CN116316717B - Opportunity constraint scheduling method for electric-hydrogen comprehensive energy system - Google Patents
Opportunity constraint scheduling method for electric-hydrogen comprehensive energy system Download PDFInfo
- Publication number
- CN116316717B CN116316717B CN202310096328.7A CN202310096328A CN116316717B CN 116316717 B CN116316717 B CN 116316717B CN 202310096328 A CN202310096328 A CN 202310096328A CN 116316717 B CN116316717 B CN 116316717B
- Authority
- CN
- China
- Prior art keywords
- hydrogen
- period
- denotes
- electric
- node
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 229910052739 hydrogen Inorganic materials 0.000 title claims abstract description 192
- 239000001257 hydrogen Substances 0.000 title claims abstract description 192
- 238000000034 method Methods 0.000 title claims abstract description 18
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 claims abstract description 135
- 238000004519 manufacturing process Methods 0.000 claims abstract description 29
- 230000005540 biological transmission Effects 0.000 claims abstract description 26
- 150000002431 hydrogen Chemical class 0.000 claims abstract description 17
- 239000011159 matrix material Substances 0.000 claims description 12
- 229910052799 carbon Inorganic materials 0.000 claims description 7
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 238000009826 distribution Methods 0.000 claims description 3
- 238000010438 heat treatment Methods 0.000 claims description 3
- 125000004435 hydrogen atom Chemical group [H]* 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 3
- 238000005457 optimization Methods 0.000 abstract description 8
- 230000008878 coupling Effects 0.000 abstract description 7
- 238000010168 coupling process Methods 0.000 abstract description 7
- 238000005859 coupling reaction Methods 0.000 abstract description 7
- 238000004364 calculation method Methods 0.000 description 3
- 238000011161 development Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000005611 electricity Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 230000000087 stabilizing effect Effects 0.000 description 2
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000010485 coping Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 238000004146 energy storage Methods 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06315—Needs-based resource requirements planning or analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J15/00—Systems for storing electric energy
- H02J15/008—Systems for storing electric energy using hydrogen as energy vector
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/007—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources
- H02J3/0075—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources for providing alternative feeding paths between load and source according to economic or energy efficiency considerations, e.g. economic dispatch
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/28—The renewable source being wind energy
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Power Engineering (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Marketing (AREA)
- Physics & Mathematics (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Game Theory and Decision Science (AREA)
- Educational Administration (AREA)
- Development Economics (AREA)
- Health & Medical Sciences (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention provides an opportunity constraint scheduling method of an electricity-hydrogen comprehensive energy system, which is based on a detailed model of a hydrogen transmission pipeline and considers the joint optimization scheduling of an electric power system and the hydrogen transmission system. First, the coupling of the electricity-hydrogen integrated energy system is considered, and a day-ahead scheduling method of the electricity-hydrogen integrated energy system is provided. And secondly, adopting opportunity constraint to treat uncertainty caused by wind power fluctuation, and providing an opportunity constraint optimization scheduling method of the electricity-hydrogen comprehensive energy system. The invention can not only improve the economical efficiency of the comprehensive energy system through the electric hydrogen production coupling electric-hydrogen network, but also fully consider uncertain factors caused by fluctuation of wind power and ensure the operation reliability of the comprehensive energy system.
Description
Technical Field
The invention belongs to the technical field of economic dispatch of integrated energy systems, and particularly provides an opportunity constraint dispatch method of an electric-hydrogen integrated energy system.
Background
In the important development stage of the hydrogen energy industry, key technologies of hydrogen energy production, transportation, storage and application are continuously broken through, and the coupling between electric power and a hydrogen energy network is continuously deepened. The hydrogen energy is connected into the power system, so that the carbon emission of the power system can be reduced, the problems of peak clipping and valley filling of a power grid, new energy consumption promotion, high-proportion new energy grid connection stability reduction and the like are solved. Related technologies related to hydrogen production and application of hydrogen energy have been researched and developed more, and future hydrogen energy storage and transportation technologies will become important factors influencing the development of the hydrogen energy industry. At present, the hydrogen energy is mainly transported by trucks, the transport capacity is small, the distance is short, and the hydrogen energy transport pipeline can realize large-scale and long-distance hydrogen energy transport, thereby being more suitable for long-term development.
