Energy storage configuration method, device, equipment and storage medium for deep-sea working platforms

Abstract

The present invention discloses a method, device, equipment, and storage medium for configuring energy storage for a deep-sea working platform. The method includes: obtaining internal and external parameters of the deep-sea working platform; constructing a corresponding deep-sea working platform model; constructing a first objective function and a first constraint condition with the goal of maximizing the net present value of configuring energy storage for the deep-sea working platform, and constructing a second objective function and a second constraint condition with the goal of minimizing the annual system operating cost of the deep-sea working platform; solving the first and second objective functions under the constraints of the first and second constraints to obtain the rated capacity and rated power of the energy storage configured for the deep-sea working platform when the net present value of the energy storage configured for the deep-sea working platform is maximized and the annual system operating cost is minimized, and configuring the energy storage for the deep-sea working platform. The present invention can achieve optimal energy storage configuration for the deep-sea working platform.

Description

Technical Field

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

[0002] Offshore platforms play a vital role in energy extraction, scientific research, and other fields. With the growing demand for marine energy development and advances in deepwater drilling technology, offshore platforms are increasingly being deployed in deep-sea areas. However, due to the high cost of submarine transmission cables and the high energy losses associated with long-distance transmission, connecting these platforms to onshore power grids is uneconomical. Therefore, these platforms are typically equipped with gas-fired or oil-fired turbine generators for self-generation, creating isolated microgrids. For example, traditional offshore oil and gas platforms use diesel and gas-fired turbine generators for their power supply. However, this self-generation process consumes fuel and results in significant carbon emissions, compromising the economic and environmental performance of the platform system.

[0003] The booming development of offshore wind power presents a promising opportunity for the low-carbon transition of offshore platforms. However, the intermittent and random nature of wind power presents new challenges for the operation and scheduling of offshore platforms. Energy storage, which redistributes energy across time and space, can address this issue and serve as a solution to support the integration of wind power into offshore platforms. However, the integration of wind power and energy storage can significantly impact the operational scheduling of offshore platforms. Therefore, it is necessary to study the optimal configuration of energy storage to maintain the proper operation and scheduling of offshore platforms.

[0004] Although relevant literature currently provides some solutions for energy storage configuration when connecting wind power to microgrids, most of them focus on onshore power systems and offshore work platforms. Existing research on the impact of energy storage on the operation of the system's original turbine generators does not conform to the actual situation of deep-sea work platforms. Summary of the Invention

[0005] The present invention provides an energy storage configuration method, device, equipment and storage medium for deep-sea working platforms to solve the technical problem that the existing energy storage configuration of wind power access to microgrids is not suitable for deep-sea working platforms.

[0006] In order to solve the above technical problems, an embodiment of the present invention provides an energy storage configuration method for a deep-sea working platform, comprising:

[0007] Obtaining internal and external parameters of the deep-sea platform; wherein the internal parameters include: system topology, impedance of interconnecting submarine cables between nodes, maximum transmission capacity of interconnecting submarine cables between nodes, wind turbine capacity, turbine generator capacity at each node, and power load capacity at each node; the external parameters include: wind speed in the sea area adjacent to the offshore platform and price parameters; the price parameters include: energy storage price, gas delivery price, carbon tax price, equipment operation and maintenance price, and discount rate;

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

[0009] Based on the external parameters and the deep-sea working platform model, a first objective function and a first constraint condition are constructed with the goal of maximizing the net present value of configuring energy storage for the deep-sea working platform, and a second objective function and a second constraint condition are constructed with the goal of minimizing the annual system operating cost of the deep-sea working platform;

[0010] Under the constraints of the first and second constraints, the first and second objective functions are solved to determine the rated capacity and rated power of the energy storage for the deep-sea platform that maximize the net present value of energy storage and minimize the annual operating cost of the system. Energy storage for the deep-sea platform is then configured based on the rated capacity and rated power.

[0011] As a preferred solution, under the constraints of the first constraint condition and the second constraint condition, the first objective function and the second objective function are solved to obtain the rated capacity and rated power of the energy storage configured for the deep-sea working platform when the net present value of the energy storage configured for the deep-sea working platform is maximized and the annual operating cost of the system is minimized, including:

[0012] Calculate the annual operating costs of a deep-sea platform without energy storage;

[0013] Calculating an initial rated power and an initial rated capacity of the energy storage configuration of the deep-sea working platform, and solving the second objective function based on the initial rated power and the initial rated capacity, subject to the second constraint, to obtain a minimum annual operating cost of the energy storage configuration of the deep-sea working platform;

[0014] Comparing the minimum annual operating cost with the annual operating cost without energy storage to determine the reduction in annual operating cost;

[0015] Taking the reduction amount as the net cash flow of the deep-sea working platform, and solving the first objective function based on the net cash flow and subject to the first constraint condition to obtain a net present value of the deep-sea working platform system at the initial rated power and initial rated capacity;

[0016] The initial rated power and initial rated capacity of the energy storage configuration of the deep-sea working platform are updated according to the net present value, so as to obtain the rated capacity and rated power of the energy storage configuration of the deep-sea working platform when the net present value of the energy storage configuration of the deep-sea working platform is maximized and the annual operating cost of the system is minimized.

