Wind-solar hydrogen production optimization scheduling method and device based on hydrogen-carbon ratio and computer equipment

Abstract

The invention relates to a wind-solar hydrogen production optimization scheduling method and device based on a hydrogen-carbon ratio and computer equipment. The method comprises the following steps: acquiring a wind-light predicted value and a green hydrogen predicted value in the wind-light hydrogen production optimization scheduling method based on the hydrogen-carbon ratio; performing difference value calculation according to the wind and light predicted value and the green hydrogen predicted value to obtain a power difference value; acquiring the energy state of the energy storage system; according to the power difference value and the energy state, adjusting the charging and discharging operation of the energy storage system; and according to the power difference value and the charging and discharging operation, performing network access operation. By adopting the method, the fluctuation of wind and light power generation can be combined with the hydrogen demand, and through the intelligent scheduling of the energy storage system, the wind and light abandoning phenomenon is effectively reduced, the system operation efficiency is effectively improved, the maximum utilization of renewable energy sources is realized, and the defects of poor matching between the hydrogen yield and the demand, poor scheduling flexibility and the like in the prior art are overcome.

Description

Technical Field

[0001] The present application relates to the technical field of wind-solar hydrogen production, and particularly to an optimized scheduling method, device and computer equipment for wind-solar hydrogen production based on the hydrogen-carbon ratio. Background Art

[0002] With the advancement of the global energy transition, hydrogen energy has gradually become an important part of the energy system. Using renewable energy (such as wind power and photovoltaic power generation) to produce hydrogen is an environmentally friendly and low-carbon hydrogen production method. However, wind power and photovoltaic power generation are volatile and intermittent, which brings challenges to the scheduling of the hydrogen production process. In addition, the industrial production has certain proportional requirements for the demand of hydrogen and carbon-based raw materials, and the hydrogen-carbon ratio has a decisive impact on chemical processes such as syngas production and methanol production. How to optimize the hydrogen production process of wind-solar power under the premise of meeting the hydrogen-carbon ratio is one of the difficulties in the current technological development.

[0003] The existing wind-solar hydrogen production technologies usually adopt a strategy based on single-power scheduling, that is, the start-stop and power adjustment of the electrolyzer are directly determined by the power output of wind power and photovoltaic power generation. However, this scheduling method fails to dynamically adjust according to the hydrogen demand at the industrial end, which easily leads to overproduction or insufficient supply of hydrogen, thereby reducing the overall operating efficiency of the system. In addition, the management strategy of the hydrogen storage system in the existing technology is relatively simple, and it is difficult to effectively cope with the volatility of wind power and photovoltaic power generation, resulting in frequent curtailment of wind and light. At the same time, the volatility of hydrogen demand is not fully considered, which limits the flexibility and economy of the system.

[0004] There is also a major problem with the existing scheduling technologies, that is, they fail to fully combine the dynamic characteristics of wind-solar power generation with the demand for the hydrogen-carbon ratio in industrial production, resulting in a mismatch between the output of green hydrogen and the actual production demand, affecting the optimized scheduling effect and economy of the entire system. Summary of the Invention

[0005] Based on this, in view of the above technical problems, it is necessary to provide an optimized scheduling method, device, computer equipment, computer-readable storage medium and computer program product for wind-solar hydrogen production based on the hydrogen-carbon ratio that can dynamically adjust the electrolyzer.

[0006] In a first aspect, the present application provides an optimized scheduling method for wind-solar hydrogen production based on the hydrogen-carbon ratio. The method includes:

[0007] Obtain wind-solar prediction data and green hydrogen prediction data;

[0008] Perform difference calculation according to the wind-solar prediction data and the green hydrogen prediction data to obtain a power difference;

[0009] Obtain the energy storage state of the energy storage system;

[0010] Adjust the charge and discharge operations of the energy storage system according to the power difference and the energy storage state;

[0011] Perform grid connection and disconnection operations according to the power difference and the charge and discharge operations.

[0012] In one embodiment, detect whether the power difference is greater than a power threshold;

[0013] If the power difference is greater than the power threshold, charge the energy storage system;

[0014] If the power difference is less than or equal to the power threshold, discharge the energy storage system.

[0015] In one embodiment, detect whether the energy storage state is greater than an energy storage range;

[0016] If the energy storage state is greater than the energy storage range, prohibit the energy storage system from charging;

[0017] If the energy storage state is less than the energy storage range, prohibit the energy storage system from discharging.

[0018] In one embodiment, if the power difference is greater than the power threshold and the energy storage system is prohibited from charging, perform a grid connection plan;

[0019] If the power difference is less than the power threshold and the energy storage system is prohibited from discharging, perform a grid disconnection plan.

[0020] In one embodiment, detect whether the power difference is less than a grid connection threshold;

[0021] If the power difference is less than the grid connection threshold, perform a grid connection plan;

[0022] If the power difference is greater than or equal to the grid connection threshold, perform a wind curtailment plan and / or a PV curtailment plan.

