A grid-connected wind power system electric-thermal coordinated overload control method and system

Abstract

This invention proposes a method and system for electrothermal coordination overload control of grid-connected wind power systems. The method involves acquiring current measurements of the transmission components and wind farm of the grid-connected wind power system; predicting wind speed based on meteorological data; obtaining the temperature of the transmission components; and predicting the active power of the wind farm within a set time step of the current control cycle. Considering the predicted wind speed, transmission component temperature, and wind farm active power, an optimization problem is established based on the electrothermal coordination model of the grid-connected wind power system. Process-oriented electrothermal coordination control is then implemented to ensure that the temperature of the grid-connected line does not exceed limits during overload control. The optimization problem is solved under constraints to determine the optimal control sequence. The active power of the first wind farm group in the optimal control sequence is applied to the current wind farm's power generation control. This invention uses the maximum allowable temperature of the transmission components as a limit to dynamically coordinate and continuously optimize the wind farm output and the temperature of the external transmission components in the grid-connected system. Compared to traditional overload control methods, this method can further tap the overload potential of the external transmission components, which is beneficial for alleviating the contradiction of wind energy consumption.

Description

Technical Field

[0001] This invention belongs to the field of power grid control technology and relates to a method and system for electrothermal coordination overload control of grid-connected wind power systems. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] With the continuous growth of grid-connected wind power capacity, the risk of overload exceeding limits at the transmission sections of wind power clusters is increasing. During periods of high wind power generation, the transmission components sometimes fail to meet the N-1 safety constraint. Insufficient current-carrying capacity of grid-connected wind power systems has become one of the important factors restricting safe and economical operation and wind energy consumption. For grid-connected wind power systems, improper overload control at the transmission section may trigger a chain reaction of failures in the transmission components, leading to large-scale wind curtailment.

[0004] With the application of flexible AC and DC transmission technologies, thermal stability limitations have gradually become one of the key factors restricting the load capacity of wind power transmission lines. Based on this, Dynamic Thermal Setpoint (DTR) technology, which promotes the exploitation of the current-carrying capacity of transmission components, has been further applied. Combining DTR technology, researchers have proposed the Electrothermal Coordination (ETC) theory. This theory deeply elucidates the interaction between electrical quantities in the power system and the thermal processes of transmission components, and introduces the temperature of transmission components as an important state variable into the analysis and control decisions of the power system as a basis for overload judgment. This allows the operation and control of the power system to fully exploit the current-carrying capacity of transmission components from their essential temperature characteristics.

[0005] However, according to the inventors, there is currently a lack of research on overload control of transmission sections in grid-connected wind power systems with large-scale wind power integration. Existing studies often use the static thermal setpoint of transmission components as a criterion for power flow exceeding limits or approximate the thermal inertia of transmission components by setting the delay time of overload protection. This means that overload control fails to address the temperature-dependent current-carrying capacity of transmission components and truly coordinate the dynamic process of current carrying capacity and temperature of wind power transmission components. It also fails to fully exploit the current-carrying potential inherent in the thermal inertia of transmission components, resulting in conservative overload control. Furthermore, as the penetration of renewable energy sources such as wind power increases, the connection between the power grid and grid-connected wind power systems is also strengthening, leading to increased coupling and mutual influence between the two. Many past studies have neglected the topological structure and voltage constraints within wind farms. The determination of the power regulation range in overload control methods for grid-connected wind power systems is often merely a simple algebraic sum of the adjustment limits of each unit, which is unreasonable for large-scale grid-connected wind power systems. Summary of the Invention

[0006] To address the aforementioned problems, this invention proposes a method and system for electrothermal coordination overload control in grid-connected wind power systems. This invention uses the maximum allowable temperature of the transmission components as a limit, dynamically coordinating and continuously optimizing the wind farm output and the temperature of the external transmission components within the grid-connected system. Compared to traditional overload control methods, this approach can further tap into the overload potential of the external transmission components, thus helping to alleviate the contradiction in wind energy consumption.

[0007] According to some embodiments, the present invention adopts the following technical solution:

[0008] A method for electrothermal coordinated overload control of a grid-connected wind power system, which cyclically executes the following steps as the control cycle is updated:

[0009] Obtain the current measurement values ​​of the transmission components of the grid-connected wind power system and the current measurement values ​​of the wind farm;

[0010] Based on meteorological data, wind speed is predicted, the temperature of power transmission components is obtained, and the active power of the wind farm within the set time step of the current control cycle is predicted.

[0011] Taking into account the predicted wind speed, the temperature of the transmission components, and the predicted active power of the wind farm, an optimization problem is established based on the electrothermal coordination model of the wind power grid connection system. Process-oriented electrothermal coordination control is carried out to ensure that the temperature of the grid connection line does not exceed the limit during the overload control process.

[0012] The optimization problem is solved under constraints to determine the optimal control sequence. The active power of the first wind farm group in the optimal control sequence is then applied to the power generation control of the current wind farm.

[0013] An electrothermal coordinated overload control system for a grid-connected wind power system, comprising:

[0014] The parameter acquisition module is configured to acquire the current measurement values ​​of the transmission components of the grid-connected wind power system and the current measurement values ​​of the wind farm;

[0015] The parameter prediction module is configured to predict wind speed based on meteorological data, obtain the temperature of power transmission components, and predict the active power of the wind farm within the set time step of the current control cycle.

[0016] The model building module is configured to comprehensively consider the predicted wind speed, the temperature of the transmission components, and the predicted active power of the wind farm. Based on the electrothermal coordination model of the wind power grid connection system, it establishes an optimization problem and performs process-oriented electrothermal coordination control to ensure that the temperature of the grid connection line does not exceed the limit during the overload control process.

[0017] The optimization control module is configured to solve optimization problems under constraints, determine the optimal control sequence, and apply the active power of the first wind farm group in the optimal control sequence to the power generation control of the current wind farm.

[0018] A computer-readable storage medium storing a plurality of instructions adapted for loading by a processor of a terminal device and executing steps in the method.

[0019] A terminal device includes a processor and a computer-readable storage medium, the processor being configured to implement instructions; the computer-readable storage medium being configured to store a plurality of instructions adapted to be loaded by the processor and executed in accordance with the steps of the method described therein.

[0020] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0021] This invention treats the overhead line conductor and transformer hot spot temperature as operating state variables of the grid-connected wind power system. After the external power grid is equivalent to an infinite power source, it is combined with the power flow calculation of the grid-connected wind power system to construct an optimization model of the grid-connected wind power system based on electrothermal coordination.

[0022] The optimization model of this invention takes maximizing wind power at the grid connection point as the objective function, and the constraints consist of a set of nonlinear differential equations. This model relaxes the current-carrying constraints of transmission elements limited by static thermal setpoints in traditional overload control optimization models, thereby finding the optimal control decision that satisfies the corresponding constraints.

[0023] The optimization model of this invention, under the framework of MPC (Model Predictive Control), uses the measurement information of the current grid-connected wind power system as the initial value for the next prediction and performs rolling optimization and iteration. This corrects the impact of prediction errors on overload control results to a certain extent, and aims to maximize the short-term overload capacity of transmission lines and components so as to quickly restore the normal operation of the system under emergency conditions and improve the utilization efficiency of transmission components.

[0024] Another optimization model of this invention introduces the active power output and reactive power injected by the doubly-fed asynchronous wind turbine as decision variables, and proposes an overload control method based on electrothermal coordination under the refined modeling of grid-connected wind farms. Based on the active-reactive power regulation of the doubly-fed asynchronous wind turbine unit, with the goal of minimizing wind curtailment in the grid-connected wind power system, it can tap the short-term overload capacity of the transmission line while utilizing the regulation characteristics of the doubly-fed asynchronous wind turbine.