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

[0018]

[0019] Among them, 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 during period t. When the operating power of the energy storage is positive, it indicates discharge, and when it is negative, it indicates charging; n node is the number of nodes in the system; c(i) is the set of all terminal nodes headed by node i; is the voltage amplitude of node i during time period t; is the voltage phase angle difference between nodes i and j during period t; g ij and b ij are the conductance and susceptance of the line between nodes i and j, respectively; is the natural gas intake rate; q g2h is the calorific value of natural gas; 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 during the period t; v in 、v r and v out They are respectively the cut-in wind speed, rated wind speed and cut-out wind speed of the wind turbine.

[0020] As a preferred solution, the first objective function is:

[0021]

[0022] Among them, C NPV is the net present value of energy storage configuration; ny The expected life cycle of energy storage; is the annual net cash flow of energy storage configuration in the yth year; r is the discount rate; and are the rated power and initial rated capacity of energy storage respectively; c P and c E They are the unit rated power price and capacity price of the energy storage system respectively.

[0023] As a preferred solution, the first constraint condition is:

[0024]

[0025] in, and They are and The maximum value of .

[0026] As a preferred solution, the second objective function is:

[0027]

[0028] Among them, C op，y The annual operating cost of energy storage configuration in year y; C gas，y 、 and C carbon,y are the natural gas consumption, energy storage operation and maintenance, gas turbine generator operation and maintenance, and annual carbon tax costs in the yth year of energy storage configuration; n d is the number of the selected typical day; c gas is the sales price of natural gas delivered; is the gas intake rate of the gas turbine generator at node i during period t on a typical day of year y; Δt is the scheduling period interval; and These are the operation and maintenance prices of energy storage and corresponding supporting converters; The operation and maintenance price of the gas turbine generator; is the equivalent operating hours of the gas turbine generator at node i on a typical day d in year y; c carbon is the tax price of CO2 emissions; η g2c The conversion factor for natural gas to CO2; and are the actual operating hours of the gas turbine generator at node i at high, medium, low and very low load levels on a typical day of year y; a H 、a M 、a L and a XLare the equivalent operating time coefficients of the gas turbine generator at high, medium, low and very low load levels on a typical day d in year y, respectively; is the capacity of the energy storage after configuration for y years; β is the annual attenuation coefficient of the energy storage capacity.

[0029] As a preferred solution, the second constraint condition is:

[0030]

[0031]

[0032] in, is the voltage amplitude of node i in period t on a typical day of year y; and They are The upper and lower allowed boundaries of ; is the operating power of device k in node i during period t on a typical day in year y, k∈{'tur','wind','ess'}; and They are The upper and lower bounds of and are the upward ramp rate boundary limit and downward ramp rate boundary limit of the gas turbine generator at node i respectively; is the energy reserve of node i during period t on a typical day d in year y; α U and α L They are the upper and lower allowable coefficients of the energy storage state of charge, respectively.

[0033] Based on the above embodiment, another embodiment of the present invention provides an energy storage configuration device for a deep-sea working platform, comprising: a parameter acquisition module, a model construction module, an objective function construction module, and an energy storage configuration module;

[0034] The parameter acquisition module is used to acquire internal and external parameters of the deep-sea working platform; wherein the internal parameters include: system topology, impedance of the connecting submarine cables between each node, maximum transmission capacity of the connecting submarine cables between each node, wind turbine capacity, turbine generator capacity at each node, and power load capacity at each node; the external parameters include: wind speed in the sea area adjacent to the offshore working platform and price parameters; the price parameters include: energy storage price, gas delivery price, carbon tax price, equipment operation and maintenance price, and discount rate;

[0035] The model building module is used to model the equipment operation process and system network current of the deep-sea working platform according to the internal parameters, and build a corresponding deep-sea working platform model;

[0036] The objective function construction module is used to construct a first objective function and a first constraint condition based on the external parameters and the deep-sea working platform model, with the goal of maximizing the net present value of configuring energy storage for the deep-sea working platform, and to construct a second objective function and a second constraint condition with the goal of minimizing the annual system operating cost of the deep-sea working platform;

[0037] 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 rated power of the energy storage configured for the deep-sea working platform when the net present value of the energy storage configured for the deep-sea working platform is maximized and the annual operating cost of the system is minimized, and then configure the energy storage of the deep-sea working platform according to the rated capacity and rated power.

[0038] Based on the above embodiments, another embodiment of the present invention provides an electronic device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the energy storage configuration method for deep-sea working platforms described in the above embodiments of the invention.

[0039] Based on the above embodiments, another embodiment of the present invention provides a storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute the energy storage configuration method for deep-sea working platforms described in the above embodiments of the invention.

[0040] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0041] The present invention provides an energy storage configuration method for a deep-sea working platform. The method comprises obtaining internal parameters and external parameters of the deep-sea working platform; modeling the equipment 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; constructing a first objective function and a first constraint condition according to the external parameters and the deep-sea working platform model, with the goal of maximizing the net present value of energy storage configured for the deep-sea working platform, and constructing a second objective function and a second constraint condition with the goal of minimizing the annual system operating cost of the deep-sea working platform; solving 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 rated power of the energy storage configured for the deep-sea working platform when the net present value of the energy storage configured for the deep-sea working platform is maximized and the annual system operating cost is minimized, and then configuring the energy storage of the deep-sea working platform according to the rated capacity and rated power.

