Energy storage configuration method and apparatus for deep- and far-sea working platform, device, and storage medium

Abstract

Disclosed in the present invention are an energy storage configuration method and apparatus for a deep- and far-sea working platform, a device, and a storage medium. The method comprises: acquiring internal parameters and external parameters of a deep- and far-sea working platform; constructing a corresponding deep- and far-sea working platform model; constructing a first objective function and a first constraint condition with the objective of maximizing the net present value of energy storage configuration for the deep- and far-sea working platform, and constructing a second objective function and a second constraint condition with the objective of minimizing the annual system operation cost of the deep- and far-sea working platform; and under the constraints of the first constraint condition and the second constraint condition, solving the first objective function and the second objective function to obtain rated capacity and rated power of the energy storage configuration for the deep- and far-sea working platform when the net present value of the energy storage configuration for the deep- and far-sea working platform is maximized and the annual system operation cost thereof is minimized, and configuring energy storage of the deep- and far-sea working platform. The present invention can achieve optimal energy storage configuration for deep- and far-sea working platforms.

Description

An energy storage configuration method, device and equipment for a deep-sea working platform and a storage medium TECHNICAL FIELD

[0001] The present application relates to the technical field of energy storage configuration of power systems, and in particular to an energy storage configuration method, device and equipment for a deep-sea working platform and a storage medium. BACKGROUND

[0002] Offshore working platforms play an important role in energy exploitation and scientific research. With the expansion of marine energy development needs and the progress of deepwater drilling technology, offshore working platforms are advancing towards deep-sea areas. Due to the high cost of submarine transmission cables and the high energy loss caused by long-distance power transmission, it is not economical for deep-sea working platforms to access onshore power grids. Therefore, deep-sea working platforms are generally equipped with gas / oil turbine generators for self-power generation, becoming island microgrids. For example, traditional offshore oil and gas platforms use diesel and gas turbine generators as power sources. However, such self-power generation processes consume fuel and result in a large amount of carbon emissions, which is not conducive to the economy and environmental protection of the platform system.

[0003] The rapid development of offshore wind power provides a good opportunity for the low-carbon transformation of offshore working platforms, but the intermittency and randomness of wind power pose new challenges to the operation and dispatching of offshore working platforms. To address this issue, energy storage can achieve the redistribution of energy in the time and space dimensions, and can be used as a solution to support the integration of wind power into offshore working platforms. However, the introduction of wind power and energy storage will significantly affect the operation and dispatching plan of offshore working platforms. Therefore, it is necessary to study the optimal configuration scheme of energy storage to maintain the normal operation of the operation and dispatching plan of offshore working platforms.

[0004] Although there are some existing documents that provide solutions for the energy storage configuration of wind power integrated microgrids, most of them are for onshore power systems and near-sea working platforms. The existing research on the impact of energy storage on the operation of original turbine generators does not conform to the actual situation of deep-sea working platforms. SUMMARY

[0005] The present application provides an energy storage configuration method, device and equipment for a deep-sea working platform to solve the technical problem that the existing energy storage configuration of wind power integrated microgrids does not conform to deep-sea working platforms.

[0006] To solve the above technical problems, the present application provides an energy storage configuration method for a deep-sea working platform, comprising:

[0007] obtain internal parameters and external parameters of the deep-sea working platform; wherein the internal parameters comprise: system topology, impedance of each node interconnection submarine cable, maximum transmission capacity of each node interconnection submarine cable, fan capacity, turbine generator capacity at each node and power load capacity at each node; the external parameters comprise: wind speed of the sea area near the offshore working platform and price parameters; the price parameters comprise: energy storage price, gas delivery price, carbon tax price, equipment operation and maintenance price and discount rate;

[0008] model the equipment operation process and system network flow of the deep-sea working platform according to the internal parameters, and build a corresponding deep-sea working platform model;

[0009] According to the external parameters and the deep-sea working platform model, the net present value of the deep-sea working platform configuration energy storage is maximum as the target, the first objective function and the first constraint condition are constructed, and the minimum annual operation cost of the deep-sea working platform system is taken as the target, the second objective function and the second constraint condition are constructed;

[0010] Under the constraint of the first constraint condition and the second constraint condition, the first objective function and the second objective function are solved, the rated capacity and rated power of the deep-sea working platform configuration energy storage are obtained when the net present value of the deep-sea working platform configuration energy storage is maximum and the annual operation cost of the system is minimum, and then the energy storage of the deep-sea working platform is configured according to the rated capacity and rated power.

[0011] As a preferred solution, under the constraint of the first constraint condition and the second constraint condition, the first objective function and the second objective function are solved, the rated capacity and rated power of the deep-sea working platform configuration energy storage are obtained when the net present value of the deep-sea working platform configuration energy storage is maximum and the annual operation cost of the system is minimum, comprising:

[0012] Calculate the annual operation cost of the deep-sea working platform without configuring energy storage;

[0013] Calculate the initial rated power and initial rated capacity of the deep-sea working platform energy storage configuration, and solve the second objective function under the constraint of the second constraint condition according to the initial rated power and initial rated capacity, to obtain the minimum annual operation cost of the deep-sea working platform configuration energy storage;

[0014] Compare the minimum annual operation cost with the annual operation cost without configuring energy storage to obtain the reduction of annual operation cost;

[0015] The reduction amount is taken as the net cash flow of the deep-sea working platform, and the first objective function is solved under the constraint of the first constraint condition according to the net cash flow, to obtain the net present value of the deep-sea working platform system under the initial rated power and initial rated capacity;

[0016] The initial rated power and initial rated capacity of the deep-sea working platform energy storage configuration are updated according to the net present value, to obtain the rated capacity and rated power of the deep-sea working platform configured with energy storage when the net present value of the deep-sea working platform configured with energy storage is maximum and the annual operation cost of the system is minimum.

