Cost optimization method and equipment for off-grid wind-solar-storage combined hydrogen production, and medium

Abstract

The invention provides a cost optimization method and equipment for off-grid wind-solar-storage combined hydrogen production and a medium, and relates to the technical field of wind-solar-storage combined hydrogen production. The method comprises the following steps: establishing a mathematical model of a subsystem of a wind-solar-storage combined hydrogen production system, subsystems of the wind-solar-storage combined hydrogen production system specifically comprise a wind power generation system, a photovoltaic power generation system, a novel energy storage system, a hydrogen production electrolytic bath system and a hydrogen storage tank system; taking the lowest leveling hydrogen production cost as a target function of the off-grid wind-solar-storage combined hydrogen production cost model; based on the subsystem mathematical model, respectively establishing constraint conditions of an off-grid wind-solar-storage combined hydrogen production cost model from a decision-making layer and an operation layer; and solving the off-grid wind-solar-storage combined hydrogen production cost model by adopting a genetic algorithm to obtain an optimal wind-solar-storage combined hydrogen production system design scheme. According to the technical scheme provided by the invention, a planning design scheme with the lowest leveling hydrogen production cost as a target can be realized.

Description

Technical Field

[0001] This document relates to the technical field of wind, solar and storage combined hydrogen production, and in particular to a cost optimization method, equipment and medium for off-grid wind, solar and storage combined hydrogen production. Background Art

[0002] Wind and photovoltaic power generation are important components of renewable energy, but their generation is volatile and random, posing challenges to the stable operation of power systems. Off-grid wind, solar, and storage combined hydrogen production systems, which can integrate renewable energy and improve energy efficiency, have become a research hotspot.

[0003] Currently, such systems typically employ the following approach: They prioritize wind power or photovoltaic power generation, failing to fully leverage the complementary nature of wind and solar power, leading to unstable energy supply. System capacities (e.g., wind power, photovoltaics, energy storage, electrolyzers) are often set based on experience and lack optimization, resulting in high costs or low efficiency. Fixed operational scheduling rules are unable to adapt to wind and solar fluctuations and load variations, impacting hydrogen production efficiency and energy storage lifespan. Only a portion of investment or operating costs is considered, ignoring key factors such as energy storage losses and electrolyzer startup and shutdown, leading to inaccurate cost calculations.

[0004] Existing technologies suffer from the following shortcomings: Significant wind and solar power curtailment and low renewable energy utilization. Irrational system configuration and scheduling strategies lead to high hydrogen production costs. Dynamic response to energy supply and demand fluctuations is difficult, resulting in weak collaborative optimization capabilities. Constraints such as energy storage lifespan and electrolyzer start-up and shutdown are ignored, resulting in optimization results that are inconsistent with actual operations. Summary of the Invention

[0005] The present invention provides a cost optimization method, equipment and medium for off-grid wind-solar-storage combined hydrogen production, aiming to solve the above-mentioned problems.

[0006] According to an embodiment of the present invention, a cost optimization method for off-grid wind-solar-storage combined hydrogen production is provided, comprising:

[0007] Establishing a mathematical model of the subsystems of a wind-solar-storage combined hydrogen production system, wherein the subsystems of the wind-solar-storage combined hydrogen production system specifically include: a wind power generation system, a photovoltaic power generation system, a new energy storage system, a hydrogen production electrolyzer system, and a hydrogen storage tank system;

[0008] The objective function of the off-grid wind-solar-storage combined hydrogen production cost model is to minimize the levelized hydrogen production cost.

[0009] Based on the mathematical model of the subsystem, the constraints of the off-grid wind-solar-storage combined hydrogen production cost model are established from the decision-making level and the operation level respectively;

[0010] A genetic algorithm is used to solve the off-grid wind-solar-storage combined hydrogen production cost model to obtain the optimal wind-solar-storage combined hydrogen production system design scheme.

[0011] According to an embodiment of the present invention, there is provided an electronic device, including:

[0012] processor; and,

[0013] A memory arranged to store computer-executable instructions, which, when executed, cause the processor to perform the steps of the above-mentioned cost optimization method for off-grid wind-solar-storage combined hydrogen production.

[0014] According to an embodiment of the present invention, a storage medium is provided for storing computer-executable instructions, which, when executed, implement the steps of the above-mentioned cost optimization method for off-grid wind-solar-storage combined hydrogen production.