[0042] The present invention is aimed at deep-sea working platforms, with the goal of maximizing the net present value of energy storage configured for the deep-sea working platform and minimizing the annual operating cost of the system. A corresponding objective function and constraints are constructed, and the objective function is solved under the constraints to obtain an optimal energy storage configuration scheme, that is, the rated capacity and rated power of the energy storage configured for the deep-sea working platform when the net present value of energy storage configured for the deep-sea working platform is maximized and the annual operating cost of the system is minimized. Then, based on the rated capacity and rated power, the optimal energy storage configuration for the deep-sea working platform can be achieved, thereby maintaining the normal operation of the offshore working platform operation scheduling plan. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 This is a flow chart of an energy storage configuration method for a deep-sea working platform provided by one embodiment of the present invention;

[0044] Figure 2 This is an architectural diagram of the dual-layer optimization method for energy storage configuration for deep-sea working platforms of the present invention;

[0045] Figure 3 This is a schematic diagram of the structure of a typical offshore work platform for wind power and energy storage access;

[0046] Figure 4 This is a system structure diagram of an isolated offshore work platform in the South China Sea;

[0047] Figure 5 This is the annual operating data chart of the energy storage life cycle of an isolated offshore platform in the South China Sea;

[0048] Figure 6 This is a graph showing the net present value of energy storage under different investment scenarios using the grid method.

[0049] Figure 7 This is a structural diagram of an energy storage configuration device for a deep-sea working platform provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0050] To make the objectives, technical solutions, and advantages of this application more clear, the technical solutions in this application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of this application.

[0051] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned figure descriptions are intended to cover non-exclusive inclusions.

[0052] In the description of the embodiments of this application, the technical terms "first" and "second" are used only to distinguish different objects and should not be understood to indicate or imply relative importance or implicitly specify the quantity, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, the meaning of "plurality" is more than two, unless otherwise clearly and specifically defined.

[0053] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may 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 refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0054] In the description of the embodiments of this application, the term "and / or" is simply a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent the following three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.

[0055] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0056] In the description of the embodiments of the present application, unless otherwise expressly specified or limited, technical terms such as "installed," "connected," "connected," and "fixed" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integration; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; internal connections between two components or interactions between two components. Those skilled in the art can understand the specific meanings of the above terms in the embodiments of the present application based on specific circumstances.

[0057] Example 1

[0058] Please refer to Figure 1, which is a flow chart of a method for configuring energy storage for a deep-sea working platform according to an embodiment of the present invention, including the following specific steps:

[0059] S1. Obtaining internal and external parameters of the deep-sea working platform; wherein the internal parameters include: system topology, impedance of the connecting submarine cables between each node, maximum transmission capacity of the connecting submarine cables between each node, wind turbine capacity, turbine generator capacity at each node, and power load capacity at each node; the external parameters include: wind speed in the sea area adjacent to the offshore working platform and price parameters; the price parameters include: energy storage price, gas delivery price, carbon tax price, equipment operation and maintenance price, and discount rate;

[0060] For details, please refer to Figure 2 , is an architecture diagram of a two-layer optimization method for energy storage configuration for a deep-sea working platform according to the present invention. The energy storage configuration method for a deep-sea working platform provided by the present invention includes the following steps:

[0061] (1) Collect and set parameters:

[0062] First, the internal parameters and parameters of the deep-sea working platform are obtained. The internal parameters include: physical parameters and system structure parameters such as system topology, impedance and maximum transmission capacity of the submarine cables connecting nodes of the offshore working platform, wind turbine capacity, turbine generator capacity and load capacity at each node; external parameters include: environmental parameters such as wind speed in the sea area near the offshore working platform, as well as economic parameters such as energy storage price, gas delivery price, carbon tax price, equipment operation and maintenance price, discount rate; and particle swarm algorithm parameters such as particle number, individual factor, learning factor, inertia factor, maximum number of iterations, maximum and minimum speed are set.

[0063] S2. Modeling the equipment operation process and system network flow of the deep-sea working platform based on the internal parameters to construct a corresponding deep-sea working platform model;

[0064] Preferably, the deep sea working platform model is:

[0065]

[0066] Among them, 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 during period t. When the operating power of the energy storage is positive, it indicates discharge, and when it is negative, it indicates charging; n nodeis the number of nodes in the system; c(i) is the set of all terminal nodes headed by node i; is the voltage amplitude of node i during time period t; is the voltage phase angle difference between nodes i and j during period t; g ij and b ij are the conductance and susceptance of the line between nodes i and j, respectively; is the natural gas intake rate; q g2h is the calorific value of natural gas; 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 during the period t; v in 、v r and v out They are respectively the cut-in wind speed, rated wind speed and cut-out wind speed of the wind turbine.

