Distributed optimization operation method and device for electrical integrated energy system

Abstract

The invention relates to the technical field of energy scheduling, and particularly provides a distributed optimization operation method and device for an electrical integrated energy system, and the method comprises the steps: determining a distributed optimization operation target function of the electrical integrated energy system based on the economic cost and environment cost of the electrical integrated energy system; solving the distributed optimization operation objective function of the electrical integrated energy system by adopting an alternating direction multiplier method to obtain an optimization result; based on the optimization result, obtaining a distributed optimization operation scheme of the electrical integrated energy system; according to the technical scheme provided by the invention, economic operation and low-carbon operation of the electrical integrated energy system can be realized.

Description

Technical Field

[0001] This invention relates to the field of energy dispatching technology, specifically to a distributed optimized operation method and apparatus for an integrated electrical energy system. Background Technology

[0002] With the increasing prominence of environmental pollution and the contradiction between energy supply and demand, diversified and open energy supply systems and complementary and interconnected energy consumption patterns are developing rapidly. Therefore, it is crucial to integrate renewable energy into the existing energy system and consider the carbon dioxide emissions of the integrated energy system. Constructing an integrated electrical system in which the power system and the natural gas system are coupled and operate in a coordinated manner is of great significance for improving energy utilization efficiency and fully leveraging the flexibility of multi-energy systems.

[0003] Traditional integrated energy system optimization scheduling is mainly based on economic considerations and does not take into account environmental impact. Therefore, it is particularly important to transform the original single economic scheduling into low-carbon economic scheduling. Summary of the Invention

[0004] To overcome the above-mentioned shortcomings, this invention proposes a distributed optimization operation method and device for an integrated electrical energy system.

[0005] Firstly, a distributed optimization operation method for an integrated electrical energy system is provided, the method comprising:

[0006] Determine the objective function for the distributed optimal operation of the integrated electrical energy system based on its economic and environmental costs;

[0007] The objective function of the distributed optimization operation of the electrical integrated energy system is solved using the alternating direction multiplier method, and the optimization results are obtained.

[0008] Based on the optimization results, a distributed optimized operation scheme for the integrated electrical energy system is obtained;

[0009] The integrated electrical energy system includes at least one of the following: power grid, natural gas grid, wind turbine, photovoltaic power station, energy storage device, P2G equipment, gas turbine, substation, and gas distribution station. The optimization results include at least one of the following: active power of substation, active power of gas turbine, active power generated by wind turbine, active power generated by photovoltaic power station, charging and discharging power of energy storage device, active power transmitted by power grid line, active power consumed by P2G equipment, active power load, and natural gas pipeline inventory.

[0010] Preferably, the economic cost of the integrated electrical energy system is as follows:

[0011]

[0012] In the above formula, f eco For the economic cost of an integrated electrical energy system, The economic cost of the power network for an integrated electrical energy system. The economic cost of the natural gas network for an integrated electrical energy system.

[0013] Furthermore, the economic cost of the power network for the aforementioned integrated electrical energy system is as follows:

[0014]

[0015] The economic cost of the natural gas network in the aforementioned integrated electrical energy system is as follows:

[0016]

[0017] In the above formula, These are the unit electricity price and unit gas price at time t, respectively. These represent the unit electricity load reduction cost, unit wind power output reduction cost, unit solar power output reduction cost, and unit gas load reduction cost at time t, respectively, Ω. PN Ω is the set of nodes in a power network. GN For a set of natural gas network nodes, The unit operation and maintenance costs at time t are: substation, wind turbine, photovoltaic unit, energy storage equipment, P2G equipment, and gas turbine. Let be the active power outputs of the substation, gas turbine, wind turbine, and photovoltaic power station at node i at time t. Let be the active power consumed by the P2G device at node i at time t. Let be the discharge and charge power of the energy storage device at node i at time t, respectively. Let be the load at node i, the power reduction of the wind turbine, and the photovoltaic power station at time t, and T be the total time of the optimization period. Let be the natural gas flow rate consumed by the substation at node m at time t. Reduce the natural gas flow at node m.

[0018] Furthermore, the environmental costs of the aforementioned integrated electrical energy system are as follows:

[0019] f env =C CET +C GCT

[0020] In the above formula, f env For the environmental cost of an integrated electrical energy system, C CET For carbon trading costs, CGCT Costs associated with green certificate transactions.

[0021] Furthermore, the carbon trading costs are as follows:

[0022]

[0023] In the above formula, γ is the base price for carbon trading, and E r E represents the actual carbon emissions under the carbon-green certificate joint trading mechanism. d Let λ represent the total amount of carbon emission trading quotas, λ represent the purchase range of tiered carbon trading, and k represent the growth rate of the tiered carbon trading price.

