Low-carbon economic dispatching method and system for electric power-natural gas energy system, medium and processor

Abstract

The invention provides a power-natural gas energy system low-carbon economic dispatching method, which comprises the following steps of: modeling a voltage, current and power relationship in a power distribution network by adopting a branch power flow model to obtain a power distribution network model, and performing conversion by applying second-order cone relaxation; the method comprises the following steps: modeling a relationship between pressure and gas flow in a natural gas pipeline network by adopting a Weymoth equation to obtain a gas distribution network model, and performing conversion by applying second-order cone relaxation; performing mathematical modeling on devices in the multi-type energy base station; constructing a comprehensive demand response model based on multiple types of energy base stations; and calculating and scheduling the low-carbon economic operation of the system by integrating the mathematical models of the power distribution network, the gas distribution network and the multi-type energy base station and the comprehensive demand response model. According to the method, the power distribution network and gas distribution network models are established, the comprehensive demand response scheduling model is provided, and meanwhile, the multi-type energy base station detail model is provided, so that different energy networks can directly coordinate low-carbon economic operation.

Description

Technical Field

[0001] The present invention relates to the field of energy system control technology, and in particular to a low-carbon economic dispatching method, system, medium and processor for an electricity-natural gas energy system. Background Art

[0002] The application of renewable energy to cleanly replace traditional fossil energy is the key path to achieving the dual carbon goals of the energy system. The urban pattern and planning of our country are basically based on industrial parks as "units". There are a large number of industrial parks across the country, each of which has highly concentrated elements, booming innovation activities, and low coordination difficulty for participants. It is currently the most suitable scenario for low-carbon research and practice of energy systems. At present, the energy system of industrial parks is generally centered on the power system, which is composed of power systems, thermal systems, natural gas systems distributed in a region, and multi-energy conversion equipment as coupling links, and comprehensive scheduling and coordinated optimization of multiple energy sources. However, new energy represented by wind power and photovoltaics has typical random volatility and intermittency, and it is necessary to fully call on the flexible resources on the load side to ensure safe and economic energy supply.

[0003] In view of this, a low-carbon economic dispatch method, system, medium and processor for an electricity-natural gas energy system are needed. Summary of the invention

[0004] In view of the typical random volatility and intermittency of new energy in the prior art, the present invention provides a low-carbon economic dispatch method, system, medium and processor for the electric-natural gas energy system, which can consider comprehensive demand response and carbon capture technology, and fully call on the flexibility resources on the load side to ensure safe and economic energy supply. The specific technical solution is as follows:

[0005] A low-carbon economic dispatching method for an electricity-natural gas energy system, comprising:

[0006] The branch power flow model is used to model the relationship between voltage, current and power in the distribution network, and the distribution network model is obtained and transformed by applying second-order cone relaxation;

[0007] The Weymouth equation is used to model the relationship between pressure and gas flow in the natural gas pipeline network, and the gas distribution network model is obtained and transformed by applying second-order cone relaxation.

[0008] Mathematical modeling of gas turbines, power-to-gas equipment and carbon capture devices in various energy base stations;

[0009] Build a comprehensive demand response model based on multiple types of energy base stations;

[0010] The mathematical models of the above-mentioned distribution network, gas distribution network, and various types of energy base stations and the comprehensive demand response model are combined to calculate and dispatch the low-carbon economic operation of the system.

[0011] Furthermore, the branch power flow model is used to model the relationship between voltage, current and power in the distribution network, and the distribution network model is obtained and converted by applying second-order cone relaxation, which includes the following steps:

[0012] The distribution network is modeled as follows:

[0013]

[0014] (V j,t ) 2 =(V i,t ) 2 -2(P jk,t r ij +Q ij,t x ij )+(z ij ) 2 (I ij,t ) 2 ;

[0015]

[0016] Apply second-order cone relaxation for transformation, introduce relaxation variables, and let:

[0017]

[0018] The distribution network model formula after conversion is as follows:

[0019]

[0020] The equivalent transformation of the second-order cone relaxation is as follows:

[0021]

[0022] In the above formula, L ij,t , U i,t , U j,t They are The corresponding slack variables; I, K represent the upstream bus set and downstream bus set of bus j respectively; i is the upstream bus of bus j, k is the downstream bus of bus j; P j,t ,Q j,t They are respectively represented as the active power and reactive power injected into bus j; P ij,t ,Q ij,t They are respectively represented as the active power and reactive power of branch ij flowing from bus i to bus j; P jk,t ,Q jk,tThey are respectively represented as the active power and reactive power of branch jk flowing from bus j to bus k; ij ,r ij ,z ij Respectively represent the reactance, resistance and impedance of branch ij; V i,t ,V j,t They are represented as the voltage of bus i and bus j respectively; I ij,t is the branch ij current.