[0015] By adopting the embodiments of the present invention, the capacity configuration and operation strategy of the wind, solar and storage combined system are optimized, and the levelized hydrogen production cost is significantly reduced, thereby improving economic efficiency. Taking into account the life attenuation of the energy storage system and the start-up and shutdown losses of the electrolyzer, the operation mode is optimized, equipment losses are reduced, and the service life of key components is extended. A more comprehensive mathematical model is established, covering constraints such as wind and solar power generation, energy storage charging and discharging, and electrolyzer load response, so that the optimization results are more in line with actual operational needs. It provides data support for project investment and planning, helps to formulate more reasonable wind, solar and hydrogen storage system design plans, and promotes the large-scale application of clean energy hydrogen production. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate one or more embodiments of this specification 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 only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 This is a flow chart of a cost optimization method for off-grid wind-solar-storage combined hydrogen production according to an embodiment of the present invention;

[0018] Figure 2 This is a framework diagram of an off-grid wind-solar-storage combined hydrogen production system according to an embodiment of the present invention;

[0019] Figure 3 This is a hierarchical architecture diagram of the cost optimization method for off-grid wind-solar-storage combined hydrogen production according to an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below in conjunction with the drawings in one or more embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this document.

[0021] Method Example

[0022] According to an embodiment of the present invention, a cost optimization method for off-grid wind-solar-storage combined hydrogen production is provided. Figure 1 This is a flow chart of the cost optimization method for off-grid wind-solar-storage combined hydrogen production according to an embodiment of the present invention. Figure 1 As shown, the cost optimization method for off-grid wind-solar-storage combined hydrogen production according to an embodiment of the present invention specifically includes:

[0023] S1. Establish a mathematical model of the subsystems of the wind-solar-storage combined hydrogen production system, wherein the subsystems of the wind-solar-storage combined hydrogen production system specifically include: a wind power generation system, a photovoltaic power generation system, a new energy storage system, a hydrogen production electrolyzer system, and a hydrogen storage tank system;

[0024] like Figure 2 As shown in the figure, by establishing mathematical models for each system, including the energy supply model of wind and photovoltaic power generation, the electrochemical energy storage charging and discharging model, the load response model of the hydrogen production electrolyzer, etc., starting from the problems faced by the decision-making and operation levels, comprehensive consideration is given, the operational response and logical relationship between wind, light, and storage combined hydrogen production are explored, and the energy scheduling strategy of wind, light, and storage combined hydrogen production is studied to improve the energy rate, reduce the amount of power wasted, and improve the overall economic benefits of the system.

[0025] Wind power generation system: Wind power generation is a system that converts wind kinetic energy into electrical energy. A wind power generation system primarily consists of a rotor, drive system, generator, control system, tower, and foundation. The rotor captures wind energy and converts it into mechanical energy, which is then transferred to the generator via the drive system. The control system ensures stable operation. The tower supports the rotor and generator, and the foundation secures the tower. Wind power generation is significantly affected by variations in wind speed and exhibits high volatility and randomness.

[0026] Photovoltaic power generation system: Photovoltaic power generation uses the photovoltaic effect at the interface of semiconductors to directly convert sunlight into electrical energy. A photovoltaic power generation system primarily consists of three components: solar panels, a controller, and an inverter. However, photovoltaic power generation is primarily affected by sunlight and cannot generate electricity at night.

[0027] New energy storage systems: New energy storage refers to energy storage technologies that primarily output electricity, in addition to pumped hydro storage. These technologies include lithium-ion batteries, compressed air, lead-carbon (acid) batteries, and flow batteries. my country's new energy storage systems are experiencing rapid development, with diverse forms and unique characteristics, and are trending towards centralized, large-scale systems.

[0028] Hydrogen electrolyzer systems: Hydrogen electrolyzers produce hydrogen by electrolyzing water. They primarily consist of anode and cathode chambers, with oxygen generated in the anode and hydrogen in the cathode. Depending on the electrolyte type and technology used, hydrogen electrolyzers primarily include alkaline electrolyzers, proton exchange membrane electrolyzers, and solid oxide electrolyzers. Alkaline electrolyzers, with their advantages such as high, stable hydrogen production rates and long lifespan, are suitable for large-scale hydrogen production and are currently one of the most mature and economical hydrogen production methods.

[0029] Hydrogen storage tank system: Hydrogen storage tanks are equipment used to store hydrogen and play a key role in the production, transportation, storage and application of hydrogen energy.

[0030] S2. The objective function of the off-grid wind-solar-storage combined hydrogen production cost model is to minimize the levelized hydrogen production cost.