[0024] Furthermore, the actual carbon emissions under the carbon-green certificate joint trading mechanism are as follows:

[0025]

[0026] The total amount of carbon emission trading quotas is as follows:

[0027]

[0028] In the above formula, Ω sub Ω gt Ω wt Ω pv Ω p2g These are collections of substations, gas turbines, wind turbines, photovoltaic power plants, and P2G equipment, respectively. g s gt s wt s pv These represent the carbon emissions per unit of active power output for thermal power units, gas turbines, wind turbines, and photovoltaic power plants, respectively. p2g δ represents the mass of CO2 utilized when a P2G device converts a unit of electrical energy into natural gas. g δ gt δ wt δ pv These represent the carbon emission trading quotas for thermal power units, gas turbines, wind turbines, and photovoltaic power plants per unit of active power output, δ E Carbon emissions offset by redundant green certificates.

[0029] Furthermore, the transaction costs for the green certificate are as follows:

[0030]

[0031] In the above formula, ξ is the unit green certificate trading price, ω is the system green certificate quota ratio, and Ω is the green certificate trading price. PL For the set of power grid load nodes, Let B be the electrical load power of node i at time t.o This refers to the number of green certificates issued to renewable energy power generation companies.

[0032] Furthermore, the mathematical model corresponding to the natural gas network is as follows:

[0033]

[0034] M=ρωA

[0035] In the above formula, ρ is the gas density, M is the gas mass flow rate, t represents time t, A is the cross-sectional area of ​​the pipe, and x is the pipe length. Let λ be the average gas flow rate, λ be the purchase range for tiered carbon trading, and d be the pipe diameter.

[0036] Furthermore, the mathematical model corresponding to the natural gas network is as follows:

[0037]

[0038] In the above formula, A ij Let M be the cross-sectional area of ​​the gas pipeline ij. i,t M j,t M represents the mass flow rate of natural gas at the beginning and end of the gas pipeline ij at time t, respectively. i,t+1 M j,t+1 p represents the mass flow rate of natural gas at the beginning and end of the gas transmission pipeline ij at time t+1. i,t p j,t p represents the gas pressure at the beginning and end of the gas pipeline ij at time t, respectively. i,t+1 p j,t+1 ρ represents the gas pressure at the beginning and end of the gas pipeline ij at time t+1. i,t ρ j,t ρ represents the gas density at the beginning and end of the gas pipeline ij at time t. i,t+1 ρ j,t+1 Let be the gas densities at the beginning and end of the gas pipeline ij at time t+1, respectively. Let d be the length of the gas pipeline ij. ij Let be the diameter of the gas pipeline ij. Let denoted as the average flow rate of natural gas in the gas pipeline ij, and λ be the purchase range for the tiered carbon trading scheme.

[0039] Furthermore, the mathematical model corresponding to the natural gas network includes the following constraint model:

[0040]

[0041] M i,t =F i,t ρ i,t

[0042] In the above formula, Let each be a set of gas pipelines in a natural gas network, with node i at the beginning and node i at the end. Let represent the gas purchase volume of the gas distribution station at node i at time t. Let be the mass flow rate of natural gas produced by the P2G device at node i at time t. Let be the natural gas load of node i at time t. Let be the mass flow rate of natural gas consumed by the gas turbine at node i at time t. Let be the mass flow rates of natural gas at the beginning and end of the gas transmission pipeline ij at time t, respectively. Let p be the mass flow rate of natural gas at the end of the gas pipeline ki at time t. i,t Let be the gas pressure at node i at time t. Let be the gas pressure at the beginning of the gas pipeline ij at time t. Let ki be the gas pressure at the end of the gas pipeline at time t. These are the lower and upper pressure limits for node i, respectively. These are the lower and upper limits of the natural gas mass flow rate at the inlet of the gas transmission pipeline ij, respectively. These are the lower and upper limits of the natural gas mass flow rate at the ij terminal of the gas transmission pipeline, respectively. Let represent the natural gas reduction at node i at time t. This provides typical natural gas load scenario data for node i. Let F be the peak natural gas load at node i. i,t For mass flow rate M i,t The gas flow rate corresponding to natural gas.

[0043] Secondly, a distributed optimization operation device for an integrated electrical energy system is provided, the integrated electrical energy system distributed optimization operation device comprising:

[0044] The first analysis module is used to determine the objective function for the distributed optimal operation of the integrated electrical energy system based on the economic and environmental costs of the integrated electrical energy system.

[0045] The second analysis module is used to solve the distributed optimization operation objective function of the electrical integrated energy system using the alternating direction multiplier method, and obtain the optimization results;

[0046] The third analysis module is used to obtain a distributed optimized operation scheme for the integrated electrical energy system based on the optimization results.

[0047] The integrated electrical energy system includes at least one of the following: power grid, natural gas grid, wind turbine, photovoltaic power station, energy storage device, P2G equipment, gas turbine, substation, and gas distribution station. The optimization results include at least one of the following: active power of substation, active power of gas turbine, active power generated by wind turbine, active power generated by photovoltaic power station, charging and discharging power of energy storage device, active power transmitted by power grid line, active power consumed by P2G equipment, active power load, and natural gas pipeline inventory.