[0067] (2) Constructing an offshore work platform model

[0068] Please refer to Figure 3 , is a schematic diagram of the structure of a typical offshore work platform connected to wind power and energy storage. Turbine generators and wind turbines constitute the power supply system of the offshore work platform. The power load is divided into operational load and life load. The operational load mainly includes various induction motors and occupies a dominant position in the load structure. The life load mainly meets the daily needs of the staff, including lighting, air conditioning, communication, etc. For the nodes in the offshore work platform power system, the power flow model is as follows

[0069]

[0070] Where, 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 during period t. When the operating power of the energy storage is positive, it indicates discharge, and when it is negative, it indicates charging; n node is the number of nodes in the system; c(i) is the set of all terminal nodes headed by node i; is the voltage amplitude of node i during time period t; is the voltage phase angle difference between nodes i and j during period t; g ij and b ij are the conductance and susceptance of the line between nodes i and j, respectively.

[0071] The output power of the gas turbine generator can be adjusted by the natural gas intake rate, as shown in the following formula:

[0072]

[0073] Where, is the natural gas intake rate; q g2h is the calorific value of natural gas; η tur is the efficiency of the gas turbine generator.

[0074] The maximum power of a wind turbine in MPPT mode is limited by wind speed, as shown in the following formula:

[0075]

[0076] Where, P r wind,i is the rated power of the wind turbine at node i; v t is the average wind speed during the period t; v in 、v r and v out They are respectively the cut-in wind speed, rated wind speed and cut-out wind speed of the wind turbine.

[0077] It's important to note that the offshore platform model constructed above primarily reflects the equipment's operating mechanism and the power-gas coupling characteristics of the turbine generator. The equipment's operating process and network power flow are incorporated into the constraints of the lower-level optimization algorithm, while fuel consumption from the power-gas coupling is added to the cost of the objective function. This optimizes both the equipment's operating power in the lower-level algorithm and the energy storage capacity in the upper-level algorithm.

[0078] S3. Based on the external parameters and the deep-sea platform model, a first objective function and a first constraint are constructed with the goal of maximizing the net present value of configuring energy storage for the deep-sea platform, and a second objective function and a second constraint are constructed with the goal of minimizing the annual system operating cost of the deep-sea platform;

[0079] Preferably, the first objective function is:

[0080]

[0081] Among them, C NPV is the net present value of energy storage configuration; n y The expected life cycle of energy storage; is the annual net cash flow of energy storage configuration in the yth year; r is the discount rate; and are the rated power and initial rated capacity of energy storage respectively; c P and c EThey are the unit rated power price and capacity price of the energy storage system respectively.

[0082] Preferably, the first constraint condition is:

[0083]

[0084] in, and They are and The maximum value of .

[0085] Preferably, the second objective function is:

[0086]

[0087] Among them, C op，y The annual operating cost of energy storage configuration in year y; C gas，y 、 and C carbon,y are the natural gas consumption, energy storage operation and maintenance, gas turbine generator operation and maintenance, and annual carbon tax costs in the yth year of energy storage configuration; n d is the number of the selected typical day; c gas is the sales price of natural gas delivered; is the gas intake rate of the gas turbine generator at node i during period t on a typical day of year y; Δt is the scheduling period interval; and These are the operation and maintenance prices of energy storage and corresponding supporting converters; The operation and maintenance price of the gas turbine generator; is the equivalent operating hours of the gas turbine generator at node i on a typical day d in year y; c carbon is the tax price of CO2 emissions; η g2c The conversion factor for natural gas to CO2; and are the actual operating hours of the gas turbine generator at node i at high, medium, low and very low load levels on a typical day of year y; a H 、a M 、a L and a XL are the equivalent operating time coefficients of the gas turbine generator at high, medium, low and very low load levels on a typical day d in year y, respectively; is the capacity of the energy storage after configuration for y years; β is the annual attenuation coefficient of the energy storage capacity.

[0088] Preferably, the second constraint condition is:

[0089]

[0090] in, is the voltage amplitude of node i in period t on a typical day of year y; and They are The upper and lower allowed boundaries of ; is the operating power of device k in node i during period t on a typical day in year y, k∈{'tur','wind','ess'}; and They are The upper and lower bounds of and are the upward ramp rate boundary limit and downward ramp rate boundary limit of the gas turbine generator at node i respectively; is the energy reserve of node i during period t on a typical day d in year y; α U and α L They are the upper and lower allowable coefficients of the energy storage state of charge, respectively.

[0091] (3) Setting the objective function and constraints of the upper-level optimization algorithm

[0092] The objective function of the upper-level optimization algorithm is to maximize the net present value of 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 energy storage configuration by optimizing the rated capacity and rated power of the energy storage. The net present value refers to the expected net cash flow discounted at present value, which can appropriately reflect the overall economic benefits of the energy storage system configuration throughout its entire life cycle. Its objective function expression is as follows:

[0093]

[0094] Where C NPV is the net present value of energy storage configuration; n y The expected life cycle of energy storage; is the annual net cash flow of energy storage configuration in the yth year; r is the discount rate; and are the rated power and initial rated capacity of energy storage respectively; c P and c E They are the unit rated power price and capacity price of the energy storage system respectively.

[0095] Based on the space and load-bearing deployment requirements of the offshore work platform, the constraints on the energy storage rated power and rated capacity in the upper-level optimization are set as follows:

[0096]

[0097] Where, and They are and The maximum value of .