[0023] Furthermore, the Weymouth equation is used to model the relationship between pressure and gas flow in the natural gas pipeline network, and the gas distribution network model is obtained and converted by applying second-order cone relaxation, which includes the following steps:

[0024] The gas distribution network is modeled as follows:

[0025]

[0026] Apply second-order cone relaxation to transform and introduce binary variables and make:

[0027]

[0028] Introducing the variable π m,t and π n,t ,make:

[0029]

[0030] The formula after transforming the gas distribution network model is as follows:

[0031]

[0032] Introducing variable M mn,t,k ,make:

[0033]

[0034] The equivalent transformation of the second-order cone relaxation is obtained as follows:

[0035]

[0036] In the above formula, f mn,k,t is the natural gas flow rate of pipeline mn; sgn(m,n) k,t Indicates the flow direction of natural gas in the pipeline at the nodes on both sides; c k is the pipeline coefficient; p m,t 、p n,t Respectively represent the pressure at the m and n nodes of the pipeline; Δx k ,D kare the length and inner diameter of the pipe mn respectively; ρ0 represents the gas density; F k , R are the friction coefficient and gas constant, T and Z are the gas temperature and compressibility coefficient respectively.

[0037] Furthermore, the mathematical modeling of the gas turbine, power-to-gas equipment and carbon capture device in the multi-type energy base station is as follows:

[0038] P gt,k,t =η gt,k H g f gt,k,t ;

[0039] O gt,k,t =λ gt,k f gt,k,t；

[0040] f p2g,k,t =(η p2g,k P p2g,k,t ) / H g ;

[0041] O p2g,k,t =λ p2g,k,t f p2g,k,t ;

[0042]

[0043] In the above formula, P gt,k,t ,P p2g,k,t ,P ccu,k,t Represent the electrical power of the gas turbine, the power-to-gas device and the carbon capture device respectively; η gt,k ,η p2g,k ,η ccu,k Represent the operating efficiency of gas turbine, power-to-gas equipment and carbon capture device respectively; O gt,k,t ,O p2g,k,t , are the amounts of carbon dioxide output from the gas turbine, absorbed by the power-to-gas device, injected into the carbon capture device, and captured by the carbon capture device; H g Indicates the calorific value of natural gas, f gt,k,t ,f p2g,k,t Respectively represent the gas flow of gas turbine and power-to-gas equipment; gt,k ,λ p2g,k ,λ ccu,k They represent the carbon conversion efficiency of gas turbines, power-to-gas equipment and carbon capture devices respectively.

[0044] Furthermore, the formula for constructing a comprehensive demand response model based on multiple types of energy base stations is as follows:

[0045]

[0046] f MEH,k,t +f p2g,k,t =f load,k,t +f cut,k,t +f tran,k,t +f gt,k,t；

[0047] P MEH,k,t +P gt,k,t =P load,k,t +P cut,k,t +P tran,k,t +P p2g,k,t；

[0048] In the above formula, f MEH，k,t Indicates the amount of gas flowing into the multi-type energy base station; f p2g，k,t Indicates the gas flow rate of the power-to-gas device; f load,k,t ,f cut,k,t ,f tran,k,t Respectively represent the air flow of rigid load, reducible load and transferable load; f gt，k,t Indicates the gas flow of the gas turbine; P MEH，k,t Represents the active power flowing into the multi-type energy base station; P gt，k,t Represents the electrical power of the gas turbine; P load,k,t ,P cut,k,t ,P tran,k,t Represent the electric power of rigid load, curtailable load and transferable load respectively; P p2g，k,t Indicates the electrical power of the power-to-gas equipment; They represent the maximum air flow and electric power that can be reduced. They represent the maximum reducible gas flow and electrical power of the transferable load respectively.

[0049] Furthermore, the calculation and scheduling of the low-carbon economic operation of the system includes the following steps:

[0050]

[0051] In the above formula, C1 and C2 represent the prices of electricity and natural gas purchased from the main grid, respectively; C3 and C4 represent the penalty coefficients of electricity load and gas load in the load that can be reduced, respectively; P Grid,i,t ,f Grid,k,t Respectively represent the electric power and gas flow purchased from the main grid, P cut,i,t , f cut,i,t Indicates the electrical power and gas flow that can be reduced.

