Energy storage capacity configuration method considering new energy island hydrogen production under low output working condition

Abstract

The invention discloses an energy storage capacity configuration method considering new energy island hydrogen production under a low-output working condition, and the method comprises the following steps: taking the maximum daily net income value of a wind and light storage combined hydrogen production system as a target, and proposing a target function; obtaining the real-time power of the wind driven generator and the real-time photovoltaic output power; constructing an electrolytic cell output model under the non-constant operation current; establishing constraint conditions for the model; and analyzing operation characteristics of a wind power system and a photovoltaic system, and simulating under a new energy low output condition according to the constraint condition to obtain an output simulation result of the wind-solar coupling hydrogen production system within one day. By supplementing the constraint conditions of the extreme working conditions in the model, the unbalanced risk of power supply in the extreme scene can be effectively reduced, and the reliability of stable operation of the power system is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy hydrogen production, and in particular to a method for configuring the energy storage capacity for new energy island hydrogen production under low output conditions. Background Art

[0002] As a clean and efficient secondary energy source, hydrogen energy has received more and more extensive attention. Hydrogen can not only be widely used as an industrial raw material in fields such as chemical industry and metallurgy, but also can be an important energy carrier in fields such as transportation and power generation. In order to achieve large-scale hydrogen energy applications, breakthroughs and optimizations in hydrogen production technologies are the key. Among them, the electrolytic water hydrogen production technology is considered to be a crucial part of the future sustainable energy system because it does not produce greenhouse gas emissions.

[0003] However, renewable energy hydrogen production systems relying on wind energy and solar energy have obvious intermittency and instability. Especially in extreme working conditions, such as the island mode without wind and light, the supply of renewable energy will be severely affected, resulting in the interruption of hydrogen production. How to reasonably configure the energy storage capacity to ensure the continuity of hydrogen energy production and the stability of the system is very important. The "Optimization Method for Medium- and Long-Term Operation Modes of a Large-Scale New Energy Base Transmitted by UHV DC" established a medium- and long-term operation mode optimization model with the goal of maximizing the external transmission and consumption of new energy, considering the operation constraints of various power sources and UHV DC, and proposed an annual production simulation calculation method based on weekly calculations. However, it did not constrain the coupled operation of new energy and energy storage in the model; the team of China University of Petroleum in the "Coordinated Operation Strategy and Capacity Configuration Optimization of an Off-grid Wind-Solar Power Generation Combined Hydrogen Production System" adopted a combination of wind / solar power generation, alkaline electrolyzers and energy storage devices, proposed a coordinated hydrogen production strategy for electrolyzer mode allocation and energy storage day-ahead planning, and based on considering the unit hydrogen production cost and the curtailment rate of wind and light, used an algorithm to optimize the capacity configuration. However, it did not consider the capacity configuration problem under low output conditions, and the power supply was unbalanced in extreme scenarios, and the reliability of the power system operation was poor. Studying the energy storage capacity configuration for new energy island hydrogen production under extreme weather conditions of low output of new energy can not only provide technical support for improving the reliability of the hydrogen production system, but also provide a theoretical basis for the future large-scale application of new energy hydrogen production technology, which has important practical significance and application value. Summary of the Invention

[0004] To solve the current technical problems, the main purpose of the present invention is to provide a method for configuring the energy storage capacity for new energy island hydrogen production under low output conditions. By supplementing the constraint conditions of extreme working conditions in the model, the risk of power supply imbalance in extreme scenarios can be effectively reduced, and the reliability of the stable operation of the power system can be improved.

[0005] The technical solution adopted by the present invention is: a method for configuring the energy storage capacity for new energy island hydrogen production under low output conditions, including the following steps: Taking the maximum daily net income value of the wind-solar-storage combined hydrogen production system as the goal, a target function is proposed; According to the output characteristics of the wind turbine and the output power model of the photovoltaic module, the real-time power of the wind turbine and the output power of the photovoltaic at each moment are obtained respectively; According to the overall operating power of each hydrogen production unit for electrolytic hydrogen production, considering the power consumption of the converter, an output model of the electrolytic cell under non-constant operating current is constructed; Constraints are established for the model, and the constraints include constraints on new energy equipment, energy storage equipment, the coupled operation of new energy and energy storage, and supplementary constraints under extreme conditions; Analyze the operating characteristics of the wind power system and the photovoltaic system, and simulate the new energy under low output conditions according to the constraints to obtain the output simulation results of the wind-solar coupled hydrogen production system within one day.

[0006] Comprehensively considering the electricity sales revenue, total investment cost, operation and maintenance cost, and depreciation residual value of the wind-solar-storage combined hydrogen production system, a target function is constructed. The expression for the maximum value of the daily net income of the wind-solar-storage combined hydrogen production system is as follows: ;(1) In the formula, F represents the daily net income of the wind-solar-storage combined hydrogen production system, e represents the electricity sales revenue of the system, r inv represents the total investment cost of the system, r ope represents the operation and maintenance cost of the system, r res represents the depreciation residual value of the system. All of the above are continuous optimization variables.

