Optimal control method, device and equipment for hybrid energy storage equipment of offshore wind power system and medium

Abstract

The invention discloses a hybrid energy storage equipment optimization control method, device and equipment of an offshore wind power system and a storage medium, and the method comprises the steps: calculating a charging coefficient and a discharging coefficient corresponding to each energy storage equipment according to an energy storage equipment charge state value of each energy storage equipment; according to the state-of-charge value of the storage battery and the state-of-charge value of the super capacitor in each energy storage device, obtaining a power distribution strategy for energy exchange between the storage battery and the super capacitor in each energy storage device; and according to the grid-connected power balance configuration model, taking the minimum throughput total power of the hybrid energy storage equipment as a target, and combining a charging coefficient, a discharging coefficient and a power distribution strategy to obtain a hybrid energy storage equipment optimization control scheme, and performing optimization control on the hybrid energy storage equipment of the offshore wind power system according to the hybrid energy storage equipment optimization control scheme. According to the invention, the hybrid energy storage equipment can be optimally controlled, and the wind power utilization rate and the system operation stability of an offshore wind power system are enhanced.

Description

Technical Field

[0001] The present invention relates to the field of new energy power generation system control technology, and in particular to a hybrid energy storage device optimization control method, device, equipment and medium for an offshore wind power system. Background Art

[0002] The development of offshore wind power systems is an important part of the global energy transformation and renewable energy development. Global offshore wind power installed capacity has grown significantly and is expected to continue to expand rapidly in the next few years. The site selection trend of offshore wind power projects is moving towards larger scale, farther from the coast, and deeper water levels to take advantage of better wind resources and reduce the impact on the nearshore environment.

[0003] Among them, the application of hybrid energy storage equipment in offshore wind power generation systems is one of the key strategies to improve the overall efficiency and stability of the system. Due to its unique geographical location and natural environment, offshore wind power generation faces many challenges, such as intermittent wind power, isolated island operation far away from the land power grid, and harsh marine environment. Hybrid energy storage systems can effectively meet these challenges by combining different types of energy storage technologies. The output power of offshore wind power generation is greatly affected by changes in wind speed. Hybrid energy storage systems (such as those combined with lithium batteries and supercapacitors) can quickly respond to power fluctuations, absorb or release energy, make the output power smoother, and reduce the impact on the power grid. By smoothing the power output, the hybrid energy storage system can reduce the frequent start and stop of wind turbines, reduce the mechanical stress of the equipment, and extend the service life of the equipment.

[0004] However, due to the performance differences between different energy storage devices, such as energy density, power density, response speed, cycle life and cost, they need to be precisely matched and controlled to ensure the efficient operation of the overall system. However, the existing technology is currently unable to achieve optimized control of hybrid energy storage systems and cannot ensure the reliable operation of the system. Summary of the invention

[0005] The present invention provides a hybrid energy storage device optimization control method, device, equipment and medium for an offshore wind power system to solve the technical problem that the prior art cannot achieve the optimization control of the hybrid energy storage system and cannot ensure the reliable operation of the system.

[0006] In order to solve the above technical problems, an embodiment of the present invention provides a hybrid energy storage device optimization control method for an offshore wind power system, comprising:

[0007] Construct a grid-connected power balance configuration model for offshore wind power systems;

[0008] Obtaining the state of charge value of each energy storage device in the offshore wind power system, as well as the battery state of charge value of the battery and the supercapacitor state of charge value of the supercapacitor in each energy storage device;

[0009] Calculate the charging coefficient and discharging coefficient of each energy storage device according to the state of charge value of the energy storage device;

[0010] According to the state of charge value of the battery and the state of charge value of the supercapacitor, a power allocation strategy for energy exchange between the battery and the supercapacitor in each energy storage device is obtained;

[0011] According to the grid-connected power balancing configuration model, with the goal of minimizing the total power throughput of the hybrid energy storage device in the grid-connected power balancing configuration model, and in combination with the charging coefficient, the discharging coefficient and the power allocation strategy, an optimization control scheme for the hybrid energy storage device of the offshore wind power system is obtained, and then the hybrid energy storage device of the offshore wind power system is optimized and controlled according to the optimization control scheme for the hybrid energy storage device.