[0017] As a preferred solution, the deep-sea working platform model is:

[0018] Wherein, P t tur,i , P t ess,i , P t wind,i and P t load,i are the operating power of the gas turbine generator, the energy storage, the wind turbine and the load at node i in t period, and the operating power of the energy storage is positive when discharging and negative when charging; n node is the number of nodes in the system; c(i) is the set of all terminal nodes with node i as the head; is the voltage amplitude of node i in t period; is the voltage phase angle difference between nodes i and j in t period; g ij and b ij are the conductance and susceptance of the line between nodes i and j; is the natural gas inlet rate; q g2h is the natural gas calorific value; η tur is the efficiency of the gas turbine generator, P r wind,i is the rated power of the wind turbine at node i; v t is the average wind speed in t period; v in , v r and v out are the cut-in wind speed, rated wind speed and cut-out wind speed of the wind turbine, respectively.

[0019] As a preferred solution, the first objective function is:

[0020] Wherein, C NPV is the net present value of the energy storage configuration; n y is the expected service life of the energy storage; is the annual net cash flow of the energy storage configuration in year y; r is the discount rate; and are the rated power and initial rated capacity of the energy storage, respectively; c P and c E are the unit price of the rated power and the capacity of the energy storage system, respectively.

[0021] As a preferred solution, the first constraint condition is:

[0022] wherein, and are the maximum values of and , respectively.

[0023] As a preferred solution, the second objective function is:

[0024] wherein, nC op,y is the annual operation cost of the energy storage configuration in year y; C gas,y , and C carbon,y are the annual costs of natural gas consumption, energy storage operation and maintenance, gas turbine generator operation and maintenance, and carbon tax, respectively; n d is the number of selected typical days; c gas is the delivered sales price of natural gas; is the gas inlet rate of the gas turbine generator at node i in year y on d typical day t; Δt is the dispatch interval; and are the operation and maintenance prices of the energy storage and the corresponding converter, respectively; is the operation and maintenance price of the gas turbine generator; is the equivalent operating hours of the gas turbine generator at node i in year y on d typical day; c carbon is the tax price of CO2 emission; η g2c is the conversion coefficient of CO2 generated by natural gas; and are the actual operating hours of the gas turbine generator at node i in year y on d typical day at high, medium, low, and extremely low load levels, respectively; a H , a M , a L , and a XL are the equivalent operating time length coefficients of the gas turbine generator in year y on d typical day at high, medium, low, and extremely low load levels, respectively; is the capacity of the energy storage in year y; β is the annual attenuation coefficient of the energy storage capacity.

[0025] As a preferred solution, the second constraint condition is:

[0026] wherein, is the voltage amplitude of node i at the time period t of the d typical day in the year y; and are respectively the upper allowable boundary and the lower allowable boundary of is the operating power of device k in node i at the time period t of the d typical day in the year y, k∈{'tur','wind','ess'}; and are respectively the upper boundary limit and the lower boundary limit of and are respectively the up ramp rate boundary limit and the down ramp rate boundary limit of the gas turbine generator of node i; is the energy storage of the energy storage in node i at the time period t of the d typical day in the year y; α U and α L are respectively the upper limit allowable coefficient and the lower limit allowable coefficient of the state of charge of the energy storage.

[0027] On the basis of the above embodiment, another embodiment of the application provides an energy storage configuration device for a deep sea working platform, comprising: a parameter acquisition module, a model construction module, a target function construction module and an energy storage configuration module;

[0028] The parameter acquisition module is configured to acquire internal parameters and external parameters of the deep sea working platform; wherein the internal parameters comprise: a system topology structure, impedance of a tie-in submarine cable between nodes, maximum transmission capacity of the tie-in submarine cable between nodes, fan capacity, turbine generator capacity at each node and electrical load capacity at each node; and the external parameters comprise: wind speed of a sea area adjacent to the offshore working platform and price parameters; the price parameters comprise: energy storage price, gas delivery price, carbon tax price, equipment operation and maintenance price and discount rate;

[0029] The model construction module is configured to model device operation processes and system network power flow of the deep sea working platform according to the internal parameters, and construct a corresponding deep sea working platform model;

[0030] The target function construction module is configured to construct a first target function and a first constraint condition with the maximum net present value of the deep sea working platform configured with energy storage as a target according to the external parameters and the deep sea working platform model, and construct a second target function and a second constraint condition with the minimum annual operation cost of the deep sea working platform as a target;

[0031] The energy storage configuration module is configured to solve the first objective function and the second objective function under the constraints of the first constraint condition and the second constraint condition, to obtain the rated capacity and the rated power of the deep-sea working platform configured with energy storage when the net present value of the deep-sea working platform configured with energy storage is maximum and the annual operation cost of the system is minimum, and then configure the energy storage of the deep-sea working platform according to the rated capacity and the rated power.

[0032] On the basis of the above-mentioned embodiments, a further embodiment of the application provides an electronic device, which comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the energy storage configuration method for deep-sea working platforms when executing the computer program.

[0033] On the basis of the above-mentioned embodiments, a further embodiment of the application provides a storage medium, which comprises a stored computer program, wherein the device where the storage medium is located executes the energy storage configuration method for deep-sea working platforms when the computer program runs.