[0025] Guided by the decision-making objectives, this invention can utilize the flexible and rapid voltage regulation capability of the doubly fed wind turbine generator set itself, or improve the reactive power regulation capability by sacrificing some active power, to explore its own control potential, address voltage issues within the grid-connected wind farm, and maximize the absorption of wind energy while ensuring safer overload control results. Attached Figure Description

[0026] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0027] Figure 1 This is a flowchart of the control process in Example 1;

[0028] Figure 2 This is the steady-state equivalent circuit of a doubly-fed asynchronous wind turbine generator;

[0029] Figure 3 This is a structural diagram of the grid-connected wind power system in the engineering example of Implementation Example 1;

[0030] Figure 4 This is a structural diagram of the doubly-fed wind turbine group in the engineering example of Implementation Example 1;

[0031] Figure 5 This refers to the power output of each wind farm and the temperature changes of the 110kV transmission line for wind power in Example 1 of the engineering calculation.

[0032] Figure 6 The output results of the STR downwind field and the temperature change of the 110kV transmission line are shown in Example 1 of the engineering calculation.

[0033] Figure 7 The wind farm output results and temperature changes of the 110kV transmission line in Example 1 of the engineering calculation are shown in Example 1.

[0034] Figure 8 The node and active power of Unit 46 in Example 2 of Implementation Example 1;

[0035] Figure 9 This refers to the power output of each wind farm and the temperature changes of the transformer hotspot in Example 2 of the engineering calculation in Example 1;

[0036] Figure 10 The output results of each wind farm and the temperature change of the transformer hot spot are shown in Example 2 of the engineering calculation under normal periodic load.

[0037] Figure 11 The results of wind farm output and changes in hot spot temperature of power transformers using this method are shown in Example 1, Engineering Calculation 2.

[0038] Figure 12 The voltage and active power of the node where Unit 46 is located in Example 1, Engineering Calculation Example 2.

[0039] Figure 13 This is a flowchart of Example 2;

[0040] Figure 14 This is a structural diagram of a grid-connected wind power system;

[0041] Figure 15 This refers to the power output of the wind farm group and the temperature changes of the 110kV transmission line for external wind power in Example 1 of the engineering calculation in Example 2;

[0042] Figure 16 The results of wind farm output under static thermal setpoint and temperature change of 110kV transmission line in Example 2, Engineering Calculation 1;

[0043] Figure 17 The results of the wind farm output at the maximum allowable temperature of the transmission components and the temperature change of the 110kV transmission line are shown in Example 2, Engineering Calculation 1.

[0044] Figure 18 This refers to the changes in power output of the wind farm group and the temperature of the transformer hotspot in Example 2 of the engineering calculation.

[0045] Figure 19 The output results of each wind farm and the temperature change of the transformer hot spot are shown in Example 2 of the engineering calculation.

[0046] Figure 20 The output results of each wind farm and the change of transformer hot spot temperature under the maximum allowable hot spot temperature during long-term emergency load in Example 2 of Engineering Calculation;

[0047] Figure 21 The variations in wind farm output, 110kV transmission line temperature, and transformer hot spot temperature are shown in Example 2, Engineering Calculation 3.

[0048] Figure 22 The variations in wind farm output, 110kV transmission line temperature, and transformer hot spot temperature under static thermal setpoints in Example 2, Engineering Calculation 3;

[0049] Figure 23 The variations in wind farm output, 110kV transmission line temperature, and transformer hot spot temperature under the maximum allowable temperature of the transmission components in Example 2, Engineering Calculation 3. Detailed implementation method:

[0050] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0051] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention.

[0052] Example 1

[0053] like Figure 1As shown, an electrothermal coordinated overload control method includes the following specific steps:

[0054] (1) A measurement device based on DTR technology installed at key spans of grid-connected lines is used to monitor and measure the grid-connected wind power system and provide the required measurement values ​​(including wind speed (v[0|t]), ambient temperature (Ta[0|t]), solar radiation intensity (S[0|t]) and wind speed of wind turbines along the transmission line).

[0055] (2) Perform meteorological data forecasting, forecast the vector increment of meteorological data (wind speed, ambient temperature and solar radiation intensity along the line) and the forecast value (wind speed) of wind turbines, and determine the active power of each wind turbine within the K time step range of the grid-connected power transmission components.

[0056] The prediction used in this embodiment can adopt existing prediction models. The meteorological data and active power of the wind farm are calculated from numerical weather forecast data (including wind speed, temperature, humidity, terrain conditions, etc.) to obtain the actual wind power output and meteorological data. When the environment remains stable, the model has good prediction performance. Currently, the prediction results are applicable to short-term meteorological forecasts and short-term wind power forecasts.

[0057] (3) Based on the electrothermal coordination model of the wind power grid-connected system (see the description below), an optimization problem was established in conjunction with model predictive control to determine the active power output of the wind turbine within K time steps. Temperature was used as a dynamic capacity constraint for the conductor.

[0058] If the grid-connected line temperature tends to exceed the maximum allowable temperature (70°C in this embodiment), timely process-oriented electrothermal coordination control is implemented to ensure that the grid-connected line temperature does not exceed the limit during overload control. Simultaneously, the voltage level of each wind turbine node is dynamically monitored. If any limit exceedance is detected, control is implemented based on the active-reactive power regulation range model of the doubly-fed asynchronous wind turbine to keep the voltage level within a reasonable range.

[0059] (4) Select the optimal control calculation values ​​for the active power, reactive power output of the wind turbine, and the temperature of the grid-connected transmission components. Once the optimal control sequence is determined, the active power command of the first wind farm group in the optimal control sequence is issued and applied to the power generation control of the current wind farm. As time progresses from t to t+1, the grid-connected wind power system responds to the control accordingly, and the process is repeated when new measurements are available, performing rolling optimization overload control.

[0060] The models involved are described in detail below.

[0061] 1. Power regulation characteristics of doubly-fed wind turbine units

[0062] The active-reactive power regulation model of a doubly-fed asynchronous wind turbine can be derived from its steady-state model. Its steady-state equivalent circuit is as follows: Figure 2 As shown.

[0063] pass Figure 2 The steady-state equivalent current shown can be expressed as follows:

[0064]

[0065] In equation (1), U s U r and E m These represent the stator voltage, rotor voltage, and air gap induced electromotive force, respectively. s I r and I m These represent the stator current, rotor current, and excitation current, respectively. sσ X rσ and X m These represent the stator leakage reactance, rotor leakage reactance, and magnetizing reactance, respectively. R s R r s and s represent the stator and rotor resistances and slip, respectively. According to equation (1), since the doubly-fed asynchronous wind turbine is limited by the rotor voltage and stator current, its total active power output (P) is limited. W ) and stator-side reactive power (Q) s The relationship between ) can be expressed as:

[0066]

[0067]

[0068] Among them, P s Q s These represent the active power on the stator side and the reactive power on the stator side, respectively; I r I s and U s These represent the peak value of the rotor single-phase current, the peak value of the stator single-phase voltage, and the peak value of the stator single-phase current, respectively. X s This represents the stator reactance. I rmax I smax These represent the maximum permissible stator single-phase current and the maximum permissible rotor single-phase current, respectively. In addition, the grid-side converter of this type of wind turbine can also undertake some reactive power regulation tasks, and its regulation capability is limited by the maximum permissible capacity (S). cmax Given the limitations of ), and combining the above formula, the reactive power output limit can be derived as shown in the following formula.

[0069]

[0070]

[0071] Therefore, the upper and lower limits of reactive power output of a doubly-fed asynchronous wind turbine generator can be expressed as:

[0072]

[0073] In summary, the active-reactive power regulation range model of a doubly-fed asynchronous wind turbine generator can be expressed as:

[0074]

[0075] It can be seen that while the range is determined by active and reactive power, the turbine speed and terminal voltage can also affect its regulation range. Calculations show that the shape of this regulation range is similar to an ellipse. The speed is in the denominator of this constraint; as the speed increases (decreases), the ellipse extends (retracts) in the active power direction, thus increasing (decreasing) the adjustment limit to some extent. Changes in the terminal voltage will affect the position and radius of the ellipse's center. Therefore, speed and terminal voltage are two factors that must be included in the calculation of the active-reactive power regulation range. The active-reactive power regulation range is one of the most important steady-state characteristics of a doubly-fed asynchronous wind turbine, playing a crucial role in overload control of grid-connected wind power systems. Previous academic research typically fixed the active power output of the wind turbine, considering only the adjustable range of reactive power. However, the power adjustment limit of this type of wind turbine actually presents a relationship of mutual constraint between active and reactive power. While this reduces the computational difficulty and energy consumption, it wastes the flexible regulation capability of the doubly-fed asynchronous wind turbine. Therefore, if we can make in-depth application of this inverse relationship between active and reactive power, it will be of great significance for overload control of wind power grid-connected systems.