[0048] Thirdly, a computer device is provided, comprising: one or more processors;

[0049] The processor is used to execute one or more programs;

[0050] When the one or more programs are executed by the one or more processors, the distributed optimized operation method of the integrated electrical energy system is implemented.

[0051] Fourthly, a computer-readable storage medium is provided, on which a computer program is stored, wherein when the computer program is executed, the distributed optimized operation method of the integrated electrical energy system is implemented.

[0052] The above-described technical solutions of the present invention have at least one or more of the following beneficial effects:

[0053] This invention provides a distributed optimization operation method for an integrated electrical energy system. The method includes: determining an objective function for the distributed optimization operation of the integrated electrical energy system based on its economic and environmental costs; solving the objective function using the alternating direction multiplier method to obtain optimization results; and obtaining a distributed optimization operation scheme for the integrated electrical energy system based on the optimization results. The integrated electrical energy system includes at least one of the following: a power grid, a natural gas grid, wind turbines, a photovoltaic power station, an energy storage device, a P2G device, a gas turbine, a substation, and a gas distribution station. The optimization results include at least one of the following: the active power of the substation, the active power of the gas turbine, the active power generated by the wind turbine, the active power generated by the photovoltaic power station, the charging and discharging power of the energy storage device, the active power transmitted by the power grid lines, the active power consumed by the P2G device, the active load of the power grid, and the natural gas pipeline inventory. The technical solution provided by this invention considers the dynamic transmission characteristics of natural gas, using the gas pipeline inventory as a flexible scheduling resource, increasing the energy utilization efficiency and flexibility of the integrated electrical energy system, thereby achieving economical and low-carbon operation of the integrated electrical energy system. Attached Figure Description

[0054] Figure 1This is a schematic diagram of the main steps of the distributed optimization operation method of the electrical integrated energy system according to an embodiment of the present invention. Detailed Implementation

[0055] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0056] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0057] Example 1

[0058] See appendix Figure 1 , Figure 1 This is a schematic flowchart illustrating the main steps of a distributed optimized operation method for an integrated electrical energy system according to an embodiment of the present invention. Figure 1 As shown, the distributed optimization operation method of the integrated electrical energy system in this embodiment of the invention mainly includes the following steps:

[0059] Step S101: Determine the objective function for the distributed optimal operation of the integrated electrical energy system based on its economic and environmental costs;

[0060] Step S102: Solve the objective function of the distributed optimization operation of the electrical integrated energy system using the alternating direction multiplier method to obtain the optimization result;

[0061] Step S103: Based on the optimization results, obtain the distributed optimized operation scheme of the integrated electrical energy system;

[0062] The integrated electrical energy system includes at least one of the following: power grid, natural gas grid, wind turbine, photovoltaic power station, energy storage device, P2G equipment, gas turbine, substation, and gas distribution station. The optimization results include at least one of the following: active power of substation, active power of gas turbine, active power generated by wind turbine, active power generated by photovoltaic power station, charging and discharging power of energy storage device, active power transmitted by power grid line, active power consumed by P2G equipment, active power load, and natural gas pipeline inventory.

[0063] In this embodiment, the economic cost of the integrated electrical energy system is as follows:

[0064]

[0065] In the above formula, feco For the economic cost of an integrated electrical energy system, The economic cost of the power network for an integrated electrical energy system. The economic cost of the natural gas network for an integrated electrical energy system.

[0066] In one embodiment, the economic cost of the power network for the integrated electrical energy system is as follows:

[0067]

[0068] The economic cost of the natural gas network in the aforementioned integrated electrical energy system is as follows:

[0069]

[0070] In the above formula, These are the unit electricity price and unit gas price at time t, respectively. These represent the unit electricity load reduction cost, unit wind power output reduction cost, unit solar power output reduction cost, and unit gas load reduction cost at time t, respectively, Ω. PN Ω is the set of nodes in a power network. GN For a set of natural gas network nodes, The unit operation and maintenance costs at time t are: substation, wind turbine, photovoltaic unit, energy storage equipment, P2G equipment, and gas turbine. Let be the active power outputs of the substation, gas turbine, wind turbine, and photovoltaic power station at node i at time t. Let be the active power consumed by the P2G device at node i at time t. Let be the discharge and charge power of the energy storage device at node i at time t, respectively. Let be the load at node i, the power reduction of the wind turbine, and the photovoltaic power station at time t, and T be the total time of the optimization period. Let be the natural gas flow rate consumed by the substation at node m at time t. Reduce the natural gas flow at node m.

[0071] In one embodiment, the environmental cost of the integrated electrical energy system is as follows:

[0072] f env =C CET +C GCT

[0073] In the above formula, f env For the environmental cost of an integrated electrical energy system, C CET For carbon trading costs, C GCTCosts associated with green certificate transactions.

