A capacity assessment method and system for integrated wind and storage systems based on dynamic heat settling

Abstract

This invention belongs to the field of wind and energy storage capacity assessment, and provides a method and system for capacity assessment of integrated wind and energy storage systems based on dynamic thermal setpoints. The method includes: acquiring the output power of the integrated wind and energy storage system and the actual environmental variables of the pre-installed turbine location; calculating the electro-thermal coupling relationship between the integrated wind and energy storage system and the main power system via overhead transmission lines based on dynamic thermal setpoints; analyzing the power transmission status of the overhead transmission lines based on the obtained electro-thermal coupling relationship and the actual environmental variables of the pre-installed turbine location; and determining the output capacity of the integrated wind and energy storage system based on the power transmission status of the overhead transmission lines and the initial capacity of the integrated wind and energy storage system. This invention solves the electro-thermal balance equations of the dynamic heat exchange process affected by various changing environmental conditions, effectively analyzing the optimal scale of wind farms and energy storage considering the dynamic performance of dedicated overhead lines, while simultaneously achieving a balance between investment costs and operational efficiency.

Description

Technical Field

[0001] This invention belongs to the field of wind and storage capacity assessment technology, specifically relating to a method and system for assessing the capacity of an integrated wind and storage system based on dynamic thermal settling. 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] The trade-off between the uncertainties of wind power generation and the efficiency of dedicated overhead transmission lines (OTLs), which connect wind farms and the main power grid to transmit fluctuating power flows, remains an unresolved issue. Deploying energy storage systems in large wind farms to maintain system power balance presents an opportunity to resolve this contradiction. With the decreasing cost of energy storage devices, new wind farms generally require the inclusion of energy storage equipment to mitigate power output fluctuations. Energy storage operation can significantly reduce the power reserve requirements of the main power grid under the influence of wind power uncertainties, thereby improving system stability.

[0004] Centralized wind farms are primarily located in remote areas with abundant wind resources, far from load centers. Therefore, dedicated overhead transmission lines, as an effective and reliable transmission technology, are used to transmit wind power and integrate it into the main power system. Typically, power generation and transmission belong to and are regulated by different operating systems. On the power generation side, the need to increase profits has spurred more investment in building integrated wind power systems, creating a demand for transmission equipment. However, grid company decision-makers are reluctant to invest heavily in dedicated overhead transmission lines connecting wind power integrated systems to the main system. This is due to the low utilization rate of dedicated overhead transmission lines caused by the volatility and intermittency of sustainable energy. Given these two contradictions, exploring the potential transmission capacity of these lines has become a key issue for economically and efficiently expanding the scale of wind power systems.

[0005] Static thermal rating (STR) is an effective method for evaluating the maximum permissible current or active power of a transmission line under a fixed set of typical environmental parameters. However, environmental conditions can vary significantly over time and at different locations. While traditional STR methods for assessing transmission capacity can largely guarantee system safety, the line's capacity is not fully utilized when carrying fluctuating and intermittent renewable power, thus reducing its operational efficiency. Therefore, maximizing the utilization of overhead transmission lines and further expanding the scale of wind energy integration becomes a challenging decision.

[0006] Dynamic thermal rating (DTR) calculates the available capacity of power lines using real-time environmental parameters, overcoming the conservatism of traditional static methods and effectively increasing the scale of integrated wind power systems connected to the main grid. Furthermore, changes in environmental factors such as wind speed not only directly alter the output of wind turbine generators but also affect transmission capacity through their impact on the electrothermal characteristics of overhead transmission lines. For example, higher wind speeds increase wind power generation and provide favorable conditions for line heat dissipation, thereby increasing transmission capacity. Therefore, DTR significantly enhances the physical capabilities of transmission systems and improves the efficiency of wind power grid connection. However, research on synchronous timing simulation of wind power generation and the transmission capacity of overhead transmission lines is limited, which is one of the main problems addressed in this embodiment. Summary of the Invention

[0007] To address the aforementioned issues, this invention proposes a capacity assessment method and system for integrated wind and energy storage systems based on dynamic thermal setpoints. This invention resolves the conflict between wind power generation and transmission by configuring energy storage systems within wind farms, defining this as an integrated wind and energy storage system. Through coordination among wind power generation, maximizing transmission potential, and the energy storage system, it is expected to optimize investment economics and operational performance within the integrated wind power system. Transmission capacity assessment based on environmental condition changes rather than traditional static parameters is considered a more effective method for guiding energy storage operation within integrated wind power systems.