[0076] 2. Thermal balance models of two commonly used power transmission components in grid-connected wind power systems

[0077] (1) Thermal balance model of overhead conductor

[0078] The thermal dynamics of overhead conductors depend on their current and external gas phase conditions. According to the IEEE standard thermal balance model for overhead conductors, it can be expressed as follows:

[0079]

[0080] In equation (8), θ l q represents the surface temperature of a conductor (°C). j q represents the Joule heat (W / m) generated per unit length of conductor due to resistance heating. s q represents the amount of heat absorbed by sunlight (W / m²). c q represents the heat dissipation (W / m) generated by air convection.r This represents the heat dissipation (W / m) generated by thermal radiation. The specific calculation formulas for the heat absorption and heat dissipation in equation (8) are as follows:

[0081]

[0082] q s =α s Q se sin(θ)A′ (10)

[0083]

[0084]

[0085] In equation (9), I l R(θ) represents the current (A) flowing through the conductor. l ) represents a conductor at its temperature θ l Resistance per unit length (Ω / m) at that time. [θ] low ,θ high This is expressed as a reasonable range for the relationship between conductor resistance and temperature. In equation (10), α s Q represents the light absorption rate of a conductor. se Represents the solar radiation per unit area after elevation correction (W / m²) 2 θ represents the angle of incidence of sunlight (°), and A' represents the projected area per unit length of conductor (m²). 2 / m). In equation (11), D represents the outer diameter of the conductor (m), ρ f Represents air density (kg / m³) 3 ), μ f V represents air viscosity (kg / ms). w Represents wind speed (m / s), k angle The wind direction factor represents the angle between the conductor's axis and the wind direction. q c1 and q c2 It can be used to calculate the heat dissipation generated by forced convection at low and high wind speeds, respectively. At a given wind speed, q is generally chosen. c1 and q c2 The larger value after solving is taken as the heat dissipation. q c3 This is used to calculate the heat dissipation generated by natural convection at zero wind speed. According to IEEE standards, in practical applications, at low wind speeds, the larger of the calculated results from natural convection and forced convection should be used as q. c In equation (12), ε represents the thermal emissivity of the conductor, and θ a Represents the ambient temperature (°C) around the conductor.

[0086] (2) Transformer thermal balance model

[0087] Power transformers are a crucial component of power systems. With the gradual improvement of modern ultra-high voltage (UHV) networks, their voltage levels and capacities are increasing, leading to a corresponding increase in failure rates. Related articles, starting from the transmission capacity limitations of transformers, propose using hotspot temperature and failure rate as constraints. When the hotspot temperature exceeds the upper limit, the aging rate of the insulation material increases drastically, affecting the normal operation of the transformer. Therefore, determining the temperature of the hotspot is one of the important factors determining its operating condition and ensuring the safe operation of grid-connected wind power systems.

[0088] Scholar D. Susa summarized the temperature rise process of a transformer during operation into two stages: (1) hot spot temperature - bottom oil temperature; (2) bottom oil temperature - ambient temperature. The corresponding heat balance equation can be expressed as:

[0089]

[0090]

[0091] In equation (13), C boil The bottom oil heat capacity of the transformer (J / K); q fe It expresses its no-load loss; R boil The nonlinear thermal resistance (K / W) between the oil and air at the bottom of the transformer; θ boil Expressed as its bottom oil temperature (°C); q load For load loss. In equation (14), C hs R is the winding heat capacity (J / K); hs This represents the nonlinear thermal resistance (K / W) between the top insulation surface of its winding and the bottom oil; θ hs Hotspot temperature (°C); q cu This refers to the winding losses of the transformer.

[0092] 2. Optimization Model for Electrothermal Coordination Overload Control Based on Refined Modeling of Grid-Connected Wind Farms

[0093] (1) Objective function

[0094] Assuming a reasonable voltage distribution, a mathematical optimization model is created by using the active (reactive) output of each wind turbine as the decision variable and minimizing the wind curtailment of all doubly-fed asynchronous wind turbines as the objective function. The objective function can be expressed as:

[0095]

[0096] In equation (15), t represents the current decision-making period, and P WGmax，i(t) and P WG，i(t)M represents the active power output of the doubly-fed wind turbine unit i at time t, and the maximum active power limit calculated through online measurement, respectively. G It is the collection of all wind turbine generators in a grid-connected wind power system.

[0097] (2) Constraints

[0098] 1) Wind field tidal balance constraints

[0099] Each wind farm, once activated, can be considered a small radial network. Therefore, for a grid-connected wind power system containing several wind farms, the external power grid after grid connection can also be considered a sufficiently powerful infinite system. The internal structure of the wind power system can be viewed as a small-scale load flow calculation system, and its power flow balance equation can be expressed as:

[0100]

[0101]

[0102]

[0103]

[0104] Where t is the decision cycle of the current overload control, and M is the set of nodes in the grid-connected wind power system. P ij(t) and Q ij(t) These are the active and reactive power of the transmitting ends at branches i and j, respectively, P WGj(t) Q is the active power output at the generator terminal of a doubly-fed asynchronous wind turbine at time j. WGj(t) U is the reactive power injected into the doubly-fed asynchronous wind turbine generator terminal at time t. i(t) and U j(t) These are the voltage magnitudes at nodes i and j, respectively, r ij and x ij These are the resistance and reactance of branches i and j, respectively.

[0105] 2) Temperature constraints of overhead lines

[0106]

[0107] 3) Transformer temperature constraint

[0108]

[0109]

[0110]

[0111] 4) Current-carrying constraints of transmission elements

[0112] I m,(t) ≤I m,max(t) (twenty four)

[0113] In the formula, I m,max(t) Let m be the maximum allowable current carrying capacity of the transmission element.

[0114] 5) Node voltage constraints

[0115]

[0116] In the formula, This is the lower limit of the voltage at node i; is the upper limit of the voltage at node i.

[0117] 6) Constraints on the active and reactive power regulation range of doubly-fed asynchronous wind turbine generator units

[0118] 0≤P WG,i(t) ≤P WGmax,i(t) (26)

[0119] Q WGmin,i(t) ≤Q WGi(t) ≤Q WGmax,i(t) (27)

[0120] In the formula,

[0121] Among them, P WGmax,i(t) This represents the upper limit of the active power that a doubly-fed asynchronous wind turbine can output at time t;

[0122] Q WGmax,i(t) and Q WGmin,i(t) These represent the active power P of the unit at time t. WG,i(t) The upper and lower limits of reactive power under adjustment. X s X m Represented as stator reactance and magnetizing reactance; I smax I rmax ω is the maximum permissible thermocurrent of a single phase of the stator (rotor) winding; r,i(t) S is the rotational speed of the wind turbine generator set. cmax This represents the maximum permissible apparent capacity.

[0123] Based on the constraints of the electrothermal coordination model of the wind power grid-connected system and with the objective function of minimizing wind curtailment in the wind farm cluster, this embodiment uses the commercial solution software GAMS to solve the model and obtain the optimal control sequence. Once the optimal control sequence is determined, the active power of the wind farm cluster at the first moment in the optimal control sequence is distributed for the current wind farm's power generation control. As time progresses from t to t+1, the grid-connected wind power system responds to the control accordingly, and when new measurements are available, this process is repeated for rolling optimization overload control.