[0074] In one implementation, the carbon trading cost is as follows:

[0075]

[0076] In the above formula, γ is the base price for carbon trading, and E r E represents the actual carbon emissions under the carbon-green certificate joint trading mechanism. d Let λ represent the total amount of carbon emission trading quotas, λ represent the purchase range of tiered carbon trading, and k represent the growth rate of the tiered carbon trading price.

[0077] In one implementation, the actual carbon emissions under the carbon-green certificate joint trading mechanism are as follows:

[0078]

[0079] The total amount of carbon emission trading quotas is as follows:

[0080]

[0081] In the above formula, Ω sub Ω gt Ω wt Ω pv Ω p2g These are collections of substations, gas turbines, wind turbines, photovoltaic power plants, and P2G equipment, respectively. g s gt s wt s pv These represent the carbon emissions per unit of active power output for thermal power units, gas turbines, wind turbines, and photovoltaic power plants, respectively. p2g δ represents the mass of CO2 utilized when a P2G device converts a unit of electrical energy into natural gas. g δ gt δ wt δ pv These represent the carbon emission trading quotas for thermal power units, gas turbines, wind turbines, and photovoltaic power plants per unit of active power output, δ E Carbon emissions offset by redundant green certificates.

[0082] In one implementation, the transaction cost of the green certificate is as follows:

[0083]

[0084] In the above formula, ξ is the unit green certificate trading price, ω is the system green certificate quota ratio, and Ω is the green certificate trading price. PL For the set of power grid load nodes, Let B be the electrical load power of node i at time t.o This refers to the number of green certificates issued to renewable energy power generation companies.

[0085] In one implementation, the mathematical model corresponding to the natural gas network is as follows:

[0086]

[0087]

[0088] M=ρωA

[0089] In the above formula, ρ is the gas density, M is the gas mass flow rate, t represents time t, A is the cross-sectional area of ​​the pipe, and x is the pipe length. Let λ be the average gas flow rate, λ be the purchase range for tiered carbon trading, and d be the pipe diameter.

[0090] In one implementation, the mathematical model corresponding to the natural gas network is as follows:

[0091]

[0092] In the above formula, A ij Let M be the cross-sectional area of ​​the gas pipeline ij. i,t M j,t M represents the mass flow rate of natural gas at the beginning and end of the gas pipeline ij at time t, respectively. i,t+1 M j,t+1 p represents the mass flow rate of natural gas at the beginning and end of the gas transmission pipeline ij at time t+1. i,t p j,t p represents the gas pressure at the beginning and end of the gas pipeline ij at time t, respectively. i,t+1 p j,t+1 ρ represents the gas pressure at the beginning and end of the gas pipeline ij at time t+1. i,t ρ j,t ρ represents the gas density at the beginning and end of the gas pipeline ij at time t. i,t+1 ρ j,t+1 Let be the gas densities at the beginning and end of the gas pipeline ij at time t+1, respectively. Let d be the length of the gas pipeline ij. ij Let be the diameter of the gas pipeline ij. Let denoted as the average flow rate of natural gas in the gas pipeline ij, and λ be the purchase range for the tiered carbon trading scheme.

[0093] In one implementation, the mathematical model corresponding to the natural gas network includes the following constraint model:

[0094]

[0095] M i,t =F i,t ρ i,t

[0096] In the above formula, Let each be a set of gas pipelines in a natural gas network, with node i at the beginning and node i at the end. Let represent the gas purchase volume of the gas distribution station at node i at time t. Let be the mass flow rate of natural gas produced by the P2G device at node i at time t. Let be the natural gas load of node i at time t. Let be the mass flow rate of natural gas consumed by the gas turbine at node i at time t. Let be the mass flow rates of natural gas at the beginning and end of the gas transmission pipeline ij at time t, respectively. Let p be the mass flow rate of natural gas at the end of the gas pipeline ki at time t. i,t Let be the gas pressure at node i at time t. Let be the gas pressure at the beginning of the gas pipeline ij at time t. Let ki be the gas pressure at the end of the gas pipeline at time t. These are the lower and upper pressure limits for node i, respectively. These are the lower and upper limits of the natural gas mass flow rate at the inlet of the gas transmission pipeline ij, respectively. These are the lower and upper limits of the natural gas mass flow rate at the ij terminal of the gas transmission pipeline, respectively. Let represent the natural gas reduction at node i at time t. This provides typical natural gas load scenario data for node i. Let F be the peak natural gas load at node i. i,t For mass flow rate M i,t The gas flow rate corresponding to natural gas.