[0034] Compared with the prior art, the embodiments of the application have the following beneficial effects:

[0035] The application provides an energy storage configuration method for deep-sea working platforms, which obtains internal parameters and external parameters of a deep-sea working platform, models the device operation process and system network flow of the deep-sea working platform according to the internal parameters, constructs a corresponding deep-sea working platform model, constructs a first objective function and a first constraint condition according to the external parameters and the deep-sea working platform model, taking the maximum net present value of the deep-sea working platform configured with energy storage as the target, and constructs a second objective function and a second constraint condition taking the minimum annual operation cost of the deep-sea working platform as the target, solves the first objective function and the second objective function under the constraints of the first constraint condition and the second constraint condition, to obtain the rated capacity and the rated power of the deep-sea working platform configured with energy storage when the net present value of the deep-sea working platform configured with energy storage is maximum and the annual operation cost of the system is minimum, and then configures the energy storage of the deep-sea working platform according to the rated capacity and the rated power.

[0036] The present application is directed to a deep-sea working platform, and aims to maximize the net present value of the deep-sea working platform configured with energy storage and minimize the annual operating cost of the system, build a corresponding objective function and constraint condition, and solve the objective function under the constraint condition to obtain an optimal energy storage configuration scheme, i.e., the rated capacity and rated power of the deep-sea working platform configured with energy storage when the net present value of the deep-sea working platform configured with energy storage is maximized and the annual operating cost of the system is minimized, and then the optimal energy storage configuration of the deep-sea working platform can be achieved according to the rated capacity and rated power, thereby maintaining the normal operation of the offshore working platform operation scheduling plan. BRIEF DESCRIPTION OF DRAWINGS

[0037] Fig. 1 is a flowchart of a deep-sea working platform-oriented energy storage configuration method according to an embodiment of the present application;

[0038] Fig. 2 is an architecture diagram of a deep-sea working platform-oriented energy storage configuration double-layer optimization method according to the present application;

[0039] Fig. 3 is a structural schematic diagram of a typical offshore working platform with wind power and energy storage;

[0040] Fig. 4 is a system structure diagram of a certain isolated offshore working platform in the South China Sea;

[0041] Fig. 5 is an annual operation data diagram of the energy storage in the life cycle of a certain isolated offshore working platform in the South China Sea;

[0042] Fig. 6 is a result diagram of the net present value of the energy storage under different investment schemes using a grid method;

[0043] Fig. 7 is a structural schematic diagram of a deep-sea working platform-oriented energy storage configuration device according to an embodiment of the present application. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical scheme and advantages of the present application clearer, the technical scheme in the present application will be described clearly and completely below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without making creative efforts fall within the scope of protection of the present application.

[0045] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit the present application; the terms "include" and "have" and any variations thereof in the specification and claims of the present application and the above description of drawings are intended to cover non-exclusive inclusion.

[0046] In the description of the embodiments of the present application, the technical terms "first", "second" and the like are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "multiple" is more than two, unless otherwise explicitly and specifically limited.

[0047] Reference herein to "embodiments" means that the particular features, structures, or characteristics described in connection with the embodiments can be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily all refer to the same embodiment, nor is it necessarily independent or alternative embodiments to each other. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0048] In the description of the embodiments of the present application, the term "and / or" is only a description of the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which can represent the three cases of A alone, A and B together, and B alone. In addition, the character " / " herein generally represents an "or" relationship between the associated objects before and after it.

[0049] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two), and similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0050] In the description of the embodiments of the present application, unless otherwise explicitly specified and limited, the technical terms "mounting", "connecting", "connecting", "fixing" and the like should be understood in a broad sense, for example, it can be fixedly connected, or it can be detachably connected, or it can be integrated; it can be mechanical connection, or it can be electrical connection; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the internal communication of two elements or the interaction relationship between two elements. For those skilled in the art, the specific meaning of the above terms in the embodiments of the present application can be understood according to the specific circumstances.

[0051] Embodiment one

[0052] Please refer to FIG. 1, which is a flowchart of a kind of energy storage configuration method for deep sea working platform provided by an embodiment of the present application, comprising the following specific steps:

[0053] S1, acquire internal parameters and external parameters of the deep sea working platform; wherein the internal parameters include: system topology, impedance of the interconnection submarine cable between nodes, maximum transmission capacity of the interconnection submarine cable between nodes, fan capacity, turbine generator capacity at each node and electrical load capacity at each node; the external parameters include: wind speed of the sea area near the offshore working platform and price parameters; the price parameters include: energy storage price, gas transmission price, carbon tax price, equipment operation and maintenance price and discount rate;

[0054] Specifically, please refer to Figure 2, which is the architecture diagram of the double-layer optimization method for energy storage configuration of the deep sea working platform of the application, the energy storage configuration method for the deep sea working platform provided by the application includes the following steps:

[0055] (1) Collect and set parameters:

[0056] First, acquire internal parameters and parameters of the deep sea working platform, the internal parameters include: system topology, impedance and maximum transmission capacity of the interconnection submarine cable between nodes of the offshore working platform, fan capacity, turbine generator capacity and load capacity at each node, and other physical parameters and system structure parameters; the external parameters include: environmental parameters such as wind speed of the sea area near the offshore working platform, and economic parameters such as energy storage price, gas transmission price, carbon tax price, equipment operation and maintenance price, discount rate; and set particle number, individual factor, learning factor, inertia factor, maximum iteration number, maximum and minimum speed and other particle swarm algorithm parameters.