[0007] The electricity sales revenue, total investment cost, operation and maintenance cost, and depreciation residual value of the wind-solar-storage combined hydrogen production system are respectively expressed as follows: ;(2) ;(3) ;(4) ;(5) In the formula, represents the overall operating power of electrolytic hydrogen production, C and S respectively represent the installed capacity of energy storage power generation and the capacity of the energy storage device, S w and S crespectively represent the installed capacity of wind power and photovoltaic power, and the corresponding coefficient π d represents the system's electricity selling price, w and c respectively represent the investment costs per unit installed capacity of wind power and photovoltaic power, b c and b s respectively represent the investment cost per unit power generation installed capacity and the investment cost per unit capacity of energy storage.

[0008] The output characteristics of the wind turbine are shown in the following formula: ;(6) In the formula ，P w ( t ) is the real-time power of the wind turbine; P r is the rated power of the wind turbine; v is the real-time wind speed; v ci is the cut-in wind speed; v co is the cut-out wind speed; v r is the rated wind speed; The output power model of the photovoltaic module is shown in the following formula: ;(7) In the formula, P c ( t ) is t the output power of the photovoltaic at time P STC is the rated maximum output power of the photovoltaic under standard conditions; G STC is the solar irradiance under standard conditions; G C is the actual solar irradiance at the operating point; k is the power temperature coefficient; T c ( t ) is t the operating point temperature at time T STC is the operating temperature under standard conditions.

[0009] The overall operating power of each hydrogen production unit for electrolytic hydrogen production P P2H is expressed as: ;(8) In the formula, is the power consumption of the converter, is the power of the electrolyzer; The power consumption of the converter includes the fixed iron loss of the transformer, the switching loss linearly related to the current, the on-state switching loss linearly related to the square of the current, the copper loss of the transformer, and the loss of capacitive and inductive components, which is calculated as shown in the following formula: ;(9) The power characteristic of the electrolyzer is expressed as the product of the external voltage and the current, including the quadratic term and the linear term of the current, which is calculated as shown in the following formula: ;(10) Wherein, is the electrolysis current; λ, μ, ω, α, and β are fitting coefficients respectively; Combining formulas (9) and (10), the output model of the electrolyzer under non-constant operating current is obtained as follows: ;(11) Wherein, f ( I P2H ) represents a function including the quadratic term and the linear term of I P2H ; is the constant term; is the electrolysis current; P w ( t ) is the real-time power of the wind turbine; P c ( t ) is t the output power of the photovoltaic at time

[0010] The constraints on new energy devices include power balance constraints, wind power and photovoltaic power range constraints, and the overall operating power constraint relationship of electrolytic hydrogen production under non-constant operating current. The specific steps include: Construct power balance constraints: ;(12) ;(13) Wherein, ( t )、 ( t ) and ( t ) respectively represent the wind power output, photovoltaic output, and charge and discharge power of the energy storage device in the t th time period, P out ( t ) and P in ( t ) respectively represent the discharge power and charge power of the energy storage device; Construct the power range constraints for wind power and photovoltaic power: ;(14) In the formula, and respectively represent the normalized theoretical output powers of wind power and photovoltaic power in the t time period, both of which are known quantities; Construct the overall operating power constraint relationship for electrolytic hydrogen production under non-constant operating current: The constraint relationship between the wind power output ( t ) and the overall operating power of electrolytic hydrogen production is calculated as follows: ;(15) By introducing the 0-1 decision variables γ , θ and the integer M , the right side of the above formula is equivalent to a mixed-integer linear constraint, and the specific calculation is as follows; ;(16) ;(17) ;(18) ;(19) In the formula, is the electrolysis current, is the constant term.

[0011] The constraints on the energy storage device include the energy storage capacity range constraint, the energy storage power generation installed capacity and energy storage device capacity range constraint, the energy storage capacity balance constraint, and the energy storage charge and discharge power range constraint. The specific steps are as follows: Construct the energy storage capacity range constraint: ;(20) In the formula, E b ( t ) The energy storage capacity of the energy storage device in the t time period, ( t ) and ( t ) respectively represent the maximum and minimum energy storage capacity coefficients of the energy storage in the t time period, both of which are known quantities; Construct the energy storage power generation installed capacity and energy storage device capacity range constraint: ;(21) In the formula, and respectively represent the upper and lower limits of the installed capacity of energy storage power generation, and respectively represent the upper and lower limits of the capacity of the energy storage device, both of which are known quantities; Construct the energy storage power balance constraint: ;(22) In the formula, and respectively represent the discharge efficiency and charge efficiency of the energy storage device, both of which are known quantities; Construct the energy storage charge and discharge power range constraint: ;(23) In the formula, and respectively represent the maximum charge power coefficient and the maximum discharge power coefficient of the energy storage device in the t time period, both of which are known quantities.

