, improving hydrogen production efficiency and reducing hydrogen production costs, and promoting energy structure transformation and green development of the coal chemical industry are issues that technical personnel in this field urgently need to solve. Summary of the Invention

[0005] In view of the above problems, the present invention provides an integrated energy management system for green electricity hydrogen production coupled with coal chemical industry to at least solve some of the technical problems mentioned in the above background technology.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] The present invention provides an integrated energy management system for green electricity hydrogen production coupled with coal chemical industry, which realizes the integrated energy management of wind power generation subsystem, photovoltaic power generation subsystem, energy storage subsystem, hydrogen production subsystem and coal chemical industry subsystem, including:

[0008] The day-ahead data prediction unit is used to obtain the wind power generation power forecast value, photovoltaic power generation power forecast value, green power consumption forecast value of the hydrogen production subsystem, hydrogen production efficiency forecast value and hydrogen storage tank inventory forecast value within a preset time period in the future, as well as the hydrogen demand forecast value of the coal chemical subsystem;

[0009] The intraday data real-time monitoring unit is used to collect the energy storage subsystem capacity, actual hydrogen tank inventory, actual wind power generation power, actual photovoltaic power generation power, actual hydrogen production efficiency, and actual hydrogen demand of the coal chemical subsystem at the current time point;

[0010] a day-ahead scheduling unit, configured to optimize and generate a day-ahead scheduling instruction based on the data acquired by the day-ahead data prediction unit and taking minimization of the full-cycle hydrogen production cost as the day-ahead objective function;

[0011] An intraday rolling optimization unit is configured to generate an intraday dispatch instruction based on the data obtained by the intraday data real-time monitoring unit, with minimization of real-time wind and solar power curtailment as the intraday objective function, combined with the energy storage subsystem capacity over-limit warning and hydrogen demand deviation feedback;

[0012] The control execution unit is used to execute the day-ahead scheduling instruction and the intra-day scheduling instruction.

[0013] Furthermore, the day-ahead dispatching instructions include the day-ahead dispatching instructions for the electrolyzer, the day-ahead dispatching instructions for external power purchases, and the day-ahead dispatching instructions for the energy storage subsystem.

[0014] Furthermore, the intraday scheduling instructions include intraday scheduling instructions for the electrolyzer and intraday scheduling instructions for the energy storage subsystem.

[0015] Furthermore, the objective function before the day is expressed as:

[0016]

[0017] Where T represents the number of preset time periods in the future preset time period; C grid (t) represents the external grid electricity price in the tth period; P grid (t) represents the external power purchase in the tth period; λ curt Indicates the penalty coefficient for curtailing wind and solar power; represents the predicted value of wind power generation in the tth period; represents the predicted value of photovoltaic power generation in the tth period; represents the predicted value of green power consumption in the tth period; H2 Indicates the penalty coefficient for exceeding the limit of hydrogen storage tank inventory; represents the predicted value of hydrogen storage tank inventory in period t; It represents the safety value of hydrogen storage tank inventory in the tth period.

[0018] Furthermore, the constraints corresponding to the day-ahead objective function include:

[0019] (1) Dynamic balance constraints of hydrogen storage tank inventory:

[0020]

[0021] in, It represents the predicted value of hydrogen production efficiency of electrolyzer; represents the predicted value of hydrogen demand of the coal chemical subsystem in the tth period;

[0022] (2) Hydrogen storage tank inventory constraints:

[0023]

[0024] in, Indicates the lower limit of hydrogen storage tank inventory; Indicates the upper limit of hydrogen storage tank inventory;

[0025] (3) Electrolyzer operation constraints in the hydrogen production subsystem:

[0026]

[0027] Among them, P H2 (t) represents the operating power of the electrolyzer at the tth period; Indicates the minimum operating power of the electrolytic cell; Indicates the maximum operating power of the electrolytic cell;

[0028] (4) External power purchase power constraints:

[0029]

[0030] in, Indicates the maximum external power purchase power;

[0031] (5) Hydrogen demand constraints of coal chemical subsystem:

[0032]

[0033] (6) Energy storage subsystem capacity constraints:

[0034]

[0035] SOC min ≤SOC(t)≤SOC max

[0036]

[0037] P ch (t)·P dis (t) = 0

[0038] Where SOC(t) represents the remaining energy of the energy storage subsystem in time period t; ηch represents the charging efficiency of the energy storage subsystem; η dis represents the discharge efficiency of the energy storage subsystem; P ch (t) represents the charging power of the energy storage subsystem; P dis (t) represents the discharge power of the energy storage subsystem; Indicates the maximum charge and discharge power of the energy storage subsystem; SOC min Indicates the lower limit of energy storage subsystem capacity; SOC max Indicates the upper limit of the energy storage subsystem capacity.

