A method and device for operating and controlling a wind-solar-hydrogen storage integrated energy system, and equipment

Abstract

The application belongs to the technical field of intelligent control, and discloses a kind of operation control method and device, equipment of wind and light hydrogen storage comprehensive energy system, by controlling scheduling layer MPC to run with first control period, in each cycle, generate the coupling reference trajectory of future time domain SOC, SOCH and grid interaction power reference value, build optimization problem to obtain the optimal solution of energy storage power and electrolytic cell reference power;Control control layer MPC to run with shorter second control period, and receive coupling reference trajectory as hard tracking target in each cycle, and build optimization problem to generate energy storage and electrolytic cell control instruction sequence;So it can reduce grid tie line power fluctuation, effectively decouple long-term economy and short-term real-time control demand;At the same time, embedding the dynamic energy conversion constraint of electrolytic cell reference power and SOCH can ensure the physical realizability of reference trajectory, improve the success rate of optimization solution, and enhance the robustness of system operation.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology, specifically to an operation control method and device, electronic equipment, and storage medium for a wind-solar-hydrogen-storage integrated energy system. Background Technology

[0002] The installed capacity of renewable energy sources such as wind power and solar power in the power system continues to increase. However, wind power and solar power are characterized by strong randomness, volatility, and unschedulability, posing serious challenges to the safe operation of the power grid and high-proportion absorption. Battery energy storage systems (BESS) and power-to-hydrogen electrolysis, as two important flexible resources, can provide energy buffering capabilities across time scales through "electricity-electricity" and "electricity-hydrogen" paths, respectively, and are therefore widely integrated into integrated wind-solar-hydrogen-storage energy systems.

[0003] The existing operation and control strategies for integrated wind, solar, hydrogen and storage energy systems mainly include single-layer model predictive control (MPC). Although it can handle constrained optimization, it focuses on a single objective in hourly economic dispatch or minute-level power smoothing, and usually only considers the "electricity-storage" system.

[0004] The complexity of the problem increases significantly when an electrolysis hydrogen production unit is introduced into the system. On the one hand, electrolyzers have limited start-up and shutdown cycles, nonlinear efficiency variations with power, and response delays. On the other hand, the State of Charge for Hydrogen (SOCH) and the State of Charge for Energy (SOC) are heterogeneous in terms of time scale and regulation capability, making coordination through a unified MPC framework difficult. More importantly, in scenarios with significant errors in ultra-short-term wind and solar forecasts, a single-timescale MPC is prone to constraint conflicts that render the optimization problem infeasible, resulting in a low success rate in solving the optimization problem and thus affecting the system's robustness. Summary of the Invention

[0005] To address the aforementioned shortcomings, the present invention aims to provide an operation control method and device, electronic equipment, and storage medium for a wind-solar-hydrogen-storage integrated energy system, which can improve the success rate of solving optimization problems and enhance the robustness of system operation.

[0006] The first aspect of this invention discloses an operation control method for a wind-solar-hydrogen-storage integrated energy system, applied to an electronic device. The electronic device is embedded with a dual-time-scale rolling optimization system, which includes a scheduling layer MPC unit and a control layer MPC unit. The method includes:

[0007] Based on the real-time measured values ​​of wind power generation, photovoltaic power generation, power load, energy storage state of charge, and hydrogen storage state of charge, an ultra-short-term power prediction sequence for a specified future time period is determined. The ultra-short-term power prediction sequence includes the predicted values ​​of wind power generation, photovoltaic power generation, and power load.

[0008] The system controls the scheduling layer MPC unit to operate in a first control cycle, and within each first control cycle, corrects the initial scheduling benchmark according to the ultra-short-term power prediction sequence to obtain the grid interaction power reference value, and generates a coupled reference trajectory of the energy storage state of charge, the hydrogen storage state of charge, and the grid interaction power reference value in the future time domain; and constructs a first optimization problem with the goal of minimizing the system's full-cycle operating cost, and solves the first optimization problem to obtain the optimal solution for the energy storage power and the electrolyzer reference power; wherein, the constraints when solving the first optimization problem include the dynamic energy conversion constraints between the electrolyzer reference power and the hydrogen storage state of charge;

[0009] The control layer MPC unit is controlled to operate in a second control cycle shorter than the first control cycle. Within each second control cycle, the coupled reference trajectory is received as a hard tracking target. A second optimization problem is constructed with the goal of minimizing the net power tracking error and the control increment. Solving the second optimization problem yields a sequence of control commands corresponding to the optimal solutions for the energy storage power and the electrolyzer reference power. The net power tracking error refers to the difference between the system's net power and the grid interaction power reference value in the coupled reference trajectory.

[0010] If the control command sequence is feasible, the first control command in the control command sequence is sent to the corresponding execution device.