[0012] The constraints on the combined operation of new energy and energy storage include the wind power and photovoltaic curtailment state constraint, and the wind power and photovoltaic curtailment state constraint is as follows: ;(27) In the formula, Q ( t ) represents the wind power and photovoltaic curtailment state.

[0013] The supplementary constraints for extreme working conditions include the following steps: Define the average hourly output of new energy lower than the rated output level of k d (0 ≤ k d < 1) times, that is, it is identified as a low output scenario, and the expression is as follows: ;(28) The constraint expression for the extreme low output scenario of new energy is as follows: ;(29) ;(30) In the formula, , , respectively represent the wind and light output and the energy storage charge and discharge power in the extreme scenario; the set E represents the wind and light output set, S E represents the wind and light installed capacity, represents the wind and light output set in the extreme scenario, represents the normalized wind and light output fluctuation amount in the extreme case; It is the wind and light abandoned electricity quantity.

[0014] Analyzing the operating characteristics of the wind power system includes the following steps: establishing a wind power generation model using the Weibull distribution model, and drawing the output curve of the fan on a typical day through the wind speed probability density function; among them, the wind speed probability density function f ( v ) has the following expression: ;(31) Among them, v is the wind speed of the fan blade; k w is the shape parameter of the Weibull distribution; λ w is the scale parameter; Analyzing the operating characteristics of the photovoltaic system includes the following steps: obtaining the solar radiation intensity and drawing the output curve of the photovoltaic on a typical day; observing the overall trend of the active power output of the wind power generation during a day, comparing the output characteristics with the user's electricity demand, and analyzing its relationship with the load demand; among them, the probability density function expression of the active output power of the photovoltaic power generation system is as follows: ;(42) Among them, α 1、 β 1 is the shape parameter; Г is the gamma function, P pv is the active output power of the current photovoltaic system; P pvm is the maximum value of the active output; Based on the typical day scenario, determine the time step, set the installed capacity of wind power and photovoltaic in the wind-solar-hydrogen combined production system, and simulate the normalized theoretical output sequences of wind power and photovoltaic and the power balance diagram of the wind-solar coupled hydrogen production system in a day.

[0015] The present invention has the following beneficial effects: 1. The present invention considers the system output under the low output condition of new energy.

[0016] During the operation of the new energy power generation system, it is significantly affected by weather conditions. Especially in extreme weather scenarios, the output of the new energy power generation system will drop significantly. Under the low output condition of new energy, the imbalance between power supply and demand will pose a serious threat to the safe and stable operation of the power system.

[0017] The present invention embeds the operation constraints considering the extreme weather scenario of low output of new energy in the planning model, which can effectively control the imbalance risk of power supply under extreme scenarios and ensure the safe and reliable operation of the power system.

[0018] 2. The present invention constructs an optimization model considering the electricity sales revenue, total investment cost, operation and maintenance cost, and depreciation residual value of the system.

[0019] New energy power generation has volatility and intermittency, posing great challenges to the economy and stability of the power system. In a new energy power generation system, the energy storage unit, as an important means to regulate the power supply and demand balance, can cut peaks and fill valleys, improve the new energy consumption rate, and ensure the safe operation of the system. To maximize economic benefits and make full use of the energy storage unit and new energy power generation resources, an optimization model that comprehensively considers the system's revenue and operation cost is established, and the best charge and discharge strategy for the energy storage unit and the output power scheduling plan for the new energy power generation unit are formulated.

[0020] 3. The present invention proposes an objective function for maximizing the daily revenue of the system, and combines a series of constraint conditions to optimize the combination of the energy storage unit and new energy power generation. The optimization model is solved through a series of constraint conditions, thereby improving the economic benefits and operation efficiency of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0022] Figure 1 It is a flowchart of the present invention.

[0023] Figure 2 It is a schematic diagram of the output curve of a typical daily wind turbine.

[0024] Figure 3 It is a schematic diagram of the output curve of a typical daily photovoltaic power generation.

[0025] Figure 4 It is a schematic diagram of the framework of the capacity optimization configuration model for wind-solar-hydrogen combined production.

[0026] Figure 5 It is a schematic diagram of the theoretical output sequence of wind power in a day.

[0027] Figure 6 It is a schematic diagram of the theoretical output sequence of photovoltaic power in a day.