[0039] Furthermore, the intraday objective function is expressed as:

[0040]

[0041] ΔSOC(t)=max(SOC(t)-SOC max ,SOC min -SOC(t),0)

[0042] Among them, λ curt Indicates the penalty coefficient for curtailing wind and solar power; Indicates the actual value of wind power generation in period t; Indicates the actual value of photovoltaic power generation during period t; represents the predicted value of green power consumption in the tth period; SOC represents the penalty coefficient for exceeding the capacity limit of the energy storage subsystem; SOC(t) represents the remaining energy of the energy storage subsystem in time period t; ΔSOC(t) represents the deviation between the capacity of the energy storage subsystem and the safety range represents the hydrogen demand deviation penalty coefficient; represents the actual value of hydrogen demand of the coal chemical subsystem in the tth period; Indicates the actual value of hydrogen production efficiency of the electrolyzer; P H2 (t) represents the operating power of the electrolyzer at the tth period; SOC min Indicates the lower limit of energy storage subsystem capacity; SOC max Indicates the upper limit of the energy storage subsystem capacity.

[0043] Furthermore, the constraints corresponding to the intraday objective function include:

[0044] (1) Power balance constraints:

[0045]

[0046] Among them, P grad (t) represents the external power purchase; P curt (t) represents the abandoned wind and solar power; Indicates other electrical power except the electrolytic cell operating power;

[0047] (2) Hydrogen storage tank inventory constraints:

[0048]

[0049] in, Indicates the actual value of the hydrogen storage tank inventory during period t;

[0050] (3) Energy storage subsystem constraints

[0051]

[0052] SOC min ≤SOC(t)≤SOC max

[0053]

[0054] P ch (t)·P dis (t) = 0

[0055] Among them, η ch represents the charging efficiency of the energy storage subsystem; η dis represents the discharge efficiency of the energy storage subsystem; P ch (t) represents the charging power of the energy storage subsystem; P dis (t) represents the discharge power of the energy storage subsystem; Indicates the maximum charge and discharge power of the energy storage subsystem.

[0056] Furthermore, in the intraday rolling optimization unit, rolling optimization is performed every preset time period.

[0057] Furthermore, the control execution unit includes an instruction conversion module and an execution module;

[0058] The instruction conversion module is used to convert the day-ahead scheduling instruction and the intraday scheduling instruction into device control signals;

[0059] The execution module is used to regulate the equipment in the wind power generation subsystem, photovoltaic power generation subsystem, energy storage subsystem, hydrogen production subsystem and coal chemical subsystem according to the equipment control signal.

[0060] Furthermore, the control execution unit further includes a multi-instruction coordination module;

[0061] The multi-command coordination module is configured to select a preset mode for execution based on a deviation level between the real-time data obtained by the intraday data real-time monitoring unit and the predicted value obtained by the day-ahead data prediction unit;

[0062] The preset modes include:

[0063] Economic priority mode: Prioritizes the execution of the day-ahead dispatch instructions, allowing the purchased electricity to deviate from the preset deviation range;

[0064] Consumption priority mode: When the current green power output exceeds the preset value, the electrolyzer operating power is prioritized to be increased to the current green power output that can be consumed. The current green power output is the sum of the actual wind power generation power and the actual photovoltaic power generation power.

[0065] Emergency supply mode: When the inventory level of the hydrogen storage tank is lower than the safety threshold, switch to external hydrogen source for replenishment.

[0066] It can be seen from the above technical solutions that, compared with the prior art, the present invention provides an integrated energy management system for green electricity hydrogen production coupled with coal chemical industry, which has the following beneficial effects:

[0067] By integrating wind power, photovoltaics, energy storage, hydrogen production and coal chemical subsystems, the present invention can achieve efficient consumption of green electricity and balance the supply and demand of hydrogen energy, thereby reducing the rate of wind and solar power curtailment.

[0068] The present invention takes into account both the minimization of the full-cycle hydrogen production cost and the stability of real-time operation through the coordinated work of the day-ahead scheduling unit and the intra-day rolling optimization unit.

[0069] The present invention improves the matching degree between hydrogen energy production and coal chemical demand and reduces dependence on external hydrogen purchases through the cooperation of a day-ahead data prediction unit and an intraday data real-time monitoring unit.