[0052] Furthermore, the constraints for calculating the low-carbon economic operation of the system are as follows:

[0053] P j,t =P Grid,i,t +P wind,i,t +Ppv,i,t -P MEH,i,t ;

[0054] Q j,t =Q Grid,i,t +Q win,i,t +Q pv,i,t -Q MEH,i,t ;

[0055]

[0056] In the above formula, P j,t is the active power of bus j; P Grid,i,t Indicates the electric power purchased from the main grid; P wind,i,t ,P pv,i,t Represent the active power output of wind turbine and photovoltaic respectively; P MEH，i,t Represents the active power flowing into the multi-type energy base station; Q j,t is the reactive power of bus j; Q Grid,i,t Indicates the reactive power flowing in from the main grid; Q win,i,t ,Q pv,i,t Respectively represent the reactive power output of wind turbine and photovoltaic; Q MEH，i,t represents the reactive power flowing into the multi-type energy base station; f n-,k,t ,f n+,k,t They represent the gas flow in the downstream pipeline and the upstream pipeline connecting the node n respectively; f MEH，k,t Indicates the amount of gas flowing into the multi-type energy base station; f Grid,k,t Indicates the amount of gas purchased from the main network.

[0057] A low-carbon economic dispatching system for an electric power-natural gas energy system, applied to the low-carbon economic dispatching method for an electric power-natural gas energy system as described above, comprises:

[0058] A distribution network modeling module, which is used to model the relationship between voltage, current and power in the distribution network using a branch power flow model, obtain a distribution network model and transform it using second-order cone relaxation;

[0059] Gas distribution network modeling module, which is used to model the relationship between pressure and gas flow in the natural gas pipeline network using the Weymouth equation, obtain the gas distribution network model and transform it using second-order cone relaxation;

[0060] Base station modeling module, which is used to mathematically model gas turbines, power-to-gas equipment and carbon capture devices in various types of energy base stations;

[0061] Demand response modeling module, which is used to build a comprehensive demand response model based on multiple types of energy base stations;

[0062] The calculation and scheduling module is used to integrate the mathematical models of the above-mentioned distribution network, gas distribution network, and various types of energy base stations and the comprehensive demand response model to calculate and schedule the low-carbon economic operation of the system.

[0063] A computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the low-carbon economic dispatching method for the electricity-natural gas energy system as described above.

[0064] A processor is used to run a program, wherein the program, when running, executes the low-carbon economic dispatch method of the electricity-natural gas energy system as described above.

[0065] Compared with the prior art, the present invention has the following beneficial effects:

[0066] 1. Be able to consider comprehensive demand response and carbon capture technologies, and make full use of flexible resources on the load side to ensure safe and economical energy supply.

[0067] 2. Through gas turbines, power-to-gas devices and carbon capture devices, two-way energy conversion and carbon collection and utilization between the power grid and the natural gas network can be realized. At the same time, on the load side, the above-mentioned energy coupling devices can be used to achieve alternative demand response on the load side and realize complementarity between different energy networks.

[0068] 3. In terms of energy type, load types include electric load and natural gas load. In terms of response type, load types include curtailable load, transferable load and replaceable load. Comprehensive demand response can coordinate multiple types of responsive loads of different energy networks. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for the specific embodiments or the description of the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn according to the actual scale.

[0070] Figure 1 A schematic diagram of a flow chart of a low-carbon economic dispatching method for an electricity-natural gas energy system of the present invention;

[0071] Figure 2 This is a schematic diagram of the industrial park energy system structure of the present invention. DETAILED DESCRIPTION

[0072] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0073] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0074] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0075] It should be further understood that the term "and / or" used in the present description and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0076] Embodiment 1

[0077] like Figure 1 The figure shows a flow chart of a low-carbon economic dispatch method for an electricity-natural gas energy system, which is applied to Figure 2 The schematic diagram of the structure of the industrial park energy system (the multi-type energy base station in the figure is also referred to as a multi-energy collection station) shown in the figure, the scheduling method includes the following specific steps:

[0078] S1: For the distribution network, the branch flow model is used to model the relationship between voltage, current and power in the distribution network, including node active injection, reactive injection, line voltage drop and current balance, to obtain the distribution network model and apply second-order cone relaxation for transformation.

[0079] In a specific implementation, the branch flow model is used to model the relationship between voltage, current and power in the distribution network, and the distribution network model is obtained and transformed by applying second-order cone relaxation, which includes the following steps:

[0080] The distribution network is modeled, including node active injection, reactive injection, line voltage drop and current balance, and the mathematical model is as follows:

[0081]

[0082] (Vj,t ) 2 =(V i,t ) 2 -2(P jk,t r ij +Q ij,t x ij )+(z ij ) 2 (I ij,t ) 2 (3)

[0083]

[0084] In order to solve the above nonlinear model, the second-order cone relaxation is applied to transform the model and introduce relaxation variables, so that:

[0085]

[0086] In the above formula, L ij,t , U i,t , U j,t They are The corresponding slack variables;

[0087] At this time, formulas (1)-(4) can be converted to (5)-(8), and the distribution network model formula after conversion is as follows:

[0088]

[0089]

