A multi-type new energy power grid-oriented cooperative control method and device, a terminal device, and a storage medium

By calculating the output power using wind turbine and photovoltaic module models and combining it with energy storage data, a collaborative control strategy is generated, which solves the problem of unstable operation of power grids for multiple types of new energy sources and improves the stability and efficiency of the power grid.

CN119518967BActive Publication Date: 2025-10-21GUANGDONG POWER GRID CO LTD +1
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Patent Information

Application Number
CN202411556009.0
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2024-11-04
Publication Date
2025-10-21
Estimated Expiration
2044-11-04

AI Technical Summary

Technical Problem

Existing new energy control strategies mainly target single-type new energy equipment, lacking synergistic optimization of multiple new energy sources. This makes them unsuitable for use in power grids with multiple types of new energy power generation devices, leading to grid instability.

Method used

By acquiring wind and solar energy data, the output power is calculated using wind turbine and photovoltaic module models. Combined with energy storage data, a collaborative control model is used to calculate the target charge and discharge quantities and output power, generating control strategies for wind, solar, and energy storage devices to ensure stable grid operation.

Benefits of technology

It improves the operational stability of power grids with multiple types of new energy sources, effectively smooths the volatility of new energy power generation through collaborative control strategies, and improves system operating efficiency.

✦ Generated by Eureka AI based on patent content.

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Patent Text Reader

Abstract

The application discloses a kind of collaborative control methods, devices, terminal equipment and storage medium for multi-type new energy power grid, first output power and second output power are calculated by wind turbine model and photovoltaic module model, then using collaborative control model, according to energy storage data, first output power and second output power, the target charge-discharge capacity, first target output power and second target output power that can make power grid stable operation are calculated, and then first control strategy, second control strategy and the third control strategy are generated, to control wind turbine, photovoltaic generator set and energy storage device, to maintain the stable operation of power grid.Therefore, the application provides implementable collaborative control strategy for power grid with multi-type new energy power generation device by fully considering the output power of multi-type new energy power generation device, effectively improves the stability of power grid operation.
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Description

Technical Field

[0001] The present invention relates to the field of electric power technology, and in particular to a collaborative control method, device, terminal equipment and storage medium for multiple types of new energy power grids. Background Art

[0002] With the global energy crisis and environmental challenges becoming increasingly severe, the development of renewable energy sources such as wind and solar power has become a global consensus. However, due to natural conditions, both wind and solar power are intermittent and fluctuating, and their large-scale access to the power grid poses challenges to the safe and stable operation of the grid. To address this issue, it is urgent to develop efficient control strategies for renewable energy devices to smooth the power generation of renewable energy and improve its utilization. Various control strategies for renewable energy devices have been proposed, such as maximum power point tracking (MPPT), combined active and reactive power dispatch control, and predictive model-based control. These control strategies have, to a certain extent, mitigated the volatility of renewable energy generation and improved system efficiency.

[0003] However, most control strategies target a single type of renewable energy device and lack the coordinated optimization of multiple renewable energy sources. Therefore, traditional renewable energy control strategies cannot be applied in the current power grid with multiple types of renewable energy generation devices. Summary of the Invention

[0004] The embodiments of the present invention provide a collaborative control method, device, terminal equipment and storage medium for multiple types of new energy power grids. By fully considering the output power of multiple types of new energy power generation devices, an implementable collaborative control strategy is provided for power grids with multiple types of new energy power generation devices, thereby effectively improving the stability of power grid operation.

[0005] An embodiment of the present invention provides a collaborative control method for multiple types of new energy power grids, including:

[0006] Obtain wind power data, solar energy data, and energy storage data of energy storage devices;

[0007] Inputting the wind energy data into a preset wind turbine generator set model so that the wind turbine generator set model calculates a first output power of the wind turbine generator set based on the wind energy data; the wind turbine generator set model is a mathematical model that simulates the operation of the wind turbine generator set;

[0008] Inputting the light energy data into a preset photovoltaic module model so that the photovoltaic module model simulates the light energy data and calculates the second output power of the photovoltaic generator set; the photovoltaic module model is a mathematical model that simulates the operation of the photovoltaic generator set;

[0009] Inputting the energy storage data, the first output power, and the second output power into a preset coordinated control model, so that the coordinated control model calculates the target charge and discharge capacity of the energy storage device, the first target output power of the wind turbine generator set, and the second target output power of the photovoltaic generator set while ensuring stable operation of the power grid;

[0010] generating a first control strategy for the wind turbine generator set according to the first target output power, generating a second control strategy for the photovoltaic generator set according to the second target output power, and generating a third control strategy for the energy storage device according to the target charge and discharge amount;

[0011] According to the first control strategy, the second control strategy, and the third control strategy, the wind turbine generator set, the photovoltaic generator set, and the energy storage device are controlled respectively so that the wind turbine generator set outputs a first target output power, the photovoltaic generator set outputs a second target output power, and the energy storage device is charged or discharged according to the target charge and discharge amount.