[0070] The present invention adds a multi-instruction coordination module in the control execution unit, which can flexibly select the execution mode according to the deviation level between real-time data and predicted data, thereby ensuring the economy and safety of the system.

[0071] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0073] Figure 1 Schematic diagram of the framework of the green electricity hydrogen production coupled with coal chemical integrated energy management system provided by an embodiment of the present invention.

[0074] Figure 2 This is a flow chart of an integrated energy management system for green electricity hydrogen production coupled with coal chemical industry provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0075] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0076] Example 1:

[0077] The first embodiment of the present invention discloses an integrated energy management system for green electricity hydrogen production coupled with coal chemical industry, see Figure 1 and Figure 2 As shown, integrated energy management of wind power generation subsystem, photovoltaic power generation subsystem, energy storage subsystem, hydrogen production subsystem and coal chemical subsystem is achieved, including:

[0078] The day-ahead data prediction unit is used to obtain the wind power generation power forecast value, photovoltaic power generation power forecast value, green power consumption forecast value of the hydrogen production subsystem, hydrogen production efficiency forecast value and hydrogen storage tank inventory forecast value within a preset time period in the future, as well as the hydrogen demand forecast value of the coal chemical subsystem;

[0079] The intraday data real-time monitoring unit is used to collect the energy storage subsystem capacity, actual hydrogen tank inventory, actual wind power generation power, actual photovoltaic power generation power, actual hydrogen production efficiency, and actual hydrogen demand of the coal chemical subsystem at the current time point;

[0080] The day-ahead scheduling unit is used to optimize and generate day-ahead scheduling instructions based on the data obtained by the day-ahead data prediction unit, with minimizing the full-cycle hydrogen production cost as the day-ahead objective function;

[0081] The intraday rolling optimization unit is used to generate intraday dispatch instructions based on the data obtained by the intraday real-time data monitoring unit, with minimizing the real-time wind and solar power curtailment as the intraday objective function, combined with the energy storage subsystem capacity over-limit warning and hydrogen demand deviation feedback;

[0082] The control execution unit is used to execute the day-ahead scheduling instruction and the intra-day scheduling instruction.

[0083] In the embodiment of the present invention, by integrating wind power, photovoltaic, energy storage, hydrogen production and coal chemical subsystems, efficient green electricity consumption and hydrogen supply and demand balance are achieved, and the wind and solar power curtailment rate is reduced; by combining day-ahead scheduling with intraday rolling optimization, the minimization of hydrogen production costs and real-time operation stability are taken into account; by integrating predicted data with real-time data, the matching degree between hydrogen production and coal chemical demand is improved, and the dependence on external hydrogen purchases is reduced.

[0084] In the above day-ahead scheduling unit, minimizing the full-cycle hydrogen production cost is the day-ahead objective function, which is expressed as:

[0085]

[0086] Where T represents the number of preset time periods in the future preset time period; C grid (t) represents the external grid electricity price in the tth period; P grid (t) represents the external power purchase in the tth period; λ curt Indicates the penalty coefficient for curtailing wind and solar power; represents the predicted value of wind power generation in the tth period; represents the predicted value of photovoltaic power generation in the tth period; represents the predicted value of green power consumption in the tth period; H2 Indicates the penalty coefficient for exceeding the limit of hydrogen storage tank inventory; represents the predicted value of hydrogen storage tank inventory in period t; It represents the safety value of hydrogen storage tank inventory in the tth period.

[0087] The constraints corresponding to the above day-ahead objective function include:

[0088] (1) Dynamic balance constraints of hydrogen storage tank inventory:

[0089]

[0090] in, It represents the predicted value of hydrogen production efficiency of electrolyzer; represents the predicted value of hydrogen demand of the coal chemical subsystem in the tth period;

[0091] (2) Hydrogen storage tank inventory constraints:

[0092]

[0093] in, Indicates the lower limit of hydrogen storage tank inventory; Indicates the upper limit of hydrogen storage tank inventory;

[0094] (3) Electrolyzer operation constraints in the hydrogen production subsystem:

[0095]

[0096] Among them, P H2 (t) represents the operating power of the electrolyzer at the tth period; Indicates the minimum operating power of the electrolytic cell; Indicates the maximum operating power of the electrolytic cell;

[0097] (4) External power purchase power constraints:

[0098]

[0099] in, Indicates the maximum external power purchase power;

[0100] (5) Hydrogen demand constraints of coal chemical subsystem:

