Design method and related device of energy storage system of shaguo wasteland view new energy station

Abstract

This invention discloses a design method and related devices for an energy storage system in a desert-based wind and solar power station, belonging to the field of energy storage configuration technology for wind and solar power stations. The method involves collecting environmental parameters of the target desert area and historical operating parameters of the supporting wind and solar power stations, filtering out high-temperature and normal-temperature output datasets, and calculating the output fluctuation range during these periods. Based on the environmental parameters, the method performs basic selection of battery models and protection structures, and uses historical operating parameters of the wind and solar power stations to perform redundancy correction on the selection. It combines the temperature compensation requirements of the desert area with the capacity redundancy requirements of the wind and solar power stations to perform collaborative calculations of the total power of the heating elements and the energy storage design capacity. Based on the output fluctuation range, it sets charging and discharging power limits and heat dissipation mode switching logic under different operating conditions. Finally, based on the environmental parameters of the desert area and the historical wind curtailment rate of the wind and solar power stations, it collaboratively optimizes the self-cleaning cycle and cleaning period of the energy storage system.

Description

Technical Field

[0001] This invention belongs to the field of energy storage configuration technology for wind and solar new energy power stations, and relates to a design method and related devices for an energy storage system of a wind and solar new energy power station in Shagohuang. Background Technology

[0002] As the global energy structure transitions towards clean and low-carbon energy, the proportion of renewable energy, represented by wind and solar power, continues to increase. The construction of large-scale wind and solar power plants in desert and Gobi areas has become an important part of energy strategy. However, wind power output is inherently intermittent, volatile, and random, posing a challenge to the stable operation of the power grid when connected on a large scale. To address this issue, configuring energy storage systems and constructing a collaborative operation model of "renewable energy + energy storage" has become an industry consensus and standard configuration. Energy storage systems can smooth wind power output fluctuations, participate in grid peak shaving and frequency regulation, and improve wind power absorption capacity, making them a key technical means to ensure the safe and stable operation of a grid with a high proportion of renewable energy.

[0003] Currently, the design methods for configuring energy storage systems at wind and solar power plants mostly follow a generalized and template-based approach. These traditional design methods typically only consider the macroscopic output characteristics of the wind and solar power plants themselves (such as rated power and maximum rate of change) and the standard performance parameters of the energy storage equipment, failing to deeply integrate the specific physical environment of the energy storage system and the long-term historical operating characteristics of the specific wind and solar power plants it serves. This disconnect between design and application scenarios exposes increasingly significant limitations in the extremely harsh environments of desert and Gobi regions, mainly in the following aspects: First, the lack of scenario synergy leads to reduced system reliability. Desert and Gobi environments are characterized by extreme high temperatures, huge diurnal temperature variations, and high dust concentrations. These environmental factors not only directly affect the performance degradation rate, cycle life, and safe operation of energy storage equipment (especially electrochemical batteries), but also indirectly affect the operating status of the wind turbine generators themselves. For example, extreme high temperatures may cause a decrease in wind turbine efficiency or trigger load shedding, causing its output curve to exhibit different fluctuation characteristics compared to areas with normal temperatures. Existing design methods treat environmental impact factors and the operational impact of wind and solar power plants as two isolated dimensions, failing to conduct integrated correlation analysis. As a result, the designed energy storage system may suffer from insufficient cooling capacity and accelerated battery degradation when facing the unique "high temperature-high fluctuation" coupled conditions of desert regions, ultimately leading to frequent system failures, increased downtime, and an inability to meet the stringent requirements of long-term stable operation of energy storage systems in desert wind power bases. Second, insufficient consideration of life-cycle costs and efficiency leads to poor economic performance. Generalized template designs often tend to adopt conservative redundancy configurations to ensure safety, easily resulting in "over-design" and high one-time investment costs. However, this approach may overlook the operation and maintenance costs and system efficiency throughout the entire life cycle. In desert environments, sand and dust can clog cooling ducts and filters, exacerbating the equipment's heat dissipation burden. Without intelligent planning of cleaning and maintenance cycles based on local sand and dust frequency and the wind curtailment periods of wind and solar power plants, maintenance costs will surge, and frequent maintenance downtime will also affect power plant revenue. Third, the dynamic response characteristics are mismatched with the actual requirements of the power grid, resulting in poor collaborative stability. Grid commands to energy storage systems often require rapid and precise responses. Due to the unique environmental characteristics of wind and solar power plants in desert areas, the amplitude and rate of power output fluctuations may be more abrupt. Existing design methods based on general data fail to fully utilize recent minute / ten-minute historical power output data from wind and solar power plants for in-depth analysis to identify and quantify the unique fluctuation patterns in desert environments.

