Planning method, system and equipment for electricity-hydrogen coupling system considering carbon-green evidence market and hydrogen load uncertainty and storage medium

Abstract

The invention relates to the technical field of power-hydrogen coupling system planning, in particular to a planning method, system and device for a power-hydrogen coupling system considering carbon-green certificate market and hydrogen load uncertainty and a storage medium, and the method comprises the steps: obtaining the historical operation data of the power-hydrogen coupling system and the historical transaction data of the carbon-green certificate market; generating a plurality of hydrogen load typical random scenes by utilizing a Monte Carlo simulation method according to historical operation data of the electricity-hydrogen coupling system; reducing the number of typical random scenes through a synchronous backward reduction method, and obtaining a typical reduced scene; based on the objective function and the constraint condition, constructing an electricity-hydrogen coupling system planning model considering the carbon-green evidence market and hydrogen load uncertainty; and inputting the obtained data into the electro-hydrogen coupling system planning model, and solving and calculating to obtain an electro-hydrogen coupling system planning scheme. The energy utilization efficiency of the electro-hydrogen coupling system can be improved, the system investment cost is reduced, the system stability is improved, and the system carbon emission is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of the planning of an electric-hydrogen coupling system, and in particular to a planning method, system, device, and storage medium for an electric-hydrogen coupling system considering the carbon-green certificate market and the uncertainty of hydrogen load. Background Art

[0002] As a key technical path for realizing the transformation of clean energy, the electric-hydrogen coupling energy system is gradually becoming an important direction for the reconstruction of the global energy system. By deeply coupling renewable energy power generation with water electrolysis hydrogen production technology, this system can effectively solve the problem of accommodating volatile power sources such as wind power and photovoltaic power, and at the same time provide zero-carbon hydrogen energy for industries, transportation and other fields.

[0003] However, the planning and construction of this system face multiple complex challenges: First, the terminal hydrogen load demand shows significant spatio-temporal uncertainty, which is not only restricted by market factors such as the promotion process of fuel cell vehicles and the hydrogen consumption patterns of industrial users, but also affected by system operation characteristics such as the peak shaving demand of the power grid and the fluctuation of renewable energy output. Traditional deterministic planning methods are difficult to accurately capture this multi-dimensional coupling uncertainty feature; Second, the price formation mechanisms of the carbon trading market and the green certificate trading market have strong dynamic correlations. The green certificate subscription rate and the new energy installed capacity show a non-linear growth relationship. This market coupling mechanism has a combined impact on the system economy; Third, existing planning models mostly adopt a single market mechanism or a simplified scenario generation method, and cannot take into account the dual needs of optimizing equipment capacity configuration and avoiding market risks.

[0004] There are mainly three limitations in the current research: In terms of uncertainty modeling, most literature adopts probability distribution assumptions based on historical data, and fails to fully consider the non-stationary data characteristics brought about by the explosive growth of the hydrogen energy market; In terms of scenario processing methods, traditional forward scenario generation techniques are prone to cause an explosion in the dimensionality of the scenario space. When multi-market coupling modeling is involved, the computational complexity increases exponentially; At the level of market mechanism integration, existing models often independently analyze the carbon trading cost or the green certificate income, ignoring the dynamic game relationship between the two market mechanisms and their synergistic impact on the system planning scheme. Therefore, it is urgent to further consider the uncertainty problem of hydrogen load, combine the carbon trading market and the green certificate trading market, and establish a planning model for the electric-hydrogen coupling system that meets the carbon emission reduction target.

[0005] The information disclosed in this background art section is only intended to deepen the understanding of the overall background art of the present invention, and should not be regarded as an admission or any form of implication that this information constitutes the prior art known to those skilled in the art. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a planning method, system, device and storage medium for an electric-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty, which can improve the energy utilization efficiency of the electric-hydrogen coupling system, reduce the system investment cost, improve the system stability, and reduce the system carbon emissions.

[0007] In order to achieve the above object, the technical solution adopted by the present invention is: a planning method for an electric-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty, comprising the following steps:

[0008] Obtain the historical operation data of the electric-hydrogen coupling system and the historical transaction data of the carbon-green certificate market;

[0009] According to the historical operation data of the electric-hydrogen coupling system, use the Monte Carlo simulation method to generate a number of typical random scenarios of hydrogen load;

[0010] Reduce the number of the typical random scenarios through the synchronous backward reduction method to obtain typical reduced scenarios;

[0011] Based on the objective function and constraint conditions, construct a planning model for the electric-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty;

[0012] Input the obtained historical operation data of the electric-hydrogen coupling system and the historical transaction data of the carbon-green certificate market into the planning model of the electric-hydrogen coupling system, and obtain the planning scheme of the electric-hydrogen coupling system after solving and calculating.

[0013] Further, the historical operation data of the electric-hydrogen coupling system includes historical electric-hydrogen load data, historical output data, and historical unit installed capacity data.

[0014] Further, the step of generating a number of typical random scenarios of hydrogen load according to the historical operation data of the electric-hydrogen coupling system by using the Monte Carlo simulation method includes the following steps:

[0015] Set k as the time and s as the index of the scenario, where the initial value is 1, NK is the maximum time value, and NS is the maximum number of scenarios;

[0016] According to the hydrogen load prediction value at time k and the corresponding prediction error probability distribution function, extract the hydrogen load prediction error value that conforms to the normal distribution of the hydrogen load prediction error at time k, and determine the actual value of the hydrogen load at time k under time 1 according to the sum of the hydrogen load prediction value at time k and the hydrogen load prediction error value at time k;

[0017] Repeat the above steps until the condition is met: k = NK, and obtain the actual values of the hydrogen load at the typical times of the entire planning period under the current scenario s; and form typical random scenarios of hydrogen load as hydrogen load data respectively;

[0018] Repeat the above steps until the scenario meets the condition: s = NS, and obtain the actual hydrogen load values at typical moments during the entire planning period for each scenario s.

[0019] Based on the obtained actual hydrogen load values, form several corresponding typical random scenarios of hydrogen load.

[0020] Furthermore, the steps for reducing the number of typical random scenarios by the synchronous backward reduction method to obtain typical reduced scenarios are as follows:

[0021] Set S as the initial scenario set, DS as the set of scenarios to be reduced, and DS is initially an empty set. The representation form of each scenario set is: ξ s (s = 1, 2,..., N), all including 1, 2,…, N typical random scenarios of hydrogen load, and the probability of each scenario occurring is p s , the distance DT s,s′ between each pair of scenario pairs is: DT s,s′ = DT(ξ s , ξ s′ ), s, s′ = 1, 2,..., N;

[0022] For scenario i, there exists a scenario j that satisfies DT i (j) = min DT i,s′ , i, s′ ∈ S and s′ ≠ k, and determine that scenario j is the scenario number with the minimum distance from scenario i;

[0023] According to the condition: PD i (j) = p i · DT i (j), i ∈ S, determine the probability distance between scenario i and scenario j, and according to the condition: PD d = min PD j , j ∈ S, determine the scenario d with the minimum probability distance from scenario j;

[0024] According to the formula S = S - {d}, DS = DS + {d}, p j = p j + p d Perform scenario deletion and probability superposition, so that scenario d is reduced from the initial scenario set S, scenario d is added to the set of scenarios to be reduced DS, and the occurrence probability of scenario d is passed to scenario j;

[0025] Repeat the above steps until the number of scenarios in the set of scenarios to be reduced DS reaches the preset requirement.

[0026] Furthermore, the expression of the objective function is:

[0027]

[0028] where r is the discount rate; C RE,inv is the investment and construction cost of new energy; C BES,inv is the investment and construction cost of electrochemical energy storage; C AE,inv is the investment and construction cost of electrolyzers; C HFC,inv is the investment and construction cost of hydrogen fuel cells; C HS,inv is the investment and construction cost of hydrogen energy storage; C carbon is the trading cost of the carbon market; C green is the trading cost of the green certificate market; C thermal is the operating cost of thermal power; C hbuy is the cost of purchasing hydrogen; C RE,curt is the penalty cost for curtailment of new energy; C load,curt is the penalty cost for load shedding; t represents the planning stage; NT represents the total number of planning stages.

[0029] Furthermore, the investment and construction cost C of the new energy RE,inv is obtained by the following formula:

[0030]

[0031] where represents the unit investment and construction cost of new energy j; represents the rated capacity of new energy j; yj ,t represents the investment and construction status of new energy j in the t-th stage, controlled by 0 or 1, where 0 represents not invested and 1 represents invested; Ω RE represents the set of new energy to be built.

[0032] Furthermore, the investment and construction cost C of the electrochemical energy storage BES,inv is obtained by the following formula:

[0033]

[0034] where represents the unit investment and construction cost of electrochemical energy storage j; represents the rated capacity of electrochemical energy storage j; y j,t represents the investment and construction status of electrochemical energy storage j in the t-th stage, controlled by 0 or 1, where 0 represents not invested and 1 represents invested; Ω BES represents the set of electrochemical energy storage to be built.

