Day-ahead dispatching method and related equipment for offshore oil and gas fields connected to wind power

Abstract

The present invention provides a method for day-ahead scheduling of offshore oil and gas fields connected to wind power and related equipment, the method comprising: obtaining the operating parameters of each device in the power network, natural gas network and crude oil network of the offshore oil and gas field system; solving the target optimization function based on the operating parameters and preset constraints to obtain the day-ahead scheduling strategy of the offshore oil and gas field system within the target scheduling period, the constraints are the operating constraints for the equipment in the offshore oil and gas field system; controlling the operation of each device of the offshore oil and gas field system within the target scheduling period based on the day-ahead scheduling strategy; the optimization target of the target optimization function is to minimize the operating cost within the target scheduling period, and the operating cost within the target scheduling period includes the natural gas cost, fuel cost, carbon dioxide emission cost, wind power purchase cost, unit startup cost and wind abandonment cost within the target scheduling period. The present invention can realize the day-ahead scheduling of offshore oil and gas fields after access to wind power.

Description

Technical Field

[0001] The present invention relates to the field of new energy technology, and in particular to a day-ahead dispatching method for offshore oil and gas fields connected to wind power and related equipment. Background Art

[0002] As energy demand continues to grow, offshore oil and gas, as an important source of energy supply, plays an increasingly important role. Due to the long distance from the shore, traditional offshore oil and gas fields that adopt an isolated operation mode rely on traditional fossil energy for energy supply. Although traditional fossil energy has high power supply reliability, it has problems such as low power generation efficiency, high energy cost, and environmental pollution.

[0003] Offshore wind energy resources and oil and gas resources are abundant. Offshore wind resources and offshore oil and gas fields have a good match in space and resources. The connection of offshore oil and gas fields to offshore wind power can reduce energy costs and reduce environmental pollution. After the daily production plan of traditional offshore oil and gas fields is formulated, it usually does not change in a short period of time, and it is only powered by turbine generator sets that consume self-produced oil and gas, and the source-load relationship is basically stable. However, offshore wind power has natural uncertainty. After offshore wind power is connected to the grid, the uncertainty of the originally stable source-load relationship will increase significantly, making the coupling between the power grid, gas grid and oil grid closer. The traditional analysis method based on a single power network is no longer applicable to the offshore oil and gas field energy system with strong coupling of electricity, gas and oil. It is urgent to seek a coordinated and optimized scheduling method that takes into account the connection of wind power from the perspective of the integrated energy system of electricity, gas and oil. Summary of the invention

[0004] The present invention provides a method for day-ahead scheduling of offshore oil and gas fields connected to wind power and related equipment, so as to solve the defect that the optimization scheduling method based on a single power network in the prior art is not suitable for the offshore oil and gas field system after the wind power is connected, and realize the optimization scheduling suitable for the offshore oil and gas field after the wind power is connected.

[0005] The present invention provides a method for day-ahead scheduling of offshore oil and gas fields connected to wind power, comprising:

[0006] Obtaining operating parameters of various devices in the power network, natural gas network and crude oil network of the offshore oil and gas field system, wherein the power network includes turbine generators and wind turbine generators;

[0007] Based on the operating parameters and preset constraints, solving the target optimization function to obtain the day-ahead scheduling strategy of the offshore oil and gas field system within the target scheduling period, wherein the constraints are operating constraints for equipment in the offshore oil and gas field system;

[0008] Controlling the operation of each device of the offshore oil and gas field system within the target scheduling period based on the day-ahead scheduling strategy;

[0009] Among them, the optimization objective of the target optimization function is to minimize the operating cost within the target scheduling period, and the operating cost within the target scheduling period includes the natural gas cost, fuel cost, carbon dioxide emission cost, wind power purchase cost, unit startup cost and wind abandonment cost within the target scheduling period.

[0010] According to a method for day-ahead scheduling of offshore oil and gas fields connected to wind power provided by the present invention, the target scheduling cycle includes multiple scheduling periods, and the calculation formula of the unit startup cost is:

[0011]

[0012]

[0013]

[0014] Among them, C on is the startup cost of the unit, Ω SP ={1,2,…,N} represents the set of N scheduling periods included in the target scheduling period, sp∈Ω SP ;Ω GT and Ω DT are the sets of gas turbine generators and oil turbine generators respectively, gt∈Ω GT , dt∈Ω DT , μ gt,sp represents the start and stop status of the gas turbine generator in the sp scheduling period, μ dt,sp represents the start and stop status of the fuel turbine generator in the sp scheduling period, c on,gt and c on,dt They represent the cost of starting a gas turbine generator and a fuel turbine generator, respectively, and C on,gt,sp and C on,dt,sp They respectively represent the startup costs of the gas turbine generator and the oil turbine generator in the sp-th scheduling period.

[0015] According to a method for day-ahead scheduling of offshore oil and gas fields connected to wind power provided by the present invention,

[0016] The calculation formula for the wind abandonment cost is:

[0017]

[0018] Among them, C CW is the wind curtailment cost, c CW is the unit cost of wind curtailment, T represents the time step of a single dispatch period, Ω wt is the collection of offshore wind power, wt∈Ω wt , P F,wt,sp The purchased power of wind power in the sp dispatch period, Pwt,sp Represents the output active power of the wind turbine in the sp-th scheduling period.

[0019] According to a method for day-ahead scheduling of offshore oil and gas fields connected to wind power provided by the present invention, the constraint condition includes a first constraint condition, which is used to constrain the ratio of the real-time output to the maximum output of all turned-on turbine generator sets to be the same, and the first constraint condition is:

[0020]

[0021] Where δ is the load factor of the generator set, P i represents the real-time output of the i-th turbine generator set, represents the maximum output constraint of the i-th turbine generator set, and n is the total number of all turbine generator sets running online.