The large-scale grid connection of new energy requires that an electric power system must consider uncertain factors caused by intermittence and fluctuation. In an integrated energy system of electro-hydrogen coupling, uncertainty affects not only the power system, but also the hydrogen delivery system through the electro-hydrogen production device. At present, the research on uncertainty of a power system is mature, and main optimization methods comprise robust optimization and random optimization. Opportunistic constraint optimization is an important branch of random optimization, and is established under a certain confidence level by defining an inequality constraint containing uncertain variables, so as to improve the reliability of the system.
Based on the above description, the scheduling method of the electric-hydrogen comprehensive energy system mainly considers the following two aspects: firstly, taking a detailed model of a hydrogen transmission pipeline into consideration, and carrying out optimized scheduling on a comprehensive energy system; and secondly, on the basis of a day-ahead scheduling model, the uncertainty generated by wind power fluctuation is processed through opportunity bundles.
Disclosure of Invention
The invention aims to: the invention aims to solve the technical problem of overcoming the defects of the prior art and providing an opportunity constraint scheduling method of an electricity-hydrogen comprehensive energy system. The invention can not only reduce the operation cost by coupling the electro-hydrogen network, but also improve the operation reliability of the system by considering the uncertainty of wind power.
The technical scheme is as follows: in order to solve the technical problems, the invention provides an opportunity constraint scheduling method of an electricity-hydrogen comprehensive energy system, which comprises the following steps:
Step 1, acquiring operation parameters of the electric-hydrogen comprehensive energy system, wherein the operation parameters comprise a unit, an electric hydrogen production device, a circuit, a hydrogen source, a pipeline and pressurization station information;
Step 2, obtaining information of electric load, hydrogen load and wind power output;
Step 3, aiming at the operation parameters, the electric load, the hydrogen load and the wind power output information of the electric-hydrogen integrated energy system, using the operation constraint of the electric power system, the operation constraint of the hydrogen transmission system and the electric hydrogen production constraint as constraint conditions, and constructing an objective function with the minimum overall operation cost of the integrated energy system;
And 4, considering uncertainty of wind power output, increasing opportunity constraint of the power system and the hydrogen delivery system based on the constraint condition in the step 3, solving by using GUROBI solver to obtain an optimal solution by taking the expected value of the system running cost as an objective function, and optimally scheduling the electric-hydrogen comprehensive energy system according to the optimal solution.
Further, in step 3, the objective function is:
Wherein, T represents the number of time sections, the subscript T represents the scheduling period, the subscript v represents the traditional unit, and the subscript z represents the hydrogen source; c G2,v and C G1,v respectively represent a secondary cost coefficient and a primary cost coefficient of the conventional unit v, C S,z represents a unit hydrogen supply cost of the hydrogen source z, P G,v,t represents an active force of the conventional unit v in a period t, and F S,z,t represents a hydrogen supply amount of the hydrogen source z in the period t.
Further, in step 3, relevant operation constraints of a day-ahead scheduling model of the energy system are integrated, which are specifically as follows:
1) Power system operation constraints
Wherein: subscripts i and j denote power buses, subscript r denotes a wind turbine generator, subscript d denotes an electrical load, subscript s denotes an electrical hydrogen generating device, E v (i) denotes a conventional set of power generators connected to bus i, E r (i) denotes a set of wind turbines connected to bus i, E d (i) denotes a set of electrical loads connected to bus i, E s (i) denotes a set of electrical hydrogen generating devices connected to bus i, E (i) denotes a set of lines connected to bus i, P W,r,t denotes an output of wind turbines r during period t, P L,d,t denotes a required power of electrical loads d during period t, P PTH,s,t denotes an output of electrical hydrogen generating device s during period t, b ij denotes susceptances of lines i-j, θ i,t and θ j,t respectively denote voltage phase angles of power buses i and j during period t,And/>Respectively represent the upper limit value and the lower limit value of the v output of the traditional generator,/>Representing the predicted value before the day of the wind turbine r,/>Representing the transmission capacity of line i-j,/>The upper limit value of the v adjustment amount of the conventional unit is represented.