[0028] Figure 7 It is the power balance diagram of the wind-solar-hydrogen combined production system in a day; where P b ( t ) and P P2HThey are the optimized energy storage output and electrolyzer output within a day respectively. Specific Embodiments

[0029] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0030] See Figure 1 , a method for configuring the energy storage capacity for hydrogen production in a new energy island considering low-output working conditions, comprising the following steps: S1. Taking the maximum daily net income value of the wind-solar-storage combined hydrogen production system as the goal, a target function is proposed.

[0031] Specifically, considering the electricity sales revenue, total investment cost, operation and maintenance cost, and depreciation residual value of the wind-solar-storage combined hydrogen production system, a target function is constructed. The expression for the maximum value of the daily net income of the wind-solar-storage combined hydrogen production system is as follows: ;(1) In the formula, F represents the daily net income of the wind-solar-storage combined hydrogen production system, e represents the electricity sales revenue of the system, r inv represents the total investment cost of the system, r ope represents the operation and maintenance cost of the system, r res represents the depreciation residual value of the system. All of the above are continuous optimization variables.

[0032] Calculate the electricity sales revenue, total investment cost, operation and maintenance cost, and depreciation residual value of the system, respectively representing the installed capacity of energy storage power generation and the capacity of the energy storage device: ;(2) ;(3) ;(4) ;(5) In the formula, represents the overall operating power of electrolytic hydrogen production; C and S respectively represent the installed capacity of energy storage power generation and the capacity of the energy storage device; S w and S c respectively represent the installed capacity of wind power and photovoltaic power; the corresponding coefficients π dIndicates the selling price of electricity of the system; w and c respectively represent the investment costs per unit installed capacity of wind power and photovoltaic power; b c and b s respectively represent the investment cost per unit power generation installed capacity and the investment cost per unit capacity of energy storage. All of the above are known quantities.

[0033] S2. Obtain the real-time power of the wind turbine and the output power of the photovoltaic at the moment respectively according to the output characteristics of the wind turbine and the output model of the photovoltaic module.

[0034] Specifically, the solar radiation intensity is the key determinant of the output power of photovoltaic power generation, which is closely related to the elevation angle of the sun, the orientation of the photovoltaic system, and the meteorological conditions of the region where it is located. The random fluctuation and intensity of the wind speed also bring significant uncertainties to the output power of the wind turbine generator. The output power of the wind turbine is affected by various factors. As a key factor affecting the output power of wind power, the output characteristics of the wind turbine can be approximately described by a piecewise function as: ; (6) In formula (6): P w ( t ) is the real-time power of the wind turbine; P r is the rated power of the wind turbine; v is the real-time wind speed; v ci is the cut-in wind speed; v co is the cut-out wind speed; v r is the rated wind speed.

[0035] The actual power of the photovoltaic module is related to factors such as solar radiation, ambient temperature, and the rated power under standard conditions. Its output model is expressed as: ; (7) In formula (7): is t the output power of the photovoltaic at the moment; P STC is the rated maximum output power of the photovoltaic under standard conditions; G STC is the solar irradiance under standard conditions; G C is the actual solar irradiance at the working point; k is the power temperature coefficient; T c ( t ) is tInstantaneous operating point temperature; T STC The operating temperature under standard conditions.

[0036] S3. According to the overall operating power of electrolytic hydrogen production for each hydrogen production unit, considering the power consumption of the converter, construct an output model of the electrolyzer under non-constant operating current.

[0037] Specifically, the overall operating power of electrolytic hydrogen production for each hydrogen production unit can be expressed as: ;(8) In Equation (8): is the power consumption of the converter, is the power of the electrolyzer.

[0038] It includes the fixed iron loss of the transformer, the switching loss linearly related to the current, the switching on-state loss linearly related to the square of the current, the copper loss of the transformer, and the loss of capacitive and inductive components, so it can be described as a quadratic function of the operating current, as shown in Equation (9). The power characteristic of the electrolyzer can be expressed as the product of the external voltage and the current, including the current square term and the linear term, as shown in Equation (10).

[0039] ;(9) ;(10) In the formula: is the electrolysis current; λ, μ, ω, α, β are fitting coefficients, λ = 2.868×10 -4 , μ = 6.633×10 -3 , ω = 1.217×10 -2 , α = 1.67×10 -2 , β = 0.25.

[0040] Combining Equations (9) and (10), the output model of the electrolyzer under non-constant operating current is obtained as follows: ;(11) In the formula: f ( I P2H ) represents a function including the quadratic term and the linear term of I P2H ; is the constant term; when < , the output power of the fan is difficult to maintain the normal operation of the electrolytic hydrogen production system, so is 0.

[0041] S4. Establish constraints for the model. The constraints include constraints on new energy equipment, energy storage equipment, the combined operation of new energy and energy storage, and supplementary constraints under extreme conditions.