[0011] In some embodiments, the dynamic energy conversion constraint specifically refers to:

[0012]

[0013] in, This represents the state of charge of the hydrogen storage at the end of the kth first control cycle, with a value ranging from 0% to 100%. The reference power of the electrolyzer output is calculated for the scheduling layer MPC unit, in kW; The average energy conversion efficiency of the electrolytic cell; The lower heating value of hydrogen; This is the volume of hydrogen that can be stored. The sampling period of the scheduling layer MPC unit; To predict the length of the time domain.

[0014] In some embodiments, after issuing the first control instruction in the control instruction sequence to the corresponding execution device, the method further includes:

[0015] Obtain the actual operational feedback data after the corresponding execution device executes the control command;

[0016] Based on the actual operation feedback data, the average energy conversion efficiency of the electrolyzer and the internal resistance of the battery are jointly estimated and updated online, and the updated average energy conversion efficiency of the electrolyzer and the internal resistance of the battery are fed back to the scheduling layer MPC unit and the control layer MPC unit.

[0017] In some embodiments, the constraints for solving the first optimization problem further include equipment safety boundary constraints and system power balance constraints; wherein, the equipment safety boundary constraints include the SOC safety boundary, the SOCH safety boundary, the electrolyzer ramp rate, the grid switching power limit, and the number of electrolyzer start-ups and shutdowns; the system power balance constraints are:

[0018] P WT + P PV = P Load + P Bat +P EL + P Grid,ref

[0019] Among them, P WT P is the predicted value of the wind power generation capacity. PV P is the predicted value of the photovoltaic power generation. Load P is the predicted value of the power load. Bat It is the controllable power of energy storage, P EL It is the controllable power of the electrolytic cell, P Grid,ref It is the power grid interaction reference value in the coupled reference trajectory.

[0020] In some embodiments, the method further includes:

[0021] If the control command sequence is not feasible, some constraints are relaxed in sequence according to a preset priority; wherein, some constraints include the SOCH safety boundary, the power grid exchange power limit and the electrolyzer ramp rate; the preset priority is set as: SOCH safety boundary > power grid exchange power limit > electrolyzer ramp rate.

[0022] The second aspect of this invention discloses an operation control device for a wind-solar-hydrogen-storage integrated energy system. The device is embedded with a dual-timescale rolling optimization system, which includes a scheduling layer MPC unit and a control layer MPC unit. The device comprises:

[0023] The prediction unit is used to determine an ultra-short-term power prediction sequence for a specified period of time in the future based on the measured values ​​of wind power generation, photovoltaic power generation, power load, energy storage state of charge and hydrogen storage state of charge collected in real time. The ultra-short-term power prediction sequence includes the predicted values ​​of wind power generation, photovoltaic power generation and power load.

[0024] The first optimization unit is used to control the scheduling layer MPC unit to operate in a first control cycle, and within each first control cycle, to correct the initial scheduling benchmark according to the ultra-short-term power prediction sequence to obtain the grid interaction power reference value, and to generate a coupled reference trajectory of the energy storage state of charge, the hydrogen storage state of charge, and the grid interaction power reference value in the future time domain; and to construct a first optimization problem with the goal of minimizing the system's full-cycle operating cost, and to solve the first optimization problem to obtain the optimal solution for the energy storage power and the electrolyzer reference power; wherein, the constraints when solving the first optimization problem include the dynamic energy conversion constraints between the electrolyzer reference power and the hydrogen storage state of charge;

[0025] The second optimization unit is used to control the control layer MPC unit to operate in a second control cycle shorter than the first control cycle, and to receive the coupled reference trajectory as a hard tracking target in each second control cycle, and to construct a second optimization problem with the goal of minimizing the net power tracking error and the control increment, and to solve the second optimization problem to obtain a control command sequence corresponding to the optimal solution of the energy storage power and the reference power of the electrolyzer; wherein, the net power tracking error refers to the difference between the system net power and the grid interaction power reference value in the coupled reference trajectory;

[0026] An execution unit is configured to, when the control command sequence is feasible, issue the first control command in the control command sequence to the corresponding execution device.

[0027] In some embodiments, the apparatus further includes:

[0028] The feedback unit is used to obtain the actual operation feedback data of the corresponding execution device after the execution unit issues the first control instruction in the control instruction sequence to the corresponding execution device;

[0029] The update unit is used to perform online joint estimation and update of the average energy conversion efficiency of the electrolyzer and the internal resistance of the battery based on the actual operation feedback data, and to feed back the updated average energy conversion efficiency of the electrolyzer and the internal resistance of the battery to the scheduling layer MPC unit and the control layer MPC unit.

[0030] In some embodiments, the apparatus further includes a relaxation unit, configured to relax some constraints sequentially according to a preset priority when the control command sequence is not feasible; wherein the partial constraints include the SOCH safety boundary, the grid exchange power limit, and the electrolyzer ramp rate; the preset priority is set as follows: the SOCH safety boundary > the grid exchange power limit > the electrolyzer ramp rate.