[0090] The equivalent transformation of the second-order cone relaxation is as follows:

[0091]

[0092] In the above formula, I and K represent the upstream bus set and downstream bus set of bus j respectively; i is the upstream bus of bus j, and k is the downstream bus of bus j; P j,t ,Q j,t They are respectively represented as the active power and reactive power injected into bus j; P ij,t ,Q ij,t They are respectively represented as the active power and reactive power of branch ij flowing from bus i to bus j; P jk,t ,Q jk,t They are respectively represented as the active power and reactive power of branch jk flowing from bus j to bus k; ij ,r ij ,z ij Respectively represent the reactance, resistance and impedance of branch ij; V i,t ,V j,t They are represented by the voltage of bus i and bus j respectively; I ij,tis the branch ij current.

[0093] S2: For the medium-pressure natural gas pipeline network, the Weymouth equation is used to model the relationship between pressure and gas flow in the natural gas pipeline network. The Weymouth equation is used to describe the numerical association between pressure and gas flow in the pipeline, and the gas distribution network model is obtained and transformed by applying second-order cone relaxation.

[0094] In a specific implementation, the Weymouth equation is used to model the relationship between pressure and gas flow in the natural gas pipeline network, a gas distribution network model is obtained, and a second-order cone relaxation is applied for transformation, including the following steps:

[0095] The gas distribution network is modeled and the Weymouth equation is used to describe the numerical relationship between the pressure and gas flow in the pipeline. The calculation process and formula are as follows:

[0096]

[0097] Perform second-order cone relaxation on the natural gas pipeline model, apply second-order cone relaxation to transform it, and introduce binary variables and make:

[0098]

[0099] Introducing the variable π m,t and π n,t represents the square of the node pressure, let:

[0100]

[0101] The formula after transforming the gas distribution network model is as follows:

[0102]

[0103] Introducing variable M mn,t,k ,make:

[0104]

[0105] The equivalent transformation of the second-order cone relaxation is obtained as follows:

[0106]

[0107] In the above formula, formula (9) describes the numerical relationship between the gas flow rate in the pipeline and the node pressure on both sides of the pipeline, f mn,k,t is the natural gas flow rate of pipeline mn; sgn(m,n) k,t Indicates the flow direction of natural gas in the pipeline at the nodes on both sides; c k is the pipeline coefficient; p m,t 、pn,t Respectively represent the pressure at the m and n nodes of the pipeline; Δx k ,D k are the length and inner diameter of the pipe mn respectively; ρ0 represents the gas density; F k , R are the friction coefficient and gas constant, T and Z are the gas temperature and compressibility coefficient respectively.

[0108] By introducing the second-order cone relaxation technology into the distribution network and gas distribution network models, the nonlinear problem is converted into a mixed integer second-order cone programming problem that can be reliably solved, which can solve the problems of slow system scheduling solution speed and unreliable solution of nonlinear optimal problems for integrated multi-type energy networks. After the detailed modeling and second-order cone relaxation of the present invention, the optimization model can be directly calculated by commercial solvers such as CPLEX for the optimal scheduling strategy.

[0109] S3: Multi-type energy base stations obtain energy supply from the distribution network and the gas distribution network, and meet various types of load demands through gas turbines, power-to-gas equipment and carbon capture devices. Mathematical modeling is performed on the three typical devices of gas turbines, power-to-gas equipment and carbon capture devices in multi-type energy base stations.

[0110] In the specific implementation, the three typical equipment mathematical models of the gas turbine, power-to-gas equipment and carbon capture device in the multi-type energy base station are as follows:

[0111] P gt,k,t =η gt,k H g f gt,k,t (17)

[0112] O gt,k,t =λ gt,k f gt,k,t (18)

[0113] f p2g,k,t =(η p2g,k P p2g,k,t ) / H g (19)

[0114] O p2g,k,t =λ p2g,k,t f p2g,k,t (20)

[0115]

[0116] In the above formula, formula (17) and (18) represent the numerical relationship between the power generation, gas consumption and carbon dioxide emission of the gas turbine, formula (19) and (20) represent the numerical relationship between the gas production, power consumption and carbon dioxide absorption of the power-to-gas equipment, and (21)-(22) describe the efficiency of carbon capture device in absorbing carbon dioxide and the electric power consumed.gt,k,t ,P p2g,k,t ,P ccu,k,t Represent the electrical power of the gas turbine, the power-to-gas device and the carbon capture device respectively; η gt,k ,η p2g,k ,η ccu,k Represent the operating efficiency of gas turbine, power-to-gas equipment and carbon capture device respectively; O gt,k,t ,O p2g,k,t , are the amounts of carbon dioxide output from the gas turbine, absorbed by the power-to-gas device, injected into the carbon capture device, and captured by the carbon capture device; H g Indicates the calorific value of natural gas, f gt,k,t ,f p2g,k,t Respectively represent the gas flow of gas turbine and power-to-gas equipment; gt,k ,λ p2g,k ,λ ccu,k They represent the carbon conversion efficiency of gas turbines, power-to-gas equipment and carbon capture devices respectively.

