Photovoltaic and hydrogen energy storage multi-time scale capacity planning method considering demand response

Abstract

The invention relates to the technical field of new energy storage application, and provides a photovoltaic and hydrogen energy storage multi-time scale capacity planning method considering demand response, comprising the following steps: constructing a user response model according to user power demand response; constructing a hydrogen energy storage system model, including constructing an electrolytic cell model and a fuel cell model; according to the user response model and the hydrogen energy storage system model, establishing a photovoltaic-hydrogen storage system multi-time scale capacity planning model considering the system cost and the system benefit, wherein the photovoltaic-hydrogen storage system multi-time scale capacity planning model comprises an objective function and constraint conditions; and calculating the capacity plan of hydrogen energy storage based on the photovoltaic-hydrogen storage system multi-time scale capacity planning model. According to the method, the capacity planning model is constructed by considering the demand response and combining different characteristics of the hydrogen energy storage system under multiple time scales, so that the accurate constant volume of the hydrogen energy storage capacity is realized, and the large-scale redundant configuration of hydrogen production-storage equipment is avoided.

Description

Technical Field

[0001] The present invention relates to the field of new energy storage application technology, and in particular to a photovoltaic and hydrogen energy storage multi-time scale capacity planning method considering demand response. Background Art

[0002] At present, as an important power source component of the large power grid, the output volatility and anti-peak characteristics of photovoltaics have become key factors restricting their efficient utilization. This factor has directly led to a significant phenomenon of abandoned light, posing a severe challenge to the utilization efficiency and environmental benefits of photovoltaics.

[0003] To meet this challenge, relevant scholars have explored increasing the capacity of energy storage systems to smooth out the fluctuations in photovoltaic output, in order to achieve stable operation of the power grid and maximize the use of photovoltaics. However, this strategy faces many technical bottlenecks and economic considerations. The initial investment, daily operation and maintenance, and future replacement costs of energy storage equipment are high. If the scale of energy storage is expanded blindly, it may not only lead to redundant configuration of equipment resources, but also cause major coordination problems between cost and benefit, affecting overall economic efficiency and sustainable development.

[0004] Therefore, it is particularly necessary to explore effective cost-effectiveness optimization strategies to balance the economic pressure brought about by the increase in energy storage capacity and the need to improve grid stability, ensure that the energy storage system can fully exert its flexible adjustment efficiency, and optimize the capacity configuration strategy of new energy storage devices. Summary of the invention

[0005] The purpose of the present invention is to solve at least one technical problem in the background technology and to provide a multi-time scale capacity planning method for photovoltaic and hydrogen energy storage considering demand response.

[0006] To achieve the above objectives, the present invention provides a multi-time scale capacity planning method for photovoltaic and hydrogen energy storage considering demand response, comprising:

[0007] Build a user response model based on user electricity demand response;

[0008] Construct a hydrogen energy storage system model, including an electrolyzer model and a fuel cell model;

[0009] According to the user response model and the hydrogen energy storage system model, a multi-time scale capacity planning model of a photovoltaic-hydrogen storage system considering system cost and system benefit is established, including: an objective function and constraint conditions;

[0010] The objective function is constructed based on system cost and system benefit; the constraints include: power balance constraint, system equivalent power balance constraint, grid-connected power constraint, hydrogen storage tank capacity constraint, hydrogen supply reliability constraint, demand response load reduction constraint and ramp constraint;

[0011] The capacity planning of hydrogen energy storage is calculated based on the multi-time scale capacity planning model of photovoltaic-hydrogen storage system.

[0012] According to one aspect of the present invention, the user response model is a time-of-use electricity price demand response model:

[0013]

[0014] Where: ΔP L,t To introduce the load change after demand response, is the load value before the system demand response, -ξ is the time-of-use electricity price demand response coefficient, q t is the electricity price in period t, is the electricity price before demand response at time t, P Dmax and P Dmin are the maximum and minimum power consumption respectively;

[0015] Among them, the following constraints are imposed on electricity prices:

[0016]

[0017] Where: and is the peak and valley value of the time-of-use electricity price, δ max and δ min They are the maximum and minimum values ​​of the peak-to-valley electricity price ratio respectively.

[0018] According to one aspect of the present invention, the electrolytic cell model is:

[0019] P el.min ≤P el (t)≤P el.max ;

[0020] P el.min =0.5P el.max ;

[0021] Where: P el (t) is the input power of the electrolytic cell; P el.min , P el.max They are the minimum and maximum operating power of the electrolyzer under grid-connected conditions;

[0022] The fuel cell model is:

[0023] P fc (t) = H fc (t)η fc H LHV ;

[0024] 0≤P fc (t)≤P fc.max ;

[0025] Where: P fc (t) is the power of the fuel cell module; P fc.max is the nominal power of the fuel cell module; η fc is the power generation efficiency of the fuel cell; H fc (t) is the real-time hydrogen consumption of the fuel cell; H LHV It is the low calorific value of hydrogen.