2) Hydrogen transport system operating constraints
Wherein subscripts m and n denote hydrogen nodes, subscript e denotes hydrogen load, subscript p denotes hydrogen pressurizing station, H z (m) denotes hydrogen source set connected to node m, H e (m) denotes hydrogen load set connected to node m, H s (m) denotes electric hydrogen generating device set connected to node m, H p (m) denotes pressurizing station set connected to node m, H (m) denotes pipe set connected to node m, H B denotes hydrogen pipe set, F PTH,s,t denotes hydrogen flow rate outputted by electric hydrogen generating device s in period t, F L,e,t denotes hydrogen load e demand flow rate in period t, F C,p,t denotes hydrogen flow rate of hydrogen flowing through pressurizing station p in period t, τ p,t denotes hydrogen flow rate consumed by pressurizing station p in period t, F mn,t and F nm,t denote hydrogen flow rates consumed by pipe m-n head and tail end in period t, respectively,Represents the average hydrogen flow of the pipeline m-n in the period t, W mn represents the Weymouth constant of the pipeline m-n, pi m,t represents the pressure of the node m in the period t, pi n,t represents the pressure of the node n in the period t, L mn,t represents the pipe stock of the pipeline m-n in the period t, K mn represents the pipe stock constant of the pipeline m-n, ζ p represents the percentage of the hydrogen consumed by the pressurizing station p in the transmission flow, and I/ORepresenting the transmission capacity of the pressurizing station p,/>And/>Representing the pressure of the pressurizing station p at the inlet and outlet of the period t respectively,/>And/>Respectively representing the upper limit value and the lower limit value of the pressurizing ratio of the pressurizing station p,/>And/>Respectively represent the upper limit value and the lower limit value of the hydrogen supply amount of the hydrogen source z,/>Represents the upper limit value of the adjustment amount of the hydrogen source z,/>And/>Representing the upper and lower limits of the transmission capacity of the pipe m-n,And/>The upper limit value and the lower limit value of the pressure at the node m are indicated, respectively, and L min represents the lower limit value of the hydrogen gas pipe stock.
3) Constraint of electro-hydrogen production
Wherein η PTH represents the energy conversion efficiency of the electro-hydrogen plant, HHV represents the heating value of the hydrogen,And/>The upper limit value and the lower limit value of the output of the electric hydrogen production device s are respectively shown.
Further, in step 4, the opportunity constraints of the power system and the hydrogen delivery system are:
Where the subscript k represents the number of power system buses and E v (j) represents the set of conventional gensets connected to bus j. Alpha v,t and beta s,t respectively represent participation coefficients of the traditional unit v and the electric hydrogen production device s in a period t, describe the condition of stabilizing wind power fluctuation of the traditional unit and the electric hydrogen production device, B k-1 represents a matrix formed by removing the kth row and the kth column from the node susceptance matrix, Representing the matrix of zero elements of row k and column k after inversion of B k-1, θ k,t representing the voltage phase angle of the power bus k during period t,Representation matrix/>In the ith row and the jth column, delta i,t is an auxiliary variable of the power bus i in a period t and is used for calculating line variance, eta mn,t and eta nm,t respectively represent fluctuation values of head flow and tail flow of a pipeline m-n in the period t due to wind power uncertainty, and the fluctuation values are/areRepresents the fluctuation value of the average flow of the pipeline m-n in the period t due to wind power uncertainty, and lambda m,t and lambda n,t respectively represent the fluctuation value of the pressure of the node m and the node n in the period t due to wind power uncertainty,/>And/>Respectively express/>Elements in the ith row and the jth row in the (a), [ sigma ] r represents variance of r fluctuation value of the wind turbine generator set,/>An inverse function representing standard normal distribution, epsilon representing the probability of out-of-limit, u mn,t and v m,t representing auxiliary variables of pipeline m-n and node m in period t, respectively, for processing bilinear terms,/>, in hydrogen delivery system opportunity constraintsRepresenting the total capacity of the wind power plant,/>And/>Upper and lower values of the variable lambda m,t,/>, respectivelyAnd/>Variable/>, respectivelyUpper and lower limits of (2).
Considering that the output of a traditional generator is a random variable, the running cost is also a random variable related to wind power fluctuation, and cannot be directly obtained, and the minimum expected value of the running cost is adopted as an objective function:
And taking the power system operation constraint, the hydrogen transmission system operation constraint, the electricity-hydrogen production constraint, the power system opportunity constraint and the hydrogen transmission system opportunity constraint as constraint conditions, taking the expected value of the total operation cost of the system as an objective function, solving by using GUROBI solver to obtain an optimal solution, and carrying out optimal scheduling on the electricity-hydrogen comprehensive energy system.
The beneficial effects are that: compared with the prior art, the technical scheme of the invention has the following beneficial technical effects:
The invention considers the coordination of the power system, the hydrogen transmission system and the day-ahead scheduling of the electric hydrogen production device, and researches the influence of uncertain factors of wind power fluctuation on the system. The invention can not only reduce the operation cost by coupling the electro-hydrogen network, but also improve the operation reliability of the system by considering the uncertainty of wind power.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
FIG. 2 is an exemplary diagram of an electro-hydrogen integrated energy system.
