Optimal configuration method and device for energy storage of new energy base

Abstract

The invention provides an optimal configuration method and device for energy storage of a new energy base, and can be applied to the technical field of frequency control and energy storage optimal configuration of a new energy power system. The method comprises the following steps: constructing a target inertia of a new energy storage system based on respective system parameters of a plurality of new energy storage systems included in a target new energy base; determining operation and maintenance resources of the target new energy base based on a preset demand of the target new energy base and the respective operation parameters and system parameters of the plurality of new energy storage systems; under the condition that the target new energy base is subjected to virtual disturbance, frequency response analysis is carried out on the fluctuation frequency of energy storage of the disturbed target new energy base, and an analysis result is obtained; and on the basis of the analysis result, the disturbance power of the virtual disturbance, and the transmission power, the energy storage capacity and the charging and discharging power of the target new energy base, constructing constraint conditions, and on the basis of operation and maintenance resources, satisfying an optimization target to adjust system parameters to obtain target system parameters.

Description

Technical Field

[0001] This disclosure relates to the field of frequency control and energy storage optimization configuration technology for new energy power systems, specifically to an optimization configuration method and device for energy storage in new energy bases. Background Technology

[0002] With the development and maturation of new energy technologies, new energy bases relying entirely on renewable energy sources have emerged in regions with excellent wind and solar conditions, such as deserts, wastelands, and Gobi. However, due to the lack of traditional thermal power support in these new energy bases, their inertia is extremely low, frequency stability is poor, and they are prone to drastic frequency fluctuations under disturbances, leading to system instability. Electrochemical energy storage systems, due to their rapid response capabilities, are widely used in frequency support and power balance regulation in new energy bases, and are an important way to construct virtual inertia for new energy systems.

[0003] In implementing this disclosure, it was discovered that related technologies typically configure electrochemical energy storage systems based on a single-frequency response modeling approach, meaning they only consider expanding electrochemical energy storage capacity and improving the ability of new energy bases to cope with disturbances. However, this configuration method does not take into account the dynamic coupling between virtual inertia and system output, resulting in excessively large energy storage capacity and wasted resources. Summary of the Invention

[0004] In view of the above problems, this disclosure provides an optimized configuration method and device for energy storage in new energy bases.

[0005] According to the first aspect of this disclosure, an optimized configuration method for energy storage in a new energy base is provided, comprising: constructing target inertia for multiple new energy storage systems based on the system parameters of each of the multiple new energy storage systems included in the target new energy base, wherein the new energy storage systems include a first energy storage system based on mechanical power generation and a second energy storage system based on photovoltaic power generation, and the system parameters include rated energy storage capacity and rated power; determining the operation and maintenance resources of the target new energy base based on the preset requirements of the target new energy base, the operating parameters of each of the multiple new energy storage systems, and the system parameters; performing frequency response analysis on the fluctuation frequency of the energy storage of the target new energy base after the disturbance, based on the target inertia, under the condition that the target new energy base is subjected to a virtual disturbance, and obtaining the analysis results, wherein the analysis results are used to represent the disturbance resistance capability of the target new energy base; constructing constraints based on the analysis results, the disturbance power of the virtual disturbance, the transmission power, energy storage capacity, and charging and discharging power of the target new energy base, and adjusting the system parameters based on the constraints and the operation and maintenance resources to meet the optimization objective, thereby obtaining the target system parameters.

[0006] The second aspect of this disclosure provides an optimized configuration device for energy storage in a new energy base, comprising: an inertia construction module, used to construct the target inertia of multiple new energy storage systems based on the system parameters of each of the multiple new energy storage systems included in the target new energy base, wherein the new energy storage systems include a first energy storage system based on mechanical power generation and a second energy storage system based on photovoltaic power generation, and the system parameters include rated energy storage capacity and rated power; a resource determination module, used to determine the operation and maintenance resources of the target new energy base based on the preset requirements of the target new energy base, the operating parameters of each of the multiple new energy storage systems, and the system parameters; and a disturbance analysis module, used for... When the target new energy base is subjected to a virtual disturbance, a frequency response analysis is performed on the target new energy base based on the target inertia to obtain the analysis results. The frequency response analysis is used to analyze the fluctuation frequency of the energy storage of the target new energy base after the disturbance, and the analysis results are used to represent the disturbance resistance capability of the target new energy base. The parameter adjustment module is used to construct constraints based on the analysis results, the disturbance power of the virtual disturbance, the transmission power of the target new energy base, the energy storage capacity, and the charging and discharging power. Based on the constraints, the system parameters are adjusted to obtain the target system parameters. Under the target system parameters, the operation and maintenance resources meet the optimization objective.

[0007] According to embodiments of this disclosure, a target inertia is constructed based on the system parameters of multiple new energy storage systems in a target new energy base. This allows for the quantitative simulation of the inertial response characteristics of the new energy system, addressing the problem of poor frequency stability caused by the lack of traditional thermal power inertia support in new energy storage systems. During configuration optimization, operation and maintenance resources are determined by combining preset requirements and operating parameters, achieving economic evaluation. Furthermore, frequency response analysis under virtual disturbances quantifies the system's anti-disturbance capability. Adjusting system parameters based on the analysis results and constraints optimizes the energy storage configuration scale while balancing steady-state economics and transient security, ensuring a balance between frequency stability of the new energy base and the economics of energy storage investment. Attached Figure Description

[0008] The foregoing contents, as well as other objects, features, and advantages of this disclosure, will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0009] Figure 1 This diagram illustrates an application scenario of an optimized configuration method and apparatus for energy storage in a new energy base according to embodiments of the present disclosure.

[0010] Figure 2 A flowchart illustrating an optimized configuration method for energy storage in a new energy base according to an embodiment of the present disclosure is shown in the schematic diagram.

[0011] Figure 3This diagram schematically illustrates the frequency response of a new energy base to disturbances after optimization using the energy storage optimization configuration method for a new energy base according to an embodiment of this disclosure.

[0012] Figure 4 The diagram illustrates the daily operation results after optimization of the energy storage optimization configuration method for a new energy base according to an embodiment of the present disclosure.

[0013] Figure 5 A frequency line graph illustrating the optimized configuration method for energy storage in a new energy base according to an embodiment of the present disclosure is shown schematically.

[0014] Figure 6 This schematically illustrates a structural block diagram of an optimized configuration device for energy storage in a new energy base according to an embodiment of the present disclosure; and

[0015] Figure 7 A block diagram of an electronic device suitable for implementing an optimized configuration method for energy storage in a new energy base, according to an embodiment of the present disclosure, is shown schematically. Detailed Implementation

[0016] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0017] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0018] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0019] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0020] Figure 1 The illustration shows an application scenario of the optimized configuration method and apparatus for energy storage in a new energy base according to an embodiment of the present disclosure.