[0031] Specifically include:

[0032] Taking into account the construction investment and operating costs of wind, solar, storage, and hydrogen, the maximum wind and solar installed capacity allowed in the current region or project is used as a constraint, and the lowest unit hydrogen production cost is set as the optimization goal. The formula for unit hydrogen production cost is: unit hydrogen production cost = investment / hydrogen output = (construction investment + operating cost) / hydrogen output;

[0033] From the decision-making level, the variables to be optimized include wind power installed capacity, photovoltaic installed capacity, the number of hydrogen electrolyzers installed, and the power and discharge hours of the energy storage system:

[0034]

[0035] in: is the installed capacity of wind power,

[0036] is the installed capacity of photovoltaic power generation,

[0037] is the number of installed electrolytic cells, which must be a positive integer;

[0038] is the power of the energy storage battery;

[0039] It is the discharge hours of the energy storage battery, usually 1h or 2h.

[0040] From an operational perspective, the variables to be optimized include the number of electrolyzers started or stopped at the beginning of the nth hour:

[0041] in: The number of electrolytic cells started at the beginning of the nth period; is the number of electrolytic cells stopped at the beginning of the nth hour period.

[0042] S3. Based on the mathematical model of the subsystem, establish the constraint conditions of the off-grid wind-solar-storage combined hydrogen production cost model from the decision-making level and the operation level respectively;

[0043] S3 specifically includes: by establishing mathematical models for each system, including energy supply models for wind and photovoltaic power generation, electrochemical energy storage charging and discharging models, and load response models for hydrogen electrolyzers, etc., starting from the problems faced by the decision-making and operation levels, comprehensively considering the operational responses and logical relationships between wind, solar, and storage combined hydrogen production, and studying the energy scheduling strategy of wind, solar, and storage combined hydrogen production to improve energy efficiency, reduce power curtailment, and improve the overall economic benefits of the system, such as Figure 3 This is a hierarchical architecture diagram of the cost optimization method for off-grid wind-solar-storage combined hydrogen production according to an embodiment of the present invention.

[0044] The constraints of the wind-solar-storage combined hydrogen production system include: cost constraint function, wind-solar power generation constraint function, energy storage system constraint function and hydrogen production load response constraint function;

[0045] The cost constraint function includes:

[0046] Construction investment cost, calculated as follows: Construction investment cost = construction investment cost per unit installed capacity × installed capacity;

[0047] Variable operating costs are calculated as follows: variable operating costs = variable cost per unit of output × output.

[0048]

[0049] in: are the variable operating costs per unit of wind and solar power generation, are the variable operating costs of wind and solar power generation in the nth hour respectively.

[0050] The wind and solar power generation constraint function includes:

[0051] Maximum power generation capacity constraint, calculated as follows: Maximum power generation capacity = power generated per unit installed capacity × installed capacity scale;

[0052]

[0053] in, are the unit installed power generation;

[0054] in, are the maximum power generation capacity of wind and solar power in the nth hour respectively.

[0055] The power consumption constraint is calculated as follows: power consumption = maximum power generation capacity - power curtailment.

[0056]

[0057] in: are the amount of curtailed wind and solar power generation in the nth hour respectively; They are the electricity consumption delivered by wind and solar power generation in the nth hour respectively.

[0058] The energy storage system constraint function includes:

[0059] Maximum discharge depth limit, the constraint condition is that the maximum discharge depth of the energy storage battery reaches 95%;

[0060]

[0061] in: The maximum discharge depth of the energy storage battery can be 95%; It is the minimum storage capacity of the energy storage battery.

[0062] The charge and discharge process constraints are calculated as follows: energy storage capacity at the end of the n-th hour = energy storage capacity at the beginning of the n-th hour + energy storage charging capacity at the n-th hour - energy storage discharging capacity at the n-th hour × comprehensive charge and discharge efficiency of the energy storage device;

[0063]

[0064] in: are the energy storage charge and discharge capacity in the nth hour respectively; are the energy storage capacity at the beginning and end of the nth period respectively; The comprehensive efficiency of charge and discharge of the energy storage device can be taken as 80%.

[0065] The hydrogen production load response constraint function satisfies: the number of electrolyzers started in the nth hour is less than the number of electrolyzers that are not currently in operation.

[0066] Specifically include: is the number of electrolytic cells started at the beginning of the nth period, is the electricity consumption of the electrolyzer in the nth hour. The constraint function of the hydrogen production electrolyzer load must meet the following requirements: the number of electrolyzers started in the nth hour is less than the number of electrolyzers that are not currently in operation; taking the electrolyzer startup time of 2 hours as an example, the electricity consumption in the next 2 hours must meet the startup time of the electrolyzer; and at the same time, the energy conservation between the source and the load must be met.