[0012] As a preferred solution, the grid-connected power balancing configuration model of the offshore wind power system is:

[0013] P hess =P b +P sc ;

[0014] P hess =P WT -P g ;

[0015] Among them, P hess is the total active power throughput of the hybrid energy storage in the offshore wind power system, P b and P sc are the active power handled by the battery and the active power handled by the supercapacitor in each energy storage device, P g and P WT They are the grid-connected power of the hybrid energy storage device and the output power of the offshore wind farm respectively.

[0016] As a preferred solution, the charging coefficient corresponding to each energy storage device is calculated by the following formula:

[0017]

[0018] Among them, k ch is the charging coefficient corresponding to each energy storage device, and SOC is the state of charge value of the energy storage device.

[0019] As a preferred solution, the discharge coefficient corresponding to each energy storage device is calculated by the following formula:

[0020]

[0021] Among them, k dis is the discharge coefficient corresponding to each energy storage device.

[0022] As a preferred solution, the power allocation strategy for energy exchange between the battery and the supercapacitor is:

[0023] When SOC b (t)∈(0,0.2) and SOC sc (t)∈(0,0.2):

[0024]

[0025] When SOC b (t)∈(0,0.2) and SOC sc (t)∈[0.2,1]:

[0026]

[0027] When SOC b (t)∈[0.2,1) and SOC sc (t)∈(0,0.2):

[0028]

[0029] When SOC b (t)∈[0.2,0.8] and SOC sc When (t)∈[0.2,0.8]: there is no need for energy exchange between the battery and the supercapacitor;

[0030] When SOC b (t)∈(0.8,1) and SOC sc (t)∈(0,0.8]:

[0031]

[0032] When SOC b (t)∈(0,0.8] and SOC sc (t)∈(0.8,1):

[0033]

[0034] When SOC b (t)∈(0.8,1) and SOC sc When (t)∈(0.8,1): there is no need for energy exchange between the battery and the supercapacitor;

[0035] Among them, SOC b (t) is the battery state of charge value of the battery in the energy storage device, SOC sc (t) is the supercapacitor charge state value of the supercapacitor in the energy storage device, E bN and EscN They are the rated capacity of the battery and the rated capacity of the supercapacitor respectively.

[0036] On the basis of the above-mentioned embodiment, another embodiment of the present invention provides a hybrid energy storage device optimization control device for an offshore wind power system, comprising: a grid-connected power balance configuration model construction module, an equipment charge state value acquisition module, a charge and discharge power coefficient calculation module, a power allocation strategy generation module and a hybrid energy storage device optimization control module;

[0037] The grid-connected power balance configuration model construction module is used to construct a grid-connected power balance configuration model for an offshore wind power system;

[0038] The device state of charge value acquisition module is used to obtain the energy storage device state of charge value of each energy storage device in the offshore wind power system, as well as the battery state of charge value of the battery in each energy storage device and the supercapacitor state of charge value of the supercapacitor;

[0039] The charging and discharging coefficient calculation module is used to calculate the charging coefficient and discharging coefficient corresponding to each energy storage device according to the state of charge value of the energy storage device;

[0040] The power allocation strategy generation module is used to obtain a power allocation strategy for energy exchange between the battery and the supercapacitor in each energy storage device according to the state of charge value of the battery and the state of charge value of the supercapacitor;

[0041] The hybrid energy storage device optimization control module is used to obtain an optimization control scheme for the hybrid energy storage device of the offshore wind power system according to the grid-connected power balance configuration model, with the goal of minimizing the total power throughput of the hybrid energy storage device in the grid-connected power balance configuration model, and in combination with the charging coefficient, the discharging coefficient and the power allocation strategy, and then optimize the control of the hybrid energy storage device of the offshore wind power system according to the hybrid energy storage device optimization control scheme.