[0026] According to one aspect of the present invention, the system cost includes:

[0027] Annual investment cost f1 for electrolyzer, compressor, hydrogen storage tank and fuel cell:

[0028]

[0029] Where: i is 1, 2, 3, 4, Q1, Q2, Q3 are the unit capacities of electrolyzer, hydrogen storage tank and fuel cell respectively; Q4 is the unit capacity of converter; C1 is the unit capacity price of electrolyzer; C2 is the unit capacity price of compressor; C3 and C4 are the unit capacity prices of hydrogen storage tank and fuel cell transmission project respectively; L i is the project life; ω is the equipment depreciation rate;

[0030] The annual operation and maintenance cost f2 and electricity purchase cost f3 are expressed as:

[0031]

[0032] Where: P s (t), ζ s (t) are the purchased power and the purchased power cost respectively; l i The proportion of hydrogen energy system operation and maintenance costs to investment costs;

[0033] The penalty cost f4 for abandoning solar power and the penalty cost f5 for lack of hydrogen are expressed as:

[0034]

[0035] Where: pv P is the penalty cost coefficient for abandoned light; pv.cut (t) is the abandoned light power; pv (t) is the on-grid electricity price of photovoltaic power generation; ph (t) is the real-time hydrogen price in the market; λ ph Penalize cost factor for hydrogen shortage; D dm (t) is the real-time demand for hydrogen energy, D sh (t) is the real-time available supply of hydrogen energy;

[0036] The system load response cost f6 is expressed as:

[0037]

[0038] Where: a and b represent the linear coefficients of demand and electricity price;

[0039] The system benefits include:

[0040] The system's hydrogen sales revenue f7 and power supply revenue f8 are expressed as:

[0041]

[0042] Where: P pv (t) represents the photovoltaic power generation;

[0043] The objective function is:

[0044] maxf=f7+f8-f1-f2-f3-f4-f5-f6.

[0045] According to one aspect of the present invention, the power balance constraint is:

[0046] P pv.on (t)+P pv.cut (t)+P el (t) = P pv (t);

[0047] Where: P pv.on (t) is the photovoltaic grid-connected power;

[0048] The equivalent power balance constraint of the system is that the electrolyzer produces hydrogen, which is compressed by a compressor and stored in a hydrogen storage tank or sold directly:

[0049]

[0050] Among them, the amount of hydrogen stored in the hydrogen storage tank is:

[0051] Q tan (t) = Q tan (t-1)+Q in (t)-Q sh (t)-Q fc (t);

[0052] D sh (t) = Q sh (t)δ;

[0053] Where: Q tan (t) is the hydrogen storage capacity at time t; Q in (t) is the amount of hydrogen compressed into the hydrogen storage tank by the compressor; Q tan (t-1) is the hydrogen storage capacity at time t-1; Qfc (t) is the hydrogen consumption of the fuel cell at time t; Q sh (t) is the amount of hydrogen sold at time t; δ is the mass volume fraction of high-pressure hydrogen;

[0054] The grid-connected power constraint is:

[0055] 0≤P pv.on +P fc (t)≤P bpv ;

[0056] Where: P bpv The upper limit of photovoltaic grid-connected capacity;

[0057] The hydrogen storage tank capacity constraint is:

[0058] 0.1Q tan ≤Q tan (t)≤0.9Q tan ;

[0059] Where: Q tan is the maximum capacity of the hydrogen storage tank;

[0060] The hydrogen supply reliability constraint is:

[0061]

[0062] Where: T is the number of points in the selected sampling interval;

[0063] The demand response load reduction constraint and ramp constraint include:

[0064]

[0065] 0≤ΔP L,t -ΔP L,t-1 ≤P LU ;

[0066] 0≤ΔP L,t-1 -ΔP L,t ≤P LD ;

[0067]

[0068] Where: is the maximum load reduction at time t, ΔP L,t-1 is the load change after the demand response is introduced at the next moment, v t is a 0-1 state variable; P LU and P LD The upper and lower limits of the load shedding ramp; is the maximum load value at time t, S max The maximum load reduction amount.