[0042] Specifically, the steps for constraining new energy equipment in the model are as follows: 1) Power balance constraint: ;(12) ;(13) In the formula: , and respectively represent the wind power output, photovoltaic power output, and charge-discharge power of the energy storage device in the t time period. The charge-discharge power of the energy storage device can be expressed as the difference between the discharge power of the energy storage device P out ( t ) and the charge power of the energy storage device P in ( t ). All of the above are continuous variables. P out ( t ) and P in ( t ) respectively represent the discharge power and charge power of the energy storage device.

[0043] Among them, if , it means the energy storage device is discharging; if , it means the energy storage device is charging.

[0044] 2) Wind and photovoltaic power generation power range constraint: ;(14) and respectively represent the normalized theoretical power outputs of wind power and photovoltaic power in the t time period, and both are known quantities. This constraint limits the power outputs of wind power and photovoltaic power in each time period to not exceed their theoretical maximum power generation.

[0045] 3) Overall operation power constraint relationship of electrolytic hydrogen production under non-constant operating current: The constraint relationship between the wind power output and the overall operation power of electrolytic hydrogen production is shown in Equation (15): ;(15) The relationship can be established by introducing 0-1 decision variables γ , θand very large integers M The right - hand side of the above formula is equivalent to the mixed - integer linear constraints shown in Equations (16) - (19): ;(16) ;(17) ;(18) .(19) The constraints on the energy storage devices in the model, the specific steps include: 1) Energy storage capacity range constraint: ;(20) In the formula: E b ( t ) The stored energy of the energy storage device at the t th time period, which is a continuous variable; ( t ) and ( t ) represent the maximum and minimum stored - energy coefficients of the energy storage at the t th time period respectively, both of which are known quantities.

[0046] 2) Energy storage power generation installation and energy storage device capacity range constraint: ;(21) In the formula: and represent the upper and lower limits of the energy storage power generation installation respectively, and represent the upper and lower limits of the energy storage device capacity respectively, both of which are known quantities.

[0047] 3) Energy storage stored - energy balance constraint: ;(22) In the formula: and represent the discharge efficiency and charge efficiency of the energy storage device respectively, both of which are known quantities.

[0048] 4) Energy storage charge - discharge power range constraint: ;(23) and represent the maximum charge - power coefficient and maximum discharge - power coefficient of the energy storage device at the t th time period respectively, both of which are known quantities.

[0049] However, the energy storage capacity balance constraint belongs to piecewise constraints and is difficult to solve directly. Therefore, linearization operations need to be performed on it, and Equation (22) is written in the following form: ;(24) Equation (11) also contains quadratic constraints and needs to be linearized to facilitate the solution of the model. It can be linearized into the following form: ;(25) ;(26) To realize the selection of the charging and discharging states of the energy storage device, 0-1 variables I ( t ) and O ( t ) are introduced, which represent the charging state and discharging state of the energy storage device in the t th time period respectively. Equation (26) represents the mutual exclusion of the charging state and discharging state of the energy storage device in the t th time period.

[0050] The specific steps for the constraints of the combined operation of new energy and energy storage in the model include: Wind power and photovoltaic curtailment state constraint: ;(27) In the formula: Q ( t ) represents the curtailment state of wind power and photovoltaic, which is a 0-1 variable. Combining Equation (14), it can be seen that Q ( t ) = 1 indicates that the total power generation of wind power and photovoltaic is less than the maximum theoretical total power generation of the two, indicating that new energy is curtailed. Q ( t ) = 0 indicates that the total power generation of wind power and photovoltaic is equal to the maximum theoretical total power generation of the two, indicating that new energy is not curtailed. This equation realizes the Q ( t ) value.

[0051] The constraint conditions for extreme working conditions in the model are supplemented. The specific steps include: Define the average hourly output of new energy lower than the rated output level of k d (0 ≤ k d < 1) times, that is, it is identified as a low output scenario, which can be represented by formula (28). k d Select 0.1.

[0052] ;(28) Constraints to be supplemented in the extreme scenario of low renewable output (LR): ;(29) ;(30) Equation (29) constructs the power balance constraint in the extreme scenario of renewable power output, and equation (30) is the upper and lower limit constraints of the output of wind power and photovoltaic power. Among them, 、 、 represent the renewable power output and the charge and discharge power of energy storage in the extreme scenario respectively; the set E represents the set of renewable power output, S E represents the installed capacity of renewable power, represents the set of renewable power output in the extreme scenario, represents the normalized fluctuation amount of renewable power output in the extreme case; is the amount of curtailed renewable power.

[0053] S5. Analyze the operating characteristics of the wind power system and the photovoltaic system, and simulate the low renewable output condition according to the above constraints to obtain the simulation results of the output of the renewable power coupled hydrogen production system within one day.