[0117] Energy complementarity is achieved by setting up multiple energy coupling devices in multiple energy base stations. The calculation of multiple energy complementarity is reflected in the above formulas (17)-(22). Through gas turbines, power-to-gas equipment and carbon capture devices, two-way conversion of energy and collection and utilization of carbon between the distribution network and the gas distribution network (natural gas) are realized. At the same time, on the load side, the above energy coupling devices are used to realize the alternative demand response on the load side, realize the complementarity between different energy networks, and solve the problem that the complementarity between multiple types of energy networks is not considered in the existing energy system scheduling.

[0118] S4: Construct a comprehensive demand response model based on multiple types of energy base stations.

[0119] In a specific implementation, the formula for constructing a comprehensive demand response model based on multiple types of energy base stations is as follows:

[0120]

[0121]

[0122] f MEH,k,t +f p2g,k,t =f load,k,t +f cut,k,t +f tran,k,t +f gt,k,t (29)

[0123] P MEH,k,t +P gt,k,t =P load,k,t +P cut,k,t +P tran,k,t +P p2g,k,t (30)

[0124] In the above formula, formula (23) and (24) describe the load constraints that can be reduced, formula (25)-(28) describe the load constraints that can be transferred, and formula (29) and (30) describe the load balance within the multi-type energy base station. MEH，k,t Indicates the amount of gas flowing into the multi-type energy base station; f p2g，k,t Indicates the gas flow rate of the power-to-gas device; f load,k,t ,f cut,k,t ,f tran,k,t Respectively represent the air flow of rigid load, reducible load and transferable load; f gt，k,t Indicates the gas flow of the gas turbine; P MEH，k,t Represents the active power flowing into the multi-type energy base station; P gt，k,t Represents the electrical power of the gas turbine; P load,k,t ,P cut,k,t ,P tran,k,t Represent the electric power of rigid load, curtailable load and transferable load respectively; P p2g，k,t Indicates the electrical power of the power-to-gas equipment; They represent the maximum air flow and electric power that can be reduced. They represent the maximum reducible gas flow and electric power of the transferable load, respectively. The replaceable load is actually achieved by the coupled units and does not refer to the specific load.

[0125] From the perspective of energy type, load types include electric load and natural gas load. From the perspective of response type, load types include curtailable load, transferable load and replaceable load. To achieve comprehensive demand response, it is necessary to coordinate multiple types of responsive loads from different energy networks. By performing balance calculations using formulas (23)-(30), the problem of multiple adjustable load types and difficulty in unified coordination on the load side in demand response can be solved.

[0126] S5: The mathematical models of the above-mentioned distribution network, gas distribution network, and various types of energy base stations and the comprehensive demand response model are integrated to calculate and dispatch the low-carbon economic operation of the system.

[0127] In a specific implementation, the calculation and scheduling of the low-carbon economic operation of the system includes the following steps:

[0128]

[0129] In the above formula, the objective function F is the total cost of system operation, including the electricity and natural gas purchased from the main grid, and the penalty cost caused by load reduction; where C1 and C2 represent the prices of electricity and natural gas purchased from the main grid, C3 and C4 represent the penalty coefficients of electricity load and gas load in the load that can be reduced, respectively, and P Grid,i,t ,f Grid,k,tRespectively represent the electric power and gas flow purchased from the main grid, P cut,i,t , f cut,i,t Represents the electric power and gas flow that can be reduced. Minimizing the objective function can achieve the low-carbon economic operation goal of multi-type energy base stations.

[0130] In the specific implementation, the constraints for calculating the low-carbon economic operation of the system are as follows:

[0131] P j,t =P Grid,i,t +P wind,i,t +P pv,i,t -P MEH,i,t (32)

[0132] Q j,t =Q Grid,i,t +Q win,i,t +Q pv,i,t -Q MEH,i,t (33)

[0133]

[0134] Formulas (32) and (33) represent the active power balance and reactive power balance of each bus node in the distribution network; P j,t is the active power of bus j; P Grid,i,t Indicates the electric power purchased from the main grid; P wind,i,t ,P pv,i,t Represent the active power output of wind turbine and photovoltaic respectively; P MEH，i,t Represents the active power flowing into the multi-type energy base station; Q j,t is the reactive power of bus j; Q Grid,i,t Indicates the reactive power flowing in from the main grid; Q win,i,t ,Q pv,i,t Respectively represent the reactive power output of wind turbine and photovoltaic; Q MEH，i,t Indicates the reactive power flowing into the multi-type energy base station;

[0135] Formula (34) represents the gas flow balance of each node in the gas distribution network; where f n-,k,t ,f n+,k,t They represent the gas flow in the downstream pipeline and the upstream pipeline connecting the node n respectively; f MEH，k,t represents the gas volume flowing into the multi-type energy base station; fGrid,k,t represents the gas volume purchased from the main grid.