[0004] In summary, there is an urgent need in this field for a new energy storage system design method that can break through the limitations of existing general templates, deeply integrate long-term environmental monitoring data of desert areas with detailed historical operation data of wind and solar power plants, and achieve precise and scenario-based design across the entire chain from equipment selection and capacity configuration to control strategies, so as to solve the outstanding problems of adaptability, economy and stability mentioned above. Summary of the Invention

[0005] The purpose of this invention is to provide a design method and related devices for an energy storage system of a wind and solar power plant in Shagohuang, so as to solve the technical problems of poor reliability and stability of traditional design methods in the prior art, and the existence of over-design leading to cost waste.

[0006] To achieve the above objectives, the present invention employs the following technical solution: In a first aspect, the present invention provides a design method for an energy storage system at a wind and solar power plant in Shagohuang, comprising the following steps: Simultaneously collect environmental parameters and historical operating parameters of supporting wind and solar new energy power stations in the target desert area, and filter out the power output datasets for high temperature period and normal temperature period, and then calculate the power output fluctuation range between high temperature period and normal temperature period; Based on the environmental parameters of the desert area, the battery model and protection structure were selected, and the selection was redundantly corrected using the historical operating parameters of the wind and solar new energy power station. The temperature compensation requirements of the desert area are combined with the capacity redundancy requirements of wind and solar new energy power stations to perform a collaborative calculation of the total power of the heating elements and the energy storage design capacity. Based on the output fluctuation range, set charging and discharging power limits and heat dissipation mode switching logic under different operating conditions; Based on the environmental parameters of the Shagohuang area and the historical wind curtailment rate of wind and solar power plants, the self-cleaning cycle and cleaning period of the energy storage system were optimized in a coordinated manner to complete the design of the energy storage system.

[0007] Furthermore, the step of simultaneously collecting environmental parameters of the target desert area and historical operating parameters of the supporting wind and solar power stations, and filtering out high-temperature period output datasets and normal-temperature period output datasets, and then calculating the output fluctuation range between the high-temperature period and the normal-temperature period, specifically includes: Simultaneously collect environmental parameters of the target desert area and historical operating parameters of the supporting wind and solar power stations; the environmental parameters of the desert area include extreme high temperature values ​​(T). max Average diurnal temperature range ΔT, and maximum monthly dust concentration S max The monthly frequency of sandstorms, F; the historical operating parameters of the wind and solar power stations include the historical maximum output surge value ΔP. up The historical maximum output drop value ΔP downRated power P of wind and solar new energy power stations rated Rated energy storage capacity E rated 10-minute output data of wind and solar new energy power stations; Based on the extreme high temperature values ​​in the environmental parameters, the power output data of wind and solar power plants were filtered to obtain the high-temperature period power output dataset P. high and the power output dataset P during normal temperature period normal ; The specific formula for calculating the power output fluctuation range between the high-temperature period and the normal-temperature period is as follows:

[0008] In the formula, For P high Standard deviation; For P normal The standard deviation.

[0009] Furthermore, the steps of making basic selections of battery models and protective structures based on environmental parameters of the desert region, and redundancy corrections to the selections using historical operating parameters of wind and solar power plants, specifically include: Based on the environmental parameters of the desert region, the battery model was selected as follows: the battery's high-temperature capacity retention rate is ≥1-(T max -25℃)×0.005; using historical operating parameters of wind and solar new energy power stations to correct the basic selection, the high-temperature capacity retention rate of the battery is obtained ≥[1-(T max [-25℃) × 0.005 + 5%; The maximum monthly average dust concentration S max IP65 protection is selected when the average monthly dust concentration is ≥500μg / m³. max Select IP55 protection for values ​​<500μg / m³; The power correction formula for a cooling fan is: Final fan power = (T) max -45℃)×0.5+Base fan power×1.1.