[0097] In one implementation, the power network model is as follows:

[0098]

[0099] Where: Ω PN (i) represents all nodes connected to node i in the power grid; These represent the active power and reactive power of the substation, respectively. These represent the active power and reactive power of the gas turbine, respectively. This indicates the active power generated by the wind turbine. This indicates the active power generated by the photovoltaic power station; These represent the discharge power and charging power of the energy storage device, respectively. These represent the active power and reactive power transmitted through the power grid line ij, respectively. This indicates the active power consumed by the P2G device; Indicates active and reactive power loads; or V i min V i max These represent the square of the node voltage amplitude and its lower and upper limits, respectively; r ij x ij Let represent the resistance per unit length and the reactance per unit length of the power grid line ij, respectively; Indicates the length of the power grid line ij; This indicates the upper limit of the transmission capacity of power grid line ij; Electricity active load reduction; This represents data related to typical power load scenarios; Indicates the peak value of the active power load; ε l This represents the power factor of the electrical load.

[0100] The wind turbine and photovoltaic power station models are as follows:

[0101]

[0102] In the formula: This represents the power reduction of the wind turbine at time t; This represents the maximum power output that the wind turbine can generate at time t; This represents the power reduction of the photovoltaic power plant at time t; This represents the maximum power output that a photovoltaic power station can generate at time t.

[0103] The P2G device model is as follows:

[0104]

[0105] In the formula: η p2g Indicates the energy conversion efficiency of P2G equipment; H represents the active power consumed by the P2G device at time t; gas Indicates the calorific value of natural gas; Indicates the upper limit of the operating power of P2G devices; This represents the flow rate of natural gas produced and injected into node m of the natural gas network by the P2G device at time t; These represent the mass of carbon dioxide emissions that P2G devices can reduce and the density of carbon dioxide, respectively.

[0106] In one specific implementation, based on the objective function and constraints, the Alternating Direction Method of Multipliers (ADMM) is used to decouple the original problem, iteratively solving the power system and the natural gas system, and finally obtaining the optimal scheduling scheme at the convergence point of the objective function. ADMM can realize distributed solutions to large-scale problems, and has the advantages of simple form, good convergence, and ease of solution. By iteratively applying relevant variables, it achieves common convergence. The optimization problem is shown in the following equation:

[0107] minf(x) + g(y)

[0108] st Ax+By=C

[0109] In the formula: f(x) and g(y) are two convex optimization subproblems; x and y are variables; A, B, and C are constraint matrices of the variables in the equality constraints. The augmented Lagrangian function is as follows: L ρ (x,y,λ):

[0110]

[0111] In the formula: λ is the Lagrange multiplier; ρ is the dual update step size and ρ>0; ||2 represents the L2 norm.

[0112] The iteration process requires updating three parts: variables x, y, and the Lagrange multiplier λ. The standard update format for iteration k+1 is:

[0113]

[0114] In the formula, the superscript indicates the number of iterations.

[0115] Furthermore, the electrical power of the P2G equipment and the gas turbine are selected as coupling variables, where the relevant constraints between the dual variables are determined by the models of the gas turbine and the P2G unit. This decouples the integrated electrical energy system, splitting the original objective function into two parts: a distribution network subsystem and a natural gas subsystem, which are then solved using the ADMM algorithm. Other variables and related constraints are assigned to their respective subproblems, thus achieving the separation of the two electrical subsystems. The solution method based on the ADMM algorithm is shown below:

[0116] The interconnection power between the distribution network and the gas distribution network is selected as the coupling variable, and decoupling is achieved at the coupling variable. This includes the power P of P2G equipment. P2G The power of the gas turbine P GT By introducing auxiliary variables at the coupling variables, spatial decoupling of the integrated electrical energy system can be achieved.

[0117] Through the decoupling process, the centralized optimization problem of the integrated electrical energy system can be transformed into a combination of the distribution network optimization sub-problem and the gas distribution network optimization sub-problem, and finally solved iteratively.

[0118] Example 2

[0119] Based on the same inventive concept, the present invention also provides a distributed optimization operation device for an integrated electrical energy system, the distributed optimization operation device for an integrated electrical energy system comprising:

[0120] The first analysis module is used to determine the objective function for the distributed optimal operation of the integrated electrical energy system based on the economic and environmental costs of the integrated electrical energy system.

[0121] The second analysis module is used to solve the distributed optimization operation objective function of the electrical integrated energy system using the alternating direction multiplier method, and obtain the optimization results;

[0122] The third analysis module is used to obtain a distributed optimized operation scheme for the integrated electrical energy system based on the optimization results.

[0123] The integrated electrical energy system includes at least one of the following: power grid, natural gas grid, wind turbine, photovoltaic power station, energy storage device, P2G equipment, gas turbine, substation, and gas distribution station. The optimization results include at least one of the following: active power of substation, active power of gas turbine, active power generated by wind turbine, active power generated by photovoltaic power station, charging and discharging power of energy storage device, active power transmitted by power grid line, active power consumed by P2G equipment, active power load, and natural gas pipeline inventory.

[0124] Preferably, the economic cost of the integrated electrical energy system is as follows:

[0125]

[0126] In the above formula, f eco For the economic cost of an integrated electrical energy system, The economic cost of the power network for an integrated electrical energy system. The economic cost of the natural gas network for an integrated electrical energy system.