[0008] According to some embodiments, the first aspect of the present invention provides a capacity assessment method for an integrated wind and storage system based on dynamic thermal setpoints, employing the following technical solution:

[0009] A capacity assessment method for integrated wind and storage systems based on dynamic thermal settling includes:

[0010] Obtain the output power of the integrated wind and storage system and the actual environmental variables of the pre-installed unit location;

[0011] Based on dynamic thermal setpoints, the electro-thermal coupling relationship of overhead transmission lines between the integrated wind and energy storage system and the main power system is calculated;

[0012] Based on the obtained electro-thermal coupling relationship and the actual environmental variables of the pre-installed equipment location, the power transmission status of the overhead transmission line is analyzed;

[0013] The output capacity of the integrated wind and energy storage system is determined based on the power transmission status of the overhead transmission line and the initial capacity of the integrated wind and energy storage system.

[0014] According to some embodiments, the second aspect of the present invention provides a capacity assessment system for an integrated wind and storage system based on dynamic thermal settling, employing the following technical solution:

[0015] A capacity assessment system for integrated wind and storage systems based on dynamic thermal settling includes:

[0016] The data acquisition module is configured to acquire the output power of the integrated wind and storage system and the actual environmental variables of the pre-installed unit location;

[0017] The data processing module is configured to calculate the electro-thermal coupling relationship between the wind-storage integrated system and the main power system through overhead transmission lines based on dynamic thermal setpoints.

[0018] The transmission capacity analysis module is configured to analyze the power transmission status of overhead transmission lines based on the obtained electro-thermal coupling relationship and the actual environmental variables of the pre-installed location;

[0019] The evaluation module is configured to determine the output capacity of the integrated wind and energy storage system based on the power transmission status of the overhead transmission line and the initial capacity of the integrated wind and energy storage system.

[0020] According to some embodiments, a third aspect of the present invention provides a computer-readable storage medium.

[0021] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the capacity assessment method for an integrated wind-storage system based on dynamic thermal settling as described in the first aspect above.

[0022] According to some embodiments, a fourth aspect of the present invention provides a computer device.

[0023] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps in the capacity assessment method for an integrated wind-storage system based on dynamic thermal setpoints as described in the first aspect above.

[0024] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0025] This invention proposes a method for calculating the power transmission limitations of overhead transmission lines by solving the electrothermal balance equations of a dynamic heat exchange process affected by various changing environmental conditions. Furthermore, under the condition that the conductor temperature remains at its maximum allowable value, wind power transmission is optimized and maximized through energy storage operation. Further, simulations based on this method demonstrate the coordinated operation of wind farms, associated energy storage systems, and dedicated overhead transmission lines, i.e., a wind-storage integration system (WSIS). This analysis considers the effectiveness of optimizing the scale of wind farms and energy storage based on the dynamic performance of dedicated overhead lines, while simultaneously achieving a balance between investment costs and operational efficiency. 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 the power transmission model between the integrated wind and energy storage system and the main power system in this embodiment of the invention;

[0028] Figure 2 This is a flowchart of the algorithm for evaluating the transmission capacity of overhead power transmission lines in an embodiment of the present invention;

[0029] Figure 3 This is a flowchart of the wind farm capacity assessment algorithm in an embodiment of the present invention;

[0030] Figure 4 These are the operating characteristic curves corresponding to different power levels in the embodiments of the present invention;

[0031] Figure 5 These are simulation results of the dynamic evaluation method in the embodiments of the present invention;

[0032] Figure 6 This describes the relationship between wind curtailment and energy storage ratio in this embodiment of the invention.