[0012] Furthermore, after generating a first control strategy for the wind turbine generator set according to the first target output power, generating a second control strategy for the photovoltaic generator set according to the second target output power, and generating a third control strategy for the energy storage device according to the target charge and discharge amount, the method further includes:

[0013] generating a wind turbine simulation sub-model according to the first control strategy and the wind turbine model;

[0014] generating a photovoltaic component simulation sub-model according to the second control strategy and the photovoltaic component model;

[0015] Inputting the wind power data, the light energy data, the energy storage data, the third control strategy, the wind turbine simulation sub-model, and the photovoltaic module simulation sub-model into a preset power grid flow simulation model for simulation, and generating a power grid operation simulation result within a preset simulation time;

[0016] When it is determined that the operation simulation result indicates that the power grid operates normally within a preset simulation time, the first control strategy, the second control strategy, and the third control strategy are output.

[0017] Furthermore, the coordinated control model calculates the target charge and discharge capacity of the energy storage device, the first target output power of the wind turbine generator set, and the second target output power of the photovoltaic generator set under the condition of ensuring stable operation of the power grid, including:

[0018] Obtain the current electricity purchase price and energy storage cost;

[0019] Constructing an objective function based on the current electricity purchase price, the energy storage cost, the energy storage data, the first output power, and the second output power; wherein the decision variables of the objective function are the energy storage data, the first output power, and the second output power, and the calculation result of the objective function is the operating cost;

[0020] Under several preset constraints for ensuring stable operation of the power grid, the energy storage data, the first output power, and the second output power are iteratively optimized with the goal of minimizing the calculation result of the objective function, and when the calculation result is less than a preset threshold, a target charge and discharge amount, a first target output power, and a second target output power are generated.

[0021] Furthermore, generating a first control strategy for the wind turbine generator set according to the first target output power includes:

[0022] Adopting an adaptive pitch control method to determine, based on the wind power data and the first target output power, a target pitch angle required for the wind turbine generator set to output the first target output power;

[0023] determining, according to the control system of the wind turbine generator set, control parameters required for adjusting the target pitch angle;

[0024] The first control strategy is generated according to the control parameters.

[0025] Furthermore, generating a second control strategy for the photovoltaic power generation group according to the second target output power includes:

[0026] determining a disturbance voltage step size according to the second target output power and the second output power;

[0027] Adopting a variable step-size perturbation observation method, determining a step-size adjustment parameter according to the light energy data and the perturbation voltage step-size;

[0028] The second control strategy is generated according to the step size adjustment parameter.

[0029] Another embodiment of the present invention provides a collaborative control device for multiple types of new energy power grids, including:

[0030] A data acquisition module is used to acquire wind power data, light energy data, and energy storage data of the energy storage device;

[0031] a first model calculation module, configured to input the wind energy data into a preset wind turbine generator set model, so that the wind turbine generator set model calculates a first output power of the wind turbine generator set based on the wind energy data; the wind turbine generator set model is a mathematical model that simulates the operation of the wind turbine generator set;

[0032] a second model calculation module, configured to input the light energy data into a preset photovoltaic module model, so that the photovoltaic module model simulates the light energy data and calculates a second output power of the photovoltaic generator set; the photovoltaic module model is a mathematical model that simulates the operation of the photovoltaic generator set;

[0033] a power calculation module, configured to input the energy storage data, the first output power, and the second output power into a preset coordinated control model, so that the coordinated control model calculates a target charge and discharge capacity of the energy storage device, a first target output power of the wind turbine generator set, and a second target output power of the photovoltaic generator set while ensuring stable operation of the power grid;

[0034] a strategy generation module, configured to generate a first control strategy for the wind turbine generator set according to the first target output power, generate a second control strategy for the photovoltaic generator set according to the second target output power, and generate a third control strategy for the energy storage device according to the target charge and discharge amount;

[0035] a collaborative control module, configured to control the wind turbine generator set, the photovoltaic generator set, and the energy storage device according to the first control strategy, the second control strategy, and the third control strategy, respectively, so that the wind turbine generator set outputs a first target output power, the photovoltaic generator set outputs a second target output power, and the energy storage device is charged or discharged according to a target charge or discharge amount.