[0057] S2, according to the internal parameters, model the device operation process and system network power flow of the deep sea working platform, and build the corresponding deep sea working platform model;

[0058] Preferably, the deep sea working platform model is:

[0059] Wherein, P t tur,i , P t ess,i , P t wind,i and P t load,i are the operating power of the gas turbine generator, energy storage, wind turbine and load at node i in t period, when the operating power of the energy storage is positive, it means discharging, and when it is negative, it means charging; n node is the number of nodes in the system; c(i) is the set of all end nodes with node i as the first node; is the voltage amplitude of node i in t period; is the voltage phase angle difference between nodes i and j in t period; g ij and b ijThese are the conductance and susceptance of the line between nodes i and j, respectively. q represents the natural gas intake rate. g2h η is the calorific value of natural gas. tur For the efficiency of a gas turbine generator, P r wind,i v represents the rated power of the wind turbine at node i; t v is the average wind speed during the time period t; in v r and v out The table shows the cut-in wind speed, rated wind speed, and cut-out wind speed of the wind turbine.

[0060] (2) Constructing a model of an offshore working platform

[0061] Please refer to Figure 3, which is a schematic diagram of a typical offshore work platform with wind power and energy storage integration. Turbine generators and wind turbines constitute the power supply system of the offshore work platform. Electrical loads are divided into operational loads and residential loads. Operational loads mainly include various induction motors and occupy a dominant position in the load composition. Residential loads mainly meet the daily living needs of the staff, including lighting, air conditioning, and communication. The power flow model for the nodes in the offshore work platform's power system is as follows:

[0062] In the formula, P t tur,i P t ess,i P t wind,i and P t load,i Let n represent the operating power of the gas turbine generator, energy storage, wind turbine generator, and load at node i during time period t. A positive value for the energy storage operating power indicates discharging, while a negative value indicates charging. node Let c be the number of nodes in the system; c(i) is the set of all end nodes starting with node i. Let i be the voltage amplitude of node i during time period t; The voltage phase angle difference between nodes i and j within time period t; g ij and b ij These are the conductance and susceptance of the line between nodes i and j, respectively.

[0063] The output power of a gas turbine generator can be adjusted by the natural gas intake rate, as shown in the following formula:

[0064] In the formula, q represents the natural gas intake rate. g2h η is the calorific value of natural gas. tur The efficiency of the gas turbine generator.

[0065] The maximum power of the wind turbine in the MPPT mode is limited by the wind speed, as shown in the following formula:

[0066] In the formula, P r wind,i is the rated power of the wind turbine at node i; v t is the average wind speed in the period t; v in , v r and v out respectively represent the cut-in wind speed, rated wind speed and cut-out wind speed of the wind turbine.

[0067] It should be noted that the offshore work platform model constructed above mainly represents the operation mechanism of the equipment and the power-gas coupling characteristics of the turbine generator. The equipment operation process and the network power flow are added to the constraint conditions of the lower-level optimization algorithm, and the fuel consumption in the power-gas coupling is added to the cost of the objective function, so as to optimize the equipment operation power in the lower-level algorithm and the energy storage configuration capacity in the upper-level algorithm.

[0068] S3, according to the external parameters and the deep sea work platform model, a first objective function and a first constraint condition are constructed with the maximum net present value of the deep sea work platform configuration energy storage as the target, and a second objective function and a second constraint condition are constructed with the minimum annual operating cost of the deep sea work platform system as the target;

[0069] Preferably, the first objective function is:

[0070] In the formula, C NPV is the net present value of the energy storage configuration; n y is the expected life cycle of the energy storage; is the annual net cash flow of the energy storage configuration in the yth year; r is the discount rate; and respectively represent the rated power and the initial rated capacity of the energy storage; c P and c E respectively represent the unit rated power price and the capacity price of the energy storage system.

[0071] Preferably, the first constraint condition is:

[0072] In the formula, C and respectively represent the maximum value of C and .

[0073] Preferably, the second objective function is:

[0074] wherein nC op,y is the annual operation cost of the energy storage configuration in year y; C gas,y 、 and C carbon,y are the annual cost of natural gas consumption, energy storage operation and maintenance, gas turbine generator operation and maintenance, and carbon tax, respectively, of the energy storage configuration in year y; n d is the number of selected typical days; c gas is the delivered sales price of natural gas; is the gas inlet rate of the gas turbine generator at node i in year y on d typical day t; Δt is the dispatch interval; and are the operation and maintenance prices of the energy storage and corresponding converter, respectively; is the operation and maintenance price of the gas turbine generator; is the equivalent operation hours of the gas turbine generator at node i in year y on d typical day; c carbon is the tax price of CO2emission; η g2c is the conversion coefficient of CO2emission of natural gas; and are the actual operation hours of the gas turbine generator at node i in year y on d typical day at high, medium, low, and very low load levels, respectively; a H , a M , a L , and a XL are the equivalent operation time length coefficients of the gas turbine generator in year y on d typical day at high, medium, low, and very low load levels, respectively; is the capacity of the energy storage in year y of configuration; β is the annual attenuation coefficient of the energy storage capacity.

[0075] Preferably, the second constraint condition is:

[0076] wherein, is the voltage amplitude of node i in year y on d typical day t; and are the upper and lower allowable boundaries of , respectively; is the operation power of device k at node i in year y on d typical day t, k∈{'tur', 'wind', 'ess'}; and are the upper and lower boundary limits of , respectively; and are the upper and lower ramp rate boundary limits of the gas turbine generator at node i, respectively. Energy storage for node i in the yth year on the dth typical day at the tth time period; a U and a L are the upper and lower allowable coefficients of the state of charge of the energy storage, respectively.