[0042] As a preferred solution, the charging coefficient corresponding to each energy storage device is calculated by the following formula:

[0043]

[0044] Among them, k ch is the charging coefficient corresponding to each energy storage device, and SOC is the state of charge value of the energy storage device.

[0045] As a preferred solution, the discharge coefficient corresponding to each energy storage device is calculated by the following formula:

[0046]

[0047] Among them, k dis is the discharge coefficient corresponding to each energy storage device.

[0048] 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, and when the processor executes the computer program, the hybrid energy storage device optimization control method of the offshore wind power system described in the above invention embodiment is implemented.

[0049] 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 hybrid energy storage device optimization control method for the offshore wind power system described in the above invention embodiment.

[0050] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0051] The present invention provides a hybrid energy storage device optimization control method for an offshore wind power system. First, a grid-connected power balancing configuration model for the offshore wind power system is constructed. Then, the energy storage device charge state value of each energy storage device in the offshore wind power system, as well as the battery charge state value of the battery in each energy storage device and the supercapacitor charge state value of the supercapacitor are obtained.

[0052] Then, according to the state of charge value of the energy storage device, the charging coefficient and the discharging coefficient corresponding to each energy storage device are calculated. For the SOC values ​​of different energy storage devices, the corresponding charging and discharging coefficients are calculated to achieve fast charging when the SOC value is low and fast discharging when the SOC value is high. According to the state of charge value of the battery and the state of charge value of the supercapacitor, the power allocation strategy for energy exchange between the battery and the supercapacitor in each energy storage device is obtained; further, since the adjustment of the charging and discharging coefficient has certain limitations and cannot completely solve the SOC over-limit problem of the energy storage device, the power allocation strategy for energy exchange between the battery and the supercapacitor hybrid energy storage is obtained, and precise SOC control is used to ensure that the hybrid energy storage works within an efficient optimized control range and reduce the SOC over-limit rate of the battery and the supercapacitor.

[0053] Finally, according to the grid-connected power balance configuration model, with the goal of minimizing the total power throughput of the hybrid energy storage device in the grid-connected power balance configuration model, and combined with the charging coefficient, discharge coefficient and power allocation strategy, an optimization control scheme for the hybrid energy storage device of the offshore wind power system is obtained, and then the hybrid energy storage device of the offshore wind power system is optimized and controlled according to the optimization control scheme for the hybrid energy storage device. The present invention can optimize the control of the hybrid energy storage device, thereby enhancing the wind power utilization rate and system operation stability of the offshore wind power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a flow chart of a hybrid energy storage device optimization control method for an offshore wind power system provided by an embodiment of the present invention;

[0055] Figure 2 It is a structural schematic diagram of a hybrid energy storage device optimization control device for an offshore wind power system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are 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 creative work are within the scope of protection of this application.

[0057] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field 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" in the specification and claims of this application and the above-mentioned figure descriptions and any variations thereof are intended to cover non-exclusive inclusions.

[0058] In the description of the embodiments of the present application, the technical terms "first", "second", etc. 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 clearly and specifically defined.

[0059] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0060] 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, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0061] 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).

[0062] In the description of the embodiments of the present application, unless otherwise clearly specified and limited, technical terms such as "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, and it can be the internal connection of two elements or the interaction relationship between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present application can be understood according to the specific circumstances.

[0063] Embodiment 1

[0064] Please refer to Figure 1 , is a flow chart of a hybrid energy storage device optimization control method for an offshore wind power system provided by an embodiment of the present invention, comprising the following specific steps:

[0065] S1. Construct a grid-connected power balance configuration model for offshore wind power systems;

[0066] Preferably, the grid-connected power balancing configuration model of the offshore wind power system is:

[0067] P hess =P b +P sc ;

[0068] P hess =P WT -P g ;

[0069] Among them, P hess is the total active power throughput of the hybrid energy storage in the offshore wind power system, P b and P sc are the active power handled by the battery and the active power handled by the supercapacitor in each energy storage device, P g and P WT They are the grid-connected power of the hybrid energy storage device and the output power of the offshore wind farm respectively.