[0036] Furthermore, the collaborative control device for multiple types of new energy grids further includes: a strategy verification module;

[0037] The strategy verification module is used to generate a first control strategy for the wind turbine generator set according to the first target output power, generate a second control strategy for the photovoltaic generator set according to the second target output power, and generate a third control strategy for the energy storage device according to the target charge and discharge amount.

[0038] generating a wind turbine simulation sub-model according to the first control strategy and the wind turbine model;

[0039] generating a photovoltaic component simulation sub-model according to the second control strategy and the photovoltaic component model;

[0040] Inputting the wind power data, the light energy data, the energy storage data, the third control strategy, the wind turbine simulation sub-model, and the photovoltaic module simulation sub-model into a preset power grid flow simulation model for simulation, and generating a power grid operation simulation result within a preset simulation time;

[0041] When it is determined that the operation simulation result indicates that the power grid operates normally within a preset simulation time, the first control strategy, the second control strategy, and the third control strategy are output.

[0042] Furthermore, the coordinated control model calculates the target charge and discharge capacity of the energy storage device, the first target output power of the wind turbine generator set, and the second target output power of the photovoltaic generator set under the condition of ensuring stable operation of the power grid, including:

[0043] Obtain the current electricity purchase price and energy storage cost;

[0044] Constructing an objective function based on the current electricity purchase price, the energy storage cost, the energy storage data, the first output power, and the second output power; wherein the decision variables of the objective function are the energy storage data, the first output power, and the second output power, and the calculation result of the objective function is the operating cost;

[0045] Under several preset constraints for ensuring stable operation of the power grid, the energy storage data, the first output power, and the second output power are iteratively optimized with the goal of minimizing the calculation result of the objective function, and when the calculation result is less than a preset threshold, a target charge and discharge amount, a first target output power, and a second target output power are generated.

[0046] Another embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements a collaborative control method for multiple types of new energy power grids as described in any one of the embodiments.

[0047] Another embodiment of the present invention provides a storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute a collaborative control method for multiple types of new energy power grids as described in any one of the above embodiments.

[0048] The following beneficial effects are achieved by implementing the present invention:

[0049] The present invention discloses a collaborative control method, device, terminal equipment and storage medium for a multi-type new energy power grid. Through a wind turbine model and a photovoltaic component model, the first output power of the current wind turbine and the second output power of the photovoltaic generator are calculated. Then, a collaborative control model is adopted to calculate the target charge and discharge amount, the first target output power, and the second target output power for stable operation of the power grid according to the energy storage data, the first output power, and the second output power of the energy storage device, and a first control strategy, a second control strategy, and the third control strategy are generated to control the wind turbine, the photovoltaic generator, and the energy storage device respectively, so that the wind turbine outputs the first target output power, the photovoltaic generator outputs the second target output power, and the energy storage device is charged or discharged according to the target charge and discharge amount. Therefore, the present invention provides an implementable collaborative control strategy for a power grid with multiple types of new energy power generation devices by fully considering the output power of multiple types of new energy power generation devices, thereby effectively improving the stability of power grid operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a flow chart of a collaborative control method for multiple types of new energy power grids provided by one embodiment of the present invention.

[0051] Figure 2 This is a structural diagram of a collaborative control device for multiple types of new energy power grids provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0052] To make the objectives, technical solutions, and advantages of this application more clear, the technical solutions in this application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of this application.

[0053] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned figure descriptions are intended to cover non-exclusive inclusions.

[0054] In the description of the embodiments of this application, the technical terms "first" and "second" are used only to distinguish different objects and should not be understood to indicate or imply relative importance or implicitly specify the quantity, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, the meaning of "plurality" is more than two, unless otherwise clearly and specifically defined.

[0055] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0056] In the description of the embodiments of this application, the term "and / or" is simply a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent the following three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.

[0057] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0058] In the description of the embodiments of the present application, unless otherwise expressly specified or limited, technical terms such as "installed," "connected," "connected," and "fixed" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integration; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; internal connections between two components or interactions between two components. Those skilled in the art can understand the specific meanings of the above terms in the embodiments of the present application based on specific circumstances.