[0035] Furthermore, the investment and construction cost C of the electrolyzers AE,inv is obtained by the following formula:

[0036]

[0037] where represents the unit investment and construction cost of electrolyzer j; represents the rated capacity of electrolyzer j; yj,t Indicates the construction status of electrolyzer j in stage t, controlled by 0 or 1, where 0 represents not constructed and 1 represents constructed; Ω AE Represents the set of electrochemical energy storage to be built.

[0038] Furthermore, the construction cost C of the hydrogen fuel cell HFC,inv Is obtained by the following formula:

[0039]

[0040] In the formula, Represents the unit construction cost of hydrogen fuel cell j; Represents the rated capacity of hydrogen fuel cell j; yj ,t Indicates the construction status of hydrogen fuel cell j in stage t, controlled by 0 or 1, where 0 represents not constructed and 1 represents constructed; Ω HFC Represents the set of electrochemical energy storage to be built.

[0041] Furthermore, the construction cost C of the hydrogen energy storage HS,inv Is obtained by the following formula:

[0042]

[0043] In the formula, Represents the unit construction cost of hydrogen energy storage j; Represents the rated capacity of hydrogen energy storage j; y j,t Indicates the construction status of hydrogen energy storage j in stage t, controlled by 0 or 1, where 0 represents not constructed and 1 represents constructed; Ω HS Represents the set of electrochemical energy storage to be built.

[0044] Furthermore, the carbon market trading cost C cabron Is obtained by the following formula:

[0045]

[0046]

[0047]

[0048]

[0049] In the formula, Represents the carbon trading price in stage t; Represents the actual carbon emissions in stage t; Represents the proportionality coefficient for decomposing the total carbon emission index to each stage; M the Is the total carbon emission index of the power-to-hydrogen coupling system after considering multi-stage emission reduction; Is the theoretical carbon emissions of the power-to-hydrogen coupling system in stage t; λe Denote the carbon emission coefficient per unit power of the thermal power unit as λ h The carbon emission coefficient per unit power of the hydrogen source point is P j,k,t Denote the output of the thermal power unit j at the k-th moment in the t-th stage as Denote the hydrogen purchase volume of the hydrogen source point h at the k-th moment in the t-th stage as Denote the magnitude of the electrical load j at the k-th moment in the t-th stage as Denote the magnitude of the hydrogen load j at the k-th moment in the t-th stage as σ dec Denote the total emission reduction index of the electric-hydrogen coupling system. Horizon is the total number of moments in a typical day. T Ω HN Ω LD Ω HD Ω are the sets of thermal power units, hydrogen source points, electrical loads, and hydrogen loads, respectively.

[0050] Furthermore, the green certificate market transaction cost C green is obtained by the following formula:

[0051]

[0052] In the formula, Denote the green certificate trading price in the t-th stage. ι is the specified quota ratio of renewable energy power generation to the total on-grid power. is the total on-grid power of the electric-hydrogen coupling system at the k-th moment in the t-th stage. Denote the output of the new energy j at the k-th moment in the t-th stage.

[0053] Furthermore, the thermal power operation cost C thermal is obtained by the following formula:

[0054]

[0055] In the formula, c fuel is the unit fuel price of the thermal power unit. is the heat consumption curve of the thermal power unit j. SU j,k,t SD j,k,t are the start-stop costs of the thermal power unit j at the k-th moment in the t-th stage, respectively.

[0056] Furthermore, the hydrogen purchase cost C hbuy is obtained by the following formula:

[0057]

[0058] In the formula, c hd Denote the unit hydrogen purchase cost.

[0059] Furthermore, the new energy curtailment penalty cost C RE,curt is obtained by the following formula:

[0060]

[0061] Wherein, c RE,curt represents the unit penalty cost for abandoned new energy power; represents the predicted magnitude of new energy j at time k in stage t.

[0062] Furthermore, the load shedding penalty cost C load,curt is obtained by the following formula:

[0063]

[0064] Wherein, c LD,curt is the unit penalty cost for lost power load; is the magnitude of the lost load of electrical load j at time k in stage t; c HD,curt is the unit penalty cost for lost power load; is the magnitude of the lost load of hydrogen load j at time k in stage t.

[0065] Furthermore, the constraint conditions include equipment investment constraints, thermal power operation constraints, new energy operation constraints, electrochemical energy storage operation constraints, electrolyzer operation constraints, hydrogen fuel cell operation constraints, hydrogen energy storage operation constraints, hydrogen source point output constraints, power supply and demand balance constraints, and hydrogen energy supply and demand balance constraints.

[0066] Furthermore, the equipment investment constraint is:

[0067]

[0068] Wherein, represents the investment status of new energy j in stage t, controlled by a 0-1 variable, where 0 represents not invested and 1 represents invested; represents the investment status of electrolyzer j in stage t, controlled by a 0-1 variable, where 0 represents not invested and 1 represents invested; represents the investment status of hydrogen energy storage j in stage t, controlled by a 0-1 variable, where 0 represents not invested and 1 represents invested; represents the investment status of hydrogen fuel cell j in stage t, controlled by a 0-1 variable, where 0 represents not invested and 1 represents invested; represents the investment status of electrochemical energy storage j in stage t, controlled by a 0-1 variable, where 0 represents not invested and 1 represents invested; Ω RE represents the set of new energy to be built; Ω AE represents the set of electrochemical energy storage to be built; Ω HS represents the set of electrochemical energy storage to be built; Ω HFC represents the set of electrochemical energy storage to be built; Ω BES represents the set of electrochemical energy storage to be built.

[0069] Furthermore, the thermal power operation constraints are as follows:

[0070]

[0071]

[0072]

[0073] In the formula, are the minimum and maximum outputs of thermal power unit j respectively; I j,k,t is the start-stop state of thermal power unit j at time k in stage t, controlled by 0 or 1, where "0" represents shutdown and "1" represents startup; is the status variable for judging whether thermal power unit j is in the startup or shutdown state at time k in stage t; su j and sd j are the unit start-stop costs of thermal power unit j at time k in stage t respectively; UR j and DR j are the upward and downward ramp rates of thermal power unit j respectively; P j,k,t represents the output of thermal power unit j at time k in stage t; are the start and stop times of thermal power unit j at time k in stage t; SU j,k,t and SD j,k,t are the start-stop costs of thermal power unit j at time k in stage t respectively.

[0074] Furthermore, the new energy operation constraints are as follows:

[0075]

[0076] In the formula, represents the output of new energy j at time k in stage t; represents the predicted value of new energy j at time k in stage t.

[0077] Furthermore, the electrochemical energy storage operation constraints are as follows:

[0078]

[0079]

[0080] E j,0,t = E j,Horizon,t

[0081] In the formula, are the charging and discharging powers of electrochemical energy storage j at time k in stage t respectively; They are the charge and discharge state variables of the electro-chemical energy storage j at the k-th moment of the t-th stage, controlled by 0 or 1. "0" represents shutdown, and "1" represents startup. is the upper limit of the charge and discharge power of the electro-chemical energy storage j; E j,k,t is the energy of the electro-chemical energy storage j at the k-th moment of the t-th stage; They are the charge and discharge efficiencies of the electro-chemical energy storage j respectively; They are the upper and lower limits of the capacity of the electro-chemical energy storage j respectively; E j,0,t represents the energy of the electro-chemical energy storage j at the starting moment of the t-th stage; E j,Horizon,t represents the energy of the electro-chemical energy storage j at the final moment of the t-th stage.

[0082] Furthermore, the operating constraints of the electrolyzer are as follows:

[0083]

[0084] In the formula, is the amount of hydrogen generated by the electrolyzer j at the k-th moment of the t-th stage; χ is the unit conversion coefficient for converting electrical energy into hydrogen of the same energy; is the electrical power consumed by the electrolyzer j at the k-th moment of the t-th stage; η AE is the conversion efficiency of the electrolyzer; is the upper limit of the output of the electrolyzer j.

[0085] Furthermore, the operating constraints of the hydrogen fuel cell are as follows:

[0086]

[0087] In the formula, is the output of the hydrogen fuel cell j at the k-th moment of the t-th stage; is the amount of hydrogen consumed by the hydrogen fuel cell j at the k-th moment of the t-th stage; η HFC is the conversion efficiency of the hydrogen fuel cell; is the upper limit of the hydrogen consumption of the hydrogen fuel cell j.