[0031] The third aspect of this invention discloses an electronic device, including a memory storing executable program code and a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute the operation control method of the wind-solar-hydrogen-storage integrated energy system disclosed in the first aspect.

[0032] The fourth aspect of this invention discloses a computer-readable storage medium storing a computer program, wherein the computer program causes a computer to execute the operation control method of the integrated wind-solar-hydrogen-storage energy system disclosed in the first aspect.

[0033] Compared with existing technologies, the beneficial effects of this invention are as follows: By embedding a dual-timescale rolling optimization system including a scheduling layer MPC unit and a control layer MPC unit; based on the real-time collected measured values ​​of wind power generation, photovoltaic power generation, power load, SOC, and SOCH, an ultra-short-term power prediction sequence is determined; the scheduling layer MPC unit is controlled to operate in a first control cycle, and within each cycle, the initial scheduling benchmark is corrected according to the ultra-short-term power prediction sequence to obtain a grid interaction power reference value, and a coupled reference trajectory of SOC, SOCH, and grid interaction power reference values ​​in the future time domain is generated; and a first optimization problem is constructed with the goal of minimizing the system's full-cycle operating cost, and the optimal solution for energy storage power and electrolyzer reference power is obtained; the control layer... The layered MPC unit operates with a shorter second control cycle and receives the coupled reference trajectory as a hard tracking target in each cycle. It constructs a second optimization problem with the goal of minimizing net power tracking error and control increment, and solves it to obtain the control command sequence for energy storage and electrolyzer. Thus, through the hierarchical architecture of generating an electric-hydrogen coordinated reference trajectory at the scheduling layer and forcing tracking at the control layer, the renewable energy absorption capacity can be significantly improved, grid tie-line power fluctuations can be reduced, and long-term economic efficiency and short-term real-time control requirements can be effectively decoupled. At the same time, embedding the dynamic energy conversion constraints of the electrolyzer reference power and SOCH in the optimization process of the scheduling layer can ensure the physical realizability of the reference trajectory, avoid generating infeasible commands, greatly improve the success rate of solving the optimization problem at the control layer, and enhance the robustness of system operation. Attached Figure Description

[0034] Figure 1 This is a flowchart of an operation control method for a wind-solar-hydrogen-storage integrated energy system disclosed in an embodiment of the present invention;

[0035] Figure 2 This is a schematic diagram of the operation control device of a wind-solar-hydrogen-storage integrated energy system disclosed in an embodiment of the present invention;

[0036] Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of the present invention;

[0037] Figure 4 This is a schematic diagram of the structure of a computer device disclosed in an embodiment of the present invention.

[0038] Explanation of reference numerals in the attached figures:

[0039] 201. Prediction unit; 202. First optimization unit; 203. Second optimization unit; 204. Execution unit; 301. Memory; 302. Processor. Detailed Implementation

[0040] To enable those skilled in the art to better understand the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

[0041] In some of the processes described in the specification, claims, and accompanying drawings of this invention, multiple operations appearing in a specific order are included. However, it should be clearly understood that these operations may not be executed in the order they appear herein, or may be executed in parallel. The operation numbers, such as 110, 120, etc., are merely used to distinguish different operations and do not themselves represent any execution order. Furthermore, these processes may include more or fewer operations, and these operations may be executed sequentially or in parallel. It should be noted that the descriptions such as "first," "second," etc., in this document are used to distinguish different messages, devices, modules, etc., and do not represent a sequential order, nor do they limit "first" and "second" to different types.

[0042] It will be understood by those skilled in the art that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any units and all combinations of one or more associated listed items.

[0043] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by those skilled in the art to which this invention pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0044] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Throughout the description, the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0045] Please see Figure 1 This invention discloses an operation control method for a wind-solar-hydrogen-storage integrated energy system. The method can be executed by electronic devices such as computers, laptops, tablets, industrial controllers, or management terminals, or by an operation control device for the wind-solar-hydrogen-storage integrated energy system embedded in an electronic device; this invention does not limit this. In this embodiment, an electronic device is used as an example. The electronic device is equipped with a dual-time-scale rolling optimization system, which includes a scheduling layer MPC unit and a control layer MPC unit. Figure 1 As shown, the method includes the following steps 110-140:

[0046] 110. Based on the real-time collected measured values ​​of wind power generation, photovoltaic power generation, power load, energy storage state of charge, and hydrogen storage state of charge, determine the ultra-short-term power prediction sequence for a specified future period. The ultra-short-term power prediction sequence includes the predicted values ​​of wind power generation, photovoltaic power generation, and power load.

