Real-time feedback optimization method for electricity-hydrogen composite energy storage system

Abstract

The invention discloses a real-time feedback optimization method for an electricity-hydrogen composite energy storage system. The real-time feedback optimization method for the electricity-hydrogen composite energy storage system comprises the following steps: constructing a real-time feedback optimization model for energy self-adaptive adjustment of the electricity-hydrogen composite energy storage system; constructing operation constraints of the electricity-hydrogen composite energy storage system, wherein the operation constraints comprise an electrochemical energy storage operation constraint and a hydrogen energy storage operation constraint; the charging and discharging power of electrochemical energy storage and hydrogen energy storage is calculated; by means of hydrogen energy storage and online measurement of the energy state of an electrochemical battery unit, an electricity-hydrogen composite energy storage system real-time feedback optimization strategy based on measurement feedback is designed. The method can comprehensively consider the wind power fluctuation stabilization demand and the physical operation characteristics of the electrochemical energy storage system and the hydrogen energy storage coefficient, obtains a better control result of the electricity-hydrogen composite energy storage system, and has the advantages of being scientific and reasonable, high in applicability, good in effect and the like.

Description

Technical Field

[0001] The present invention belongs to the field of wind farm electric-hydrogen composite energy storage system control, and in particular to a real-time feedback optimization method for electric-hydrogen composite energy storage system for reducing wind farm output power prediction deviation. Background Art

[0002] New energy stations need to have certain adjustment capabilities, and if necessary, they should be equipped with certain energy storage to improve the adjustability of new energy stations. Among them, electrochemical energy storage and hydrogen energy storage have certain complementarity in power density and energy density. Configuring a certain capacity of electric-hydrogen composite energy storage system on the new energy station side is an effective means to improve the adjustability of new energy stations. However, the physical properties of electrochemical energy storage and hydrogen energy storage are quite different, and the cost is relatively high. How to control the electric-hydrogen composite energy storage system to reduce the output power forecast deviation of wind farms is crucial.

[0003] The prior art discloses a control method for an electric-hydrogen composite energy storage system, establishes an optimal control model and objective function of the electric-hydrogen composite energy storage system, and most studies achieve rapid power distribution through filtering or heuristic electric-hydrogen composite energy storage system control strategies.

[0004] However, the above method is limited in the control objectives and scenarios to which it is applicable. It fails to fully consider the internal power distribution of the electric-hydrogen composite energy storage system, and does not consider the differences in wind power smoothing demand in different time periods to adjust the operating state of the electric-hydrogen composite energy storage system, which may lead to a more conservative control strategy. Summary of the invention

[0005] In view of the problems existing in the above-mentioned prior art, the purpose of the present invention is to provide a scientific, reasonable, highly applicable and effective optimal control strategy for an electric-hydrogen composite energy storage system, which aims to comprehensively consider the demand for reducing the prediction deviation of wind farm output power and the physical operating characteristics of electrochemical energy storage and hydrogen energy storage, so as to obtain the optimal power of electrochemical energy storage and hydrogen energy storage.

[0006] In a first aspect, the present invention provides a real-time feedback optimization method for an electric-hydrogen composite energy storage system, comprising:

[0007] Construct the optimization objective function and corresponding operation constraints of the electric-hydrogen hybrid energy storage system;

[0008] Constructing a feedback optimization strategy based on the wind power output by the wind farm and the optimization objective function;

[0009] updating the electrochemical energy storage system power and the hydrogen energy storage system power in real time according to the feedback optimization strategy;

[0010] Calculate the wind power power after energy storage adjustment based on the updated electrochemical energy storage system power and hydrogen energy storage system power;

[0011] If the adjusted wind power exceeds the preset upper and lower limits of the predicted wind power, the parameters of the feedback optimization strategy are adjusted, and the power of the electrochemical energy storage system and the power of the hydrogen energy storage system are re-updated.

[0012] Preferably, the optimization objective function of the electric-hydrogen composite energy storage system includes:

[0013]

[0014]

[0015] Where Min represents minimization, f is the loss cost of the electric-hydrogen composite energy storage system, C V is the operating cost of the electric-hydrogen hybrid energy storage system, is the power of the ith battery cell at time t, is the power of the i-th hydrogen storage unit at time t, λ BESS and λ HESS are the operating cost coefficients of the electrochemical energy storage system and the hydrogen energy storage system, Δt is the unit time interval, is the penalty function for the state of charge, is the penalty function for the hydrogen storage state; γ is the penalty factor, δ1 and δ2 are the parameters of the electrochemical energy storage system and the hydrogen energy storage system, respectively, SOC t.i is the state of charge of the ith battery cell at time t, SOC max and SOC min The upper and lower limits of the state of charge of a single battery cell, SOH t.i is the hydrogen storage state of the hydrogen storage tank in the i-th hydrogen storage unit at time t, SOH max and SOH min They are respectively the upper and lower limits of the hydrogen storage state of the hydrogen storage tank.