[0069] According to one aspect of the present invention, the constraint condition further includes:

[0070] Loads can only be transferred in or out within the same dispatch cycle, that is, the transfer period should meet the following requirements:

[0071] t′∈T,t″∈T;

[0072] Where: t′ is the load transfer-in period; t″ is the load transfer-out period;

[0073] Load transfer constraints:

[0074] The load transfer amount should satisfy the requirement that the total load demand before and after the demand response remains unchanged within a dispatching cycle, and the load transfer amount at each moment should not exceed the maximum load transfer amount:

[0075]

[0076] Where: Δt is the time interval.

[0077] Furthermore, to achieve the above-mentioned purpose, the present invention also provides a photovoltaic and hydrogen energy storage multi-time scale capacity planning system considering demand response, comprising:

[0078] A user response model building module, which builds a user response model according to the user's power demand response;

[0079] A hydrogen energy storage system model building module is used to build a hydrogen energy storage system model, including an electrolyzer model and a fuel cell model;

[0080] A photovoltaic-hydrogen storage system multi-time scale capacity planning model building module is used to build a photovoltaic-hydrogen storage system multi-time scale capacity planning model that takes into account system costs and system benefits based on the user response model and the hydrogen energy storage system model, including: objective functions and constraints;

[0081] The objective function is constructed based on system cost and system benefit; the constraints include: power balance constraint, system equivalent power balance constraint, grid-connected power constraint, hydrogen storage tank capacity constraint, hydrogen supply reliability constraint, demand response load reduction constraint and ramp constraint.

[0082] The hydrogen energy storage capacity planning calculation module calculates the capacity planning of hydrogen energy storage based on the multi-time scale capacity planning model of the photovoltaic-hydrogen storage system.

[0083] Furthermore, to achieve the above-mentioned purpose, the present invention also provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, the multi-time-scale capacity planning method for photovoltaic and hydrogen energy storage considering demand response as described above is implemented.

[0084] Furthermore, to achieve the above objectives, the present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the multi-time-scale capacity planning method for photovoltaic and hydrogen energy storage considering demand response as described above is implemented.

[0085] According to the solution of the present invention, by increasing demand response, when the power load is too high but the sunlight is insufficient resulting in less photovoltaic power generation, by setting a higher electricity price, users can reduce electricity consumption or not use it during this period, thereby effectively reducing the maximum load and reducing the demand for energy storage discharge; when the power load is too low but the sunlight is sufficient resulting in more photovoltaic power generation, by lowering the electricity price, users can transfer their electricity demand from other periods to this period, thereby effectively absorbing photovoltaic power and reducing energy storage, and calculating the capacity planning of hydrogen energy storage.

[0086] According to the solution of the present invention, the present invention can solve the problem that due to the high initial investment, daily operation and maintenance and future replacement costs of energy storage equipment, if the energy storage scale is blindly expanded, it may lead to redundant configuration of equipment resources.

[0087] According to the solution of the present invention, the present invention constructs a capacity planning model by considering demand response and combining the different characteristics of the hydrogen energy storage system at multiple time scales, thereby achieving accurate capacity determination of the hydrogen energy storage capacity and avoiding large-scale redundant configuration of hydrogen production and storage equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0088] Figure 1 A flowchart schematically shows a method for multi-time-scale capacity planning of photovoltaic and hydrogen energy storage considering demand response according to an embodiment of the present invention. DETAILED DESCRIPTION

[0089] The present invention will now be discussed with reference to exemplary embodiments. It should be understood that the embodiments discussed are only to enable those skilled in the art to better understand and thus implement the present invention, rather than implying any limitation on the scope of the present invention.

[0090] As used herein, the term “including” and variations thereof are to be interpreted as open-ended terms meaning “including, but not limited to.” The term “based on” is to be interpreted as “based, at least in part, on.” The terms “one embodiment” and “an embodiment” are to be interpreted as “at least one embodiment.”

[0091] Figure 1 A flowchart schematically shows a method for multi-time scale capacity planning of photovoltaic and hydrogen energy storage considering demand response according to an embodiment of the present invention. Figure 1 As shown, in this embodiment, the multi-time scale capacity planning method of photovoltaic and hydrogen energy storage considering demand response includes:

[0092] Build a user response model based on user electricity demand response;

[0093] Construct a hydrogen energy storage system model, including an electrolyzer model and a fuel cell model;

[0094] According to the user response model and the hydrogen energy storage system model, a multi-time scale capacity planning model of the photovoltaic-hydrogen storage system considering the system cost and system benefit is established, including: objective function and constraints;

[0095] The objective function is constructed based on system cost and system benefit; the constraints include: power balance constraint, system equivalent power balance constraint, grid-connected power constraint, hydrogen storage tank capacity constraint, hydrogen supply reliability constraint, demand response load reduction constraint and ramp constraint;

[0096] The capacity planning of hydrogen energy storage is calculated based on the multi-time scale capacity planning model of photovoltaic-hydrogen storage system.