[0088] Furthermore, the operating constraints of the hydrogen energy storage are as follows:

[0089]

[0090] In the formula, is the hydrogen storage of the hydrogen energy storage j at the k-th moment of the t-th stage; They are the hydrogen charging and discharging amounts of the hydrogen energy storage j at the k-th moment of the t-th stage respectively; η HS,cha 、η HS,dis They are the hydrogen charging and discharging efficiencies of the hydrogen energy storage respectively; is the upper limit of the hydrogen charging and discharging of the hydrogen energy storage; They are the hydrogen charging and discharging state variables of hydrogen energy storage j at the k-th moment in the t-th stage, controlled by 0 or 1; They are the upper and lower limits of the capacity of hydrogen energy storage j respectively; They are the hydrogen storage amounts of hydrogen energy storage j at the starting and final moments in the t-th stage respectively.

[0091] Furthermore, the output constraint of the hydrogen source point is:

[0092]

[0093] In the formula, is the upper limit of the output of hydrogen source point j; represents the hydrogen purchase amount of hydrogen source point h at the k-th moment in the t-th stage.

[0094] Furthermore, the power supply-demand balance constraint is:

[0095]

[0096] In the formula, Ω T , Ω LD are the sets of thermal power units and electrical loads respectively; represents the magnitude of electrical load j at the k-th moment in the t-th stage; is the magnitude of the load shedding of electrical load j at the k-th moment in the t-th stage.

[0097] Furthermore, inputting the obtained historical operation data of the electric-hydrogen coupling system and the historical transaction data of the carbon-green certificate market into the electric-hydrogen coupling system planning model, the electric-hydrogen coupling system planning scheme obtained after solving and calculating includes:

[0098] Screening and processing the obtained historical operation data of the electric-hydrogen coupling system and the historical transaction data of the carbon-green certificate market;

[0099] Sequentially inputting the processed data into the electric-hydrogen coupling system planning model, and using a solver to solve to obtain the electric-hydrogen coupling system planning scheme.

[0100] The present invention also provides a planning system for an electric-hydrogen coupling system considering the carbon-green certificate market and the uncertainty of hydrogen load, including:

[0101] A data acquisition module for acquiring the historical operation data of the electric-hydrogen coupling system and the historical transaction data of the carbon-green certificate market;

[0102] A scenario construction module for generating a number of typical random scenarios of hydrogen load according to the historical operation data of the electric-hydrogen coupling system by using the Monte Carlo simulation method;

[0103] A scenario reduction module for reducing the number of the typical random scenarios through the synchronous backward reduction method to obtain typical reduced scenarios;

[0104] A model construction module, configured to construct an electric-hydrogen coupling system planning model considering the carbon-green certificate market and the uncertainty of hydrogen load based on an objective function and constraint conditions;

[0105] A solution planning module, configured to input the obtained historical operation data of the electric-hydrogen coupling system and the historical transaction data of the carbon-green certificate market into the electric-hydrogen coupling system planning model, and obtain an electric-hydrogen coupling system planning scheme after solving and calculating.

[0106] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the steps of the planning method of the electric-hydrogen coupling system considering the carbon-green certificate market and the uncertainty of hydrogen load as described in any one of the above are implemented.

[0107] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the planning method of the electric-hydrogen coupling system considering the carbon-green certificate market and the uncertainty of hydrogen load as described in any one of the above are implemented.

[0108] The beneficial effects of the present invention are as follows: Through the coupled application of Monte Carlo simulation and synchronous backward reduction method, the present invention comprehensively considers various complex working conditions such as the carbon-green certificate market and the uncertainty of hydrogen load, and through scenario distance clustering and probability weight optimization, greatly improves the authenticity and accuracy of scenario optimization, provides a planning tool with economy, reliability and policy adaptability for the electric-hydrogen coupling system, improves the energy utilization efficiency of the electric-hydrogen coupling system, reduces the system investment cost, improves the system stability, and reduces the system carbon emissions. Description of the Drawings

[0109] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0110] Figure 1 It is a schematic flowchart of the planning method of the electric-hydrogen coupling system considering the carbon-green certificate market and the uncertainty of hydrogen load in the embodiment of the present invention;

[0111] Figure 2 It is a schematic diagram of the equipment investment and construction in Schemes 1 to 4 in the embodiment of the present invention;

[0112] Figure 3 It is a schematic diagram of the planning cost in Schemes 1 to 4 in the embodiment of the present invention;

[0113] Figure 4 It is a schematic diagram of the carbon emissions in Schemes 1 to 4 in the embodiments of the present invention;

[0114] Figure 5 It is a schematic diagram of the carbon emissions at each stage in Schemes 1 to 4 in the embodiments of the present invention;

[0115] Figure 6 It is a schematic structural diagram of a planning system for an electricity-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty in the embodiments of the present invention. Detailed implementation manners

[0116] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments.

[0117] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly on the other element or there can also be a middle element. When an element is considered to be "connected" to another element, it can be directly connected to the other element or there may be a middle element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are only for the purpose of illustration and do not represent the only implementation manners.

[0118] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs. The terms used in the description of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0119] As Figure 1 shown, the planning method for an electricity-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty includes the following steps:

[0120] Obtain the historical operation data of the electricity-hydrogen coupling system and the historical transaction data of the carbon-green certificate market;

[0121] According to the historical operation data of the electricity-hydrogen coupling system, use the Monte Carlo simulation method to generate a number of typical random scenarios of hydrogen load;

[0122] Reduce the number of typical random scenarios through the synchronous backward reduction method to obtain typical reduced scenarios;

[0123] Based on the objective function and constraint conditions, construct a planning model for an electricity-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty;

[0124] Input the obtained historical operation data of the electric-hydrogen coupling system and the historical transaction data of the carbon-green certificate market into the electric-hydrogen coupling system planning model, and after solving and calculating, obtain the electric-hydrogen coupling system planning scheme.

[0125] Through the coupled application of Monte Carlo simulation and synchronous backward reduction method, the present invention comprehensively considers various complex working conditions such as the carbon-green certificate market and the uncertainty of hydrogen load. Through scenario distance clustering and probability weight optimization, the authenticity and accuracy of scenario optimization are greatly improved, providing a planning tool with economy, reliability and policy adaptability for the electric-hydrogen coupling system, improving the energy utilization efficiency of the electric-hydrogen coupling system, reducing the system investment cost, improving the system stability, and reducing the system carbon emissions.

[0126] The electric-hydrogen coupling system provided in this embodiment is composed of a thermal power unit, a wind power unit, a hydrogen storage tank, an electrolyzer and a hydrogen fuel cell. This system realizes the mutual conversion of hydrogen energy and electric energy through the electrolyzer and the fuel cell.

[0127] Based on the above embodiment, the historical operation data of the electric-hydrogen coupling system includes historical electric-hydrogen load data, historical output data and historical unit installed capacity data; through the historical electric-hydrogen load data, historical output data and historical unit installed capacity data, Monte Carlo simulation can more accurately capture the operation characteristics of the electric-hydrogen coupling system, thus ensuring the accuracy of hydrogen load scenario generation and enhancing the adaptability of system planning.

[0128] Based on the above embodiment, according to the historical operation data of the electric-hydrogen coupling system, the steps of generating several typical random scenarios of hydrogen load by using the Monte Carlo simulation method are as follows:

[0129] Set k as the time and s as the index of the scenario, where the initial value is 1, NK is the maximum time value, and NS is the maximum number of scenarios; generate data by setting the time k period by period, completely retaining the intra-day fluctuation law and seasonal characteristics of the hydrogen load, and greatly improving the simulation accuracy of time series correlation;

[0130] According to the hydrogen load prediction value at time k and the corresponding prediction error probability distribution function, extract the hydrogen load prediction error value at time k that conforms to the normal distribution of the hydrogen load prediction error, and determine the actual value of the hydrogen load at time k at time 1 according to the sum of the hydrogen load prediction value at time k and the hydrogen load prediction error value at time k; dynamically correct the prediction value based on the prediction error probability distribution function, greatly reducing the problem of scenario distortion caused by error accumulation;

[0131] Repeat the above steps until the condition is met: k = NK, and obtain the actual value of the hydrogen load at the typical time of the entire planning period under the current scenario s; and respectively form hydrogen load data to form a typical random scenario of hydrogen load;

[0132] Repeat the above steps until the scenario meets the condition: s = NS, and obtain the actual hydrogen load values at typical moments during the entire planning period for each scenario s.

[0133] Based on the obtained actual hydrogen load values, form several corresponding typical random scenarios of hydrogen load.

[0134] Through a double-loop structure of scenario index and time index, achieve batch generation of a large number of scenarios and comprehensive coverage of operating conditions within the hydrogen load fluctuation range.