Fig. 3 is a line power profile at different confidence levels.
FIG. 4 is a case where the generator and the electro-hydrogen production participate in balancing wind power fluctuations.
Detailed Description
The present application is further illustrated in the accompanying drawings and detailed description which are to be understood as being merely illustrative of the application and not limiting of its scope, since various modifications of the application, which are equivalent to those skilled in the art, will fall within the scope of the application as defined in the appended claims after reading the application.
As shown in fig. 1, the invention provides an opportunity constraint scheduling method of an electricity-hydrogen integrated energy system, which comprises the following steps:
Step 1, acquiring operation parameters of the electric-hydrogen comprehensive energy system, wherein the operation parameters comprise a unit, an electric hydrogen production device, a circuit, a hydrogen source, a pipeline and pressurization station information;
Step 2, obtaining information of electric load, hydrogen load and wind power output;
Step 3, aiming at the operation parameters, the electric load, the hydrogen load and the wind power output information of the electric-hydrogen integrated energy system, using the operation constraint of the electric power system, the operation constraint of the hydrogen transmission system and the electric hydrogen production constraint as constraint conditions, and constructing an objective function with the minimum overall operation cost of the integrated energy system;
And 4, considering uncertainty of wind power output, increasing opportunity constraint of the power system and the hydrogen delivery system based on the constraint condition in the step 3, solving by using GUROBI solver to obtain an optimal solution by taking the expected value of the system running cost as an objective function, and optimally scheduling the electric-hydrogen comprehensive energy system according to the optimal solution.
Further, in step 3, the objective function is:
Wherein, T represents the number of time sections, the subscript T represents the scheduling period, the subscript v represents the traditional unit, and the subscript z represents the hydrogen source; c G2,v and C G1,v respectively represent a secondary cost coefficient and a primary cost coefficient of the conventional unit v, C S,z represents a unit hydrogen supply cost of the hydrogen source z, P G,v,t represents an active force of the conventional unit v in a period t, and F S,z,t represents a hydrogen supply amount of the hydrogen source z in the period t.
Further, in step 3, relevant operation constraints of a day-ahead scheduling model of the energy system are integrated, which are specifically as follows:
1) Power system operation constraints
Wherein: subscripts i and j denote power buses, subscript r denotes a wind turbine generator, subscript d denotes an electrical load, subscript s denotes an electrical hydrogen generating device, E v (i) denotes a conventional set of power generators connected to bus i, E r (i) denotes a set of wind turbines connected to bus i, E d (i) denotes a set of electrical loads connected to bus i, E s (i) denotes a set of electrical hydrogen generating devices connected to bus i, E (i) denotes a set of lines connected to bus i, P W,r,t denotes an output of wind turbines r during period t, P L,d,t denotes a required power of electrical loads d during period t, P PTH,s,t denotes an output of electrical hydrogen generating device s during period t, b ij denotes susceptances of lines i-j, θ i,t and θ j,t respectively denote voltage phase angles of power buses i and j during period t,And/>Respectively represent the upper limit value and the lower limit value of the v output of the traditional generator,/>Representing the predicted value before the day of the wind turbine r,/>Representing the transmission capacity of line i-j,/>The upper limit value of the v adjustment amount of the conventional unit is represented.
2) Hydrogen transport system operating constraints
Wherein subscripts m and n denote hydrogen nodes, subscript e denotes hydrogen load, subscript p denotes hydrogen pressurizing station, H z (m) denotes hydrogen source set connected to node m, H e (m) denotes hydrogen load set connected to node m, H s (m) denotes electric hydrogen generating device set connected to node m, H p (m) denotes pressurizing station set connected to node m, H (m) denotes pipe set connected to node m, H B denotes hydrogen pipe set, F PTH,s,t denotes hydrogen flow rate outputted by electric hydrogen generating device s in period t, F L,e,t denotes hydrogen load e demand flow rate in period t, F C,p,t denotes hydrogen flow rate of hydrogen flowing through pressurizing station p in period t, τ p,t denotes hydrogen flow rate consumed by pressurizing station p in period t, F mn,t and F nm,t denote hydrogen flow rates consumed by pipe m-n head and tail end in period t, respectively,Represents the average hydrogen flow of the pipeline m-n in the period t, W mn represents the Weymouth constant of the pipeline m-n, pi m,t represents the pressure of the node m in the period t, pi n,t represents the pressure of the node n in the period t, L mn,t represents the pipe stock of the pipeline m-n in the period t, K mn represents the pipe stock constant of the pipeline m-n, ζ p represents the percentage of the hydrogen consumed by the pressurizing station p in the transmission flow, and I/ORepresenting the transmission capacity of the pressurizing station p,/>And/>Representing the pressure of the pressurizing station p at the inlet and outlet of the period t respectively,/>And/>Respectively representing the upper limit value and the lower limit value of the pressurizing ratio of the pressurizing station p,/>And/>Respectively represent the upper limit value and the lower limit value of the hydrogen supply amount of the hydrogen source z,/>Represents the upper limit value of the adjustment amount of the hydrogen source z,/>And/>Representing the upper and lower limits of the transmission capacity of the pipe m-n,And/>The upper limit value and the lower limit value of the pressure at the node m are indicated, respectively, and L min represents the lower limit value of the hydrogen gas pipe stock.