[0136] Among them, purchasing from the main grid or flowing into from the main grid means that the distribution network or gas distribution network obtains electricity or natural gas from the external main grid, and flowing into multiple types of energy base stations means that electricity from the distribution network or gas from the gas distribution network flows into multiple types of energy base stations.

[0137] In the present application, by establishing the distribution network, gas distribution network, various equipment in multi-type energy base stations and a comprehensive demand response model, and then according to the constraints of the low-carbon economic operation calculation, the electric power and gas flow purchased from the main grid, the electric power and gas flow that can be reduced are obtained, and then the minimum total cost of the system operation can be calculated to achieve safe and economical energy supply of the energy system.

[0138] The present invention is a low-carbon economic dispatch method for an electricity-natural gas energy system that takes into account comprehensive demand response and carbon capture technology. First, the present invention establishes a detailed physical transmission model of the distribution network and the gas distribution network, and introduces the second-order cone relaxation technology to convert the nonlinear problem into a mixed integer second-order cone programming problem that can be reliably solved. Furthermore, the present invention proposes a comprehensive demand response dispatch model based on multiple types of energy base stations, and respectively models the reducible, transferable and replaceable load-side flexibility resources in detail, while providing detailed models of carbon capture technology, power-to-gas technology and gas turbines, so that different energy networks can directly coordinate low-carbon economic operations.

[0139] This application proposes a low-carbon economic dispatching method for an electricity-natural gas energy system that considers comprehensive demand response and carbon capture technology, solves the complementarity between multiple types of energy networks in system dispatching, proposes a consistent coordinated dispatching method that integrates multiple types of demand response load resources, and proposes a model nonlinear processing technology based on the second-order cone relaxation method.

[0140] Embodiment 2

[0141] A low-carbon economic dispatching system for an electric power-natural gas energy system, used to implement the low-carbon economic dispatching method for an electric power-natural gas energy system described in Example 1, comprising:

[0142] A distribution network modeling module, which is used to model the relationship between voltage, current and power in the distribution network using a branch power flow model, obtain a distribution network model and transform it using second-order cone relaxation;

[0143] Gas distribution network modeling module, which is used to model the relationship between pressure and gas flow in the natural gas pipeline network using the Weymouth equation, obtain the gas distribution network model and transform it using second-order cone relaxation;

[0144] Base station modeling module, which is used to mathematically model gas turbines, power-to-gas equipment and carbon capture devices in various types of energy base stations;

[0145] Demand response modeling module, which is used to build a comprehensive demand response model based on multiple types of energy base stations;

[0146] The calculation and scheduling module is used to integrate the mathematical models of the above-mentioned distribution network, gas distribution network, and various types of energy base stations and the comprehensive demand response model to calculate and schedule the low-carbon economic operation of the system.

[0147] Embodiment 3

[0148] A computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the above-mentioned low-carbon economic dispatching method for the electricity-natural gas energy system.

[0149] Embodiment 4

[0150] A processor is used to run a program, wherein the program executes the above-mentioned low-carbon economic dispatching method for the electricity-natural gas energy system when running.

[0151] The present application provides a method for low-carbon economic dispatching of an electric power-natural gas energy system, including: using a branch flow model to model the relationship between voltage, current and power in the distribution network, obtaining a distribution network model and applying second-order cone relaxation for transformation; using the Weymouth equation to model the relationship between pressure and gas flow in the natural gas pipeline network, obtaining a gas distribution network model and applying second-order cone relaxation for transformation; mathematically modeling gas turbines, power-to-gas equipment and carbon capture devices in multiple types of energy base stations; building a comprehensive demand response model based on multiple types of energy base stations; combining the mathematical models of the above-mentioned distribution network, gas distribution network, and various types of energy base stations, and the comprehensive demand response model, to calculate and dispatch the low-carbon economic operation of the system. The present invention establishes a detailed physical transmission model of the distribution network and the gas distribution network, and introduces the second-order cone relaxation technology to convert the nonlinear problem into a mixed integer second-order cone programming problem that can be reliably solved. Furthermore, the present invention proposes a comprehensive demand response scheduling model based on multiple types of energy base stations, which respectively models the reducible, transferable and replaceable load-side flexibility resources in detail, and provides detailed models of carbon capture technology, power-to-gas technology and gas turbines, thereby enabling different energy grids to directly coordinate low-carbon economic operations.