[0135] On the basis of the above embodiments, reducing the number of typical random scenarios through the synchronous backward reduction method, and obtaining typical reduced scenarios includes the following steps:

[0136] Set S as the initial scenario set, DS as the scenario set to be reduced, and DS is initially an empty set, where the representation form of each scenario set is: ξ s (s = 1, 2,..., N), all include 1, 2,..., N typical random scenarios of hydrogen load, and the probability of each scenario occurring is p s , the distance DT s,s′ between each pair of scenario pairs is: DT s,s′ = DT(ξ s , ξ s′ ), s, s' = 1, 2,..., N;

[0137] For scenario i, there exists scenario j that satisfies DT i (j) = min DT i,s′ , i, s' ∈ S and s' ≠ k, determine scenario j as the scenario number with the minimum distance from scenario i;

[0138] According to the condition: PD i (j) = p i ·DT i (j), i ∈ S to determine the probability distance between scenario i and scenario j, and according to the condition: PD d = min PD j , j ∈ S to determine the scenario d with the minimum probability distance from scenario j;

[0139] According to the formula S = S - {d}, DS = DS + {d}, p j = p j + p d Perform scenario deletion and probability superposition, so that scenario d is reduced in the initial scenario set S, scenario d is added to the scenario set DS to be reduced, and the occurrence probability of scenario d is passed to scenario j;

[0140] Repeat the above steps until the number of scenarios in the scenario set DS to be reduced reaches the preset requirement.

[0141] By comprehensively considering the distance between scenarios and the probability distance, dynamic iteration and optimization are carried out to ensure that key scenarios with high probability can be preferentially retained, providing scenario support for the collaborative optimization of the electricity-hydrogen-carbon multi-market.

[0142] Based on the above embodiments, the expression of the objective function is:

[0143]

[0144] In the formula, r is the discount rate; C RE,inv is the investment and construction cost of new energy; C BES,inv is the investment and construction cost of electrochemical energy storage; C AE,inv is the investment and construction cost of electrolyzers; C HFC,inv is the investment and construction cost of hydrogen fuel cells; C HS,inv is the investment and construction cost of hydrogen energy storage; C carbon is the trading cost of the carbon market; C green is the trading cost of the green certificate market; C thermal is the operating cost of thermal power; C hbuy is the cost of purchasing hydrogen; C RE,curt is the penalty cost of new energy curtailment; C load,curt is the penalty cost of load shedding; t represents the planning stage; NT represents the total number of planning stages.

[0145] Based on the above embodiments, the investment and construction cost C of new energy RE,inv is obtained by the following formula:

[0146]

[0147] In the formula, represents the unit investment and construction cost of new energy j; represents the rated capacity of new energy j; y j,t represents the investment and construction status of new energy j in the t stage, controlled by 0 or 1, 0 represents not invested, 1 represents invested; Ω RE represents the set of new energy to be built.

[0148] Based on the above embodiments, the investment and construction cost C of electrochemical energy storage BES,inv is obtained by the following formula:

[0149]

[0150] In the formula, represents the unit investment and construction cost of electrochemical energy storage j; represents the rated capacity of electrochemical energy storage j; y j,t represents the investment and construction status of electrochemical energy storage j in the t stage, controlled by 0 or 1, 0 represents not invested, 1 represents invested; Ω BES represents the set of electrochemical energy storage to be built.

[0151] Based on the above embodiments, the construction cost C of the electrolyzer AE,inv is obtained by the following formula:

[0152]

[0153] wherein, represents the unit construction cost of electrolyzer j; represents the rated capacity of electrolyzer j; y j,t represents the construction status of electrolyzer j at stage t, controlled by 0 or 1, 0 represents not constructed, and 1 represents constructed; Ω AE represents the set of electrochemical energy storage to be built.

[0154] Based on the above embodiments, the construction cost C of the hydrogen fuel cell HFC,inv is obtained by the following formula:

[0155]

[0156] wherein, represents the unit construction cost of hydrogen fuel cell j; represents the rated capacity of hydrogen fuel cell j; y j,t represents the construction status of hydrogen fuel cell j at stage t, controlled by 0 or 1, 0 represents not constructed, and 1 represents constructed; Ω HFC represents the set of electrochemical energy storage to be built.

[0157] Based on the above embodiments, the construction cost C of the hydrogen energy storage HS,inv is obtained by the following formula:

[0158]

[0159] wherein, represents the unit construction cost of hydrogen energy storage j; represents the rated capacity of hydrogen energy storage j; y j,t represents the construction status of hydrogen energy storage j at stage t, controlled by 0 or 1, 0 represents not constructed, and 1 represents constructed; Ω HS represents the set of electrochemical energy storage to be built.

[0160] Based on the above embodiments, the carbon market trading cost C cabron is obtained by the following formula:

[0161]

[0162]

[0163] wherein, represents the carbon trading price at stage t; Represents the actual carbon emissions at stage t; Represents the proportionality coefficient for decomposing the total carbon emission target into each stage; M the Is the total carbon emission target of the power-to-hydrogen coupling system considering multi-stage emission reduction; Is the theoretical carbon emissions of the power-to-hydrogen coupling system at stage t; λ e Represents the carbon emission coefficient per unit power of the thermal power unit; λ h Is the carbon emission coefficient per unit power of the hydrogen source point; P j,k,t Represents the output of thermal power unit j at moment k in stage t; Represents the hydrogen purchase volume of hydrogen source point h at moment k in stage t; Represents the magnitude of the electrical load j at moment k in stage t; Represents the magnitude of the hydrogen load j at moment k in stage t; σ dec Represents the total emission reduction target of the power-to-hydrogen coupling system; Horizon is the total number of moments in a typical day; Ω T 、Ω HN 、Ω LD 、Ω HD Are the sets of thermal power units, hydrogen source points, electrical loads, and hydrogen loads respectively.

[0164] Based on the above embodiments, the green certificate market transaction cost C green Is obtained by the following formula:

[0165]

[0166] In the formula, Represents the green certificate trading price at stage t; ι is the specified quota ratio of renewable energy power generation to the total on-grid power; Is the total on-grid power of the power-to-hydrogen coupling system at moment k in stage t; Represents the output of new energy j at moment k in stage t.

[0167] Based on the above embodiments, the thermal power operation cost C thermal Is obtained by the following formula:

[0168]

[0169] In the formula, c fuel Is the unit fuel price of the thermal power unit; Is the heat consumption curve of thermal power unit j; SU j,k,t 、SD j,k,t Are the start-stop costs of thermal power unit j at moment k in stage t respectively.

[0170] Based on the above embodiments, the hydrogen purchase cost C hbuy Is obtained by the following formula:

[0171]

[0172] In the formula, c hd represents the unit hydrogen purchase cost.

[0173] Based on the above embodiments, the new energy curtailment penalty cost C RE,curt is obtained by the following formula:

[0174]

[0175] In the formula, c RE,curt represents the new energy curtailment unit penalty cost; represents the predicted magnitude of new energy j at time k in stage t.

[0176] Based on the above embodiments, the load shedding penalty cost C load,curt is obtained by the following formula:

[0177]

[0178] In the formula, c LD,curt is the unit penalty cost for lost power load; is the magnitude of load shedding of electrical load j at time k in stage t; c HD,curt is the unit penalty cost for lost power load; is the magnitude of load shedding of hydrogen load j at time k in stage t.

[0179] Based on the above embodiments, the constraint conditions include equipment investment constraints, thermal power operation constraints, new energy operation constraints, electrochemical energy storage operation constraints, electrolyzer operation constraints, hydrogen fuel cell operation constraints, hydrogen energy storage operation constraints, hydrogen source point output constraints, power supply and demand balance constraints, and hydrogen energy supply and demand balance constraints.

[0180] Based on the above embodiments, the equipment investment constraint is:

[0181]

[0182] In the formula, represents the investment status of new energy j in stage t, which is controlled by a 0-1 variable, where 0 represents not invested and 1 represents invested; represents the investment status of electrolyzer j in stage t, which is controlled by a 0-1 variable, where 0 represents not invested and 1 represents invested; represents the investment status of hydrogen energy storage j in stage t, which is controlled by a 0-1 variable, where 0 represents not invested and 1 represents invested; represents the investment status of hydrogen fuel cell j in stage t, which is controlled by a 0-1 variable, where 0 represents not invested and 1 represents invested; Indicates the construction status of the electrochemical energy storage j at stage t, controlled by a 0-1 variable, where 0 represents not yet constructed and 1 represents constructed; Ω RE Represents the set of new energy to be built; Ω AE Represents the set of electrochemical energy storage to be built; Ω HS Represents the set of electrochemical energy storage to be built; Ω HFC Represents the set of electrochemical energy storage to be built; Ω BES Represents the set of electrochemical energy storage to be built.