[0010] Furthermore, the formula for calculating the total power of the heating element is as follows: P heat =(E rated ×1000 / cell voltage) ×0.1 ×ΔT × (1+ΔP) up / 200) In the formula, E rated ×1000 / individual cell voltage, representing the total capacity of the battery pack; ΔP up / 200 is the power redundancy coefficient caused by fluctuations in wind and solar power plant operations; The formula for calculating the energy storage design capacity is as follows: E design =E rated ×(1+ΔP up / 100)×(1+(T) max -45℃ / 100 In the formula, (1+ΔP) up / 100) is the capacity redundancy coefficient to cope with the sudden increase in the maximum output of wind and solar power plants; (1+(T max (-45℃) / 100) is a redundancy coefficient to cope with the high-temperature capacity decay and increased fluctuations during the high-temperature period in the desert.

[0011] Furthermore, the charge / discharge power limitation includes: When wind power suddenly increases by ΔP up ≥ΔP up ×0.8 and extreme high temperature value T max At ≥45℃, the charge / discharge power limit P limit =P rated ×(1+ΔP up ( / 100)×1.05; When wind power suddenly drops ΔP up ≤-ΔP down ×0.8 and extreme high temperature value T max At ≤15℃, the charge / discharge power limit P limit =P rated ×(1+ΔP down / 100)×0.95; The heat dissipation mode switching logic is as follows: When the extreme high temperature value T max When the temperature is ≥ 45℃ and the power output fluctuation ΔP of the wind and solar power station is ≥ 20%, the heat pipe and fan are used for combined heat dissipation. When 15℃ < extreme high temperature value T max When the temperature is <45℃ and ΔP <20%, only heat pipe cooling is activated; When the extreme high temperature value T max When the temperature is ≤15℃ and ΔP≤-20%, turn off the fan and start the insulation layer and heating element.

[0012] Furthermore, the formula for calculating the self-cleaning cycle is as follows: T clean =24 / (F / 30)×(1-historical wind curtailment rate / 200) In the formula, F / 30 represents the daily average frequency of sandstorms; historical wind curtailment rate / 200 is the wind curtailment rate correction coefficient; T clean This is a self-cleaning cycle; The clean period is preferentially set to be activated during periods when the historical wind curtailment rate of wind and solar new energy power plants is ≥ 10%.

[0013] Furthermore, the method also includes: The designed energy storage system is uniformly verified. If the verification indicators do not meet the preset requirements, the relevant parameters are adjusted synchronously. The verification indicators include: battery temperature ≤ 50℃ during the high temperature period of desertification; battery charge-discharge cycle life ≥ 5000 times during the high temperature period; system output voltage fluctuation ≤ ±5%.

[0014] Secondly, the present invention provides a design system for an energy storage system for a wind and solar power plant in Shagohuang, comprising: The data acquisition module is used to synchronously collect environmental parameters of the target desert area and historical operating parameters of the supporting wind and solar new energy power stations, and to filter out the power output datasets for high-temperature periods and normal-temperature periods, and then calculate the power output fluctuation range between high-temperature periods and normal-temperature periods. The battery and protection selection module is used to make basic selections of battery models and protection structures based on environmental parameters in the desert area, and to perform redundant corrections on the selection using historical operating parameters of wind and solar new energy power stations. The collaborative capacity configuration module is used to combine the temperature compensation requirements of the desert with the capacity redundancy requirements of wind and solar new energy power stations to perform collaborative calculations of the total power of the heating elements and the energy storage design capacity. The operation control strategy setting module is used to set the charging and discharging power limits and heat dissipation mode switching logic under different operating conditions based on the output fluctuation amplitude; The maintenance strategy optimization module is used to coordinate and optimize the self-cleaning cycle and cleaning period of the energy storage system based on the environmental parameters of the desert area and the historical wind curtailment rate of wind and solar new energy power plants, so as to complete the design of the energy storage system.