[0077] (3) Setting the objective function and constraint conditions of the upper-level optimization algorithm

[0078] The objective function of the upper-level optimization algorithm is the maximum net present value of the energy storage configuration, and the decision variables are the rated capacity and rated power of the energy storage. The upper-level optimization algorithm maximizes the net present value of the energy storage configuration by optimizing the rated capacity and rated power of the energy storage, where the net present value refers to the expected net cash flow discounted by the present value, which can appropriately reflect the overall economic benefits of the energy storage system configuration in the entire life cycle. The objective function expression is as follows:

[0079] In the formula, C NPV is the net present value of the energy storage configuration; n y is the expected life cycle of the energy storage; is the annual net cash flow of the energy storage configuration in the yth year; r is the discount rate; and are the rated power and initial rated capacity of the energy storage, respectively; c P and c E are the unit rated power price and capacity price of the energy storage system, respectively.

[0080] According to the space and load deployment requirements of offshore platforms, the constraint conditions of the rated power and rated capacity of the energy storage in the upper-level optimization are set as follows:

[0081] In the formula, and are the maximum values of and , respectively.

[0082] (4) Setting the objective function and constraint conditions of the lower-level optimization algorithm

[0083] The objective function of the lower-level optimization algorithm is the minimum annual operating cost of the system, and the decision variables are the operating powers of the gas turbine generator, energy storage, and wind turbine in the system at each time period. The lower-level optimization algorithm aims to maximize the annual operating cost by optimizing the operating powers of the devices, and the objective function expression is as follows:

[0084] In the formula, nC op,y is the annual operating cost of the energy storage configuration in the yth year; C gas,y , and Ccarbon,y are the annual costs of natural gas consumption, energy storage operation and maintenance, gas turbine generator operation and maintenance, and carbon tax, respectively, in the yth year of the energy storage configuration, and are expressed as follows:

[0085] where n d is the number of selected typical days; c gas is the delivered sales price of natural gas; is the gas inlet rate of the gas turbine generator at node i in the yth year of the dth typical day at the tth time interval; and Δt is the dispatch time interval; and are the operation and maintenance prices of the energy storage and the corresponding converter, respectively; is the operation and maintenance price of the gas turbine generator; is the equivalent operation hours of the gas turbine generator at node i in the yth year of the dth typical day; c carbon is the tax price of CO2emission; η g2c is the conversion coefficient of CO2emission of natural gas; and are the actual operation hours of the gas turbine generator at node i in the yth year of the dth typical day at high, medium, low, and extremely low load levels, respectively; a H , a M , a L , and a XL are the equivalent operation time length coefficients of the gas turbine generator at high, medium, low, and extremely low load levels in the yth year of the dth typical day, respectively; is the capacity of the energy storage in the yth year of the configuration; and β is the annual attenuation coefficient of the energy storage capacity.

[0086] According to the physical parameters and operation boundaries of each device, the constraint conditions of the lower-level optimization algorithm are set as follows:

[0087] Equations (1)-(3) (15)

[0088] where, is the voltage amplitude of node i in the yth year of the dth typical day at the tth time interval; and are the upper and lower allowable boundaries of , respectively; is the operation power of device k at node i in the yth year of the dth typical day at the tth time interval, k∈{'tur', 'wind', 'ess'}; and are the upper and lower boundary limits of , respectively; and The up-ramp rate boundary limit value and the down-ramp rate boundary limit value of the gas turbine generator of the node i respectively; The energy storage of the energy storage of the node i in the yth year and the dth typical day time period; α U And α L The upper limit and the lower limit of the allowable coefficient of the state of charge of the energy storage.

[0089] S4, under the constraints of the first constraint condition and the second constraint condition, solving the first objective function and the second objective function to obtain the rated capacity and the rated power of the deep sea working platform configured with the energy storage when the net present value of the deep sea working platform configured with the energy storage is maximum and the annual operating cost of the system is minimum, and then configuring the energy storage of the deep sea working platform according to the rated capacity and the rated power.

[0090] Preferably, under the constraints of the first constraint condition and the second constraint condition, solving the first objective function and the second objective function to obtain the rated capacity and the rated power of the deep sea working platform configured with the energy storage when the net present value of the deep sea working platform configured with the energy storage is maximum and the annual operating cost of the system is minimum, comprises: calculating the annual operating cost of the deep sea working platform without configuring the energy storage; calculating the initial rated power and the initial rated capacity of the energy storage of the deep sea working platform, and solving the second objective function under the constraint of the second constraint condition according to the initial rated power and the initial rated capacity to obtain the minimum annual operating cost of the deep sea working platform configured with the energy storage; comparing the minimum annual operating cost with the annual operating cost without configuring the energy storage to obtain the reduction amount of the annual operating cost; taking the reduction amount as the net cash flow of the deep sea working platform, and solving the first objective function under the constraint of the first constraint condition according to the net cash flow to obtain the net present value of the system of the deep sea working platform under the initial rated power and the initial rated capacity; updating the initial rated power and the initial rated capacity of the energy storage of the deep sea working platform according to the net present value to obtain the rated capacity and the rated power of the deep sea working platform configured with the energy storage when the net present value of the deep sea working platform configured with the energy storage is maximum and the annual operating cost of the system is minimum.