[0183] Based on the above embodiments, the thermal power operation constraints are:

[0184]

[0185]

[0186]

[0187] In the formula, Are respectively the minimum and maximum outputs of the thermal power unit j; I j,k,t Is the start-stop status of the thermal power unit j at time k in stage t, controlled by 0 or 1, where "0" represents shutdown and "1" represents startup; Is the status variable for determining whether the thermal power unit j is in the startup or shutdown state at time k in stage t; su j , sd j Are respectively the unit start-stop costs of the thermal power unit j at time k in stage t; UR j , DR j Are respectively the upward and downward ramp rates of the thermal power unit j; P j,k,t Represents the output of the thermal power unit j at time k in stage t; Is the start-up and shutdown time of the thermal power unit j at time k in stage t; SU j,k,t , SD j,k,t Are respectively the start-stop costs of the thermal power unit j at time k in stage t.

[0188] Based on the above embodiments, the new energy operation constraints are:

[0189]

[0190] In the formula, Represents the output of the new energy j at time k in stage t; Represents the predicted size of the new energy j at time k in stage t.

[0191] Based on the above embodiments, the electrochemical energy storage operation constraints are:

[0192]

[0193]

[0194] E j,0,t = E j,Horizon,t

[0195] In the formula, are respectively the charging and discharging powers of the electrochemical energy storage j at the k-th moment in the t-th stage; are respectively the charging and discharging state variables of the electrochemical energy storage j at the k-th moment in the t-th stage, controlled by 0 or 1, where "0" represents shutdown and "1" represents startup; is the upper limit of the charging and discharging power of the electrochemical energy storage j; E j,k,t is the energy of the electrochemical energy storage j at the k-th moment in the t-th stage; are respectively the charging and discharging efficiencies of the electrochemical energy storage j; are respectively the upper and lower limits of the capacity of the electrochemical energy storage j; E j,0,t represents the energy of the electrochemical energy storage j at the starting moment of the t-th stage; E j,Horizon,t represents the energy of the electrochemical energy storage j at the final moment of the t-th stage.

[0196] Based on the above embodiments, the operating constraints of the electrolyzer are:

[0197]

[0198] In the formula, is the hydrogen production amount of the electrolyzer j at the k-th moment in the t-th stage; χ is the unit conversion coefficient for converting electric energy into hydrogen with the same energy; is the electric power consumed by the electrolyzer j at the k-th moment in the t-th stage; η AE is the conversion efficiency of the electrolyzer; is the upper limit of the output of the electrolyzer j.

[0199] Based on the above embodiments, the operating constraints of the hydrogen fuel cell are:

[0200]

[0201] In the formula, is the output of the hydrogen fuel cell j at the k-th moment in the t-th stage; is the hydrogen consumption amount of the hydrogen fuel cell j at the k-th moment in the t-th stage; η HFC is the conversion efficiency of the hydrogen fuel cell; is the upper limit of the hydrogen consumption of the hydrogen fuel cell j.

[0202] Based on the above embodiments, the operating constraints of the hydrogen energy storage are:

[0203]

[0204] In the formula, is the hydrogen storage of hydrogen energy storage at the k-th moment in the t-th stage; are the hydrogen charging and discharging amounts of hydrogen energy storage j at the k-th moment in the t-th stage; η HS,cha 、η HS,dis are the hydrogen charging and discharging efficiencies of hydrogen energy storage respectively; is the upper limit of hydrogen charging and discharging of hydrogen energy storage; are the hydrogen charging and discharging state variables of hydrogen energy storage j at the k-th moment in the t-th stage, controlled by 0 or 1; are the upper and lower limits of the capacity of hydrogen energy storage j respectively; are the hydrogen storages of hydrogen energy storage j at the starting and final moments in the t-th stage respectively.

[0205] On the basis of the above embodiments, the output constraint of the hydrogen source point is:

[0206]

[0207] In the formula, is the upper limit of the output of hydrogen source point j; represents the hydrogen purchase amount of hydrogen source point h at the k-th moment in the t-th stage.

[0208] On the basis of the above embodiments, the power supply and demand balance constraint is:

[0209]

[0210]

[0211] In the formula, Ω T 、Ω LD are the sets of thermal power units and electrical loads respectively; represents the magnitude of electrical load j at the k-th moment in the t-th stage; is the magnitude of the load shedding of electrical load j at the k-th moment in the t-th stage.

[0212] On the basis of the above embodiments, the historical operation data of the electric-hydrogen coupling system and the historical trading data of the carbon-green certificate market are input into the electric-hydrogen coupling system planning model, and the electric-hydrogen coupling system planning scheme obtained after solving and calculating includes:

[0213] Screen and process the obtained historical operation data of the electric-hydrogen coupling system and the historical trading data of the carbon-green certificate market;

[0214] Input the processed data into the electric-hydrogen coupling system planning model in sequence, and use the solver to solve to obtain the electric-hydrogen coupling system planning scheme.

[0215] In this embodiment, a specific planning method is provided. The improved IEEE 24-node power system coupled with a 7-node hydrogen system is used as the example background. The system originally had a total of 32 thermal power units (3650 MW in total) and a wind power installed capacity of 200 MW. At the initial stage of planning, the peak electrical load was 2850 MW, and the peak hydrogen load was 12.1 t. The parameters of each device to be planned are shown in Tables 1 to 7. During the planning period, the annual growth rate of the electrical and hydrogen loads is set at 3%. According to different carbon tax values, the planning period is divided into five stages, with each stage representing 5 years. The specific years and carbon tax prices are shown in Table 3-8, and the carbon emission reduction coefficient is taken as 0.7. The unit carbon emission of the thermal power unit is 1.08 t / (MW·h), and the unit carbon emission of the hydrogen source point is 8.96.

[0216] Table 1 Parameters of Coupled Devices

[0217] Unit capacity (MW) Efficiency Electrolyzer 10 80％ Hydrogen fuel cell 1 75％

[0218] Table 2 Parameters of Hydrogen Source Points

[0219] Gas well Upper output limit / (t) Lower output limit / (t) N1 20 0 N2 20 0

[0220] Table 3 Parameters of Hydrogen Transmission Pipelines

[0221]

[0222]

[0223] Table 4 Parameters of Hydrogen Storage Devices

[0224] Unit capacity (t) Maximum hydrogen charging and discharging rate (t / h) Hydrogen charging and discharging efficiency Hydrogen storage tank 1 0.75 95％

[0225] Table 5 Parameters of Electrochemical Energy Storage Devices

[0226]

[0227] Table 6 Relevant Costs of Each Device

[0228] Equipment Construction cost Wind turbine 800 (MW / 10,000 yuan) Electrolyzer 700 (MW / 10,000 yuan) Hydrogen fuel cell 700 (MW / 10,000 yuan) Hydrogen storage tank 50 (t / 10,000 yuan) Electrochemical energy storage 200 (MW / 10,000 yuan)

[0229] Table 7 Carbon Tax Prices for Each Stage

[0230]

[0231] To verify the effectiveness of the planning model in this embodiment, four schemes are selected to plan the electric-hydrogen coupling system respectively:

[0232] Scheme 1: Considering multi-stage planning, the planning period is divided into five stages, but without considering carbon emission reduction constraints, without considering the construction of electric-hydrogen coupling devices, without considering the uncertainty of hydrogen load, and only aiming at minimizing the total cost for system planning.

[0233] Scenario 2: Based on Scenario 1, consider the construction of electro-hydrogen coupling equipment and conduct system planning with the goal of minimizing the total investment cost.

[0234] Scenario 3: Based on Scenario 2, consider the total emission reduction constraint and conduct system planning with the goal of minimizing the total investment cost.

[0235] Scenario 4: Based on Scenario 2, consider the multi-stage emission reduction constraint and conduct system planning with the goal of minimizing the total investment cost.

[0236] Scenario 5: Based on Scenario 4, consider the uncertainty of hydrogen load, use the two-stage stochastic programming method to handle the uncertainty of hydrogen load, and conduct system planning with the goal of minimizing the total investment cost.

[0237] Scenario 6: Based on Scenario 5, further consider the carbon market and the green certificate trading market, use the two-stage stochastic programming method to handle the uncertainty of hydrogen load, and conduct system planning with the goal of minimizing the total investment cost.

[0238] Scenario 1: This scenario does not consider the construction of electro-hydrogen coupling equipment. Figures 2 to 4 It can be seen that Scenario 1 built 2100 MW of wind turbines and 5340 MW of electrochemical energy storage, with a total cost of 7.1139e+10 yuan and a carbon emission of 2.10e+08 tons.

[0239] Scenario 2: This scenario further considers the construction of electro-hydrogen coupling equipment, building 2900 MW of wind turbines, 970 MW of electrolyzers, 691 MW of hydrogen fuel cells, 1021 t of hydrogen energy storage, and 1610 MW of electrochemical energy storage. The total cost is 4.5375e+10 yuan, and the total carbon emission is 1.91e+08 tons. Compared with Scenario 1, Scenario 2 has 800 MW more wind turbines and 3730 MW less electrochemical energy storage. The total system investment cost is reduced by 36%, and the carbon emission is reduced by 9.04%. The construction of electro-hydrogen coupling equipment improves the new energy penetration rate of the system, provides a way for clean hydrogen production, improves economic efficiency, and promotes carbon emission reduction.