[0015] Thirdly, the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the energy storage system design method for a desert wind and solar new energy power station as described above.

[0016] Fourthly, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the energy storage system design method for a desert wind and solar new energy power station as described above.

[0017] Compared with the prior art, the present invention has the following beneficial effects: This invention discloses a design method and related devices for an energy storage system in a desert-based wind and solar power plant. By simultaneously collecting and filtering environmental parameters of the target desert area and historical operating parameters of the wind and solar power plant, the system accurately calculates the output fluctuation range under different temperature conditions, providing reliable data support for subsequent design. Based on environmental parameters, the system performs basic selection of batteries and protective structures, and uses historical operating parameters for correction, effectively improving the rationality of the selection and reducing the risk of failure due to environmental factors. By combining desert temperature compensation with the capacity redundancy requirements of the wind and solar power plant, the system collaboratively calculates the heating element power and energy storage capacity, achieving efficient resource utilization and stable system operation. Based on the output fluctuation range, the system sets charging and discharging power limits and heat dissipation mode switching logic, enhancing the system's adaptability and stability under different operating conditions. Simultaneously, by combining desert environmental parameters and historical wind curtailment rates, the system collaboratively optimizes the self-cleaning cycle and time period of the energy storage system, reducing the impact of sand and dust on system performance and extending its service life. This invention integrates environmental data from desert areas and data from wind and solar power plants to design an energy storage system, which improves the system's adaptability to different scenarios, enhances the matching degree between heating element power and capacity redundancy, and avoids cost waste. By linking heat dissipation and power control, it reduces the system downtime rate during periods of high temperature and high fluctuation, thereby improving system stability. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a schematic diagram of the system of the present invention; Figure 3 This is a flowchart illustrating the overall workflow of the system in an embodiment of the present invention. Detailed Implementation

[0020] The present invention will now be described in detail with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other.

[0021] The following detailed description is exemplary and intended to provide further detailed explanation of the invention. Unless otherwise specified, all technical terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. The terminology used in this invention is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention.

[0022] See Figure 1 and Figure 3 This invention discloses a design method for an energy storage system at a wind and solar power plant in the desert region, comprising the following steps: S1, synchronously collect environmental parameters and historical operating parameters of supporting wind and solar new energy power stations in the target desert area, and filter out the power output datasets for high temperature period and normal temperature period, and then calculate the power output fluctuation range between high temperature period and normal temperature period. S101, simultaneously collects historical data for the past 2-3 years on the desert environment and supporting wind and solar power stations in the target area: Environmental parameters of the desert (denoted as group A): A1: Extreme high temperature value T max (°C); A2: Average diurnal temperature range ΔT (°C); A3: Maximum monthly average dust concentration S max (μg / m³); A4: Monthly frequency of sandstorms F (times / month); Parameters of wind and solar new energy power stations (denoted as Group B): B1: The historical maximum output surge value ΔP up (%) B2: Historical maximum output drop ΔP down (%) B3: Rated power P of wind and solar new energy power station rated (kW), rated energy storage capacity E rated (MWh); B4: 10-minute power output data (kW) of wind and solar new energy power stations, data collection period: the past 2-3 years; S102, further correlation calculations were performed to filter the power output data corresponding to the high-temperature period (A1≥45℃) in the desert, denoted as dataset P. high Output data of wind and solar power plants during normal temperature periods (A1 < 45℃) are selected and denoted as dataset P. normal .

[0023] S103, the output fluctuation amplitude is quantified by calculating the standard deviation, as shown in the following formula:

[0024] in, : The i-th power output data (kW) in the dataset; : Average output of the dataset (kW); n: Number of samples in the dataset (strips); n-1: Degrees of freedom.

[0025] The specific formula for calculating the power output fluctuation range between the high-temperature period and the normal-temperature period is as follows:

[0026] In the formula, For P high Standard deviation; For P normal The standard deviation.