[0022] According to a method for day-ahead scheduling of offshore oil and gas fields connected to wind power provided by the present invention, the constraint condition includes a second constraint condition, and the second constraint condition is used to constrain the load level of the turbine generator set, and the second constraint condition is:

[0023]

[0024]

[0025]

[0026]

[0027]

[0028]

[0029] Among them, P gt,sp and P dt,sp are the active powers of the gas turbine generator and the oil turbine generator in the sp-th dispatching period, P mid,gt and P mid,dt are the minimum output active power of the gas turbine generator and the oil turbine generator in the recovery period, N L,gt and N L,dt Respectively represent the maximum number of scheduling periods during which the gas turbine generator and the oil turbine generator can continuously operate during the low load period; N C,gt and N C,dt They respectively represent the minimum number of scheduling periods during which the gas turbine generator and the oil turbine generator need to operate during the recovery period; sp0 represents any scheduling period within the target scheduling cycle.

[0030] According to a method for day-ahead scheduling of offshore oil and gas fields connected to wind power provided by the present invention, the constraint condition includes a third constraint condition, and the third constraint condition is used to constrain the hot standby power of the turbine generator set to meet the requirement that no load shedding occurs when the generator set fails and the net load fluctuates due to offshore wind power; the third constraint condition is:

[0031]

[0032] Among them, P N,gt and P N,dt are the rated powers of the gas turbine generator and the oil turbine generator in the sp-th dispatching period respectively; P pl,sp and P N,pl are the active power and rated power of the electric load in the sp-th dispatching period respectively; Ω PL is the set of electrical loads, pl∈Ω PL ; α indicates that the active power when the load is started is α times the rated power; β is the hot standby ratio that needs to be reserved for the offshore oil and gas field system during normal operation.

[0033] The present invention also provides a day-ahead dispatching device for offshore oil and gas fields connected to wind power, comprising:

[0034] A parameter acquisition module, used to acquire the operating parameters of various devices in the power network, natural gas network and crude oil network of the offshore oil and gas field system, wherein the power network includes turbine generators and wind turbine generators;

[0035] An optimization module, used to solve a target optimization function based on the operating parameters and preset constraints to obtain a day-ahead scheduling strategy for the offshore oil and gas field system within a target scheduling period, wherein the constraints are operating constraints for equipment in the offshore oil and gas field system;

[0036] A scheduling module, used for controlling the operation of each device of the offshore oil and gas field system within the target scheduling period based on the day-ahead scheduling strategy;

[0037] Among them, the optimization objective of the target optimization function is to minimize the operating cost within the target scheduling period, and the operating cost within the target scheduling period includes the natural gas cost, fuel cost, carbon dioxide emission cost, wind power purchase cost, unit startup cost and wind abandonment cost within the target scheduling period.

[0038] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a method for day-ahead scheduling of offshore oil and gas fields connected to wind power as described in any one of the above is implemented.

[0039] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for day-ahead scheduling of offshore oil and gas fields connected to wind power as described in any one of the above is implemented.

[0040] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method for day-ahead scheduling of offshore oil and gas fields connected to wind power as described in any one of the above is implemented.

[0041] The method for day-ahead scheduling of offshore oil and gas fields connected to wind power and related equipment provided by the present invention obtains the operating parameters of each device of the offshore oil and gas field system connected to turbine generators and wind turbine generators, and solves the target optimization function based on the operating parameters and the operating constraints of the equipment to obtain the scheduling strategy within the target scheduling period. The target of the target optimization function is the operating cost within the target scheduling period. The operating cost takes into account the wind power purchase cost, unit startup cost and wind abandonment cost, thereby realizing the day-ahead scheduling of offshore oil and gas fields after connecting to wind power. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0043] Figure 1 It is a flow chart of a method for day-ahead scheduling of offshore oil and gas fields connected to wind power provided by the present invention;

[0044] Figure 2 It is a schematic diagram of a power network in a method for day-ahead dispatching of offshore oil and gas fields connected to wind power provided by the present invention;

[0045] Figure 3 It is a schematic diagram of the relationship between the power generation efficiency and fuel consumption rate of the turbine generator set and the load rate in the day-ahead scheduling method for offshore oil and gas fields connected to wind power provided by the present invention;

[0046] Figure 4 It is a schematic diagram of a scheduling model in the day-ahead scheduling method for offshore oil and gas fields connected to wind power provided by the present invention;

[0047] Figure 5 It is a structural schematic diagram of a verification example of a method for day-ahead scheduling of offshore oil and gas fields connected to wind power provided by the present invention;

[0048] Figure 6 It is a day-ahead forecast curve of offshore wind power and power load in a verification example of a day-ahead dispatching method for offshore oil and gas fields connected to wind power provided by the present invention;

[0049] Figure 7 It is a schematic diagram of the proportion of power generation and cost of different energy sources in three scheduling strategies in the verification example of the day-ahead scheduling method for offshore oil and gas fields connected to wind power provided by the present invention;

[0050] Figure 8 It is the optimization result of turbine generator and wind power based on the scheduling strategy provided by the present invention in the verification example of the day-ahead scheduling method of offshore oil and gas fields connected to wind power provided by the present invention;

[0051] Fig. 9 It is a schematic diagram of the changes in wind power consumption and load rate in different scheduling periods in the verification calculation example of the day-ahead scheduling method for offshore oil and gas fields connected to wind power provided by the present invention;

[0052] Fig.10 It is a schematic diagram of the active power changes of the gas compressor and the oil pump in different scheduling periods in the verification calculation example of the day-ahead scheduling method for offshore oil and gas fields connected to wind power provided by the present invention;

[0053] Fig.11 It is a schematic diagram of the changes in the delivery volume of natural gas and crude oil in different scheduling periods in the verification example of the day-ahead scheduling method for offshore oil and gas fields connected to wind power provided by the present invention;

[0054] Fig.12 It is a structural schematic diagram of a day-ahead dispatching device for offshore oil and gas fields connected to wind power provided by the present invention;

[0055] Fig.13 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings 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.