[0091] (5) solving the energy storage configuration double-layer optimization algorithm:

[0092] Based on the collected annual wind speed data, several typical days are selected. Using the wind speeds on these typical days, a lower-level optimization algorithm is used to calculate the annual operating cost of the offshore platform without energy storage. In the upper-level optimization algorithm, a particle swarm optimization (PSO) algorithm is used to generate candidate energy storage configurations. The generated rated power and capacity of the energy storage are then transmitted to the lower-level optimization algorithm to calculate the minimum annual operating cost of the system under the current energy storage configuration. This cost reduction is compared with the annual operating cost without energy storage to obtain the net cash flow. This net cash flow is then transmitted to the upper-level optimization algorithm to calculate the net present value (NPV) of the system under the current energy storage configuration. The candidate energy storage configurations are updated using the PSO algorithm in the upper-level optimization process. This process continues until the NPV meets the optimization exit criteria, at which point the optimal configuration result for the rated power and capacity of the energy storage is output.

[0093] Specifically, the lower-level optimization algorithm is used to solve for the annual operating cost of the offshore working platform without energy storage. In the upper-level optimization algorithm, particle swarm optimization is used to generate candidate energy storage configurations. The rated power and capacity of the energy storage in the generated candidate configurations are then transmitted to the lower-level optimization algorithm to solve for the minimum annual operating cost of the system under these energy storage configurations. This cost reduction is compared with the annual operating cost without energy storage to obtain the net cash flow. The expression for the net cash flow is as follows:

[0094] Calculate the net cash flow The data is then passed to the upper-level optimization algorithm to calculate the net present value (NPV) of the system under the current energy storage configuration. The candidate energy storage configuration is updated using particle swarm optimization in the upper-level optimization process. This continues until the NPV meets the optimization exit criteria, at which point the optimal configuration result for the rated power and capacity of the energy storage is output.

[0095] In one specific embodiment, the proposed energy storage configuration method is tested using a simplified model of an isolated offshore working platform in the South China Sea. Referring to Figure 4, which shows the system structure of the isolated offshore working platform in the South China Sea, the platform is connected to an 8MW wind turbine, and three gas turbine generators are operating to supply power to the platform. To fully reflect the wind speed levels throughout the year, two days at the beginning and middle of each month are selected as typical days. The parameters used in this example are shown in Table 1 below.

[0096] Table 1. Example parameters used by a certain isolated offshore working platform in the South China Sea.

[0097] The energy storage configuration scheme is obtained by solving the proposed energy storage configuration double-layer optimization model, and the results show that the energy storage system with a capacity of 0.7972 MWh and a rated power of 0.6097 MW should be configured, and the initial investment cost is 918,780 yuan. Please refer to Figure 5 for the annual operation data diagram of the energy storage in its life cycle, the energy storage absorbs wind power in the wind power peak period and releases wind power in the wind power valley period, so as to reduce the consumption of natural gas in the self-generation process. Therefore, the operator of the offshore platform can obtain higher income by selling natural gas, and in addition, the energy storage shares the adjustment burden of the gas turbine generator, so that the operation condition of the gas turbine generator can be optimized, and the gas turbine generator can run for a longer time under medium load. Therefore, the operation and maintenance cost of the gas turbine generator is greatly reduced, and the service life of the gas turbine generator is prolonged with the configuration of the energy storage system.

[0098] It can be seen that the obtained energy storage optimization configuration scheme can effectively reduce the annual operation cost. The annual average equivalent operating hours of the gas turbine generator are reduced by 4327 hours, thereby reducing the annual average maintenance cost of the gas turbine generator by 270,438 yuan. 15,205 cubic meters of natural gas can be saved per year, and carbon emissions are reduced by 28.7 tons. As the capacity of the energy storage system decreases year by year, the support of the energy storage to the system is weakened, and the net cash flow presents a downward trend. However, the net present value of the entire life cycle of the energy storage reaches 1,845,000 yuan in total, which indicates that the overall economy of the offshore platform is significantly improved.

[0099] The grid method is used to test the net present value of the energy storage under different investment schemes, and the results are shown in Figure 6. As shown in the figure, the energy storage with small rated capacity and rated power has no obvious effect on improving wind power consumption and optimizing the operation condition of the gas turbine generator. On the other hand, if the rated capacity or rated power of the energy storage is too large, redundancy will occur. In the current situation where the price of the energy storage has not decreased significantly, the system operation cost saved by the energy storage cannot even offset the investment cost, so the net present value may become negative.

[0100] Therefore, the present application proposes a double-layer optimization method for energy storage configuration for improving the economic efficiency of wind power consumption of deep-sea working platforms. The upper-layer optimization uses a particle swarm algorithm to maximize the net present value of the energy storage in the entire life cycle. The lower-layer optimization uses a commercial solver to develop a power operation scheduling plan for each device to minimize the annual operation cost. The influence of natural gas consumption cost, carbon tax and device operation and maintenance cost on the energy storage configuration is included in the annual operation cost objective function. The operation and maintenance cost of the turbine generator considers the influence of wind power fluctuation on the operation condition of the system turbine generator, and the running time of the turbine generator at different load levels is converted into equivalent operating hours to calculate the operation and maintenance cost.

[0101] Embodiment two

[0102] Please refer to Figure 7, it is a structural schematic diagram of an energy storage configuration device for a deep sea working platform provided by an embodiment of the present application, and the device comprises: a parameter acquisition module, a model construction module, a target function construction module and an energy storage configuration module.

[0103] The parameter acquisition module is configured to acquire internal parameters and external parameters of the deep sea working platform; wherein the internal parameters comprise: a system topology structure, impedance of each node interconnection submarine cable, maximum transmission capacity of each node interconnection submarine cable, fan capacity, turbine generator capacity at each node and electric load capacity at each node; and the external parameters comprise: wind speed of a sea area near the offshore working platform and price parameters; and the price parameters comprise: energy storage price, gas delivery price, carbon tax price, equipment operation and maintenance price and discount rate.