[0101]

[0102] (6) Energy storage subsystem capacity constraints:

[0103]

[0104] SOC min ≤SOC(t)≤SOC max

[0105]

[0106] P ch (t)·P dis (t) = 0

[0107] Where SOC(t) represents the remaining energy of the energy storage subsystem in time period t; η ch represents the charging efficiency of the energy storage subsystem; η dis represents the discharge efficiency of the energy storage subsystem; P ch (t) represents the charging power of the energy storage subsystem; P dis (t) represents the discharge power of the energy storage subsystem; Indicates the maximum charge and discharge power of the energy storage subsystem; SOC min Indicates the lower limit of energy storage subsystem capacity; SOC max Indicates the upper limit of the energy storage subsystem capacity.

[0108] Afterwards, the day-ahead dispatch instructions generated based on the above-mentioned day-ahead objective function and related constraints include the day-ahead dispatch instructions for the electrolyzer, the day-ahead dispatch instructions for external power purchases, and the day-ahead dispatch instructions for the energy storage subsystem. Among them, the day-ahead dispatch instructions for the electrolyzer can effectively avoid energy waste; the day-ahead dispatch instructions for external power purchases can optimize the selection of electricity price periods and reduce the overall cost of hydrogen production; the day-ahead dispatch instructions for the energy storage subsystem can plan the energy storage charging and discharging strategy in advance to provide buffer capacity for real-time fluctuations in subsequent days.

[0109] In the above-mentioned intraday rolling optimization unit, minimizing the real-time wind and solar power curtailment is taken as the intraday objective function, which is expressed as:

[0110]

[0111] ΔSOC(t)=max(SOC(t)-SOC max ,SOC min -SOC(t),0)

[0112] Among them, λ curt Indicates the penalty coefficient for curtailing wind and solar power; Indicates the actual value of wind power generation in period t; Indicates the actual value of photovoltaic power generation during period t; represents the predicted value of green power consumption in the tth period; SOC represents the penalty coefficient for exceeding the capacity limit of the energy storage subsystem; SOC(t) represents the remaining energy of the energy storage subsystem in time period t; ΔSOC(t) represents the deviation between the capacity of the energy storage subsystem and the safety range represents the hydrogen demand deviation penalty coefficient; represents the actual value of hydrogen demand of the coal chemical subsystem in the tth period; Indicates the actual value of hydrogen production efficiency of the electrolyzer; P H2 (t) represents the operating power of the electrolyzer at the tth period; SOC min Indicates the lower limit of energy storage subsystem capacity; SOC max Indicates the upper limit of the energy storage subsystem capacity.

[0113] The constraints corresponding to the above intraday objective function include:

[0114] (1) Power balance constraints:

[0115]

[0116] Among them, P grad (t) represents the external power purchase; P curt (t) represents the abandoned wind and solar power; Indicates other electrical power except the electrolytic cell operating power;

[0117] (2) Hydrogen storage tank inventory constraints:

[0118]

[0119] in, Indicates the actual value of the hydrogen storage tank inventory during period t;

[0120] (3) Energy storage subsystem constraints

[0121]

[0122] SOC min ≤SOC(t)≤SOC max

[0123]

[0124] P ch (t)·Pdis (t)=0.

[0125] Among them, η ch represents the charging efficiency of the energy storage subsystem; η dis represents the discharge efficiency of the energy storage subsystem; P ch (t) represents the charging power of the energy storage subsystem; P dis (t) represents the discharge power of the energy storage subsystem; Indicates the maximum charge and discharge power of the energy storage subsystem.

[0126] Afterwards, intraday dispatch instructions are generated based on the above-mentioned intraday objective function and related constraints, including intraday dispatch instructions for the electrolyzer and intraday dispatch instructions for the energy storage subsystem. Among them, the intraday dispatch instructions for the electrolyzer can quickly adjust the electrolyzer power according to the fluctuations in wind and solar power output, thereby improving the flexibility of green electricity consumption; the intraday dispatch instructions for the energy storage subsystem can effectively smooth out power fluctuations and ensure grid stability.

[0127] Example 2:

[0128] In the second embodiment of the present invention, based on the above-mentioned first embodiment, in the intraday rolling optimization unit, rolling optimization is set to be performed every preset time period, for example, optimization is performed every 15 minutes; this short-cycle optimization can quickly respond to sudden changes in wind and solar power output and reduce cumulative errors; and the time-divided rolling can effectively reduce the optimization complexity and adapt to real-time control requirements.