[0054] Specifically, to analyze the operating characteristics of the wind power system, the specific steps include: The active power of the wind turbine is correlated with the wind speed. It is necessary to fit the wind speed data to obtain more accurate probability distribution characteristics. In wind power generation modeling, its wind speed probability density function f ( v ) is shown in Equation (31).

[0055] ;(31) Among them, v is the wind speed of the wind turbine blade; k w is one of the two parameters of the Weibull distribution, that is, the shape parameter of the Weibull distribution, unit: m / s; λ w is the scale parameter, unit: m / s.

[0056] The specific expression is shown as follows: ;(32) ;(33) Among them, σ is the standard deviation of the wind speed; μ represents the average wind speed; Г is the Gamma function.

[0057] Select the typical daily wind power generation curve as the research object. For example, Figure 2 As shown, the observation results show that the active power output of wind power generation generally shows a trend of being lower during the day and higher at night. It usually reaches the highest point of the whole day at about 6 am and the lowest point at about 1 pm. This output characteristic is in contrast to the electricity demand of users and shows a characteristic contrary to the load demand. Therefore, by reasonably utilizing this characteristic of the wind power generation system, the electricity demand of users can be better met while improving the energy utilization efficiency.

[0058] Analyze the operating characteristics of the photovoltaic system. The specific steps include: The radiation ability of the sun satisfies the Beta distribution, also known as the B distribution, which is a set of continuous probability density distributions defined in the interval (0,1) and has α 1 and β 1 two parameters, called shape parameters, which mainly describe the random characteristics of solar radiation intensity. The expression is as shown in Equation (34).

[0059] ;(34) In the formula: s is the solar irradiance; Г is the gamma function.

[0060] Solar irradiance s The expression of is as shown in Equation (35): ;(35) In the formula: q is the light intensity at this time; q m is the peak light intensity.

[0061] The expectation and variance of the Beta distribution are as shown in Equations (36) and (37): ;(36) ;(37) Therefore, according to Equations (35) and (36), by using the expectation and variance in the historical observation data of random variables, the two parameters of the Beta distribution can be determined, and the specific expressions are as shown in Equations (38) and (39): ;(38) ;(39) In the formula: μ 1 is the average intensity of light; σ 1 2 is the variance value of the B distribution.

[0062] The relationship between the effective output power of photovoltaic power generation, light intensity, and the area of the solar panel is shown in Equation (40): ;(40) In the formula: P pv is the active output power of the current photovoltaic system; N is the number of photovoltaic panels; A n is the area of a single photovoltaic panel; η n is the conversion efficiency of the nth photovoltaic panel. This efficiency is related to the light intensity received by the panel and is usually expressed by the efficiency at the maximum power point, as shown in Equation (41): ;(41) In the formula: U m and I m are the maximum voltage and current values output by the photovoltaic panel, respectively. Combining Equations (34) and (40), the probability density function of the active output power of the photovoltaic power generation system can be derived, as shown in Equation (42): ;(42) In the formula: P pvm is the maximum value of the active output. Similar to the typical daily variation characteristics shown by wind speed in wind power generation, light intensity also exhibits a certain daily periodicity. Therefore, the output of photovoltaic power generation also has daily variation characteristics.

[0063] As Figure 3 shows the typical output variation of a photovoltaic system in a day. From 8 pm to 6 am the next day, the output of the photovoltaic system is extremely low, almost zero, while between 11 am and 2 pm at noon, the output reaches the highest point of the day. Such a daily output curve is roughly in a normal distribution shape, which is more matched with the user's electricity demand and shows the same characteristics as the load demand.

[0064] Establish an optimal configuration model for the combined hydrogen production capacity of wind-solar energy storage with the maximum daily revenue of the system as the objective function. As Figure 4 shown, the piecewise constraints and non-linear constraints existing in the constructed model have been equivalently transformed into linear constraints and solved and calculated on the MALAB simulation platform.

[0065] In this embodiment, the simulation is based on a typical daily scenario with a time step of 1 h. During the simulation process, the installed capacities of wind power and photovoltaic power in the system are both set to 200 MW, and other parameters are shown in the following table:

[0066] The normalized theoretical output sequences of wind power and photovoltaic are respectively as Figure 5 , Figure 6 shown.

[0067] After calculation, the daily net income of the system is 1.38142 million yuan, and the energy storage (capacity S and unit installed capacity C ) configuration is 150MW / 175MW. The power balance situation of the system within 24 hours is as Figure 7 shown. It can be found that the curtailment of electricity in the system mainly occurs during the noon period of the day. At this time, the system absorbs the curtailed electricity through the energy storage device. The energy storage discharge mainly occurs at night. At this time, there is no output from photovoltaic, and the energy storage device releases the electricity stored during the day to fill the gap in the power transmitted out.