[0097] Furthermore, according to an embodiment of the present invention, when the power load is too high but the sunlight is insufficient, the photovoltaic power generation is insufficient, which does not match the actual situation. At this time, a higher electricity price can be set, and users will reduce electricity consumption or not use it during this period, thereby effectively reducing the maximum load; when the power load is too low but the sunlight is sufficient, the photovoltaic power generation is large. By lowering the electricity price, users can transfer their electricity demand from other periods to this period, thereby effectively absorbing photovoltaic power and reducing energy storage. Through the demand response mechanism, the demand for energy storage is reduced to a certain extent. Therefore, in this embodiment, the user response model is introduced as a time-of-use electricity price demand response model:

[0098]

[0099] Where: ΔP L,t To introduce the load change after demand response, is the load value before the system demand response, -ξ is the time-of-use electricity price demand response coefficient, q t is the electricity price in period t, is the electricity price before demand response at time t, P Dmax and P Dmin are the maximum and minimum power consumption respectively;

[0100] In this embodiment, in the demand response mechanism, when the electricity load is high, the more the electricity price increases, the more users will reduce their electricity consumption, and the greater the response; when the electricity load is low, the more the electricity price decreases, the more users will increase their electricity consumption, and the greater the response. Therefore, the peak-to-valley difference in electricity prices directly affects the user's response, thereby affecting the smoothness of the load curve. If the peak-to-valley difference in electricity prices is small, the response is too low and the ideal smooth load curve effect cannot be achieved. If the peak-to-valley difference in electricity prices is large, the response is excessive, and even the "peak-to-valley inversion" phenomenon may occur. Therefore, it needs to be constrained as follows:

[0101]

[0102] Where: and is the peak and valley value of the time-of-use electricity price, δ max and δ min They are the maximum and minimum values ​​of the peak-to-valley electricity price ratio respectively.

[0103] Further, according to one embodiment of the present invention,

[0104] Establish a hydrogen energy storage system model. In engineering applications, in view of the complexity of the process of hydrogen production by water electrolysis and the many influencing factors, in order to facilitate in-depth research and analysis, the following reasonable assumptions are made to simplify the model: 1) It is assumed that the hydrogen production system maintains a constant operating temperature, thereby eliminating the potential impact of temperature fluctuations on electrolysis efficiency and hydrogen yield; 2) During the electrolysis process, it is assumed that the concentration of the alkaline electrolyte remains relatively stable, ignoring the concentration changes that may occur due to the electrolysis reaction to ensure the consistency of reaction conditions; 3) Ignore the loss of gas in the compression and separation links, and regard the hydrogen separation process as completed instantly, in order to simplify the calculation process and focus on the study of the electrolysis process itself.

[0105] The operating power range of the alkaline electrolyzer is set between 5% and 100% of its rated power, with a switching time of 200 milliseconds. In order to simplify the subsequent analysis process, it is assumed that the electrolyzer operates in a scenario where electricity can be purchased for hydrogen production, and always remains in the efficient operating range, that is, between 50% and 100% of the rated power. On this basis, the power of the electrolyzer is accurately configured to optimize the overall configuration of the hydrogen energy system. The simplified model focuses on achieving the best balance between hydrogen energy system performance and cost-effectiveness through reasonable power configuration:

[0106] P el.min ≤P el (t)≤P el.max ;

[0107] P el.min =0.5P el.max ;

[0108] Where: Pel (t) is the input power of the electrolytic cell; P el.min , P el.max They are the minimum and maximum operating power of the electrolyzer under grid-connected conditions;

[0109] Proton exchange membrane fuel cells have the ability to operate flexibly within the range of 0% to 100% rated power. The entire fuel cell power generation system is constructed by multiple proton exchange membrane fuel cell units. By accurately configuring the power, the optimal combination of proton exchange membrane fuel cell units in the system can be determined to achieve the most efficient energy utilization and output.

[0110] The fuel cell model is:

[0111] P fc (t) = H fc (t)η fc H LHV ;

[0112] 0≤P fc (t)≤P fc.max ;

[0113] Where: P fc (t) is the power of the fuel cell module; P fc.max is the nominal power of the fuel cell module; η fc is the power generation efficiency of the fuel cell; H fc (t) is the real-time hydrogen consumption of the fuel cell; H LHV It is the low calorific value of hydrogen.