[0033] Figure 7 These are simulation results under energy storage coordinated control in the embodiments of the present invention;

[0034] Figure 8 This is the result of the economic simulation algorithm in the embodiments of the present invention;

[0035] Figure 9 This refers to the amount of wind curtailment generated due to power transmission limitations in this embodiment of the invention. Detailed Implementation

[0036] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0037] 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 in these embodiments have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0038] It should be noted that 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. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0039] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0040] Example 1

[0041] This embodiment provides a capacity assessment method for an integrated wind and storage system based on dynamic thermal settling. In this embodiment, the method includes the following steps:

[0042] Obtain the output power of the integrated wind and storage system and the actual environmental variables of the pre-installed unit location;

[0043] Based on dynamic thermal setpoints, the electro-thermal coupling relationship of overhead transmission lines between the integrated wind and energy storage system and the main power system is calculated;

[0044] Based on the obtained electro-thermal coupling relationship and the actual environmental variables of the pre-installed equipment location, the power transmission status of the overhead transmission line is analyzed;

[0045] The output capacity of the integrated wind and energy storage system is determined based on the power transmission status of the overhead transmission line and the initial capacity of the integrated wind and energy storage system.

[0046] The method is as follows:

[0047] The intermittency and volatility of wind power generation severely impact the reliability and stability of wind power systems. To mitigate the negative impacts of wind power grid connection, wind farms are often equipped with a certain proportion of energy storage. The application of energy storage systems improves the quality of wind power grid connection and wind energy utilization efficiency. In this study, wind farms equipped with energy storage and their dedicated overhead lines are defined as integrated wind-storage systems. This section focuses on the establishment and interpretation of integrated wind-storage models that consider environmental factors.

[0048] 1. Power transfer model based on integrated wind and energy storage system and power system

[0049] The equivalent test model of WSIS (Wind and Storage Integrated System) is as follows: Figure 1 As shown, wind farms equipped with energy storage and the main power system located in two different locations are connected via dedicated overhead lines. Wind power is transmitted between the power source node (W) and the receiving node (S) via the connecting lines. Furthermore, for wind power grid connection, reactive power compensation devices should be properly planned to provide optimal voltage support for wind power generation. In this case, it can be assumed that there is sufficient reactive power on both sides of the overhead transmission line to ensure the level and stability of the node voltage amplitude. Then, the power value of each unit transmitted via the dedicated overhead line can be expressed as:

[0050]

[0051]

[0052]

[0053] in

[0054]

[0055] In the formula, Z B It is the reference value of the reactance, which can be calculated according to equation (5); P w and P s It refers to the active power output and received by the wind farm; P loss I and r are the active power loss and current flowing through the line; r and x are the resistance and reactance per unit length of the overhead transmission line; L is the length of the line; correspondingly, R and X are the series resistance and reactance of the transmission line. θ is the phase angle difference between the complex voltage and the complex current; U G U w and U S These are the voltages at nodes G, W, and S, respectively.

[0056]

[0057] In equation (5), S B U B I B These represent the reference capacity, reference voltage, and reference current, respectively.

[0058] The integrated wind-storage power is defined by equation (1), which represents the actual wind power generation value integrated into the main system. Furthermore, it is assumed that the voltage amplitudes of both nodes can operate at constant voltage, and U is set respectively. s =1.0pu,U w =1.0pu. Then, according to equation (4), equations (1) and (2) can be rewritten as follows to obtain the P of each unit. w and P s .

[0059]

[0060]

[0061] Furthermore, since power transmission networks generally use a star connection, the phase current can be considered equal to the line current, and z is the line impedance value. According to equation (8), the current passing through the line can be expressed as a function of r, L, and θ by equation (8):

[0062]

[0063] 2. Integrated wind and energy storage model considering electrothermal characteristics

[0064] Since the environmental conditions of three-phase overhead conductors are not significantly different, when simulating the electrothermal behavior of three-phase overhead transmission lines, it can be assumed that the environmental parameters of different phases are the same. In traditional power system analysis, r is generally regarded as a constant, ignoring the changes in r caused by electrothermal coupling. Here, r is the resistance per unit length of the overhead transmission line. For actual transmission line operation, the line temperature and r are approximately linearly related within a certain range, which can be expressed by equation (9).

[0065]

[0066] Here, the proportionality coefficient σ describes the correlation between temperature and resistance. T is the operating temperature of the circuit, and R... h and R l These represent high temperature (T) h ) and low temperature (T l The resistance value under ().

[0067] The electrothermal relationship of overhead transmission lines can be represented in two ways. One is an electrothermal coupling solution algorithm that focuses on the steady-state thermal behavior of the line, as shown in Equation (10). Steady-state electrothermal coupling assumes that when heat absorption and dissipation reach equilibrium, the derivative of temperature with respect to time is 0. The other method focuses on the dynamic thermal behavior of the line, allowing the line temperature to change dynamically with time, as shown in Equation (11).