[0016] Preferably, the operation constraints include operation constraints of an electrochemical energy storage system and operation constraints of a hydrogen energy storage system, and the operation constraints of the electrochemical energy storage system include:

[0017]

[0018] In the formula, is the energy of the i-th battery cell at time t, η BESS.E and η BESS.F are the charge and discharge efficiency of the battery unit, Q BESS is the capacity of the battery cell, is the power of the electrolyzer in the i-th hydrogen storage unit at time t, is the power of the fuel cell in the i-th hydrogen storage unit at time t;

[0019] The operating constraints of the hydrogen energy storage system include:

[0020] Electrolyzer Constraints:

[0021]

[0022] In the formula, is the power of the electrolyzer in the i-th hydrogen storage unit at time t, η elec is the hydrogen production efficiency of the electrolyzer of the hydrogen storage unit, is the mass of hydrogen produced by the electrolyzer in the i-th hydrogen storage unit at time t, H is the calorific value of hydrogen, P elec.max and P elec.min are the upper and lower limits of the input power of a single electrolyzer of the hydrogen storage unit, The maximum amount of hydrogen that flows into the hydrogen storage tank per unit time for a single electrolyzer of the hydrogen storage unit;

[0023] Hydrogen storage tank constraints:

[0024]

[0025] SOH min ≤SOH t.i ≤SOH max

[0026] In the formula, Q HS is the capacity of the hydrogen storage tank, is the amount of hydrogen consumed by the fuel cell in the i-th hydrogen storage unit at time t; is the amount of hydrogen consumed by the fuel cell in the i-th hydrogen storage unit at time t;

[0027] Fuel cell constraints:

[0028]

[0029] Where η FC The efficiency of the fuel cell hydrogen energy conversion into electrical energy for the hydrogen storage unit, is the power of the fuel cell in the i-th hydrogen storage unit at time t, P HESS.F.max and P HESS.F.min are the upper and lower limits of the output power of a single fuel cell, It is the maximum amount of hydrogen that flows from the hydrogen storage tank to a single fuel cell per unit time.

[0030] Preferably, the feedback optimization strategy includes:

[0031] The Lagrangian function of the electric-hydrogen composite energy storage system is constructed, and the Lagrangian function is:

[0032]

[0033] Where L is the Lagrangian function, f is the loss cost of the electric-hydrogen composite energy storage system, is the wind power adjusted by energy storage, is the predicted power of the wind farm at time t, P t W.up is the predicted power upper limit of the wind farm at time t, P t W.dn is the lower limit of wind farm power forecast at time t, x up and x dn are the upper and lower limit coefficients of the predicted power of the wind farm, and μ t are the upper and lower multipliers of the Grangian function at time t, and s are the correction factors for exceeding the upper and lower limits of wind power, and β is the step size factor.

[0034] Preferably, the real-time updating of the electrochemical energy storage system power and the hydrogen energy storage system power according to the feedback optimization strategy comprises:

[0035] The Lagrangian function is used to obtain the partial derivative of the power of the battery cell to obtain the updated electrochemical energy storage system power:

[0036]

[0037] In the formula, is a range-limited function that limits y to Inside, r is the penalty parameter;

[0038] The Lagrangian function is used to obtain the partial derivative of the power of the hydrogen storage unit to obtain the updated hydrogen energy storage system power:

[0039]

[0040] In the formula, is a range-limited function that limits y to , r is the penalty parameter.

[0041] Preferably, based on the updated power of the electrochemical energy storage system and the power of the hydrogen energy storage system, the wind power after energy storage adjustment is calculated according to the following formula:

[0042]

[0043] in, is the maximum wind power output of the wind farm at time t, is the wind power abandoned at time t.