[0114] Further, according to an embodiment of the present invention, the system cost includes:

[0115] Annual investment cost f1 for electrolyzer, compressor, hydrogen storage tank and fuel cell:

[0116]

[0117] Where: i is 1, 2, 3, 4, Q1, Q2, Q3 are the unit capacities of electrolyzer, hydrogen storage tank and fuel cell respectively; Q4 is the unit capacity of converter; C1 is the unit capacity price of electrolyzer; C2 is the unit capacity price of compressor; C3 and C4 are the unit capacity prices of hydrogen storage tank and fuel cell transmission project respectively; L i is the project life; ω is the equipment depreciation rate;

[0118] The annual operation and maintenance cost f2 and electricity purchase cost f3 are expressed as:

[0119]

[0120] Where: P s (t), ζs (t) are the purchased power and the purchased power cost respectively; l i The proportion of hydrogen energy system operation and maintenance costs to investment costs;

[0121] The penalty cost f4 for abandoning solar power and the penalty cost f5 for lack of hydrogen are expressed as:

[0122]

[0123] Where: pv P is the penalty cost coefficient for abandoned light; pv.cut (t) is the abandoned light power; pv (t) is the on-grid electricity price of photovoltaic power generation; ph (t) is the real-time hydrogen price in the market; λ ph Penalize cost factor for hydrogen shortage; D dm (t) is the real-time demand for hydrogen energy, D sh (t) is the real-time available supply of hydrogen energy;

[0124] The system load response cost f6 is expressed as:

[0125]

[0126] Where: a and b represent the linear coefficients of demand and electricity price;

[0127] System benefits include:

[0128] The system's hydrogen sales revenue f7 and power supply revenue f8 are expressed as:

[0129]

[0130] Where: P pv (t) represents the photovoltaic power generation;

[0131] The objective function is:

[0132] maxf=f7+f8-f1-f2-f3-f4-f5-f6.

[0133] Further, according to an embodiment of the present invention, the power balance constraint is:

[0134] P pv.on (t)+P pv.cut (t)+P el (t) = P pv (t);

[0135] Where: P pv.on (t) is the photovoltaic grid-connected power;

[0136] The system equivalent power balance constraint is that the electrolyzer produces hydrogen, which is compressed by a compressor and stored in a hydrogen storage tank or sold directly:

[0137]

[0138] Among them, the amount of hydrogen stored in the hydrogen storage tank is:

[0139] Q tan (t) = Q tan (t-1)+Q in (t)-Q sh (t)-Q fc (t);

[0140] D sh (t) = Q sh (t)δ;

[0141] Where: Q tan (t) is the hydrogen storage capacity at time t; Q in (t) is the amount of hydrogen compressed into the hydrogen storage tank by the compressor; Q tan (t-1) is the hydrogen storage capacity at time t-1; Q fc (t) is the hydrogen consumption of the fuel cell at time t; Q sh (t) is the amount of hydrogen sold at time t; δ is the mass volume fraction of high-pressure hydrogen;

[0142] The grid-connected power constraint is:

[0143] 0≤P pv.on +P fc (t)≤P bpv ;

[0144] Where: P bpv The upper limit of photovoltaic grid-connected capacity;

[0145] The hydrogen storage tank capacity constraint is:

[0146] 0.1Q tan ≤Q tan (t)≤0.9Q tan ;

[0147] Where: Q tan is the maximum capacity of the hydrogen storage tank;

[0148] The hydrogen supply reliability constraint mainly considers the hydrogen supply load demand capacity of the hydrogen energy system, and the load hydrogen shortage rate is used to express the hydrogen supply reliability, that is:

[0149]

[0150] Where: T is the number of points in the selected sampling interval, obviously H SSP The smaller it is, the higher the reliability of hydrogen supply;

[0151] Demand response fills the peak and valley differences between system load and power generation by changing users’ electricity consumption, and can be regarded as a virtual generator set in the scheduling model.

[0152] Similar to generators, load reduction at a certain moment has a maximum reduction constraint and a ramp constraint. In addition, the load reduction amount of the entire dispatch cycle also has an upper limit constraint. The demand response load reduction constraint and ramp constraint include:

[0153]

[0154] 0≤ΔP L,t -ΔP L,t-1 ≤P LU ;

[0155] 0≤ΔP L,t-1 -ΔP L,t ≤P LD ;

[0156]

[0157] Where: is the maximum load reduction at time t, ΔP L,t-1 is the load change after the demand response is introduced at the next moment, v t is a 0-1 state variable; P LU and P LD The upper and lower limits of the load shedding ramp; is the maximum load value at time t, S max The maximum load reduction amount.