[0068] f s =-(I·I B ) 2 r+Q=0 (10)

[0069]

[0070] in,

[0071] Q = q s -q c -q r (12)

[0072] f s It is the static thermal setpoint difference component, f d It is the dynamic thermal setpoint difference component, where Q is the value of heat exchange between the overhead line and the outside world, and C is the value of heat exchange between the overhead line and the outside world. p It is the specific heat capacity of the circuit;

[0073] q s q c and q s The detailed expression is as follows:

[0074] 1) Convective heat loss q c

[0075] q c Including natural convection (q cn) and forced convection (q cf As shown in equation (13).

[0076] q c =max(q) cn ,q cf (13)

[0077] q cf Under different wind speed conditions, different relationships can be obtained, as shown in equation (14).

[0078]

[0079] in,

[0080] C h =(Dρ f V w ) / μ f (15)

[0081] Where D is the conductor diameter. V w It refers to the wind speed around the power line. T a It refers to the ambient temperature around the line. Define T. f The average values ​​of ambient temperature and conductor temperature are shown in equation (16).

[0082] T f =(T+T) a ) / 2 (16)

[0083] K f and μ f The formulas are given in equations (17) and (18), respectively, and they are both T. f The function, under feasible operating conditions, with T f It increases with the increase of.

[0084] k f It is the thermal conductivity of air. μ f It is the absolute viscosity of air.

[0085]

[0086]

[0087] K a and ρ f It can be calculated using equations (19) and (20) respectively.

[0088] K a =1.194-cos(φ)+0.194cos(2φ)+0.368sin(3φ) (19)

[0089]

[0090] Where φ represents the angle between the wind direction and the guide wire, and He represents the altitude. cn The expression is detailed in equation (21).

[0091]

[0092] b) Radiative heat loss q r

[0093] q r It depends on the diameter and surface conditions of the conductor, therefore, q as shown in equation (22) r The detailed expression depends on D, T, T a and emissivity ε.

[0094]

[0095] c) Solar thermal gain q s

[0096] In q s Both direct and diffusion effects were considered. q s The detailed expression for is given in equation (23).

[0097] q s =αDK s Q s sinθ s (twenty three)

[0098] Where α is the absorption rate of light by the circuit, which is determined by the material of the conductor. Q s K represents radiant heat intensity. s The elevation correction factor for the route is shown in equation (24):

[0099]

[0100] Among them, altitude H e It varies within the altitude range of 0-3000 meters in human habitation. According to equations (23) and (24), q s With H e The effective incident angle θ gradually increases. s As shown in equation (25).

[0101]

[0102] In the formula, Z c and Z l The azimuth angles of the sun and the conductor are respectively, and the azimuth angle Z is... l Using due south as the reference direction. Due to the arbitrary direction of overhead transmission lines, Za It is a variable between 0 and 90°. ω is the hour angle, L a Where δ is the geographical latitude, N is the solar declination angle, and H is the number of days in a year. c The solar altitude angle is the angle between the sun's rays and the horizontal plane, ranging from 0 to 90°. Where C... a It is determined by ω and λ, as shown in equation (26).

[0103]

[0104] δ and Q s The relationship can be obtained using equation (27), which means that the range of δ is between -23.46 and 23.46.

[0105]

[0106] Among them, A i This represents the polynomial coefficients for solar thermal intensity under different environments. N is the number of days in a year. The options for this parameter depend on the actual operating conditions of the overhead transmission line; specific values ​​can be found in the references. It is worth noting that q... s q c and q s Both can be represented as functions of environmental variables. Based on the electro-thermal coupling characteristics of overhead transmission lines, environmental factors can be introduced to analyze the power transmission status of the lines. Furthermore, environmental conditions also simultaneously affect wind power generation and transmission. Under normal operating conditions, high wind speeds allow wind turbines to generate more wind power. Simultaneously, due to high wind speeds, ideal heat dissipation of overhead conductors allows dedicated lines to carry more wind power. Therefore, the dynamic process involving the electro-thermal coupling behavior of wind power generation and dedicated overhead transmission lines can accurately reflect the grid connection capacity of wind power, thereby determining the optimal scale.