[0027] S2, based on the environmental parameters of the desert area, makes basic selection of battery type and protection structure, and uses the historical operating parameters of wind and solar new energy power stations to redundancy correction of the selection; The basic selection is determined using parameters from Group A of the Shagohuang wind and solar power plant, and redundancy is corrected by combining parameters from Group B of the wind and solar power plant, as detailed below: 1. Battery model selection: Basic formula: Battery high-temperature capacity retention rate ≥ 1 - (A1 - 25℃) × 0.005; Corrected data: Industry experimental data shows that under a high temperature environment of 60℃, the capacity of lithium iron phosphate batteries decreases by approximately 1.7% for every additional 100 charge-discharge cycles (normal cycle life: 80% capacity retention after 1000 cycles, i.e., 2% capacity reduction after 100 cycles; under high temperature conditions, the capacity reduction rate increases by 15%, resulting in a 2.3% capacity reduction after 100 cycles). Assuming an average annual charge-discharge cycle count of 800 at room temperature, the average annual cycle count increases by 30% at high temperatures, resulting in 800 × (1 + 30%) = 1040 cycles, 240 more than at room temperature. The additional capacity reduction is approximately 5.5% (240 cycles / 100 cycles) × 2.3%. Considering the redundancy simplification principle in engineering design, this is rounded down to 5%, meaning the final capacity retention requirement is the base value + 5%, which is used to select the appropriate battery model.

[0028] 2. Selection of protective structure and heat dissipation: Protection level: S max (A3) For values ​​≥500 μg / m³, select IP65 protection. max (A3) When <500μg / m³, select IP55 protection, and the dustproof mesh aperture (mm) = dust particle diameter × 0.5; Cooling fan power correction: Due to the increased converter losses when the output of wind and solar new energy power stations suddenly increases, and the fluctuations are more drastic during high-temperature periods, the fan power needs to be increased by an additional 10%. The final fan power (W) = (A1-45℃)×0.5 + base fan power (W)×1.1, where the base fan power is the fan power benchmark value adapted for normal temperature period (A1<45℃).

[0029] S3 combines the temperature compensation requirements of the desert with the capacity redundancy requirements of wind and solar new energy power stations to perform collaborative calculations on the total power of the heating elements and the energy storage design capacity. By combining the temperature compensation requirements of desert wastelands with the capacity redundancy requirements of wind and solar power plants, double calculations can be avoided. 1. Total power of heating elements: Formula: P heat (W) = (E) rated ×1000 / cell voltage) ×0.1 ×ΔT × (1+ΔP) up / 200) Where: E rated ×1000 / individual cell voltage, representing the total capacity of the battery pack (Ah); ΔP up / 200 is the power redundancy coefficient caused by fluctuations in wind and solar power plant operations; 2. Energy storage design capacity: Formula: E design (MWh) = E rated ×(1+ΔP up / 100)×(1+(A1-45℃) / 100) in: (1+ΔP) up / 100) is the capacity redundancy coefficient to cope with the sudden increase in the maximum output of wind and solar power plants; (1+(A1-45℃) / 100) is a redundancy coefficient to cope with the high-temperature capacity decay and increased fluctuations during the high-temperature period in the desert.

[0030] S4 sets charging and discharging power limits and heat dissipation mode switching logic under different operating conditions based on the output fluctuation range; Based on the power output fluctuation range of wind and solar power plants, the desert cooling mode is switched synchronously without the need to set separate thresholds. 1. Charge / discharge power limit: When wind power surges (ΔP ≥ ΔP) up When A1 ≥ 45℃ (×0.8), P limit =P rated ×(1+ΔP up / 100)×1.05 (1.05 is the extra redundancy factor for high temperature to cope with high fluctuation scenarios); When wind power drops sharply (ΔP≤-ΔP) down When (×0.8) and A1≤15℃: P limit =P rated ×(1+ΔP down ( / 100)×0.95 (0.95 is the low-temperature power protection factor to avoid over-discharge of the battery). 2. Cooling mode switching: When A1≥45℃ and ΔP (power output fluctuation of wind and solar new energy power station)≥20% (high fluctuation of wind power), it is heat pipe + fan. The formula for calculating fan wind speed is: wind speed (m / s) = (A1-45℃)×0.2+3.5; When 15℃ < A1 < 45℃ and ΔP < 20% (low fluctuations in wind power), only heat pipes are used; When A1≤15℃ and ΔP≤-20% (wind power drops sharply), turn off the fan + insulation layer + heating element and start.