[0124] Engineering Calculation Example 1

[0125] To better verify the technical concept of this application, a specific calculation example analysis is given below: A wind farm cluster centrally connected to a 500kV substation is shown in the connection diagram below. Figure 3 As shown, the installed wind power capacity is 345MW. This includes three wind farms connected to the 110kV bus, each with a capacity of 75MW, consisting of 50 doubly-fed wind turbines with a rated capacity of 1.5MW each; and wind farms connected to the 220kV bus with a capacity of 120MW, consisting of 80 doubly-fed asynchronous wind turbines with a rated capacity of 1.5MW each. The area comprises multiple wind farms connected in series via multiple power transmission lines, linking to the 220kV power transmission line via the 110kV line. Simultaneously, a wind farm directly connected to the 220kV bus is connected in series, and then connected to the 500kV bus. To ensure reliable power supply, the wind farm's transmission lines and transformers operate in parallel.

[0126] Furthermore, based on this, the wind farm is opened up, and the topology of the wind farm group after refined modeling is considered. The topology diagrams for wind farms with installed capacities of 75MW and 120MW are shown below. Figure 4 As shown in Table 1, all wind turbines in the wind farm are doubly-fed asynchronous wind turbines with a rated capacity of 1.5MW. Their parameters are derived from actual surveys. The reasonable level of node voltage within the wind farm in the example is limited to 0.95-1.05pu. The 110kV transmission line uses LGJ-300 / 40 steel-cored aluminum stranded wire, assuming a transformer capacity of 120MVA; LGJ-400 / 35 is the model for 220kV transmission lines. The maximum allowable temperature of the overhead conductor is set at 70℃. For the transformer's hot spot temperature, under normal cyclic load, it can reach a maximum of 120℃, and under sudden faults, it can reach a maximum of 140℃. The entire control process has a time domain of 1 hour. Considering the temperature variation characteristics of the external transmission components, the time domain is divided into 12 intervals, each with a duration of Δt = 5 minutes.

[0127] Table 1 shows some parameters of the generator set in the engineering example of Example 1.

[0128]

[0129] Assuming that one of the 110kV transmission lines of this grid-connected wind power system experiences an interruption at time t=0, and without controlling the current carrying capacity of the transmission line, the conductor temperature of the intact overhead conductor and the power output of the four wind farms during the 12 time periods are as follows: Figure 5 As shown.

[0130] from Figure 5 As can be seen, when an emergency line failure occurs, the current carrying capacity of the intact wind power transmission line will increase sharply during the decision-making period due to power flow shift, resulting in its current exceeding STR after 15 minutes. Simultaneously, the temperature of this 110kV transmission line exceeds the maximum allowable temperature limit at 35 minutes, reaching 72.12℃. Using STR and the optimization model proposed in this invention as constraints on the thermal load capacity of the wind power transmission line, the output decision results for each wind farm and the temperature change results of the intact 110kV transmission line are as follows: Figure 6 and Figure 7 As shown.

[0131] pass Figure 5 and Figure 7The comparison shows that when STR is the thermal load capacity limit of the transmission line, wind curtailment will be necessary after 15 minutes within the decision-making period because the transmission line reaches the static thermal setpoint, leading to a conservative decision and a large amount of wind curtailment. However, in the method proposed in this embodiment, the maximum allowable temperature of the transmission conductor is still used as the load capacity constraint during grid-connected wind power system overload control, and also as a decision variable in the optimization model. Throughout the decision-making period, due to the thermal inertia of the transmission components, although the current carrying capacity of the transmission line has exceeded the static thermal setpoint... However, due to the lag in temperature changes, it only begins to exceed the limit after 30 minutes. Therefore, compared to STR (Surveyor Stratification) as a method for overload control of grid-connected wind power systems to limit the thermal load capacity of transmission lines, this method, to a certain extent, taps into the load potential of transmission lines during thermal dynamics, thereby improving wind power utilization. Under the refined modeling of grid-connected wind farms, the system structure is further opened up. With the autonomous and flexible control potential of doubly-fed induction generators, the distribution of reactive power is more reasonable. However, due to the refined modeling of the wind farm structure, the presence of transmission components inside the wind farm increases network losses. To analyze the voltage regulation effect of the method proposed in this embodiment, Unit 46 is used as an example to compare and analyze the method of this embodiment with two commonly used reactive power and voltage control methods in grid-connected wind power systems. Method 1 operates each unit at full power with a power factor of 1, without participating in reactive power adjustment; Method 2 operates each unit at maximum active power, and according to the reactive power and voltage control requirements of the grid connection point, each unit is proportionally allocated according to its maximum reactive power output capacity. The comparison results are as follows Figure 8 As shown.

[0132] Analysis shows that within the 30-35 minute timeframe, to ensure the generator terminal voltage does not exceed the limit, the unit sacrifices a small portion of active power, thereby gaining additional reactive power regulation capability and ensuring its voltage level remains within a reasonable range. In contrast, in Method 1, the reactive power transfer direction is from the grid connection point to the remote unit, and the reactive power transfer value is larger. Since transformers and lines within the generator group consume reactive power, in Method 1, the node voltage sometimes fails to meet the requirements (below the minimum value), resulting in significant network losses. Simultaneously, in Method 2, the generator terminal voltage of No. 46 exceeds the limit, with the terminal voltage exceeding the upper voltage limit during high wind speed periods. In summary, this embodiment, without relying on any auxiliary control equipment, leverages the sacrifice of a portion of wind power during periods of high wind speed in the grid-connected wind power system to unlock more reactive power regulation capability, thereby flexibly addressing the issue of exceeding the terminal voltage limit, making safer and more economical overload control.

[0133] Engineering Calculation Example 2

[0134] In a system structure identical to that in Engineering Example 1, assuming that a step-up transformer at the 110kV bus in the grid-connected wind power system needs to be taken out of operation for maintenance at time t=0, if the operating status of another operating transformer is not controlled, then the power output of the three wind farms and the hot spot temperature of the operating transformer during the 12 time periods in the overload control would be as follows: Figure 9 As shown.

[0135] from Figure 9 Analysis shows that when one main transformer is taken out of service, the other still-operating transformer will bear the entire load during the decision-making period. During the 12 overload control periods, the load factor K of the still-operating transformer... C The values ​​exceeded the long-term operating allowable current load factor K1 = 1.18 in four time periods. Although the transformer hotspot temperature also increased, it only exceeded the temperature limit in control periods 8 and 9. Using the long-term allowable load factor of the transformer under normal periodic load and the optimization model proposed in this invention as constraints on the thermal load capacity of the wind power transmission line, the output decision results for each wind farm and the hotspot temperature change results of the still-operating power transformers are as follows: Figure 10 and Figure 11 As shown. To analyze the effect of the proposed method on node voltage during emergency transformer shutdown, this section uses Unit 46 as an example to compare and analyze the method in this embodiment with two common reactive power control methods mentioned in Engineering Example 1. The comparison results are as follows. Figure 12 As shown.

[0136] pass Figure 10 and Figure 11 Analysis shows that if the long-term allowable load factor of the transformer under normal periodic load is used as a constraint, after one transformer is taken out of operation, as the wind farm output increases, the transformer load factor in periods 6, 7, 8, and 9 (four periods) exhibits some wind curtailment to meet the long-term allowable load factor requirements. However, under the method mentioned in this embodiment, the transformer's maximum allowable hot spot temperature under long-term emergency load is used as the load capacity constraint for overload control. Therefore, after one transformer is taken out of operation, the hot spot temperature of the still-operating transformer only exceeds the upper temperature limit for 10 minutes, resulting in a small amount of wind curtailment. Compared to using the long-term allowable load factor of the transformer under normal periodic load as a constraint, using the maximum allowable hot spot temperature under long-term emergency load as the load capacity constraint for overload control highlights the transformer's thermal inertia and further explores the transformer's overload capacity.