[0047] The measured values ​​of wind turbine power (PWT), photovoltaic power (PPV), power load (PLoad), energy storage state of charge (SOC), and hydrogen storage state of charge (SOCH) at the current moment can be acquired in real time through a Supervisory Control and Data Acquisition (SCADA) system. These values ​​are then input into the prediction service interface to obtain an ultra-short-term power prediction sequence. The ultra-short-term power prediction sequence includes, but is not limited to, the predicted values ​​of wind turbine power, photovoltaic power, and power load; the specified duration can be set to 1 hour; and the acquisition cycle can be set to execute once every 300 seconds.

[0048] 120. The control and scheduling layer MPC unit operates in the first control cycle, and within each control cycle, it corrects the initial scheduling benchmark according to the ultra-short-term power prediction sequence to obtain the grid interaction power reference value, and generates the coupled reference trajectory of energy storage state of charge, hydrogen storage state of charge, and grid interaction power reference value in the future time domain; and constructs a first optimization problem with the goal of minimizing the system's full-cycle operating cost, and solves the first optimization problem to obtain the optimal solution for energy storage power and electrolyzer reference power; wherein, the constraints when solving the first optimization problem include the dynamic energy conversion constraints of electrolyzer reference power and hydrogen storage state of charge.

[0049] In this embodiment of the invention, a scheduling layer MPC unit and a control layer MPC unit are constructed to form a dual-time-scale rolling optimization system. Before operation, parameters such as the sampling period, prediction time domain, control time domain, weight matrix, and grid switching limit can be initialized by loading a configuration file.

[0050] In the dual-time-scale rolling optimization system of this embodiment, the daily plan is determined as the initial scheduling benchmark based on the measured values ​​of the on-grid power and off-grid power at the current moment. On this basis, the scheduling layer MPC unit uses the ultra-short-term power prediction sequence to perform rolling correction on the initial scheduling benchmark, generating the grid interaction power reference value, i.e., the intraday plan. Then, in the optimization model of the scheduling layer MPC unit, the grid interaction power reference value is used as the core decision variable, and the optimal energy storage power and electrolyzer reference power are obtained through power balance constraint coupling. Finally, the control layer MPC unit generates the real-time control commands for the final energy storage power and electrolyzer reference power to ensure that the actual power of the system tracks the grid interaction power reference value.

[0051] For the scheduling layer MPC unit, the sampling period is set to The prediction time domain length is set to That is, 24 hours. For the control layer MPC unit, the sampling period is set to... The prediction time domain length is set to The control time domain length is set to In addition, the system energy storage constraints are set to SOC∈[20%, 90%], the reference power range of the electrolyzer is set to PEL∈[0.2,1.0]pu, and the ramp rate is set to ≤10% / min. The system solver adopts a quadratic programming (QP) solver, such as qpOASES or OSQP solver, which supports hot start and infeasibility detection, and can ensure real-time optimization at the minute level, with high efficiency.

[0052] The first control cycle is an hourly cycle, which can be set to 1 hour. The control scheduling layer MPC unit executes once every first control cycle. The execution includes: constructing and solving the first optimization problem with the goal of minimizing the system's full-cycle operating cost, and generating coupled reference trajectories of the energy storage state of charge, hydrogen storage state of charge, and grid interaction power reference values ​​in the future time domain. The full system cycle refers to a complete control cycle. The operating cost may include one or more of the following: equipment investment cost, equipment maintenance cost, and electricity purchase cost. In this embodiment of the invention, the full system cycle operating cost includes the equipment investment cost, equipment maintenance cost, and electricity purchase cost allocated according to the cycle. The first optimization problem with the goal of minimizing the system's full-cycle operating cost is shown in the following equation (1):

[0053] (1)

[0054] in, For the prediction time domain of the scheduling layer MPC unit, That is, 24 hours; The time-of-use electricity price for the k-th control period. This is the grid interaction power reference value in the coupled reference trajectory during the k-th control cycle. Let $\frac{ ... The equipment operation and maintenance cost for the k-th control cycle is... Weighting of equipment operation and maintenance costs; The equipment investment cost for the k-th control cycle is... This is the weighting of equipment investment costs.

[0055] Alternatively, the equipment operation and maintenance costs may include, but are not limited to, the maintenance costs of energy storage batteries and electrolytic cells, as shown in the following formula (2):

[0056] (2)

[0057] in, and These are the unit maintenance costs for energy storage batteries and electrolyzers, respectively. and These are the power reference values ​​for the energy storage battery and the electrolyzer, respectively, during the k-th control cycle.

[0058] The equipment investment cost includes, but is not limited to, the fixed investment cost of energy storage batteries and electrolytic cells, as shown in the following formula (3):

[0059] (3)

[0060] in, and These represent the total initial investment in energy storage batteries and electrolytic cells, respectively. and These refer to the design life of the energy storage battery and the electrolyzer, respectively. and These represent the operating hours of the energy storage battery and the electrolyzer during this control cycle, respectively.