[0044] Preferably, the parameters of adjusting the feedback optimization strategy include:

[0045]

[0046] In a second aspect, the present invention provides a real-time feedback optimization device for an electric-hydrogen composite energy storage system, comprising:

[0047] The first building block is used to construct the optimization objective function and operation constraints of the electric-hydrogen composite energy storage system;

[0048] A second building module is used to build a feedback optimization strategy according to the wind power output by the wind farm and the optimization objective function;

[0049] An updating module, used for updating the power of the electrochemical energy storage system and the power of the hydrogen energy storage system in real time according to the feedback optimization strategy;

[0050] A calculation module, used for calculating the wind power after energy storage adjustment according to the updated electrochemical energy storage system power and hydrogen energy storage system power;

[0051] The adjustment module is used to adjust the parameters of the feedback optimization strategy and re-update the power of the electrochemical energy storage system and the power of the hydrogen energy storage system if the adjusted wind power exceeds the upper and lower limits of the preset predicted wind power.

[0052] In a third aspect, the present invention provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the real-time feedback optimization method for an electric-hydrogen composite energy storage system.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] The present invention can update the feedback optimization strategy when the predicted wind power exceeds the preset range, and fully considers the demand for reducing the predicted deviation of the wind power output by the wind farm. At the same time, the present invention can update the power of the electrochemical energy storage system and the power of the hydrogen energy storage system in real time under the objective function and constraint conditions through the feedback optimization strategy, and takes the battery unit charge state and the hydrogen storage state of the hydrogen storage unit as the penalty function, so that the power of the electrochemical energy storage system and the power of the hydrogen energy storage system updated under different wind farm operating conditions can have better rationality, and fully considers the physical operating characteristics of electrochemical energy storage and hydrogen energy storage to obtain the better power of electrochemical energy storage and hydrogen energy storage, which has the advantages of scientific rationality, strong applicability and good effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 It is a flowchart of the real-time feedback optimization method of the electric-hydrogen composite energy storage system in Example 1;

[0056] Figure 2 This is a comparison chart of wind power before and after stabilization in the application example;

[0057] Figure 3 This is a comparison chart of the power exceeding the upper and lower limits before and after smoothing in the application example;

[0058] Figure 4 The SOC and power variation diagram of ten battery cells in the application example;

[0059] Figure 5 The SOH and power variation diagram of ten hydrogen storage units in the application example;

[0060] Figure 6 It is the enlarged image exceeding the upper limit and its gradient effect image in the application example;

[0061] Figure 7 This is a diagram showing the charging power effects of electrochemical energy storage and hydrogen energy storage in the application example;

[0062] Figure 8 It is the enlarged image below the lower limit and its gradient effect image in the application example;

[0063] Fig. 9 This is a diagram showing the discharge power effects of electrochemical energy storage and hydrogen energy storage in the application example;

[0064] Fig.10 This is an enlarged diagram of wind power within the range and a gradient effect diagram of the five intervals in the application example. DETAILED DESCRIPTION

[0065] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and the like are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, features defined as "first", "second", and the like may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "multiple" means two or more. In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood by specific circumstances.

[0066] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the protection scope of the present invention.

[0067] Example 1

[0068] Combination Figure 1 This embodiment provides a real-time feedback optimization method for an electric-hydrogen composite energy storage system, which includes:

[0069] Step 1: construct an optimization objective function for realizing energy adaptive adjustment of the electric-hydrogen composite energy storage system. The objective function is:

[0070]

[0071] Where Min represents minimization, f is the loss cost of the electric-hydrogen composite energy storage system, C V is the operating cost of the electric-hydrogen hybrid energy storage system, is the power of the ith battery cell at time t, is the power of the i-th hydrogen storage unit at time t, λ BESS and λ HESS are the operating cost coefficients of the electrochemical energy storage system and the hydrogen energy storage system, Δt is the unit time interval, is the penalty function for the state of charge, is the penalty function regarding the hydrogen storage state;

[0072] In order to facilitate the solution of the objective function formula (1) while satisfying the inequality constraints of SOC and SOH, the inequality constraints are integrated into the objective function in the form of penalty functions, and then the augmented objective function is constructed, which is shown in formula (2).

[0073] Penalty function for state of charge:

[0074]

[0075] In the formula, γ is the penalty factor, δ1 is the parameter of electrochemical energy storage, SOC t.i is the state of charge of the ith battery cell at time t, SOC max and SOC min They are the upper and lower limits of the state of charge of a single battery cell respectively.