[0137] Specifically, regarding the control of voltage and power output of doubly-fed asynchronous wind turbine generator units, through... Figure 12It is known that during the 35-40 minute period of high wind speed, in order to ensure that the voltage remains within the limit range, the method in this embodiment also involves some wind turbines sacrificing some active power to increase reactive power regulation capability. Specifically, for Unit 46, during the 35-40 minute time range, this unit increases reactive power regulation capability by sacrificing a small amount of active power, thereby keeping the voltage level within a reasonable range and ensuring the safety of the overload control process. Similar to Engineering Example 1, compared to Method 1, the voltage at the node where Unit 46 is located is lower and the network loss is higher; while in Method 2, the voltage at the node where Unit 46 is located exceeds the upper voltage limit, causing certain safety hazards. Therefore, regardless of whether the transmission line is disconnected or the power transformer in the grid-connected wind power system is shut down in an emergency, the method of this embodiment can improve the reactive power regulation capability by simply discarding a small amount of wind power during periods of high wind speed in the grid-connected wind power system. This allows each unit in the grid-connected wind power system to maximize its active-reactive power regulation characteristics and work together to better address the voltage issues of the doubly-fed asynchronous wind turbines within the wind farm, while also maximizing the short-term overload capacity of the transmission components in the grid-connected wind power system and improving wind power utilization.

[0138] An Electrothermal Coordination Overload Control Method Based on Refined Modeling of Grid-Connected Wind Farms. In the electrothermal coordination optimization model, the active power output and injected reactive power of the doubly-fed induction generator (DFIG) wind turbine are introduced as decision variables, proposing an electrothermal coordination-based overload control method under refined modeling of grid-connected wind farms. Based on the active-reactive power regulation of the DFIG wind turbine, and with the goal of minimizing wind curtailment in the grid-connected wind power system, an overload control optimization model is established that can tap into the short-term overload capacity of the transmission lines while utilizing the regulation characteristics of the DFIG wind turbine. Guided by the decision objective, this model can leverage the flexible and rapid voltage regulation capability of the DFIG wind turbine itself, or improve reactive power regulation capability by sacrificing some active power, to explore its control potential and address voltage issues within the grid-connected wind farm, maximizing wind energy utilization while ensuring safer overload control results. Meanwhile, simulation results also show that, regardless of whether a single overhead power line breaks or a transformer is urgently taken out of service, this method can improve the reactive power regulation capability of the wind turbines by simply discarding a small amount of wind power at locations with higher wind speeds in the grid-connected wind power system. This maximizes the regulation potential of each turbine and their collaborative operation. While maximizing the short-term overload capacity of the grid-connected wind power system's transmission components and improving wind power utilization, it also better addresses potential risks related to the terminal voltage of wind turbines in the wind farm. This enhances the rationality of decision-making in the safe overload control of the grid-connected wind power system.

[0139] Example 2

[0140] A method for electrothermal coordinated overload control of a grid-connected wind power system, the specific invention of which is illustrated in the flowchart below. Figure 13 As shown.

[0141] The specific steps include:

[0142] (1) Based on the DTR technology measurement device installed at the key span of the grid-connected line, the grid-connected wind power system is monitored and measured to provide the required measurement values ​​(including the measurement values ​​of transmission components and the measurement values ​​of wind farm).

[0143] (2) Perform meteorological data prediction, calculate the vector increment of meteorological data (and the measured value of wind farm group - wind speed), and determine the active power of wind farm within the K time step range of grid-connected transmission elements.

[0144] (3) Based on the electrothermal coordination model of the wind power grid-connected system, an optimization problem was established in conjunction with model predictive control. Considering both the active power of the wind farm cluster and the temperature of the grid-connected transmission components, the active power of the wind farm within K time steps was determined. Temperature was used as a dynamic capacity constraint for the conductors. If the grid-connected line temperature tends to exceed the maximum allowable temperature (70℃ in this embodiment), timely process-oriented electrothermal coordination control was implemented to ensure that the grid-connected line temperature does not exceed the limit during overload control.

[0145] (4) Select the control to track the predetermined setpoints for the wind farm's power transmission and grid connection line temperature. Once the optimal control sequence is determined, the active power of the first wind farm group in the optimal control sequence is applied to the power generation control of the current wind farm. As time progresses from t to t+1, the grid-connected wind power system responds to the control accordingly, and the process is repeated when new measurements are available, performing rolling optimization overload control.

[0146] The modeling part of Example 2 is as follows:

[0147] 1. Thermal balance models of two commonly used power transmission components in grid-connected wind power systems

[0148] (1) Thermal balance model of overhead conductor

[0149] The thermal dynamics of overhead conductors depend on their current and external gas phase conditions. According to the IEEE standard thermal balance model for overhead conductors, it can be expressed as follows:

[0150]

[0151] In equation (1), θ l q represents the surface temperature of a conductor (°C). j q represents the Joule heat (W / m) generated per unit length of conductor due to resistance heating.s q represents the amount of heat absorbed by sunlight (W / m²). c q represents the heat dissipation (W / m) generated by air convection. r This represents the heat dissipation (W / m) generated by thermal radiation. The specific calculation formulas for the heat absorption and heat dissipation in equation (1) are as follows:

[0152]

[0153] q s =α s Q se sin(θ)A′ (3)

[0154]

[0155]

[0156] In equation (2), I l R(θ) represents the current (A) flowing through the conductor. l ) represents a conductor at its temperature θ l Resistance per unit length (Ω / m) at that time. [θ] low ,θ high This is expressed as a reasonable range for the relationship between conductor resistance and temperature. In equation (3), α s Q represents the light absorption rate of a conductor. se Represents the solar radiation per unit area after elevation correction (W / m²) 2 θ represents the angle of incidence of sunlight (°), and A' represents the projected area per unit length of conductor (m²). 2 / m). In equation (4), D represents the outer diameter of the conductor (m), ρ f Represents air density (kg / m³) 3 ), μ f V represents air viscosity (kg / ms). w Represents wind speed (m / s), k angle The wind direction factor represents the angle between the conductor's axis and the wind direction. q c1 and q c2 It can be used to calculate the heat dissipation generated by forced convection at low and high wind speeds, respectively. At a given wind speed, q is generally chosen. c1 and q c2 The larger value after solving is taken as the heat dissipation. q c3 This is used to calculate the heat dissipation generated by natural convection at zero wind speed. According to IEEE standards, in practical applications, at low wind speeds, the larger of the calculated results from natural convection and forced convection should be used as q. c In equation (5), ε represents the thermal emissivity of the conductor, and θ aRepresents the ambient temperature (°C) around the conductor.

[0157] (2) Transformer thermal balance model

[0158] Power transformers are a crucial component of power systems. With the gradual improvement of modern ultra-high voltage (UHV) networks, their voltage levels and capacities are increasing, leading to a corresponding increase in failure rates. Existing literature, starting from the transmission capacity limitations of transformers, has proposed using hotspot temperature and failure rate as constraints. When the hotspot temperature exceeds the upper limit, the aging rate of the insulation material increases dramatically, thus affecting the normal operation of the transformer. Therefore, determining the temperature of its hotspot is one of the important factors determining its operating condition and ensuring the safe operation of grid-connected wind power systems.

[0159] Scholar D. Susa summarized the temperature rise process of a transformer during operation into two stages: (1) hot spot temperature - bottom oil; (2) bottom oil - ambient temperature. The corresponding heat balance equation can be expressed as:

[0160]

[0161]

[0162] In equation (6), C boil The bottom oil heat capacity of the transformer (J / K); q fe It expresses its no-load loss; R boil The nonlinear thermal resistance (K / W) between the oil and air at the bottom of the transformer; θ boil Expressed as its bottom oil temperature (°C); q load For load loss. In equation (7), C hs R is the winding heat capacity (J / K); hs This represents the nonlinear thermal resistance (K / W) between the top insulation surface of its winding and the bottom oil; θ hs Hotspot temperature (°C); q cu This refers to the winding losses of the transformer.

[0163] 2. Electrothermal Coordination Optimization Model

[0164] Based on the thermal balance models of the two commonly used power transmission components mentioned above, this embodiment proposes an electrothermal coordination optimization model to address the electrothermal coordination problem between wind farm output and grid-connected transmission components within a model predictive control framework. The objective function is the maximum power generation of the wind farm. These constraints are nonlinear and include power flow constraints, grid connection line thermal constraints, and generator constraints.