[0061] To ensure that the coupled reference trajectory is physically realizable, when the scheduling layer MPC unit generates the coupled reference trajectory, the dynamic energy conversion constraint of the electrolysis hydrogen production system can be explicitly embedded in the scheduling layer MPC unit, strongly coupling the hydrogen storage state of charge with the reference power of the electrolyzer through the energy conservation relationship. Specifically, the dynamic constraint of hydrogen storage is introduced as shown in the following equation (4):

[0062] (4)

[0063] in, This represents the state of charge of the hydrogen storage at the end of the kth first control cycle, with a value ranging from 0% to 100%. The reference power of the electrolyzer output is calculated for the scheduling layer MPC unit, in kW; The average energy conversion efficiency of the electrolyzer can be configured as a constant or a power-dependent function; The lower heating value of hydrogen; This is the volume of hydrogen that can be stored. The sampling period for the scheduling layer MPC unit can be set to 3600 seconds; To predict the length of the time domain.

[0064] By dynamically coupling the electrolyzer reference power with the hydrogen storage state of charge, the SOCH content in the coupled reference trajectory can be ensured. The evolution strictly follows physical laws, that is, ensuring the physical realizability of the coupled reference trajectory, thereby avoiding the generation of infeasible instructions.

[0065] Further optionally, multidimensional constraints can be embedded, that is, the constraints can also include equipment safety boundary constraints and system power balance constraints; among which, equipment safety boundary constraints include, but are not limited to, SOC safety boundary, SOCH safety boundary, electrolyzer ramp rate, grid exchange power limit and electrolyzer start-up and shutdown times constraints; the electrolyzer start-up and shutdown times constraints are transformed into a continuous optimization problem with a penalty term by introducing auxiliary slack variables and the Big M method, so as to be compatible with QP solvers.

[0066] The system power balance constraint is shown in equation (5) below:

[0067] P WT + P PV = P Load + P Bat +P EL + P Grid,ref (5)

[0068] Among them, P WT This is the predicted value of wind power generation, P. PV This is the predicted value of photovoltaic power generation, P. Load This is the predicted value of the power load, P. Bat It is the controllable power of energy storage, P EL It is the controllable power of the electrolytic cell, P Grid,ref It is the power reference value of the power grid interaction in the coupled reference trajectory.

[0069] 130. The control layer MPC unit operates with a second control cycle shorter than the first control cycle. Within each control cycle, it receives the coupled reference trajectory as a hard tracking target and constructs a second optimization problem aimed at minimizing the net power tracking error and control increment. Solving this second optimization problem yields the control command sequence corresponding to the optimal solution for the energy storage power and the electrolyzer reference power. Here, the net power tracking error refers to the difference between the system's net power and the grid interaction power reference value in the coupled reference trajectory.

[0070] In this invention, the control layer MPC unit uses a second control cycle with a minute-level cycle, which can be set to 5, 6, or 10 minutes. As an optional implementation, the coupled reference trajectory is received as a hard tracking target, and the second optimization problem is constructed as shown in equation (6):

[0071] (6)

[0072] in, For controllable total energy output, ; The net power of the system. ; This represents the grid interaction power reference value in the coupled reference trajectory output by the scheduling layer MPC unit. K is the current control step size. For the prediction duration of the control layer MPC unit, To control the increment, optimizing the control increment can suppress frequent fluctuations in control commands. This represents the square operation of the weighted Euclidean norm. The operator subscripts Q and R indicate that this is the error weight matrix and control increment matrix, respectively. The controlled output of the control layer MPC unit is the total controllable energy power P. gen =P Bat +P EL This refers to the sum of the controllable power of the energy storage and electrolyzers. The reference target is the difference between the system's net power and the grid interaction power reference value, i.e.: y ref = P net –P grid,ref = (P WT + P PV -P Load ) - P grid,ref .

[0073] Control layer MPC unit to minimize P gen For y ref The tracking deviation and control increment are used as optimization objectives. The `mpc_controller.compute_control()` module is called online to solve the second optimization problem through numerical calculation methods, outputting the control command sequence for the energy storage and electrolyzer, and further predicting the expected value of grid interaction power under this control command sequence. By controlling the power of the energy storage and electrolyzer through the control command sequence, the actual grid interaction power tracks the grid interaction power reference value.

[0074] If the solution is successful, the control command sequence for the energy storage and electrolyzer will be issued, and step 140 will be executed; if the solution fails, such as due to constraint conflict, step 150 will be executed.

[0075] 140. If the control command sequence is feasible, issue the first control command in the control command sequence of the energy storage and electrolytic cell to the corresponding execution device.

[0076] If the control command sequence is feasible, the solution is considered successful. The first element of the control command sequence is then taken, and after limiting and rate checks, it is sent to the corresponding execution device via the IEC-104 protocol. The execution device includes, but is not limited to, electrolyzers, fuel cells, energy storage converters, etc.

[0077] 150. If the control instruction sequence is not feasible, relax some constraints in sequence according to the preset priority.