[0057] Combine the following Figure 1-Figure 11 The present invention describes the method for day-ahead scheduling of offshore oil and gas fields connected to wind power. Figure 1 As shown, the method for day-ahead scheduling of offshore oil and gas fields connected to wind power provided by the present invention comprises the following steps:

[0058] S110, obtaining operating parameters of various devices in the power network, natural gas network, and crude oil network of the offshore oil and gas field system, wherein the power network includes turbine generators and wind turbine generators;

[0059] S120, solving the target optimization function based on the operating parameters and preset constraints to obtain the day-ahead scheduling strategy of the offshore oil and gas field system within the target scheduling period, where the constraints are operating constraints for equipment in the offshore oil and gas field system;

[0060] S130, controlling the operation of each device of the offshore oil and gas field system within the target scheduling period based on the day-ahead scheduling strategy;

[0061] The optimization objective of the target optimization function is to minimize the operating cost within the target scheduling cycle. The operating cost within the target scheduling cycle includes the natural gas cost, fuel cost, carbon dioxide emission cost, wind power purchase cost, unit startup cost and wind curtailment cost within the target scheduling cycle.

[0062] The offshore oil and gas field system is a production, gathering and transportation system that integrates offshore oil and gas production, gathering and transportation. In order to improve the efficiency of oil and gas production and transportation and reduce operating costs, offshore oil and gas fields are usually composed of multiple offshore oil and gas platforms interconnected by submarine cables and submarine oil and gas pipelines to form a multi-platform interconnected offshore oil and gas platform group. The offshore oil and gas field power grid ensures the normal production and operation of the offshore oil and gas field system, and mainly includes gas / oil turbine generator sets, gas compressors, oil pumps, submersible pumps, electric heating, cranes and other equipment. Under the dual carbon goals, in order to improve the cleanliness level of offshore oil and gas fields, offshore wind power is integrated into traditional offshore oil and gas field systems. Such as Figure 2 As shown in the figure, offshore wind power and gas / oil turbine generator sets together form an offshore integrated energy system (OIES) powered by wind power-turbine synergy. In OIES, natural gas and crude oil and electricity form a coupled network of material and energy flows with electricity-gas-oil as the main body through gas / oil generators and gas compressors.

[0063] The method provided by the present invention is to construct an optimization model, such as Figure 4 As shown in FIG. 1 , the input of the optimization model is the operating parameters of each device in the offshore oil and gas field system. Specifically, the operating parameters include energy demand data, energy cost data, system parameters, and wind power curves. Among them, system parameters refer to the fixed parameters of each device in the system (such as the rated power and rated capacity of the equipment). The optimization model includes constraints and target optimization functions. The target optimization function is solved under the premise of satisfying the constraints to obtain the output of the optimization model. The output is a scheduling strategy, which includes the operation plan, daily operating cost, daily oil and gas transportation volume, and daily carbon emissions of the turbine generator set in the offshore oil and gas field system. According to the day-ahead scheduling strategy, the operation of each device in the offshore oil and gas field system (such as turbine generator sets, gas pipelines, oil pipelines, etc.) is controlled within the target scheduling period.

[0064] Offshore oil and gas fields are typical energy systems in which power grids, gas grids, and oil grids are coupled with each other, and their economy and safety influence each other. Traditional offshore oil and gas fields only use turbine generators that consume self-produced oil and gas to supply power, making the source-load relationship basically stable. However, offshore wind power has natural uncertainty. After offshore wind power is connected to the grid, the uncertainty of the originally stable source-load relationship will increase significantly, making the coupling between the power grid, gas grid, and oil grid even tighter. Traditional analysis methods based on a single power network are no longer applicable to offshore oil and gas field energy systems with strong coupling of electricity, gas, and oil. In the method provided by the present invention, based on the coupling relationship between energy production and consumption of offshore oil and gas fields, a coupling system model of an offshore oil and gas field system with electricity, gas, and oil as the main body is proposed. Specifically, the network model composed of the power grid, natural gas grid, and crude oil grid in the offshore gas coupling system model can be expressed as:

[0065] f ele (v,θ,P,Q)=0;

[0066] f gas (M gas )=0;

[0067] f oil (M oil )=0;

[0068] f e-g (P,Q,M gas )=0;

[0069] f e-o (P,Q,M oil )=0;

[0070] Among them, f ele 、f gas and f oil Represent the models of power grid, natural gas grid and crude oil grid respectively; f e-g A coupled model of components representing the electricity network and the gas network, such as gas turbine generators and gas compressors; e-o It is a coupling model of the components of the power network and the crude oil network, such as the oil turbine generator and the oil pump. In the power network, v and θ represent the vector of the square of the bus voltage and the vector of the phase angle respectively; P and Q represent the vector of active power and the vector of reactive power respectively. In the natural gas network, M gas A vector representing the natural gas flow rate. In the crude oil network, M oil A vector representing the crude oil flow rate.

[0071] Turbine generators in offshore oil and gas field systems can be divided into two types based on the fuel used, namely, gas-fired turbine generators (GT) using natural gas as fuel and diesel-fired turbine generators (DT) using crude oil as fuel. In the present invention, when simply referred to as "turbine generator set", it refers to gas turbine generator sets and diesel turbine generator sets.

[0072] In order to ensure the safe production of offshore oil and gas, offshore oil and gas field systems are usually equipped with turbine generator sets of different manufacturers and different capacities based on the principle of multiple backups. These generator sets have the advantages of fast start and stop and fast power response. In order to improve the consumption level of offshore wind power, the start and stop sequence of the generator sets can be reasonably adjusted according to the predicted results of offshore wind power output during scheduling. In order to improve the scheduling effect of offshore oil and gas field systems, in the method provided by the present invention, the scheduling cycle is divided into multiple scheduling periods, and the obtained day-ahead scheduling strategy includes the equipment status information in each scheduling period within the target scheduling cycle, and the corresponding equipment operation is controlled in the corresponding scheduling period according to the equipment status information.

[0073] The turbine generator operation model includes various constraints on the operation of the turbine generator, which are explained below.

[0074] In the offshore oil and gas field system, the turbine generator set has a small capacity, low mechanical inertia, and priority is given to anti-disturbance performance. Considering the safety and economy of the offshore oil and gas field power grid operation, two turbine generator set control strategies can be adopted, namely, equal ratio mode and dispatch mode. Assuming that there are n turbine generator sets in operation in the system, in the equal ratio mode, the ratio of the real-time output to the maximum output of all online turbine generators is the same, which can be expressed as:

[0075]

[0076] Where δ is the load factor of the generator set, P i and They represent the real-time output and maximum output constraints of the i-th turbine generator set respectively. In the equal ratio mode, all online generator sets must output active power at the same load rate.