[0021] like Figure 1 As shown, the application scenario 100 according to this embodiment may include a first new energy storage system 101, a second new energy storage system 102, a third new energy storage system 103, a fourth new energy storage system 104, and a server 105. The first new energy storage system 101, the second new energy storage system 102, the third new energy storage system 103, the fourth new energy storage system 104, and the server 105 are communicatively connected, and the first new energy storage system 101, the second new energy storage system 102, the third new energy storage system 103, and the fourth new energy storage system 104 can transmit current to each other.

[0022] The first new energy storage system 101 and the second new energy storage system 102 can be a first energy storage system based on mechanical power generation. The first energy storage system includes at least one mechanical power generation device and at least one energy storage device.

[0023] The third new energy storage system 103 and the fourth new energy storage system 104 can be second energy storage systems based on photovoltaic power generation. The second energy storage system includes at least one photovoltaic power generation device and at least one energy storage device.

[0024] Server 105 can collect power generation data from the first new energy storage system 101, the second new energy storage system 102, the third new energy storage system 103, and the fourth new energy storage system 104. When fluctuations occur in the overall power generation and frequency of the multiple new energy storage systems within the entire new energy base, server 105 controls the discharge or storage of energy in the storage devices of these systems to maintain the overall balance of the new energy base. Server 105 can also calculate and adjust the system parameters of the multiple new energy storage systems based on the intensity of potential disturbances, thereby improving the anti-interference capability and operational stability of the new energy base.

[0025] It should be noted that the optimized configuration method for energy storage in new energy bases provided in this embodiment can generally be executed by server 105. Correspondingly, the optimized configuration device for energy storage in new energy bases provided in this embodiment can generally be located in server 105. The optimized configuration method for energy storage in new energy bases provided in this embodiment can also be executed by a server or server cluster that is different from server 105 and capable of communicating with the first new energy storage system 101, the second new energy storage system 102, the third new energy storage system 103, the fourth new energy storage system 104, and / or server 105. Correspondingly, the optimized configuration device for energy storage in new energy bases provided in this embodiment can also be located in a server or server cluster that is different from server 105 and capable of communicating with the first new energy storage system 101, the second new energy storage system 102, the third new energy storage system 103, the fourth new energy storage system 104, and / or server 105.

[0026] It should be understood that Figure 1 The number of new energy storage systems and servers shown is merely illustrative. Depending on the implementation requirements, any number of new energy storage systems and servers can be included.

[0027] The following will be based on Figure 1 The described scene, through Figures 2-5 The method for optimizing the configuration of energy storage in a new energy base according to embodiments of this disclosure will be described in detail.

[0028] Figure 2 A flowchart illustrating an optimized configuration method for energy storage in a new energy base according to an embodiment of the present disclosure is shown.

[0029] like Figure 2 As shown, the optimized configuration method for energy storage in the new energy base in this embodiment includes operations S210 to S240.

[0030] In operation S210, the target inertia of multiple new energy storage systems is constructed based on the system parameters of each of the multiple new energy storage systems included in the target new energy base.

[0031] According to embodiments of this disclosure, the target new energy base may include multiple new energy storage systems and multiple new energy power generation systems, wherein the new energy power generation systems each include devices for generating electricity using new energy sources such as wind and solar power.

[0032] According to embodiments of this disclosure, the new energy storage system includes a first energy storage system that uses wind power to drive machinery and generates electricity based on the machinery, and a second energy storage system that generates electricity based on photovoltaic power. The system parameters include rated energy storage capacity and rated power.

[0033] According to embodiments of this disclosure, the target inertia represents the property of rotating equipment such as motors and rotors to resist changes in their state of motion. For example, when the active power supplied by the power system increases, rotating equipment such as rotors absorbs excess kinetic energy to accelerate rotation, thereby suppressing an excessively rapid increase in frequency. When the active power supplied by the power system decreases, rotating equipment such as rotors continues to rotate due to the target inertia, releasing kinetic energy to provide some active power to make up for the active power shortfall, thereby suppressing the rate of frequency decrease.

[0034] According to embodiments of this disclosure, the target inertia of the first energy storage system and the second energy storage system can be constructed based on their respective system parameters.

[0035] In operating S220, based on the preset requirements of the target new energy base, the operating parameters and system parameters of each of the multiple new energy storage systems, the operation and maintenance resources of the target new energy base are determined.

[0036] According to embodiments of this disclosure, the preset requirements include the power and capacity requirements that the target new energy base can provide. The system parameters of the new energy storage system include parameters such as the rated power and rated capacity of the new energy storage system. The operating parameters of the new energy storage system include parameters such as the depreciation rate and maintenance costs of the new energy storage system.

[0037] According to embodiments of this disclosure, based on the preset requirements of the target new energy base and the operating parameters of the new energy storage system, the number of new energy storage systems required to be deployed in the target new energy base can be determined, provided that the preset requirements are met. Based on the required number of systems and the operating parameters of the new energy storage systems, the operation and maintenance resources required during the operation and maintenance of the target new energy base can be further determined.

[0038] According to embodiments of this disclosure, operation and maintenance resources refer to various cost resources involved in the planning, construction and operation of the target new energy base, which may include the investment cost, maintenance cost and overall operating cost of the grid-type new energy storage system.

[0039] In operation S230, under the condition that the target new energy base is subjected to virtual disturbance, frequency response analysis is performed on the fluctuation frequency of the energy storage of the target new energy base after the disturbance based on the target inertia, and the analysis results are obtained.

[0040] According to embodiments of this disclosure, during the daily operation of a new energy base, the unstable active power of the base due to factors such as wind power and solar intensity can disrupt the power balance of the entire power grid and affect power safety.

[0041] Therefore, a virtual disturbance can be generated based on the historical data of the target new energy base and applied to the target new energy base. Under the action of the target inertia, the target new energy base will resist the virtual disturbance to reduce the impact of the virtual disturbance on the power of the target new energy base.

[0042] According to embodiments of this disclosure, frequency response analysis can be performed on the fluctuation frequency of energy storage in a target new energy base after disturbance, and analysis results can be obtained. These analysis results represent the disturbance resistance capability of the target new energy base.

[0043] In operation S240, constraints are constructed based on the analysis results, the disturbance power of the virtual disturbance, the transmission power, energy storage capacity, and charging and discharging power of the target new energy base. Based on the constraints and the operation and maintenance resources to meet the optimization objectives, the system parameters are adjusted to obtain the target system parameters.

[0044] According to embodiments of this disclosure, sub-constraints on the disturbance immunity of a target new energy base can be determined based on the disturbance power of the virtual disturbance and the corresponding analysis results. Sub-constraints on the capability requirements of the target new energy base are constructed based on its transmission power, energy storage capacity, and charging / discharging power requirements. Constraints are then obtained based on these multiple sub-constraints.