[0098] (4) Setting the objective function and constraints of the lower-level optimization algorithm

[0099] The objective function of the lower-level optimization algorithm is to minimize the system's annual operating cost. The decision variables are the operating power of the gas turbine generator, energy storage, and wind turbine in the system at various time periods. The lower-level optimization algorithm aims to minimize annual operating costs by optimizing the operating power of each device. Its objective function is expressed as follows:

[0100]

[0101] Where C op，y The annual operating cost of energy storage configuration in year y; C gas,y 、 and C carbon,y They are respectively the natural gas consumption, energy storage operation and maintenance, gas turbine generator operation and maintenance, and annual carbon tax costs in the yth year of energy storage configuration. The expressions for each item are as follows:

[0102]

[0103] Where n d is the number of the selected typical day; c gas is the sales price of natural gas delivered; is the gas intake rate of the gas turbine generator at node i during period t on a typical day of year y; Δt is the scheduling period interval; and These are the operation and maintenance prices of energy storage and corresponding supporting converters; The operation and maintenance price of the gas turbine generator; is the equivalent operating hours of the gas turbine generator at node i on a typical day d in year y; c carbon is the tax price of CO2 emissions; η g2c The conversion factor for natural gas to CO2; and are the actual operating hours of the gas turbine generator at node i at high, medium, low and very low load levels on a typical day of year y; a H 、a M 、a L and a XL are the equivalent operating time coefficients of the gas turbine generator at high, medium, low and very low load levels on a typical day d in year y, respectively; is the capacity of the energy storage after configuration for y years; β is the annual attenuation coefficient of the energy storage capacity.

[0104] According to the physical parameters and operating boundaries of each device, set the constraints of the lower-level optimization algorithm as follows:

[0105] Formula (1) to (3) (15)

[0106]

[0107] Where, is the voltage amplitude of node i in period t on a typical day of year y; and They are The upper and lower allowed boundaries of ; is the operating power of device k in node i during period t on a typical day in year y, k∈{'tur','wind','ess'}; and They are The upper and lower bounds of and are the upward ramp rate boundary limit and downward ramp rate boundary limit of the gas turbine generator at node i respectively; is the energy reserve of node i during period t on a typical day d in year y; α U and α L They are the upper and lower allowable coefficients of the energy storage state of charge, respectively.

[0108] S4. Under the constraints of the first constraint condition and the second constraint condition, solve the first objective function and the second objective function to obtain the rated capacity and rated power of the energy storage configured for the deep-sea working platform when the net present value of the energy storage configured for the deep-sea working platform is maximized and the annual operating cost of the system is minimized, and then configure the energy storage for the deep-sea working platform according to the rated capacity and rated power.

[0109] 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 rated power of the energy storage configured for the deep-sea working platform when the net present value of the energy storage configured for the deep-sea working platform is maximized and the annual operating cost of the system is minimized, includes: calculating the annual operating cost of the deep-sea working platform when the energy storage is not configured; calculating the initial rated power and initial rated capacity of the energy storage configuration of the deep-sea working platform, and solving the second objective function under the constraints of the second constraint condition based on the initial rated power and initial rated capacity to obtain the minimum annual operating cost of the energy storage configured for the deep-sea working platform; The minimum annual operating cost is compared with the annual operating cost when no energy storage is configured to obtain a reduction in the annual operating cost; the reduction is used as the net cash flow of the deep-sea working platform, and based on the net cash flow, the first objective function is solved under the constraint of the first constraint condition to obtain a net present value of the deep-sea working platform system under the initial rated power and initial rated capacity; based on the net present value, the initial rated power and initial rated capacity of the energy storage configuration of the deep-sea working platform are updated to obtain the rated capacity and rated power of the energy storage configured for the deep-sea working platform when the net present value of the energy storage configured for the deep-sea working platform is maximized and the annual operating cost of the system is minimized.

[0110] (5) Solving the two-level optimization algorithm for energy storage configuration:

[0111] Based on the collected annual wind speed data, several typical days are selected. Based on the wind speeds on these typical days, the lower-level optimization algorithm is used to solve the annual operating cost of the offshore platform without energy storage. In the upper-level optimization algorithm, a particle swarm algorithm is used to generate candidate energy storage configurations. The generated energy storage rated power and capacity are transmitted to the lower-level optimization algorithm to solve for the system's minimum annual operating cost under this energy storage configuration. This cost reduction is compared with the annual operating cost without energy storage, resulting in the net cash flow. The net cash flow is then transmitted to the upper-level optimization algorithm to calculate the net present value of the system under this energy storage configuration. The candidate energy storage configurations are then updated using the particle swarm optimization in the upper-level optimization. The upper-level optimization process continues until the net present value meets the optimization exit criteria, outputting the optimal configuration of energy storage rated power and capacity.

[0112] Specifically, the lower-level optimization algorithm is used to solve the annual operating cost of the offshore platform when it is not equipped with energy storage. In the upper-level optimization algorithm, the particle swarm algorithm is used to generate candidate energy storage configuration schemes. The energy storage rated power and capacity of the generated candidate schemes are transmitted to the lower-level optimization algorithm to solve the minimum annual operating cost of the system under this energy storage configuration scheme. Compared with the annual operating cost when no energy storage is configured, the cost reduction is obtained as the net cash flow. The expression of the obtained net cash flow is:

[0113]

[0114] The net cash flow will be calculated The results are then sent to the upper-level optimization algorithm to calculate the net present value of the system under the current energy storage configuration. The particle swarm in the upper-level optimization process then updates the candidate energy storage configuration. This process continues until the net present value meets the optimization exit criteria, and the optimal configuration of energy storage rated power and capacity is output.