[0077] If the equal ratio mode is adopted, all turbine generator sets will participate in the regulation, and the power fluctuation caused by the disturbance can be automatically distributed to each generator set in equal ratio, which is conducive to maintaining the stability of the system. If the scheduling mode is adopted, some generator sets are set to a fixed power output, and other units are operated in an equal ratio mode. In the scheduling mode, only some units can participate in the regulation, and the anti-power disturbance performance is relatively poor, but the operating economy is relatively good. Different from the energy management mode of offshore oil and gas fields, after offshore wind power is connected to the offshore oil and gas fields, it is also necessary to smooth the uncertain offshore wind power to ensure the safety of system operation. Therefore, in the method provided by the present invention, the equal ratio mode is preferentially selected, that is, the first constraint condition needs to be met when solving, and the first constraint condition is that the load rate of all turned-on turbine generator sets is the same.

[0078] Furthermore, each turbine generator set has an optimal operating power range designed, within which the turbine generator set can operate continuously for a long time. However, after offshore wind power is connected to the grid, if the turbine generator set has been operating within the optimal operating power range, the ability to absorb offshore wind power will be greatly reduced. The turbine generator set can also operate at a light load, but if the turbine generator set operates at a light load level for a long time, it will cause the temperature and pressure of the combustion chamber to decrease, and deposits such as carbon deposits and glaze deposits to appear. A large amount of deposits will cause the power generation efficiency to decrease, and the equipment will wear out faster, resulting in an increased probability of unexpected failure or shutdown. Therefore, according to the OIES load and offshore wind power output forecast results, a scientific turbine generator set load level management strategy is formulated, which can not only ensure the performance of the turbine generator set, but also achieve the optimal absorption of offshore wind power. Based on this, in the method provided by the present invention, a second constraint condition is set, and the second constraint condition is used to constrain the load level of the turbine generator set. The second constraint condition is:

[0079]

[0080]

[0081]

[0082]

[0083]

[0084]

[0085] Among them, P gt,sp and P dt,sp are the active powers of the gas turbine generator and the oil turbine generator in the sp-th dispatching period, μ gt,sp and μ dt,sp are variables reflecting the start and stop status of the gas turbine generator and the oil turbine generator, respectively.mid,gt and P mid,dt are the minimum output active power of the gas turbine generator and the oil turbine generator in the recovery period, N L,gt and N L,dt Respectively represent the maximum number of scheduling periods during which the gas turbine generator and the oil turbine generator can continuously operate during the low load period; N C,gt and N C,dt They respectively represent the minimum number of scheduling periods during which the gas turbine generator and the oil turbine generator need to operate during the recovery period; sp0 represents any scheduling period within the target scheduling cycle.

[0086] There is a high proportion of large-capacity induction motors in OIES, which usually consume 1.5 to 2 times the rated power of active power when starting. Therefore, OIES must be able to meet the active power requirements of such high-power loads when starting. In addition, since offshore oil and gas fields do not allow load shedding events caused by generator n-1 failure (n is the total number of operating generators) and offshore wind power output forecast errors, the turbine generator set must also reserve sufficient hot standby power to meet the net load (active power generated by the power source - active power demand of the load) fluctuations caused by generator n-1 failure and offshore wind power uncertainty. The turbine generator set must meet the third constraint, which is the hot standby constraint, which is used to constrain the standby power of the turbine generator set to meet the requirement that no load shedding events occur when the generator set has n-1 failures and net load fluctuations caused by offshore wind power. The third constraint is:

[0087]

[0088] Among them, P N,gt and P N,dt are the rated powers of the gas turbine generator and the oil turbine generator in the sp-th dispatching period respectively; P pl,sp and P N,pl are the active power and rated power of the electric load in the sp-th dispatching period respectively; Ω PL is the set of electrical loads, pl∈Ω PL ; α indicates that the active power when the load is started is α times the rated power; β is the hot standby ratio that needs to be reserved for the offshore oil and gas field system during normal operation.

[0089] In addition to the above three constraints, the operation of the turbine generator set should meet the unit start-up and shutdown and stable operation boundary constraints, which are as follows:

[0090]

[0091]

[0092]

[0093]

[0094]

[0095]

[0096]

[0097]

[0098] Among them, P gt,sp and P dt,sp are the active powers of the gas turbine generator and the oil turbine generator in the sp-th dispatching period respectively; Q gt,sp and Q dt,sp are the reactive power of the gas turbine generator and the oil turbine generator in the sp-th dispatching period respectively; λ gt , and λ dt are the power factor boundaries of gas turbine generator and oil turbine generator respectively; S N,gt and S N,dt are the rated capacities of gas turbine generator and oil turbine generator respectively; μ gt,sp and μ dt,sp are variables reflecting the start and stop status of the gas turbine generator and the oil turbine generator respectively; and A are the maximum and minimum constraints for any variable A.

[0099] The operation of the turbine generator is also subject to the active power ratio distribution constraint, which can be expressed as:

[0100]

[0101]

[0102]

[0103]

[0104] Among them, δ sp is the load rate of each turbine generator set in the sp-th scheduling period, and δ represent the maximum and minimum values ​​of the turbine generator load rate, respectively. and They respectively represent the maximum active power of the gas turbine generator and the oil turbine generator.

[0105] In addition, the relationship between the power generation efficiency and fuel consumption rate of the turbine generator set and the load rate is as follows: Figure 3 As shown in the figure, the power generation efficiency of the turbine generator set has a nonlinear relationship with the load level. The lower the load level, the lower the power generation efficiency. The fuel consumption rate of the turbine generator set has an integral correlation with the load level, which can be approximated by a linear function. The turbine generator set needs to meet the fuel consumption constraint, which can be expressed by the formula:

[0106]

[0107]

[0108] Among them, a gt 、b gt is the coefficient of the fuel-power output characteristic equation of the gas turbine generator, a dt and b dt is the coefficient of the fuel-power output characteristic equation of the fuel turbine generator, a gt 、b gt 、a dt and b dt It can be obtained from experimental data.