[0023] In one embodiment, detect whether the power difference is less than a grid disconnection threshold;

[0024] If the power difference is less than the grid disconnection threshold, perform a grid disconnection plan;

[0025] If the power difference is greater than or equal to the grid disconnection threshold, perform a plan to shut down the electrolyzer.

[0026] In a second aspect, the present application also provides an optimized scheduling device for hydrogen production from wind and solar based on the hydrogen-carbon ratio. The device includes:

[0027] A prediction data module for obtaining wind and solar prediction data and green hydrogen prediction data;

[0028] A difference calculation module, configured to perform difference calculation based on the wind and light prediction data and the green hydrogen prediction data to obtain a power difference;

[0029] An energy storage state module, configured to obtain the energy storage state of the energy storage system;

[0030] A charge and discharge module, configured to adjust the charge and discharge operations of the energy storage system according to the power difference and the energy storage state;

[0031] An on-grid and off-grid module, configured to perform on-grid and off-grid operations according to the power difference and the charge and discharge operations.

[0032] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0033] Obtain the wind and light prediction values and the green hydrogen prediction values;

[0034] Perform difference calculation based on the wind and light prediction values and the green hydrogen prediction values to obtain a power difference;

[0035] Obtain the energy state of the energy storage system;

[0036] Adjust the charge and discharge operations of the energy storage system according to the power difference and the energy state;

[0037] Perform on-grid and off-grid operations according to the power difference and the charge and discharge operations.

[0038] In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0039] Obtain the wind and light prediction values and the green hydrogen prediction values;

[0040] Perform difference calculation based on the wind and light prediction values and the green hydrogen prediction values to obtain a power difference;

[0041] Obtain the energy state of the energy storage system;

[0042] Adjust the charge and discharge operations of the energy storage system according to the power difference and the energy state;

[0043] Perform on-grid and off-grid operations according to the power difference and the charge and discharge operations.

[0044] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0045] Obtain the wind-solar power prediction value and the green hydrogen prediction value;

[0046] Perform a difference calculation based on the wind-solar power prediction value and the green hydrogen prediction value to obtain a power difference;

[0047] Obtain the energy state of the energy storage system;

[0048] Adjust the charge and discharge operations of the energy storage system according to the power difference and the energy state;

[0049] Perform grid connection and disconnection operations according to the power difference and the charge and discharge operations.

[0050] The above-mentioned wind-solar hydrogen production optimization scheduling method, device and computer equipment based on the hydrogen-carbon ratio obtain the wind-solar power prediction value and the green hydrogen prediction value; perform a difference calculation based on the wind-solar power prediction value and the green hydrogen prediction value to obtain a power difference; obtain the energy state of the energy storage system; adjust the charge and discharge operations of the energy storage system according to the power difference and the energy state; perform grid connection and disconnection operations according to the power difference and the charge and discharge operations. Using this method can combine the fluctuations of wind-solar power generation with hydrogen demand, and through the intelligent scheduling of the energy storage system, effectively reduce the phenomenon of wind and light abandonment, effectively improve the system operation efficiency, maximize the utilization of renewable energy, and overcome the deficiencies of the existing technology in aspects such as poor matching between hydrogen production and demand and poor scheduling flexibility. Brief Description of the Drawings

[0051] Figure 1 It is an application environment diagram of the wind-solar hydrogen production optimization scheduling method based on the hydrogen-carbon ratio in an embodiment;

[0052] Figure 2 It is a flowchart of the wind-solar hydrogen production optimization scheduling method based on the hydrogen-carbon ratio in an embodiment;

[0053] Figure 3 It is a structural block diagram of the wind-solar hydrogen production optimization scheduling device based on the hydrogen-carbon ratio in an embodiment;

[0054] Figure 4 It is an internal structure diagram of a computer device in an embodiment. Detailed Embodiments

[0055] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0056] The wind-solar hydrogen production optimization scheduling method based on the hydrogen-carbon ratio provided by the embodiments of the present application can be applied as Figure 1In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or can be placed on the cloud or other network servers. Among them, the terminal 102 can be, but is not limited to, various personal computers, laptop computers, smart phones, tablet computers, Internet of Things devices, and portable wearable devices. The Internet of Things devices can be instrument meters, sensor devices, etc. The portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The server 104 can be implemented by an independent server or a server cluster composed of multiple servers.

[0057] In one embodiment, as Figure 2 shown, a method for optimizing the scheduling of hydrogen production from wind and solar based on the hydrogen-carbon ratio is provided. Taking the server 104 in Figure 1 as an example, the method includes the following steps:

[0058] Step 202, obtain the wind and solar prediction values and the green hydrogen prediction value.

[0059] Specifically, obtain the wind and solar prediction values through a wind and solar power prediction device. Obtain the power demand of the electrolyzer by calculating the hydrogen demand, that is, the green hydrogen prediction value.

[0060] In one embodiment, through the wind and solar power prediction device, obtain the 24-hour power prediction curves of wind power and light power, respectively obtain the power values at 96 time points, with an interval of 15 minutes for each time point. Then, superimpose the two to obtain the total power prediction curve. Finally, perform fitting processing on the total power curve to obtain a smoother and more stable total power prediction curve.