[0115] In a specific embodiment, the present invention uses a simplified model of an isolated offshore platform in the South China Sea to test the proposed energy storage configuration method. Figure 4 The following diagram shows the system architecture of an isolated offshore platform in the South China Sea. The platform is connected to an 8MW wind turbine and powered by three gas turbine generators. To fully reflect the wind speed levels throughout the year, two days at the beginning and middle of each month were selected as typical days. The parameters used in this example are shown in Table 1.

[0116]

[0117]

[0118] Table 1 Example parameters used by an isolated offshore work platform in the South China Sea

[0119] The energy storage configuration scheme is obtained by solving the proposed two-level optimization model. The results show that the energy storage system with a capacity of 0.7972MWh and a rated power of 0.6097MW should be configured, and its initial investment cost is 918,780 yuan. Please refer to Figure 5 , which shows annual operational data over the energy storage lifecycle. Energy storage absorbs wind power during peak wind periods and releases it during low wind periods, thereby reducing gas consumption during self-generated electricity. As a result, offshore platform operators can earn higher revenues through natural gas sales. Furthermore, energy storage reduces the regulation burden of gas turbine generators, optimizing their operating conditions and enabling them to operate longer at moderate loads. This significantly reduces gas turbine generator operation and maintenance costs, and extends their service life with the deployment of energy storage systems.

[0120] As can be seen, the optimized energy storage configuration effectively reduces annual operating costs. The average annual equivalent operating hours of the gas turbine generators were reduced by 4,327 hours, resulting in a reduction of 270,438 yuan in annual maintenance costs. This saves 15,205 cubic meters of natural gas annually, reducing carbon emissions by 28.7 tons. As the energy storage system's capacity decreases annually, its support for the system weakens, leading to a downward trend in net cash flow. However, overall, the net present value of the energy storage over its entire lifecycle reaches 1,845,000 yuan, demonstrating a significant improvement in the overall economic efficiency of the offshore platform.

[0121] The grid method is used to test the net present value of energy storage under different investment plans. The results are as follows: Figure 6 As shown in the figure, energy storage with low rated capacity and power has no significant effect on improving wind power consumption or optimizing gas turbine generator operating conditions. On the other hand, excessively large energy storage capacity or power can lead to redundancy. Given that energy storage prices have not yet significantly decreased, the system operating cost savings from energy storage may not even offset the investment cost, and the net present value may become negative.

[0122] It can be seen that the present invention proposes a two-layer optimization method for energy storage configuration aimed at improving the economic efficiency of wind power consumption on deep-sea working platforms. The upper-layer optimization uses a particle swarm algorithm to maximize the net present value of energy storage over its entire life cycle. The lower-layer optimization uses a commercial solver to formulate a power operation scheduling plan for each device to minimize the annual operating cost, and incorporates the impact of natural gas consumption costs, carbon taxes, and equipment operation and maintenance costs on energy storage configuration into the annual operating cost objective function. Among them, the turbine generator operation and maintenance cost takes into account the impact of wind power volatility on the system turbine generator operating conditions, and converts the turbine generator operation time at different load levels into equivalent operating hours to calculate its operation and maintenance cost.

[0123] Example 2

[0124] Please refer to Figure 7 , is a structural diagram of an energy storage configuration device for a deep-sea working platform provided by an embodiment of the present invention, the device comprising: a parameter acquisition module, a model construction module, an objective function construction module, and an energy storage configuration module;

[0125] The parameter acquisition module is used to acquire internal and external parameters of the deep-sea working platform; wherein the internal parameters include: system topology, impedance of the connecting submarine cables between each node, maximum transmission capacity of the connecting submarine cables between each node, wind turbine capacity, turbine generator capacity at each node, and power load capacity at each node; the external parameters include: wind speed in the sea area adjacent to the offshore working platform and price parameters; the price parameters include: energy storage price, gas delivery price, carbon tax price, equipment operation and maintenance price, and discount rate;

[0126] The model building module is used to model the equipment operation process and system network current of the deep-sea working platform according to the internal parameters, and build a corresponding deep-sea working platform model;

[0127] The objective function construction module is used to construct a first objective function and a first constraint condition based on the external parameters and the deep-sea working platform model, with the goal of maximizing the net present value of configuring energy storage for the deep-sea working platform, and to construct a second objective function and a second constraint condition with the goal of minimizing the annual system operating cost of the deep-sea working platform;

[0128] 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 rated power of the energy storage configured for the deep-sea working platform when the net present value of the energy storage configured for the deep-sea working platform is maximized and the annual operating cost of the system is minimized, and then configure the energy storage of the deep-sea working platform according to the rated capacity and rated power.

[0129] It should be noted that 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 across multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. In addition, in the drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art can understand and implement the present invention without inventive effort.

[0130] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0131] Example 3

[0132] Accordingly, an embodiment of the present invention provides an electronic device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the energy storage configuration method for deep-sea working platforms described in the above-mentioned embodiment of the invention.