[0104] The model construction module is configured to model device operation process and system network power flow of the deep sea working platform according to the internal parameters, and construct a corresponding deep sea working platform model.

[0105] The target function construction module is configured to construct a first target function and a first constraint condition with a maximum net present value of the deep sea working platform configured with energy storage as a target according to the external parameters and the deep sea working platform model, and construct a second target function and a second constraint condition with a minimum annual operation cost of the deep sea working platform as a target.

[0106] The energy storage configuration module is configured to solve the first target function and the second target function under the constraint of the first constraint condition and the second constraint condition, obtain rated capacity and rated power of the deep sea working platform configured with energy storage when the net present value of the deep sea working platform configured with energy storage is maximum and the annual operation cost of the system is minimum, and then configure energy storage of the deep sea working platform according to the rated capacity and the rated power.

[0107] It should be noted that the device embodiments described above are only schematic, wherein the units described as separate components can or can not be physically separate, and the components displayed as units can or can not be physical units, i.e. they can be located in one place, or distributed on multiple network units. Part or all of the modules can be selected to achieve the purpose of the embodiment scheme according to actual needs. In addition, the connection relationship between the modules in the device embodiment provided by the present application indicates that there is a communication connection between them, which can be realized as one or more communication buses or signal lines. Those skilled in the art can understand and implement it without creative labor.

[0108] Those skilled in the art can clearly understand that, for the convenience and brevity, the specific working process of the device described above can refer to the corresponding process in the foregoing method embodiment, and will not be repeated here.

[0109] Embodiment three

[0110] Correspondingly, an electronic device is provided, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the energy storage configuration method for a deep-sea working platform when executing the computer program.

[0111] The electronic device can be a desktop computer, a notebook computer, a palm computer, a cloud server, and the like. The device can include, but is not limited to, a processor and a memory.

[0112] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, and the like. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor and the like. The processor is a control center of the device, and connects all parts of the device through various interfaces and lines.

[0113] Embodiment four

[0114] Correspondingly, a storage medium is provided, which includes a stored computer program, wherein the computer program controls a device where the storage medium is located to execute the energy storage configuration method for a deep-sea working platform when the computer program runs.

[0115] The memory can be used to store the computer program, and the processor realizes various functions of the device by running or executing the computer program stored in the memory and calling data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required by a function, and the like; and the data storage area can store data created according to the use of the mobile phone and the like. In addition, the memory can include a high-speed random access memory, and can also include a nonvolatile memory, for example, a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state memory devices.

[0116] The storage medium is a computer readable storage medium, and the computer program is stored in the computer readable storage medium. When the computer program is executed by the processor, the steps of each method embodiment described above can be realized. The computer program includes computer program code, which can be in the form of source code, object code, an executable file, or some intermediate form, etc. The computer readable medium can include any entity or device capable of carrying the computer program code, a recording medium, a U disk, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc. It should be noted that the content included in the computer readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.

[0117] The above is the preferred embodiment of the present application. It should be noted that for those skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, which are also considered within the scope of protection of the present application.

Claims

1. A method for energy storage configuration for a deep sea working platform, characterized in that, The method comprises the following steps: obtaining internal parameters and external parameters of the deep-sea working platform; wherein the internal parameters comprise system topology, impedance of each node interconnection submarine cable, maximum transmission capacity of each node interconnection submarine cable, fan capacity, turbine generator capacity at each node and electric load capacity at each node; the external parameters comprise wind speed of the sea area near the offshore working platform and price parameters; the price parameters comprise energy storage price, gas transmission price, carbon tax price, equipment operation and maintenance price and discount rate; modeling device operation process and system network flow of the deep-sea working platform according to the internal parameters, and constructing a corresponding deep-sea working platform model; according to the external parameters and the deep-sea working platform model, taking the maximum net present value of the deep-sea working platform configured with energy storage as the target, constructing a first objective function and a first constraint condition, and taking the minimum annual operation cost of the deep-sea working platform as the target, constructing a second objective function and a second constraint condition; under the constraint of the first constraint condition and the second constraint condition, the first objective function and the second objective function are solved, and the rated capacity and rated power of the deep-sea working platform configured with energy storage are obtained when the net present value of the deep-sea working platform configured with energy storage is maximum and the annual operation cost of the system is minimum, and then the energy storage of the deep-sea working platform is configured according to the rated capacity and rated power.

2. The method for energy storage configuration for a deep offshore work platform according to claim 1, wherein, under the constraint of the first constraint condition and the second constraint condition, the first objective function and the second objective function are solved, and the rated capacity and rated power of the deep-sea working platform configured with energy storage are obtained when the net present value of the deep-sea working platform configured with energy storage is maximum and the annual operation cost of the system is minimum, comprising: calculating the annual operation cost of the deep-sea working platform without configuring energy storage; calculating the initial rated power and initial rated capacity of the energy storage of the deep-sea working platform, and solving the second objective function under the constraint of the second constraint condition according to the initial rated power and initial rated capacity, to obtain the minimum annual operation cost of the deep-sea working platform configured with energy storage; comparing the minimum annual operation cost with the annual operation cost without configuring energy storage to obtain the reduction amount of the annual operation cost; taking the reduction amount as the net cash flow of the deep-sea working platform, and solving the first objective function under the constraint of the first constraint condition according to the net cash flow, to obtain the net present value of the deep-sea working platform system under the initial rated power and initial rated capacity; updating the initial rated power and initial rated capacity of the energy storage of the deep-sea working platform according to the net present value, to obtain the rated capacity and rated power of the deep-sea working platform configured with energy storage when the net present value of the deep-sea working platform configured with energy storage is maximum and the annual operation cost of the system is minimum.