[0107] Evaluation algorithm for wind farm integration scale

[0108] 1. Pretreatment of multiple environmental factors

[0109] Traditional static methods focus on the steady state of the transmission system, assuming that the lines reach and maintain a state of thermal equilibrium.

[0110] In this study, the 795kcmil 26 / 7 Drake ACSR overhead line was selected, and IEEE-738std was used to study its thermal behavior. Traditional static methods focus on the steady state of the transmission system, assuming that the line reaches and maintains a thermal equilibrium state, thus eliminating the integral term in equation (11). However, considering the dynamic changes in environmental factors under actual operating conditions, the temperature of overhead transmission lines changes dynamically in real time. In addition, the uncertainty of wind farm output leads to dynamic changes in the current of the transmission line. Therefore, with the increase of wind power penetration, the steady-state method shows more shortcomings in modern power system analysis. Dynamic methods that capture the line's electrical coupling behavior are considered more practical. Since changes in environmental factors cannot be derived into explicit functional expressions, it makes line temperature tracking difficult, further affecting the assessment of the transmission capacity of the line in real time.

[0111] Therefore, in this study, the changes in environmental variables are approximated as piecewise linearized functions. Then, by solving the differential equation in equation (11), the electrothermal behavior of the circuit can be simulated in real time, which involves all time-varying environmental variables.

[0112] To simplify the relationship of θ in equation (1), r is treated as a constant. Therefore, the input is a set of discrete P w To obtain discrete values ​​of θ. During subsequent real-time evaluation of the line transmission capacity, r is considered to be dynamically changing, as shown in Equation (9), thus reflecting the dynamic thermal processes of the line.

[0113] In addition, variables such as phase angle difference, ambient temperature, wind speed, wind direction and time angle are approximated as linear functions of time, as shown in equations (28)-(32) respectively.

[0114] θ(t)=θ(t1)+t·[θ(t2)-θ(t1)] / (t2-t1) (28)

[0115] T a (t)=T a (t1)+t·(T a (t2) - T a (t1)) / (t2-t1) (29)

[0116] V w (t)=V w (t1)+t·(V w (t2)-V w (t1)) / (t2-t1) (30)

[0117] D w (t)=[D w (t1)+t·(D w(t2)-D w (t1)) / (t2-t1)]·π / 180 (31)

[0118] ω(t)=[ω(t1)+t·(ω(t2)-ω(t1)) / (t2-t1)]·π / 180 (32)

[0119] Here, t1 and t2 represent the first and last moments of the sampling time interval, respectively. As the sampling time interval shortens, the accuracy of the simulation results is expected to improve, but this will correspondingly increase the computational burden. Note that N is the number of days in a year, a continuous integer variable that does not require linear processing, as shown in equation (33).

[0120] N = N(n) (33)

[0121] Therefore, the differential equation system formed by substituting equations (28)-(32) into equation (11) is obtained. The variable at the end of the previous time is set as the initial value of the next time. Then, by iteratively solving equation (11), the dynamic solution of the conductor temperature can be obtained.

[0122] 2. Algorithm for assessing the transmission capacity of overhead transmission lines under the combined influence of multiple environmental factors

[0123] The societal demand for low-carbon energy has led to a continuous increase in the demand for sustainable energy sources such as wind power. Considering the asynchronous planning and construction of power generation and transmission, a mismatch may occur between wind power capacity and the current carrying capacity of dedicated overhead transmission lines. Assessing the transmission capacity of overhead lines under typical environmental conditions is relatively conservative and may limit the scale of wind power integration. On the other hand, over-investment in dedicated overhead transmission lines may lead to resource waste. Therefore, this embodiment proposes a dynamic transmission capacity assessment algorithm for overhead transmission lines that considers actual environmental conditions. The assessment is achieved through coordination and iteration between dynamic and steady-state methods. Detailed procedures are as follows... Figure 2 As shown, where:

[0124] 1) Input the parameters at the start and end of the sampling time interval to complete the linearization process. Then, use a dynamic method to simulate the operation of the overhead transmission line.

[0125] 2)θ m It is an intermediate variable for dynamic thermal setpoint, calculated based on actual operating environmental parameters, and calculated by a static algorithm, as shown in equation (34). Here, actual environmental parameters are taken, and the maximum allowable temperature of the line is set to T. m .