[0078] If the control command sequence is infeasible, the solution is considered to have failed, and the infeasibility recovery mechanism is activated, which relaxes constraints according to a preset priority. Only some constraints, excluding the SOC safety boundary and system power balance constraints, are set as relaxable; the SOC safety boundary and system power balance constraints are set as non-relaxable and remain hard constraints, ensuring the system always operates within the safety domain. The preset priority of the relaxable constraints can be set as: SOC safety boundary > grid exchange power limit > electrolyzer ramp rate.

[0079] As an optional implementation, after performing step 140, the following steps 141-142 may also be performed:

[0080] 141. Obtain the actual operational feedback data after the corresponding execution device executes the control command.

[0081] 142. Based on actual operation feedback data, the average energy conversion efficiency of the electrolyzer and the internal resistance of the battery are jointly estimated and updated online, and the updated average energy conversion efficiency of the electrolyzer and the internal resistance of the battery are fed back to the scheduling layer MPC unit and the control layer MPC unit.

[0082] This invention also includes a feedback correction mechanism. Based on the measured actual operating feedback data of the execution equipment, the extended Kalman filter (EKF) or unscented Kalman filter (UKF) algorithm is used to jointly estimate and update key parameters such as the average energy conversion efficiency η of the electrolyzer and the internal resistance of the battery online. The updated results are then fed back to the scheduling layer and the control layer MPC unit model, forming a cross-layer adaptive closed loop. The process then waits for the next control cycle and repeats the above steps.

[0083] In summary, by implementing the embodiments of the present invention, the hierarchical architecture of generating an electric-hydrogen collaborative reference trajectory at the scheduling layer and forcing tracking at the control layer can significantly improve the renewable energy absorption capacity, reduce grid tie-line power fluctuations, and effectively decouple long-term economic efficiency from short-term real-time control requirements. Furthermore, embedding dynamic energy conversion constraints of the electrolyzer reference power and SOCH during the scheduling layer optimization process ensures the physical realizability of the reference trajectory, avoids generating infeasible instructions, significantly improves the success rate of solving the control layer optimization problem, and enhances the system's operational robustness.

[0084] In addition, through collaborative optimization and start-stop constraints, the frequent start-stop of the electrolyzer is effectively reduced, while the energy storage SOC is maintained within a safe operating range, reducing equipment wear and extending equipment lifespan. Furthermore, by combining a high-efficiency QP solver with industrial communication protocols, the system meets the real-time, reliability, and compatibility requirements of practical integrated energy systems, demonstrating good engineering applicability.

[0085] By applying the method of this invention to a 200 MW wind-solar-hydrogen storage demonstration project, the results show that compared with the traditional single-layer MPC, the wind curtailment rate was reduced from 12.3% to 9.8%; the success rate of solving the control layer optimization problem was increased from 87% to 91%, which verifies the comprehensive superiority of this invention in terms of robustness, safety and economy.

[0086] like Figure 2 As shown in the figure, this invention also discloses an operation control device for a wind-solar-hydrogen-storage integrated energy system. This device is embedded with a dual-timescale rolling optimization system, which includes a scheduling layer MPC unit and a control layer MPC unit. The device includes a prediction unit 201, a first optimization unit 202, a second optimization unit 203, and an execution unit 204.

[0087] The prediction unit 201 is used to determine the ultra-short-term power prediction sequence within a specified time period based on the measured values ​​of wind power generation, photovoltaic power generation, power load, energy storage state of charge and hydrogen storage state of charge collected in real time. The ultra-short-term power prediction sequence includes the predicted values ​​of wind power generation, photovoltaic power generation and power load.

[0088] The first optimization unit 202 is used to control the scheduling layer MPC unit to operate in a first control cycle, and within each first control cycle, to correct the initial scheduling benchmark according to the ultra-short-term power prediction sequence to obtain the grid interaction power reference value, and to generate the coupled reference trajectory of the energy storage state of charge, the hydrogen storage state of charge, and the grid interaction power reference value in the future time domain; and to construct a first optimization problem with the goal of minimizing the system's full-cycle operating cost, and to solve the first optimization problem to obtain the optimal solution for the energy storage power and the electrolyzer reference power; wherein, the constraints when solving the first optimization problem include the dynamic energy conversion constraints of the electrolyzer reference power and the hydrogen storage state of charge;

[0089] The second optimization unit 203 is used to control the control layer MPC unit to operate in a second control cycle shorter than the first control cycle. In each second control cycle, it receives the coupled reference trajectory as a hard tracking target, constructs a second optimization problem with the goal of minimizing the net power tracking error and the control increment, and solves the second optimization problem to obtain the control command sequence corresponding to the optimal solution of the energy storage power and the reference power of the electrolyzer. Here, the net power tracking error refers to the difference between the system net power and the grid interaction power reference value in the coupled reference trajectory.