[0127] Furthermore, the economic cost of the power network for the aforementioned integrated electrical energy system is as follows:

[0128]

[0129] The economic cost of the natural gas network in the aforementioned integrated electrical energy system is as follows:

[0130]

[0131] In the above formula, These are the unit electricity price and unit gas price at time t, respectively. These represent the unit electricity load reduction cost, unit wind power output reduction cost, unit solar power output reduction cost, and unit gas load reduction cost at time t, respectively, Ω. PN Ω is the set of nodes in a power network. GN For a set of natural gas network nodes, The unit operation and maintenance costs at time t are: substation, wind turbine, photovoltaic unit, energy storage equipment, P2G equipment, and gas turbine. Let be the active power outputs of the substation, gas turbine, wind turbine, and photovoltaic power station at node i at time t. Let be the active power consumed by the P2G device at node i at time t. Let be the discharge and charge power of the energy storage device at node i at time t, respectively. Let be the load at node i, the power reduction of the wind turbine, and the photovoltaic power station at time t, and T be the total time of the optimization period. Let be the natural gas flow rate consumed by the substation at node m at time t. Reduce the natural gas flow at node m.

[0132] Furthermore, the environmental costs of the aforementioned integrated electrical energy system are as follows:

[0133] f env =C CET +C GCT

[0134] In the above formula, f env For the environmental cost of an integrated electrical energy system, C CET For carbon trading costs, C GCT Costs associated with green certificate transactions.

[0135] Furthermore, the carbon trading costs are as follows:

[0136]

[0137] In the above formula, γ is the base price for carbon trading, and E r E represents the actual carbon emissions under the carbon-green certificate joint trading mechanism. d Let λ represent the total amount of carbon emission trading quotas, λ represent the purchase range of tiered carbon trading, and k represent the growth rate of the tiered carbon trading price.

[0138] Furthermore, the actual carbon emissions under the carbon-green certificate joint trading mechanism are as follows:

[0139]

[0140] The total amount of carbon emission trading quotas is as follows:

[0141]

[0142] In the above formula, Ω sub Ω gt Ω wt Ω pv Ω p2g These are collections of substations, gas turbines, wind turbines, photovoltaic power plants, and P2G equipment, respectively. g s gt s wt s pv These represent the carbon emissions per unit of active power output for thermal power units, gas turbines, wind turbines, and photovoltaic power plants, respectively. p2g δ represents the mass of CO2 utilized when a P2G device converts a unit of electrical energy into natural gas. g δ gt δ wt δ pv These represent the carbon emission trading quotas for thermal power units, gas turbines, wind turbines, and photovoltaic power plants per unit of active power output, δ E Carbon emissions offset by redundant green certificates.

[0143] Furthermore, the transaction costs for the green certificate are as follows:

[0144]

[0145] In the above formula, ξ is the unit green certificate trading price, ω is the system green certificate quota ratio, and Ω is the green certificate trading price. PL For the set of power grid load nodes, Let B be the electrical load power of node i at time t. o This refers to the number of green certificates issued to renewable energy power generation companies.

[0146] Furthermore, the mathematical model corresponding to the natural gas network is as follows:

[0147]

[0148] M=ρωA

[0149] In the above formula, ρ is the gas density, M is the gas mass flow rate, t represents time t, A is the cross-sectional area of ​​the pipe, and x is the pipe length. Let λ be the average gas flow rate, λ be the purchase range for tiered carbon trading, and d be the pipe diameter.

[0150] Furthermore, the mathematical model corresponding to the natural gas network is as follows:

[0151]

[0152] In the above formula, A ij Let M be the cross-sectional area of ​​the gas pipeline ij. i,t M j,t M represents the mass flow rate of natural gas at the beginning and end of the gas pipeline ij at time t, respectively. i,t+1 M j,t+1 p represents the mass flow rate of natural gas at the beginning and end of the gas transmission pipeline ij at time t+1. i,t p j,t p represents the gas pressure at the beginning and end of the gas pipeline ij at time t, respectively. i,t+1 p j,t+1 ρ represents the gas pressure at the beginning and end of the gas pipeline ij at time t+1. i,t ρ j,t ρ represents the gas density at the beginning and end of the gas pipeline ij at time t. i,t+1 ρ j,t+1 Let be the gas densities at the beginning and end of the gas pipeline ij at time t+1, respectively. Let d be the length of the gas pipeline ij. ij Let be the diameter of the gas pipeline ij. Let denoted as the average flow rate of natural gas in the gas pipeline ij, and λ be the purchase range for the tiered carbon trading scheme.