[0129] Example 3:

[0130] Embodiment 3 of the present invention, based on the above-mentioned embodiment 1 or embodiment 2, the above-mentioned control execution unit instruction conversion module and execution module; wherein the instruction conversion module is used to convert the said day-ahead scheduling instructions and intraday scheduling instructions into equipment control signals; the execution module is used to regulate the equipment in the wind power generation subsystem, photovoltaic power generation subsystem, energy storage subsystem, hydrogen production subsystem and coal chemical subsystem according to the equipment control signal.

[0131] To more intuitively understand the operating mechanism of the integrated energy management system for green electricity-to-hydrogen production coupled with coal chemical industry provided by the embodiments of the present invention, we will now apply it to several specific scenarios and explain in detail how the system generates scheduling instructions based on forecast and real-time monitoring data in these scenarios, and how these instructions are converted into specific equipment control signals and affect the operation of each subsystem. Specifically:

[0132] Scenario 1: Abundant wind and solar resources + peak demand for coal-to-chemical hydrogen

[0133] (1) Current forecast data: Wind power generation capacity is expected to be 300MW, photovoltaic power capacity to be 200MW, and coal chemical hydrogen demand to be 50 tons in the next 24 hours.

[0134] (2) The dispatching instruction the day before: The hydrogen production system operates at full load (400MW), and the energy storage system discharges 50MW to cooperate with the power supply.

[0135] (3) Intraday real-time data: Actual wind power is 320MW (+20MW), photovoltaic power is 210MW (+10MW), and the inventory of hydrogen storage tanks is lower than expected.

[0136] (4) The instruction conversion module generates control signals:

[0137] Wind power converter: lift the power limit instruction, allowing over-generation of 20MW;

[0138] Photovoltaic inverter: adjust the MPPT tracking point to the maximum power output;

[0139] Electrolyzer: Increase current density to 1.5A / cm 2 (3% efficiency improvement);

[0140] Energy storage PCS: switches to charging mode, absorbing excess 30MW of power;

[0141] Coal chemical DCS: adjust the opening of the hydrogen inlet valve to 85%;

[0142] (5) Execute module operations:

[0143] The wind turbine pitch angle is adjusted to -2° to capture additional wind energy;

[0144] The photovoltaic array cleaning robot was activated to improve module efficiency;

[0145] The cooling system flow rate of the PEM electrolyzer is increased by 15% to maintain high temperature conditions;

[0146] Lithium battery energy storage SOC increased from 60% to 75%;

[0147] The pressure of the coal chemical synthesis reactor is increased to 8MPa to accelerate the reaction.

[0148] Scenario 2: Nighttime Wind Power Drop + Energy Storage Capacity Warning

[0149] (1) Day-ahead forecast data: Nighttime wind power forecast is 200MW, and energy storage is scheduled to discharge 100MW.

[0150] Real-time monitoring data: actual wind power dropped sharply to 80MW, and energy storage SOC reached the critical value of 15%.

[0151] (2) Intraday optimization instructions: Start the backup power supply of coal-fired power plants, limit the power consumption of non-critical equipment, and reduce the load of hydrogen production systems.

[0152] (3) The instruction conversion module generates signals:

[0153] Energy storage BMS: forced to switch to standby mode;

[0154] Coal-fired power unit DCS: Add 20MW output command;

[0155] Alkaline electrolyzer: current drops to 60% of rated value;

[0156] Air separation unit: Reduce oxygen production by 30%;

[0157] Lighting system: Reduce brightness in non-production areas by 50%;

[0158] (4) Execute module operations:

[0159] Energy storage PCS blocking bidirectional converter;

[0160] The coal feed rate of coal-fired power units increased by 8t / h;

[0161] The electrolyzer rectifier triggers the crowbar protection circuit;

[0162] The frequency converter of the air separation unit compressor is reduced to 35Hz;

[0163] The intelligent lighting system activates the human body sensing power saving mode.

[0164] Scenario 3: Midday PV Fluctuation + Sudden Increase in Hydrogen Demand

[0165] (1) Real-time monitoring data: PV power fluctuated from 150MW to 90MW and then recovered to 130MW within 10 minutes, and the urgent demand for coal chemical industry increased by 15 tons.

[0166] (2) Intraday optimization instructions: start flywheel energy storage instantaneous compensation, adjust SOEC electrolysis mode, and call the hydrogen storage tank spare inventory.