[0165] (1) Variable function

[0166] Under the premise of satisfying voltage level constraints, the objective function is to maximize the active power output of the wind farm, while indirectly minimizing power loss, as shown in the following formula:

[0167]

[0168] In equation (8), P PCC(t) P represents the active power output of the wind farm at time t. Gi(t) P represents the active power output of the wind farm group at node i at time t. loss(t) N represents the active power loss of a grid-connected wind power system at time t. G It is a collection of wind farm clusters, and also represents the set of nodes corresponding to each wind farm in a grid-connected wind power system.

[0169] (2) Constraints

[0170] 1) Equational constraints for current, voltage, and power of wind farm groups considering the thermal characteristics of transmission components

[0171] Currently, the power grid aims to accommodate as much wind power as possible while ensuring safe and reliable operation. Therefore, this invention focuses on the contradictions between grid-connected lines, transformers, and wind farm clusters under emergency conditions. Thus, the power grid is considered sufficiently powerful, equivalent to an infinitely large power system. Simultaneously, by simply adding the active and reactive power adjustment ranges of the generating units, the active and reactive power adjustment ranges of the entire wind farm can be obtained. Therefore, this embodiment equates the grid-connected wind power system to a simple multi-node system. The equation constraints for the current, voltage, and power of each node in the grid-connected wind power system can be expressed as equations (9) to (12).

[0172]

[0173]

[0174]

[0175]

[0176] Where t is the decision cycle of the current control, and N is the set of nodes in the grid-connected wind power system. P ij(t) and Q ij(t) These are the active and reactive power of the transmitting ends at branches i and j, respectively, P. Gj(t) Q is the active power output of the wind farm at time j. ij(t) The reactive power injected into the wind farm at time t, U i(t) And represents the voltage values ​​at nodes i and j, r ij and x ij These are the resistance and reactance of branches i and j, respectively.

[0177] 2) Equation constraints on reactive power output of wind turbines in wind farms and equality constraints in wind farm cluster aggregation.

[0178] For each turbine in a wind farm, its active and reactive power are finite. In a power system, generators typically operate in two modes: constant power factor control and constant voltage control. The generators in this embodiment all utilize constant power factor control. Constant power factor control means the generator power factor is 1, and the specific control method is shown in the following formula.

[0179]

[0180] In equation (13), Q si(t) P is the reactive power output of unit i on the stator side at time t. si(t) It is the active power output of unit i at time t. This is the power factor angle output by unit i on the stator side at time t. In the equivalent grid-connected wind power system proposed in this embodiment, the wind farm is a convergent model. Previous determinations of the active and reactive power limits for grid-connected doubly-fed induction generator (DFIG) wind turbines often directly ignored the system's internal structure and voltage limitations, simply summing the power limit ranges of each unit algebraically. Therefore, for a wind farm containing n DFIG wind turbines, the limits of active and reactive power can be expressed as:

[0181]

[0182]

[0183]

[0184]

[0185] In the formula, n is the number of doubly-fed induction generators in this wind farm.

[0186] 3) Temperature Equality Constraints of Transmission Components

[0187] The temperature equation constraint for overhead conductors can be expressed as:

[0188]

[0189] The transformer temperature equation constraint can be expressed as:

[0190]

[0191]

[0192] 4) Wind farm output constraints

[0193]

[0194] In the formula, P Gi,min(t) P represents the minimum active power output of the wind field at node i at time t. Gi,max(t) Q represents the maximum active power output of the wind field at node i at time t; Gi,min(t) Q represents the minimum reactive power output of the wind field at node i at time t. Gi,max(t) Let t be the maximum reactive power output of the wind field at node i at time t.

[0195] 5) Generator climbing rate

[0196]

[0197] In the formula, P Gv,max(t) Let be the maximum ramp rate of the wind field at node i at time t.

[0198] 6) Temperature constraints of transmission components

[0199]

[0200] In the formula, θ l，max The maximum permissible temperature (°C) for overhead conductors; θ hs，max The maximum permissible temperature (°C) for the transformer hot spot.

[0201] 7) Current-carrying constraints of transmission elements

[0202] I m,(t) ≤I m,max(t) (twenty four)

[0203] In the formula, I m,max(t) Let m be the maximum allowable current carrying capacity of the transmission element.

[0204] 8) Node voltage constraints

[0205]

[0206] In the formula, This represents the maximum voltage limit for node i. This is the minimum voltage limit for node i.

[0207] Engineering Calculation Example 1

[0208] To better verify the technical concept of this application, a specific calculation example analysis is given below: A wind farm cluster centrally connected to a 500kV substation is shown in the connection diagram below. Figure 14As shown, the installed wind power capacity is 345MW. This includes three wind farms connected to the 110kV bus, each with a capacity of 75MW, consisting of 50 doubly-fed wind turbines with a rated capacity of 1.5MW each; and wind farms connected to the 220kV bus with a capacity of 120MW, consisting of 80 doubly-fed asynchronous wind turbines with a rated capacity of 1.5MW each. The area comprises multiple wind farms connected in series via multiple power transmission lines, linking to the 220kV power transmission line via the 110kV line. Simultaneously, a wind farm directly connected to the 220kV bus is connected in series, and then connected to the 500kV bus. To ensure reliable power supply, the wind farm's transmission lines and transformers operate in parallel. The 110kV transmission line uses LGJ-300 / 40 type reinforced aluminum stranded wire, assuming a transformer capacity of 120MVA; LGJ-400 / 35 is the model for the 220kV transmission line. The maximum allowable temperature of the overhead conductor is set at 70℃. For the transformer's hot spot temperature, under normal cyclic load, it can reach a maximum of 120℃, and under sudden faults, it can reach a maximum of 140℃. The entire control process has a time domain of 1 hour. Considering the temperature change characteristics of the external transmission components, the time domain is divided into 12 intervals, each with a duration of Δt = 5 minutes.

[0209] Assume that one of the 110kV transmission lines of the grid-connected wind power system experiences an interruption at time t=0. If the current carrying capacity of the transmission line is not controlled, the conductor temperature of the intact overhead conductor and the power output of the four wind farms during the 12 time periods are shown in Figure 15.

[0210] Depend on Figure 15 It is known that when a line failure occurs, during this period, the other transmitting line will bear the overload in the power transfer, causing the load current of the transmission line to double. Throughout the 12 time periods, the current on the healthy line remains above the static thermal setpoint after 15 minutes, with a peak current of up to 1025A. However, due to the thermal inertia of the conductor, the conductor temperature gradually increases, only exceeding the maximum allowable temperature of 70℃ between 35 and 45 minutes. Using a conservative static thermal setpoint and the maximum allowable temperature of the transmission components as the load limit in overload control, the output decisions for each wind farm and the operating status of the healthy transmission line are as follows. Figure 16 and Figure 17 As shown in Table 2, the output decision results of the four wind farms in the electrothermal coordinated overload control based on model prediction are shown in Table 2.

[0211] Table 2

[0212]

[0213] If the static thermal setpoint of the transmitting conductor is used as a constraint, and one of the transmitting lines experiences a line failure, the three wind farms can only transmit wind energy through the other intact transmitting line. As the wind farm output increases, after 15 minutes, the current carrying capacity of the intact transmitting line exceeds the STR (Stable Temperature Limit), preventing it from transmitting more wind energy. For operational safety, the wind farms must forgo most of their output to meet the static thermal setpoint constraint until the process ends. In summary, using STR as the load constraint ignores the thermal inertia and short-term overload of overhead lines, leading to a conservative decision result. The total wind curtailment during the entire control process is 206.22 MW. However, if the load capacity constraint is assumed to be the maximum allowable temperature of the transmitting conductor, the power flow of the grid-connected wind power system is no longer constrained by STR. After the transmission line disconnection, the instantaneous current of the other transmission line rose from 351A to 482A. During the entire control period, the peak current of the healthy line could reach 920A. Although it remained above its static thermal setpoint (648A) for as long as 45 minutes after the disconnection, the temperature of the transmission conductor only exceeded the maximum allowable temperature of 70℃ for 10 minutes (35-45 minutes) during the entire decision-making period of 1 hour. Therefore, in the two periods of 30-45 minutes (periods 7, 8, and 9), in order to reduce the conductor temperature below the maximum allowable temperature, the wind farm proactively carried out wind curtailment and ultimately maintained the temperature of the transmission conductor at 70℃, highlighting the significant thermal inertia behavior of the overhead conductor. The wind curtailment volume during the entire control process was 67.44MW. Since no priority level was set for the three wind farms, the wind curtailment volume of the three wind farms at the same time was similar. Compared to overload control constrained by the static thermal setpoint of the transmitting conductor, the research results in this section make full use of the carrying capacity of the overhead line under thermodynamic action, reduce the amount of wind curtailment in the wind farm, and accommodate 138.78MW more wind power than by using a conservative static thermal setpoint.