[0240] Scenario 3: To further reduce carbon emissions, a total carbon emission constraint is set. Compared with Scenario 2, Scenario 3 has 500 MW more wind turbines, 250 MW more electrolyzers, 423 t more hydrogen storage tanks, and 310 MW more electrochemical energy storage. The total investment cost increases by 1.38%, and the carbon emission is reduced by 24.35%. To meet the total carbon emission constraint, the system sacrifices a certain amount of economic efficiency to improve energy efficiency and reduce carbon emissions. Figure 5 It can be seen that the carbon emissions in each stage of Scenario 4 fluctuate greatly, which does not conform to the development of China's emission reduction situation and policies, as well as the current emission reduction requirements.

[0241] Scenario 4: Further considering the carbon emission reduction constraints at each stage, it is more in line with the development of China's emission reduction situation and policies, and can better meet the current emission reduction requirements. In Scenario 4, 4800 MW of wind turbines, 2280 MW of electrolyzers, 866 MW of hydrogen fuel cells, 3888 t of hydrogen energy storage, and 1650 MW of electrochemical energy storage are built. Compared with Scenario 1 without considering the construction of electric-hydrogen equipment, its total investment cost is reduced by 31.35%, and the carbon emissions are reduced by 42.77%. The planning scenario considering the construction of electric-hydrogen equipment and multi-stage emission reduction significantly improves the economic benefits and reduces the carbon emissions. Compared with Scenario 3, the carbon emissions are further reduced, and the carbon emissions at each stage are more in line with the development of China's emission reduction situation and policies, and can better meet the current emission reduction requirements.

[0242] It can be seen from the above comparison that the system planning model of the electric-hydrogen coupling system with multi-stage emission reduction shows better economy when achieving the same emission reduction target. This model not only decomposes the total emission reduction index into each stage, but also can optimize the carbon emission distribution at each stage of the system at the cost of slight economy, making the planning model better meet the needs of China's emission reduction policies.

[0243] Scenario 5: Compared with Scenario 4, this scenario significantly enhances the ability to respond to load fluctuations by improving the flexibility of the hydrogen energy system: the electrolyzer capacity is increased by 9 MW, strengthening the consumption capacity of renewable energy hydrogen production; the installed scale of hydrogen fuel cells is increased by 241 MW significantly, effectively suppressing load fluctuations as a rapid response unit; the configured hydrogen energy storage capacity is increased by 57 tons synchronously, enhancing the hydrogen energy storage system across time scales. The total investment cost of the system increases by 2.19% compared with Scenario 4, mainly due to the increase in hydrogen energy equipment investment and operating costs; the carbon emissions increase slightly by 1.29%, which is caused by the standby demand of fossil energy due to the uncertainty of hydrogen load. By constructing a planning scenario of the electric-hydrogen coupling system considering the uncertainty of hydrogen load, the ability of the system to respond to hydrogen load fluctuations is improved within an acceptable cost increment range, providing an important reference for the multi-energy system planning under the high proportion of renewable energy penetration.

[0244] Scenario 6: Compared with Scenario 5, Scenario 6 provides a flexible cost management strategy by simultaneously using the carbon trading market and the green certificate trading market. Its total investment cost is reduced by 18.19% compared with Scenario 1. Although the carbon emissions increase by 9.31% compared with Scenario 1 and the proportion of renewable energy output does not reach the expected target, through reasonable participation in the carbon trading and green certificate markets, the investment cost and total investment cost are effectively reduced. The carbon trading cost and green certificate trading cost of Scenario 6 account for 2.29% and 12.09% of the total cost respectively, which is very efficient in optimizing cost management by using market mechanisms.

[0245] By introducing a carbon trading market and a green certificate trading market into the planning scheme, under flexible market operations and reasonable investment and construction scale allocation, not only is the cost effectively reduced, but also the efficiency and sustainability of the system are ensured. This comprehensive advantage enables the planning scheme to better meet the needs in the face of future market changes and policy adjustments, thus becoming a more economically viable and adaptable choice.

[0246] As Figure 6 shown, the present invention also provides a planning system for an electric-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty, comprising:

[0247] A data acquisition module for acquiring the historical operation data of the electric-hydrogen coupling system and the historical trading data of the carbon-green certificate market;

[0248] A scenario construction module for generating a number of typical random scenarios of hydrogen load by using the Monte Carlo simulation method according to the historical operation data of the electric-hydrogen coupling system;

[0249] A scenario reduction module for reducing the number of typical random scenarios through the synchronous backward reduction method to obtain typical reduced scenarios;

[0250] A model construction module for constructing a planning model of the electric-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty based on the objective function and constraint conditions;

[0251] A planning solution module for inputting the obtained historical operation data of the electric-hydrogen coupling system and the historical trading data of the carbon-green certificate market into the planning model of the electric-hydrogen coupling system, and obtaining a planning scheme for the electric-hydrogen coupling system after solving and calculating.

[0252] Through the coupled application of Monte Carlo simulation and synchronous backward reduction method, the present invention comprehensively considers various complex working conditions such as the carbon-green certificate market and hydrogen load uncertainty, and through scenario distance clustering and probability weight optimization, greatly improves the authenticity and accuracy of scenario optimization, provides a planning tool with economic viability, reliability and policy adaptability for the electric-hydrogen coupling system, improves the energy utilization efficiency of the electric-hydrogen coupling system, reduces the system investment cost, improves the system stability, and reduces the system carbon emissions.

[0253] The specific working process of the above system has been illustrated in the above embodiments and will not be elaborated here.

[0254] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements the steps of the planning method for the electricity-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty as described in any one of the above, including obtaining the historical operation data of the electricity-hydrogen coupling system and the historical transaction data of the carbon-green certificate market; generating a number of typical random scenarios of hydrogen load by using the Monte Carlo simulation method according to the historical operation data of the electricity-hydrogen coupling system; reducing the number of typical random scenarios by the synchronous backward reduction method to obtain typical reduced scenarios; constructing a planning model for the electricity-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty based on the objective function and constraints; and inputting the obtained historical operation data of the electricity-hydrogen coupling system and the historical transaction data of the carbon-green certificate market into the planning model of the electricity-hydrogen coupling system, and obtaining a planning scheme for the electricity-hydrogen coupling system after solving and calculating.

[0255] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of the planning method for the electricity-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty as described in any one of the above, including obtaining the historical operation data of the electricity-hydrogen coupling system and the historical transaction data of the carbon-green certificate market; generating a number of typical random scenarios of hydrogen load by using the Monte Carlo simulation method according to the historical operation data of the electricity-hydrogen coupling system; reducing the number of typical random scenarios by the synchronous backward reduction method to obtain typical reduced scenarios; constructing a planning model for the electricity-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty based on the objective function and constraints; and inputting the obtained historical operation data of the electricity-hydrogen coupling system and the historical transaction data of the carbon-green certificate market into the planning model of the electricity-hydrogen coupling system, and obtaining a planning scheme for the electricity-hydrogen coupling system after solving and calculating.

[0256] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes. The solutions in the embodiments of the present application can be implemented in various computer languages. For example, object-oriented programming languages such as Java and interpreted scripting languages such as JavaScript.

[0257] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows 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 the processors of general-purpose computers, special-purpose computers, embedded processors, or other programmable data processing devices to generate a machine, so that the instructions executed by the processors of the computer or other programmable data processing devices generate means for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in multiple blocks.

[0258] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including instruction means, and the instruction means implement the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in multiple blocks.

[0259] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in multiple blocks.

[0260] Although the preferred embodiments of the present application have been described, those skilled in the art can make additional changes and modifications to these embodiments once they know the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0261] Those skilled in the art of this industry should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification is only to illustrate the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A planning method for an electric-hydrogen coupling system considering the carbon-green certificate market and the uncertainty of hydrogen load, characterized in that, It includes the following steps: Obtain the historical operation data of the electric-hydrogen coupling system and the historical transaction data of the carbon-green certificate market; According to the historical operation data of the electric-hydrogen coupling system, use the Monte Carlo simulation method to generate several typical random scenarios of hydrogen load; Reduce the number of the typical random scenarios through the synchronous backward reduction method to obtain typical reduced scenarios; Based on the objective function and constraint conditions, construct an electric-hydrogen coupling system planning model considering the carbon-green certificate market and the uncertainty of hydrogen load; Input the obtained historical operation data of the electric-hydrogen coupling system and the historical transaction data of the carbon-green certificate market into the electric-hydrogen coupling system planning model, and obtain the electric-hydrogen coupling system planning scheme after solving and calculating.