[0059] See also Figure 1 , is a flow chart of a collaborative control method for multiple types of new energy power grids provided by an embodiment of the present invention, including:

[0060] S1. Acquire wind power data, light energy data, and energy storage data of the energy storage device;

[0061] In a preferred embodiment of the present invention, the wind data includes: wind speed v, wind direction θ; the light energy data includes: solar radiation intensity G, ambient temperature T a The energy storage data includes: collecting the voltage U of the energy storage battery b, voltage of series battery pack U bs Current I b It should be noted that, in order to ensure the accuracy of the subsequent calculation process, this embodiment cleans the data after acquiring it, that is, removes redundant and abnormal data, so as to improve the data quality and lay a data foundation for subsequent modeling.

[0062] S2. Inputting the wind energy data into a preset wind turbine generator model, so that the wind turbine generator model calculates a first output power of the wind turbine generator according to the wind energy data; the wind turbine generator model is a mathematical model that simulates the operation of the wind turbine generator;

[0063] S3. Inputting the light energy data into a preset photovoltaic module model, so that the photovoltaic module model simulates the light energy data and calculates the second output power of the photovoltaic generator set; the photovoltaic module model is a mathematical model that simulates the operation of the photovoltaic generator set;

[0064] In a preferred embodiment of the present invention, the wind turbine model adopts a piecewise polynomial to fit the wind turbine power curve; the wind speed v is used as the independent variable and the unit output power P is used as the independent variable. w is the dependent variable;

[0065] In different wind speed ranges, polynomials of different orders are used for fitting, and the polynomial coefficients are determined by least squares fitting. The polynomial fitting formula is:

[0066]

[0067] Among them, a i ,b i ,...,k i are polynomial coefficients, v1,v2,...,v i+1 The wind speed segmentation point.

[0068] Secondly, the photovoltaic module model adopts an improved single diode equivalent circuit model, taking into account the photocurrent I ph , diode reverse saturation current I0, series resistance R s and parallel resistor R sh Impact on photovoltaic output voltage U and current I; the photovoltaic module model formula is:

[0069]

[0070] Where a is the diode ideality factor, V T is the thermoelectric potential.

[0071] Finally, this embodiment also constructs a battery energy storage model for detecting the battery power during the subsequent charging and discharging process. Specifically, the Shepherd correction model is used as the battery equivalent circuit model to describe the battery terminal voltage U b The relationship with the internal parameters of the battery, which include internal resistance R, polarization constant K, and capacity Q; the formula of the battery energy storage model is:

[0072]

[0073] Among them, E0 is the open circuit voltage, A and B are fitting parameters; the battery SOC is estimated using the ampere-hour integration method, that is, based on the initial SOC, i.e. SOC0 and the charge and discharge current I b , integrate the current and calculate the current SOC:

[0074]

[0075] Among them, C N is the rated capacity of the battery.

[0076] S4. Inputting the energy storage data, the first output power, and the second output power into a preset coordinated control model, so that the coordinated control model calculates the target charge and discharge capacity of the energy storage device, the first target output power of the wind turbine generator set, and the second target output power of the photovoltaic generator set while ensuring stable operation of the power grid. Preferably, the coordinated control model calculates the target charge and discharge capacity of the energy storage device, the first target output power of the wind turbine generator set, and the second target output power of the photovoltaic generator set while ensuring stable operation of the power grid, including:

[0077] S41. Obtain the current electricity purchase price and energy storage cost;

[0078] S42: Constructing an objective function based on the current electricity purchase price, the energy storage cost, the energy storage data, the first output power, and the second output power; wherein the decision variables of the objective function are the energy storage data, the first output power, and the second output power, and the calculation result of the objective function is the operating cost;

[0079] S43. Under several preset constraints for ensuring stable operation of the power grid, with the goal of minimizing the calculation result of the objective function, iteratively optimize the energy storage data, the first output power, and the second output power, and generate a target charge and discharge amount, a first target output power, and a second target output power when the calculation result is less than a preset threshold.