[0214] Engineering Calculation Example 2

[0215] As shown in Engineering Example 1, overhead conductors possess significant thermal inertia, a characteristic that can be leveraged to further explore the short-term overload capacity of transmission lines in grid-connected wind power systems. In grid-connected wind power systems, besides the potential for transmission line failures causing disruptions, the overload capacity of transformers also impacts the wind energy absorption rate of the system under emergency conditions. To investigate the effectiveness of the proposed method in transformer emergency situations, Engineering Example 2 assumes that a step-up transformer at the 110kV busbar in the grid-connected wind power system needs to be taken out of service for maintenance at t=0. Without controlling the operating status of another operating transformer, the output of the three wind farms and the hot spot temperature of the operating transformer during the 12 time periods in the overload control would be as follows: Figure 18 As shown.

[0216] Depend on Figure 18 It can be seen that when one main transformer is taken out of service, the other transformer still in operation will bear the entire load during the 12 time periods of the control process. According to "Power Transformers Part 7: Load Guidelines for Oil-Immersed Power Transformers," the continuous overload capacity of a transformer can be expressed by its load factor (K). C The allowable current load factor K1 for a transformer under normal cyclical load is 1.18 (at which point the transformer's hot spot temperature is 120℃ and the ambient temperature is 20℃). Under long-term emergency load conditions, the maximum allowable hot spot temperature is 140℃. The load factor K1 for the transformer still in operation over 12 time periods is... C If the value exceeds K1 in four time periods, the load factor K for the entire decision-making period is... C The peak value can reach 1.634. Although the transformer hot spot temperature is also rising, it only exceeds 160℃ in 35-45 minutes (control periods 8 and 9), reaching a maximum of 178.44℃. Using the transformer's long-term allowable load factor under normal cyclic load and the transformer's maximum allowable hot spot temperature under long-term emergency load as the load capacity constraints for this engineering example, the decision results for the output of each wind farm and the hot spot temperature change process of the transformers still in operation are shown in Figure 19 and... Figure 20 As shown in Table 3, the output decision results of the four wind farms in the electrothermal coordinated overload control based on model prediction are shown in Table 3.

[0217] Table 3

[0218]

[0219]

[0220] If the long-term allowable load factor of the transformer under normal periodic load is used as a constraint, after one transformer is taken out of operation, as the wind farm output increases, the transformer load factor exceeds the long-term allowable load factor K1 after 30 minutes until 50 minutes (time periods 6, 7, 8, and 9). Therefore, in these four time periods, in order to meet the requirements of the long-term allowable load factor, all three wind farms exhibit some wind curtailment. After 50 minutes, as the wind farm's own output decreases, the transformer current load factor also decreases accordingly, and no limit is exceeded. In summary, using the long-term allowable load factor of the transformer under normal periodic load as a constraint, and neglecting the transformer's thermal inertia and short-term overload, the decision result is relatively conservative. The total wind curtailment of the entire grid-connected wind power system during the entire control process is 130.52MW. If the maximum allowable hot spot temperature of the transformer under long-term emergency load is used as the load capacity limit, after one transformer is taken out of operation, although the load factor of the current of the other still-operating transformer exceeds K1 in four time periods (30-50 min), the hot spot temperature of the transformer only exceeds 140℃ for 10 minutes (35-45 min) during the entire decision-making period. Therefore, in time periods 7-9, in order to meet the operating constraint of the transformer at the maximum allowable hot spot temperature under long-term emergency load, there will be a small amount of predictable wind curtailment in the three wind farms. The total wind curtailment during the entire control process is evenly distributed among the three wind farms, amounting to 87.37MW. During this process, the current of other transmission components is smaller than STR. Compared with using coefficient K1 as a constraint, using the maximum allowable hot spot temperature of the transformer under long-term emergency load as the load capacity limit in overload control highlights its thermal inertia and further explores its overload capacity, reducing the wind curtailment by 43.15MW.

[0221] Engineering Calculation Example 3

[0222] Building upon Examples 1 and 2, this example combines the short-term overload capacity of transformers and transmission lines to further analyze and explore the load potential of transmission components in a grid-connected wind power control system under N-2 conditions. Assuming that one transmission line and one transformer in the system are taken out of operation for maintenance due to a fault at t=0, without constraining the operating status of the transformer and the intact transmission line, the output of the three wind farms, the hot spot temperature of the transformer, and the temperature of the transmission line during the 12 time periods in the control process are as follows: Figure 21 As shown.

[0223] Depend on Figure 21It can be seen that, under the condition of N-2, the sound transmission line and the still-operating transformer will bear the overload of power flow transfer during the decision period. Throughout the overload control process, for the overhead conductor, as the wind farm output increases, the current on the sound line will exceed the static thermal setpoint in 9 time periods (15-60 minutes). The current load factor of the still-operating transformer will exceed the long-term allowable current load factor under normal periodic load in 6 time periods. However, due to the thermal inertia of the overhead conductor and transformer, the conductor temperature of the transmission line will only exceed 70℃ in 6 time periods. The hot spot temperature of the transformer will only exceed 140℃ in 2 time periods. Therefore, overload control is performed using the static thermal setpoint of the transmission line, the long-term allowable current load factor of the transformer under normal periodic load, the maximum allowable temperature of the transmission line, and the maximum allowable hot spot temperature of the transformer under long-term emergency load as constraints. The decision results for each wind farm output and the operating status of the sound transmission line and transformer are as follows: Figure 22 and Figure 23 As shown in Table 4, the output decision results of the four wind farms in the electrothermal coordinated overload control based on model prediction are as follows.

[0224] Table 4

[0225]

[0226] If the STR value of the transmitting conductor and the transformer coefficient K1 are used as operating constraints, after one transmitting line and one transformer are taken out of operation due to fault maintenance, the current carrying capacity of the transmitting conductor reaches 738.32A within 15 minutes, reaching the upper limit, and remains at the STR value until the overload control ends; while the transformer's current load coefficient K1 also reaches its limit within 15 minutes. CThe value reached 1.186, hitting the upper limit of the constraint. This situation persisted until 45 minutes later when it was alleviated due to the decrease in wind farm output. In order to meet the constraints of the transmission lines and transformers under conservative conditions, the wind farms had to give up a large portion of their output to maintain safe operation until the end of the process. During this process, the total amount of wind curtailed was 355.74MW. Assuming that overload control is performed based on the maximum allowable temperature of the transmission lines and the maximum allowable hot spot temperature of the transformer under long-term emergency load, for the transmission lines, when the transmission line is taken out of operation, the peak current of the healthy line during the entire control period can reach 1027A. The current carrying capacity is higher than the static thermal setpoint for 45 minutes. However, the conductor temperature exceeds the maximum allowable temperature for only 20-40 minutes during the control period. Since the conservative static thermal setpoint constraint is abandoned, the three wind farms have a process-based wind curtailment action within 15-40 minutes to ensure that the conductor temperature of the transmission lines does not exceed 70℃. Meanwhile, when one transformer is taken out of operation, the remaining transformer takes over all wind power output. Its hot spot temperature only exceeds 140℃ for 30-40 minutes. Since the thermal inertia of the transformer is not as significant as that of the transmission line, the maximum output of the wind farm is determined by the maximum allowable temperature of the transmission line for 20-30 minutes during the entire control process, and by the maximum hot spot temperature of the transformer under long-term emergency load conditions for 30-40 minutes. Throughout the entire control process, the three wind farms relatively evenly distributed a total of 85.59MW of wind curtailment. In summary, compared to conservative static thermal setpoint constraints, using the maximum allowable temperature of the transmission line and the maximum hot spot temperature of the transformer as constraints reduced wind curtailment by 270.143MW, highlighting the thermal inertia of the two transmission components and improving the grid-connected wind power system's ability to absorb wind energy. Since the thermal inertia of overhead conductors is more significant than that of transformers, when the maximum allowable temperature of both transmission components fails to meet the constraint conditions, the maximum hot spot temperature of the transformer is often used as the constraint condition for overload control of the entire system. This is more in line with the rule that the thermal inertia of overhead conductors is more significant than that of transformers.