[0133] The electronic device may be a computing device such as a desktop computer, a notebook computer, a PDA, a cloud server, etc. The device may include, but is not limited to, a processor and a memory.

[0134] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the device and connects various parts of the entire device using various interfaces and lines.

[0135] Example 4

[0136] Accordingly, an embodiment of the present invention provides a storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute the energy storage configuration method for deep-sea working platforms described in the above-mentioned embodiment of the invention.

[0137] 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 the 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 for a function, etc.; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0138] 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, it can implement the steps of the above-mentioned various method embodiments. The computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained 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, computer-readable media do not include electric carrier signals and telecommunication signals.

[0139] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for configuring energy storage for deep-sea working platforms, characterized in that: include: Obtaining internal and external parameters of the deep-sea platform; wherein the internal parameters include: system topology, impedance of interconnecting submarine cables between nodes, maximum transmission capacity of interconnecting submarine cables between nodes, wind turbine capacity, turbine generator capacity at each node, and power load capacity at each node; the external parameters include: wind speed in the sea area adjacent to the offshore platform and price parameters; the price parameters include: energy storage price, gas delivery price, carbon tax price, equipment operation and maintenance price, and discount rate; Modeling the equipment operation process and system network current of the deep-sea working platform according to the internal parameters, and constructing a corresponding deep-sea working platform model; Based on the external parameters and the deep-sea working platform model, a first objective function and a first constraint condition are constructed with the goal of maximizing the net present value of configuring energy storage for the deep-sea working platform, and a second objective function and a second constraint condition are constructed with the goal of minimizing the annual system operating cost of the deep-sea working platform; Under the constraints of the first and second constraints, solving the first and second objective functions to obtain the rated capacity and rated power of the energy storage configured for the deep-sea working platform when the net present value of configuring the energy storage for the deep-sea working platform is maximized and the annual operating cost of the system is minimized, and then configuring the energy storage for the deep-sea working platform based on the rated capacity and rated power; The deep sea working platform model is: ； ； ； in, 、 、 and are the operating power of the gas turbine generator, energy storage, wind turbine and load at node i during period t. When the operating power of the energy storage is positive, it indicates discharge, and when it is negative, it indicates charging; n node is the number of nodes in the system; c(i) is the set of all terminal nodes headed by node i; is the voltage amplitude of node i during time period t; is the voltage phase angle difference between nodes i and j during period t; and are the conductance and susceptance of the line between nodes i and j, respectively; is the natural gas intake rate; is the calorific value of natural gas; is the efficiency of the gas turbine generator, is the rated power of the wind turbine at node i; v t is the average wind speed during the period t; v in 、v r and v out They are respectively the cut-in wind speed, rated wind speed and cut-out wind speed of the wind turbine; The first objective function is: ； Among them, C NPV is the net present value of energy storage configuration; n y The expected life cycle of energy storage; is the annual net cash flow of energy storage configuration in the yth year; r is the discount rate; and are the rated power and initial rated capacity of energy storage respectively; c P and c E are the unit rated power price and capacity price of the energy storage system respectively; The first constraint condition is: ； ； in, and They are and The maximum value of The second objective function is: ； ； ； ； ； ； ； ； in, The annual operating cost of energy storage configuration in year y; 、 、 and are the natural gas consumption, energy storage operation and maintenance, gas turbine generator operation and maintenance, and annual carbon tax costs in the yth year of energy storage configuration; n d The number of days for the selected typical day; is the sales price of natural gas delivered; is the gas intake rate of the gas turbine generator at node i during period t on a typical day of year y; Δt is the scheduling period interval; and These are the operation and maintenance prices of energy storage and corresponding supporting converters; The operation and maintenance price of the gas turbine generator; is the equivalent operating hours of the gas turbine generator at node i on a typical day d in year y; c carbon is the tax price of CO2 emissions; The conversion factor for natural gas to CO2; 、 、 and are the actual operating hours of the gas turbine generator at node i at high, medium, low and very low load levels on a typical day d in year y, respectively; 、 、 and are the equivalent operating time coefficients of the gas turbine generator at high, medium, low and very low load levels on a typical day d in year y, respectively; is the capacity of the energy storage when it is configured in y years; β is the annual attenuation coefficient of the energy storage capacity; The second constraint is: ； ； ； ； ； ； ； ； in, is the voltage amplitude of node i in period t on a typical day of year y; and They are The upper and lower allowed boundaries of ; is the operating power of device k in node i during period t on a typical day of year y, ; and They are The upper and lower bounds of and are the upward ramp rate boundary limit and downward ramp rate boundary limit of the gas turbine generator at node i respectively; The energy reserve of node i during period t on a typical day d in year y; and They are the upper and lower allowable coefficients of the energy storage state of charge, respectively.