[0076] Penalty function for hydrogen storage state:

[0077]

[0078] In the formula, γ is the penalty factor, δ1 and δ2 are the parameters of electrochemical energy storage and hydrogen energy storage, respectively, and SOC t.iis the state of charge of the ith battery cell at time t, SOC max and SOC min They are the upper and lower limits of the state of charge of a single battery cell, SOH t.i is the hydrogen storage state of the hydrogen storage tank in the i-th hydrogen storage unit at time t, SOH max and SOH min They are respectively the upper and lower limits of the hydrogen storage state of the hydrogen storage tank.

[0079] Step 2: Construct the operating constraints of the hydrogen energy storage system and the electrochemical energy storage system.

[0080] 1) The operating constraints of the electrochemical energy storage system are:

[0081]

[0082] In the formula, is the energy of the i-th battery cell at time t, η BESS.E and η BESS.F are the battery charge and discharge efficiency, Q BESS is the capacity of the battery, is the power of the electrolytic cell in the i-th battery unit at time t, is the power of the fuel cell in the i-th battery unit at time t;

[0083] 2) The operating constraints of the hydrogen energy storage system are:

[0084] (a) Electrolyzer constraints:

[0085]

[0086] Where η elec is the hydrogen production efficiency of the electrolyzer of the hydrogen storage unit, is the mass of hydrogen produced by the electrolyzer in the i-th hydrogen storage unit at time t, H is the calorific value of hydrogen, P elec.max and P elec.min are the upper and lower limits of the input power of a single electrolyzer of the hydrogen storage unit, is the maximum amount of hydrogen that flows into the hydrogen storage tank per unit time for a single electrolyzer of the hydrogen storage unit. Based on the inequality constraint of formula (7) and the relationship expression of formula (6), the power constraint at this time can be deduced as formula (8). The electrolyzer has two constraints, namely, formula (7) and (8). The smaller value of the two constraints is taken as the upper limit of the electrolyzer input power, thereby obtaining the constraint of the electrolyzer input power, which is specifically shown in formula (9).

[0087] (b) Hydrogen storage tank constraints:

[0088]

[0089] SOH min≤SOH t.i ≤SOH max (11)

[0090] In the formula, Q HS is the capacity of the hydrogen storage tank, is the amount of hydrogen consumed by the fuel cell in the i-th hydrogen storage unit at time t.

[0091] (c) Fuel cell constraints:

[0092]

[0093] Where η FC is the efficiency of the fuel cell hydrogen energy conversion into electrical energy in the hydrogen storage unit, P HESS.F.max and P HESS.F.min are the upper and lower limits of the output power of a single fuel cell, is the maximum amount of hydrogen that flows from the hydrogen storage tank to a single fuel cell per unit time. From the inequality constraint of formula (13) and the relational expression in formula (12), the power constraint at this time can be deduced as formula (14). The fuel cell has two constraints, formula (13) and (14). The smaller value of the two constraints is taken as the upper limit of the fuel cell output power, thereby obtaining the constraint of the fuel cell output power, as shown in formula (15).

[0094] Step 3, design a real-time feedback optimization strategy for the electric-hydrogen composite energy storage system based on measurement feedback. The Lagrangian function of the electric-hydrogen composite energy storage system based on measurement feedback is:

[0095]

[0096] Where L is the Lagrangian function, f is the loss cost of the electric-hydrogen composite energy storage system, is the wind power adjusted by energy storage, is the predicted power of the wind farm at time t, P t W.up is the predicted power upper limit of the wind farm at time t, P t W.dn is the lower limit of wind farm power forecast at time t, x up and x dn are the upper and lower limit coefficients of the predicted power of the wind farm, and μ t are the upper and lower multipliers of the Grangian function at time t, and s are the correction factors exceeding the upper and lower limits of wind power, respectively, and β is the step size factor;

[0097] Design a real-time feedback optimization strategy for the electric-hydrogen hybrid energy storage system based on measurement feedback, including partial derivatives of the Lagrangian function, specifically:

[0098] (a) The partial derivative of the Lagrangian function with respect to the power of the battery cell is:

[0099]

[0100] In the formula, is a range-limited function that limits y to In the equation, r is the penalty parameter. (b) The partial derivative of the Lagrangian function with respect to the power of the hydrogen storage unit is:

[0101]

[0102] According to equations (19) and (21), the initial distributed power of the electric-hydrogen composite energy storage system can be obtained. To calculate the wind power after energy storage adjustment, is the maximum wind power output of the wind farm at time t, is the wind power abandoned at time t.

[0103] If the adjusted wind power is not within the upper and lower limits of the predicted wind power, the strategy of this paper needs to be used to adjust the upper and lower multipliers, that is:

[0104]

[0105] Step 4: Analyze and adjust the real-time feedback optimization strategy based on the measurement feedback.