[0158] Furthermore, according to an embodiment of the present invention, in order to avoid severe fluctuations in load, the coordinated planning of multi-time-scale energy storage is considered. The operation and balance constraints of energy storage at different time scales are different. In combination with demand response, the constraints also include the following constraints:

[0159] Loads can only be transferred in or out within the same dispatch cycle, that is, the transfer period should meet the following requirements:

[0160] t′∈T,t″∈T;

[0161] Where: t′ is the load transfer-in period; t″ is the load transfer-out period;

[0162] Load transfer constraints:

[0163] The load transfer amount should satisfy the requirement that the total load demand before and after the demand response remains unchanged within a dispatching cycle, and the load transfer amount at each moment should not exceed the maximum load transfer amount:

[0164]

[0165] Where: Δt is the time interval.

[0166] According to the above scheme of the present invention, the present invention adopts the method of increasing demand response. When the power load is too high but the light is insufficient, resulting in less photovoltaic power generation, a higher electricity price is set to allow users to reduce electricity consumption or not use it during this period, thereby effectively reducing the maximum load and reducing the demand for energy storage discharge; when the power load is too low but the light is sufficient, resulting in more photovoltaic power generation, the electricity price is lowered to allow users to transfer electricity demand from other time periods to this time period, thereby effectively absorbing photovoltaic power and reducing energy storage, and calculating the capacity planning of hydrogen energy storage.

[0167] According to the above scheme of the present invention, the present invention can solve the problem that due to the high initial investment, daily operation and maintenance and future replacement costs of energy storage equipment, if the energy storage scale is expanded blindly, it may lead to redundant configuration of equipment resources.

[0168] According to the above scheme of the present invention, the present invention constructs a capacity planning model by considering demand response and combining the different characteristics of the hydrogen energy storage system at multiple time scales, thereby achieving accurate capacity determination of the hydrogen energy storage capacity and avoiding large-scale redundant configuration of hydrogen production and storage equipment.

[0169] Furthermore, to achieve the above-mentioned purpose, the present invention also provides a photovoltaic and hydrogen energy storage multi-time scale capacity planning system considering demand response, comprising:

[0170] A user response model building module, which builds a user response model according to the user's power demand response;

[0171] A hydrogen energy storage system model building module is used to build a hydrogen energy storage system model, including an electrolyzer model and a fuel cell model;

[0172] The photovoltaic-hydrogen storage system multi-time scale capacity planning model construction module, based on the user response model and the hydrogen energy storage system model, establishes a photovoltaic-hydrogen storage system multi-time scale capacity planning model that takes into account system costs and system benefits, including: objective function and constraints;

[0173] The objective function is constructed based on system cost and system benefit; the constraints include: power balance constraint, system equivalent power balance constraint, grid-connected power constraint, hydrogen storage tank capacity constraint, hydrogen supply reliability constraint, demand response load reduction constraint and ramp constraint.

[0174] The hydrogen energy storage capacity planning calculation module calculates the capacity planning of hydrogen energy storage based on the multi-time scale capacity planning model of the photovoltaic-hydrogen storage system.

[0175] The photovoltaic and hydrogen energy storage multi-time scale capacity planning system considering demand response according to the present invention can realize the above-mentioned photovoltaic and hydrogen energy storage multi-time scale capacity planning method considering demand response. The specific method steps are as described above and will not be repeated here.

[0176] Furthermore, to achieve the above objectives, the present invention also provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, the multi-time scale capacity planning method for photovoltaic and hydrogen energy storage considering demand response as described above is implemented.

[0177] Furthermore, to achieve the above objectives, the present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the multi-time-scale capacity planning method for photovoltaic and hydrogen energy storage considering demand response as described above is implemented.

[0178] Based on the above solution of the present invention, the technical solution of the present invention is described in detail in the following in combination with the accompanying drawings in the form of a specific embodiment.

[0179] Example 1

[0180] In order to verify the effectiveness of the proposed multi-time scale capacity planning method for photovoltaic and hydrogen energy storage considering demand response, an actual case of a regional power grid is selected for example analysis. The installed capacity of photovoltaic power stations in the regional power grid is 135MW. The system's new energy grid-connected electricity price and electricity purchase price are based on the region, where the new energy grid-connected electricity price is 0.4 yuan / (kW·h), and the price of electricity purchased from the grid is 0.5 yuan / (kW·h). The system consists of a converter, an electrolyzer, a hydrogen storage device and a fuel cell. Its initial investment, operation and maintenance coefficient, and equipment life are shown in Table 1. The electrolysis efficiency is set to 75%, the hydrogen compression energy consumption is set to 2kW·h / kg, the mass fraction of high-pressure hydrogen is 0.03kg / L, the power generation efficiency of the fuel cell is set to 55%, the penalty coefficient for abandonment of light and the cost coefficient for insufficient hydrogen supply are both 0.5 yuan / (kW·h); the lower calorific value of hydrogen is 120MJ / kg (33.3kW·h / kg), and the hydrogen selling price is 42 yuan / kg.