[0070] Specifically, the hybrid energy storage device optimization control method of the present invention comprises the following steps:

[0071] Step 1: Establish a grid-connected power balance configuration model for offshore wind power systems

[0072] The offshore wind power system includes offshore wind power plants, hybrid energy storage devices, power electronic conversion devices, and DC cables. The hybrid energy storage device includes batteries and supercapacitors. The batteries are used for the throughput of low-frequency components, while the supercapacitors are used for the throughput of high-frequency components. In the offshore wind power system, the active power of the hybrid energy storage device has the following balance:

[0073] P hess =P b +P sc ;

[0074] P hess =P WT -P g ;

[0075] Among them, P hess is the total active power of the hybrid energy storage throughput, P b and P sc is the active power handled by the battery and supercapacitor, P g and P WT It is the grid-connected power and the output power of the offshore wind farm. Part of the active power output of the offshore wind farm is connected to the grid according to the dispatching requirements, and the rest is stored in the hybrid energy storage device.

[0076] The output power of offshore wind farms should be connected to the grid to the maximum extent, and the rest should be stored in the hybrid energy storage system. Therefore, the minimum total power throughput of the hybrid energy storage device is the decisive condition for maximizing the grid-connected power. That is, the larger the grid-connected amount, the less energy the hybrid energy storage device absorbs or releases, and the more economic benefits can be maximized.

[0077] S2, obtaining the state of charge value of each energy storage device in the offshore wind power system, as well as the battery state of charge value of the battery in each energy storage device and the supercapacitor state of charge value of the supercapacitor;

[0078] Step 2: Design hybrid energy storage device control strategy

[0079] During the charging and discharging process of the hybrid energy storage device, it is also necessary to improve the charging and discharging efficiency to ensure the healthy operation of the energy storage device. Among them, the state of charge (SOC) is an important parameter to measure the healthy operation of the energy storage device. The SOC value (i.e. the state of charge value of the energy storage device) of each energy storage device in the offshore wind power system is obtained in different time periods. Calling the appropriate charging and discharging coefficient can ensure the healthy operation of the energy storage device, thereby maintaining the safe and stable operation of the entire offshore wind power system.

[0080] S3. Calculate the charging coefficient and discharging coefficient corresponding to each energy storage device according to the state of charge value of the energy storage device;

[0081] Preferably, the charging coefficient corresponding to each energy storage device is calculated by the following formula:

[0082]

[0083] Among them, k ch is the charging coefficient corresponding to each energy storage device, and SOC is the state of charge value of the energy storage device.

[0084] Preferably, the discharge coefficient corresponding to each energy storage device is calculated by the following formula:

[0085]

[0086] Among them, k dis is the discharge coefficient corresponding to each energy storage device.

[0087] Step 2.1, design different charging coefficients according to different SOC values ​​of energy storage devices;

[0088] When the SOC(t)∈(0,0.2) obtained at time t, the SOC of the energy storage device is lower than the normal operating range, which is an abnormal state. A larger charging coefficient needs to be selected to quickly restore the SOC value; when SOC(t)∈[0.2,0.8], the SOC is in the normal operating range, which is a normal state and does not need to be adjusted; when SOC(t)∈(0.8,1), the SOC is higher than the normal operating range, which is an abnormal state. To avoid overcharging, a smaller charging coefficient is selected. Therefore, different charging coefficients k are designed according to different SOC values. ch :

[0089]

[0090] Step 2.2, design different discharge coefficients according to different SOC values ​​of energy storage devices;

[0091] When SOC(t)∈(0,0.2) obtained at time t, the SOC of the energy storage device is lower than the normal operating range, and a smaller discharge coefficient needs to be selected to avoid over-discharge; when SOC(t)∈[0.2,0.8], the SOC is in the normal operating range and no adjustment is required; when SOC(t)∈(0.8,1), the SOC is higher than the normal operating range, and a larger discharge coefficient is selected. Therefore, different discharge coefficients kd are designed according to different SOC values:

[0092]

[0093] S4. Obtaining a power allocation strategy for energy exchange between the battery and the supercapacitor in each energy storage device according to the battery state of charge value and the supercapacitor state of charge value;

[0094] Preferably, the power allocation strategy for energy exchange between the battery and the supercapacitor is:

[0095] When SOC b (t)∈(0,0.2) and SOC sc (t)∈(0,0.2):

[0096]

[0097] When SOC b (t)∈(0,0.2) and SOC sc (t)∈[0.2,1]:

[0098]

[0099] When SOC b (t)∈[0.2,1) and SOC sc (t)∈(0,0.2):

[0100]

[0101] When SOC b (t)∈[0.2,0.8] and SOC sc When (t)∈[0.2,0.8]: there is no need for energy exchange between the battery and the supercapacitor;

[0102] When SOC b (t)∈(0.8,1) and SOC sc (t)∈(0,0.8]:

[0103]

[0104] When SOC b (t)∈(0,0.8] and SOC sc (t)∈(0.8,1):

[0105]

[0106] When SOC b (t)∈(0.8,1) and SOC sc When (t)∈(0.8,1): there is no need for energy exchange between the battery and the supercapacitor;

[0107] Among them, SOC b (t) is the battery state of charge value of the battery in the energy storage device, SOC sc (t) is the supercapacitor charge state value of the supercapacitor in the energy storage device, E bN and E scN They are the rated capacity of the battery and the rated capacity of the supercapacitor respectively.

[0108] Step 2.3, obtaining the battery state of charge value of the battery in each energy storage device and the supercapacitor state of charge value of the supercapacitor, and designing an adaptive control strategy for the hybrid energy storage device for the combination of different SOC values ​​of the battery and the supercapacitor in the hybrid energy storage device;

[0109] In step 2.1 and step 2.2, the charge and discharge coefficient adjustment function has certain limitations and cannot completely solve the SOC over-limit problem of the energy storage device. Therefore, in this step, for the combination of different SOC values ​​of batteries and supercapacitors in the hybrid energy storage device, based on the charge and discharge coefficient adjustment function, a power secondary distribution strategy for energy exchange between batteries and supercapacitors is designed. The conservation of the total power of the hybrid energy storage device is taken as the basic criterion. By realizing the energy exchange between batteries and supercapacitors, the SOC over-limit rate of batteries and supercapacitors is reduced.

[0110] The SOC value of the battery at time t is expressed as SOC b (t), the SOC value of the supercapacitor at time t is expressed as SOC sc (t).

[0111] ①When SOC b (t)∈(0,0.2), SOC sc When (t)∈(0,0.2), it means that at time t, the SOC values ​​of the battery and supercapacitor are insufficient. In order to reduce the SOC over-limit rate of the hybrid energy storage system, at low SOC, first ensure that the supercapacitor SOC is not over-discharged. The SOC calculation of the battery and supercapacitor at this moment is designed as follows:

[0112]

[0113] In the formula, E bN and E scN are the rated capacities of the battery and supercapacitor respectively.

[0114] ②When SOC b (t)∈(0,0.2), SOC sc (t)∈[0.2,1], it means that at time t, the battery SOC value is insufficient and the supercapacitor SOC value is in a normal state. In order to reduce the SOC over-limit rate of the hybrid energy storage system and ensure that the supercapacitor SOC is not over-discharged, it is allowed to transfer power to the battery to restore the battery SOC. The SOC calculation of the battery and supercapacitor at this moment is designed as follows:

[0115]

[0116] ③When SOC b (t)∈[0.2,1), SOC scWhen (t)∈(0,0.2), it means that at time t, the battery SOC value is in a normal state, and the supercapacitor SOC value is insufficient. In order to reduce the SOC over-limit rate of the hybrid energy storage system and ensure that the battery SOC is not over-discharged, the supercapacitor is allowed to transfer power to restore the supercapacitor SOC. The SOC calculation of the battery and supercapacitor at this moment is designed as follows:

[0117]

[0118] ④When SOC b When SOC(t)∈[0.2,0.8] and SOCsc(t)∈[0.2,0.8], the battery SOC value and the supercapacitor SOC value are both in normal state, and no secondary power distribution is required.