3) Constraint of electro-hydrogen production
Wherein η PTH represents the energy conversion efficiency of the electro-hydrogen plant, HHV represents the heating value of the hydrogen,And/>The upper limit value and the lower limit value of the output of the electric hydrogen production device s are respectively shown.
Further, in step 4, the opportunity constraints of the power system and the hydrogen delivery system are:
Where the subscript k represents the number of power system buses and E v (j) represents the set of conventional gensets connected to bus j. Alpha v,t and beta s,t respectively represent participation coefficients of the traditional unit v and the electric hydrogen production device s in a period t, describe the condition of stabilizing wind power fluctuation of the traditional unit and the electric hydrogen production device, B k-1 represents a matrix formed by removing the kth row and the kth column from the node susceptance matrix, Representing the matrix of zero elements of row k and column k after inversion of B k-1, θ k,t representing the voltage phase angle of the power bus k during period t,Representation matrix/>In the ith row and the jth column, delta i,t is an auxiliary variable of the power bus i in a period t and is used for calculating line variance, eta mn,t and eta nm,t respectively represent fluctuation values of head flow and tail flow of a pipeline m-n in the period t due to wind power uncertainty, and the fluctuation values are/areRepresents the fluctuation value of the average flow of the pipeline m-n in the period t due to wind power uncertainty, and lambda m,t and lambda n,t respectively represent the fluctuation value of the pressure of the node m and the node n in the period t due to wind power uncertainty,/>And/>Respectively express/>Elements in the ith row and the jth row in the (a), [ sigma ] r represents variance of r fluctuation value of the wind turbine generator set,/>An inverse function representing standard normal distribution, epsilon representing the probability of out-of-limit, u mn,t and v m,t representing auxiliary variables of pipeline m-n and node m in period t, respectively, for processing bilinear terms,/>, in hydrogen delivery system opportunity constraintsRepresenting the total capacity of the wind power plant,/>And/>Upper and lower values of the variable lambda m,t,/>, respectivelyAnd/>Variable/>, respectivelyUpper and lower limits of (2).
Considering that the output of a traditional generator is a random variable, the running cost is also a random variable related to wind power fluctuation, and cannot be directly obtained, and the minimum expected value of the running cost is adopted as an objective function:
And taking the power system operation constraint, the hydrogen transmission system operation constraint, the electricity-hydrogen production constraint, the power system opportunity constraint and the hydrogen transmission system opportunity constraint as constraint conditions, taking the expected value of the total operation cost of the system as an objective function, solving by using GUROBI solver to obtain an optimal solution, and carrying out optimal scheduling on the electricity-hydrogen comprehensive energy system.
Calculation case analysis
The invention adopts the transformation calculation example of the Belgium 24-node power system and the 20-node hydrogen transmission system, as shown in figure 2. The electric hydrogen production devices of the power system nodes 1-15 are respectively connected with the hydrogen transmission system nodes 16, 16, 10, 10, 10, 15, 15 and 11,6,9,3,3,1,1,1. The wind turbine generator is connected with the power system nodes 1-15. The total capacity of the electric power system is 13.1GW, wherein the wind power generator has a capacity of 2.5GW, and accounts for 19.1% of the total capacity, and the electric power generator has a capacity of 0.4GW, and accounts for 16% of the wind power generator. The method is realized through a GAMS optimization platform, and a GUROBI solver is adopted to solve the QCP problem.