[0080] In a preferred embodiment of the present invention, an energy management strategy is constructed based on grid data, and a hierarchical distributed energy management strategy is proposed for a wind-solar-storage complementary microgrid; the energy storage charging and discharging plan P is optimized with the goal of minimizing operating costs. s Exchange power with the grid P g ;The objective function of the energy management strategy is:

[0081]

[0082] Among them, C g ,C s are the electricity purchase price from the grid and the energy storage charging and discharging costs respectively;

[0083] Adaptive dynamic programming algorithm is used to solve the energy management problem in the energy management strategy; the system state x(t) is used as environmental information, and the energy storage charging and discharging power P is used as the energy storage power. s (t) and the grid exchange power P g (t) is used as the control decision variable u(t), and the minimum operating cost is used as the optimization goal. Through iterative learning, the optimal control strategy is approached. The iterative formula of the adaptive dynamic programming algorithm is:

[0084]

[0085] Where k is the number of iterations and γ is the discount factor.

[0086] S5. Generate a first control strategy for the wind turbine generator set based on the first target output power, generate a second control strategy for the photovoltaic generator set based on the second target output power, and generate a third control strategy for the energy storage device based on the target charge and discharge capacity;

[0087] Preferably, generating a first control strategy for the wind turbine generator set according to the first target output power includes:

[0088] S511: Determine, using an adaptive pitch control method, a target pitch angle required for the wind turbine generator set to output the first target output power according to the wind power data and the first target output power;

[0089] S512. Determine, according to the control system of the wind turbine generator set, control parameters required for adjusting the target pitch angle;

[0090] S513: Generate the first control strategy according to the control parameters.

[0091] In a preferred embodiment of the present invention, an adaptive variable pitch control strategy is adopted. According to the fuzzy PID control algorithm preset in the wind turbine generator set, the wind speed v, wind direction θ and unit speed n are input to output the pitch angle instruction β; finally, the pitch angle instruction β and the fuzzy rule are used to adjust the PID parameter proportional gain K p , integration time K i , differential time K d ;

[0092] Preferably, generating a second control strategy for the photovoltaic power generation group according to the second target output power includes:

[0093] S521: Determine a disturbance voltage step size according to the second target output power and the second output power;

[0094] S522, using a variable step size perturbation observation method to determine a step size adjustment parameter according to the light energy data and the perturbation voltage step size;

[0095] S523: Generate the second control strategy according to the step size adjustment parameter.

[0096] In a preferred embodiment of the present invention, the perturbation observation MPPT control strategy is improved, and the photovoltaic control strategy adopts the variable step size perturbation observation method, according to the light intensity G and the component temperature T c The change rate of the disturbance voltage is adjusted adaptively, and the step size ΔU of the disturbance voltage is adjusted to speed up the maximum power point tracking speed. The disturbance voltage step size adjustment formula is:

[0097]

[0098] Where ΔU is the disturbance voltage step size, is the rate of change of light intensity, is the temperature change rate of the PV module, and f is the step size adjustment function.

[0099] It should be further explained that the third control strategy is an adaptive charge and discharge control strategy based on the battery state of health (SOH); the current SOH is estimated by the internal resistance spectrum R(f) and the capacity decrease ΔQ parameter, and the charge and discharge rate I is adjusted accordingly. bc And the upper limit of charging cut-off voltage U bmax ; The SOH estimation formula is:

[0100] SOH=g[R(f),ΔQ];

[0101] Where g[·] is an estimation function; under the premise of ensuring battery safety, the battery life is maximized.

[0102] Preferably, after generating a first control strategy for the wind turbine generator set according to the first target output power, generating a second control strategy for the photovoltaic generator set according to the second target output power, and generating a third control strategy for the energy storage device according to the target charge and discharge amount, the method further includes:

[0103] S531. Generate a wind turbine simulation sub-model according to the first control strategy and the wind turbine model;

[0104] S532: Generate a photovoltaic assembly simulation sub-model according to the second control strategy and the photovoltaic assembly model;

[0105] S533: Input the wind power data, the light energy data, the energy storage data, the third control strategy, the wind turbine simulation sub-model, and the photovoltaic module simulation sub-model into a preset power grid flow simulation model for simulation, and generate a power grid operation simulation result within a preset simulation time;

[0106] S534: When it is determined that the operation simulation result indicates that the power grid operates normally within a preset simulation time, output the first control strategy, the second control strategy, and the third control strategy.

[0107] In a preferred embodiment of the present invention, new energy equipment models of wind power, photovoltaic power, and energy storage are built in the MATLAB simulation platform, and control strategies of various devices are added to each model. Wind speed, light, and load data are selected as inputs, and the capacity parameters and simulation time of the grid load are set. The simulation model is run to record the output power curves of wind power, photovoltaic power, energy storage, and the grid, as well as the performance indicators of the system's total power generation, load demand, and abandoned wind and solar power.