[0106] According to the different intervals of SOC and SOH, in the penalty function interval of formula (3), from low to high, they are the first SOC interval, the second SOC interval, the third SOC interval, the fourth SOC interval, and the fifth SOC interval; in the penalty function interval of formula (4), from low to high, they are the first SOH interval, the second SOH interval, the third SOH interval, the fourth SOH interval, and the fifth SOH interval), and P t W.act (the actual output power of the wind farm at time t) and P t W.dn The relationship between can be used to obtain the energy storage distribution under the control strategy of this paper:

[0107] (1) When the SOC is in the first SOC range or the second SOC range

[0108] a) SOH is in the first SOH interval or the second SOH interval, when P t W.act >P t W.dn When energy storage charging is required, if the power of the battery unit is higher than its maximum power, then P t.iBESS.E =P BESS.E.max , if the power of the hydrogen storage unit is higher than its maximum power, then as shown in formula (23):

[0109]

[0110] When P t W.act <P t W.dn When the battery is in a state of low energy consumption, the battery needs to store energy and discharge it. Since the frequent start and stop of the electrolyzer of the battery unit causes large losses and has a great impact on the life of the electrolyzer, the electrolyzer of the battery unit is operated at hot standby power, that is, P t.i BESS.E =P elec.min .

[0111] b) SOH is in the third SOH interval, the fourth SOH interval, or the fifth SOH interval, when P t W.act >P t W.dn When P is reached, energy storage charging is required. At this time, the SOC is at a lower state, while the SOH state is higher, and the electrochemical energy storage system is charged first. t W.act <P t W.dn When energy storage and discharge are required, the SOC state is lower than the SOH state, and the hydrogen energy storage system discharges first.

[0112] (2) When SOC is in the third SOC range

[0113] a) SOH is in the first SOH interval or the second SOH interval, when P t W.act >P t W.dn When P is reached, energy storage charging is required. At this time, the SOC is at a higher state, while the SOH state is lower, and the hydrogen energy storage system is charged first. t W.act <P t W.dn , energy storage and discharge are required, the SOC state is higher than the SOH state, and the electrochemical energy storage system discharges first.

[0114] b) SOH is in the third SOH interval, the fourth SOH interval, and the fifth SOH interval. When P t W.act >P t W.dn When P is reached, energy storage charging is required. At this time, the SOC is at a lower state, while the SOH state is higher, and the electrochemical energy storage system is charged first. t W.act <Pt W.dn When energy storage and discharge are required, the SOC state is lower than the SOH state, and the hydrogen energy storage system discharges first.

[0115] (3) When the SOC is in the fourth SOC interval or the fifth SOC interval

[0116] a) SOH is in the first SOH interval, the second SOH interval or the third SOH interval, when P t W.act >P t W.dn When P is reached, energy storage charging is required. At this time, the SOC is at a higher state, while the SOH state is lower, and the hydrogen energy storage system is charged first. t W.act <P t W.dn When energy storage and discharge are required, the SOC state is higher than the SOH state, and the electrochemical energy storage system discharges first.

[0117] b) SOH is in the fourth SOH interval or the fifth SOH interval, when P t W.act >P t W.dn When the SOC is high, the SOH is low, and the hydrogen energy storage is charged first. If the electrolyzer is operated at the minimum power, the SOH t.i ≤SOHmax, then charging can continue. When the electrolyzer is running at minimum power, SOH t.i >SOHmax, for the safety of the hydrogen storage tank, the fuel cell needs to discharge; when P t W.act <P t W.dn When the energy storage discharge is required, the SOC state is higher than the SOH state, and the electrochemical energy storage system discharges first. If the electrochemical energy storage power is higher than its maximum power at this time, then P t.i BESS.F =P BESS.F.max , if the power of the hydrogen storage unit is higher than its maximum power, then as shown in formula (24):

[0118]

[0119] This embodiment also provides a real-time feedback optimization strategy for an electricity-hydrogen composite energy storage system that reduces wind farm output power prediction deviation.

[0120] Application Examples

[0121] Based on a wind farm with an installed capacity of 200MW, the capacity of the electrochemical energy storage system is 15MW and the capacity of the hydrogen energy storage system is 20MW, and the effectiveness of the method of the present invention is analyzed. The configuration parameters of the electrochemical energy storage and hydrogen energy storage are shown in Table 1 and Table 2. In order to verify the effectiveness of the strategy proposed in this paper, the sampling period is 7 days and the sampling interval is 1 second.