Based on the calculation example, the method provided by the invention is adopted to simulate the opportunity constraint scheduling results of the system under different confidence levels (the results are shown in table 1 and fig. 3), and the regulation power of the traditional unit and the electric hydrogen production device participating in balancing wind power fluctuation is given (the results are shown in fig. 4). The probability of variable out-of-limit can be obviously reduced and the safety margin of system operation can be increased by improving the confidence level under the opportunistic constraint method. Meanwhile, the pressure of the traditional unit for coping with wind power fluctuation can be relieved to a certain extent after the hydrogen production by electricity is considered.
Table 1 scheduling results at different confidence levels
| Confidence level | 0.90 | 0.95 | 0.97 | 0.99 |
| Running cost (M$) | 18.138 | 18.159 | 18.180 | 18.229 |
| Electric hydrogen production output (MW) | 1.357 | 1.602 | 1.679 | 2.222 |
The invention is based on a detailed model of a hydrogen transmission pipeline, and improves the running reliability of the system by an opportunity constraint method by coupling electricity hydrogen with an electricity-hydrogen energy network and simultaneously considering uncertain factors of wind power fluctuation.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any changes or substitutions easily contemplated by those skilled in the art within the scope of the present invention should be included in the scope of the present invention.
Claims (1)
1. The opportunity constraint scheduling method of the electricity-hydrogen comprehensive energy system is characterized by comprising the following steps of:
Step 1, acquiring operation parameters of the electric-hydrogen comprehensive energy system, wherein the operation parameters comprise a unit, an electric hydrogen production device, a circuit, a hydrogen source, a pipeline and pressurization station information;
Step 2, obtaining information of electric load, hydrogen load and wind power output;
Step 3, aiming at the operation parameters, the electric load, the hydrogen load and the wind power output information of the electric-hydrogen integrated energy system, using the operation constraint of the electric power system, the operation constraint of the hydrogen transmission system and the electric hydrogen production constraint as constraint conditions, and constructing an objective function with the minimum overall operation cost of the integrated energy system;
Step 4, considering uncertainty of wind power output, increasing opportunity constraint of the power system and the hydrogen delivery system based on the constraint condition in the step 3, solving by using GUROBI solver to obtain an optimal solution by taking the expected value of the system running cost as an objective function, and carrying out optimal scheduling on the electric-hydrogen comprehensive energy system according to the optimal solution;
in step3, the minimum objective function is:
Wherein, T represents the number of time sections, the subscript T represents the scheduling period, the subscript v represents the traditional unit, and the subscript z represents the hydrogen source; c G2,v and C G1,v respectively represent a secondary cost coefficient and a primary cost coefficient of the conventional unit v, C S,z represents unit hydrogen supply cost of the hydrogen source z, P G,v,t represents active force of the conventional unit v in a period t, and F S,z,t represents hydrogen supply amount of the hydrogen source z in the period t;
in step 3, relevant operation constraints of a day-ahead scheduling model of the energy system are integrated, and the method specifically comprises the following steps:
1) Power system operation constraints
Wherein subscripts i and j denote power buses, subscript r denote wind turbines, subscript d denote electrical loads, subscript s denote electrical hydrogen generating devices, E v (i) denotes a set of conventional generators connected to bus i, E r (i) denotes a set of wind turbines connected to bus i, E d (i) denotes a set of electrical loads connected to bus i, E s (i) denotes a set of electrical hydrogen generating devices connected to bus i, E (i) denotes a set of lines connected to bus i, P W,r,t denotes an output of wind turbines r during period t, P L,d,t denotes a required power of electrical loads d during period t, P PTH,s,t denotes an output of electrical hydrogen generating devices s during period t, b ij denotes a susceptance of lines i-j, θ i,t and θ j,t denote voltage phase angles of power buses i and j, respectively, during period t,And/>Respectively represent the upper limit value and the lower limit value of the v output of the traditional generator,/>Representing the predicted value before the day of the wind turbine r,/>Representing the transmission capacity of line i-j,/>The upper limit value of the v adjustment quantity of the traditional unit is represented;
2) Hydrogen transport system operating constraints