2. The planning method of the power-to-hydrogen coupling system considering the carbon-green certificate market and the uncertainty of hydrogen load according to claim 1, characterized in that, The historical operation data of the electric-hydrogen coupling system includes historical electric-hydrogen load data, historical output data, and historical unit installed capacity data.

3. The planning method of the electricity-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty according to claim 1, characterized in that, The step of using the Monte Carlo simulation method to generate several typical random scenarios of hydrogen load according to the historical operation data of the electric-hydrogen coupling system includes the following steps: Set k as the time and s as the index of the scenario, where the initial value is 1, NK is the maximum time value, and NS is the maximum number of scenarios; According to the hydrogen load prediction value at time k and the corresponding prediction error probability distribution function, extract the hydrogen load prediction error value at time k that conforms to the normal distribution of hydrogen load prediction error, and determine the actual hydrogen load value at time k at time 1 according to the sum of the hydrogen load prediction value at time k and the hydrogen load prediction error value at time k; Repeat the above steps until the condition is met: when k = NK, obtain the actual hydrogen load value at the typical time of the entire planning period in the current scenario s; and form the hydrogen load typical random scenario as the hydrogen load data respectively; Repeat the above steps until the condition is met: when s = NS, obtain the actual hydrogen load value at the typical time of the entire planning period in each scenario s; Based on the obtained several actual hydrogen load values, form several corresponding hydrogen load typical random scenarios.

4. The planning method of the electricity-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty according to claim 1, characterized in that, The step of reducing the number of the typical random scenarios through the synchronous backward reduction method to obtain typical reduced scenarios includes the following steps: Set \(S\) as the initial scenario set, \(DS\) as the scenario set to be reduced, and \(DS\) is initially an empty set, where the representation form of each scenario set is: \(\xi\) s (\(s = 1, 2, \cdots, N\)), all include \(1, 2, \cdots, N\) typical stochastic scenarios of hydrogen load, and the probability of each scenario occurring is \(p\) s , the distance \(DT\) between each pair of scenario pairs s,s′ is: \(DT\) s,s′ \(= DT(\xi\) s , \(\xi\) s′ ), \(s, s' = 1, 2, \cdots, N\); For scenario i, there exists a scenario j that satisfies DT i (j) = minDT i,s′ , where i, s′ ∈ S and s′ ≠ k, determine that scenario j is the scenario number with the minimum distance from scenario i; According to the condition: PD i (j) = p i ·DT i (j), i ∈ S to determine the probability distance between scenario i and scenario j, and according to the condition: PD d = minPD j , j ∈ S to determine the scenario d with the smallest probability distance from scenario j; According to the formula S = S - {d}, DS = DS + {d}, p j = p j + p d Perform scene deletion and probability superposition, so that scene d is reduced in the initial scene set S, scene d is added to the scene set DS to be reduced, and the occurrence probability of scene d is passed to scene j; Repeat the above steps until the number of scenarios in the scenario set DS to be reduced reaches the preset requirement.

5. The planning method of the electricity-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty according to claim 1, characterized in that The expression of the objective function is: Where r is the discount rate; C RE,inv is the investment and construction cost of new energy; C BES,inv is the investment and construction cost of electrochemical energy storage; C AE,inv is the investment and construction cost of electrolyzers; C HFC,inv is the investment and construction cost of hydrogen fuel cells; C HS,inv is the investment and construction cost of hydrogen energy storage; C carbon is the trading cost of the carbon market; C green is the trading cost of the green certificate market; C thermal is the operating cost of thermal power; C hbuy is the cost of purchasing hydrogen; C RE,curt is the penalty cost for new energy curtailment; C load,curt is the penalty cost for load shedding; t represents the planning stage; NT represents the total number of planning stages.

6. The planning method of the power-to-hydrogen coupling system considering the carbon-green certificate market and the uncertainty of hydrogen load according to claim 5, wherein The new energy investment and construction cost C RE,inv is obtained by the following formula: In the formula, represents the unit investment and construction cost of new energy j; represents the rated capacity of new energy j; y j,t represents the investment and construction status of new energy j in stage t, controlled by a 0-1 variable, where 0 represents not invested and constructed, and 1 represents invested and constructed; Ω RE represents the set of new energy to be built.

7. The planning method of the power-to-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty according to claim 6, characterized in that, The investment and construction cost C of the electrochemical energy storage BES,inv is obtained by the following formula: In the formula, represents the unit investment cost of electrochemical energy storage j; represents the rated capacity of electrochemical energy storage j; y j,t represents the investment and construction status of electrochemical energy storage j in stage t, which is controlled by a 0-1 variable. 0 represents not invested and constructed, and 1 represents invested and constructed; Ω BES represents the set of electrochemical energy storage to be built.

8. The planning method of the electricity-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty according to claim 7, characterized in that, The electrolytic cell construction cost C AE,inv is obtained from the following formula: In the formula, represents the unit construction cost of electrolyzer j; represents the rated capacity of electrolyzer j; y j,t represents the construction status of electrolyzer j in stage t, which is controlled by a 0-1 variable. 0 represents not constructed, and 1 represents constructed; Ω AE represents the set of electrochemical energy storage to be built.

9. The planning method of the electricity-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty according to claim 8, characterized in that The construction cost C of the hydrogen fuel cell HFC,inv is obtained by the following formula: In the formula, represents the unit investment and construction cost of hydrogen fuel cell j; represents the rated capacity of hydrogen fuel cell j; y j,t represents the investment and construction status of hydrogen fuel cell j in stage t, which is controlled by a 0-1 variable. 0 represents not invested and constructed, and 1 represents invested and constructed; Ω HFC represents the set of electrochemical energy storage to be built.

10. The planning method of the power-to-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty according to claim 9, characterized in that, The hydrogen energy storage investment and construction cost C HS,inv is obtained by the following formula: In the formula, represents the unit investment cost of hydrogen energy storage j; represents the rated capacity of hydrogen energy storage j; y j,t represents the investment and construction status of hydrogen energy storage j in stage t, which is controlled by a 0-1 variable. 0 represents not invested and constructed, and 1 represents invested and constructed; Ω HS represents the set of electrochemical energy storage to be built.

11. The planning method of the power-to-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty according to claim 10, wherein, The carbon market transaction cost C cabron is obtained by the following formula: Wherein, represents the carbon trading price at stage t; represents the actual carbon emissions at stage t; represents the proportionality coefficient for decomposing the total carbon emission index into each stage; M the is the total carbon emission index of the power-to-hydrogen coupling system after considering multi-stage emission reduction; is the theoretical carbon emissions of the power-to-hydrogen coupling system at stage t; λ e represents the carbon emission coefficient per unit power of the thermal power unit; λ h is the carbon emission coefficient per unit power of the hydrogen source point; P j,k,t represents the output of the thermal power unit j at time k in stage t; represents the hydrogen purchase volume of the hydrogen source point h at time k in stage t; represents the magnitude of the electrical load j at time k in stage t; represents the magnitude of the hydrogen load j at time k in stage t; σ dec represents the total emission reduction index of the power-to-hydrogen coupling system; Horizon is the total number of time moments in a typical day; Ω T Ω HN Ω LD Ω HD are the sets of thermal power units, hydrogen source points, electrical loads, and hydrogen loads respectively.

12. The planning method of the electricity-hydrogen coupling system considering the carbon-green certificate market and the uncertainty of hydrogen load according to claim 11, characterized in that, The green certificate market transaction cost C green is obtained by the following formula: In the formula, represents the trading price of green certificates at stage t; ι is the specified quota ratio of the renewable energy power generation to the total grid-connected power; is the total grid-connected power of the power-to-hydrogen coupling system at the k-th moment in the t-th stage; represents the output of new energy j at the k-th moment in the t-th stage.

13. The planning method of the power-to-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty according to claim 12, characterized in that, The thermal power operation cost C thermal is obtained by the following formula: where c fuel is the unit fuel price of the thermal power unit; is the heat consumption curve of thermal power unit j; SU j,k,t , SD j,k,t are the start-up and shut-down costs of thermal power unit j at the k-th moment in the t-th stage, respectively.

14. The planning method of the electricity-hydrogen coupling system considering the carbon-green certificate market and the uncertainty of hydrogen load according to claim 1, characterized in that, The hydrogen purchase cost C hbuy is obtained by the following formula: where c hd represents the unit hydrogen purchase cost.

15. The planning method of the electricity-hydrogen coupling system considering the carbon-green certificate market and the uncertainty of hydrogen load according to claim 1, characterized in that, The new energy curtailment penalty cost C RE,curt is obtained by the following formula: where c RE,curt represents the penalty cost per unit of abandoned electricity of new energy; represents the predicted size of new energy j at the k-th moment in the t-th stage.