2. The energy storage configuration method for deep-sea working platforms according to claim 1, characterized in that: Under the constraints of the first constraint condition and the second constraint condition, the first objective function and the second objective function are solved to obtain the rated capacity and rated power of the energy storage configured for the deep-sea working platform when the net present value of the energy storage configured for the deep-sea working platform is maximized and the annual operating cost of the system is minimized, including: Calculate the annual operating costs of a deep-sea platform without energy storage; Calculating an initial rated power and an initial rated capacity of the energy storage configuration of the deep-sea working platform, and solving the second objective function based on the initial rated power and the initial rated capacity, subject to the second constraint, to obtain a minimum annual operating cost of the energy storage configuration of the deep-sea working platform; Comparing the minimum annual operating cost with the annual operating cost without energy storage to determine the reduction in annual operating cost; Taking the reduction amount as the net cash flow of the deep-sea working platform, and solving the first objective function based on the net cash flow and subject to the first constraint condition to obtain a net present value of the deep-sea working platform system at the initial rated power and initial rated capacity; The initial rated power and initial rated capacity of the energy storage configuration of the deep-sea working platform are updated according to the net present value, so as to obtain the rated capacity and rated power of the energy storage configuration of the deep-sea working platform when the net present value of the energy storage configuration of the deep-sea working platform is maximized and the annual operating cost of the system is minimized.

3. An energy storage configuration device for deep-sea working platforms, characterized in that: include: Parameter acquisition module, model construction module, objective function construction module and energy storage configuration module; The parameter acquisition module is used to acquire internal and external parameters of the deep-sea working platform; wherein the internal parameters include: system topology, impedance of the connecting submarine cables between each node, maximum transmission capacity of the connecting submarine cables between each node, wind turbine capacity, turbine generator capacity at each node, and power load capacity at each node; the external parameters include: wind speed in the sea area adjacent to the offshore working platform and price parameters; the price parameters include: energy storage price, gas delivery price, carbon tax price, equipment operation and maintenance price, and discount rate; The model building module is used to model the equipment operation process and system network current of the deep-sea working platform according to the internal parameters, and build a corresponding deep-sea working platform model; The deep sea working platform model is: ； ； ； in, 、 、 and are the operating power of the gas turbine generator, energy storage, wind turbine and load at node i during period t. When the operating power of the energy storage is positive, it indicates discharge, and when it is negative, it indicates charging; n node is the number of nodes in the system; c(i) is the set of all terminal nodes headed by node i; is the voltage amplitude of node i during time period t; is the voltage phase angle difference between nodes i and j during period t; and are the conductance and susceptance of the line between nodes i and j, respectively; is the natural gas intake rate; is the calorific value of natural gas; is the efficiency of the gas turbine generator, is the rated power of the wind turbine at node i; v t is the average wind speed during the period t; v in 、v r and v out They are respectively the cut-in wind speed, rated wind speed and cut-out wind speed of the wind turbine; The objective function construction module is used to construct a first objective function and a first constraint condition based on the external parameters and the deep-sea working platform model, with the goal of maximizing the net present value of configuring energy storage for the deep-sea working platform, and to construct a second objective function and a second constraint condition with the goal of minimizing the annual system operating cost of the deep-sea working platform; Wherein, the first objective function is: ； Among them, C NPV is the net present value of energy storage configuration; n y The expected life cycle of energy storage; is the annual net cash flow of energy storage configuration in the yth year; r is the discount rate; and are the rated power and initial rated capacity of energy storage respectively; c P and c E are the unit rated power price and capacity price of the energy storage system respectively; The first constraint condition is: ； ； in, and They are and The maximum value of The second objective function is: ； ； ； ； ； ； ； ； in, The annual operating cost of energy storage configuration in year y; 、 、 and are the natural gas consumption, energy storage operation and maintenance, gas turbine generator operation and maintenance, and annual carbon tax costs in the yth year of energy storage configuration; n d The number of days for the selected typical day; is the sales price of natural gas delivered; is the gas intake rate of the gas turbine generator at node i during period t on a typical day of year y; Δt is the scheduling period interval; and These are the operation and maintenance prices of energy storage and corresponding supporting converters; The operation and maintenance price of the gas turbine generator; is the equivalent operating hours of the gas turbine generator at node i on a typical day d in year y; c carbon is the tax price of CO2 emissions; The conversion factor for natural gas to CO2; 、 、 and are the actual operating hours of the gas turbine generator at node i at high, medium, low and very low load levels on a typical day d in year y, respectively; 、 、 and are the equivalent operating time coefficients of the gas turbine generator at high, medium, low and very low load levels on a typical day d in year y, respectively; is the capacity of the energy storage when it is configured in y years; β is the annual attenuation coefficient of the energy storage capacity; The second constraint is: ； ； ； ； ； ； ； ； in, is the voltage amplitude of node i in period t on a typical day of year y; and They are The upper and lower allowed boundaries of ; is the operating power of device k in node i during period t on a typical day of year y, ; and They are The upper and lower bounds of and are the upward ramp rate boundary limit and downward ramp rate boundary limit of the gas turbine generator at node i respectively; The energy reserve of node i during period t on a typical day d in year y; and They are the upper limit allowable coefficient and the lower limit allowable coefficient of the energy storage state of charge respectively; 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 rated power of the energy storage configured for the deep-sea working platform when the net present value of the energy storage configured for the deep-sea working platform is maximized and the annual operating cost of the system is minimized, and then configure the energy storage of the deep-sea working platform according to the rated capacity and rated power.

4. An electronic device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the method for configuring energy storage for a deep-sea working platform as claimed in any one of claims 1 to 2 is implemented.

5. A storage medium, characterized in that The storage medium includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute the energy storage configuration method for deep-sea working platforms according to any one of claims 1 to 2.

Images