[0167] (3) The instruction conversion module generates signals:

[0168] Flywheel energy storage array: releases 20MW / 15s instantaneous power;

[0169] SOEC electrolysis stack: Switch to steam electrolysis mode (efficiency increased to 85%);

[0170] Hydrogen storage tank pressure reducing valve: open the secondary pressure reducing channel;

[0171] Hydrogen pipeline: Increase the compressor speed to 2800 rpm;

[0172] Ammonia synthesis reactor: injection of catalyst promoter;

[0173] (4) Execute module operations:

[0174] The flywheel magnetic bearing suspension gap is adjusted to 50 μm;

[0175] SOEC steam supply increased to 3.5t / h;

[0176] The hydrogen storage tank temperature control system starts liquid nitrogen cooling;

[0177] The oil pressure of the reciprocating compressor cylinder increased by 0.2MPa;

[0178] The catalyst injection system performs pulsed injection.

[0179] Scenario 4: Multi-system collaboration in extreme weather

[0180] (1) Emergency: Sandstorms cause photovoltaic output to drop to 10%, wind power forecast deviation reaches 40%, and coal chemical industry needs to maintain minimum load.

[0181] (2) The instruction conversion module generates signals:

[0182] Photovoltaic bracket: start the 30° tilt dust removal mode;

[0183] Wind turbine: The yaw system switches to anti-turbulence mode;

[0184] Flow batteries: Activate rapid circulation of vanadium electrolytes;

[0185] Standby diesel generator: pre-start command;

[0186] Coal chemical DCS: cut into low-load operation program;

[0187] (3) Execute module operations:

[0188] The photovoltaic cleaning robot starts the high-frequency vibration mode (500Hz);

[0189] The wind turbine pitch control system performs 3s level dynamic adjustment;

[0190] The flow battery pump speed is increased to 120% of the rated flow rate;

[0191] The diesel engine preheating system starts 30 minutes in advance;

[0192] The oxygen-carbon ratio of the gasifier is adjusted to 0.8:1.

[0193] This multi-time-scale and multi-spatial-dimensional coordinated control can improve the overall energy efficiency of the system by 12-15%, control the wind and solar power curtailment rate below 3%, and achieve an industry-leading comprehensive hydrogen energy utilization efficiency of 82%.

[0194] Example 4:

[0195] In the fourth embodiment of the present invention, based on the above-mentioned first, second, or third embodiments, a multi-instruction coordination module is further provided in the control execution unit, which is configured to select a preset mode for execution based on the deviation level between the real-time data obtained by the intraday data real-time monitoring unit and the predicted value obtained by the day-ahead data prediction unit; wherein the preset modes include:

[0196] Economic priority mode: Prioritizes day-ahead dispatch instructions, allowing purchased electricity to deviate from a preset range. This mode ensures low-cost operation and is suitable for scenarios with high forecast accuracy and low fluctuations.

[0197] Consumption priority mode: When the current green power output exceeds the preset value, the electrolyzer operating power is prioritized to be increased to the current green power output's maximum consumption limit; the current green power output is the sum of the actual wind power generation power and the actual photovoltaic power generation power. This mode maximizes green power consumption and is suitable for periods of abundant wind and solar resources.

[0198] Emergency supply mode: When the inventory level in the hydrogen storage tank falls below the safety threshold, it switches to an external hydrogen source for replenishment; this mode can prevent interruptions in coal chemical operations.

[0199] Embodiment 5:

[0200] In addition to the above-mentioned Embodiment 1, Embodiment 2, or Embodiment 3 or Embodiment 4, the fifth embodiment of the present invention further includes a blockchain management unit for recording wind and solar power generation, hydrogen production and coal chemical hydrogen consumption, generating a verifiable green electricity traceability certificate, and interacting with an external power grid and a carbon trading platform; the blockchain management unit automatically matches low-price green electricity periods through smart contracts, and can optimize external power purchase strategies.

[0201] Specifically, the introduction of blockchain technology enables data such as wind and solar power generation, hydrogen production, and coal chemical hydrogen consumption to be recorded in an unalterable manner. The generated green electricity traceability certificate is highly credible and traceable, enhancing the transparency and credibility of system data. Through interaction with external power grids and carbon trading platforms, the blockchain management unit facilitates the trading of green electricity and carbon emission rights, helping to promote the healthy development of the green electricity market and the achievement of carbon reduction targets. The smart contract's automatic matching of low-price green electricity time periods enables the system to dynamically adjust electricity purchasing strategies according to market prices, reduce electricity purchasing costs, and improve the economy of the system.