[0068] The above embodiments are only used to illustrate the present invention. Among them, the structures, connection methods, manufacturing processes, etc. of each component can all be changed. Any equivalent transformation and improvement made on the basis of the technical solution of the present invention should not be excluded from the protection scope of the present invention.

Claims

1. A method for configuring energy storage capacity for isolated island hydrogen production using new energy under low output conditions, characterized in that: The following steps are involved: Taking the maximum daily net income of the wind-solar-storage combined hydrogen production system as the goal, an objective function is proposed; According to the wind turbine output characteristics and the photovoltaic module output model, the real-time power of the wind turbine generator and the output power of the photovoltaic at any moment are obtained respectively; According to the overall operating power of each hydrogen production unit for electrolysis hydrogen production, considering the power consumption of the converter, the output model of the electrolyzer under non-constant operating current is constructed; Establishing constraint conditions for the model, including constraints on new energy equipment, constraints on energy storage equipment, constraints on coupled operation of new energy and energy storage, and supplementary constraints for extreme working conditions; The operating characteristics of the wind power system and the photovoltaic system are analyzed, and the low-output working conditions of the new energy are simulated according to the constraints, and the output simulation results of the wind-solar coupled hydrogen production system within one day are obtained.

2. The energy storage capacity configuration method for isolated island hydrogen production using new energy under low output conditions according to claim 1 is characterized in that: Taking into account the electricity sales revenue, total investment cost, operation and maintenance cost and depreciation residual value of the wind-solar-storage combined hydrogen production system, the objective function is constructed. The maximum net profit expression of the wind-solar-storage combined hydrogen production system within one day is as follows: ； (1) In the formula, F It represents the net income of the wind-solar-storage combined hydrogen production system within one day. e represents the system's electricity sales revenue, r inv represents the total investment cost of the system, r ope represents the operation and maintenance cost of the system, r res Represents the depreciation residual value of the system, and all of the above are continuous optimization variables.

3. The energy storage capacity configuration method for isolated island hydrogen production using new energy under low output conditions according to claim 2 is characterized in that: The electricity sales revenue, total investment cost, operation and maintenance cost, and depreciation residual value of the wind-solar-storage combined hydrogen production system are expressed as follows: ；(2) ；(3) ；(4) ； (5) In the formula, Indicates the overall operating power of hydrogen production by electrolysis, C and S They represent the installed capacity of energy storage power generation and the capacity of energy storage device respectively. S w and S c Respectively represent wind power installed capacity and photovoltaic installed capacity, and the corresponding coefficient π d Indicates the system electricity selling price, w and c Represent the unit installed capacity investment cost of wind power and photovoltaic power, b c and b s They represent the investment cost per unit of installed power generation capacity and the investment cost per unit of capacity of energy storage respectively.

4. The energy storage capacity configuration method for isolated island hydrogen production using new energy under low output conditions according to claim 1 is characterized in that: The fan output characteristics are shown in the following formula: (6) In the formula ，P w ( t ) is the real-time power of the wind turbine generator; P r is the rated power of the wind turbine; v is the real-time wind speed; v ci is the cut-in wind speed; v co To cut out the wind speed; v r is the rated wind speed; The photovoltaic module output model is as follows: (7) In the formula, P c ( t )for t The output power of photovoltaic at all times; P STC The maximum rated output power of photovoltaic under standard conditions; G STC is the solar irradiance under standard conditions; G C is the actual solar irradiance at the working point; k is the power temperature coefficient; T c ( t )for t Working point temperature at all times; T STC The operating temperature is for standard conditions.

5. The energy storage capacity configuration method for isolated island hydrogen production using new energy under low output conditions according to claim 1 is characterized in that: The overall operating power of each hydrogen production unit for hydrogen production by electrolysis P P2H It is expressed as: ； (8) In the formula, is the power consumption of the converter, is the electrolytic cell power; The power consumption of the converter includes the fixed iron loss of the transformer, the switching loss which is linearly related to the current, the switch conduction loss which is linearly related to the square of the current, the copper loss of the transformer, and the loss of the capacitive and inductive components. The calculation is shown in the following formula: ；(9) The power characteristic of the electrolytic cell is expressed as the product of the external voltage and the current, including the square term and the linear term of the current, and is calculated as shown in the following formula: ； (10) In the formula, is the electrolysis current; λ, μ, ω, α, and β are fitting coefficients respectively; Combining equations (9) and (10), the output model of the electrolyzer under non-constant operating current is obtained as follows: ； (11) In the formula, f ( I P2H ) means including I P2H The quadratic and linear functions of ; is a constant term; is the electrolysis current; P w ( t ) is the real-time power of the wind turbine generator; P c ( t )for t The photovoltaic output power at any moment.