[0119] ⑤When SOC b (t)∈(0.8,1), SOC sc (t)∈(0,0.8], it means that at time t, the battery SOC value is at a high state, and the supercapacitor SOC value is insufficient or normal. In order to reduce the SOC over-limit rate of the hybrid energy storage system and ensure that the battery SOC is not over-discharged, the supercapacitor is allowed to transfer power to the supercapacitor so that the SOC of the two can be balanced, the SOC calculation of the battery and supercapacitor at this moment is designed as follows:

[0120]

[0121] ⑥When SOC b (t)∈(0,0.8], SOC sc When (t)∈(0.8,1), it means that at time t, the battery SOC value is in a low or normal state, and the supercapacitor SOC value is high. In order to reduce the SOC over-limit rate of the hybrid energy storage system and ensure that the supercapacitor SOC is not over-discharged, it is allowed to transfer power to the battery to balance the SOC. The SOC calculation of the battery and supercapacitor at this moment is designed as follows:

[0122]

[0123] ⑦When SOC b (t)∈(0.8,1), SOC sc When (t)∈(0.8,1), it means that at time t, the SOC values ​​of the battery and supercapacitor are both at a high level, and energy needs to be released to reduce the SOC to a normal range. At this moment, there is no need for secondary power distribution.

[0124] S5. According to the grid-connected power balancing configuration model, with the goal of minimizing the total power throughput of the hybrid energy storage device in the grid-connected power balancing configuration model, and in combination with the charging coefficient, discharging coefficient and power allocation strategy, an optimization control scheme for the hybrid energy storage device of the offshore wind power system is obtained, and then the hybrid energy storage device of the offshore wind power system is optimized and controlled according to the optimization control scheme for the hybrid energy storage device.

[0125] Step 3: According to the grid-connected power balance configuration model, with the goal of minimizing the total power throughput of the hybrid energy storage equipment in the grid-connected power balance configuration model, and combining the charging coefficient, discharge coefficient and power allocation strategy, an optimal control scheme for the hybrid energy storage equipment of the offshore wind power system is obtained, and the hybrid energy storage equipment of the offshore wind power system is optimized and controlled.

[0126] It can be seen that the present invention provides an optimization control method for hybrid energy storage equipment of an offshore wind power system. Through the present invention, firstly, a charge and discharge coefficient adjustment function is designed for the SOC values ​​of different energy storage devices, so as to achieve fast charging when the SOC value is low and fast discharging when the SOC value is high; further, since the charge and discharge coefficient adjustment function has certain limitations and cannot completely solve the SOC over-limit problem of the energy storage device, a hybrid energy storage energy exchange strategy is designed for 7 different SOC combinations of batteries and supercapacitors, and precise SOC control is used to ensure that the hybrid energy storage works within an efficient optimization control range, reduce the SOC over-limit rate of batteries and supercapacitors, optimize the performance of the hybrid energy storage equipment, extend the service life, reduce the investment cost, and enhance the wind power utilization rate and system operation stability of the offshore wind power system.