[0031] S5, based on the environmental parameters of the desert area and the historical wind curtailment rate of wind and solar new energy power plants, coordinates and optimizes the self-cleaning cycle and cleaning period of the energy storage system to complete the energy storage system design.

[0032] The cleaning cycle is adjusted according to the frequency of sandstorms, and is also linked to the wind curtailment periods of wind and solar power plants to avoid conflicts between cleaning and power supply. 1. Dust self-cleaning cycle: Formula: T clean (hours) = 24 / (F / 30) × (1 - historical wind curtailment rate / 200) Where: F / 30 is the average daily frequency of sandstorms (times / day); 1-historical wind curtailment rate / 200 is the wind curtailment rate correction coefficient, which reduces the cleaning frequency outside the wind curtailment period; 2. Selection of cleaning time period: Prioritize cleaning during periods when the historical wind curtailment rate of wind and solar new energy power stations is ≥10% to avoid affecting normal charging and discharging.

[0033] S6, Dual-Scene Parameter Verification and Fine-Tuning: Unified verification of relevant indicators for desert wastelands and wind and solar power plants; if not met, adjustments are made accordingly. Verification indicators: ① Battery temperature ≤ 50℃ during the high-temperature period in the desert; ② Battery charge-discharge cycle life ≥ 5000 cycles during the high-temperature period; ③ System output voltage fluctuation ≤ ±5%; Fine-tuning logic: If the battery temperature exceeds 50°C during high-temperature periods, the fan speed will increase by 0.5 m / s, and the capacity redundancy coefficient will increase by 2%; if the battery cycle life is less than 5000 cycles during high-temperature periods, a battery model with a higher cycle life will be used; if the voltage fluctuation exceeds ±5%, the charging and discharging power limit threshold will be adjusted by ±5%.

[0034] See Figure 2This invention discloses an energy storage system design system for a wind and solar power station in Shagohuang, including a data acquisition module, a battery and protection selection module, a collaborative capacity configuration module, an operation control strategy setting module, and a maintenance strategy optimization module. The system comprises several modules: a data acquisition module for synchronously collecting environmental parameters of the target desert region and historical operating parameters of the supporting wind and solar power plants; a battery and protection selection module for basic selection of battery models and protection structures based on environmental parameters of the desert region, and redundancy correction using historical operating parameters of the wind and solar power plants; a collaborative capacity configuration module for combining desert temperature compensation requirements with capacity redundancy requirements of the wind and solar power plants to perform collaborative calculations of the total power of the heating elements and the energy storage design capacity; an operation control strategy setting module for setting charging and discharging power limits and heat dissipation mode switching logic under different operating conditions based on output fluctuations; and a maintenance strategy optimization module for collaboratively optimizing the self-cleaning cycle and cleaning period of the energy storage system based on environmental parameters of the desert region and historical wind curtailment rates of the wind and solar power plants, thus completing the energy storage system design. This invention, by integrating desert environmental data with historical data from wind and solar power plants for integrated design, completely overcomes the shortcomings of traditional template-based methods. The impact of high temperatures on power output fluctuations was precisely quantified, and battery selection, heat dissipation power correction, and coordinated control were implemented accordingly. This ensured the energy storage system was highly compatible with the desert wind and solar power plant landscape, significantly improving operational reliability and stability. In terms of economic cost, innovative collaborative calculation models (such as combining temperature compensation with capacity redundancy) avoided over- or under-design, achieving end-to-end cost optimization from equipment selection to maintenance strategies (such as cleaning cycles based on wind curtailment rates), significantly improving the project's lifecycle economics. This resulted in a synergistic improvement in the reliability, economy, and grid friendliness of the energy storage system under extreme environments.