[0153] Furthermore, the mathematical model corresponding to the natural gas network includes the following constraint model:

[0154]

[0155]

[0156] M i,t =F i,t ρ i,t

[0157] In the above formula, Let each be a set of gas pipelines in a natural gas network, with node i at the beginning and node i at the end. Let represent the gas purchase volume of the gas distribution station at node i at time t. Let be the mass flow rate of natural gas produced by the P2G device at node i at time t. Let be the natural gas load of node i at time t. Let be the mass flow rate of natural gas consumed by the gas turbine at node i at time t. Let be the mass flow rates of natural gas at the beginning and end of the gas transmission pipeline ij at time t, respectively. Let p be the mass flow rate of natural gas at the end of the gas pipeline ki at time t. i,t Let be the gas pressure at node i at time t. Let be the gas pressure at the beginning of the gas pipeline ij at time t. Let ki be the gas pressure at the end of the gas pipeline at time t. These are the lower and upper pressure limits for node i, respectively. These are the lower and upper limits of the natural gas mass flow rate at the inlet of the gas transmission pipeline ij, respectively. These are the lower and upper limits of the natural gas mass flow rate at the ij terminal of the gas transmission pipeline, respectively. Let represent the natural gas reduction at node i at time t. This provides typical natural gas load scenario data for node i. Let F be the peak natural gas load at node i. i,t For mass flow rate M i,t The gas flow rate corresponding to natural gas.

[0158] Example 3

[0159] Based on the same inventive concept, this invention also provides a computer device, which includes a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to implement corresponding method flows or corresponding functions, thereby realizing the steps of the distributed optimized operation method of an integrated electrical energy system in the above embodiments.

[0160] Example 4

[0161] Based on the same inventive concept, this invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the distributed optimized operation method for an integrated electrical energy system described in the above embodiments.

[0162] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0163] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0164] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0165] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0166] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A distributed optimized operation method for an integrated electrical energy system, characterized in that, The method includes: Determine the objective function for the distributed optimal operation of the integrated electrical energy system based on its economic and environmental costs; The objective function of the distributed optimization operation of the electrical integrated energy system is solved using the alternating direction multiplier method, and the optimization results are obtained. Based on the optimization results, a distributed optimized operation scheme for the integrated electrical energy system is obtained; The integrated electrical energy system includes at least one of the following: power grid, natural gas grid, wind turbine, photovoltaic power station, energy storage device, P2G equipment, gas turbine, substation, and gas distribution station. The optimization results include at least one of the following: active power of substation, active power of gas turbine, active power generated by wind turbine, active power generated by photovoltaic power station, charging and discharging power of energy storage device, active power transmitted by power grid line, active power consumed by P2G equipment, active power load, and natural gas pipeline inventory.

2. The method as described in claim 1, characterized in that, The economic costs of the aforementioned integrated electrical energy system are as follows: In the above formula, f eco For the economic cost of an integrated electrical energy system, The economic cost of the power network for an integrated electrical energy system. The economic cost of the natural gas network for an integrated electrical energy system.

3. The method as described in claim 2, characterized in that, The economic cost of the power network for the aforementioned integrated electrical energy system is as follows: The economic cost of the natural gas network in the aforementioned integrated electrical energy system is as follows: In the above formula, These are the unit electricity price and unit gas price at time t, respectively. These represent the unit electricity load reduction cost, unit wind power output reduction cost, unit solar power output reduction cost, and unit gas load reduction cost at time t, respectively, Ω. PN Ω is the set of nodes in a power network. GN For a set of natural gas network nodes, The unit operation and maintenance costs at time t are: substation, wind turbine, photovoltaic unit, energy storage equipment, P2G equipment, and gas turbine. Let be the active power outputs of the substation, gas turbine, wind turbine, and photovoltaic power station at node i at time t. Let be the active power consumed by the P2G device at node i at time t. Let be the discharge and charge power of the energy storage device at node i at time t, respectively. Let be the load at node i, the power reduction of the wind turbine, and the photovoltaic power station at time t, and T be the total time of the optimization period. Let be the natural gas flow rate consumed by the substation at node m at time t. Reduce the natural gas flow at node m.

4. The method as described in claim 3, characterized in that, The environmental costs of the aforementioned integrated electrical energy system are as follows: f env =C CET +C GCT In the above formula, f env For the environmental cost of an integrated electrical energy system, C CET For carbon trading costs, C GCT Costs associated with green certificate transactions.

5. The method as described in claim 4, characterized in that, The carbon trading costs are as follows: In the above formula, γ is the base price for carbon trading, and E r E represents the actual carbon emissions under the carbon-green certificate joint trading mechanism. d Let λ represent the total amount of carbon emission trading quotas, λ represent the purchase range of tiered carbon trading, and k represent the growth rate of the tiered carbon trading price.

6. The method as described in claim 5, characterized in that, The actual carbon emissions under the carbon-green certificate joint trading mechanism are as follows: The total amount of carbon emission trading quotas is as follows: In the above formula, Ω sub Ω gt Ω wt Ω pv Ω p2g These are collections of substations, gas turbines, wind turbines, photovoltaic power plants, and P2G equipment, respectively. g s gt s wt s pv These represent the carbon emissions per unit of active power output for thermal power units, gas turbines, wind turbines, and photovoltaic power plants, respectively. p2g δ represents the mass of CO2 utilized when a P2G device converts a unit of electrical energy into natural gas. g δ gt δ wt δ pv These represent the carbon emission trading quotas for thermal power units, gas turbines, wind turbines, and photovoltaic power plants per unit of active power output, δ E Carbon emissions offset by redundant green certificates.