[0067]

[0068] S4. Use a genetic algorithm to solve the off-grid wind-solar-storage combined hydrogen production cost model to obtain the optimal wind-solar-storage combined hydrogen production system design solution.

[0069] By modeling the constraint functions of each system and the logical relationship between system scheduling and operation, and using algorithmic models such as genetic algorithms to optimize costs, we can eventually obtain a planning and design scheme with the lowest levelized hydrogen production cost for the system, providing data support for the project's investment decisions.

[0070] Device Example 1

[0071] According to an embodiment of the present invention, there is provided an electronic device, including:

[0072] processor; and,

[0073] A memory arranged to store computer executable instructions which, when executed, cause the processor to perform the steps of the above method embodiments.

[0074] Device Example 2

[0075] A storage medium is used to store computer-executable instructions, which implement the steps of the above method embodiment when executed.

[0076] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A cost optimization method for off-grid wind-solar-storage combined hydrogen production, characterized in that include: Establishing a mathematical model of the subsystems of a wind-solar-storage combined hydrogen production system, wherein the subsystems of the wind-solar-storage combined hydrogen production system specifically include: a wind power generation system, a photovoltaic power generation system, a new energy storage system, a hydrogen production electrolyzer system, and a hydrogen storage tank system; The objective function of the off-grid wind-solar-storage combined hydrogen production cost model is to minimize the levelized hydrogen production cost. Based on the mathematical model of the subsystem, the constraints of the off-grid wind-solar-storage combined hydrogen production cost model are established from the decision-making level and the operation level respectively; A genetic algorithm is used to solve the off-grid wind-solar-storage combined hydrogen production cost model to obtain the optimal wind-solar-storage combined hydrogen production system design scheme.

2. The method according to claim 1, characterized in that The constraints of the wind-solar-storage combined hydrogen production system include: a cost constraint function, a wind-solar power generation constraint function, an energy storage system constraint function, and a hydrogen production load response constraint function.

3. The method according to claim 1, characterized in that The optimization variables of the decision layer include: Wind power installed capacity and photovoltaic installed capacity; The number of installed hydrogen production electrolyzers; The power and discharge hours of the energy storage system; The optimization variables must meet the boundary condition constraints of the maximum allowable development of wind power installed capacity and photovoltaic installed capacity in the region.

4. The method according to claim 1, wherein The optimization variables of the operation layer include: The number of electrolytic cells started and stopped at the beginning of the nth hour period; The charge and discharge capacity of the energy storage system in the nth hour; The delivered and abandoned electricity of wind / solar power generation in the nth hour; The optimization variables must satisfy the hydrogen production load response constraints and the energy storage system charge and discharge constraints to achieve a real-time balance between generation, storage, and use.

5. The method according to claim 2, characterized in that The cost constraint function includes: Construction investment cost, calculated as follows: Construction investment cost = construction investment cost per unit installed capacity × installed capacity; Variable operating costs are calculated as follows: variable operating costs = variable cost per unit of output × output.

6. The method according to claim 2, characterized in that The wind and solar power generation constraint function includes: Maximum power generation capacity constraint, calculated as follows: Maximum power generation capacity = power generated per unit installed capacity × installed capacity scale; The power consumption constraint is calculated as follows: power consumption = maximum power generation capacity - power curtailment.

7. The method according to claim 2, characterized in that The energy storage system constraint function includes: Maximum discharge depth limit, the constraint condition is that the maximum discharge depth of the energy storage battery reaches 95%; The charging and discharging process constraints are calculated as follows: the energy storage capacity at the end of the n-th hour = the energy storage capacity at the beginning of the n-th hour + the energy storage charging capacity at the n-th hour - the energy storage discharging capacity at the n-th hour × the comprehensive charging and discharging efficiency of the energy storage device.

8. The method according to claim 3, characterized in that The hydrogen production load response constraint function satisfies: the number of electrolyzers started in the nth hour is less than the number of electrolyzers that are not currently in operation.

9. An electronic device comprising: processor; as well as, A memory arranged to store computer-executable instructions, which, when executed, cause the processor to perform the steps of the cost optimization method for off-grid wind-solar-storage combined hydrogen production as described in any one of claims 1 to 8.

10. A storage medium for storing computer-executable instructions, which, when executed, implement the steps of the cost optimization method for off-grid wind-solar-storage combined hydrogen production as described in any one of claims 1 to 8.

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