[0045] According to embodiments of this disclosure, the optimization objective can represent minimizing operational resources. Therefore, system parameters can be adjusted under constraints to obtain minimized operational resources while satisfying the constraints. After adjustment, the target system parameters are obtained.

[0046] According to embodiments of this disclosure, a target inertia is constructed based on the system parameters of multiple new energy storage systems in a target new energy base. This allows for the quantitative simulation of the inertial response characteristics of the new energy system, addressing the problem of poor frequency stability caused by the lack of traditional thermal power inertia support in new energy storage systems. During configuration optimization, operation and maintenance resources are determined by combining preset requirements and operating parameters, achieving economic evaluation. Furthermore, frequency response analysis under virtual disturbances quantifies the system's anti-disturbance capability. Adjusting system parameters based on the analysis results and constraints optimizes the energy storage configuration scale while balancing steady-state economics and transient security, ensuring a balance between frequency stability of the new energy base and the economics of energy storage investment.

[0047] According to embodiments of this disclosure, the operation and maintenance resources of a target new energy base are determined based on the respective operating parameters and system parameters of multiple new energy storage systems, including: determining the average resources of multiple energy devices based on the one-time resources of each energy device included in each new energy storage system and the lifespan of each energy device; and determining the operation and maintenance resources based on the multiple average resources and the operating resources of the target new energy base.

[0048] According to embodiments of this disclosure, the one-time resources for each energy device may include the resources required to purchase the energy device and the resources required for its destruction or recycling upon retirement. Based on the quotient of one-time resources and the lifespan of the energy device, the average resources required by each of the multiple energy devices for a given period of their lifespan can be obtained.

[0049] Among them, based on the discount rate r and the rated capacity E of the energy equipment B,ESS Lifespan of energy equipment (L) ESS The rated power P of energy equipment in a grid-type new energy storage system B,ESS Unit power investment cost c p and unit capacity investment cost c e It can determine the average resource C of energy equipment. in As shown in formula (1):

[0050] (1)

[0051] According to embodiments of this disclosure, the operating resources of the target new energy base include the maintenance resources required for the maintenance of energy equipment within the target new energy base. Specifically, maintenance resources are calculated based on unit capacity. m Maintenance costs j and the rated capacity E of energy equipment B,ESS It can be determined that maintenance resource C m As shown in formula (2):

[0052] (2)

[0053] According to embodiments of this disclosure, the operating resources of the target new energy base also include the supporting electricity cost C provided by the system under typical scenario q. tr,q New energy backup cost C r,q and the cost of penalties for abandoning renewable energy C pu,q .

[0054] Among them, the transmission electricity price c during time period t can be used as a reference. ele,t AC system support power P tr,qt Determine the supporting electricity cost C tr,q As shown in formula (3):

[0055] (3)

[0056] The reserve rate β of wind power generation can be used as a reference. w The theoretical generating power P of wind farms and photovoltaic power plants during time period t wav,qt The reserve rate β of photovoltaic power generation s The actual generated power P of wind farms and photovoltaic power plants during time period t sav,qt Determine the backup cost C of new energy sources. r,q As shown in formula (4):

[0057] (4)

[0058] According to the penalty for abandoned renewable energy during time period t pu,t The theoretical generating power P of wind farms and photovoltaic power plants during time period t wav,qt The actual generated power P of wind farms and photovoltaic power stations during time period t sav,qt The theoretical generating power P of the wind farm during time period t w,qt The theoretical power generation capacity P of the photovoltaic power station during time period t s,qt Determine the penalty cost C for abandoning renewable energy. pu,q As shown in formula (5):

[0059] (5)

[0060] According to embodiments of this disclosure, based on the supporting power cost C tr,q New energy backup cost C r,q and the cost of penalties for abandoning renewable energy C pu,q The average operating resource C in the operating resources can be determined. o As shown in formula (6):

[0061] (6)

[0062] Where, η q Let q represent the probability of occurrence in a typical scenario.

[0063] According to embodiments of this disclosure, based on the average resource C of the energy equipment in Maintenance Resources C m Average operating resources C o It is possible to determine the operation and maintenance resources. F As shown in formula (7):

[0064] (7)

[0065] Where, γ f This is the penalty coefficient for transient frequency instability.

[0066] According to embodiments of this disclosure, by calculating the one-time resources and service life of energy equipment in a new energy storage system to determine the average resources, and then combining the operating resources to determine the operation and maintenance resources, the planning, construction and operation costs of the energy storage system can be comprehensively quantified, providing accurate optimization indicators for optimization objectives, and ensuring that the energy storage configuration scheme meets technical requirements while achieving optimal control of investment costs and operating costs.

[0067] According to embodiments of this disclosure, the constraints include resource constraints and performance constraints. Resource constraints are used to ensure that the target new energy base meets resource requirements, and performance constraints are used to ensure that the target new energy base maintains stable operation in the presence of disturbances. Constraints are constructed based on analysis results, the disturbance power of the virtual disturbance, the transmission power, energy storage capacity, and charging / discharging power of the target new energy base. This includes: determining resource constraints based on the transmission power of the target new energy base and a preset transmission power threshold; and determining performance constraints based on analysis results, the disturbance power of the virtual disturbance, and the energy storage capacity and charging / discharging power of the target new energy base.

[0068] According to embodiments of this disclosure, resource constraints are used to represent sub-constraints on the capacity requirements of the target new energy base. Performance constraints are used to represent sub-constraints on the disturbance immunity of the target new energy base.

[0069] According to embodiments of this disclosure, based on the actual transmission power P of the target new energy base during time period t... dc,t And the preset transmission power threshold, i.e., the maximum transmission power P dc max and minimum transmission power P dc min The first sub-constraint condition can be constructed, as shown in formula (8):

[0070] (8)

[0071] The binary state variable u is adjusted upwards based on the target new energy base. up,t Downward-adjusted binary state variable u down,t Maximum gradeability power limit R up max Maximum landslide power limit R down max And the actual transmission power P of the target new energy base during time period t. dc,t The actual transmission power P of the target new energy base during the t-1 time period dc,t-1 It is possible to construct a second constraint sub-condition, as shown in formula (9):

[0072] (9)

[0073] According to the upward-adjusted binary state variable u up,t Downward-adjusted binary state variable u down,t and the maximum number of power adjustments allowed within the scheduling period N con It is possible to construct a third constraint sub-condition, as shown in formula (10):

[0074] (10)

[0075] According to the upward-adjusted binary state variable u up,t Downward-adjusted binary state variable u down,t and the number of preset time periods N T It is possible to construct a fourth constraint sub-condition, as shown in formula (11):

[0076] (11)

[0077] According to embodiments of this disclosure, the resource constraints constituted by the first, second, third, and fourth constraint sub-conditions described above can constrain the transmission power, the rate of change of transmission power, and the speed of change of the target new energy base.