Wherein subscripts m and n denote hydrogen nodes, subscript e denotes hydrogen load, subscript p denotes hydrogen pressurizing station, H z (m) denotes hydrogen source set connected to node m, H e (m) denotes hydrogen load set connected to node m, H s (m) denotes electric hydrogen generating device set connected to node m, H p (m) denotes pressurizing station set connected to node m, H (m) denotes pipe set connected to node m, H B denotes hydrogen pipe set, F PTH,s,t denotes hydrogen flow rate outputted by electric hydrogen generating device s in period t, F L,e,t denotes hydrogen load e demand flow rate in period t, F C,p,t denotes hydrogen flow rate of hydrogen flowing through pressurizing station p in period t, τ p,t denotes hydrogen flow rate consumed by pressurizing station p in period t, F mn,t and F nm,t denote hydrogen flow rates consumed by pipe m-n head and tail end in period t, respectively,Represents the average hydrogen flow of the pipeline m-n in the period t, W mn represents the Weymouth constant of the pipeline m-n, pi m,t represents the pressure of the node m in the period t, pi n,t represents the pressure of the node n in the period t, L mn,t represents the pipe stock of the pipeline m-n in the period t, K mn represents the pipe stock constant of the pipeline m-n, ζ p represents the percentage of the hydrogen consumed by the pressurizing station p in the transmission flow, and I/ORepresenting the transmission capacity of the pressurizing station p,/>And/>Representing the pressure of the pressurizing station p at the inlet and outlet of the period t respectively,/>And/>Respectively representing the upper limit value and the lower limit value of the pressurizing ratio of the pressurizing station p,/>And/>Respectively represent the upper limit value and the lower limit value of the hydrogen supply amount of the hydrogen source z,/>Represents the upper limit value of the adjustment amount of the hydrogen source z,/>And/>Representing the upper and lower limit values of the transmission capacity of the pipeline m-n,/>And (3) withRespectively representing an upper limit value and a lower limit value of the pressure of the node m, and L min represents a lower limit value of the hydrogen pipe stock;
3) Constraint of electro-hydrogen production
Wherein η PTH represents the energy conversion efficiency of the electro-hydrogen plant, HHV represents the heating value of the hydrogen,And/>Respectively representing an upper limit value and a lower limit value of the s output of the electric hydrogen production device;
In step 4, the opportunity constraints of the power system and the hydrogen delivery system are:
Wherein the subscript k represents the number of buses of the power system, E v (j) represents a conventional generator set connected with the buses j, alpha v,t and beta s,t respectively represent participation coefficients of the conventional generator set v and the electric hydrogen production device s in a period t, B k-1 represents a matrix formed by removing the kth row and the kth column from the node susceptance matrix, Represents a matrix formed by inverting B k-1 and zero elements of the kth row and the kth column, theta k,t represents a voltage phase angle of the power bus k in a period t,/>, andRepresentation matrix/>In the ith row and the jth column, delta i,t is an auxiliary variable of the power bus i in a period t and is used for calculating line variance, eta mn,t and eta nm,t respectively represent fluctuation values of head flow and tail flow of a pipeline m-n in the period t due to wind power uncertainty, and the fluctuation values are/areRepresents the fluctuation value of the average flow of the pipeline m-n in the period t due to wind power uncertainty, and lambda m,t and lambda n,t respectively represent the fluctuation value of the pressure of the node m and the node n in the period t due to wind power uncertainty,/>And/>Respectively express/>Elements in the ith row and the jth row in the (a), [ sigma ] r represents variance of r fluctuation value of the wind turbine generator set,/>An inverse function representing standard normal distribution, epsilon representing the probability of out-of-limit, u mn,t and v m,t representing auxiliary variables of pipeline m-n and node m in period t, respectively, for processing bilinear terms,/>, in hydrogen delivery system opportunity constraintsRepresenting the total capacity of the wind power plant,/>And/>Upper and lower values of the variable lambda m,t,/>, respectivelyAnd/>Variable/>, respectivelyUpper and lower limits of (2);
the minimum expected value of the running cost is adopted as an objective function:
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310096328.7A CN116316717B (en) | 2023-02-10 | 2023-02-10 | Opportunity constraint scheduling method for electric-hydrogen comprehensive energy system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310096328.7A CN116316717B (en) | 2023-02-10 | 2023-02-10 | Opportunity constraint scheduling method for electric-hydrogen comprehensive energy system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116316717A CN116316717A (en) | 2023-06-23 |
| CN116316717B true CN116316717B (en) | 2024-05-28 |
Family
ID=86798763
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310096328.7A Active CN116316717B (en) | 2023-02-10 | 2023-02-10 | Opportunity constraint scheduling method for electric-hydrogen comprehensive energy system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116316717B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109241655A (en) * | 2018-09-27 | 2019-01-18 | 河海大学 | A kind of electric-thermal interconnection integrated energy system chance constraint coordination optimizing method |