[0126]

[0127] 3) If the line temperature is higher than 100℃, reduce the step factor by θ. m. θ m Substitute into the dynamic method and solve until T (n+1) =T m Otherwise, set a step size factor to increase θ. m until temperature T (n+1) =T m In practical calculations, the convergence interval can be set to [T-ΔT, T] to avoid algorithm oscillations. That is, the calculation of the sampling interval ends when the temperature reaches [T-ΔT, T].

[0128] 4) Substitute the θ obtained by the algorithm designed above into equation (1) to calculate the maximum wind power generation that can be integrated under real-time operating conditions.

[0129] The specific method is as follows:

[0130] Step 1: Based on the wind farm output power P w According to equation (1), the phase angle difference θ of the bus voltage at both ends is calculated. To simplify the calculation, the resistance variable in the equation is set to a constant value. At the same time, the calculated bus voltage angle difference is used instead of the current as the calculation variable. Combined with discrete environmental factor variables, the line temperature change is continuously tracked according to equation (11).

[0131] Step 2: Substitute the current environmental factor variable values ​​and the maximum allowable temperature Tm into equation (34) to calculate the intermediate variable θm of the dynamic thermal setpoint, and determine whether the line temperature exceeds the thermal limit temperature T. m If no limit is exceeded, a constant step factor μ is set and continuously increased by θm until the transmission line temperature is within the range of the maximum allowable temperature; determine whether the line temperature exceeds the thermal limit temperature Tm. If it exceeds the limit, a constant step factor μ is set and continuously decreased by θm until the transmission line temperature is within the range of the maximum allowable temperature.

[0132] Step 3: After the full-time simulation of the line is completed, the voltage phase angle difference sequence at the sending and receiving ends is obtained. Based on equation (11), the maximum integrated power P of the line is calculated. jud .

[0133] 3. Energy Storage Model

[0134] Because energy storage enables the spatial and temporal conversion of energy, wind energy can be stored when the actual wind power output exceeds the maximum allowable transmission power. Simultaneously, when the wind power output falls below the maximum allowable transmission power, the stored wind energy can be integrated into the grid to further reduce wind curtailment and increase the operating profits of power plants.

[0135] The energy storage model can be represented as follows:

[0136] Regarding the charging process:

[0137] E ess (t)=Eess (t-Δt)+P ess (t)*Δt*η ess,c (35)

[0138]

[0139] For the discharge process:

[0140]

[0141]

[0142] In the formula: E ess Let P be the remaining energy of the energy storage system at time t. ess (t) represents the charging power of the energy storage device at time t, SOC represents the state of charge of the system, and E essN η is the rated capacity of the energy storage system. ess,c and η ess,d These represent the system's charge and discharge efficiencies, respectively. Δt It is the sampling time interval.

[0143] The constraints are as follows:

[0144] 1) Charge state constraints:

[0145] SOC min ≤SOC≤SOC max (39)

[0146] Among them, SOC min and SOC max These are the minimum and maximum states of charge.

[0147] 2) Charging and discharging limitations

[0148] 0≤P ess ≤P essN (40)

[0149] Among them, P essN This refers to the rated power of the energy storage.

[0150] 4. Wind farm capacity assessment considering the electrothermal coupling characteristics of overhead transmission lines

[0151] This section proposes an economic optimization algorithm for wind farm capacity. This algorithm applies the aforementioned transmission capacity assessment model to determine the economically optimal size of the wind farm. Wind power exceeding the transmission line's capacity can be absorbed by energy storage devices. However, once the energy storage system is saturated, excess wind power generation will be reduced. The algorithm calculates the amount of wind curtailment caused by limitations of the integrated wind-storage system. Wind curtailment affects the efficiency of renewable energy power plants and transmission systems.

[0152] 1) LCCA

[0153] Life cycle cost (LCC) refers to the annualized cost over the entire economic life of a wind farm, including investment, interruptions, maintenance, interest, and revenue. Specifically, revenue is treated as a negative cost in the modeling process. Without considering revenue, the LCC of a wind farm can be expressed as follows:

[0154]

[0155] Among them, C A This represents the investment cost. (C) ope (i) represents the i-th time. th Annual maintenance costs, C inv This is the initial construction cost. Based on the net present value method, the annual operation and maintenance cost is calculated using a discount factor q. i Discounted to the first year. The specific solution for q is shown in equation (41), where z is the discount rate. LT represents the technology life. R res This represents the residual value of equipment invested in after LT (Long-Term Investment).