[0109] The wind turbine operation model includes the power constraints of wind turbines in offshore oil and gas field systems. At present, commonly used offshore wind turbines can operate within the leading (absorbing reactive power) or lagging (outputting reactive power) power factor range. A larger power factor operating range means that the wind turbine has better reactive power regulation capabilities. The power constraints of offshore wind turbines can be expressed by the formula:

[0110]

[0111]

[0112]

[0113]

[0114] Where wt∈Ω WT , b WT represents the set of wind turbines in the offshore oil and gas field system; P wt,sp represents the output active power of the wind turbine in the sp-th dispatching period; Q wt,sp represents the output reactive power of the wind turbine in the sp-th scheduling period; lag,wt ~λ lead,wt is the power factor range of the wind turbine, and P wtThey represent the maximum and minimum output active power of the wind turbine respectively. and Q wt They respectively represent the maximum and minimum values ​​of the output reactive power of the wind turbine.

[0115] The gas compressor is a key natural gas transmission equipment, which boosts the pressure of natural gas for long-distance transmission. The gas compressor can be divided into two types according to the type of prime mover: natural gas driven and electric driven. In the present invention, electric driven gas compressors are given priority. Their power consumption is regarded as power load, which is one of the key coupling elements of the gas grid and the power grid. In normal operation, the gas compressor must meet the power constraint and the stable operation area constraint, which can be specifically expressed by the formula:

[0116]

[0117]

[0118]

[0119] Among them, gc∈Ω GC ,Ω GC It is a collection of gas compressors in offshore oil and gas field systems; gc,sp and Q gc,sp are respectively the active power and reactive power of the gas compressor in the sp-th scheduling period; M gc,sp is the natural gas flow rate delivered by the gas compressor in the sp-th scheduling period; γ gc,sp B is the compression ratio of the gas compressor in the sp-th scheduling period; gc and Z gc is a constant; is the rated power factor of the gas compressor; S N,gc It is the rated capacity of the gas compressor prime mover.

[0120] The oil pump transports the crude oil produced by offshore oil and gas fields over long distances by boosting the pressure, such as to tankers, oil storage tanks, etc. During normal operation, the oil pump must meet the following constraints:

[0121]

[0122]

[0123]

[0124] Where op∈Ω OP ,Ω OP is a collection of oil pumps in the offshore oil and gas field system; op,sp and Q op,spare respectively the active power and reactive power of the oil pump in the sp-th scheduling period; η op is the mechanical power of the oil pump; M op,sp is the rate at which the oil pump delivers crude oil in the sp-th scheduling period; and are respectively the pressure at the inlet and outlet of the oil pump in the sp-th scheduling period; is the rated power factor of the oil pump during normal operation; S N,op is the rated power of the oil pump.

[0125] The active and reactive power flows of the power branch ab in the offshore oil and gas field system are expressed as:

[0126]

[0127]

[0128]

[0129]

[0130] Where a,b∈Ω BUS ,Ω BUS Represents the set of all buses in the power grid; ab∈Ω EBR ,Ω EBR represents the set of all branches of the power grid; P ab,sp and Q ab,sp represents the active power and reactive power of branch ab in the sp-th scheduling period; g ab and b ab are the conductance and susceptance of branch ab respectively; b 0,ab is the equivalent charging susceptance of branch ab; V a,sp and V b,sp represents the voltage amplitude across branch ab in the sp scheduling period, θ ab,sp represents the voltage phase difference between the two ends of branch ab in the sp scheduling period; S N,ab is the rated capacity of power branch ab.

[0131] The gas transmission network branches in the offshore oil and gas field system meet the following operating constraints:

[0132]

[0133] Among them, M mn and They represent the minimum and maximum limits of the natural gas flow rate in the gas pipeline of the offshore oil and gas field system, M mn,sp represents the natural gas flow rate of the gas transmission network branch in the sp-th scheduling period; mn∈ΩGBR ,Ω GBR It is a collection of gas transmission network branches.

[0134] The oil transmission network branches in the offshore oil and gas field system meet the following operation constraints:

[0135]

[0136] Among them, M pq and They represent the minimum and maximum limits of crude oil flow rate in the oil pipeline of the offshore oil and gas field system, M pq,sp represents the crude oil flow rate of the oil transmission network branch in the sp scheduling period; pq∈Ω OBR ,Ω OBR It is a collection of branches of the oil transportation network.

[0137] The optimization target of the target optimization function in the day-ahead scheduling method for offshore oil and gas fields connected to wind power provided by the present invention is to minimize the operating cost within the target scheduling period. The operating cost within the target scheduling period includes the natural gas cost, fuel cost, carbon dioxide emission cost, wind power purchase cost, unit startup cost and wind abandonment cost within the target scheduling period.

[0138] The objective optimization function can be expressed as:

[0139] obj=minC gas +C oil +C CO2 +C WT +C on +C CW ;

[0140] Among them, C gas , C oil , C WT , C on and C CW They represent the natural gas cost, fuel cost, carbon dioxide emission cost, wind power purchase cost, unit startup cost and wind curtailment cost within the target dispatching period. The specific calculation method of each cost is explained below:

[0141]

[0142]

[0143] C gas =c gas M gas ;

[0144] C oil =c oil M oil ;

[0145]

[0146]

[0147]

[0148]

[0149]

[0150]

[0151] Where T represents the time step of a single scheduling period; M gas and M oil Respectively represent the natural gas consumption and crude oil consumption in a scheduling cycle; Ω SP ={1,2,…,N} represents a set of N scheduling periods, sp∈Ω SP ;Ω GT and Ω DT are the sets of gas turbine generators (GT) and fuel turbine generators (DT), gt∈Ω GT , dt∈Ω DT , μ gt,sp represents the start and stop status of the gas turbine generator in the sp scheduling period, μ dt,sp Indicates the start and stop status of the fuel turbine generator in the sp-th scheduling period; M gt,sp and M dt,sp are the natural gas and crude oil consumption of GT and DT in the sp scheduling period respectively; c gas represents the unit cost of natural gas; c oil represents the unit cost of crude oil; represents the unit cost of carbon dioxide emissions; c WT It represents the unit cost of purchasing wind power; and are the carbon dioxide emissions per unit volume of natural gas and crude oil respectively; Ω wt is the collection of offshore wind power, wt∈Ω wt , c on,gt and c on,dt They represent the cost of starting a gas turbine generator and a fuel turbine generator, respectively, and C on,gt,sp and C on,dt,sp are the startup costs of the gas turbine generator and the oil turbine generator in the sp-th scheduling period, respectively, and c CW is the unit cost of wind curtailment, Ω wt is the collection of offshore wind power, wt∈Ω wt , P F,wt,spThe predicted active power value of wind power in the sp scheduling period, P wt,sp Represents the output active power of the wind turbine in the sp-th scheduling period.