[0078] According to embodiments of this disclosure, at the instant of being subjected to a virtual disturbance, the target new energy base will generate a virtual synchronous inertia due to the effect of the target inertia. This virtual synchronous inertia H U,t0 The transient frequency change technical specifications in the relevant regulations of the power system need to be met in order to avoid exceeding the maximum frequency change rate and causing malfunction of the relay protection device. Therefore, the fifth constraint sub-condition is as shown in formula (12):

[0079] (12)

[0080] Among them, F RocoF P represents the maximum rate of change of frequency specified in the standard. ds H represents the preset disturbance power specified in the standard. W,lt0 P represents the real-time virtual synchronous inertia of the l-th wind farm. B,l P represents the l-th wind farm B,l H ESS,t0 This represents the real-time virtual synchronous inertia of energy equipment in a grid-type new energy storage system. The subscript t0 indicates the instant of disturbance, and f0 indicates the system frequency.

[0081] According to embodiments of this disclosure, the maximum frequency deviation requirement Δf can also be considered. max Quasi-steady-state deviation limit Δf ss The time required for the system to reach quasi-steady state (TS), and the frequency deviation of the new energy base. Quasi-steady-state deviation of new energy base Construct the sixth constraint sub-condition, as shown in formula (13):

[0082] (13)

[0083] The new energy base also needs to meet the power constraints for its participation in inertial response and primary frequency regulation, namely the seventh constraint sub-condition, as shown in formula (14):

[0084] (14)

[0085] Where α represents the maximum temporary allowable charge / discharge ratio; P c,z P represents the charging power at point z. d,z This represents the discharge power at point z.

[0086] In addition, the new energy base also needs to meet the power consumption limit constraint, namely the eighth constraint sub-condition, as shown in formula (15):

[0087] (15)

[0088] Among them, E ESS,mint Indicates the minimum capacity required to participate in the frequency response, E ESS,t This indicates the real-time capacity participating in the frequency response.

[0089] According to the embodiments of this disclosure, the constraints are divided into resource constraints and performance constraints. Resource constraints can ensure that the target new energy base meets the actual resource requirements such as UHVDC power transmission limits and ramping limits, avoiding equipment overload or frequent adjustments. Performance constraints can also ensure the frequency stability of the system under disturbances and limit the energy storage power to maintain the system's operational safety, thus achieving a dual guarantee of rational resource utilization and stable system operation.

[0090] According to embodiments of this disclosure, adjusting system parameters based on constraints to obtain target system parameters includes: repeatedly performing the following operations until the target system parameters are determined: adjusting system parameters according to optimization objectives based on resource constraints to obtain updated system parameters; updating operation and maintenance resources based on performance constraints if the updated system parameters do not meet performance constraints; and using the updated system parameters as target system parameters if the updated system parameters meet performance constraints.

[0091] According to embodiments of this disclosure, after adjusting the system parameters based on resource constraints and optimization objectives, the resulting updated system parameters are those with the lowest operational and maintenance resources among the system parameters that can meet the resource requirements of the target new energy base. However, the updated system parameters may exceed performance constraints; therefore, further constraints and adjustments to the system parameters are needed using performance constraints.

[0092] According to embodiments of this disclosure, after obtaining the updated system parameters, they are checked using performance constraints. If it is determined that the updated system parameters do not meet the performance constraints, the operation and maintenance resources are updated based on the performance constraints. Using the updated operation and maintenance resources, and based on the resource constraints, the system parameters are further adjusted according to the optimization objective until the adjusted updated system parameters meet the performance constraints. The updated system parameters can then be used as the target system parameters.

[0093] According to embodiments of this disclosure, by repeatedly executing the iterative process of parameter optimization, system parameters can be continuously optimized under resource constraints. When the updated parameters do not meet performance constraints, the parameters are forced to be adjusted through dynamic updates of operation and maintenance resources, ultimately ensuring that the target system parameters simultaneously meet resource and performance requirements, achieving precise optimization of energy storage configuration, and improving system stability and economy.

[0094] According to embodiments of this disclosure, updating operation and maintenance resources based on performance constraints includes: determining the out-of-limit status of updated system parameters based on performance constraints, wherein the out-of-limit status represents the ratio by which the updated system parameters exceed the performance constraints; determining a penalty factor based on the out-of-limit status; constructing performance constraint terms based on the penalty factor and performance constraints; and updating operation and maintenance resources using the performance constraint terms.

[0095] According to embodiments of this disclosure, the updated system parameters are checked to identify sub-parameters that do not meet performance constraints. Based on the sub-parameters and the corresponding sub-constraints within the performance constraints, the extent to which the sub-parameters exceed their limits relative to the sub-constraints is determined.

[0096] According to embodiments of this disclosure, a penalty factor corresponding to the constraint is determined based on the exceedance situation, wherein the exceedance situation indicates that the higher the ratio of the updated system parameters exceeding the performance constraint, the larger the corresponding penalty factor. A performance constraint term is constructed based on the product of the penalty factor and the performance constraint, and this performance constraint term is added to the operation and maintenance resources to update the operation and maintenance resources.

[0097] According to embodiments of this disclosure, the out-of-limit situation of updated system parameters is determined based on performance constraints. The penalty factor is determined by the out-of-limit situation and performance constraint items are constructed. Then, the operation and maintenance resources are updated. The risk of transient frequency instability can be quantified into economic cost. The optimization process is forced to prioritize meeting performance constraints through economic means, ensuring that frequency stability requirements are fed back in real time during parameter adjustment. This avoids system instability caused by improper parameter configuration and enhances the reliability of the optimization process.

[0098] According to embodiments of this disclosure, based on the system parameters of the multiple new energy storage systems included in the target new energy base, the target inertia of multiple new energy storage systems is constructed, including: determining the mechanical power energy change and rotor kinetic energy change of each power generation component during power generation due to the speed difference, based on the number of power generation components included in the first energy storage system, wherein the first energy storage system generates electricity mechanically through the rotation of the power generation components; obtaining the target energy of the power generation components based on the mechanical power energy change and rotor kinetic energy change; calculating the target inertia of the first energy storage system based on the target energy and the component parameters of the power generation components; determining the historical inertia value of the second energy storage system and the historical output value of photovoltaic power generation based on historical data; and calculating the target inertia of the second energy storage system based on the historical inertia value, the historical output value, and the real-time output value of photovoltaic power generation.

[0099] According to embodiments of this disclosure, some physical energy storage systems, such as flywheel energy storage, have rotating components, and therefore their inertial response characteristics can be constructed based on synchronous generators. Since the first energy storage system is a mechanically generated energy storage system, its target inertia can be constructed with reference to synchronous generators.