[0227] A model predictive control-based method for electrothermal coordinated overload control of grid-connected wind power systems. Within the framework of model predictive control, this method uses the current measurement information of the grid-connected wind power system as the initial value for the next prediction, performing rolling optimization and iteration. This, to a certain extent, corrects the impact of prediction errors on the overload control results, aiming to maximize the short-term overload capacity of transmission lines and components, enabling rapid restoration of normal system operation under emergency conditions and improving the utilization efficiency of transmission components. Case studies show that traditional overload control methods using STR (Short-Terminal Limit) restrict the short-term overload capacity of transmission lines and components. This method, however, uses the maximum allowable temperature as a constraint, further exploring the short-term overload capacity of overhead conductors and transformers. Compared to traditional overload control methods, this method more proactively and deeply explores the overload capacity of grid-connected wind power system transmission components, significantly improving the utilization rate of transmission components. Meanwhile, when the maximum allowable temperatures of both overhead conductors and transformers fail to meet the constraints, the maximum hot spot temperature of the transformer is often used as the constraint in the overload control of the entire system. This is more in line with the fact that overhead conductors have a more significant thermal inertia than transformers.

[0228] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for thermal coordination overload control of a grid-connected wind power system, Its characteristic is that it performs the following steps: Obtain the current measurement values ​​of the transmission components of the grid-connected wind power system and the current measurement values ​​of the wind farm; Based on meteorological data, wind speed is predicted, the temperature of power transmission components is obtained, and the active power of the wind farm within the set time step of the current control cycle is predicted. Taking into account wind speed forecasts, transmission component temperatures, and wind farm active power forecasts, an optimization problem is established based on the wind power grid-connected system's electrothermal coordination model. Process-oriented electrothermal coordination control is implemented to ensure that the grid-connected line temperature does not exceed limits during overload control. The electrothermal coordination model assumes reasonable voltage distribution, uses the active power output of each wind turbine as the decision variable, and minimizes the wind curtailment of all doubly-fed asynchronous wind turbines as the objective function, expressed as: wherein, t represents the current decision period, P WGmax,i(t) and P WG,i(t) Pi(t) and Pimax(t) represent the active power output of the doubly-fed wind turbine i at time t and the maximum active power limit calculated by online measurement, respectively, M G is the set of all wind turbines in the grid-connected wind power system; Alternatively, the electrothermal coordination model of the wind power grid-connected system, under the premise of satisfying voltage level constraints, takes maximizing the active power output of the wind farm while indirectly minimizing power loss as its objective function, and is expressed as: in, P PCC(t) Indicates the time of the wind farm t The active output, P Gi(t) Represents a node i In time t Active power output of the wind farm group at that time P loss(t) Indicates the time of grid-connected wind power system t Active power loss, It is a collection of wind farm clusters, and also represents the set of nodes corresponding to each wind farm in a grid-connected wind power system; The optimization problem is solved under constraints to determine the optimal control sequence. The active power of the first wind farm group in the optimal control sequence is then applied to the power generation control of the current wind farm.

2. The method for electrothermal coordinated overload control of a grid-connected wind power system as described in claim 1, characterized in that, The current measurements of the power transmission element include wind speed, ambient temperature, and solar radiation intensity along the transmission line; the current measurements of the wind farm include wind speed.

3. The method for electrothermal coordinated overload control of a grid-connected wind power system as described in claim 1, characterized in that, The constraints of the wind power grid-connected system electrothermal coordination model based on reasonable voltage distribution include wind farm power flow balance constraints, overhead line temperature constraints, transformer temperature constraints, transmission element current carrying constraints, node voltage constraints, and active-reactive power regulation range constraints of doubly-fed asynchronous wind turbine generator units.

4. The method for electrothermal coordinated overload control of a grid-connected wind power system as described in claim 1, characterized in that, The constraints of the wind power grid-connected system electrothermal coordination model under the premise of satisfying voltage level constraints include the equality constraints of current, voltage and power of wind farm group considering the thermal characteristics of transmission components, the equality constraints of reactive power output of wind turbine units in wind farm and the equality constraints in wind farm group aggregation, the equality constraints of transmission component temperature, wind farm output constraints, generator ramp rate, transmission component temperature constraints, transmission component current carrying constraints and node voltage constraints.

5. The method for electrothermal coordinated overload control of a grid-connected wind power system as described in claim 1, characterized in that, While performing process-oriented electrothermal coordination control, the voltage level of each wind turbine node is dynamically monitored. Once an overlimit situation is detected, control is performed based on the active-reactive power regulation range of the doubly-fed asynchronous wind turbine to keep the voltage level within the set range.

6. The method for electrothermal coordinated overload control of a grid-connected wind power system as described in claim 1, characterized in that, The specific process for determining the optimal control sequence is as follows: Based on the constraints of the electrothermal coordination model of the wind power grid-connected system and with the objective function of minimizing the wind curtailment of the wind farm group, the model is solved as a nonlinear optimal problem, which can be solved using the interior point method.

7. A grid-connected wind power system with coordinated electrothermal overload control, characterized in that, include: The parameter acquisition module is configured to acquire the current measurement values ​​of the transmission components of the grid-connected wind power system and the current measurement values ​​of the wind farm; The parameter prediction module is configured to predict wind speed based on meteorological data, obtain the temperature of power transmission components, and predict the active power of the wind farm within the set time step of the current control cycle. The model building module is configured to comprehensively consider wind speed predictions, transmission component temperatures, and wind farm active power predictions. Based on the wind power grid-connected system electrothermal coordination model, it establishes an optimization problem and performs process-oriented electrothermal coordination control to ensure that the grid-connected line temperature does not exceed limits during overload control. The wind power grid-connected system electrothermal coordination model assumes reasonable voltage distribution, uses the active power output of each wind turbine as a decision variable, and takes minimizing the wind curtailment of all doubly-fed asynchronous wind turbines as the objective function, expressed as: in, t Represents the current decision-making period. P WGmax,i(t) and P WG,i(t) These represent the active power output of the doubly-fed wind turbine unit i at time t, and the maximum active power limit calculated through online measurement, respectively. M G It is the collection of all wind turbine generators in a grid-connected wind power system; Alternatively, the electrothermal coordination model of the wind power grid-connected system, under the premise of satisfying voltage level constraints, takes maximizing the active power output of the wind farm while indirectly minimizing power loss as its objective function, and is expressed as: in, P PCC(t) Indicates the time of the wind farm t The active output, P Gi(t) Represents a node i In time t Active power output of the wind farm group at that time P loss(t) Indicates the time of grid-connected wind power system t Active power loss, It is a collection of wind farm clusters, and also represents the set of nodes corresponding to each wind farm in a grid-connected wind power system; The optimization control module is configured to solve optimization problems under constraints, determine the optimal control sequence, and apply the active power of the first wind farm group in the optimal control sequence to the power generation control of the current wind farm.

8. A terminal device, characterized in that, It includes a processor and a computer-readable storage medium, the processor being used to implement various instructions; the computer-readable storage medium being used to store a plurality of instructions adapted to be loaded by the processor and executed as steps in the method of any one of claims 1-6.

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