[0090] The execution unit 204 is used to issue the first control instruction in the control instruction sequence to the corresponding execution device when the control instruction sequence is feasible.

[0091] As an optional implementation, the apparatus further includes:

[0092] The feedback unit is used to obtain the actual operation feedback data of the corresponding execution device after the execution unit 204 issues the first control instruction in the control instruction sequence to the corresponding execution device;

[0093] The update unit is used to perform online joint estimation and update of the average energy conversion efficiency of the electrolyzer and the internal resistance of the battery based on actual operation feedback data, and to feed back the updated average energy conversion efficiency of the electrolyzer and the internal resistance of the battery to the scheduling layer MPC unit and the control layer MPC unit.

[0094] As an optional implementation, the device further includes a relaxation unit for relaxing some constraints in sequence according to a preset priority when the control command sequence is not feasible; wherein, the constraints include the SOCH safety boundary, the grid exchange power limit and the electrolyzer ramp rate; the preset priority is set as: SOCH safety boundary > grid exchange power limit > electrolyzer ramp rate.

[0095] like Figure 3 As shown, this embodiment of the invention also discloses an electronic device, including a memory 301 storing executable program code and a processor 302 coupled to the memory 301;

[0096] The processor 302 calls the executable program code stored in the memory 301 to execute the operation control method of the integrated wind-solar-hydrogen-storage energy system described in the above embodiments.

[0097] like Figure 4 As shown in the illustration, this invention also discloses a computer device. This computer device includes a processor, a memory, a network interface, a display screen, and an input device connected via a system bus. The processor in this computer design provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database of the computer device stores relevant data for the operation control method of the wind-solar-hydrogen-storage integrated energy system. The network interface of the computer device is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements the operation control method of the wind-solar-hydrogen-storage integrated energy system described in the above embodiments.

[0098] This invention also discloses a computer-readable storage medium storing a computer program that causes a computer to execute the operation control method for the integrated wind-solar-hydrogen-storage energy system described in the above embodiments. The storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, or optical data storage device, etc.

[0099] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).

[0100] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0101] The embodiments described above are merely examples of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention.

Claims

1. A method for operating and controlling a wind-solar-hydrogen-storage integrated energy system, characterized in that, The method is applied to an electronic device, which is embedded with a dual-timescale rolling optimization system, the system including a scheduling layer MPC unit and a control layer MPC unit; the method includes: Based on the real-time measured values ​​of wind power generation, photovoltaic power generation, power load, energy storage state of charge, and hydrogen storage state of charge, an ultra-short-term power prediction sequence for a specified future time period is determined. The ultra-short-term power prediction sequence includes the predicted values ​​of wind power generation, photovoltaic power generation, and power load. The system controls the scheduling layer MPC unit to operate in a first control cycle, and within each first control cycle, corrects the initial scheduling benchmark according to the ultra-short-term power prediction sequence to obtain the grid interaction power reference value, and generates a coupled reference trajectory of the energy storage state of charge, the hydrogen storage state of charge, and the grid interaction power reference value in the future time domain; and constructs a first optimization problem with the goal of minimizing the system's full-cycle operating cost, and solves the first optimization problem to obtain the optimal solution for the energy storage power and the electrolyzer reference power; wherein, the constraints when solving the first optimization problem include the dynamic energy conversion constraints between the electrolyzer reference power and the hydrogen storage state of charge; The control layer MPC unit is controlled to operate in a second control cycle shorter than the first control cycle. Within each second control cycle, the coupled reference trajectory is received as a hard tracking target. A second optimization problem is constructed with the goal of minimizing the net power tracking error and the control increment. Solving the second optimization problem yields a sequence of control commands corresponding to the optimal solutions for the energy storage power and the electrolyzer reference power. The net power tracking error refers to the difference between the system's net power and the grid interaction power reference value in the coupled reference trajectory. If the control command sequence is feasible, the first control command in the control command sequence is issued to the corresponding execution device; wherein, the dynamic energy conversion constraint is specifically: wherein, represents the state of charge of hydrogen storage at the end of the kth first control period, with a value of 0%~100%; is the electrolyzer reference power solved by the scheduling layer MPC unit, with a unit of kW; is the average energy conversion efficiency of the electrolyzer; is the low heat value of hydrogen; is the hydrogen storage volume; is the sampling period of the scheduling layer MPC unit; is the prediction time domain length. 2.The operation control method of the wind-solar-hydrogen storage comprehensive energy system according to claim 1, characterized in that, After issuing the first control instruction in the control instruction sequence to the corresponding execution device, the method further includes: Obtain the actual operational feedback data after the corresponding execution device executes the control command; Based on the actual operation feedback data, the average energy conversion efficiency of the electrolyzer and the internal resistance of the battery are jointly estimated and updated online, and the updated average energy conversion efficiency of the electrolyzer and the internal resistance of the battery are fed back to the scheduling layer MPC unit and the control layer MPC unit. 3.The operation control method of the wind-solar-hydrogen storage comprehensive energy system according to claim 1 or 2, characterized in that, The constraints for solving the first optimization problem also include equipment safety boundary constraints and system power balance constraints; wherein, the equipment safety boundary constraints include the SOC safety boundary, SOCH safety boundary, electrolyzer ramp rate, grid switching power limit, and the number of electrolyzer start-ups and shutdowns; the system power balance constraints are: P WT + P PV = P Load + P Bat +P EL + P Grid,ref wherein P WT is the predicted value of the wind power generation, P PV is the predicted value of the photovoltaic power generation, P Load is the predicted value of the power load, P Bat is the controllable power of energy storage, P EL is the controllable power of electrolytic cell, P Grid,ref is the grid interaction power reference value in the coupling reference trajectory. 4.The operation control method of the wind-solar-hydrogen storage comprehensive energy system according to claim 3, characterized in that, The method further includes: If the control command sequence is not feasible, some constraints are relaxed in sequence according to a preset priority; wherein, some constraints include the SOCH safety boundary, the power grid exchange power limit and the electrolyzer ramp rate; the preset priority is set as: SOCH safety boundary > power grid exchange power limit > electrolyzer ramp rate.