[0181] Table 1

[0182] equipment Initial Investment Operation and maintenance coefficient Lifespan / year Transmission Converter 1000 / (yuan / kW) 5 20 Electrolyzer 5000 / (yuan / kW) 5 10 Hydrogen storage equipment 3750 / (yuan / m3) 1 20 Fuel Cells 2250 / (yuan / kW) 5 10

[0183] The calculation model results show that the configuration of hydrogen energy storage is compared on two typical days without considering demand response and after considering demand response, as shown in Table 2. The comparison results show that after considering demand response, the capacity of electrolyzers and hydrogen storage equipment configured in the hydrogen energy storage system continues to decrease, and the benefits continue to increase, thereby effectively and accurately determining the hydrogen energy storage capacity and avoiding large-scale redundant configuration of hydrogen production and storage equipment.

[0184] Table 2

[0185]

[0186] Those skilled in the art will appreciate that the modules and algorithm steps described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0187] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and equipment can refer to the corresponding processes in the aforementioned method implementation methods, and will not be repeated here.

[0188] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0189] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the embodiments of the present invention.

[0190] In addition, each functional module in the embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0191] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the energy-saving signal sending / receiving method of each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical disks.

[0192] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other.

[0193] It should be understood that the size of the serial numbers of each step in the content of the invention and the implementation methods of the present invention does not absolutely mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the implementation methods of the present invention.

Claims

1. A multi-time scale capacity planning method for photovoltaic and hydrogen energy storage considering demand response, characterized in that: include: Build a user response model based on user electricity demand response; Construct a hydrogen energy storage system model, including an electrolyzer model and a fuel cell model; According to the user response model and the hydrogen energy storage system model, a multi-time scale capacity planning model of a photovoltaic-hydrogen storage system considering system cost and system benefit is established, including: an objective function and constraint conditions; The objective function is constructed based on system cost and system benefit; the constraints include: power balance constraint, system equivalent power balance constraint, grid-connected power constraint, hydrogen storage tank capacity constraint, hydrogen supply reliability constraint, demand response load reduction constraint and ramp constraint; The capacity planning of hydrogen energy storage is calculated based on the multi-time scale capacity planning model of photovoltaic-hydrogen storage system.

2. The photovoltaic and hydrogen energy storage multi-time scale capacity planning method considering demand response according to claim 1 is characterized in that: The user response model is a time-of-use electricity price demand response model: Where: ΔP L,t To introduce the load change after demand response, is the load value before the system demand response, -ξ is the time-of-use electricity price demand response coefficient, q t is the electricity price in period t, is the electricity price before demand response at time t, P Dmax and P Dmin are the maximum and minimum power consumption respectively; Among them, the following constraints are imposed on electricity prices: Where: and is the peak and valley value of the time-of-use electricity price, δ max and δ min They are the maximum and minimum values ​​of the peak-to-valley electricity price ratio respectively.

3. The photovoltaic and hydrogen energy storage multi-time scale capacity planning method considering demand response according to claim 2 is characterized in that: The electrolytic cell model is: P el.min ≤P el (t)≤P el.max ; P el.min =0.5P el.max ; Where: P el (t) is the input power of the electrolytic cell; P el.min , P el.max They are the minimum and maximum operating power of the electrolyzer under grid-connected conditions; The fuel cell model is: P fc (t)=H fc (t)η fc H LHV ; 0≤P fc (t)≤P fc.max ; Where: P fc (t) is the power of the fuel cell module; P fc.max is the nominal power of the fuel cell module; η fc is the power generation efficiency of the fuel cell; H fc (t) is the real-time hydrogen consumption of the fuel cell; H LHV It is the low calorific value of hydrogen.

4. The photovoltaic and hydrogen energy storage multi-time scale capacity planning method considering demand response according to claim 3 is characterized in that: The system cost includes: Annual investment cost f1 for electrolyzer, compressor, hydrogen storage tank and fuel cell: Where: i is 1, 2, 3, 4, Q1, Q2, Q3 are the unit capacities of electrolyzer, hydrogen storage tank and fuel cell respectively; Q4 is the unit capacity of converter; C1 is the unit capacity price of electrolyzer; C2 is the unit capacity price of compressor; C3 and C4 are the unit capacity prices of hydrogen storage tank and fuel cell transmission project respectively; L i is the project life; ω is the equipment depreciation rate; The annual operation and maintenance cost f2 and electricity purchase cost f3 are expressed as: Where: P s (t), ζ s (t) are the purchased power and the purchased power cost respectively; l i The proportion of hydrogen energy system operation and maintenance costs to investment costs; The penalty cost f4 for abandoning solar power and the penalty cost f5 for lack of hydrogen are expressed as: Where: pv P is the penalty cost coefficient for abandoned light; pv.cut (t) is the abandoned light power; pv (t) is the on-grid electricity price of photovoltaic power generation; ph (t) is the real-time hydrogen price in the market; λ ph Penalize cost factor for hydrogen shortage; D dm (t) is the real-time demand for hydrogen energy, D sh (t) is the real-time available supply of hydrogen energy; The system load response cost f6 is expressed as: Where: a and b represent the linear coefficients of demand and electricity price; The system benefits include: The system's hydrogen sales revenue f7 and power supply revenue f8 are expressed as: Where: P pv (t) represents the photovoltaic power generation; The objective function is: maxf=f7+f8-f1-f2-f3-f4-f5-f6.