[0061] Through the wind and solar power prediction device, respectively obtain the wind power prediction curve P wind (t) and the light power prediction curve P solar (t), where t represents the time point, and the value range is t = 1, 2, 3, 4,..., 96 corresponding to the power prediction values every 15 minutes within 24 hours.

[0062] P wind (t): represents the predicted power generation value of the wind power system at time t, with the unit of kW.

[0063] P solar (t): represents the predicted power generation value of the photovoltaic system at time t, with the unit of kw.

[0064] Superimpose the wind power generation and photovoltaic power generation curves to obtain the total power prediction curve. In this way, at each time point t, the wind and solar prediction value P total (t) is the sum of the wind power and the light power:

[0065] P total (t) = P wind (t) + P solar (t)

[0066] P total (t): The predicted value of wind and light at time t, with the unit of kW.

[0067] In practical applications, there may be noise or fluctuations in the wind power and light power curves. The superimposed curve can be smoothed, and the polynomial fitting method can be used to obtain the smoothed total power prediction curve.

[0068] Assume that the fitted polynomial is a cubic polynomial:

[0069] P total，fit (t) = a 0 + a 1 t + a 2 t 2 + a 3 t 3

[0070] By fitting the parameters a 0 , a 1 , a 2 , a 3 , the smoothed total power prediction curve is obtained.

[0071] P total，fit (t): The predicted value of wind and light at time t after fitting, with the unit of kW.

[0072] In this embodiment, the time range is 24 hours, with 96 time points, and the interval between each time point is 15 minutes. The total power prediction output is:

[0073]

[0074] By obtaining the real-time demand of the carbon-based material flow rate and the hydrogen-carbon ratio in the industrial production process, dynamically calculating the hydrogen demand, and converting it into the power demand of the electrolyzer, the green hydrogen prediction value is obtained.

[0075] According to the process end demand planning and the combination of the carbon-based material flow rate and the hydrogen-carbon ratio calculation, the hydrogen demand can be obtained.

[0076] Hydrogen demand formula:

[0077]

[0078] Where: n H2 (t) is the hydrogen demand flow rate at time t (mol / h); R H / C (t) is the hydrogen-carbon ratio at time t (varying according to the reaction process setting); n C(t) is the flow rate of carbon-based substances at time t (mol / h).

[0079] Based on the prediction of the hydrogen-carbon ratio and the flow rate of carbon-based substances, the predicted values of hydrogen demand corresponding to 96 time points within 24 hours are obtained:

[0080]

[0081] The core of the hydrogen production process is to convert electrical energy into hydrogen through an electrolyzer. The hydrogen-electricity ratio (also known as the electrolysis efficiency) represents how many moles of hydrogen can be produced per 1 kWh of electrical energy consumed.

[0082] The formula for the hydrogen-electricity ratio:

[0083]

[0084] Where: P(t) is the power required by the electrolyzer at time t (kW); is the hydrogen demand flow rate at time t (mol / h); H / T is the hydrogen-electricity ratio of the electrolyzer, usually a fixed value, representing the electrical energy required to produce 1 mol of hydrogen (kWh / mol).

[0085] Convert the predicted hydrogen demand curves at each time point within the time range to obtain the predicted value of green hydrogen. In this embodiment, the time range is 24 hours, with 96 time points, and each time point is spaced 15 minutes apart. The predicted line of hydrogen production power is:

[0086] P = [P(1), P(2), P(3), P(4),..., P(96)]

[0087] Step 204, calculate the difference according to the predicted value of wind and light and the predicted value of green hydrogen to obtain the power difference.

[0088] Specifically, by calculating the difference between the predicted value of wind and light and the predicted value of green hydrogen, the power balance between wind and light power generation and hydrogen production demand is determined. By calculating the power difference in real time, the flow of energy is dynamically adjusted to ensure that while meeting the hydrogen production demand, renewable energy is maximally utilized and economic benefits are optimized.

[0089] In one embodiment, for each time point t (t = 1, 2, 3, 4,..., 96), calculate the difference ΔP(t), and the formula is:

[0090] ΔP(t) = P total，fit (t) - P(t)

[0091] Where: the power difference ΔP(t) is the difference between the predicted value of wind and light P total，fit (t) and the predicted value of green hydrogen P(t).

[0092] Calculate the difference sequence ΔP(t) of 96 time points, that is:

[0093] ΔP = [ΔP(1), ΔP(2), ΔP(3), ΔP(4),..., ΔP(96)]

[0094] The adjusting the charge and discharge operations of the energy storage system according to the power difference includes: detecting whether the power difference is greater than a power threshold; if the power difference is greater than the power threshold, charging the energy storage system; if the power difference is less than or equal to the power threshold, discharging the energy storage system.

[0095] In one embodiment, when ΔP(t)>0: it means that the predicted value of wind and light is greater than the predicted value of green hydrogen, and there is excess power, and the energy storage system can be charged.

[0096] When ΔP(t)<0: it means that the predicted value of wind and light is less than the predicted value of green hydrogen, there is a power gap, and power needs to be released from the energy storage system or purchased from the grid to supplement the consumption of the electrolyzer.