5. A wind-solar-hydrogen storage integrated energy system operation control device, characterized in that, The device is embedded with a dual-timescale rolling optimization system, which includes a scheduling layer MPC unit and a control layer MPC unit; the device includes: The prediction unit is used to determine an ultra-short-term power prediction sequence for a specified period of time in the future based on the measured values ​​of wind power generation, photovoltaic power generation, power load, energy storage state of charge and hydrogen storage state of charge collected in real time. The ultra-short-term power prediction sequence includes the predicted values ​​of wind power generation, photovoltaic power generation and power load. The first optimization unit is used to control the scheduling layer MPC unit to operate in a first control cycle, and within each first control cycle, to correct the initial scheduling benchmark according to the ultra-short-term power prediction sequence to obtain the grid interaction power reference value, and to generate a coupled reference trajectory of the energy storage state of charge, the hydrogen storage state of charge, and the grid interaction power reference value in the future time domain; and to construct a first optimization problem with the goal of minimizing the system's full-cycle operating cost, and to solve the first optimization problem to obtain the optimal solution for the energy storage power and the electrolyzer reference power; wherein, the constraints when solving the first optimization problem include the dynamic energy conversion constraints between the electrolyzer reference power and the hydrogen storage state of charge; The second optimization unit is used to control the control layer MPC unit to operate in a second control cycle shorter than the first control cycle, and to receive the coupled reference trajectory as a hard tracking target in each second control cycle, and to construct a second optimization problem with the goal of minimizing the net power tracking error and the control increment, and to solve the second optimization problem to obtain a control command sequence corresponding to the optimal solution of the energy storage power and the reference power of the electrolyzer; wherein, the net power tracking error refers to the difference between the system net power and the grid interaction power reference value in the coupled reference trajectory; An execution unit is configured to, when the control command sequence is feasible, issue the first control command in the control command sequence to the corresponding execution device; Specifically, the dynamic energy conversion constraint is as follows: wherein, represents the state of charge of hydrogen storage at the end of the kth first control period, with a value of 0%~100%; is the electrolyzer reference power solved by the scheduling layer MPC unit, with a unit of kW; is the average energy conversion efficiency of the electrolyzer; is the low heat value of hydrogen; is the hydrogen storage volume; is the sampling period of the scheduling layer MPC unit; is the prediction time domain length. 6.The operation control device of the wind-solar-hydrogen storage comprehensive energy system according to claim 5, characterized in that, The device further includes: The feedback unit is used to obtain the actual operation feedback data of the corresponding execution device after the execution unit issues the first control instruction in the control instruction sequence to the corresponding execution device; The update unit is used to perform online joint estimation and update of the average energy conversion efficiency of the electrolyzer and the internal resistance of the battery based on the actual operation feedback data, and to feed back the updated average energy conversion efficiency of the electrolyzer and the internal resistance of the battery to the scheduling layer MPC unit and the control layer MPC unit. 7.The operation control device of the wind-solar-hydrogen-storage comprehensive energy system according to claim 5, characterized in that, The device further includes a relaxation unit, used to relax some constraints in sequence according to a preset priority when the control command sequence is not feasible; wherein, some constraints include SOCH safety boundary, grid exchange power limit and electrolyzer ramp rate; the preset priority is set as: SOCH safety boundary > grid exchange power limit > electrolyzer ramp rate.

8. An electronic device, comprising: It includes a memory storing executable program code and a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute the operation control method of the wind-solar-hydrogen-storage integrated energy system according to any one of claims 1 to 4.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program causes a computer to execute the operation control method of the integrated wind-solar-hydrogen-storage energy system according to any one of claims 1 to 4.

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