[0202] Example 6:

[0203] In addition to the above-mentioned embodiments one, two, three, four or five, the fifth embodiment of the present invention further includes a three-dimensional visualization unit, an integrated digital twin model, and a dynamic display of the topological structure, energy flow and equipment operating parameters of the wind power generation subsystem, photovoltaic power generation subsystem, energy storage subsystem, hydrogen production subsystem and coal chemical subsystem, thereby enhancing the operability and maintainability of the system.

[0204] Specifically, the three-dimensional visualization unit uses a digital twin model to display complex system structures, energy flows, and equipment operating parameters in an intuitive three-dimensional form, allowing users to more easily understand the system operating status and improve the system's operability; through three-dimensional visualization, users can more quickly locate problems and fault points in the system, perform maintenance and repairs in a timely manner, reduce system downtime, and improve system stability and reliability; the three-dimensional visualization unit provides an intuitive reference and basis for system optimization and upgrades. Users can more accurately tune and improve the system based on the visualized system status and operating data, thereby promoting the continuous development and progress of the system.

[0205] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0206] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A green electricity hydrogen production coupled with coal chemical integrated energy management system, characterized in that: Realize integrated energy management of wind power generation subsystem, photovoltaic power generation subsystem, energy storage subsystem, hydrogen production subsystem and coal chemical subsystem, including: The day-ahead data prediction unit is used to obtain the wind power generation power forecast value, photovoltaic power generation power forecast value, green power consumption forecast value of the hydrogen production subsystem, hydrogen production efficiency forecast value and hydrogen storage tank inventory forecast value within a preset time period in the future, as well as the hydrogen demand forecast value of the coal chemical subsystem; The intraday data real-time monitoring unit is used to collect the energy storage subsystem capacity, actual hydrogen tank inventory, actual wind power generation power, actual photovoltaic power generation power, actual hydrogen production efficiency, and actual hydrogen demand of the coal chemical subsystem at the current time point; a day-ahead scheduling unit, configured to optimize and generate a day-ahead scheduling instruction based on the data acquired by the day-ahead data prediction unit and taking minimization of the full-cycle hydrogen production cost as the day-ahead objective function; An intraday rolling optimization unit is configured to generate an intraday dispatch instruction based on the data obtained by the intraday data real-time monitoring unit, with minimization of real-time wind and solar power curtailment as the intraday objective function, combined with the energy storage subsystem capacity over-limit warning and hydrogen demand deviation feedback; The control execution unit is used to execute the day-ahead scheduling instruction and the intra-day scheduling instruction.

2. The green electricity hydrogen production coupled with coal chemical integrated energy management system according to claim 1 is characterized in that: The day-ahead dispatching instructions include the day-ahead dispatching instructions for the electrolyzer, the day-ahead dispatching instructions for external power purchases, and the day-ahead dispatching instructions for the energy storage subsystem.

3. The green electricity hydrogen production coupled with coal chemical integrated energy management system according to claim 1 is characterized in that: The intraday scheduling instructions include intraday scheduling instructions for the electrolyzer and intraday scheduling instructions for the energy storage subsystem.

4. The green electricity hydrogen production coupled with coal chemical integrated energy management system according to claim 1 is characterized in that: The objective function at the present day is expressed as: Where T represents the number of preset time periods in the future preset time period; C grid (t) represents the external grid electricity price in the tth period; P grid (t) represents the external power purchase in the tth period; λ curt Indicates the penalty coefficient for curtailing wind and solar power; represents the predicted value of wind power generation in the tth period; represents the predicted value of photovoltaic power generation in the tth period; represents the predicted value of green power consumption in the tth period; H2 Indicates the penalty coefficient for exceeding the limit of hydrogen storage tank inventory; represents the predicted value of hydrogen storage tank inventory in period t; It represents the safety value of hydrogen storage tank inventory in the tth period.