[0097] When ΔP(t)=0: it means that the predicted value of wind and light is equal to the predicted value of green hydrogen, and there is no need to dispatch the energy storage or perform grid connection and disconnection operations.

[0098] Step 206, obtain the energy state of the energy storage system.

[0099] Specifically, read the current power of the energy storage system to obtain the energy state.

[0100] In one embodiment, the energy state E(t) of the energy storage system at each time point. The energy state of the energy storage system will be dynamically adjusted over time according to the charging and discharging behaviors.

[0101] The energy state formula of the energy storage system is:

[0102]

[0103] Among them, E(t + 1) is the energy state at time t + 1; E(t) is the energy state at time t; P charge (t) is the charging power at time t; P discharge (t) is the discharging power at time t; η charge is the charging efficiency of the energy storage system; η discharge is the discharging efficiency of the energy storage system; Δt is the time interval (hours).

[0104] Step 208, adjust the charge and discharge operations of the energy storage system according to the power difference and the energy state.

[0105] Specifically, it is detected whether the energy state is greater than the energy storage range; if the energy state is greater than the energy storage range, charging of the energy storage system is prohibited; if the energy state is less than the energy storage range, discharging of the energy storage system is prohibited.

[0106] In one embodiment, the energy storage system is used to balance the fluctuations of wind and solar power generation. When the predicted value of wind and solar power is greater than the predicted value of green hydrogen, the excess power is stored in the energy storage device; when the predicted value of wind and solar power is less than the predicted value of green hydrogen, the energy storage system releases the stored energy to make up for the power gap.

[0107] When the predicted value of wind and solar power is greater than the predicted value of green hydrogen, that is, ΔP(t)>0, the energy storage system starts to charge. The charging power of the energy storage system should be limited by the system capacity and the charging rate. The charging power of the energy storage system can be expressed by the following formula:

[0108]

[0109] where ΔP(t) is the excess power at the current time t; is the maximum charging power of the energy storage system; E max is the maximum capacity (kWh) of the energy storage system; E(t) is the state of the energy storage system at time t (i.e., the currently stored energy) kWh; η charge is the charging efficiency of the energy storage system; Δt is the time interval (hours), for a 15-minute time step, Δt = 0.25 hours.

[0110] When the predicted value of wind and solar power is less than the predicted value of green hydrogen, that is, ΔP(t)<0, the energy storage system starts to discharge. The discharging power is limited by the currently stored capacity of the energy storage system, the maximum discharging power and the discharging efficiency. The discharging power of the energy storage system can be expressed by the following formula:

[0111]

[0112] where -ΔP(t) is the power gap at the current time t; is the maximum discharging power of the energy storage system; E(t) is the currently stored energy (kWh) of the energy storage system; η discharge is the discharging efficiency of the energy storage system; Δt is the time interval (hours), for a 15-minute time step, Δt = 0.25 hours.

[0113] To implement the optimal scheduling model for wind and solar hydrogen production based on the hydrogen-carbon ratio, the constraint conditions of various physical devices and systems need to be considered. The following is a detailed list of constraint conditions:

[0114] Step 210, perform grid connection and disconnection operations according to the power difference and the charge and discharge operations.

[0115] Specifically, if the power difference is greater than the power threshold and charging of the energy storage system is prohibited, a grid connection plan is carried out; if the power difference is less than the power threshold and discharging of the energy storage system is prohibited, a grid disconnection plan is carried out.

[0116] More specifically, it is detected whether the power difference is less than the power purchase threshold; if the power difference is less than the power purchase threshold, a grid disconnection plan is carried out; if the power difference is greater than or equal to the power purchase threshold, an electrolyzer shutdown plan is carried out.

[0117] In one embodiment, the grid disconnection plan refers to the operation of purchasing electricity from the grid. When there is a gap in the power generation power, electricity can be purchased from the grid, and the power purchase is limited by the maximum power supply capacity of the grid:

[0118]

[0119] where P grid_down (t) is the power purchased from the grid at time t; is the maximum power supply of the grid.

[0120] Adjust the electrolyzer according to the power difference ΔP(t). The power output P ele (t) of the electrolyzer can be adjusted through the following logic:

[0121]

[0122] where P ele (t) is the actual power output (kW) of the electrolyzer at time t; is the maximum power output limit (kW) of the electrolyzer; ΔP(t) is the difference (kW) between the predicted value of wind and light and the predicted value of green hydrogen at time t.

[0123] More specifically, it is detected whether the power difference is less than the power supply threshold; if the power difference is less than the power supply threshold, a grid connection plan is carried out; if the power difference is greater than or equal to the power supply threshold, a wind abandonment plan and / or a light abandonment plan is carried out.

[0124] In one embodiment, the grid connection plan refers to sending the excess power into the grid. The excess power can be sold to the grid through grid connection, and the power is limited by the maximum grid connection power of the grid.

[0125]

[0126] where P grid_up (t) is the grid connection power at time t; is the maximum grid connection power of the grid.