[0108] By drawing the output power curves of various devices, analyzing the changes in volatility and stability before and after optimized control, and by calculating the proportion of renewable energy power generation, wind and solar power curtailment rates, and the proportion of power purchased by the power grid, the optimization effect of the proposed control strategy is quantitatively evaluated.

[0109] S6. According to the first control strategy, the second control strategy, and the third control strategy, the wind turbine generator set, the photovoltaic generator set, and the energy storage device are controlled respectively so that the wind turbine generator set outputs a first target output power, the photovoltaic generator set outputs a second target output power, and the energy storage device is charged or discharged according to the target charge and discharge amount.

[0110] This embodiment provides a collaborative control method for a multi-type new energy power grid. Through a wind turbine model and a photovoltaic component model, the first output power of the current wind turbine and the second output power of the photovoltaic turbine are calculated. Then, a collaborative control model is adopted to calculate the target charge and discharge amount, the first target output power, and the second target output power for stable operation of the power grid based on the energy storage data, the first output power, and the second output power of the energy storage device, and a first control strategy, a second control strategy, and the third control strategy are generated to control the wind turbine, the photovoltaic turbine, and the energy storage device respectively, so that the wind turbine outputs the first target output power, the photovoltaic turbine outputs the second target output power, and the energy storage device is charged or discharged according to the target charge and discharge amount. Therefore, the present invention provides an implementable collaborative control strategy for a power grid with multiple types of new energy power generation devices by fully considering the output power of multiple types of new energy power generation devices, thereby effectively improving the stability of power grid operation.

[0111] See also Figure 2 , is a schematic structural diagram of a coordinated control device for multiple types of new energy grids provided by one embodiment of the present invention, including:

[0112] A data acquisition module is used to acquire wind power data, light energy data, and energy storage data of the energy storage device;

[0113] a first model calculation module, configured to input the wind energy data into a preset wind turbine generator set model, so that the wind turbine generator set model calculates a first output power of the wind turbine generator set based on the wind energy data; the wind turbine generator set model is a mathematical model that simulates the operation of the wind turbine generator set;

[0114] a second model calculation module, configured to input the light energy data into a preset photovoltaic module model, so that the photovoltaic module model simulates the light energy data and calculates a second output power of the photovoltaic generator set; the photovoltaic module model is a mathematical model that simulates the operation of the photovoltaic generator set;

[0115] a power calculation module, configured to input the energy storage data, the first output power, and the second output power into a preset coordinated control model, so that the coordinated control model calculates a target charge and discharge capacity of the energy storage device, a first target output power of the wind turbine generator set, and a second target output power of the photovoltaic generator set while ensuring stable operation of the power grid;

[0116] a strategy generation module, configured to generate a first control strategy for the wind turbine generator set according to the first target output power, generate a second control strategy for the photovoltaic generator set according to the second target output power, and generate a third control strategy for the energy storage device according to the target charge and discharge amount;

[0117] a collaborative control module, configured to control the wind turbine generator set, the photovoltaic generator set, and the energy storage device according to the first control strategy, the second control strategy, and the third control strategy, respectively, so that the wind turbine generator set outputs a first target output power, the photovoltaic generator set outputs a second target output power, and the energy storage device is charged or discharged according to a target charge or discharge amount.

[0118] Preferably, the collaborative control device for multiple types of new energy grids further includes: a strategy verification module;

[0119] The strategy verification module is used to generate a first control strategy for the wind turbine generator set according to the first target output power, generate a second control strategy for the photovoltaic generator set according to the second target output power, and generate a third control strategy for the energy storage device according to the target charge and discharge amount.

[0120] generating a wind turbine simulation sub-model according to the first control strategy and the wind turbine model;

[0121] generating a photovoltaic component simulation sub-model according to the second control strategy and the photovoltaic component model;

[0122] Inputting the wind power data, the light energy data, the energy storage data, the third control strategy, the wind turbine simulation sub-model, and the photovoltaic module simulation sub-model into a preset power grid flow simulation model for simulation, and generating a power grid operation simulation result within a preset simulation time;

[0123] When it is determined that the operation simulation result indicates that the power grid operates normally within a preset simulation time, the first control strategy, the second control strategy, and the third control strategy are output.