[0152] Through the method provided by the present invention, for any unit cost of offshore wind power, natural gas, crude oil and carbon dioxide, and offshore wind power scenario, compared with other scheduling strategies, the proposed scheduling strategy can always achieve the minimum total operation cost of day-ahead scheduling and the maximum offshore wind power consumption capacity. And the lower the unit cost of offshore wind power, the higher the cost of carbon dioxide emissions, and the greater the daily average wind power, the more obvious the economic advantages and wind power consumption advantages of the proposed scheduling strategy. Since natural gas has a greater price advantage than the unit cost of crude oil, and the gas turbine generator set configured in the existing offshore oil and gas fields has a high unit capacity, the gas turbine generator is the main peak-shaving power source to smooth the uncertainty of offshore wind power. When offshore wind energy resources are very abundant during the scheduling period, the offshore oil and gas fields will transport more natural gas and crude oil to the outside, and the receiving station must also reserve more storage or production capacity in advance to consume this part of natural gas and crude oil.

[0153] In order to verify the feasibility and superiority of the day-ahead dispatching method for offshore oil and gas fields connected to wind power provided by the present invention, a study is conducted using an offshore oil and gas field in the north as an example. Figure 5 As shown. The system contains four offshore oil and gas platforms, platform A1 and platform A2 form a production unit, and platform B1 and platform B2 form another production unit. The two production units are networked through a 15km submarine cable. The power grid of the system contains 6 busbars, among which busbar 5 and busbar 5' are regarded as one busbar because they are of the same voltage level and are very close to each other. The offshore oil and gas field is equipped with 9 turbine generator sets, including two gas turbine generator sets with a rated capacity of 5MW (G1~G2) and 7 fuel generator sets with a rated capacity of 1.2MW (G3~G9). A 5MW offshore wind turbine unit is connected to the offshore oil and gas field through the oil and gas platform A1. The offshore oil and gas field is equipped with a gas compressor (C1) with a rated power of 600kW and two oil pumps (P1~P2) with a rated power of 350kW to transport the produced oil and gas. The day-ahead forecast output curve of offshore wind power, except for the gas compressor and oil pump loads, the day-ahead forecast results of other power loads are as follows Figure 6 shown.

[0154] According to the day-ahead prediction results of the loads of offshore wind farms and offshore oil and gas fields, compare the traditional day-ahead scheduling strategy S1 considering the equal-ratio operation constraint and the scheduling strategy S2 considering the unit start-stop constraint with the strategy S3 generated by the method provided by the present invention. The proportions of natural gas power generation, crude oil power generation, and wind power purchase in the total power, the proportions of natural gas cost, crude oil cost, and wind power purchase cost in the total operating cost, and the cost per unit of electricity of natural gas, crude oil, and wind power are as Figure 7 shown.

[0155] It can be found from the figure that when the total operating cost of the three scheduling strategies is optimized, the cost per unit of electricity of offshore wind power is the lowest, the cost per unit of electricity of natural gas is much lower than that of crude oil, and the consumption of natural gas is the largest. This is because the unit cost of natural gas is relatively lower than that of crude oil, and natural gas is preferentially used for power generation. As the proportion of wind power purchase in the three scheduling strategies increases continuously (S1 < S2 < S3), the proportion of natural gas power generation cost gradually exceeds the proportion of natural gas power generation, while the proportion of crude oil power generation cost is always higher than the proportion of crude oil power generation. This shows that as the wind power utilization rate increases, the natural gas power generation decreases continuously, resulting in a decrease in the power generation efficiency of gas generators. Therefore, compared with fuel turbine generator sets, gas turbine generator sets have more economic advantages in co-operation with offshore wind power.

[0156] Based on the scheduling strategy generated by the method provided by the present invention, the obtained day-ahead scheduling results are as Figure 8 shown, the changes in the wind curtailment volume and the load rate of the turbine generator sets are as Fig. 9 shown, the relationship between the power changes of gas compressors and oil transfer pumps and the wind power purchase power is as Fig.10 shown, and taking the traditional offshore oil and gas field without offshore wind power grid connection as a reference, the changes in the natural gas and crude oil delivery volumes in different scheduling periods are as Fig.11 shown.

[0157] It can be seen from the results of the example verification that the method provided by the present invention, as the output of offshore wind power continues to change, OIES continuously adjusts the start and stop status and load level of the turbine generator set to maximize the absorption of offshore wind power. As the main unit, the gas turbine generator set has been in an open state to meet the peak-shaving demand caused by the uncertainty of offshore wind power. The fuel turbine generator set serves as a power supplement to the gas generator set to jointly maintain the power balance of the system. When the wind power is low, the turbine generator sets all operate at a high load rate level. As the wind power continues to increase, the turbine generator set continuously switches between low load rate levels and high load rate levels to maximize the absorption of offshore wind power and ensure the operating performance of the turbine generator set. As the wind power purchase power changes, the change in the active power demand of the oil pump is basically stable, and the change in the active power demand of the gas compressor is the same as the change trend of the wind power purchase power. The strategy generated by the method provided by the present invention will not only achieve the maximum absorption of offshore wind power, but will also have an impact on offshore oil and gas transportation. The natural gas and crude oil transportation volume in different scheduling periods will change with the changes in the absorption volume of offshore wind power, requiring natural gas and crude oil storage and transportation or producers to increase their storage and transportation or production capacity of natural gas and crude oil.