[0127] When the power difference is greater than or equal to the power supply threshold, a wind abandonment plan and / or a light abandonment plan needs to be executed.

[0128] By calculating the curtailment power, reasonably dispatching energy storage devices, the power of power grid connection and disconnection, and the start and stop of electrolyzers, the curtailment amount of renewable energy is minimized as much as possible.

[0129] Curtailment power calculation, curtailment power P abandon (t) refers to the predicted value of wind and light at the current time t, P total (t)), which is the part that is not utilized and wasted. The formula is as follows:

[0130] P abandon (t) = max(0, P total (t) - P ele (t) - P charge (t) - P grid_up (t))

[0131] Among them, P total (t) is the predicted value of wind and light; P ele (t) is the actual power output (kW) of the electrolyzer at time t; P charge (t) is the charging efficiency of the energy storage system; P grid_up (t) is the power of power grid connection, that is, the part of the excess power sold through the power grid.

[0132] The calculation formula of the curtailment rate objective function is as follows:

[0133]

[0134] This objective function represents the ratio of the curtailment amount to the total power generation in the next 24 hours (96 time points). The optimization objective is to make this ratio as close to 0 as possible, so as to maximize the utilization of wind and light power generation.

[0135] In one embodiment, in order to implement the optimization dispatch model of wind and light hydrogen production based on the hydrogen-carbon ratio, the constraint conditions of various physical devices and systems need to be considered. The following is a detailed list of constraint conditions:

[0136] 1) Energy storage system constraint conditions

[0137] The charge and discharge operations of the energy storage system are restricted by various constraint conditions:

[0138] ① Energy storage capacity constraint: The energy state E(t) of the energy storage system must always be kept within its capacity range:

[0139] E min ≤ E(t) ≤ E max

[0140] Among them, E min is the minimum available capacity of the energy storage system; E maxis the maximum capacity of the energy storage system, representing the maximum storable energy (kWh) of the energy storage system.

[0141] ② Energy storage charging power constraint: The charging power is limited by the charging capacity of the system and the current energy storage capacity:

[0142]

[0143] ③ Energy storage discharging power constraint: The discharging power is limited by the discharging capacity of the system and the current energy storage capacity:

[0144]

[0145] ④ Charging and discharging operation mutual exclusion constraint: The energy storage system is not allowed to perform charging and discharging operations simultaneously at the same time:

[0146] P charge (t)·P discharge (t) = 0

[0147] 2) Electrolyzer power constraint

[0148] The operation of the electrolyzer is restricted by the maximum and minimum power outputs of its physical equipment.

[0149] ① Electrolyzer power upper and lower limits: The actual power output of the electrolyzer must be between its maximum and minimum powers:

[0150]

[0151] Among them, P ele (t) is the power output (kW) of the electrolyzer at time t; are the minimum and maximum powers of the electrolyzer.

[0152] ② Electrolyzer start-stop constraint: The electrolyzer cannot be started and stopped frequently, and its start-stop times are restricted by the durability of the process equipment and the start-stop time. Therefore, the start-stop time of the electrolyzer should be greater than a certain threshold T min :

[0153] T on ≥ T min , T off ≥ T min

[0154] Among them, T on is the continuous working time of the electrolyzer; T off is the continuous shutdown time of the electrolyzer; T min is the minimum time between the start and stop of the electrolyzer.

[0155] ③ Electrolyzer load regulation rate constraint

[0156] The load regulation rate (Ramp Rate) of the electrolyzer defines the rate of conversion between different operating states of the electrolyzer. This parameter is crucial because it determines how quickly the electrolyzer can adjust the hydrogen production power.

[0157] Load regulation rate limit: The ramp-up rate and ramp-down rate are subject to physical and safety limitations:

[0158]

[0159] RR min ≤RR≤RR max

[0160] where RR is the actual load regulation rate of the electrolyzer (kW / min); ΔP ele is the change in electrolyzer power (kW); Δt is the time interval, representing the time elapsed for the change in electrolyzer power (min); RR max is the maximum load regulation rate of the electrolyzer (kW / min); RR min is the minimum load regulation rate of the electrolyzer (kW / min).

[0161] 3) Power balance constraint

[0162] At each time point, the power balance needs to be satisfied among the wind and solar power generation, the electrolyzer power, the charge and discharge power of the energy storage system, and the grid connection and purchase power:

[0163] P wind (t)+P solar (t)=P ele (t)+P charge (t)+P grid_up (t)-P discharge (t)-P grid_down (t)

[0164] where P wind (t) is the wind power generation at time t (kW); P solar is the photovoltaic power generation at time t; P ele (t) is the power output of the electrolyzer at time t (kW); P charge (t) is the charging power of the energy storage system at time t (kW); P discharge (t) is the discharging power of the energy storage system at time t (kW); P grid_up (t) is the grid connection power at time t (kW); P grid_down (t) is the power purchase at time t (kW).