5. The green electricity hydrogen production coupled with coal chemical integrated energy management system according to claim 4 is characterized in that: The constraints corresponding to the day-ahead objective function include: (1) Dynamic balance constraints of hydrogen storage tank inventory: in, It represents the predicted value of hydrogen production efficiency of electrolyzer; represents the predicted value of hydrogen demand of the coal chemical subsystem in the tth period; (2) Hydrogen storage tank inventory constraints: in, Indicates the lower limit of hydrogen storage tank inventory; Indicates the upper limit of hydrogen storage tank inventory; (3) Electrolyzer operation constraints in the hydrogen production subsystem: Among them, P H2 (t) represents the operating power of the electrolyzer at the tth period; Indicates the minimum operating power of the electrolytic cell; Indicates the maximum operating power of the electrolytic cell; (4) External power purchase power constraints: in, Indicates the maximum external power purchase power; (5) Hydrogen demand constraints of coal chemical subsystem: (6) Energy storage subsystem capacity constraints: P ch (t)·P dis (t)=0 Where SOC(t) represents the remaining energy of the energy storage subsystem in time period t; η ch represents the charging efficiency of the energy storage subsystem; η dis represents the discharge efficiency of the energy storage subsystem; P ch (t) represents the charging power of the energy storage subsystem; P dis (t) represents the discharge power of the energy storage subsystem; Indicates the maximum charge and discharge power of the energy storage subsystem; SOC min Indicates the lower limit of energy storage subsystem capacity; SOC max Indicates the upper limit of the energy storage subsystem capacity.

6. The green electricity hydrogen production coupled with coal chemical integrated energy management system according to claim 1 is characterized in that: The intraday objective function is expressed as: ΔSOC(t)=max(SOC(t)-SOC max ,SOC min -SOC(t),0) Among them, λ curt Indicates the penalty coefficient for curtailing wind and solar power; Indicates the actual value of wind power generation in period t; Indicates the actual value of photovoltaic power generation during period t; represents the predicted value of green power consumption in the tth period; SOC represents the penalty coefficient for exceeding the capacity limit of the energy storage subsystem; SOC(t) represents the remaining energy of the energy storage subsystem in time period t; ΔSOC(t) represents the deviation between the capacity of the energy storage subsystem and the safety range represents the hydrogen demand deviation penalty coefficient; represents the actual value of hydrogen demand of the coal chemical subsystem in the tth period; Indicates the actual value of hydrogen production efficiency of the electrolyzer; P H2 (t) represents the operating power of the electrolyzer at the tth period; SOC min Indicates the lower limit of energy storage subsystem capacity; SOC max Indicates the upper limit of the energy storage subsystem capacity.

7. The green electricity hydrogen production coupled with coal chemical integrated energy management system according to claim 6, characterized in that: The constraints corresponding to the intraday objective function include: (1) Power balance constraints: Among them, P grad (t) represents the external power purchase; P curt (t) represents the abandoned wind and solar power; Indicates other electrical power except the electrolytic cell operating power; (2) Hydrogen storage tank inventory constraints: in, Indicates the actual value of the hydrogen storage tank inventory during period t; (3) Energy storage subsystem constraints SOC min ≤SOC(t)≤SOC max P ch (t)·P dis (t)=0 Among them, η ch represents the charging efficiency of the energy storage subsystem; η dis represents the discharge efficiency of the energy storage subsystem; P ch (t) represents the charging power of the energy storage subsystem; P dis (t) represents the discharge power of the energy storage subsystem; Indicates the maximum charge and discharge power of the energy storage subsystem.

8. The green electricity hydrogen production coupled with coal chemical integrated energy management system according to claim 1, characterized in that: In the intraday rolling optimization unit, rolling optimization is performed every preset time period.

9. The green electricity hydrogen production coupled with coal chemical integrated energy management system according to claim 1, characterized in that: The control execution unit includes an instruction conversion module and an execution module; The instruction conversion module is used to convert the day-ahead scheduling instruction and the intraday scheduling instruction into device control signals; The execution module is used to regulate the equipment in the wind power generation subsystem, photovoltaic power generation subsystem, energy storage subsystem, hydrogen production subsystem and coal chemical subsystem according to the equipment control signal.

10. The green electricity hydrogen production coupled with coal chemical integrated energy management system according to claim 9, characterized in that: The control execution unit also includes a multi-instruction coordination module; The multi-command coordination module is configured to select a preset mode for execution based on a deviation level between the real-time data obtained by the intraday data real-time monitoring unit and the predicted value obtained by the day-ahead data prediction unit; The preset modes include: Economic priority mode: Prioritizes the execution of the day-ahead dispatch instructions, allowing the purchased electricity to deviate from the preset deviation range; Consumption priority mode: When the current green power output exceeds the preset value, the electrolyzer operating power is prioritized to be increased to the current green power output that can be consumed. The current green power output is the sum of the actual wind power generation power and the actual photovoltaic power generation power. Emergency supply mode: When the inventory level of the hydrogen storage tank is lower than the safety threshold, switch to external hydrogen source for replenishment.

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