[0158] The following is a description of the day-ahead dispatching device for offshore oil and gas fields connected to wind power provided by the present invention. The day-ahead dispatching device for offshore oil and gas fields connected to wind power described below and the day-ahead dispatching method for offshore oil and gas fields connected to wind power described above can be referred to each other. Fig.12 As shown, the day-ahead dispatching device for offshore oil and gas fields connected to wind power provided by the present invention comprises:

[0159] The parameter acquisition module 1210 is used to acquire the operating parameters of each device in the power network, natural gas network and crude oil network of the offshore oil and gas field system, wherein the power network includes turbine generators and wind turbine generators;

[0160] The optimization module 1220 is used to solve the target optimization function based on the operating parameters and preset constraints to obtain the day-ahead scheduling strategy of the offshore oil and gas field system within the target scheduling period, wherein the constraints are operating constraints for the equipment in the offshore oil and gas field system;

[0161] A scheduling module 1230, configured to control the operation of each device of the offshore oil and gas field system within the target scheduling period based on the day-ahead scheduling strategy;

[0162] Among them, the optimization objective of the target optimization function is to minimize the operating cost within the target scheduling period, and the operating cost within the target scheduling period includes the natural gas cost, fuel cost, carbon dioxide emission cost, wind power purchase cost, unit startup cost and wind abandonment cost within the target scheduling period.

[0163] Fig.13 An example of a physical structure diagram of an electronic device is shown in FIG. Fig.13 As shown, the electronic device may include: a processor (processor) 1310, a communication interface (Communications Interface) 1320, a memory (memory) 1330 and a communication bus 1340, wherein the processor 1310, the communication interface 1320, and the memory 1330 communicate with each other through the communication bus 1340. The processor 1310 can call the logic instructions in the memory 1330 to execute the day-ahead scheduling method for offshore oil and gas fields connected to wind power, the method comprising: obtaining the operating parameters of each device in the power network, natural gas network and crude oil network of the offshore oil and gas field system, the power network including turbine generators and wind turbines; solving the target optimization function based on the operating parameters and preset constraints to obtain the day-ahead scheduling strategy of the offshore oil and gas field system within the target scheduling period, the constraints being the operating constraints for the equipment in the offshore oil and gas field system; controlling the operation of each device in the offshore oil and gas field system within the target scheduling period based on the day-ahead scheduling strategy; wherein the optimization target of the target optimization function is to minimize the operating cost within the target scheduling period, and the operating cost within the target scheduling period includes the natural gas cost, fuel cost, carbon dioxide emission cost, wind power purchase cost, unit startup cost and wind abandonment cost within the target scheduling period.

[0164] In addition, the logic instructions in the above-mentioned memory 1330 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including 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, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0165] On the other hand, the present invention also provides a computer program product, which includes a computer program, and the computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the day-ahead scheduling method for offshore oil and gas fields connected to wind power provided by the above methods, the method including: obtaining the operating parameters of each device in the power network, natural gas network and crude oil network of the offshore oil and gas field system, the power network including turbine generators and wind turbines; solving the target optimization function based on the operating parameters and preset constraints to obtain the day-ahead scheduling strategy of the offshore oil and gas field system within the target scheduling period, the constraints being the operating constraints for the equipment in the offshore oil and gas field system; controlling the operation of each device of the offshore oil and gas field system within the target scheduling period based on the day-ahead scheduling strategy; wherein the optimization target of the target optimization function is to minimize the operating cost within the target scheduling period, and the operating cost within the target scheduling period includes the natural gas cost, fuel cost, carbon dioxide emission cost, wind power purchase cost, unit startup cost and wind abandonment cost within the target scheduling period.

[0166] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the day-ahead scheduling method for offshore oil and gas fields connected to wind power provided by the above-mentioned methods, the method comprising: obtaining operating parameters of each device in the power network, natural gas network and crude oil network of the offshore oil and gas field system, the power network including turbine generators and wind turbines; solving a target optimization function based on the operating parameters and preset constraints to obtain a day-ahead scheduling strategy for the offshore oil and gas field system within a target scheduling period, the constraints being operating constraints for the equipment in the offshore oil and gas field system; controlling the operation of each device in the offshore oil and gas field system within the target scheduling period based on the day-ahead scheduling strategy; wherein the optimization target of the target optimization function is to minimize the operating cost within the target scheduling period, and the operating cost within the target scheduling period includes the natural gas cost, fuel cost, carbon dioxide emission cost, wind power purchase cost, unit startup cost and wind abandonment cost within the target scheduling period.