[0100] According to embodiments of this disclosure, the first energy storage system may include multiple wind turbines. For the first energy storage system, the rated power generation capacity S of a single wind turbine can be used as the basis for... B,w And the energy E contained when the frequency is supported by a single wind turbine blade. w (t), the target inertia H of the first energy storage system w,t As shown in formula (16):

[0101] (16)

[0102] Among them, the energy E contained when the frequency support is provided by a single wind turbine blade w (t) can be determined according to formula (17):

[0103] (17)

[0104] Where, ΔE w,m ΔE represents the change in mechanical power energy caused by the difference in the rotational speed of the wind turbine blades. w,kThis represents the change in mechanical power energy ΔE caused by the difference in the rotational speed of the wind turbine rotor. w,m It can be determined according to formula (18):

[0105] (18)

[0106] Where T represents the time a single wind turbine participates in frequency support, and P w,m (t)-P0 represents the change in mechanical power caused by the difference in the speed of the wind turbine blades, P w,m (t) represents the mechanical power captured by a single wind turbine blade, which can be determined according to formula (19):

[0107] (19)

[0108] Where ρ represents air density, R represents the blade rotation radius, and v t This indicates the real-time wind speed on the windward side of the blades. (C) p (λ t λ(β) represents the wind energy utilization coefficient, which characterizes the physical limit of the turbine system in converting wind kinetic energy into mechanical energy. t β represents the real-time tip speed ratio, and β represents the blade pitch angle.

[0109] According to embodiments of this disclosure, the wind energy utilization factor can be determined according to formula (20):

[0110] (20)

[0111] According to embodiments of this disclosure, when the fan speed is uniformly varying at the moment frequency support is provided, the mechanical power energy change ΔE w,m It can also be determined according to formula (21):

[0112] (twenty one)

[0113] Where λ0 represents the tip speed ratio at the instant of frequency modulation response and ω0 represents the rotational speed.

[0114] Based on the tip speed ratio at the instant of frequency modulation response, the real-time tip speed ratio λ can be determined according to formula (22). t :

[0115] (twenty two)

[0116] According to embodiments of this disclosure, the change in the kinetic energy of the wind turbine rotor is related to the wind turbine's state. For example, based on the operating speed of the wind turbine rotor, the operating conditions can be distinguished into three types: low-speed, medium-speed, and high-speed. In the low-speed condition, the wind turbine output power is less than 20% of the rated operating power, and the wind turbine does not participate in inertial response. In the medium-speed condition, the wind turbine operates at its maximum power point, and the wind energy utilization coefficient reaches its highest level. In the high-speed condition, the rotor is at its maximum speed, but as the wind speed against the blades increases, the mechanical power captured by the wind turbine blades continues to increase until the rated operating condition is reached.

[0117] According to embodiments of this disclosure, the change in kinetic energy ΔE of the wind turbine rotor w,k It can be determined according to formula (23):

[0118] (twenty three)

[0119] Among them, v k0 The instantaneous wind speed, v, represents the frequency modulation response. k1 The wind speed, v, represents the wind speed at the instant the maximum power tracking ends. k2 λ represents the rated wind speed at which the fan operates. r This indicates the optimal tip speed ratio, J. w,k ω represents the inherent inertia of a single wind turbine. max ω represents the maximum speed of the fan rotor. min This represents the minimum rotational speed of the fan rotor.

[0120] According to embodiments of this disclosure, when multiple wind turbines in a wind farm are operating under the same conditions, the virtual synchronous inertia H of the wind farm is... W,t It can be determined according to formula (24):

[0121] (twenty four)

[0122] Among them, P B,W P represents the installed capacity of the wind farm, N represents the total number of operating wind turbines in the wind farm, and P represents the total installed capacity of the wind farm. B,n H represents the installed capacity of the nth wind turbine. w,n This represents the virtual synchronization inertia.

[0123] According to embodiments of this disclosure, since the inertia constant of electrochemical energy storage is typically within 4-12 seconds according to relevant regulations, the frequency oscillation of new energy bases will be significantly aggravated when encountering sudden power disturbances during peak wind and solar power output periods. Therefore, a target inertia can also be constructed for the second energy storage system to achieve dynamic adjustment of the inertia constant of electrochemical energy storage.

[0124] According to embodiments of this disclosure, the target inertia H of the second energy storage system ESS,tIt can be determined according to formula (25):

[0125] (25)

[0126] Among them, H ESS,max H represents the historical maximum value of the virtual inertia of an electrochemically networked new energy storage system. ESS,min P represents the historical minimum value of the virtual inertia of an electrochemically networked new energy storage system. RE,max P represents the maximum output of new energy sources. RE,min P represents the minimum output of the new energy source. RE,t This indicates that the new energy source is generating power in real time.

[0127] According to embodiments of this disclosure, for the first energy storage system, a target inertia is constructed by calculating the changes in mechanical power energy and rotor kinetic energy of the power generation components, which can accurately characterize the inertial characteristics of equipment such as wind turbines. For the second energy storage system, the target inertia is dynamically calculated based on historical data and real-time output, solving the problem of photovoltaic systems lacking mechanical inertia. The combination of these two methods enables inertia modeling for different types of energy storage systems, providing accurate inertia parameters for frequency response analysis and improving the accuracy of system frequency stability assessment.

[0128] According to embodiments of this disclosure, the control strategy of the new energy storage system includes at least a grid-based strategy and a grid-following strategy. Based on the target inertia, frequency response analysis is performed on the new energy storage system to obtain analysis results, including: determining the synchronization inertia based on the target inertia of the grid-based new energy storage system applying the grid-based strategy in the target new energy base and the system parameters of the grid-based new energy storage system, wherein the synchronization inertia is used to resist the influence of virtual disturbances; and determining the analysis results based on the synchronization inertia, target inertia, system damping of the target new energy base, and preset power data of the new energy storage system.

[0129] According to embodiments of this disclosure, based on the real-time virtual synchronous inertia and rated power of a grid-type wind farm, and the real-time virtual synchronous inertia and rated power of a grid-type new energy storage system, the determined synchronous inertia H is... U,t As shown in formula (26):

[0130] (26)

[0131] Among them, the synchronous inertia H U,t The virtual synchronous inertia H in formula (12) U,t0 In its general form, L represents the number of grid-based new energy storage systems employing a grid-based strategy in the new energy base, and H represents... W,lt H represents the real-time virtual synchronous inertia of the l-th grid-type wind farm. ESS,t P represents the rated power of the l-th grid-type wind farm. B,lP represents the real-time virtual synchronous inertia of the energy storage power station. B,ESS This indicates the rated power of the energy storage power station.

[0132] According to embodiments of this disclosure, the preset power data may include the active power of virtual disturbances, the changes in system frequency caused by virtual disturbances, and the changes in active power of wind farms and energy storage power stations caused by virtual disturbances.