3. The method for energy storage configuration for a deep offshore work platform as claimed in claim 1, wherein, The deep sea working platform model is: where P t tur,i , P t ess,i , P t wind,i and P t load,i are the operating power of gas turbine generator, energy storage, wind turbine and load at node i in time period t, respectively, where positive value of energy storage represents discharging and negative value represents charging; n node is the number of nodes in the system; c(i) is the set of all terminal nodes with node i as the head; Let i be the voltage amplitude of node i during time period t; is the voltage phase angle difference between nodes i and j for the time period t; g ij and b ij are the conductance and susceptance, respectively, of the line between nodes i and j; is the natural gas inlet flow rate; q g2h is the natural gas heating value; η tur is the efficiency of the gas turbine generator, P r wind,i is the rated power of the wind turbine at node i; v t is the average wind speed over the time period t; v in , v r , and v out are the cut-in, rated, and cut-out wind speeds of the wind turbine, respectively.

4. The method for energy storage configuration for a deep offshore work platform according to claim 3, wherein, The first objective function is: where C NPV is the net present value of the energy storage configuration; n y is the expected life span of the energy storage in years; NCFY is the net annual cash flow in year y for the energy storage configuration; r is the discount rate; and respectively the rated power and the initial rated capacity of the energy storage; c P and c E respectively the unit price of the rated power and the unit price of the capacity of the energy storage system.

5. The method for energy storage configuration for a deep offshore work platform as claimed in claim 4, wherein, The first constraint condition is: wherein and respectively and The maximum value of the net present value of the deep-sea working platform configured with energy storage is obtained.

6. The method for energy storage configuration for a deep offshore work platform according to claim 5, wherein, The second objective function is: wherein nC op,y Cyearly is the annual operating cost in the yth year for the energy storage configuration; C gas,y 、 and C carbon,y are the natural gas consumption, the storage operation and maintenance, the gas turbine generator operation and maintenance and the carbon tax annual costs of the energy storage configuration in the yth year, respectively; n d is the number of selected typical days; c gas is the outgoing sales price of natural gas; Gin,y,d,t is the gas inlet rate for the node i gas turbine generator at the yth year, dth typical day, and tth time period; Δt is the dispatch time period interval; and The operation and maintenance prices of the energy storage and the corresponding matching converter, respectively; For the operation and maintenance price of gas turbine generator; Equivalent operating hours for node i gas turbine generator in year y on day d typical; c carbon Tax price for CO2 emissions; η g2c Conversion factor for CO2 emissions from natural gas; and respectively the actual operating hours of the gas turbine generator at node i at high, medium, low and very low load levels on the d typical day in year y; a H , a M , a L and a XL respectively the equivalent operating hours factor of the gas turbine generator at high, medium, low and very low load levels on the d typical day in year y; is the capacity of the energy storage configured for y years; β is the annual attenuation coefficient of the energy storage capacity.

7. The method for energy storage configuration for a deep offshore work platform according to claim 6, wherein, The second constraint condition is: wherein Vitd,y,i = voltage amplitude for node i at time period t of typical day d in year y; and respectively upper and lower allowable boundaries of the parameter; Pik,y,d,t is the operating power of device k in node i at time period t of typical day d in year y, k e {'tur, 'wind, 'ess'}; and respectively upper and lower boundary limits of the range of values of the parameter; and respectively, are the upper and lower ramp rate boundary limits for the gas turbine generator at node i; Soi is the energy storage of node i in the yth year on the dth typical day at the tth time period; a U and a L are the upper and lower allowable coefficients of the state of charge of the energy storage, respectively.

8. An energy storage arrangement for a deep offshore work platform, characterized by The method comprises the following steps: a parameter acquisition module, a model construction module, an objective function construction module and an energy storage configuration module; The parameter acquisition module is configured to acquire internal parameters and external parameters of the deep-sea working platform; the internal parameters include a system topology, impedance of inter-node tie-in submarine cables, maximum transmission capacity of the inter-node tie-in submarine cables, fan capacity, turbine generator capacity at each node, and electric load capacity at each node; the external parameters include wind speed of a sea area near the offshore working platform and price parameters; the price parameters include energy storage price, gas transmission price, carbon tax price, equipment operation and maintenance price, and discount rate; The model construction module is configured to model equipment operation processes and system network power flow of the deep-sea working platform according to the internal parameters, and construct a corresponding deep-sea working platform model; The objective function construction module is configured to construct a first objective function and a first constraint condition according to the external parameters and the deep-sea working platform model, with a maximum net present value of the deep-sea working platform configured with energy storage as a target, and construct a second objective function and a second constraint condition with a minimum annual operation cost of the deep-sea working platform as a target; The energy storage configuration module is configured to solve the first objective function and the second objective function under the constraint of the first constraint condition and the second constraint condition, to obtain a rated capacity and a rated power of the deep-sea working platform configured with energy storage when the net present value of the deep-sea working platform configured with energy storage is maximum and the annual operation cost of the system is minimum, and then configure energy storage of the deep-sea working platform according to the rated capacity and the rated power.

9. An electronic device, comprising: The storage medium includes a stored computer program, wherein the computer program controls a device where the storage medium is located to perform the energy storage configuration method for a deep-sea working platform according to any one of claims 1 to 7 when the computer program is running.

10. A storage medium, characterized by The storage medium includes a stored computer program, wherein the computer program controls a device where the storage medium is located to perform the energy storage configuration method for a deep-sea working platform according to any one of claims 1 to 7 when the computer program is running.

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