[0167] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0168] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0169] 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 make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for day-ahead scheduling of offshore oil and gas fields connected to wind power, characterized in that: include: Obtaining operating parameters of various devices in the power network, natural gas network and crude oil network of the offshore oil and gas field system, wherein the power network includes turbine generators and wind turbine generators; Based on the operating parameters and preset constraints, solving the target optimization function to obtain the day-ahead scheduling strategy of the offshore oil and gas field system within the target scheduling period, wherein the constraints are operating constraints for equipment in the offshore oil and gas field system; Controlling the operation of each device of the offshore oil and gas field system within the target scheduling period based on the day-ahead scheduling strategy; The optimization objective of the target optimization function is to minimize the operating cost within the target scheduling period, and the operating cost within the target scheduling period includes the natural gas cost, fuel cost, carbon dioxide emission cost, wind power purchase cost, unit startup cost and wind abandonment cost within the target scheduling period; The target scheduling cycle includes multiple scheduling periods, and the calculation formula of the unit startup cost is: Among them, C on is the startup cost of the unit, Ω SP ={1,2,…,N} represents the set of N scheduling periods included in the target scheduling period, sp∈Ω SP ;Ω GT and Ω DT are the sets of gas turbine generators and oil turbine generators respectively, gt∈Ω GT , dt∈Ω DT , μ gt,sp represents the start and stop status of the gas turbine generator in the sp scheduling period, μ dt,sp represents the start and stop status of the fuel turbine generator in the sp scheduling period, c on,gt and c on,dt They represent the cost of starting a gas turbine generator and a fuel turbine generator, respectively, and C on,gt,sp and C on,dt,sp They represent the startup costs of the gas turbine generator and the oil turbine generator in the sp-th scheduling period respectively; The constraint condition includes a first constraint condition, which is used to constrain the ratio of the real-time output to the maximum output of all turned-on turbine generator sets to be the same, and the first constraint condition is: Where δ is the load factor of the generator set, P i represents the real-time output of the i-th turbine generator set, represents the maximum output constraint of the i-th turbine generator set, and n is the total number of all turbine generator sets running online; The constraint condition includes a second constraint condition, which is used to constrain the load level of the turbine generator set. The second constraint condition is: Among them, P gt,sp and P dt,sp are the active powers of the gas turbine generator and the oil turbine generator in the sp-th dispatching period, P mid,gt and P mid,dt are the minimum output active power of the gas turbine generator and the oil turbine generator in the recovery period, N L,gt and N L,dt Respectively represent the maximum number of scheduling periods during which the gas turbine generator and the oil turbine generator can continuously operate during the low load period; N C,gt and N C,dt They respectively represent the minimum number of scheduling periods that the gas turbine generator and the oil turbine generator need to operate during the recovery period; sp0 represents any scheduling period within the target scheduling cycle; The constraint condition includes a third constraint condition, which is used to constrain the hot standby power of the turbine generator set to meet the requirement that no load shedding occurs when the generator set fails and the net load fluctuates due to offshore wind power; the third constraint condition is: Among them, P N,gt and P N,dt are the rated powers of the gas turbine generator and the oil turbine generator in the sp-th dispatching period respectively; P pl,sp and P N,pl are the active power and rated power of the electric load in the sp-th dispatching period respectively; Ω PL is the set of electrical loads, pl∈Ω PL ; α indicates that the active power when the load is started is α times the rated power; β is the hot standby ratio that needs to be reserved for the offshore oil and gas field system during normal operation.

2. The method for day-ahead scheduling of offshore oil and gas fields connected to wind power according to claim 1, characterized in that: The calculation formula for the wind abandonment cost is: Among them, C CW is the wind curtailment cost, c CW is the unit cost of wind curtailment, T represents the time step of a single dispatch period, Ω wt is the collection of offshore wind power, wt∈Ω wt , P F,wt,sp The predicted active power value of wind power in the sp scheduling period, P wt,sp Represents the output active power of the wind turbine in the sp-th scheduling period.

3. A day-ahead dispatching device for offshore oil and gas fields connected to wind power, characterized in that: include: A parameter acquisition module, used to acquire the operating parameters of various devices in the power network, natural gas network and crude oil network of the offshore oil and gas field system, wherein the power network includes turbine generators and wind turbine generators; An optimization module, used to solve the target optimization function based on the operating parameters and preset constraints to obtain a day-ahead scheduling strategy for the offshore oil and gas field system within a target scheduling period, wherein the constraints are operating constraints for equipment in the offshore oil and gas field system; A scheduling module, used for controlling the operation of each device of the offshore oil and gas field system within the target scheduling period based on the day-ahead scheduling strategy; The optimization objective of the target optimization function is to minimize the operating cost within the target scheduling period, and the operating cost within the target scheduling period includes the natural gas cost, fuel cost, carbon dioxide emission cost, wind power purchase cost, unit startup cost and wind abandonment cost within the target scheduling period; The target scheduling cycle includes multiple scheduling periods, and the calculation formula of the unit startup cost is: Among them, C on is the startup cost of the unit, Ω SP ={1,2,…,N} represents the set of N scheduling periods included in the target scheduling period, sp∈Ω SP ;Ω GT and Ω DT are the sets of gas turbine generators and oil turbine generators respectively, gt∈Ω GT , dt∈Ω DT , μ gt,sp represents the start and stop status of the gas turbine generator in the sp scheduling period, μ dt,sp represents the start and stop status of the fuel turbine generator in the sp scheduling period, c on,gt and c on,dt They represent the cost of starting a gas turbine generator and a fuel turbine generator, respectively, and C on,gt,sp and C on,dt,sp They represent the startup costs of the gas turbine generator and the oil turbine generator in the sp-th scheduling period respectively; The constraint condition includes a first constraint condition, which is used to constrain the ratio of the real-time output to the maximum output of all turned-on turbine generator sets to be the same, and the first constraint condition is: Where δ is the load factor of the generator set, P i represents the real-time output of the i-th turbine generator set, represents the maximum output constraint of the i-th turbine generator set, and n is the total number of all turbine generator sets running online; The constraint condition includes a second constraint condition, which is used to constrain the load level of the turbine generator set. The second constraint condition is: Among them, P gt,sp and P dt,sp are the active powers of the gas turbine generator and the oil turbine generator in the sp-th dispatching period, P mid,gt and P mid,dt are the minimum output active power of the gas turbine generator and the oil turbine generator in the recovery period, N L,gt and N L,dt Respectively represent the maximum number of scheduling periods during which the gas turbine generator and the oil turbine generator can continuously operate during the low load period; N C,gt and N C,dt They respectively represent the minimum number of scheduling periods that the gas turbine generator and the oil turbine generator need to operate during the recovery period; sp0 represents any scheduling period within the target scheduling cycle; The constraint condition includes a third constraint condition, which is used to constrain the hot standby power of the turbine generator set to meet the requirement that no load shedding occurs when the generator set fails and the net load fluctuates due to offshore wind power; the third constraint condition is: Among them, P N,gt and P N,dt are the rated powers of the gas turbine generator and the oil turbine generator in the sp-th dispatching period respectively; P pl,sp and P N,pl are the active power and rated power of the electric load in the sp-th dispatching period respectively; Ω PL is the set of electrical loads, pl∈Ω PL ; α indicates that the active power when the load is started is α times the rated power; β is the hot standby ratio that needs to be reserved for the offshore oil and gas field system during normal operation.

4. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method for day-ahead scheduling of offshore oil and gas fields connected to wind power as described in any one of claims 1 to 2 is implemented.

5. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for day-ahead scheduling of offshore oil and gas fields connected to wind power as claimed in any one of claims 1 to 2 is implemented.

6. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the method for day-ahead scheduling of offshore oil and gas fields connected to wind power as claimed in any one of claims 1 to 2 is implemented.

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