[0152] Those of ordinary skill in the art will appreciate that the units of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition of each example has been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0153] In the embodiments provided by the present invention, it should be understood that the division of units is only a logical function division, and there may be other division methods in actual implementation, for example, multiple units can be combined into one unit, one unit can be split into multiple units, or some features can be ignored, etc.

[0154] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0155] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-0nlyMemory), random access memory (RAM, RandomAccessMemory), mobile hard disk, magnetic disk or optical disk, etc., which can store program code.

[0156] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A low-carbon economic dispatching method for an electricity-natural gas energy system, characterized in that: include: The branch power flow model is used to model the relationship between voltage, current and power in the distribution network, and the distribution network model is obtained and transformed by applying second-order cone relaxation; The Weymouth equation is used to model the relationship between pressure and gas flow in the natural gas pipeline network, and the gas distribution network model is obtained and transformed by applying second-order cone relaxation. Mathematical modeling of gas turbines, power-to-gas equipment and carbon capture devices in various energy base stations; Build a comprehensive demand response model based on multiple types of energy base stations; The mathematical models of the above-mentioned distribution network, gas distribution network, and various types of energy base stations and the comprehensive demand response model are combined to calculate and dispatch the low-carbon economic operation of the system.

2. The low-carbon economic dispatching method for the electricity-natural gas energy system according to claim 1 is characterized in that: The method of using a branch power flow model to model the relationship between voltage, current and power in a distribution network, obtaining a distribution network model and applying second-order cone relaxation for transformation includes the following steps: The distribution network is modeled as follows: (V j,t ) 2 =(V i,t ) 2 -2(P jk,t r ij +Q ij,t x ij )+(z ij ) 2 (I ij,t ) 2 ; Apply second-order cone relaxation for transformation, introduce relaxation variables, and let: The distribution network model formula after conversion is as follows: The equivalent transformation of the second-order cone relaxation is as follows: In the above formula, L ij,t , U i,t , U j,t They are The corresponding slack variables; I, K represent the upstream bus set and downstream bus set of bus j respectively; i is the upstream bus of bus j, k is the downstream bus of bus j; P j,t ,Q j,t They are respectively represented as the active power and reactive power injected into bus j; P ij,t ,Q ij,t They are respectively represented as the active power and reactive power of branch ij flowing from bus i to bus j; P jk,t ,Q jk,t They are respectively represented as the active power and reactive power of branch jk flowing from bus j to bus k; ij ,r ij ,z ij Respectively represent the reactance, resistance and impedance of branch ij; V i,t ,V j,t They are represented by the voltage of bus i and bus j respectively; I ij,t is the branch ij current.

3. The low-carbon economic dispatching method for the electricity-natural gas energy system according to claim 1 is characterized in that: The method of using the Weymouth equation to model the relationship between pressure and gas flow in the natural gas pipeline network, obtaining a gas distribution network model and applying second-order cone relaxation for transformation includes the following steps: The gas distribution network is modeled as follows: Apply second-order cone relaxation to transform and introduce binary variables and make: Introducing the variable π m,t and π n,t ,make: The formula after transforming the gas distribution network model is as follows: Introducing variable M mn,t,k ,make: The equivalent transformation of the second-order cone relaxation is obtained as follows: In the above formula, f mn,k,t is the natural gas flow rate of pipeline mn; sgn(m,n) k,t Indicates the flow direction of natural gas in the pipeline at the nodes on both sides; c k is the pipeline coefficient; p m,t 、p n,t Respectively represent the pressure at the m and n nodes of the pipeline; Δx k ,D k are the length and inner diameter of the pipe mn respectively; ρ0 represents the gas density; F k , R are the friction coefficient and gas constant, T and Z are the gas temperature and compressibility coefficient respectively.

4. The low-carbon economic dispatching method for the electricity-natural gas energy system according to claim 1 is characterized in that: The mathematical modeling of the gas turbine, power-to-gas equipment and carbon capture device in the multi-type energy base station is as follows: P gt,k,t =η gt,k H g f gt,k,t ; The gt,k,t =λ gt,k f gt,k,t ; f p2g,k,t =(η p2g,k P p2g,k,t ) / H g ; The p2g,k,t =λ p2g,k,t f p2g,k,t ; In the above formula, P gt,k,t ,P p2g,k,t ,P ccu,k,t Represent the electrical power of the gas turbine, the power-to-gas device and the carbon capture device respectively; η gt,k ,η p2g,k ,η ccu,k Represent the operating efficiency of gas turbine, power-to-gas equipment and carbon capture device respectively; O gt,k,t ,O p2g,k,t , are the amounts of carbon dioxide output from the gas turbine, absorbed by the power-to-gas device, injected into the carbon capture device, and captured by the carbon capture device; H g Indicates the calorific value of natural gas, f gt,k,t ,f p2g,k,t Respectively represent the gas flow of gas turbine and power-to-gas equipment; gt,k ,λ p2g,k ,λ ccu,k They represent the carbon conversion efficiency of gas turbines, power-to-gas equipment and carbon capture devices respectively.