5. The photovoltaic and hydrogen energy storage multi-time scale capacity planning method considering demand response according to claim 4 is characterized in that: The power balance constraint is: P pv.on (t)+P pv.cut (t)+P el (t)=P pv (t); Where: P pv.on (t) is the photovoltaic grid-connected power; The equivalent power balance constraint of the system is that the electrolyzer produces hydrogen, which is compressed by a compressor and stored in a hydrogen storage tank or sold directly: Among them, the amount of hydrogen stored in the hydrogen storage tank is: Q tan (t)=Q tan (t-1)+Q in (t)-Q sh (t)-Q fc (t); D sh (t)=Q sh (t)δ; Where: Q tan (t) is the hydrogen storage capacity at time t; Q in (t) is the amount of hydrogen compressed into the hydrogen storage tank by the compressor; Q tan (t-1) is the hydrogen storage capacity at time t-1; Q fc (t) is the hydrogen consumption of the fuel cell at time t; Q sh (t) is the amount of hydrogen sold at time t; δ is the mass volume fraction of high-pressure hydrogen; The grid-connected power constraint is: 0≤P pv.on +P fc (t)≤P bpv ; Where: P bpv The upper limit of photovoltaic grid-connected capacity; The hydrogen storage tank capacity constraint is: 0.1Q tan ≤Q tan (t)≤0.9Q tan ; Where: Q tan is the maximum capacity of the hydrogen storage tank; The hydrogen supply reliability constraint is: Where: T is the number of points in the selected sampling interval; The demand response load reduction constraint and ramp constraint include: 0≤ΔP L,t -ΔP L,t-1 ≤P LU ; 0≤ΔP L,t-1 -ΔP L,t ≤P LD ; Where: is the maximum load reduction at time t, ΔP L,t-1 is the load change after the demand response is introduced at the next moment, v t is a 0-1 state variable; P LU and P LD The upper and lower limits of the load shedding ramp; is the maximum load value at time t, S max The maximum load reduction amount.

6. The photovoltaic and hydrogen energy storage multi-time scale capacity planning method considering demand response according to claim 5 is characterized in that: The constraints also include: Loads can only be transferred in or out within the same dispatch cycle, that is, the transfer period should meet the following requirements: t′∈T,t″∈T; Where: t′ is the load transfer-in period; t″ is the load transfer-out period; Load transfer constraints: The load transfer amount should satisfy the requirement that the total load demand before and after the demand response remains unchanged within a dispatching cycle, and the load transfer amount at each moment should not exceed the maximum load transfer amount: Where: Δt is the time interval.

7. Photovoltaic and hydrogen energy storage multi-time scale capacity planning system considering demand response, characterized by: include: A user response model building module, which builds a user response model according to the user's power demand response; A hydrogen energy storage system model building module is used to build a hydrogen energy storage system model, including an electrolyzer model and a fuel cell model; A photovoltaic-hydrogen storage system multi-time scale capacity planning model building module is used to build a photovoltaic-hydrogen storage system multi-time scale capacity planning model that takes into account system costs and system benefits based on the user response model and the hydrogen energy storage system model, including: objective functions and constraints; The objective function is constructed based on system cost and system benefit; the constraints include: power balance constraint, system equivalent power balance constraint, grid-connected power constraint, hydrogen storage tank capacity constraint, hydrogen supply reliability constraint, demand response load reduction constraint and ramp constraint. The hydrogen energy storage capacity planning calculation module calculates the capacity planning of hydrogen energy storage based on the multi-time scale capacity planning model of the photovoltaic-hydrogen storage system.

8. An electronic device, characterized in that The method comprises a processor, a memory and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements a multi-time-scale capacity planning method for photovoltaic and hydrogen energy storage taking into account demand response as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for multi-time-scale capacity planning of photovoltaic and hydrogen energy storage considering demand response as described in any one of claims 1-6 is implemented.

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