[0124] Preferably, the coordinated control model calculates the target charge and discharge capacity of the energy storage device, the first target output power of the wind turbine generator set, and the second target output power of the photovoltaic generator set under the condition of ensuring stable operation of the power grid, including:

[0125] Obtain the current electricity purchase price and energy storage cost;

[0126] Constructing an objective function based on the current electricity purchase price, the energy storage cost, the energy storage data, the first output power, and the second output power; wherein the decision variables of the objective function are the energy storage data, the first output power, and the second output power, and the calculation result of the objective function is the operating cost;

[0127] Under several preset constraints for ensuring stable operation of the power grid, the energy storage data, the first output power, and the second output power are iteratively optimized with the goal of minimizing the calculation result of the objective function, and when the calculation result is less than a preset threshold, a target charge and discharge amount, a first target output power, and a second target output power are generated.

[0128] It should be noted that the device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed across multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. In addition, in the drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art can understand and implement the present invention without inventive effort.

[0129] Those skilled in the art will clearly understand that for the sake of convenience and brevity, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0130] Another preferred embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements a collaborative control method for multiple types of new energy power grids as described in any one of the above embodiments.

[0131] The terminal device may be a computing device such as a desktop computer, a notebook computer, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0132] The processor may be a central processing unit (CPU), other general-purpose processors, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, connecting various parts of the entire terminal device using various interfaces and lines.

[0133] The memory can be used to store the computer program, and the processor realizes various functions of the terminal device by running or executing the computer program stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function, etc.; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Med i aCard, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0134] Another preferred embodiment of the present invention provides a storage medium, which is a computer-readable storage medium, and the computer program is stored in the computer-readable storage medium. When the computer program is executed by the processor, it can implement the steps of the above-mentioned various method embodiments. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunications signal, and a software distribution medium.

[0135] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A collaborative control method for multi-type new energy power grids, characterized in that: include: Obtain wind power data, solar energy data, and energy storage data of energy storage devices; Inputting the wind power data into a preset wind turbine generator set model so that the wind turbine generator set model calculates a first output power of the wind turbine generator set based on the wind power data; the wind turbine generator set model is a mathematical model that simulates the operation of the wind turbine generator set; Inputting the light energy data into a preset photovoltaic module model so that the photovoltaic module model simulates the light energy data and calculates the second output power of the photovoltaic generator set; the photovoltaic module model is a mathematical model that simulates the operation of the photovoltaic generator set; Inputting the energy storage data, the first output power, and the second output power into a preset coordinated control model, so that the coordinated control model calculates the target charge and discharge capacity of the energy storage device, the first target output power of the wind turbine generator set, and the second target output power of the photovoltaic generator set while ensuring stable operation of the power grid; generating a first control strategy for the wind turbine generator set according to the first target output power, generating a second control strategy for the photovoltaic generator set according to the second target output power, and generating a third control strategy for the energy storage device according to the target charge and discharge amount; Generate a wind turbine simulation sub-model based on the first control strategy and the wind turbine model; generate a photovoltaic module simulation sub-model based on the second control strategy and the photovoltaic module model; input the wind power data, the light energy data, the energy storage data, the third control strategy, the wind turbine simulation sub-model, and the photovoltaic module simulation sub-model into a preset power grid flow simulation model for simulation, and generate an operation simulation result of the power grid within a preset simulation time; when it is determined that the operation simulation result indicates that the power grid operates normally within the preset simulation time, output the first control strategy, the second control strategy, and the third control strategy; According to the first control strategy, the second control strategy, and the third control strategy, the wind turbine generator set, the photovoltaic generator set, and the energy storage device are controlled respectively so that the wind turbine generator set outputs a first target output power, the photovoltaic generator set outputs a second target output power, and the energy storage device is charged or discharged according to the target charge and discharge amount.

2. A collaborative control method for multiple types of new energy power grids according to claim 1, characterized in that: The coordinated control model calculates the target charge and discharge capacity of the energy storage device, the first target output power of the wind turbine generator set, and the second target output power of the photovoltaic generator set under the condition of ensuring stable operation of the power grid, including: Obtain the current electricity purchase price and energy storage cost; Constructing an objective function based on the current electricity purchase price, the energy storage cost, the energy storage data, the first output power, and the second output power; wherein the decision variables of the objective function are the energy storage data, the first output power, and the second output power, and the calculation result of the objective function is the operating cost; Under several preset constraints for ensuring stable operation of the power grid, the energy storage data, the first output power, and the second output power are iteratively optimized with the goal of minimizing the calculation result of the objective function, and when the calculation result is less than a preset threshold, a target charge and discharge amount, a first target output power, and a second target output power are generated.