[0133] According to embodiments of this disclosure, based on the synchronization inertia H U,t The analysis results, determined by the target inertia, system damping, and preset electrical data, can be expressed through the drive of the rotor motion, thus obtaining the system frequency change rate. As shown in formula (27):

[0134] (27)

[0135] Where, ΔP ds (t) represents the active power of the virtual disturbance, Δf(t) represents the change in system frequency caused by the virtual disturbance, and ΔP w (t) represents the change in active power of the wind farm caused by the virtual disturbance, ΔP ESS (t) represents the change in active power of the energy storage power station caused by the virtual disturbance, D represents the system damping, and H represents the system damping. t This represents the synchronization inertia during time period t.

[0136] According to embodiments of this disclosure, by determining the analysis results based on the system frequency change rate, it is possible to determine the fluctuation of the power frequency of the new energy base over time, thereby evaluating the ability of the new energy base to maintain stability and resist interference under virtual disturbances.

[0137] According to the embodiments of this disclosure, for the differences between grid-type and follow-grid-type control strategies, the synchronous inertia is determined based on the target inertia and parameters of the grid-type new energy storage system. Combined with data such as system damping, frequency response analysis is performed, which can accurately obtain the frequency response characteristics of the system under different control strategies. This provides more realistic analysis results for evaluating the system's anti-disturbance capability and guides the optimization of energy storage configuration to improve system frequency stability.

[0138] Figure 3 The diagram illustrates the frequency response of a new energy base to disturbances after optimization of the energy storage configuration method according to an embodiment of the present disclosure.

[0139] like Figure 3As shown, the normal system frequency of the new energy base is f0, and the new energy base is disturbed at time t0. During the period t0-t2, it is the inertial response phase, where, due to the characteristics of synchronous inertial response, the inertial support power reaches its peak in a short time, then decays exponentially until it drops to 0 at node t2 when the inertial response ends. During the period t1-t3, it is the primary frequency regulation phase, where the wind farm and energy storage power station perform a frequency regulation operation after crossing the t0-t1 time period. The frequency regulation power output of this operation is linearly related to the frequency deviation.

[0140] There is an overlapping time period t1-t2 between the inertial response stage and the primary frequency modulation stage. During this time period, the system frequency response is simultaneously affected by the inertial response and the primary frequency modulation. Under the synergistic effect of the inertial response and the primary frequency modulation, the frequency response is adjusted.

[0141] According to embodiments of this disclosure, the method for optimizing the configuration of energy storage in a new energy base further includes: when a new grid-type new energy storage system is added to the target new energy base, configuring the system parameters of the newly added grid-type new energy storage system based on preset requirements; and adjusting the system parameters of each of the multiple grid-type new energy storage systems in the target new energy base in response to the addition of the new grid-type new energy storage system to the target new energy base.

[0142] According to embodiments of this disclosure, the preset requirements may include the transmission frequency, energy storage capacity, etc., required by the target renewable energy base. Based on the preset requirements, at least one existing grid-type renewable energy storage system in the target renewable energy base, and constraints, the system parameters that the newly added grid-type renewable energy storage system needs to meet are determined, and the system parameters of the newly added grid-type renewable energy storage system are configured.

[0143] According to the embodiments of this disclosure, when a new grid-type new energy storage system is added to the target new energy base, the operation and maintenance resources of the target new energy base will change. Based on the optimization objectives, the system parameters of each new energy storage system can be adjusted again to ensure that the target new energy base can meet the requirements.

[0144] Therefore, the new energy base after adding the new grid-type new energy storage system can be used as the target new energy base, and the above-mentioned new energy base energy storage optimization configuration method can be used for recalculation, so as to ensure the balance between frequency stability of the target new energy base and the economics of energy storage investment.

[0145] According to the embodiments of this disclosure, when adding a new grid-type new energy storage system, the original system parameters can be adjusted based on preset requirements configuration parameters to dynamically adapt to the expansion needs of the new energy base, ensuring that the new equipment works in tandem with the original system, improving the overall inertia support capability, maintaining system frequency stability, optimizing resource allocation, avoiding the risk of frequency instability caused by system expansion, and enhancing the scalability and adaptability of the system.

[0146] According to embodiments of this disclosure, performance constraints are determined based on analysis results, the disturbance power of virtual disturbances, the energy storage capacity and charge / discharge power of the target new energy base, including: determining the transient power and energy constraints of the newly added grid-type new energy storage system based on the energy storage capacity and charge / discharge power of the target new energy base.

[0147] According to the embodiments of this disclosure, after determining that a new grid-type new energy storage system is added to the target new energy base, the optimal configuration scheme can be obtained by optimizing the configuration of the entire target new energy base. However, this adjustment method requires a lot of computing power. When the target new energy base frequently adds or removes new energy storage systems, the configuration scheme needs to be optimized frequently, resulting in excessive computing load.

[0148] Therefore, after adding a new grid-type new energy storage system, transient power and energy constraints can be set for the new grid-type new energy storage system, and adjustments can be made to the new grid-type new energy storage system based on the transient power and energy constraints so that the entire target new energy base meets the overall performance constraints.

[0149] According to the embodiments of this disclosure, by means of the above-described adjustment method, after adding an energy storage system, no global optimization is performed, but only local optimization is performed so that the optimized target new energy base meets the overall performance constraints, which can ensure the safety of the target new energy base, ensure its stable operation, reduce the computational load, and improve the optimization configuration efficiency.

[0150] According to embodiments of this disclosure, since each local optimization cannot guarantee that the optimized system parameters will fully meet the optimization objectives in terms of operation and maintenance resources, there will be a small deviation compared to the optimal target system parameters. Therefore, an optimization threshold can be preset. After the number of times a new energy storage system is added or removed from the target new energy base reaches the preset optimization threshold, a global optimization is performed based on the target new energy base after the addition or removal of the new energy storage system, using the new energy base energy storage optimization configuration method. This avoids the problem of multiple additions and removals leading to the accumulation of multiple small deviations, resulting in excessive deviations and high operation and maintenance resource requirements.

[0151] According to embodiments of this disclosure, when adding a grid-type new energy storage system to a target new energy base, the parameters of the new system are configured based on preset requirements, and the parameters of the existing multiple grid-type systems are adjusted in response to the addition of the new system. This allows for dynamic adaptation to the expansion needs of the new energy base. This process ensures that the new equipment and the existing systems work collaboratively under the grid-type control strategy. By aggregating virtual inertia, the overall inertia support capability is improved, effectively resisting frequency fluctuations caused by power disturbances and maintaining system frequency stability. Simultaneously, the parameter adjustment process, combined with operation and maintenance resource optimization objectives, avoids resource waste or configuration redundancy caused by system expansion. While improving inertia support capability, it optimizes resource allocation, reduces the risk of frequency instability due to system expansion, and significantly enhances the scalability and operational adaptability of the new energy base in equipment expansion scenarios.