[0127] Embodiment 2

[0128] Please refer to Figure 2 , is a structural schematic diagram of a hybrid energy storage device optimization control device for an offshore wind power system provided by an embodiment of the present invention, the device comprising: a grid-connected power balancing configuration model construction module, an equipment charge state value acquisition module, a charge and discharge power coefficient calculation module, a power allocation strategy generation module and a hybrid energy storage device optimization control module;

[0129] The grid-connected power balance configuration model construction module is used to construct a grid-connected power balance configuration model for an offshore wind power system;

[0130] The device state of charge value acquisition module is used to obtain the energy storage device state of charge value of each energy storage device in the offshore wind power system, as well as the battery state of charge value of the battery in each energy storage device and the supercapacitor state of charge value of the supercapacitor;

[0131] The charging and discharging coefficient calculation module is used to calculate the charging coefficient and discharging coefficient corresponding to each energy storage device according to the state of charge value of the energy storage device;

[0132] The power allocation strategy generation module is used to obtain a power allocation strategy for energy exchange between the battery and the supercapacitor in each energy storage device according to the state of charge value of the battery and the state of charge value of the supercapacitor;

[0133] The hybrid energy storage device optimization control module is used to obtain an optimization control scheme for the hybrid energy storage device of the offshore wind power system according to the grid-connected power balance configuration model, with the goal of minimizing the total power throughput of the hybrid energy storage device in the grid-connected power balance configuration model, and in combination with the charging coefficient, the discharging coefficient and the power allocation strategy, and then optimize the control of the hybrid energy storage device of the offshore wind power system according to the hybrid energy storage device optimization control scheme.

[0134] Preferably, the charging coefficient corresponding to each energy storage device is calculated by the following formula:

[0135]

[0136] Among them, k ch is the charging coefficient corresponding to each energy storage device, and SOC is the state of charge value of the energy storage device.

[0137] Preferably, the discharge coefficient corresponding to each energy storage device is calculated by the following formula:

[0138]

[0139] Among them, k dis is the discharge coefficient corresponding to each energy storage device.

[0140] It should be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying 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 may understand and implement it without paying any creative effort.

[0141] Those skilled in the art can 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.

[0142] Embodiment 3

[0143] Accordingly, an embodiment of the present invention provides an electronic device, comprising 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 optimizing and controlling a hybrid energy storage device of an offshore wind power system as described in the above-mentioned embodiment of the invention is implemented.

[0144] The electronic device may be a computing device such as a desktop computer, a notebook, a palm computer, a cloud server, etc. The device may include, but is not limited to, a processor and a memory.

[0145] 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 various interfaces and lines are used to connect various parts of the entire device.

[0146] Embodiment 4

[0147] 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 hybrid energy storage device optimization control method for the offshore wind power system described in the above-mentioned embodiment of the invention.

[0148] 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 Med ia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0149] 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 implemented. Among them, 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, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-On l yMemory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc. 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.

[0150] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle 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 hybrid energy storage device optimization control method for an offshore wind power system, characterized in that: include: Construct a grid-connected power balance configuration model for offshore wind power systems; Obtaining the state of charge value of each energy storage device in the offshore wind power system, as well as the battery state of charge value of the battery and the supercapacitor state of charge value of the supercapacitor in each energy storage device; Calculate the charging coefficient and discharging coefficient of each energy storage device according to the state of charge value of the energy storage device; According to the state of charge value of the battery and the state of charge value of the supercapacitor, a power allocation strategy for energy exchange between the battery and the supercapacitor in each energy storage device is obtained; According to the grid-connected power balancing configuration model, with the goal of minimizing the total power throughput of the hybrid energy storage device in the grid-connected power balancing configuration model, and in combination with the charging coefficient, the discharging coefficient and the power allocation strategy, an optimization control scheme for the hybrid energy storage device of the offshore wind power system is obtained, and then the hybrid energy storage device of the offshore wind power system is optimized and controlled according to the optimization control scheme for the hybrid energy storage device.

2. The hybrid energy storage device optimization control method for an offshore wind power system according to claim 1, characterized in that: The grid-connected power balancing configuration model of offshore wind power system is: P hess =P b +P sc ; P hess =P WT -P g ; Among them, P hess is the total active power throughput of the hybrid energy storage in the offshore wind power system, P b and P sc are the active power handled by the battery and the active power handled by the supercapacitor in each energy storage device, P g and P WT They are the grid-connected power of the hybrid energy storage device and the output power of the offshore wind farm respectively.