7. The method as described in claim 6, characterized in that, The transaction costs for the green certificate are as follows: In the above formula, ξ is the unit green certificate trading price, ω is the system green certificate quota ratio, and Ω is the green certificate trading price. PL For the set of power grid load nodes, Let B be the electrical load power of node i at time t. o This refers to the number of green certificates issued to renewable energy power generation companies.

8. The method as described in claim 7, characterized in that, The mathematical model corresponding to the natural gas network is as follows: M=ρωA In the above formula, ρ is the gas density, M is the gas mass flow rate, t represents time t, A is the cross-sectional area of ​​the pipe, and x is the pipe length. Let λ be the average gas flow rate, λ be the purchase range for tiered carbon trading, and d be the pipe diameter.

9. The method as described in claim 7, characterized in that, The mathematical model corresponding to the natural gas network is as follows: In the above formula, A ij Let M be the cross-sectional area of ​​the gas pipeline ij. i,t M j,t M represents the mass flow rate of natural gas at the beginning and end of the gas pipeline ij at time t, respectively. i,t+1 M j,t+1 p represents the mass flow rate of natural gas at the beginning and end of the gas transmission pipeline ij at time t+1. i,t p j,t p represents the gas pressure at the beginning and end of the gas pipeline ij at time t, respectively. i,t+1 p j,t+1 ρ represents the gas pressure at the beginning and end of the gas pipeline ij at time t+1. i,t ρ j,t ρ represents the gas density at the beginning and end of the gas pipeline ij at time t. i,t+1 ρ j,t+1 Let be the gas densities at the beginning and end of the gas pipeline ij at time t+1, respectively. Let d be the length of the gas pipeline ij. ij Let be the diameter of the gas pipeline ij. Let denoted as the average flow rate of natural gas in the gas pipeline ij, and λ be the purchase range for the tiered carbon trading scheme.

10. The method as described in claim 9, characterized in that, The mathematical model corresponding to the natural gas network includes the following constraint model: M i,t =F i,t r i,t In the above formula, Let each be a set of gas pipelines in a natural gas network, with node i at the beginning and node i at the end. Let represent the gas purchase volume of the gas distribution station at node i at time t. Let be the mass flow rate of natural gas produced by the P2G device at node i at time t. Let be the natural gas load of node i at time t. Let be the mass flow rate of natural gas consumed by the gas turbine at node i at time t. Let be the mass flow rates of natural gas at the beginning and end of the gas transmission pipeline ij at time t, respectively. Let p be the mass flow rate of natural gas at the end of the gas pipeline ki at time t. i,t Let be the gas pressure at node i at time t. Let be the gas pressure at the beginning of the gas pipeline ij at time t. Let ki be the gas pressure at the end of the gas pipeline at time t. These are the lower and upper pressure limits for node i, respectively. These are the lower and upper limits of the natural gas mass flow rate at the inlet of the gas transmission pipeline ij, respectively. These are the lower and upper limits of the natural gas mass flow rate at the ij terminal of the gas transmission pipeline, respectively. Let represent the natural gas reduction at node i at time t. This provides typical natural gas load scenario data for node i. Let F be the peak natural gas load at node i. i,t For mass flow rate M i,t The gas flow rate corresponding to natural gas.

11. An apparatus based on the distributed optimized operation method of an integrated electrical energy system according to any one of claims 1-10, characterized in that, The device includes: The first analysis module is used to determine the objective function for the distributed optimal operation of the integrated electrical energy system based on the economic and environmental costs of the integrated electrical energy system. The second analysis module is used to solve the distributed optimization operation objective function of the electrical integrated energy system using the alternating direction multiplier method, and obtain the optimization results; The third analysis module is used to obtain a distributed optimized operation scheme for the integrated electrical energy system based on the optimization results. The integrated electrical energy system includes at least one of the following: power grid, natural gas grid, wind turbine, photovoltaic power station, energy storage device, P2G equipment, gas turbine, substation, and gas distribution station. The optimization results include at least one of the following: active power of substation, active power of gas turbine, active power generated by wind turbine, active power generated by photovoltaic power station, charging and discharging power of energy storage device, active power transmitted by power grid line, active power consumed by P2G equipment, active power load, and natural gas pipeline inventory.

12. A computer device, characterized in that, include: One or more processors; The processor is used to execute one or more programs; When the one or more programs are executed by the one or more processors, the distributed optimized operation method of the integrated electrical energy system as described in any one of claims 1 to 10 is implemented.

13. A computer-readable storage medium, characterized in that, It contains a computer program, which, when executed, implements the distributed optimized operation method of the integrated electrical energy system as described in any one of claims 1 to 10.

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