[0152] Figure 4 The diagram illustrates the daily operation results after optimization of the energy storage optimization configuration method for a new energy base according to an embodiment of the present disclosure.

[0153] like Figure 4 As shown, S1~S4 represent the daily running results of a natural day in spring, summer, autumn and winter, respectively.

[0154] According to the daily operation results in spring, the output of new energy sources such as wind and solar power is relatively low during certain periods in spring. Therefore, AC systems are needed to provide power support to meet the minimum requirements for DC transmission.

[0155] Under resource constraints, during periods of low renewable energy output in spring, the power gap can be supplemented by the target inertia, thereby ensuring the stability of the frequency and power of the target renewable energy base.

[0156] According to the daily operation results in summer, due to the large amount of solar power generation in summer, a small amount of solar power wasted occurred between 16:00 and 17:00.

[0157] According to the daily operation results in autumn, due to the strong winds in autumn, there will be a small amount of wind curtailment at certain times.

[0158] Under performance constraints, the amount of wind and solar power curtailed in summer and autumn both meet relevant regulations and requirements.

[0159] Based on the aforementioned optimized configuration method for energy storage in new energy bases, this disclosure also provides an optimized configuration device for energy storage in new energy bases. The following will be combined with... Figure 5 The device is described in detail.

[0160] Figure 5 A frequency line graph illustrating the optimized configuration method for energy storage in a new energy base according to an embodiment of the present disclosure is shown.

[0161] like Figure 5 As shown, the target new energy base is disturbed at 15:00. Compared with the optimized configuration method using the new energy base energy storage, the energy storage power configuration using the comparative configuration method is lower. Therefore, the maximum power that the energy storage can release under the comparative configuration method cannot meet the corresponding inertia requirements when facing the disturbance. The configuration optimized using the comparative configuration method has higher maximum frequency deviation and maximum frequency change rate when facing the disturbance than the configuration optimized using the new energy base energy storage optimization method of this disclosure. Therefore, the optimized configuration method for new energy base energy storage can significantly improve the stability and anti-interference capability of the target new energy base.

[0162] Figure 6 The diagram illustrates a structural block diagram of an optimized configuration device for energy storage in a new energy base according to an embodiment of the present disclosure.

[0163] like Figure 6 As shown, the energy storage optimization configuration device 600 of the new energy base in this embodiment includes an inertia construction module 610, a resource determination module 620, a disturbance analysis module 630, and a parameter adjustment module 640.

[0164] The inertia construction module 610 is used to construct the target inertia of multiple new energy storage systems based on the system parameters of each of the multiple new energy storage systems included in the target new energy base. The new energy storage systems include a first energy storage system based on mechanical power generation and a second energy storage system based on photovoltaic power generation. The system parameters include rated energy storage capacity and rated power. In one embodiment, the inertia construction module 610 can be used to perform the operation S210 described above, which will not be repeated here.

[0165] The resource determination module 620 is used to determine the operation and maintenance resources of the target new energy base based on the preset requirements of the target new energy base, the operating parameters of each of the multiple new energy storage systems, and the system parameters. In one embodiment, the resource determination module 620 can be used to execute the operation S220 described above, which will not be repeated here.

[0166] The disturbance analysis module 630 is used to perform frequency response analysis on the target new energy base based on the target inertia when the target new energy base is subjected to a virtual disturbance, and obtain analysis results. The frequency response analysis is used to analyze the fluctuation frequency of the energy storage in the target new energy base after the disturbance, and the analysis results represent the disturbance resistance capability of the target new energy base. In one embodiment, the disturbance analysis module 630 can be used to execute the operation S230 described above, which will not be repeated here.

[0167] The parameter adjustment module 640 is used to construct constraints based on the analysis results, the disturbance power of the virtual disturbance, the transmission power, energy storage capacity, and charging / discharging power of the target new energy base. Based on these constraints, the system parameters are adjusted to obtain the target system parameters, whereby the operation and maintenance resources meet the optimization objective under the target system parameters. In one embodiment, the parameter adjustment module 640 can be used to execute the operation S240 described above, which will not be repeated here.

[0168] According to the embodiments of this disclosure, the energy storage optimization configuration device 600 for new energy bases can be used to implement the energy storage optimization configuration method for new energy bases in the above embodiments. For the operations that each module of the energy storage optimization configuration device 600 for new energy bases can perform, please refer to the energy storage optimization configuration method for new energy bases described above, which will not be repeated here.

[0169] According to embodiments of this disclosure, any plurality of modules among the inertia construction module 610, resource determination module 620, disturbance analysis module 630, and parameter adjustment module 640 may be combined into one module, or any one of these modules may be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of other modules and implemented in one module. According to embodiments of this disclosure, at least one of the inertia construction module 610, resource determination module 620, disturbance analysis module 630, and parameter adjustment module 640 may be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging the circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the inertia building module 610, resource determination module 620, disturbance analysis module 630, and parameter adjustment module 640 may be implemented at least partially as a computer program module, which can perform corresponding functions when the computer program module is run.

[0170] Embodiments of this disclosure also include an electronic device comprising: one or more processors; and a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the methods provided in the embodiments of this disclosure.

[0171] Figure 7 A block diagram of an electronic device suitable for implementing an optimized configuration method for energy storage in a new energy base, according to an embodiment of the present disclosure, is shown schematically.

[0172] like Figure 7As shown, an electronic device 700 according to an embodiment of the present disclosure includes a processor 701, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage portion 708 into a random access memory (RAM) 703. The processor 701 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 701 may also include onboard memory for caching purposes. The processor 701 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0173] RAM 703 stores various programs and data required for the operation of electronic device 700. Processor 701, ROM 702, and RAM 703 are interconnected via bus 704. Processor 701 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 702 and / or RAM 703. It should be noted that the programs may also be stored in one or more memories other than ROM 702 and RAM 703. Processor 701 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in said one or more memories.

[0174] According to embodiments of this disclosure, the electronic device 700 may further include an input / output (I / O) interface 705, which is also connected to a bus 704. The electronic device 700 may also include one or more of the following components connected to the input / output (I / O) interface 705: an input section 706 including a keyboard, mouse, etc.; an output section 707 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN card, modem, etc. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the input / output (I / O) interface 705 as needed. A removable medium 711, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 710 as needed so that computer programs read from it can be installed into the storage section 708 as needed.

[0175] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0176] According to embodiments of this disclosure, the computer-readable storage medium can be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this disclosure, the computer-readable storage medium may include ROM 702 and / or RAM 703 and / or one or more memories other than ROM 702 and RAM 703 described above.

[0177] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code is used to cause the computer system to implement the methods provided in the embodiments of this disclosure.