5. The low-carbon economic dispatching method for the electricity-natural gas energy system according to claim 1 is characterized in that: The formula for constructing a comprehensive demand response model based on multiple types of energy base stations is as follows: f MEH,k,t +f p2g,k,t =f load,k,t +f cut,k,t +f tran,k,t +f gt,k,t； P MEH,k,t +P gt,k,t =P load,k,t +P cut,k,t +P tran,k,t +P p2g,k,t； In the above formula, f MEH，k,t Indicates the amount of gas flowing into the multi-type energy base station; f p2g，k,t Indicates the gas flow rate of the power-to-gas device; f load,k,t ,f cut,k,t ,f tran,k,t Respectively represent the air flow of rigid load, reducible load and transferable load; f gt，k,t Indicates the gas flow of the gas turbine; P MEH，k,t Represents the active power flowing into the multi-type energy base station; P gt，k,t Represents the electrical power of the gas turbine; P load,k,t ,P cut,k,t ,P tran,k,t Represent the electric power of rigid load, curtailable load and transferable load respectively; P p2g，k,t Indicates the electrical power of the power-to-gas equipment; They represent the maximum air flow and electric power that can be reduced. They represent the maximum reducible gas flow and electrical power of the transferable load respectively.

6. The low-carbon economic dispatching method of the electricity-natural gas energy system according to claim 1 is characterized in that: The calculation and scheduling of the low-carbon economic operation of the system includes the following steps: In the above formula, C1 and C2 represent the prices of electricity and natural gas purchased from the main grid, respectively; C3 and C4 represent the penalty coefficients of electricity load and gas load in the load that can be reduced, respectively; P Grid,i,t ,f Grid,k,t Respectively represent the electric power and gas flow purchased from the main grid, P cut,i,t , f cut,i,t Indicates the electrical power and gas flow that can be reduced.

7. The low-carbon economic dispatching method for the electricity-natural gas energy system according to claim 6 is characterized in that: The constraints for calculating the low-carbon economic operation of the system are as follows: P j,t =P Grid,i,t +P wind,i,t +P pv,i,t -P MEH,i,t ; Q j,t =Q Grid,i,t +Q win,i,t +Q pv,i,t -Q MEH,i,t ; In the above formula, P j,t is the active power of bus j; P Grid,i,t Indicates the electric power purchased from the main grid; P wind,i,t ,P pv,i,t Represent the active power output of wind turbine and photovoltaic respectively; P MEH，i,t Represents the active power flowing into the multi-type energy base station; Q j,t is the reactive power of bus j; Q Grid,i,t Indicates the reactive power flowing in from the main grid; Q win,i,t ,Q pv,i,t Respectively represent the reactive power output of wind turbine and photovoltaic; Q MEH，i,t represents the reactive power flowing into the multi-type energy base station; f n-,k,t ,f n+,k,t They represent the gas flow in the downstream pipeline and the upstream pipeline connecting the node n respectively; f MEH，k,t Indicates the amount of gas flowing into the multi-type energy base station; f Grid,k,t Indicates the amount of gas purchased from the main network.

8. A low-carbon economic dispatching system for an electricity-natural gas energy system, characterized in that: The low-carbon economic dispatch method for the electric power-natural gas energy system as claimed in any one of claims 1 to 7 comprises: A distribution network modeling module, which is used to model the relationship between voltage, current and power in the distribution network using a branch power flow model, obtain a distribution network model and transform it using second-order cone relaxation; Gas distribution network modeling module, which is used to model the relationship between pressure and gas flow in the natural gas pipeline network using the Weymouth equation, obtain the gas distribution network model and transform it using second-order cone relaxation; Base station modeling module, which is used to mathematically model gas turbines, power-to-gas equipment and carbon capture devices in various types of energy base stations; Demand response modeling module, which is used to build a comprehensive demand response model based on multiple types of energy base stations; The calculation and scheduling module is used to integrate the mathematical models of the above-mentioned distribution network, gas distribution network, and various types of energy base stations and the comprehensive demand response model to calculate and schedule the low-carbon economic operation of the system.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the low-carbon economic dispatch method for the electricity-natural gas energy system according to any one of claims 1 to 7.

10. A processor, characterized in that: The processor is used to run a program, wherein the program, when running, executes the low-carbon economic dispatch method for the electricity-natural gas energy system described in any one of claims 1 to 7.

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