[0035] In one embodiment of the present invention, a computer device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to achieve a corresponding method flow or corresponding function. The processor described in this embodiment of the present invention can be used in the operation of an energy storage system design method for a wind and solar renewable energy power station in Shagohuang.

[0036] This invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the energy storage system design method for a desert wind and solar renewable energy power station in the above embodiments.

[0037] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0038] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0039] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0040] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0041] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A design method for an energy storage system of a wind and solar renewable energy power station in the desert region, characterized in that, Includes the following steps: Simultaneously collect environmental parameters and historical operating parameters of supporting wind and solar new energy power stations in the target desert area, and filter out the power output datasets for high temperature period and normal temperature period, and then calculate the power output fluctuation range between high temperature period and normal temperature period; Based on the environmental parameters of the desert region, the basic selection of battery models and protective structures is carried out, and the selection is redundancy-corrected using historical operating parameters of wind and solar new energy power stations; specifically including: The environmental parameters of the Shaguo barren area are used for basic selection of the battery model, and the following is obtained: the high-temperature capacity retention rate of the battery is ≥1- (T max -25℃)×0.005; the historical operation parameters of the wind-solar new energy station are used to correct the basic selection, and the high-temperature capacity retention rate of the battery is ≥[1- (T max -25℃)×0.005] + 5%; T max is an extreme high temperature value. IP65 protection is selected when the maximum monthly average dust concentration S max ≥ 500 μg / m³, IP55 protection is selected when the maximum monthly average dust concentration S max < 500 μg / m³; S max is the maximum monthly average dust concentration; The power correction formula of the heat dissipation fan is: final fan power = (T max -45℃) x 0.5 + base fan power x 1.1; The temperature compensation requirements of the desert area are combined with the capacity redundancy requirements of wind and solar new energy power stations to perform a collaborative calculation of the total power of the heating elements and the energy storage design capacity. The formula for calculating the total power of the heating element is: P heat = (E rated × 1000 / cell voltage) x 0.1 x ΔT x (1 + ΔP up / 200) In the formula, E rated ×1000 / battery cell voltage, the total capacity of the battery pack; ΔP up / 200 is the power redundancy coefficient caused by the sudden increase of the maximum output of the wind-solar new energy station; ΔT is the average value of the day-night temperature difference; P heat is the total power of the heating sheet; The formula for calculating the energy storage design capacity is as follows: E design =E rated × (1 + ΔP up / 100) x (1 + (T max - 45°C) / 100) In the formula, (1+ΔP) up / 100) is the capacity redundancy coefficient to cope with the sudden increase in the maximum output of wind and solar power plants; (1+(T max (-45℃) / 100) is a redundancy factor to cope with the high-temperature capacity decay and increased fluctuations during the high-temperature period in the desert; E rated E is the rated energy storage capacity. design Designed capacity for energy storage; Based on the output fluctuation range, set charging and discharging power limits and heat dissipation mode switching logic under different operating conditions; The charge / discharge power limitation includes: When wind power suddenly increases by ΔP up ≥ΔP up ×0.8 and extreme high temperature value T max At ≥45℃, the charge / discharge power limit P limit =P rated ×(1+ΔP up / 100)×1.05; ΔP up This represents the largest increase in output in history; P rated Rated power of wind and solar power plants When wind power suddenly drops ΔP up ≤-ΔP down ×0.8 and extreme high temperature value T max At ≤15℃, the charge / discharge power limit P limit =P rated ×(1+ΔP down / 100)×0.95; ΔP down The largest drop in output in history The heat dissipation mode switching logic is as follows: When the extreme high temperature value T max When the temperature is ≥ 45℃ and the power output fluctuation ΔP of the wind and solar power station is ≥ 20%, the heat pipe and fan are used for combined heat dissipation. When 15℃ < extreme high temperature value T max When the temperature is <45℃ and ΔP <20%, only heat pipe cooling is activated; When the extreme high temperature value T max When the temperature is ≤15℃ and ΔP≤-20%, turn off the fan and start the insulation layer and heating element; Based on the daily frequency of sandstorms in the Shagohuang area and the historical wind curtailment rate of wind and solar power plants, the self-cleaning cycle and cleaning period of the energy storage system were optimized in a coordinated manner to complete the design of the energy storage system.