[0178] When the computer program is executed by the processor 701, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0179] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 709, and / or installed from a removable medium 711. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0180] In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 709, and / or installed from the removable medium 711. When the computer program is executed by the processor 701, it performs the functions defined in the system of this disclosure embodiment. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0181] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on a user's computing device, partially on a user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0182] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0183] Those skilled in the art will understand that the features described in the various embodiments of this disclosure can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. In particular, the features described in the various embodiments of this disclosure can be combined and / or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0184] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. An optimized configuration method for energy storage in a new energy base, characterized in that, The method includes: Based on the system parameters of the multiple new energy storage systems included in the target new energy base, the target inertia of the multiple new energy storage systems is constructed. The new energy storage system includes a first energy storage system based on mechanical power generation and a second energy storage system based on photovoltaic power generation. The system parameters include rated energy storage capacity and rated power. Based on the preset requirements of the target new energy base, the operating parameters of each of the multiple new energy storage systems, and the system parameters, the operation and maintenance resources of the target new energy base are determined. When the target new energy base is subjected to a virtual disturbance, based on the target inertia, a frequency response analysis is performed on the fluctuation frequency of the energy storage of the target new energy base after the disturbance, and the analysis results are obtained. The analysis results are used to represent the disturbance resistance capability of the target new energy base. Based on the analysis results, the disturbance power of the virtual disturbance, the transmission power, energy storage capacity, and charging / discharging power of the target new energy base, constraints are constructed. Based on the constraints and the operation and maintenance resources meeting the optimization objective, the system parameters are adjusted to obtain the target system parameters.

2. The method according to claim 1, characterized in that, The constraints include resource constraints and performance constraints. The resource constraints are used to ensure that the target new energy base meets resource requirements, and the performance constraints are used to ensure that the target new energy base maintains stable operation in the presence of disturbances. Based on the analysis results, the disturbance power of the virtual disturbance, the transmission power, energy storage capacity, and charging / discharging power of the target new energy base, constraints are constructed, including: Based on the transmission power of the target new energy base and the preset transmission power threshold, the resource constraints are determined. Based on the analysis results, the disturbance power of the virtual disturbance, the energy storage capacity and charging / discharging power of the target new energy base, the performance constraints are determined.

3. The method according to claim 2, characterized in that, The process of adjusting the system parameters based on the constraints to obtain the target system parameters includes: Repeat the following operations until the target system parameters are determined: Based on the resource constraints, the system parameters are adjusted according to the optimization objective to obtain the updated system parameters; If the updated system parameters do not meet the performance constraints, the operation and maintenance resources shall be updated based on the performance constraints. If the updated system parameters satisfy the performance constraints, the updated system parameters shall be used as the target system parameters.

4. The method according to claim 3, characterized in that, The updating of the operation and maintenance resources based on the performance constraints includes: Based on the performance constraints, the out-of-limit situation of the updated system parameters is determined, wherein the out-of-limit situation is used to represent the ratio by which the updated system parameters exceed the performance constraints; Based on the aforementioned exceedance situation, a penalty factor is determined; Based on the penalty factor and the performance constraints, construct the performance constraint terms; The operation and maintenance resources are updated using the performance constraints.

5. The method according to claim 1, characterized in that, The construction of the target inertia of the multiple new energy storage systems based on their respective system parameters within the target new energy base includes: Based on the number of power generation components included in the first energy storage system, the mechanical power energy change and rotor kinetic energy change of each power generation component during the power generation process caused by the speed difference are determined, wherein the first energy storage system generates mechanical power through the rotation of the power generation components; The target energy of the power generation component is obtained based on the changes in mechanical power energy and the changes in rotor kinetic energy. Based on the target energy and the component parameters of the power generation component, the target inertia of the first energy storage system is calculated; Based on the historical data, the historical inertia value of the second energy storage system and the historical output value of photovoltaic power generation are determined; Based on the historical inertia value, the historical power output value, and the real-time power output value of the photovoltaic power generation, the target inertia of the second energy storage system is calculated.

6. The method according to claim 5, characterized in that, The control strategy of the new energy storage system includes at least a grid-based strategy and a grid-following strategy; The frequency response analysis of the new energy storage system based on the target inertia is performed to obtain the analysis results, including: Based on the target inertia of the grid-type new energy storage system applying the grid-type strategy in the target new energy base and the system parameters of the grid-type new energy storage system, the synchronization inertia is determined, wherein the synchronization inertia is used to resist the influence of the virtual disturbance. The analysis results are determined based on the synchronous inertia, the target inertia, the system damping of the target new energy base, and the preset power data of the new energy storage system.

7. The method according to claim 5, characterized in that, The determination of the operation and maintenance resources of the target new energy base based on the individual operating parameters of the multiple new energy storage systems and the system parameters includes: Based on the one-time resources of each energy device included in each of the new energy storage systems and the service life of each of the multiple energy devices, the average resources of each of the multiple energy devices are determined; The operation and maintenance resources are determined based on the average resources and the operating resources of the target new energy base.

8. The method according to claim 6, characterized in that, The method further includes: When the grid-type new energy storage system is added to the target new energy base, the system parameters of the newly added grid-type new energy storage system are configured based on the preset requirements. In response to the addition of the newly added grid-type new energy storage system to the target new energy base, the system parameters of each of the multiple grid-type new energy storage systems in the target new energy base are adjusted.

9. The method according to claim 8, characterized in that, The performance constraints are determined based on the analysis results, the disturbance power of the virtual disturbance, the energy storage capacity and charge / discharge power of the target new energy base, including: Based on the energy storage capacity of the target new energy base and the charging and discharging power, the transient power and energy constraints of the newly added grid-type new energy storage system are determined.

10. An optimized configuration device for energy storage in a new energy base, characterized in that, The device includes: An inertia construction module is used to construct the target inertia of multiple new energy storage systems based on the system parameters of each of the multiple new energy storage systems included in the target new energy base. The new energy storage system includes a first energy storage system based on mechanical power generation and a second energy storage system based on photovoltaic power generation. The system parameters include rated energy storage capacity and rated power. The resource determination module is used to determine the operation and maintenance resources of the target new energy base based on the preset requirements of the target new energy base, the operating parameters of the multiple new energy storage systems, and the system parameters. The disturbance analysis module is used to perform frequency response analysis on the target new energy base based on the target inertia when the target new energy base is subjected to virtual disturbance, and obtain analysis results. The frequency response analysis is used to analyze the fluctuation frequency of the energy storage of the target new energy base after being disturbed, and the analysis results are used to represent the disturbance resistance capability of the target new energy base. The parameter adjustment module is used to construct constraints based on the analysis results, the disturbance power of the virtual disturbance, the transmission power, energy storage capacity, and charging / discharging power of the target new energy base, and adjust the system parameters based on these constraints to obtain target system parameters. Under these target system parameters, the operation and maintenance resources meet the optimization objective.

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