3. The hybrid energy storage device optimization control method for an offshore wind power system according to claim 1, characterized in that: The charging coefficient corresponding to each energy storage device is calculated by the following formula: Among them, k ch is the charging coefficient corresponding to each energy storage device, and SOC is the state of charge value of the energy storage device.

4. The hybrid energy storage device optimization control method for an offshore wind power system according to claim 3, characterized in that: The discharge coefficient corresponding to each energy storage device is calculated by the following formula: Among them, k dis is the discharge coefficient corresponding to each energy storage device.

5. The hybrid energy storage device optimization control method for an offshore wind power system according to claim 1, characterized in that: The power allocation strategy for energy exchange between batteries and supercapacitors is: When SOC b (t)∈(0,0.2) and SOC sc (t)∈(0,0.2): When SOC b (t)∈(0,0.2) and SOC sc (t)∈[0.2,1]: When SOC b (t)∈[0.2,1) and SOC sc (t)∈(0,0.2): When SOC b (t)∈[0.2,0.8] and SOC sc When (t)∈[0.2,0.8]: there is no need for energy exchange between the battery and the supercapacitor; When SOC b (t)∈(0.8,1) and SOC sc (t)∈(0,0.8]: When SOC b (t)∈(0,0.8] and SOC sc (t)∈(0.8,1): When SOC b (t)∈(0.8,1) and SOC sc When (t)∈(0.8,1): there is no need for energy exchange between the battery and the supercapacitor; Among them, SOC b (t) is the battery state of charge value of the battery in the energy storage device, SOC sc (t) is the supercapacitor charge state value of the supercapacitor in the energy storage device, E bN and E scN They are the rated capacity of the battery and the rated capacity of the supercapacitor respectively.

6. A hybrid energy storage device optimization control device for an offshore wind power system, characterized in that: include: Grid-connected power balance configuration model building module, equipment charge state value acquisition module, charge and discharge coefficient calculation module, power allocation strategy generation module and hybrid energy storage equipment optimization control module; The grid-connected power balance configuration model construction module is used to construct a grid-connected power balance configuration model for an offshore wind power system; The device state of charge value acquisition module is used to obtain the energy storage device state of charge value of each energy storage device in the offshore wind power system, as well as the battery state of charge value of the battery in each energy storage device and the supercapacitor state of charge value of the supercapacitor; The charging and discharging coefficient calculation module is used to calculate the charging coefficient and discharging coefficient corresponding to each energy storage device according to the state of charge value of the energy storage device; The power allocation strategy generation module is used to obtain a power allocation strategy for energy exchange between the battery and the supercapacitor in each energy storage device according to the state of charge value of the battery and the state of charge value of the supercapacitor; The hybrid energy storage device optimization control module is used to obtain an optimization control scheme for the hybrid energy storage device of the offshore wind power system according to the grid-connected power balance configuration model, with the goal of minimizing the total power throughput of the hybrid energy storage device in the grid-connected power balance configuration model, and in combination with the charging coefficient, the discharging coefficient and the power allocation strategy, and then optimize the control of the hybrid energy storage device of the offshore wind power system according to the hybrid energy storage device optimization control scheme.

7. The hybrid energy storage device optimization control device for an offshore wind power system according to claim 6, characterized in that: The charging coefficient corresponding to each energy storage device is calculated by the following formula: Among them, k ch is the charging coefficient corresponding to each energy storage device, and SOC is the state of charge value of the energy storage device.

8. The hybrid energy storage device optimization control device for an offshore wind power system according to claim 7, characterized in that: The discharge coefficient corresponding to each energy storage device is calculated by the following formula: Among them, k dis is the discharge coefficient corresponding to each energy storage device.

9. An electronic device, characterized in that: It comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, it implements the hybrid energy storage device optimization control method of the offshore wind power system as described in any one of claims 1 to 5.

10. 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 hybrid energy storage device optimization control method for an offshore wind power system as described in any one of claims 1 to 5.

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