[0122] Table 1 Electrochemical energy storage related parameters

[0123] parameter Numeric Rated Power 5MW Rated capacity 15KWh State of charge upper / lower limit 0.9 / 0.1 Charge / discharge efficiency 0.85～09 Electrochemical battery cell 10

[0124] Table 2 Hydrogen energy storage related parameters

[0125] parameter Numeric Number of electrolyzer units 10 Calorific value 33.3KWh / kg Electrolyzer input power upper / lower limit 5 / 0.5MW Maximum hydrogen production per unit time of electrolyzer 10kg / h Electrolyzer efficiency 0.62～0.67 Number of hydrogen storage tank units 10 Maximum amount of hydrogen flowing in / out of the storage tank per unit time 20 / 20kg / h Hydrogen storage state upper / lower limit 0.9 / 0.1 Hydrogen storage tank capacity 5.6m3 Number of fuel cell units 10 Fuel cell efficiency 0.62～0.67 Fuel cell power limit 5MW

[0126] The method of the present invention is used to compare the wind power before and after leveling and the power exceeding the upper and lower limits before and after leveling. The results are as follows Figure 2 , Figure 3 As can be seen from the figure, the wind power before leveling exceeded the upper limit at 740 to 800 seconds, and was below the lower limit at 3200 to 3400 seconds, while the wind power after leveling was within the upper and lower limits in the above interval. In the figure of the power exceeding the upper and lower limits before and after leveling, "××" represents the part of the wind power exceeding its upper limit, and "circle" represents the part of the wind power below its lower limit. After adjustment according to the strategy proposed in this paper, the power exceeding the upper and lower limits after leveling is about 0.1MW, while the power exceeding the upper and lower limits before adjustment is about 3MW. It can be seen that the wind power curve after regulation tends to be stable and the fluctuation is significantly reduced. This shows that the regulation strategy adopted in this paper can effectively reduce the volatility of wind power, making it more controllable, thereby better meeting the requirements of the power system for wind power output.

[0127] Comparing the power and SOC of the battery unit and the power and SOH of the hydrogen storage unit, the results are as follows Figure 4 , Figure 5 As shown, Figure 4The distribution of power inside the battery cell is shown, where all powers fluctuate within the range of -0.5MW to 0.5MW, and no situation occurs outside this range. This shows that the internal power distribution strategy of the battery cell proposed in this paper has good effectiveness. Due to the difference in power inside the battery cell and the introduction of the penalty function, the SOC of each battery cell is also different, but the overall trend of change is the same. The SOC of each battery cell changes relatively slowly in the range of 0.3 to 0.7, and the curve changes tend to be stable; in the range of 0.2 to 0.3 and 0.7 to 0.8, the SOC curve changes faster; in the range of 0.1 to 0.2 and 0.8 to 0.9, the SOC curve changes significantly faster. By quickly adjusting the power distribution, the system can effectively pull the SOC back to a more ideal range, thereby avoiding the risk of overcharging or discharging. These results prove that the strategy in this paper can effectively manage the SOC of the battery cell under various working conditions to ensure the safety and effectiveness of the system.

[0128] Figure 5 The power distribution inside the hydrogen storage unit is shown, where all powers fluctuate within the range of -0.5MW to 0.5MW, and there is no situation outside this range. Due to the difference in power inside the hydrogen storage unit and the introduction of the penalty function, the SOH of each hydrogen storage unit is also different, but the change trend of SOH in each interval is the same as SOC. Considering the high charging and discharging loss of hydrogen energy storage and the low energy density of electrochemical energy storage, the penalty function of hydrogen energy storage is set greater than the penalty function of electrochemical energy storage, so the SOC will change frequently and the SOH will change relatively slowly. Overall, by comparing the SOC and SOH curves of electrochemical energy storage and hydrogen energy storage, it can be seen that the dynamic response characteristics of different energy storage systems under the corresponding control strategies. Hydrogen energy storage and electrochemical energy storage undertake long and short-term charging and discharging tasks respectively, which reduces the loss of hydrogen energy storage and maintains the battery SOC within the allowable range.