2. The energy storage system design method for a wind and solar power station in the desert region according to claim 1, characterized in that, The steps of synchronously collecting environmental parameters and historical operating parameters of the supporting wind and solar power plants in the target desert area, filtering out high-temperature and normal-temperature power output datasets, and then calculating the power output fluctuation range between the high-temperature and normal-temperature periods specifically include: Simultaneously collect environmental parameters of the target desert area and historical operating parameters of the supporting wind and solar power stations; the environmental parameters of the desert area include extreme high temperature values ​​(T). max Average diurnal temperature range ΔT, and maximum monthly dust concentration S max The monthly frequency of sandstorms, F; the historical operating parameters of the wind and solar power stations include the historical maximum output surge value ΔP. up The historical maximum output drop value ΔP down Rated power P of wind and solar new energy power stations rated Rated energy storage capacity E rated 10-minute output data of wind and solar new energy power stations; Based on the extreme high temperature values ​​in the environmental parameters, the power output data of wind and solar power plants were filtered to obtain the high-temperature period power output dataset P. high and the power output dataset P during normal temperature period normal ; The specific formula for calculating the power output fluctuation range between the high-temperature period and the normal-temperature period is as follows: In the formula, For P high Standard deviation; For P normal The standard deviation.

3. The energy storage system design method for a desert wind-solar new energy power station according to claim 1, characterized in that, The formula for calculating the self-cleaning cycle is: T clean =24 / (F / 30)×(1-historical wind curtailment rate / 200) In the formula, F / 30 represents the daily average frequency of sandstorms; historical wind curtailment rate / 200 is the wind curtailment rate correction coefficient; T clean This is a self-cleaning cycle; The clean period is preferentially set to be activated during periods when the historical wind curtailment rate of wind and solar new energy power plants is ≥ 10%.

4. The energy storage system design method for a wind and solar renewable energy power station in the desert region according to claim 1, characterized in that, Also includes: The completed energy storage system is uniformly verified. If the verification indicators do not meet the preset requirements, the relevant parameters are adjusted synchronously. The verification indicators include: battery temperature ≤ 50℃ during the high-temperature period of the desert; Battery charge-discharge cycle life at high temperatures ≥ 5000 cycles; system output voltage fluctuation ≤ ±5%.

5. A design system for an energy storage system of a wind and solar renewable energy power station in the desert region, characterized in that, A design method for an energy storage system of a wind-solar renewable energy power station in Shagohuang, based on any one of claims 1 to 4, includes: The data acquisition module is used to synchronously collect environmental parameters of the target desert area and historical operating parameters of the supporting wind and solar new energy power stations, and to filter out the power output datasets for high-temperature periods and normal-temperature periods, and then calculate the power output fluctuation range between high-temperature periods and normal-temperature periods. The battery and protection selection module is used to make basic selections of battery models and protection structures based on environmental parameters in the desert area, and to perform redundant corrections on the selection using historical operating parameters of wind and solar new energy power stations. The collaborative capacity configuration module is used to combine the temperature compensation requirements of the desert with the capacity redundancy requirements of wind and solar new energy power stations to perform collaborative calculations of the total power of the heating elements and the energy storage design capacity. The operation control strategy setting module is used to set the charging and discharging power limits and heat dissipation mode switching logic under different operating conditions based on the output fluctuation amplitude; The maintenance strategy optimization module is used to coordinate and optimize the self-cleaning cycle and cleaning period of the energy storage system based on the environmental parameters of the desert area and the historical wind curtailment rate of wind and solar new energy power plants, so as to complete the design of the energy storage system.

6. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the energy storage system design method for the Shagohuang wind and solar new energy power station as described in any one of claims 1-4.

7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the energy storage system design method for the Shagohuang wind and solar new energy power station as described in any one of claims 1-4.

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