[0165] Furthermore, by calculating the objective function of maximizing economic benefits, adopting reasonable energy storage charge and discharge strategies, grid connection and off-grid power scheduling, and start-stop operations of electrolyzers, the overall revenue can be maximized or the operating cost can be minimized. The objective function of maximizing economic benefits is mainly achieved by balancing the power purchase cost, power sales revenue, and energy storage charge and discharge cost.

[0166] The economic benefits can be obtained by calculating the balance between the power sales revenue and the power purchase cost, energy storage losses, etc. The total economic revenue objective function is:

[0167]

[0168] where, c grid_up (t) is the electricity sales price at time t; P grid_up (t) is the grid-connected power at time t; c grid_down (t) is the grid power purchase price at time t; P grid_down (t) is the power purchased from the grid at time t; c battery (t) is the charge and discharge cost of the energy storage system, mainly including the power loss caused by charge and discharge losses, the maintenance cost of the energy storage system, etc.; P charge / discharge (t) is the charging power or discharging power of the energy storage system.

[0169] In actual optimization, minimizing the curtailment rate and maximizing economic benefits are two objectives that need to be optimized simultaneously. Therefore, we need to construct a multi-objective optimization model to comprehensively optimize these two objectives. The combined objective function can be expressed as:

[0170] MinF = α × AbandonRate - β × profit

[0171] where, α and β are weight coefficients used to balance the curtailment rate and economic benefits. When α is larger, the system will give priority to reducing curtailment and pay attention to the full utilization of renewable energy; when β is larger, the system will give priority to maximizing economic benefits and try to obtain the maximum profit through grid connection and off-grid and energy storage strategies.

[0172] In the above optimization scheduling method for hydrogen production from wind and solar based on the hydrogen-carbon ratio, the wind and solar prediction values and the green hydrogen prediction values are obtained; the power difference is calculated based on the wind and solar prediction values and the green hydrogen prediction values; the energy state of the energy storage system is obtained; the charge and discharge operations of the energy storage system are adjusted according to the power difference and the energy state; and the grid connection and off-grid operations are performed according to the power difference and the charge and discharge operations. Using this method, the fluctuations of wind and solar power generation can be combined with the hydrogen demand. Through the intelligent scheduling of the energy storage system, the phenomenon of wind and solar curtailment can be effectively reduced, the system operation efficiency can be effectively improved, the maximization of renewable energy utilization can be achieved, and the deficiencies of the existing technology in poor matching between hydrogen production and demand and poor scheduling flexibility are overcome.

[0173] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this article, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0174] Based on the same inventive concept, an embodiment of the present application further provides a device for optimizing the scheduling of hydrogen production from wind and solar based on the hydrogen-carbon ratio for implementing the above-mentioned method for optimizing the scheduling of hydrogen production from wind and solar based on the hydrogen-carbon ratio. The implementation solutions provided by this device for solving problems are similar to the implementation solutions described in the above method. Therefore, the specific limitations in one or more embodiments of the device for optimizing the scheduling of hydrogen production from wind and solar based on the hydrogen-carbon ratio provided below can refer to the limitations on the method for optimizing the scheduling of hydrogen production from wind and solar based on the hydrogen-carbon ratio in the above text, and will not be repeated here.

[0175] In one embodiment, as Figure 3 shown, a device for optimizing the scheduling of hydrogen production from wind and solar based on the hydrogen-carbon ratio is provided, including: a prediction data module 310, a difference calculation module 320, an energy state module 330, a charge and discharge module 340, and an on-off grid module 350, where:

[0176] The prediction data module 310 is used to obtain the wind and solar prediction values and the green hydrogen prediction values.

[0177] The difference calculation module 320 is used to perform difference calculation based on the wind and solar prediction values and the green hydrogen prediction values to obtain a power difference.

[0178] The energy state module 330 is used to obtain the energy state of the energy storage system;

[0179] The charge and discharge module 340 is used to adjust the charge and discharge operations of the energy storage system according to the power difference and the energy state;

[0180] The on-off grid module 350 is used to perform on-off grid operations according to the power difference and the charge and discharge operations.

[0181] The charge and discharge module 340 is further used to detect whether the power difference is greater than the power threshold;

[0182] If the power difference is greater than the power threshold, charge the energy storage system;

[0183] If the power difference is less than or equal to the power threshold, discharge the energy storage system.

[0184] The charge and discharge module 340 is further configured to detect whether the energy storage state is greater than the energy storage range;

[0185] If the energy storage state is greater than the energy storage range, prohibit the energy storage system from charging;

[0186] If the energy storage state is less than the energy storage range, prohibit the energy storage system from discharging.

[0187] The grid connection and disconnection module 350 is further configured to perform a grid connection plan if the power difference is greater than the power threshold and the energy storage system is prohibited from charging;

[0188] If the power difference is less than the power threshold and the energy storage system is prohibited from discharging, perform a grid disconnection plan.

[0189] The grid connection and disconnection module 350 is further configured to detect whether the power difference is less than the grid connection threshold;

[0190] If the power difference is less than the grid connection threshold, perform a grid connection plan;

[0191] If the power difference is greater than or equal to the grid connection threshold, perform a wind curtailment plan and / or a PV curtailment plan.