6. The energy storage capacity configuration method for isolated island hydrogen production using new energy under low output conditions according to claim 1 is characterized in that: The constraints on new energy equipment include power balance constraints, wind power and photovoltaic power generation power range constraints, and the overall operating power constraints of electrolysis hydrogen production under non-constant operating current. The specific steps include: Constructing power balance constraints: ；(12) ；(13) In the formula, ( t ), ( t )and ( t ) represent the t The wind power output, photovoltaic output and charging and discharging power of the energy storage device in each period, P out ( t )and P in ( t ) represent the discharging power and charging power of the energy storage device respectively; Construct wind and photovoltaic power generation power range constraints: ；(14) In the formula, and Represents wind power and photovoltaic power in the t The normalized theoretical output of each time period is a known quantity; Construct the overall operating power constraint relationship of hydrogen electrolysis under non-constant operating current: Wind power output ( t ) and the overall operating power of hydrogen production by electrolysis The constraint relationship is calculated as follows: ；(15) By introducing 0-1 decision variables γ , θ and integers M , the right side of the above equation is equivalent to a mixed integer linear constraint, and the specific calculation is as follows; ；(16) ；(17) ；(18) ；(19) In the formula, is the electrolysis current, is a constant term.

7. The energy storage capacity configuration method for isolated island hydrogen production using new energy under low output conditions according to claim 1 is characterized in that: The constraints on energy storage equipment include energy storage capacity range constraints, energy storage power generation installed capacity and energy storage device capacity range constraints, energy storage capacity balance constraints, and energy storage charging and discharging power range constraints. The specific steps include: Construct energy storage capacity range constraints: ；(20) In the formula, E b ( t ) The energy storage device is in the t The amount of power stored during the period, ( t )and ( t ) represent the energy storage in the t The maximum and minimum storage coefficients of the time period are both known quantities; Constructing energy storage power generation installed capacity and energy storage device capacity range constraints: ；(21) In the formula, and They represent the upper and lower limits of energy storage power generation installed capacity, and They represent the upper and lower limits of the capacity of the energy storage device, respectively, and are both known quantities; Construct energy storage capacity balance constraints: ；(22) In the formula, and They represent the discharge efficiency and charging efficiency of the energy storage device, respectively, and are both known quantities; Construct energy storage charging and discharging power range constraints: ；(23) In the formula, and Respectively represent the energy storage device in the t The maximum charging power coefficient and the maximum discharging power coefficient of the time period are both known quantities.

8. The energy storage capacity configuration method for isolated island hydrogen production using new energy under low output conditions according to claim 1 is characterized in that: The constraints on the coupled operation of new energy and energy storage include wind power and photovoltaic power abandonment state constraints. The wind power and photovoltaic power abandonment state constraints are as follows: ； (27) In the formula, Q ( t ) indicates the power abandonment status of wind power and photovoltaic power.

9. The method for configuring energy storage capacity for isolated island hydrogen production using new energy under low output conditions according to claim 1, characterized in that: The additional constraints for extreme conditions include the following steps: Definition: Average hourly output of renewable energy Below rated output level of k d (0≤ k d <1) times, it is identified as a low output scenario, and the expression is as follows: ；(28) The constraint expression for the extreme scenario of low output of new energy is as follows: ；(29) ；(30) In the formula, , , They represent the wind and solar output and energy storage charging and discharging power in extreme scenarios respectively; Set E represents the wind and solar power output set. S E Represents the installed capacity of wind and solar power. Indicates the wind and solar power output in extreme scenarios. Represents the normalized wind and solar power output fluctuation under extreme conditions; For wind and solar power curtailment.

10. The energy storage capacity configuration method for isolated island hydrogen production using new energy under low output conditions according to claim 1 is characterized by: Analyzing the operating characteristics of a wind power system includes the following steps: The Weibull distribution model is used to establish wind power generation modeling, and the wind speed probability density function is used to draw the typical day wind turbine output curve; among them, the wind speed probability density function f ( v ) is as follows: ；(31) in, v is the wind speed of the fan blade; k w is the shape parameter of the Weibull distribution; λ w is the scale parameter; Analyzing the operating characteristics of the photovoltaic system includes the following steps: obtaining the solar radiation intensity and drawing a typical day photovoltaic output curve; observing the overall trend of the active power output of wind power generation during the day, comparing the output characteristics with the user's electricity demand, and analyzing its relationship with the load demand; among them, the probability density function expression of the active output power of the photovoltaic power generation system is as follows: ；(42) in, α 1、 β 1 is the shape parameter; Г is the gamma function, P pv is the active output power of the current photovoltaic system; P pvm is the maximum value of active output; Based on a typical daily scenario, the time step is determined, the wind power and photovoltaic installed capacity in the wind-solar-storage combined hydrogen production system is set, and the normalized wind power and photovoltaic theoretical output sequence and the power balance diagram of the wind-solar-storage coupled hydrogen production system within a day are obtained through simulation.

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