[0129] Furthermore, in order to study the power distribution and changes in more detail, we further zoom in on a specific interval for analysis. Figure 6 As shown in the figure, the time period between 740 and 800 seconds is selected to magnify the situation where the wind power exceeds the upper limit. When the actual wind power exceeds its upper limit, according to the strategy of this paper, the gradient is increased by adjusting the supermultiplier. The larger the gradient, the more negative the power at the next moment tends to be (in this paper, negative values ​​represent charging, and positive values ​​represent discharging). Therefore, the increase in the gradient will make the system tend to perform more charging operations at the next moment. The charging power of electrochemical energy storage and hydrogen energy storage increases with the increase in the gradient. When charging, the energy storage system can effectively reduce the power adjusted by the energy storage. Figure 8As shown in the figure, the time period between 3200 and 3400 seconds is selected to magnify the situation where the wind power is lower than the lower limit. When the actual wind power is lower than its lower limit, according to the strategy of this article, the lower multiplier should be adjusted to reduce the gradient. The reduction in the gradient will cause the power at the next moment to tend to a positive value. Therefore, the reduction in the gradient will make the system tend to perform more discharge operations at the next moment. When the energy storage system is discharging, it can effectively increase the power adjusted by the energy storage. The charging power effect diagram of electrochemical energy storage and hydrogen energy storage is shown in the figure. Figure 7 As shown, the discharge power effect diagram of electrochemical energy storage and hydrogen energy storage is as follows Fig. 9 Further, Fig.10 As shown in the figure, the time period between 40,000 seconds and 60,000 seconds is selected to magnify the situation where the wind power is within its upper and lower limits. When the actual wind power is within its upper and lower limits, the upper and lower multipliers are 0, and the size of the gradient is determined by the penalty function. When the electrochemical energy storage / hydrogen energy storage is in intervals one and five, the gradient is very large, and the electrochemical energy storage / hydrogen energy storage system can quickly approach interval three; when the electrochemical energy storage / hydrogen energy storage is in intervals two and four, the gradient is large, and the electrochemical energy storage / hydrogen energy storage can also move quickly to interval three; and when the electrochemical energy storage / hydrogen energy storage is in interval three, the gradient is very small, so the electrochemical energy storage / hydrogen energy storage will remain in this stable range. It can be seen that this article can effectively adjust the operating state of electrochemical energy storage / hydrogen energy storage and improve the life of the system through reasonable gradient control.

[0130] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0131] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0132] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0133] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0134] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the enlightenment of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the purpose of the present invention and the claims, which all fall within the protection of the present invention.

Claims

1. A real-time feedback optimization method for an electric-hydrogen composite energy storage system, characterized in that: include: Construct the optimization objective function and corresponding operation constraints of the electric-hydrogen hybrid energy storage system; Constructing a feedback optimization strategy based on the wind power output by the wind farm and the optimization objective function; updating the electrochemical energy storage system power and the hydrogen energy storage system power in real time according to the feedback optimization strategy; Calculate the wind power power after energy storage adjustment based on the updated electrochemical energy storage system power and hydrogen energy storage system power; If the adjusted wind power exceeds the preset upper and lower limits of the predicted wind power, the parameters of the feedback optimization strategy are adjusted, and the power of the electrochemical energy storage system and the power of the hydrogen energy storage system are re-updated.

2. A real-time feedback optimization method for an electric-hydrogen composite energy storage system according to claim 1, characterized in that: The optimization objective function of the electric-hydrogen composite energy storage system includes: In the formula, Min represents minimization, f is the loss cost of the electric-hydrogen composite energy storage system, C V is the operating cost of the electric-hydrogen hybrid energy storage system, is the power of the ith battery cell at time t, is the power of the i-th hydrogen storage unit at time t, λ BESS and λ HESS are the operating cost coefficients of the electrochemical energy storage system and the hydrogen energy storage system, Δt is the unit time interval, is the penalty function for the state of charge, is the penalty function for the hydrogen storage state; γ is the penalty factor, δ1 and δ2 are the parameters of the electrochemical energy storage system and the hydrogen energy storage system, respectively, SOC t.i is the state of charge of the ith battery cell at time t, SOC max and SOC min The upper and lower limits of the state of charge of a single battery cell, SOH t.i is the hydrogen storage state of the hydrogen storage tank in the i-th hydrogen storage unit at time t, SOH max and SOH min They are respectively the upper and lower limits of the hydrogen storage state of the hydrogen storage tank.