[0192] The grid connection and disconnection module 350 is further configured to detect whether the power difference is less than the grid disconnection threshold;

[0193] If the power difference is less than the grid disconnection threshold, perform a grid disconnection plan;

[0194] If the power difference is greater than or equal to the grid disconnection threshold, perform a plan to shut down the electrolyzer.

[0195] Each module in the above-mentioned optimization scheduling device for hydrogen production from wind and PV based on the hydrogen-carbon ratio can be implemented in whole or in part by software, hardware, and their combination. The above-mentioned modules can be embedded in the processor of the computer device in the form of hardware or independent of it, or stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above-mentioned modules.

[0196] In one embodiment, a computer device is provided. The computer device can be a server, and its internal structure diagram can be as Figure 4As shown. The computer device includes a processor, a memory, and a network interface connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store wind and light prediction data. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, it implements an optimized scheduling method for wind and light hydrogen production based on the hydrogen-carbon ratio.

[0197] Those skilled in the art can understand that Figure 4 the structure shown in is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0198] In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, it implements any one of the optimized scheduling methods for wind and light hydrogen production based on the hydrogen-carbon ratio in the above embodiments.

[0199] Obtain wind and light prediction data and green hydrogen prediction data;

[0200] Perform a difference calculation based on the wind and light prediction data and the green hydrogen prediction data to obtain a power difference;

[0201] Obtain the energy storage state of the energy storage system;

[0202] Adjust the charge and discharge operations of the energy storage system according to the power difference and the energy storage state;

[0203] Perform grid connection and disconnection operations according to the power difference and the charge and discharge operations.

[0204] In one embodiment, when the processor executes the computer program, it also implements the following steps: Detect whether the power difference is greater than a power threshold;

[0205] If the power difference is greater than the power threshold, charge the energy storage system;

[0206] If the power difference is less than or equal to the power threshold, discharge the energy storage system.

[0207] In one embodiment, when the processor executes the computer program, it also implements the following steps: Detect whether the energy storage state is greater than an energy storage range;

[0208] If the energy storage state is greater than the energy storage range, charging of the energy storage system is prohibited;

[0209] If the energy storage state is less than the energy storage range, discharging of the energy storage system is prohibited.

[0210] In one embodiment, when the processor executes the computer program, the following steps are further implemented: If the power difference is greater than the power threshold and charging of the energy storage system is prohibited, a grid connection plan is carried out;

[0211] If the power difference is less than the power threshold and discharging of the energy storage system is prohibited, a grid disconnection plan is carried out.

[0212] In one embodiment, when the processor executes the computer program, the following steps are further implemented: Detect whether the power difference is less than the grid connection threshold;

[0213] If the power difference is less than the grid connection threshold, a grid connection plan is carried out;

[0214] If the power difference is greater than or equal to the grid connection threshold, a wind curtailment plan and / or a PV curtailment plan is carried out.

[0215] In one embodiment, when the processor executes the computer program, the following steps are further implemented: Detect whether the power difference is less than the grid disconnection threshold;

[0216] If the power difference is less than the grid disconnection threshold, a grid disconnection plan is carried out;

[0217] If the power difference is greater than or equal to the grid disconnection threshold, a plan to shut down the electrolyzer is carried out.

[0218] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, any one of the above-mentioned embodiments of the optimization scheduling method for wind-solar hydrogen production based on the hydrogen-carbon ratio is implemented.

[0219] Obtain wind-solar prediction data and green hydrogen prediction data;

[0220] Perform difference calculation according to the wind-solar prediction data and the green hydrogen prediction data to obtain a power difference;

[0221] Obtain the energy storage state of the energy storage system;

[0222] Adjust the charge and discharge operations of the energy storage system according to the power difference and the energy storage state;

[0223] Perform grid connection and disconnection operations according to the power difference and the charge and discharge operations.

[0224] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: detecting whether the power difference is greater than a power threshold;

[0225] If the power difference is greater than the power threshold, charging the energy storage system;

[0226] If the power difference is less than or equal to the power threshold, discharging the energy storage system.

[0227] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: detecting whether the energy storage state is greater than an energy storage range;

[0228] If the energy storage state is greater than the energy storage range, prohibiting the energy storage system from charging;

[0229] If the energy storage state is less than the energy storage range, prohibiting the energy storage system from discharging.

[0230] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: if the power difference is greater than the power threshold and the energy storage system is prohibited from charging, performing a grid connection plan;

[0231] If the power difference is less than the power threshold and the energy storage system is prohibited from discharging, performing a grid disconnection plan.

[0232] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: detecting whether the power difference is less than a grid connection threshold;

[0233] If the power difference is less than the grid connection threshold, performing a grid connection plan;

[0234] If the power difference is greater than or equal to the grid connection threshold, performing a wind curtailment plan and / or a photovoltaic curtailment plan.

[0235] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: detecting whether the power difference is less than a grid disconnection threshold;

[0236] If the power difference is less than the grid disconnection threshold, performing a grid disconnection plan;

[0237] If the power difference is greater than or equal to the grid disconnection threshold, performing an electrolyzer shutdown plan.