16. The planning method of the electricity-hydrogen coupling system considering the carbon-green certificate market and the uncertainty of hydrogen load according to claim 1, characterized in that The load loss penalty cost C load,curt is obtained by the following formula: where c LD,curt is the penalty cost per unit of load loss; is the amount of load loss of electrical load j at the k-th moment in the t-th stage; c HD,curt is the penalty cost per unit of load loss; is the amount of load loss of hydrogen load j at the k-th moment in the t-th stage.

17. The planning method of the power-to-hydrogen coupling system considering the carbon-green certificate market and the uncertainty of hydrogen load according to claim 1, characterized in that The constraint conditions include equipment investment and construction constraints, thermal power operation constraints, new energy operation constraints, electrochemical energy storage operation constraints, electrolyzer operation constraints, hydrogen fuel cell operation constraints, hydrogen energy storage operation constraints, hydrogen source point output constraints, power supply and demand balance constraints, and hydrogen energy supply and demand balance constraints.

18. The planning method of the power-to-hydrogen coupling system considering the carbon-green certificate market and the uncertainty of hydrogen load according to claim 1, characterized in that The equipment investment and construction constraints are: Wherein, represents the construction status of new energy j in stage t, which is controlled by a 0-1 variable, where 0 represents not constructed and 1 represents constructed; represents the construction status of electrolyzer j in stage t, which is controlled by a 0-1 variable, where 0 represents not constructed and 1 represents constructed; represents the construction status of hydrogen energy storage j in stage t, which is controlled by a 0-1 variable, where 0 represents not constructed and 1 represents constructed; represents the construction status of hydrogen fuel cell j in stage t, which is controlled by a 0-1 variable, where 0 represents not constructed and 1 represents constructed; represents the construction status of electrochemical energy storage j in stage t, which is controlled by a 0-1 variable, where 0 represents not constructed and 1 represents constructed; Ω RE represents the set of new energy to be constructed; Ω AE represents the set of electrochemical energy storage to be constructed; Ω HS represents the set of electrochemical energy storage to be constructed; Ω HFC represents the set of electrochemical energy storage to be constructed; Ω BES represents the set of electrochemical energy storage to be constructed.

19. The planning method of the electricity-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty according to claim 18, characterized in that, The thermal power operation constraints are: SU j,k,t ≥su j ·(I j,k,t -I j,k-1,t ),SU j,k,t ≥0 SD j,k,t ≥sd j ·(I j,k-1,t -I j,k,t ),SD j,k,t ≥0 In the formula, are the minimum output and maximum output of thermal power unit j respectively; I j,k,t is the start-stop state of thermal power unit j at time k in stage t, controlled by a 0-1 variable. "0" represents shutdown, and "1" represents startup; is a state variable for judging whether thermal power unit j is in the startup or shutdown state at time k in stage t; su j and sd j are the unit start-stop costs of thermal power unit j at time k in stage t respectively; UR j and DR j are the upward and downward ramp rates of thermal power unit j respectively; P j,k,t represents the output of thermal power unit j at time k in stage t; are the start and stop times of thermal power unit j at time k in stage t; SU j,k,t and SD j,k,t are the start-stop costs of thermal power unit j at time k in stage t respectively.

20. The planning method of the electricity-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty according to claim 19, characterized in that The new energy operation constraints are: Wherein, represents the output of new energy j at the k-th moment of the t-th stage; represents the predicted magnitude of new energy j at the k-th moment of the t-th stage.

21. The planning method of the electricity-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty according to claim 20, characterized in that The electrochemical energy storage operation constraints are: E j,0,t = E j,Horizon,t Wherein, are respectively the charging and discharging powers of the electrochemical energy storage j at the k-th moment in the t-th stage; are respectively the charging and discharging state variables of the electrochemical energy storage j at the k-th moment in the t-th stage, which are controlled by 0-1 variables, where "0" represents shutdown and "1" represents startup; is the upper limit of the charging and discharging power of the electrochemical energy storage j; E j,k,t is the energy of the electrochemical energy storage j at the k-th moment in the t-th stage; are respectively the charging and discharging efficiencies of the electrochemical energy storage j; are respectively the upper and lower limits of the capacity of the electrochemical energy storage j; E j,0,t represents the energy of the electrochemical energy storage j at the starting moment of the t-th stage; E j,Horizon,t represents the energy of the electrochemical energy storage j at the final moment of the t-th stage.

22. The planning method of the power-to-hydrogen coupling system considering the carbon-green certificate market and the uncertainty of hydrogen load according to claim 21, wherein The electrolyzer operation constraints are: In the formula, is the hydrogen production of electrolyzer j at the k-th moment of the t-th stage; χ is the unit conversion coefficient for converting electrical energy into hydrogen with the same energy; is the electrical power consumed by electrolyzer j at the k-th moment of the t-th stage; η AE is the conversion efficiency of the electrolyzer; is the upper limit of the output of electrolyzer j.

23. The planning method of the power-to-hydrogen coupling system considering the carbon-green certificate market and the uncertainty of hydrogen load according to claim 22, characterized in that, The hydrogen fuel cell operation constraints are: In the formula, is the output of the hydrogen fuel cell j at the k-th moment of the t-th stage; is the amount of hydrogen consumed by the hydrogen fuel cell j at the k-th moment of the t-th stage; η HFC is the conversion efficiency of the hydrogen fuel cell; is the upper limit of hydrogen consumption of the hydrogen fuel cell j.

24. The planning method of an electricity-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty according to claim 23, characterized in that The hydrogen energy storage operation constraints are: In the formula, is the hydrogen storage of hydrogen energy storage j at the k-th moment in the t-th stage; are the hydrogen charging and discharging amounts of hydrogen energy storage j at the k-th moment in the t-th stage; η HS,cha and η HS,dis are the hydrogen charging and discharging efficiencies of hydrogen energy storage respectively; is the upper limit of hydrogen charging and discharging of hydrogen energy storage; are the hydrogen charging and discharging status variables of hydrogen energy storage j at the k-th moment in the t-th stage, controlled by 0 or 1, where 0 represents not built and 1 represents built; are the upper and lower limits of the capacity of hydrogen energy storage j respectively; are the hydrogen storages of hydrogen energy storage j at the starting and final moments in the t-th stage respectively.

25. The planning method of the electricity-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty according to claim 24, characterized in that, The hydrogen source point output constraints are: In the formula, is the upper limit of the output of hydrogen source point j; represents the hydrogen purchase volume of hydrogen source point h at the k-th moment in the t-th stage.

26. The planning method of the electricity-hydrogen coupling system considering the carbon-green certificate market and the uncertainty of hydrogen load according to claim 25, characterized in that, The power supply and demand balance constraints are: where, Ω T and Ω LD are the sets of thermal power units and electrical loads respectively; represents the magnitude of electrical load j at time k in stage t; is the magnitude of load shedding of electrical load j at time k in stage t.

27. The planning method of the electricity-hydrogen coupling system considering the carbon-green certificate market and hydrogen load uncertainty according to claim 1, characterized in that, The step of inputting the obtained historical operation data of the electric-hydrogen coupling system and the historical transaction data of the carbon-green certificate market into the electric-hydrogen coupling system planning model, and obtaining the electric-hydrogen coupling system planning scheme after solving and calculating includes: Carry out screening and processing on the obtained historical operation data of the electric-hydrogen coupling system and the historical transaction data of the carbon-green certificate market; Input the processed data into the electro-hydrogen coupling system planning model in sequence, and use a solver to solve it to obtain the electro-hydrogen coupling system planning scheme.

28. A planning system for an electric-hydrogen coupling system considering the carbon-green certificate market and the uncertainty of hydrogen load, characterized in that, It includes: A data acquisition module for acquiring the historical operation data of the electro-hydrogen coupling system and the historical transaction data of the carbon-green certificate market; A scenario construction module for generating a number of typical random scenarios of hydrogen load by using the Monte Carlo simulation method according to the historical operation data of the electro-hydrogen coupling system; A scenario reduction module for reducing the number of the typical random scenarios through the synchronous backward reduction method to obtain typical reduced scenarios; A model construction module for constructing an electro-hydrogen coupling system planning model considering the carbon-green certificate market and the uncertainty of hydrogen load based on the objective function and constraints; A solving and planning module for inputting the obtained historical operation data of the electro-hydrogen coupling system and the historical transaction data of the carbon-green certificate market into the electro-hydrogen coupling system planning model, and obtaining the electro-hydrogen coupling system planning scheme after solving and calculating.

29. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements the steps of the planning method of the electro-hydrogen coupling system considering the carbon-green certificate market and the uncertainty of hydrogen load as described in any one of claims 1 to 27.

30. A computer-readable storage medium, characterized in that, A computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the planning method of the electro-hydrogen coupling system considering the carbon-green certificate market and the uncertainty of hydrogen load as described in any one of claims 1 to 27.

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