3. The collaborative control method for multiple types of new energy power grids according to claim 2, characterized in that: Generating a first control strategy for the wind turbine generator set according to the first target output power includes: Adopting an adaptive pitch control method to determine, based on the wind power data and the first target output power, a target pitch angle required for the wind turbine generator set to output the first target output power; determining, according to the control system of the wind turbine generator set, control parameters required for adjusting the target pitch angle; The first control strategy is generated according to the control parameters.

4. A collaborative control method for multiple types of new energy power grids according to claim 3, characterized in that: Generating a second control strategy for the photovoltaic power generation group according to the second target output power includes: determining a disturbance voltage step size according to the second target output power and the second output power; Adopting a variable step-size perturbation observation method, determining a step-size adjustment parameter according to the light energy data and the perturbation voltage step-size; The second control strategy is generated according to the step size adjustment parameter.

5. A collaborative control device for multiple types of new energy power grids, characterized in that: include: A data acquisition module is used to acquire wind power data, light energy data, and energy storage data of the energy storage device; a first model calculation module, configured to input the wind power data into a preset wind turbine generator set model, so that the wind turbine generator set model calculates a first output power of the wind turbine generator set according to the wind power data; The wind turbine model is a mathematical model that simulates the operation of the wind turbine; a second model calculation module, configured to input the light energy data into a preset photovoltaic module model, so that the photovoltaic module model simulates the light energy data and calculates a second output power of the photovoltaic generator set; the photovoltaic module model is a mathematical model that simulates the operation of the photovoltaic generator set; a power calculation module, configured to input the energy storage data, the first output power, and the second output power into a preset coordinated control model, so that the coordinated control model calculates a target charge and discharge capacity of the energy storage device, a first target output power of the wind turbine generator set, and a second target output power of the photovoltaic generator set while ensuring stable operation of the power grid; a strategy generation module, configured to generate a first control strategy for the wind turbine generator set according to the first target output power, generate a second control strategy for the photovoltaic generator set according to the second target output power, and generate a third control strategy for the energy storage device according to the target charge and discharge amount; a strategy verification module, configured to generate a wind turbine simulation sub-model based on the first control strategy and the wind turbine model; generate a photovoltaic module simulation sub-model based on the second control strategy and the photovoltaic module model; input the wind power data, the light energy data, the energy storage data, the third control strategy, the wind turbine simulation sub-model, and the photovoltaic module simulation sub-model into a preset power grid flow simulation model for simulation, and generate operation simulation results of the power grid within a preset simulation time; and output the first control strategy, the second control strategy, and the third control strategy when it is determined that the operation simulation results indicate that the power grid operates normally within the preset simulation time; a collaborative control module, configured to control the wind turbine generator set, the photovoltaic generator set, and the energy storage device according to the first control strategy, the second control strategy, and the third control strategy, respectively, so that the wind turbine generator set outputs a first target output power, the photovoltaic generator set outputs a second target output power, and the energy storage device is charged or discharged according to a target charge or discharge amount.

6. The collaborative control device for multiple types of new energy grids according to claim 5, characterized in that: The coordinated control model calculates the target charge and discharge capacity of the energy storage device, the first target output power of the wind turbine generator set, and the second target output power of the photovoltaic generator set under the condition of ensuring stable operation of the power grid, including: Obtain the current electricity purchase price and energy storage cost; Constructing an objective function based on the current electricity purchase price, the energy storage cost, the energy storage data, the first output power, and the second output power; wherein the decision variables of the objective function are the energy storage data, the first output power, and the second output power, and the calculation result of the objective function is the operating cost; Under several preset constraints for ensuring stable operation of the power grid, the energy storage data, the first output power, and the second output power are iteratively optimized with the goal of minimizing the calculation result of the objective function, and when the calculation result is less than a preset threshold, a target charge and discharge amount, a first target output power, and a second target output power are generated.

7. A terminal device, characterized in that: It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, it implements a collaborative control method for multiple types of new energy power grids as described in any one of claims 1 to 4.

8. A storage medium, characterized in that: The storage medium includes a stored computer program, wherein, when the computer program is running, the device where the storage medium is located is controlled to execute a collaborative control method for multiple types of new energy power grids as described in any one of claims 1 to 4.

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