| CN109741110A (en) * | 2019-01-07 | 2019-05-10 | 福州大学 | A kind of wind hydrogen system combined optimization modeling method based on chance constrained programming |
| CN110009152A (en) * | 2019-04-03 | 2019-07-12 | 东南大学 | A kind of consideration electricity turns gas and probabilistic regional complex energy system operation robust Optimal methods |
| CN113629736A (en) * | 2021-08-12 | 2021-11-09 | 国网江苏省电力有限公司常州供电分公司 | Intraday rolling optimization method based on power distribution network hydrogen energy storage system |
| CN115619006A (en) * | 2022-09-23 | 2023-01-17 | 河海大学 | Electricity-gas-hydrogen series-parallel connection comprehensive energy system optimization scheduling method considering auxiliary service |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2021108745A1 (en) * | 2019-11-27 | 2021-06-03 | Cruickshank Iii Robert F | An optimized load shaping system, method & apparatus for optimizing production and consumption of energy |
-
2023
- 2023-02-10 CN CN202310096328.7A patent/CN116316717B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109241655A (en) * | 2018-09-27 | 2019-01-18 | 河海大学 | A kind of electric-thermal interconnection integrated energy system chance constraint coordination optimizing method |
| CN109741110A (en) * | 2019-01-07 | 2019-05-10 | 福州大学 | A kind of wind hydrogen system combined optimization modeling method based on chance constrained programming |
| CN110009152A (en) * | 2019-04-03 | 2019-07-12 | 东南大学 | A kind of consideration electricity turns gas and probabilistic regional complex energy system operation robust Optimal methods |
| CN113629736A (en) * | 2021-08-12 | 2021-11-09 | 国网江苏省电力有限公司常州供电分公司 | Intraday rolling optimization method based on power distribution network hydrogen energy storage system |
| CN115619006A (en) * | 2022-09-23 | 2023-01-17 | 河海大学 | Electricity-gas-hydrogen series-parallel connection comprehensive energy system optimization scheduling method considering auxiliary service |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116316717A (en) | 2023-06-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110135631B (en) | Electric comprehensive energy system scheduling method based on information gap decision theory | |
| CN109741110B (en) | Opportunity constraint planning-based wind-hydrogen system joint optimization modeling method | |
| CN101281637A (en) | Electric power system optimizing swim and real time pricing method based on hyperplane form safety field periphery | |
| CN113217131B (en) | Electric heating load scheduling method of multi-energy complementary cogeneration system based on carbon emission reduction | |
| CN115619006B (en) | Electric-gas-hydrogen series-parallel comprehensive energy system optimization scheduling method considering auxiliary service | |
| CN113489003B (en) | Source network coordination planning method considering wind-light-water integrated complementary operation | |
| CN112053035A (en) | Power transmission channel and energy storage joint planning method considering economy and flexibility | |
| CN112018756A (en) | Day-ahead robust coordinated optimization scheduling method for gas-electricity combined system | |
| CN110783950A (en) | Method for determining photovoltaic optimal configuration capacity of power distribution network node | |
| CN116247719A (en) | Micro-grid two-stage robust optimal configuration method based on ladder carbon transaction | |
| CN116826729A (en) | Robust optimal configuration method for multi-source combined system considering wind and light uncertainty | |
| CN115099063A (en) | Operation optimization method for electricity-mixed hydrogen natural gas coupling comprehensive energy system | |
| CN109510238B (en) | Coordinated dispatching unit combination method for efficiently solving hydroelectric power, thermal power and wind power | |
| CN110994697A (en) | Optimal operation control method and system for alternating current-direct current distribution network containing light storage complex | |
| CN116316717B (en) | Opportunity constraint scheduling method for electric-hydrogen comprehensive energy system | |
| CN112713615B (en) | Quick coordination scheduling method and system for electricity-gas integrated energy system | |
| CN115293518B (en) | Low-carbon economic dispatching method of gas-electricity coupling comprehensive energy system considering flexible climbing | |
| CN112836957A (en) | Regional comprehensive energy system planning method considering power supply reliability | |
| CN110377973B (en) | Construction method of standard linear comprehensive energy system model | |
| CN110189231B (en) | Method for determining optimal power supply scheme of power grid based on improved genetic algorithm | |
| CN109492809B (en) | Wind power plant value evaluation method based on node electricity price | |
| CN113221358B (en) | Standby output optimization method of electric-gas coupling system based on reliability parameters | |
| CN115719972A (en) | Energy-saving loss-reducing optimization method for connecting distributed power supply to power distribution network | |
| CN109447715B (en) | Node electricity price calculation method considering wind power grid-connected transmission margin value | |
| CN112270481A (en) | Multi-target planning method and system for power and natural gas coupling system and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |