CN117713251B - Steady-state multi-energy flow calculation method and system of electro-hydro-carbon multi-energy system - Google Patents
Steady-state multi-energy flow calculation method and system of electro-hydro-carbon multi-energy system Download PDFInfo
- Publication number
- CN117713251B CN117713251B CN202410160386.6A CN202410160386A CN117713251B CN 117713251 B CN117713251 B CN 117713251B CN 202410160386 A CN202410160386 A CN 202410160386A CN 117713251 B CN117713251 B CN 117713251B
- Authority
- CN
- China
- Prior art keywords
- hydrogen
- energy
- flow
- carbon
- 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
- 238000004364 calculation method Methods 0.000 title claims abstract description 41
- 239000004215 Carbon black (E152) Substances 0.000 title claims description 13
- 229910052739 hydrogen Inorganic materials 0.000 claims abstract description 222
- 239000001257 hydrogen Substances 0.000 claims abstract description 221
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 claims abstract description 174
- 229910052799 carbon Inorganic materials 0.000 claims abstract description 173
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 claims abstract description 147
- 238000000034 method Methods 0.000 claims abstract description 76
- 239000011159 matrix material Substances 0.000 claims abstract description 37
- 230000005540 biological transmission Effects 0.000 claims abstract description 28
- 238000009826 distribution Methods 0.000 claims abstract description 17
- 150000002431 hydrogen Chemical class 0.000 claims description 26
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 claims description 22
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 claims description 22
- 239000013598 vector Substances 0.000 claims description 22
- 239000007789 gas Substances 0.000 claims description 16
- 230000035425 carbon utilization Effects 0.000 claims description 14
- 238000002347 injection Methods 0.000 claims description 13
- 239000007924 injection Substances 0.000 claims description 13
- 238000010248 power generation Methods 0.000 claims description 13
- 229910002092 carbon dioxide Inorganic materials 0.000 claims description 11
- 239000001569 carbon dioxide Substances 0.000 claims description 11
- 230000009919 sequestration Effects 0.000 claims description 11
- 239000003345 natural gas Substances 0.000 claims description 10
- 238000005516 engineering process Methods 0.000 claims description 9
- 239000000446 fuel Substances 0.000 claims description 9
- 238000006243 chemical reaction Methods 0.000 claims description 7
- 239000000203 mixture Substances 0.000 claims description 7
- 238000010438 heat treatment Methods 0.000 claims description 6
- 238000005265 energy consumption Methods 0.000 claims description 4
- 230000006835 compression Effects 0.000 claims description 3
- 238000007906 compression Methods 0.000 claims description 3
- 238000012937 correction Methods 0.000 claims description 3
- 239000011203 carbon fibre reinforced carbon Substances 0.000 claims description 2
- 230000003647 oxidation Effects 0.000 claims description 2
- 238000007254 oxidation reaction Methods 0.000 claims description 2
- 230000004927 fusion Effects 0.000 abstract description 5
- 230000008569 process Effects 0.000 description 17
- 239000000243 solution Substances 0.000 description 12
- 230000008878 coupling Effects 0.000 description 8
- 238000010168 coupling process Methods 0.000 description 8
- 238000005859 coupling reaction Methods 0.000 description 8
- 241000283690 Bos taurus Species 0.000 description 7
- 238000011160 research Methods 0.000 description 7
- 230000008901 benefit Effects 0.000 description 6
- 230000006870 function Effects 0.000 description 6
- 230000009467 reduction Effects 0.000 description 6
- 230000000694 effects Effects 0.000 description 5
- 238000003860 storage Methods 0.000 description 5
- 238000004458 analytical method Methods 0.000 description 4
- 239000007788 liquid Substances 0.000 description 4
- 238000010276 construction Methods 0.000 description 3
- 238000011161 development Methods 0.000 description 3
- 230000003993 interaction Effects 0.000 description 3
- 238000013178 mathematical model Methods 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 238000000354 decomposition reaction Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 230000007246 mechanism Effects 0.000 description 2
- 239000007787 solid Substances 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 239000003245 coal Substances 0.000 description 1
- 238000006880 cross-coupling reaction Methods 0.000 description 1
- -1 density Chemical compound 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 230000008278 dynamic mechanism Effects 0.000 description 1
- 230000005672 electromagnetic field Effects 0.000 description 1
- 238000004146 energy storage Methods 0.000 description 1
- 239000002803 fossil fuel Substances 0.000 description 1
- 230000001939 inductive effect Effects 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 229910052987 metal hydride Inorganic materials 0.000 description 1
- 150000004681 metal hydrides Chemical class 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 238000000611 regression analysis Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000012546 transfer Methods 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
- H02J3/38—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
-
- 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
- H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
-
- 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
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
-
- 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]
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a steady-state multi-energy flow calculation method and a steady-state multi-energy flow calculation system of an electro-hydrogen-carbon multi-energy system, and relates to the technical field of electro-hydrogen-carbon multi-energy, wherein the method comprises the following steps: constructing a power network tide model, a hydrogen energy steady-state transmission model and a carbon flow collection traceability model; establishing an electro-hydrogen unified energy path model; solving the electro-hydrogen unified energy path model based on a cow pulling method to obtain a state variable of a power network tide model; calculating a power network energy flow by adopting the power network power flow model based on state variables of the power network power flow model; calculating the energy flow of a hydrogen energy network by adopting a hydrogen energy steady-state transmission model based on the path flow of the long tube trailer and the density and heat value influence factors; and calculating the energy flow of the carbon flow network by adopting a carbon flow collection traceability model based on the tide distribution matrix, the carbon emission intensity and the active power of the power system source branch. The steady-state multi-energy flow of the electro-hydrogen-carbon multi-energy system is obtained through modeling and calculation solving of the multi-energy flow network of the electro-hydrogen-carbon fusion energy system.
Description
Technical Field
The invention relates to the technical field of electro-hydrogen-carbon multi-energy sources, in particular to a steady-state multi-energy flow calculation method and system of an electro-hydrogen-carbon multi-energy source system.
Background
Along with the increasingly outstanding problems of energy crisis and climate change, the development of clean renewable energy and the reduction of excessive consumption of fossil fuel are of great significance for the construction of novel power systems and the sustainable development of low carbon. The hydrogen energy is used as clean energy with high energy density, long service life and convenient storage and transportation, has the characteristic of being mutually coupled with the wind-solar power generation technology, can fully exert the advantages of long-term energy storage and power regulation, and further improves the grid connection stability of the renewable energy. Because the carbon flow can be equivalently decomposed, converged and transmitted along with the current and the hydrogen flow on the power network and the hydrogen pipeline, the cross coupling relation between the electric hydrogen conversion process and the carbon flow is not negligible. On one hand, the power generation ratio of clean energy sources such as distributed clean energy sources, coal/gas burning units, distributed hydrogen producing units and the like directly determine the carbon emission and the electric hydrogen conversion; on the other hand, carbon utilization behaviors such as methane production by hydrogen and carbon dioxide, carbon sequestration technology and energy consumption requirements of users and carbon emission reduction measures have direct influence on carbon flow and energy flow distribution. Considering the coupling relation among the electric power flow, the hydrogen energy flow and the carbon flow, it is necessary to research the steady-state multi-energy flow calculation of the electric hydrogen-carbon multi-energy system.
The power network modeling is divided into an ac model and a dc model. The alternating current model considers node active power and reactive power, and considers influence factors such as voltage phase angle difference at the head and the tail of a line, ground conductance and the like, so that the calculation is accurate, and the practical application is more. In comparison, the direct current model ignores reactive power, only considers active power balance of nodes generally, only considers influence of voltage phase angle, has low calculation accuracy, and is suitable for quick calculation occasions. The existing researches lack steady-state modeling of hydrogen energy flow aiming at a hydrogen energy transportation network alone, and most of the existing researches are used for researching a dynamic model of a hydrogen-doped natural gas network. The hydrogen-loaded natural gas network generally builds partial differential equations for gas flow and node pressure based on differences in gas heating value and density and hydrogen loading ratio. The carbon emission flow theory is used as a main analysis tool for low-carbon optimized operation research of the electric power system, so that the overall carbon emission of the system can be accurately obtained, and the emission of a power plant can be fairly distributed to the loads of all nodes and the power of all branches, so that the carbon emission in the system is tracked, the carbon emission responsibilities on both sides of a source load can be more reasonably distributed, and the carbon emission reduction potential of a user side can be further excavated. However, the existing carbon flow calculation study only considers the carbon emission responsibility of the power generation side in the description of the carbon flow index, and does not consider the carbon emission reduction and carbon utilization benefits of the user side. Accordingly, there is still a need for in-depth research into hydrogen flow models for hydrogen energy system transportation networks and pipeline transportation networks, and carbon flow models that take into account carbon emission reduction and carbon utilization benefits.
The mainstream multi-energy flow unified modeling method at home and abroad comprises an energy junction method, a unified energy path method and an energy network method. The energy hub method abstracts a multi-energy flow system into an input-output dual-port network, and describes conversion, storage and distribution relations among energy sources by utilizing a multi-energy coupling matrix; the unified energy path method converts a multi-energy flow network into an energy path diagram represented by a plurality of capacitive, inductive and resistive energy path elements and connected branches by referring to the deduction theory from an electromagnetic field to a circuit of a power system, and is widely applied to analysis of thermal paths, gas paths and waterways; the energy network method is based on energy essence and dynamic mechanism, and builds a unified mathematical model to represent the coupling-conversion-transmission relation among energy flow systems. The common solving method of the multi-energy flow can be divided into two ideas of a unified solving method and a decomposing solving method. The unified solution method is to carry out simultaneous iterative solution on the energy flow equation of each energy sub-network as a whole, and the solution algorithm is generally a Newton-Laporton method or a Gaussian iteration method. Compared with a decomposition solution method, the unified solution method has the advantages of small iteration times and high calculation speed, but the difference of energy flow equations is large, the decomposition solution method decouples all subsystems and solves all the subsystems in an iterative manner, the method has the advantages of relatively independent calculation, high single iteration speed and good convergence, and the calculation efficiency is reduced due to excessive iteration times. However, the existing research focuses on modeling and calculating the energy flow of an electric-gas coupling, an electric, a thermal coupling and an electric-gas-thermal coupling multi-energy system, and does not consider the interaction model relation between an electric hydrogen energy source and a carbon flow and the solving method of the electric-hydrogen-carbon multi-energy flow.
Disclosure of Invention
Based on the above, the invention aims to provide a steady-state multi-energy flow calculation method and a steady-state multi-energy flow calculation system of an electro-hydrogen-carbon multi-energy system, which are used for obtaining the steady-state multi-energy flow of the electro-hydrogen-carbon multi-energy system through modeling and calculation solution of a multi-energy flow network of the electro-hydrogen-carbon fusion energy system.
In order to achieve the above object, the present invention provides the following solutions: a steady-state multi-energy flow calculation method for an electro-hydro-carbon multi-energy system, comprising: constructing a power network tide model, a hydrogen energy steady-state transmission model and a carbon flow collection traceability model; establishing an electro-hydrogen unified energy path model based on a unified energy flow theory; solving the electro-hydrogen unified energy path model based on a cow pulling method to obtain a state variable of the power network tide model; calculating a power network energy flow using the power network power flow model based on state variables of the power network power flow model; the power network energy flow includes injection power of a power system source node; calculating the energy flow of a hydrogen energy network by adopting the hydrogen energy steady-state transmission model based on the path flow of the long tube trailer and the density and heat value influence factors; the hydrogen energy network energy flow comprises the hydrogen delivery quantity of a long pipe trailer hydrogen delivery traffic network and a pipeline network; calculating the energy flow of a carbon flow network by adopting the carbon flow collection traceability model based on the tide distribution matrix, the carbon emission intensity and the active power of the power system source branch; the carbon flow network energy flow comprises the carbon utilization amount of the methane-methanolic reactor, the carbon emission amount reduced by adopting a carbon sequestration technology and the node carbon potential index.
In order to achieve the above purpose, the present invention also provides the following solutions: a steady state multi-energy flow computing system for an electro-hydro-carbon multi-energy system, comprising: the electric hydrogen-carbon multi-energy system model building module is used for building a power network tide model, a hydrogen energy steady-state transmission model and a carbon flow collection traceability model; the electric hydrogen unified energy path model building module is used for building an electric hydrogen unified energy path model based on a unified energy flow theory; the solving module is used for solving the electro-hydrogen unified energy path model based on a cow pulling method to obtain a state variable of the power network power flow model; a power network energy flow calculation module for calculating a power network energy flow using the power network power flow model based on state variables of the power network power flow model; the power network energy flow includes injection power of a power system source node; the hydrogen energy network energy flow calculation module is used for calculating the hydrogen energy network energy flow by adopting the hydrogen energy steady-state transmission model based on the path flow, the density and the heat value influence factor of the long tube trailer; the hydrogen energy network energy flow comprises the hydrogen delivery quantity of a long pipe trailer hydrogen delivery traffic network and a pipeline network; the carbon flow network energy flow calculation module is used for calculating the carbon flow network energy flow by adopting the carbon flow collection traceability model based on the tide distribution matrix, the carbon emission intensity and the active power of the power system source branch; the carbon flow network energy flow comprises the carbon utilization amount of the methane-methanolic reactor, the carbon emission amount reduced by adopting a carbon sequestration technology and the node carbon potential index.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects: according to the invention, the multi-energy network modeling is carried out on the electric power network, the hydrogen energy network and the carbon flow network, and the steady-state multi-energy flow of the electric hydrogen-carbon multi-energy system is obtained by solving, namely, the electric power network energy flow, the hydrogen energy network energy flow and the carbon flow network energy flow, so that a basic scene can be provided for the problems of optimal operation and collaborative planning of the electric hydrogen-carbon multi-energy system under the time scale of the week and the time scale of the year, the multi-scale electric power energy balance analysis method of the electric hydrogen-carbon comprehensive energy system taking electric hydrogen as secondary energy, the energy interaction mechanism of the electric hydrogen-carbon fusion energy system, multilateral transactions and the like.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a steady-state multi-energy flow calculation method of an electro-hydro-carbon multi-energy system provided by the invention.
FIG. 2 is a detailed flow chart of a steady-state multi-energy flow calculation method for an electro-hydro-carbon multi-energy system according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide a steady-state multi-energy flow calculation method and system of an electro-hydrogen-carbon multi-energy system.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
Embodiment one: the embodiment provides a steady-state multi-energy flow calculation method of an electro-hydro-carbon multi-energy system, as shown in fig. 1-2, and the method comprises steps S1-S6.
S1: and constructing a power network tide model, a hydrogen energy steady-state transmission model and a carbon flow collection traceability model.
S2: and establishing an electric hydrogen unified energy path model based on a unified energy flow theory.
S3: and solving the electro-hydrogen unified energy path model based on a cow pulling method to obtain a state variable of the power network tide model.
S4: calculating a power network energy flow by adopting the power network power flow model based on state variables of the power network power flow model; the power network energy flow comprises injection power of the power system source node.
S5: calculating the energy flow of a hydrogen energy network by adopting a hydrogen energy steady-state transmission model based on the path flow of the long tube trailer and the density and heat value influence factors; the hydrogen energy network energy flow includes hydrogen energy network and pipeline network node injection traffic.
S6: calculating the energy flow of a carbon flow network by adopting a carbon flow collection traceability model based on the tide distribution matrix, the carbon emission intensity and the active power of a power system source branch; the carbon flow network energy flow comprises the carbon utilization amount of the methane-methanolic reactor, the carbon emission amount reduced by adopting a carbon sequestration technology and the node carbon potential index.
Further, step S1 specifically includes steps S11 to S13.
S11: and constructing a power network tide model.
For a given network topology, node voltage and power of the power system under a specific scenario can be solved based on node voltage equations. The construction of the power network power flow model meets the power balance and simultaneously limits the equipment operation power to the upper and lower limit ranges of rated power and meets the bus operation currentNot exceeding the rated current/>Etc.
(1)。
(2)。
(3)。
(4)。
(5)。
In the method, in the process of the invention,And/>Respectively, node/>Active power and reactive power are injected into the reactor; /(I)For node/>Is set to the voltage amplitude of (1); /(I)For node/>Is set to the voltage amplitude of (1); n is the number of nodes; /(I)、/>、/>The conductance, susceptance and phase angle of branch ij respectively; /(I)For node/>Active power of the connected power generation equipment; /(I)For node/>Reactive power of the connected power generation equipment; /(I)And/>The upper limit and the lower limit of the active power of the power generation equipment connected with the node i are respectively set; /(I)And/>The upper limit and the lower limit of reactive power of the power generation equipment connected with the node i are respectively set; /(I)And/>Respectively, node/>Upper and lower limits of the voltage amplitude of (a).
S12: and constructing a hydrogen energy steady-state transmission model.
The hydrogen transportation modes mainly comprise gas hydrogen transportation, liquid hydrogen transportation and solid hydrogen transportation according to different hydrogen storage states and transportation quantities. The gaseous transportation is divided into two types, namely long tube trailer transportation and pipeline transportation, the long tube trailer transportation technology has low operation cost and relatively small energy consumption, and the hydrogen filling and discharging response speed is high, so that the method is applicable to short-distance and user-dispersed occasions and is the most common storage and transportation mode used at present; the pipeline hydrogen transportation cost is low, the energy consumption is low, the hydrogen energy continuity, the large-scale and long-distance transportation can be realized, and the pipeline hydrogen transportation method is a necessary development trend for large-scale utilization of hydrogen energy in the future. The liquid transportation is suitable for long-distance and large-capacity transportation, and can be carried by a liquid hydrogen tank truck or a special liquid hydrogen barge. The hydrogen energy stored by the metal hydride can adopt a richer transportation means, and transportation means such as barges, large tank cars and the like can be used for transporting solid hydrogen. In consideration of two aspects of transportation cost and potential safety hazard, the invention mainly researches the construction of a long-tube trailer hydrogen transportation network model and a pipeline hydrogen transportation flow balance model.
It is contemplated that the travel time of long tube trailers in a traffic network may be affected by the effects of road congestion, i.e., the more vehicles that are carried on a road segment, the longer the time required to traverse the road segment. Thus, a time delay function based on the road segment predicted flow can be constructed to represent the effect of hydrogen transportation road congestion. From traffic surveys, regression analysis of a large number of road segments by the united states highway office (Bureau of Public Road, BPR), it was found that: the road section travel time is a strictly increasing function of the road section traffic flow, and both satisfy the BPR function relationship shown in the formula (6).
(6)。
In the method, in the process of the invention,Time/>Long tube trailer/>At road section/>Is used for predicting the driving time of the vehicle; /(I)Indicating long tube trailerAt road section/>Travel time in a free-flow state (the vehicle can travel freely without traffic jam); /(I)And/>Respectively represent road segments/>At time/>And its road traffic volume. Based on/>Long tube trailer/>At node/>AndPredicted travel time of different paths betweenCan be expressed as:
(7)。
In the method, in the process of the invention, Representing nodes/>And/>Long tube trailerTravel route/>And road segment/>When node/>AndPath betweenRoad segment of passing by1 When the time is equal to or 0 when the time is equal to or less than the time; /(I)Representing a collection of traffic network segments. In the actual transportation process, the long tube trailer predicts the driving time based on different paths, and the path trip with the minimum delay cost and the shortest distance is always prone to be selected in the path decision, so that the negative exponential function is adopted to describe the actual path flow/>, of the long tube trailerAnd the relationship between the route prediction travel time and the route distance, as shown in the formula (8):
(8)。
In the middle of Maximum capacity for the predicted path; /(I)Is a decision coefficient, and the larger the travel willingness of the long-tube trailer is, the smaller the decision coefficient is; /(I)Representing road segment/>Is a length of (c). To ensure traffic conservation of the actual traffic network, nodes/>And/>Between at time/>The total traffic flow of (a) should be equal to the sum of traffic flows on all paths between two nodes; meanwhile, the time delay effect of the long tube trailer is considered, and nodes/>, in the traffic network topologyAt time/>Traffic flow of (1) should sum node/>At time/>Is kept consistent. Thus, a traffic network model of the hydrogen delivery of a long tube trailer is shown below.
(9)。
(10)。
In the method, in the process of the invention,Representing the amount of hydrogen fixedly transported by each long tube trailer; /(I)Representing nodes/>At time/>The amount of hydrogen transported by the tube trailer; /(I)Representing nodes/>At time/>The amount of hydrogen transported by the tube trailer; Representing nodes/> And/>A set of path connections between.
The traditional natural gas network energy flow calculation is to calculate the values of the gas flow in the pipeline and the node pressure under the conditions of the gas load demand, the reference source pressure and the gas source composition of a given node. Based on density and heat value influence factors in consideration of difference of characteristics of hydrogen and natural gas such as density, heat value and the likeAnd constructing a pipeline hydrogen delivery flow balance model.
(11)。
(12)。
(13)。
(14)。
In the method, in the process of the invention,And/>Respectively represent the densities of hydrogen and natural gas; /(I)And/>Respectively represent the heating values of hydrogen and natural gas; /(I)And/>Respectively representing weight coefficients; /(I)Representing nodes/>Hydrogen mass flow rate of (2); /(I)And/>Respectively represent nodes/>The mass flow rate of the injected hydrogen and the mass flow rate of the hydrogen on the hydrogen conveying pipeline; /(I)Is a hydrogen conveying pipeline set; Is the pipe coefficient; /(I) 、/>、/>、/>And/>The standard condition pressure, the standard condition temperature, the gas compression coefficient and the friction resistance coefficient are respectively; /(I)Represents hydrogen density; /(I)And/>The inner diameter and the length of the pipeline are respectively; /(I)、、/>The pressure of the node k, the pressure of the node l and the pressure square difference of the node k and the node l are respectively; when/>In the time-course of which the first and second contact surfaces,When/>Time,/>。
S13: and constructing a carbon flow collection traceability model.
The carbon emission flows are distributed in all links of production, transmission and consumption of the power network and the hydrogen energy network, so that a carbon flow collection traceability model is required to be constructed based on tide tracking and proportion sharing principles. By establishing a carbon flow collection traceability model, responsibility can be intuitively allocated to carbon emission of the electro-hydrogen coupled energy network, so that a more effective energy-saving and emission-reduction strategy is formulated. For nodes in a power flow networkNode power conservation constraints are considered, i.e., the ingress node power is equal to the egress node power.
(15)。
(16)。
In the method, in the process of the invention,And/>Respectively, node/>The upper power generation injection power and the load outflow power; /(I)For node/>The load on the load flows out of the power; /(I)For node/>Flow direction node/>Active power of (2); /(I)And/>Respectively, node/>And node/>Is a phase angle of (2); /(I)Is a branch circuitImpedance of (c); /(I)For and node/>Connected and active flow to node/>Is defined by a node set. Based on the tide relation and the proportion sharing principle, a tide distribution matrix/>, which reflects the correlation of the generated power and the load power, can be deducedAnd a matrix form of formula (15), specifically as follows:
(17)。
(18)。
In the method, in the process of the invention, And/>The vector is composed of each node generator and load active power; /(I)Is the power flow distribution matrix/>Line/>Column elements. /(I)、/>Respectively is/>Active power of the generator and the load. Considering that the carbon emissions of the electric power system are mainly derived from the tail gas generated by the fuel generating set, the carbon emission intensity/>, which describes the carbon emission amount generated by the unit electric energy produced by the set, can be adoptedTo express:
(19)。
(20)。
In the method, in the process of the invention, Active output of the fuel unit; /(I)And/>The carbon content and the carbon oxidation rate of the unit fuel are respectively; Is carbon capture efficiency; /(I) And/>The molar mass of carbon dioxide and carbon respectively; /(I)And/>、/>、/>Respectively, units/>Fuel consumption and characteristic parameters per unit of electric energy; /(I)Is a correction coefficient. Introduction of bypass carbon flow Rate/>Branch carbon flow density/>Node carbon potential/>Three carbon emission flow basic indexes, wherein the branch carbon flow rate is defined as the carbon emission quantity generated by maintaining the active power flow of the system in unit time of the power plant; the branch carbon flow density is used for describing the relation between the branch carbon emission flow and the active power flow; the node carbon potential refers to the ratio of the sum of the carbon flow rates into the node expressed as the bypass carbon flow rate and the carbon utilization/>, for the methane-methanolic reactor to the node's outflow powerReduced carbon emissions/>, using carbon sequestration techniquesDifference between them.
(21)。
(22)。
(23)。
(24)。
(25)。
In the method, in the process of the invention,Is a unit column vector; /(I)A vector formed by the carbon emission intensity of the unit; /(I)Is the molar mass of hydrogen; /(I)Is the reaction proportionality coefficient of hydrogen and carbon dioxide; /(I)For node/>The total hydrogen amount of the methane-methanolic reactor is supplied by a hydrogen energy network; /(I)For node/>The total mass of carbon dioxide captured by the carbon capture device connected thereto.
Further, step S2 specifically includes: considering that the carbon emission flow is a virtual carbon emission network flow attached to the power flow in order to ensure the branch flow in the power system, the electric-hydrogen-carbon coupling mode is simplified into the solution of the electric-hydrogen coupling mode, and then the flow calculation of the carbon flow is carried out independently. When uniformly modeling two heterogeneous energy sources, namely an electric power flow and a hydrogen flow, the energy flow process is generally analyzed by adopting a uniform energy path method so as to establish a network equation with a similar mathematical form.
(1) A circuit network equation for a power system.
Medium-length lines in power systems are generally usedThe equivalent circuit is used for representing, and the corresponding mathematical model is solved by adopting a node voltage method, as follows:
(26)。
In the method, in the process of the invention, The diagonal line element is the sum of the line admittance and the earth admittance connected with the node, and the off-diagonal line element is the negative number of the line admittance connected with the node; /(I)And/>The vectors are composed of node voltage and injection current, respectively.
(2) And a gas path network equation of the hydrogen energy system.
Hydrogen energy systems and electrical power systems have many similarities as a network for energy transfer. Taking a hydrogen energy system pipeline network as an example, the gas path of the hydrogen energy pipeline network and the circuit of the power system are compared, so that the steady state can be obtainedEquivalent parameter branch impedance/>Controlled air pressure Source/>And admittance to earth/>、/>Is calculated according to the formula:
(27)。
(28)。
(29)。
(30)。
(31)。
In the method, in the process of the invention, And/>Respectively air resistance and controlled air pressure source of air path distribution parameters; /(I)、/>、/>、/>、/>、/>The cross-sectional area, the inner diameter, the length, the friction resistance coefficient, the flow velocity basic value and the dip angle of the pipeline are respectively; /(I)Is the hydrogen temperature. Introducing node-branch incidence matrix/>Node-outflow branch correlation matrix/>And node-inflow tributary association matrixDescribing the network topology characteristic of the pipe network, and further deducing a steady-state network equation of the hydrogen energy pipeline network gas circuit.
(32)。
(33)。
In the method, in the process of the invention,And/>The vector is composed of the node hydrogen pressure and flow; /(I)A generalized node admittance matrix of the hydrogen energy pipeline network; /(I)And/>A diagonal matrix of branch admittances and controlled air pressure sources, respectively.
The unified energy path model of the hydrogen energy network is similar to the pipeline network, and is not described herein again, and can be expressed as a node hydrogen path traffic flow vectorDistance vector from path/>Of (3), wherein/>A generalized node admittance matrix for a hydrogen energy transportation network:
(34)。
And writing a unified energy path model of the electric power network, the hydrogen energy pipeline and the traffic network, namely the electric hydrogen unified energy path model into a matrix mode.
(35)。
By considering the difference of the heterogeneous energy transmission characteristics and the similarity of network characteristics, an electro-hydrogen unified energy path model with consistent mathematical forms is constructed, and theoretical support is provided for subsequent unified energy flow solving.
Further, step S3 specifically includes the following steps.
(1) Flow equation and to-be-solved variable
Comprehensive electric-hydrogen unified energy path model, carrying out joint solution on flow equations of an electric power system and a hydrogen energy system, and waiting for the equation to be solvedAnd the variables to be solved/>The number is kept consistent, and the specific expression is:
(36)
(37)。
（38）。
In the method, in the process of the invention, 、/>、/>And/>The active power, the reactive power, the hydrogen flow of the hydrogen energy traffic network and the hydrogen flow of the hydrogen energy pipeline network of each node of the power network are vectors respectively, wherein the elements are specifically shown in a formula (38). /(I)、/>、/>、/>The variable quantity of the active power, the reactive power, the hydrogen flow of the hydrogen energy traffic network and the hydrogen flow of the hydrogen energy pipeline network of each node of the power network are respectively; /(I)And/>Respectively representing initial values of hydrogen flow of the hydrogen energy traffic network and hydrogen flow of the hydrogen energy pipeline network; /(I)、/>Representing initial values of node injected active and reactive power.
Solving the nonlinear equation set based on the bovine method, the iterative formula is as follows,The iteration times; /(I)To expand the unified jacobian matrix.
(39)。
(40)。
Wherein: Is the state variable of the (s+1) th iteration,/> State change quantity for the (s+1) th iteration; matrix diagonal/>And/>Jacobian matrices of the power network and the hydrogen energy network are respectively expressed as node power deviation equation vs. power grid state variable/>And/>Partial derivative of hydrogen mass flow versus hydrogen net state variable/>And/>Is a partial derivative of (2); since the mathematical model of the electro-hydrogen coupling conversion element is not considered, the state variable changes of the power network and the hydrogen energy network cannot influence each other, so that the off-diagonal block/>, in the unified Jacobian matrix is expanded=/> ; Specifically, the following is shown.
(41)。
(42)。
(43)。
(44)。
Wherein H, N, M, L are intermediate variables;、/> the partial derivative function in the matrix is shown, the jacobian variables of the hydrogen road transportation and the hydrogen pipeline transportation network are indicated, and the jacobian variables are indicated.
(2) And (5) an electric hydrogen power flow simultaneous solving process.
Based on the electro-hydrogen unified energy path model and the extended jacobian matrix, the state variable calculation flow of the electro-hydrogen coupled energy system is as follows:
1) Related technical parameters in the power system and the hydrogen energy system at the current moment are acquired, wherein the related technical parameters comprise loads of all nodes, active and reactive power of a generator, a network topology structure, hydrogen flow of an air source node, path prediction running time and the like, and known data are provided for subsequent bovine-derived method calculation.
2) Setting initial values of state variables to be solved of electric power system and hydrogen energy systemLet the iteration number be/>。/>
3) According to the state variables to be solvedCalculating unbalance amount/>, of electric power system and hydrogen energy system。
4) Unified jacobian matrix for computing expansion。
5) Calculating correction amountAnd update state variables。
6) Setting calculation accuracyIf/>Ending the iterative calculation to obtain the state variable/>。
Further, the steps S4 to S6 specifically include the following steps.
1) Based on step S3, node voltage amplitude is calculatedAnd phase angle/>And (3) calculating the injection power of the source node of the power system according to the formula (1), and calculating the hydrogen delivery quantity of the long-tube trailer hydrogen delivery traffic network and the pipeline network according to the formula (9) and the formula (14).
2 Calculating the node voltage amplitude based on the step S3And phase angle/>Active power of each branch according to formula (16)。
3) Active power based on each branchActive output/>, of a fuel assemblyThe carbon emission intensity of each fuel cell stack is calculated according to formulas (19) - (20).
4) A tidal current distribution matrix is constructed according to the formula (18), and a branch carbon flow rate and a branch carbon flow density are calculated according to the formulas (21) and (22) based on the branch power corresponding to the allocated generator power components.
5) The carbon utilization amount of the methane-methanolic reactor and the carbon emission amount reduced by using the carbon sequestration technique are calculated according to the formula (24) and the formula (25), respectively, and the node carbon potential is calculated based on the formula (23).
Firstly, constructing a power network tide model, a hydrogen energy steady-state transmission model and a carbon flow collection and tracing model, wherein the hydrogen energy steady-state transmission model is divided into a long-tube trailer hydrogen transmission traffic network model and a pipeline hydrogen transmission flow balance model based on path delay, and the carbon flow collection and tracing model considers the combined action of the carbon emission of a power generation side, the carbon emission reduction amount of a user side and the carbon utilization amount; secondly, an electro-hydrogen unified energy path model is built based on a unified energy flow theory, and theoretical support is provided for subsequent unified energy flow solving; and finally, considering that the carbon flow has no direct load, constructing a unified energy flow solving method of the electro-hydrogen energy system based on the cattle pulling method and a carbon flow solving flow based on power flow calculation. The unified modeling of the fusion electric-hydrogen-carbon multi-energy flow network is difficult due to the difference of storage and transmission time scales of the electric-hydrogen multi-energy flow working medium. Therefore, after the energy flows of each network are obtained by modeling the power system, the hydrogen energy network and the carbon flow network, basic scenes can be provided for the problems of optimizing operation and collaborative planning of the comprehensive energy system of the electric-hydrogen-carbon under the time scale of week and the time scale of year, the multi-scale electric power energy balance analysis method of the comprehensive energy system of the electric-hydrogen-carbon by taking the electric hydrogen as secondary energy, the energy interaction mechanism of the energy system of the electric-hydrogen-carbon fusion, multilateral transactions and the like.
Embodiment two: in order to perform a corresponding method of the above embodiments to achieve the corresponding functions and technical effects, a steady-state multi-energy flow computing system of an electro-hydro-carbon multi-energy system is provided below, which includes the following modules.
And the electric hydrogen-carbon multi-energy system model building module is used for building a power network tide model, a hydrogen energy steady-state transmission model and a carbon flow collection traceability model.
And the electric hydrogen unified energy path model building module is used for building an electric hydrogen unified energy path model based on a unified energy flow theory.
And the solving module is used for solving the electro-hydrogen unified energy path model based on a cow pulling method to obtain a state variable of the power network tide model.
A power network energy flow calculation module for calculating a power network energy flow using the power network power flow model based on state variables of the power network power flow model; the power network energy flow includes injection power of a power system source node.
The hydrogen energy network energy flow calculation module is used for calculating the hydrogen energy network energy flow by adopting the hydrogen energy steady-state transmission model based on the path flow, the density and the heat value influence factor of the long tube trailer; the hydrogen energy network energy flow comprises a hydrogen energy network and pipeline network node injection flow.
The carbon flow network energy flow calculation module is used for calculating the carbon flow network energy flow by adopting the carbon flow collection traceability model based on the tide distribution matrix, the carbon emission intensity and the active power of the power system source branch; the carbon flow network energy flow comprises the carbon utilization amount of the methane-methanolic reactor, the carbon emission amount reduced by adopting a carbon sequestration technology and the node carbon potential index.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In summary, the present description should not be construed as limiting the invention.
Claims (5)
1. A steady-state multi-energy flow calculation method for an electro-hydro-carbon multi-energy system, comprising:
Constructing a power network tide model, a hydrogen energy steady-state transmission model and a carbon flow collection traceability model;
Establishing an electro-hydrogen unified energy path model based on a unified energy flow theory;
Solving the electro-hydrogen unified energy path model based on a cow pulling method to obtain a state variable of the power network tide model;
calculating a power network energy flow using the power network power flow model based on state variables of the power network power flow model; the power network energy flow includes injection power of a power system source node;
Calculating the energy flow of a hydrogen energy network by adopting the hydrogen energy steady-state transmission model based on the path flow of the long tube trailer and the density and heat value influence factors; the hydrogen energy network energy flow comprises the hydrogen delivery quantity of a long pipe trailer hydrogen delivery traffic network and a pipeline network;
calculating the energy flow of a carbon flow network by adopting the carbon flow collection traceability model based on the tide distribution matrix, the carbon emission intensity and the active power of the power system source branch; the carbon flow network energy flow comprises the carbon utilization amount of a methane-methanolic reactor, the carbon emission amount reduced by adopting a carbon sequestration technology and the node carbon potential;
The hydrogen energy steady-state transmission model comprises a long-tube trailer hydrogen transmission traffic network model and a pipeline hydrogen transmission flow balance model;
The expression of the long tube trailer hydrogen transportation network model is as follows:
；
；
wherein, Representing nodes/>At time/>The amount of hydrogen transported by the tube trailer; /(I)The hydrogen amount of the fixed transportation of the long tube trailer m is represented; /(I)The flow of the long tube trailer in the path w at the moment t is shown; /(I)Representing nodes/>And node/>A set of path connections between; /(I)Representing nodes/>At time/>The amount of hydrogen transported by the tube trailer; Representing a long tube trailer/> At node/>And node/>Predicted travel time for different paths between; /(I)Representing road segment/>At time/>Is used for predicting traffic flow;
the expression of the pipeline hydrogen delivery flow balance model is as follows:
；
；
；
；
wherein, Representing nodes/>Hydrogen mass flow rate of (2); /(I)Representing nodes/>The mass flow of the injected hydrogen; Represents a hydrogen pipeline/> The hydrogen mass flow rate; /(I)Is a hydrogen conveying pipeline set; /(I)Representing density and heating value influencing factors; /(I)Representing the pipe coefficients; /(I)、/>The pressure of the node k and the pressure of the node l are respectively; /(I)The pressure square difference of the node k and the pressure square difference of the node l are respectively; /(I)And/>All represent weight coefficients; /(I)And/>Respectively represent the densities of hydrogen and natural gas; /(I)And/>Respectively represent the heating values of hydrogen and natural gas; /(I)、/>、/>、/>And/>The standard condition pressure, the standard condition temperature, the gas compression coefficient and the friction resistance coefficient are respectively; /(I)And/>Hydrogen delivery pipeline/>, respectivelyIs a diameter and length of (a); /(I)Represents hydrogen density;
the expression of the carbon flow collection traceability model is as follows:
；
；
；
；
；
wherein, Represents the carbon utilization of the methane-methanolic reactor; /(I)Representing reduced carbon emissions using carbon sequestration techniques; /(I)Representing the node carbon potential; /(I)Is the reaction proportionality coefficient of hydrogen and carbon dioxide; /(I)Is the molar mass of carbon dioxide; /(I)Is the molar mass of hydrogen; /(I)For node/>The total hydrogen amount of the methane-methanolic reactor is supplied by a hydrogen energy network; /(I)For node/>The carbon capture equipment connected with the carbon capture equipment captures the total mass of carbon dioxide; /(I)Representing a set of nodes connecting the carbon capture device; /(I)A set of nodes representing a power system; /(I)Representing the bypass carbon flow rate; /(I)Representing nodes/>Flow direction node/>Active power of (2); /(I)Represents the carbon emission intensity; /(I)Representing a unit column vector; t represents a transpose; /(I)Representing a tidal current distribution matrixFirst/>Line/>Elements of a column; /(I)Representing nodes/>The load on the load flows out of the power; /(I)A vector representing the active power composition of each node generator; /(I)A vector representing the composition of the unit carbon emission intensity; /(I)Representing branch carbon flow density;
The expression of the electro-hydrogen unified energy path model is as follows:
；
wherein, Representing a node admittance matrix; /(I)And/>Vectors composed of node voltage and injection current respectively; /(I)A generalized node admittance matrix representing a hydrogen energy network; /(I)A vector representing the node hydrogen pressure composition; /(I)A vector representing the node hydrogen flow constitution; /(I)A generalized node admittance matrix of the hydrogen energy path traffic network; /(I)A generalized node admittance matrix representing a hydrogen energy path traffic network; /(I)Representing the path distance vector.
2. The method for steady-state multi-energy flow calculation of an electro-hydro-carbon multi-energy system according to claim 1, wherein the expression of the power network flow model is as follows:
；
；
；
；
；
wherein, And/>Respectively, node/>Active power and reactive power are injected into the reactor; /(I)For node/>Is set to the voltage amplitude of (1); /(I)For node/>Is set to the voltage amplitude of (1); n is the number of nodes; /(I)、/>、/>The conductance, susceptance and phase angle of branch ij respectively; /(I)Active power of the power generation equipment connected to node i; /(I)Reactive power of the power generation equipment connected to node i; /(I)And/>The upper limit and the lower limit of the active power of the power generation equipment connected with the node i are respectively set; /(I)And/>The upper limit and the lower limit of reactive power of the power generation equipment connected with the node i are respectively set; /(I)And/>The upper limit and the lower limit of the voltage amplitude of the node i are respectively; /(I)The bus running current of the node i; /(I)The line current rating for node i.
3. The method for calculating the steady-state multi-energy flow of the electro-hydro-carbon multi-energy system according to claim 1, wherein the expression of the power flow distribution matrix is as follows:
；
wherein, Representing a tidal current distribution matrix/>First/>Line/>Elements of a column; /(I)Representing nodes/>Flow direction node/>Active power of (2); /(I)Representing nodes/>The load on the load flows out of the power; /(I)Representing a set of nodes of the power system.
4. The method for calculating the steady-state multi-energy flow of the electro-hydro-carbon multi-energy system according to claim 1, wherein the calculation formula of the carbon emission intensity is:
；
；
wherein, Represents the carbon emission intensity; /(I)And/>Respectively representing the carbon content and the carbon oxidation rate of the unit fuel; /(I)Representing carbon capture efficiency; /(I)And/>Molar mass of carbon dioxide and carbon, respectively; /(I)Representing the units/>Is a unit electric energy consumption fuel amount; /(I)、/>、/>All represent characteristic parameters; /(I)Is a correction coefficient; /(I)Is the active output of the fuel unit.
5. A steady state multi-energy flow computing system for an electro-hydro-carbon multi-energy system, comprising:
the electric hydrogen-carbon multi-energy system model building module is used for building a power network tide model, a hydrogen energy steady-state transmission model and a carbon flow collection traceability model;
the electric hydrogen unified energy path model building module is used for building an electric hydrogen unified energy path model based on a unified energy flow theory;
The solving module is used for solving the electro-hydrogen unified energy path model based on a cow pulling method to obtain a state variable of the power network power flow model;
A power network energy flow calculation module for calculating a power network energy flow using the power network power flow model based on state variables of the power network power flow model; the power network energy flow includes injection power of a power system source node;
the hydrogen energy network energy flow calculation module is used for calculating the hydrogen energy network energy flow by adopting the hydrogen energy steady-state transmission model based on the path flow, the density and the heat value influence factor of the long tube trailer; the hydrogen energy network energy flow comprises the hydrogen delivery quantity of a long pipe trailer hydrogen delivery traffic network and a pipeline network;
the carbon flow network energy flow calculation module is used for calculating the carbon flow network energy flow by adopting the carbon flow collection traceability model based on the tide distribution matrix, the carbon emission intensity and the active power of the power system source branch; the carbon flow network energy flow comprises the carbon utilization amount of a methane-methanolic reactor, the carbon emission reduced by adopting a carbon sequestration technology and node carbon potential indexes;
The hydrogen energy steady-state transmission model comprises a long-tube trailer hydrogen transmission traffic network model and a pipeline hydrogen transmission flow balance model;
The expression of the long tube trailer hydrogen transportation network model is as follows:
；
；
wherein, Representing nodes/>At time/>The amount of hydrogen transported by the tube trailer; /(I)The hydrogen amount of the fixed transportation of the long tube trailer m is represented; /(I)The flow of the long tube trailer in the path w at the moment t is shown; /(I)Representing nodes/>And node/>A set of path connections between; /(I)Representing nodes/>At time/>The amount of hydrogen transported by the tube trailer; Representing a long tube trailer/> At node/>And node/>Predicted travel time for different paths between; /(I)Representing road segment/>At time/>Is used for predicting traffic flow;
the expression of the pipeline hydrogen delivery flow balance model is as follows:
；
；
；
；
wherein, Representing nodes/>Hydrogen mass flow rate of (2); /(I)Representing nodes/>The mass flow of the injected hydrogen; Represents a hydrogen pipeline/> The hydrogen mass flow rate; /(I)Is a hydrogen conveying pipeline set; /(I)Representing density and heating value influencing factors; /(I)Representing the pipe coefficients; /(I)、/>The pressure of the node k and the pressure of the node l are respectively; /(I)The pressure square difference of the node k and the pressure square difference of the node l are respectively; /(I)And/>All represent weight coefficients; /(I)And/>Respectively represent the densities of hydrogen and natural gas; /(I)And/>Respectively represent the heating values of hydrogen and natural gas; /(I)、/>、/>、/>And/>The standard condition pressure, the standard condition temperature, the gas compression coefficient and the friction resistance coefficient are respectively; /(I)And/>Hydrogen delivery pipeline/>, respectivelyIs a diameter and length of (a); /(I)Represents hydrogen density;
the expression of the carbon flow collection traceability model is as follows:
；
；
；
；
；
wherein, Represents the carbon utilization of the methane-methanolic reactor; /(I)Representing reduced carbon emissions using carbon sequestration techniques; /(I)Representing the node carbon potential; /(I)Is the reaction proportionality coefficient of hydrogen and carbon dioxide; /(I)Is the molar mass of carbon dioxide; /(I)Is the molar mass of hydrogen; /(I)For node/>The total hydrogen amount of the methane-methanolic reactor is supplied by a hydrogen energy network; /(I)For node/>The carbon capture equipment connected with the carbon capture equipment captures the total mass of carbon dioxide; /(I)Representing a set of nodes connecting the carbon capture device; /(I)A set of nodes representing a power system; /(I)Representing the bypass carbon flow rate; /(I)Representing nodes/>Flow direction node/>Active power of (2); /(I)Represents the carbon emission intensity; /(I)Representing a unit column vector; t represents a transpose; /(I)Representing a tidal current distribution matrixFirst/>Line/>Elements of a column; /(I)Representing nodes/>The load on the load flows out of the power; /(I)A vector representing the active power composition of each node generator; /(I)A vector representing the composition of the unit carbon emission intensity; /(I)Representing branch carbon flow density;
The expression of the electro-hydrogen unified energy path model is as follows:
；
wherein, Representing a node admittance matrix; /(I)And/>Vectors composed of node voltage and injection current respectively; /(I)A generalized node admittance matrix representing a hydrogen energy network; /(I)A vector representing the node hydrogen pressure composition; /(I)A vector representing the node hydrogen flow constitution; /(I)A generalized node admittance matrix of the hydrogen energy path traffic network; /(I)A generalized node admittance matrix representing a hydrogen energy path traffic network; /(I)Representing the path distance vector.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410160386.6A CN117713251B (en) | 2024-02-05 | 2024-02-05 | Steady-state multi-energy flow calculation method and system of electro-hydro-carbon multi-energy system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410160386.6A CN117713251B (en) | 2024-02-05 | 2024-02-05 | Steady-state multi-energy flow calculation method and system of electro-hydro-carbon multi-energy system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117713251A CN117713251A (en) | 2024-03-15 |
| CN117713251B true CN117713251B (en) | 2024-04-26 |
Family
ID=90162801
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410160386.6A Active CN117713251B (en) | 2024-02-05 | 2024-02-05 | Steady-state multi-energy flow calculation method and system of electro-hydro-carbon multi-energy system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117713251B (en) |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110188972A (en) * | 2019-03-12 | 2019-08-30 | 贵州电网有限责任公司 | A kind of non-special customer cut-in method of 10kV power distribution network |
| CN113315242A (en) * | 2021-05-31 | 2021-08-27 | 天津大学 | Virtual wind abandoning-hydrogen production combination for promoting wind abandoning consumption based on hydrogen energy economy |
| CN115102159A (en) * | 2022-06-17 | 2022-09-23 | 国网浙江省电力有限公司电力科学研究院 | Shared energy storage optimized operation method considering carbon emission flow |
| CN115481883A (en) * | 2022-09-13 | 2022-12-16 | 广东电网有限责任公司广州供电局 | Electrical coupling system safety analysis method based on improved iterative jacobian matrix |
| CN115563860A (en) * | 2022-09-26 | 2023-01-03 | 武汉大学 | Modeling and time sequence optimization method for electric-hydrogen-carbon coupling characteristics of steel park |
| CN116388147A (en) * | 2022-12-16 | 2023-07-04 | 国网浙江省电力有限公司台州供电公司 | Carbon emission monitoring method for electric-gas coupled comprehensive energy system |
| CN116562464A (en) * | 2023-07-03 | 2023-08-08 | 南京菁翎信息科技有限公司 | Deep reinforcement learning-based low-carbon optimal scheduling method for power system |
| CN116979558A (en) * | 2023-06-27 | 2023-10-31 | 华中科技大学 | Time-frequency optimization scheduling method for electric hydrogen comprehensive energy system |
| CN117096390A (en) * | 2023-09-19 | 2023-11-21 | 福州大学 | Modeling method of fuel cell air supply system based on unified energy path |
| CN117455104A (en) * | 2023-10-24 | 2024-01-26 | 国网上海市电力公司 | Carbon flow analysis and calculation method based on all elements of power grid |
-
2024
- 2024-02-05 CN CN202410160386.6A patent/CN117713251B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110188972A (en) * | 2019-03-12 | 2019-08-30 | 贵州电网有限责任公司 | A kind of non-special customer cut-in method of 10kV power distribution network |
| CN113315242A (en) * | 2021-05-31 | 2021-08-27 | 天津大学 | Virtual wind abandoning-hydrogen production combination for promoting wind abandoning consumption based on hydrogen energy economy |
| CN115102159A (en) * | 2022-06-17 | 2022-09-23 | 国网浙江省电力有限公司电力科学研究院 | Shared energy storage optimized operation method considering carbon emission flow |
| CN115481883A (en) * | 2022-09-13 | 2022-12-16 | 广东电网有限责任公司广州供电局 | Electrical coupling system safety analysis method based on improved iterative jacobian matrix |
| CN115563860A (en) * | 2022-09-26 | 2023-01-03 | 武汉大学 | Modeling and time sequence optimization method for electric-hydrogen-carbon coupling characteristics of steel park |
| CN116388147A (en) * | 2022-12-16 | 2023-07-04 | 国网浙江省电力有限公司台州供电公司 | Carbon emission monitoring method for electric-gas coupled comprehensive energy system |
| CN116979558A (en) * | 2023-06-27 | 2023-10-31 | 华中科技大学 | Time-frequency optimization scheduling method for electric hydrogen comprehensive energy system |
| CN116562464A (en) * | 2023-07-03 | 2023-08-08 | 南京菁翎信息科技有限公司 | Deep reinforcement learning-based low-carbon optimal scheduling method for power system |
| CN117096390A (en) * | 2023-09-19 | 2023-11-21 | 福州大学 | Modeling method of fuel cell air supply system based on unified energy path |
| CN117455104A (en) * | 2023-10-24 | 2024-01-26 | 国网上海市电力公司 | Carbon flow analysis and calculation method based on all elements of power grid |
Non-Patent Citations (4)
| Title |
|---|
| 《低碳经济下钢铁企业碳成本分析与定量研究》;王琳等;《求索》;20130630(第06期);30-32 * |
| 《混合电力市场下碳排放流的分配》;陈达等;《电网技术》;20160630;40(6);83-88 * |
| 《综合能源***分析的统一能路理论(一):气路》;陈彬彬等;《中国电机工程学报》;20200120(第02期);77-85 * |
| 《考虑碳捕集电厂的电力***多目标最优潮流及其碳流分析》;马瑞等;《电力科学与技术学报》;20150328(第01期);16-23 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117713251A (en) | 2024-03-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108494015B (en) | Method for designing source-load-storage coordinated interaction comprehensive energy system | |
| Xie et al. | Autonomous optimized economic dispatch of active distribution system with multi-microgrids | |
| CN109063992B (en) | Power distribution network expansion planning method considering optimized operation of regional comprehensive energy system | |
| CN109871989A (en) | A kind of power distribution network hierarchical reconfiguration planning method containing distributed generation resource | |
| CN110266010B (en) | Grid structure of direct-current power distribution network and distributed photovoltaic multi-target collaborative optimization method | |
| CN111428351B (en) | Electric-thermal comprehensive energy system tide calculation method based on forward-push back substitution method | |
| CN112035984B (en) | Collaborative planning method for comprehensive energy system of electricity-gas-storage area | |
| CN111416356A (en) | Transmission and distribution network linkage optimization method based on alternating direction multiplier method and optimal power flow | |
| Karaoğlan et al. | Investigation of the effects of battery types and power management algorithms on drive cycle simulation for a range-extended electric vehicle powertrain | |
| CN114444850A (en) | Park energy storage planning method, device, equipment and medium based on digital twin | |
| CN117713251B (en) | Steady-state multi-energy flow calculation method and system of electro-hydro-carbon multi-energy system | |
| Iranpour Mobarakeh et al. | Robust management and optimization strategy of energy hub based on uncertainties probability modelling in the presence of demand response programs | |
| CN112668186B (en) | ELM-based location and volume-fixing collaborative optimization method for integrated energy storage system | |
| Ma et al. | Intelligent charging control method of shared vehicle based on MPPT algorithm in the environment of internet of things | |
| Kanouni et al. | Advanced efficient energy management strategy based on state machine control for multi-sources PV-PEMFC-batteries system | |
| Jung et al. | A study on peak power reduction using regenerative energy in railway systems through DC subsystem interconnection | |
| CN110323779B (en) | Method and system for dynamically aggregating power of distributed power generation and energy storage device | |
| Kumar et al. | Optimal allocation of Hybrid Solar-PV with STATCOM based on Multi-objective Functions using combined OPF-PSO Method | |
| CN117013552A (en) | Cooperative operation strategy of electric power traffic coupling network | |
| Velaz-Acera et al. | Economic and emission reduction benefits of the implementation of eVTOL aircraft with bi-directional flow as storage systems in islands and case study for Canary Islands | |
| Mei et al. | Multi-objective optimization of integrated energy system based on improved NSGA-II algorithm | |
| CN111555282B (en) | Elastic power distribution network post-disaster emergency response operation control system and method | |
| Consul et al. | Intelligent switching mechanism for power distribution in photovoltaic-fed battery electric vehicles | |
| Feng et al. | Design and dispatching of all-clean energy producing-consuming system with six-energy coupling | |
| CN117410960B (en) | Cooperative scheduling method and terminal of electric traffic coupling system |
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 |