[0238] In one embodiment, a computer program product is provided, including a computer program which, when executed by a processor, implements the following steps:

[0239] Obtaining wind and photovoltaic power prediction data and green hydrogen prediction data;

[0240] Perform a difference calculation based on the predicted wind and light data and the predicted green hydrogen data to obtain a power difference;

[0241] Obtain the energy storage state of the energy storage system;

[0242] Adjust the charge and discharge operations of the energy storage system according to the power difference and the energy storage state;

[0243] Perform grid connection and disconnection operations according to the power difference and the charge and discharge operations.

[0244] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: Detect whether the power difference is greater than a power threshold;

[0245] If the power difference is greater than the power threshold, charge the energy storage system;

[0246] If the power difference is less than or equal to the power threshold, discharge the energy storage system.

[0247] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: Detect whether the energy storage state is greater than an energy storage range;

[0248] If the energy storage state is greater than the energy storage range, prohibit the energy storage system from charging;

[0249] If the energy storage state is less than the energy storage range, prohibit the energy storage system from discharging.

[0250] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: If the power difference is greater than the power threshold and the energy storage system is prohibited from charging, perform a grid connection plan;

[0251] If the power difference is less than the power threshold and the energy storage system is prohibited from discharging, perform a grid disconnection plan.

[0252] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: Detect whether the power difference is less than an on-grid threshold;

[0253] If the power difference is less than the on-grid threshold, perform an on-grid plan;

[0254] If the power difference is greater than or equal to the on-grid threshold, perform a wind curtailment plan and / or a light curtailment plan.

[0255] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented: Detect whether the power difference is less than an off-grid threshold;

[0256] If the power difference is less than the off-grid threshold, perform an off-grid plan;

[0257] If the power difference is greater than or equal to the grid-off threshold, a plan to shut down the electrolyzer is carried out.

[0258] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0259] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAM), magnetoresistive random access memories (MRAM), ferroelectric random access memories (FRAM), phase change memories (PCM), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in this application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in this application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0260] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, 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, it should be considered as the scope recorded in this specification.

[0261] The above-described embodiments merely represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all fall within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A method for optimizing the scheduling of wind-solar hydrogen production based on the hydrogen-carbon ratio, characterized in that: The method comprises: Obtain wind and solar power forecast data and green hydrogen forecast data; Performing difference calculation based on the wind and solar power prediction data and the green hydrogen prediction data to obtain a power difference; Obtain the energy storage status of the energy storage system; Adjusting the charging and discharging operation of the energy storage system according to the power difference and the energy storage state; The grid-on and grid-off operations are performed according to the power difference and the charging and discharging operations.

2. The method according to claim 1, characterized in that The adjusting the charging and discharging operation of the energy storage system according to the power difference includes: Detecting whether the power difference is greater than a power threshold; If the power difference is greater than the power threshold, charging the energy storage system; If the power difference is less than or equal to the power threshold, the energy storage system is discharged.

3. The method according to claim 2, characterized in that The adjusting the charging and discharging operation of the energy storage system according to the power difference and the energy storage state comprises: Detecting whether the energy storage state is greater than the energy storage range; If the energy storage state is greater than the energy storage range, the energy storage system is prohibited from charging; If the energy storage state is less than the energy storage range, the energy storage system is prohibited from discharging.

4. The method according to claim 3, characterized in that The performing the network access operation according to the power difference and the charging and discharging operation includes: If the power difference is greater than the power threshold and the energy storage system is prohibited from charging, then an online access plan is performed; If the power difference is less than the power threshold and the energy storage system is prohibited from discharging, a grid-connected plan is implemented.

5. The method according to claim 4, characterized in that If the power difference is greater than the power threshold and the energy storage system is prohibited from charging, the online access plan includes: Detecting whether the power difference is less than an Internet access threshold; If the power difference is less than the Internet access threshold, the Internet access plan is carried out; If the power difference is greater than or equal to the grid-connected threshold, a wind power abandonment plan and / or a solar power abandonment plan is implemented.

6. The method according to claim 4, characterized in that If the power difference is less than the power threshold and the energy storage system is prohibited from discharging, the off-grid plan includes: Detecting whether the power difference is less than a threshold for disconnecting from the network; If the power difference is less than the off-grid threshold, then the off-grid plan is implemented; If the power difference is greater than or equal to the grid-offline threshold, the electrolyzer shutdown plan is implemented.

7. A wind-solar hydrogen production optimization scheduling device based on hydrogen-carbon ratio, characterized in that: The device comprises: Prediction data module, used to obtain wind and solar power prediction data and green hydrogen prediction data; A difference calculation module, used to perform difference calculation based on the wind and solar power prediction data and the green hydrogen prediction data to obtain a power difference; Energy storage status module, used to obtain the energy storage status of the energy storage system; A charging and discharging module, used for adjusting the charging and discharging operation of the energy storage system according to the power difference and the energy storage state; The up-and-down network module is used to perform up-and-down network operations according to the power difference and the charging and discharging operations.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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