3. A real-time feedback optimization method for an electric-hydrogen composite energy storage system according to claim 2, characterized in that: The operation constraints include the operation constraints of the electrochemical energy storage system and the operation constraints of the hydrogen energy storage system. The operation constraints of the electrochemical energy storage system include: In the formula, is the energy of the i-th battery cell at time t, η BESS.E and η BESS.F are the charge and discharge efficiency of the battery unit, Q BESS is the capacity of the battery cell, is the power of the electrolyzer in the i-th hydrogen storage unit at time t, is the power of the fuel cell in the i-th hydrogen storage unit at time t; The operating constraints of the hydrogen energy storage system include: Electrolyzer Constraints: In the formula, is the power of the electrolyzer in the i-th hydrogen storage unit at time t, η elec is the hydrogen production efficiency of the electrolyzer of the hydrogen storage unit, is the mass of hydrogen produced by the electrolyzer in the i-th hydrogen storage unit at time t, H is the calorific value of hydrogen, P elec.max and P elec.min are the upper and lower limits of the input power of a single electrolyzer of the hydrogen storage unit, The maximum amount of hydrogen that flows into the hydrogen storage tank per unit time for a single electrolyzer of the hydrogen storage unit; Hydrogen storage tank constraints: SOH min ≤SOH t.i ≤SOH max In the formula, Q HS is the capacity of the hydrogen storage tank, is the amount of hydrogen consumed by the fuel cell in the i-th hydrogen storage unit at time t; is the amount of hydrogen consumed by the fuel cell in the i-th hydrogen storage unit at time t; Fuel cell constraints: Where η FC The efficiency of the fuel cell that converts hydrogen energy into electrical energy for the hydrogen storage unit, is the power of the fuel cell in the i-th hydrogen storage unit at time t, P HESS.F.max and P HESS.F.min are the upper and lower limits of the output power of a single fuel cell, It is the maximum amount of hydrogen that flows from the hydrogen storage tank to a single fuel cell per unit time.

4. A real-time feedback optimization method for an electric-hydrogen composite energy storage system according to claim 3, characterized in that: The feedback optimization strategy includes: The Lagrangian function of the electric-hydrogen composite energy storage system is constructed, and the Lagrangian function is: Where L is the Lagrangian function, f is the loss cost of the electric-hydrogen composite energy storage system, is the wind power adjusted by energy storage, is the predicted power of the wind farm at time t, P t W.up is the predicted power upper limit of the wind farm at time t, P t W.dn is the lower limit of wind farm power forecast at time t, x up and x dn are the upper and lower limit coefficients of the predicted power of the wind farm, and μ t are the upper and lower multipliers of the Grangian function at time t, and s are the correction factors for exceeding the upper and lower limits of wind power, and β is the step size factor.

5. A real-time feedback optimization method for an electric-hydrogen composite energy storage system according to claim 4, characterized in that: The real-time updating of the electrochemical energy storage system power and the hydrogen energy storage system power according to the feedback optimization strategy includes: The Lagrangian function is used to obtain the partial derivative of the power of the battery cell to obtain the updated electrochemical energy storage system power: In the formula, is a range-limited function that limits y to Inside, r is the penalty parameter; The Lagrangian function is used to obtain the partial derivative of the power of the hydrogen storage unit to obtain the updated hydrogen energy storage system power: In the formula, is a range-limited function that limits y to , r is the penalty parameter.

6. A real-time feedback optimization method for an electric-hydrogen composite energy storage system according to claim 5, characterized in that: Based on the updated power of the electrochemical energy storage system and the power of the hydrogen energy storage system, the wind power after energy storage adjustment is calculated according to the following formula: in, is the maximum wind power output of the wind farm at time t, is the wind power abandoned at time t.

7. A real-time feedback optimization method for an electric-hydrogen composite energy storage system according to claim 6, characterized in that: The parameters of adjusting the feedback optimization strategy include:

8. A real-time feedback optimization device for an electric-hydrogen composite energy storage system, characterized in that: include: The first building block is used to construct the optimization objective function and operation constraints of the electric-hydrogen composite energy storage system; A second building module is used to build a feedback optimization strategy according to the wind power output by the wind farm and the optimization objective function; An updating module, used for updating the power of the electrochemical energy storage system and the power of the hydrogen energy storage system in real time according to the feedback optimization strategy; A calculation module, used for calculating the wind power after energy storage adjustment according to the updated electrochemical energy storage system power and hydrogen energy storage system power; The adjustment module is used to adjust the parameters of the feedback optimization strategy and re-update the power of the electrochemical energy storage system and the power of the hydrogen energy storage system if the adjusted wind power exceeds the upper and lower limits of the preset predicted wind power.

9. A storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the real-time feedback optimization method for an electric-hydrogen composite energy storage system according to any one of claims 1 to 7 is implemented.

Images