[0156] The revenue in this study only includes the revenue generated by wind power plants.

[0157] C inc (k)=min(P w ,P jud )*t*E price (42)

[0158] Where k is the number of sampling periods, E price For electricity price, C inc (k) represents the operating revenue for the kth sampling period.

[0159] 2) Curtailment volume

[0160] The amount of wind curtailment in LT can be calculated using the relationship shown in equation (43).

[0161]

[0162] Among them, E cur (k,i) represents the amount of wind curtailment in the k-th sampling period of the i-th year, E curall P represents the amount of wind curtailment over the entire life cycle. jud This indicates the power transmission limit.

[0163] c) Algorithm

[0164] The process of evaluating the algorithm is as follows: Figure 3 As shown.

[0165] 1) Input the initial capacity P of the wind farm rate and maximum allowed access capacity Pmax Set the initial value of the expansion factor to 0;

[0166] 2) The installed capacity of the wind farm is P rate Under the premise that, calculate C in year i respectively ope (i) and C inc (i). Note that the operating revenue C in year i is... inc (i) This can be achieved by using C for all sampling periods within the i-th year. inc (i) Summation is performed. Then, the above calculation is repeated until the simulation in LT is confirmed to be complete.

[0167] 3) Then calculate C A And determine whether the current capacity level of the WSIS (Wind and Storage Integrated System) is lower than P. max If so, increase P proportionally. rate As shown in equation (44), then repeat steps 2 and 3. Otherwise, the output will have C with different capacity sizes. A .

[0168] P rate =P rate +μP rate (44)

[0169] μ represents the iteration factor.

[0170] Research Case

[0171] This example focuses on the performance of the 795kcmile 26 / 7 Drake ACSR corresponding to IEEE-738Std, with a maximum permissible temperature of 100 degrees Celsius. When the conductor temperature exceeds 100°C, the resistance is no longer assumed to be linearly related to temperature due to unacceptable errors. However, in the approximate calculation of the short-circuit current, even when the temperature is much higher than T... tl Equation (12) is still used to estimate the resistance value. The meteorological and operational parameters in this study were collected from multiple wind farms in actual operation. Due to the limitations of the source data, the sampling interval was set to 15 minutes in this case. The parameters of the WSIS dedicated transmission line are shown in Table 1. In addition, r corresponding to the discrete angle value was set to 8.235*10-5Ω / m.

[0172] Table 1 Parameters of the test system

[0173]

[0174]

[0175] A. Verification of the transmission capacity assessment algorithm

[0176] This case study aims to demonstrate the effectiveness of the proposed transmission capacity assessment algorithm compared to traditional assessment methods. Furthermore, this section verifies the improvement of wind power integration performance through the use of energy storage technology. Measured data from actual wind farms with energy storage configurations in my country are used. Then, over a one-year period, the proposed assessment method is used to simulate the transmission operation and line temperature variations of dedicated overhead transmission lines from 13 adjacent wind farms with different capacities. The highest operating temperature and maximum allowable transmission power of the dedicated overhead transmission lines over one year are shown below. Figure 4 As shown.

[0177] like Figure 4 As shown, the maximum line temperature has a quadratic function relationship with wind power. The maximum allowable temperature of the line is set to 100℃. When the thermal limit is reached, the maximum allowable transmission power of the line connecting different wind farms is approximately 443MW, due to their proximity and similar environmental conditions. Furthermore, if the maximum allowable temperature of the line is set to 100℃, the electricity from wind farms with a capacity of less than 265MW can be fully integrated into the system without exceeding transmission limits. In this case, energy storage configured at the wind farm does not need to handle and store excess wind energy. Otherwise, wind farms with a capacity greater than 265MW must pay higher energy storage costs to handle excess wind power generation, or directly reduce wind power generation regardless of cost.

[0178] To verify the effectiveness of the proposed evaluation algorithm, this embodiment conducts a detailed analysis of a 375MW wind farm. The electrothermal behavior of wind power generation and dedicated transmission lines is simultaneously simulated in a real-world operating scenario, and the dynamic and static thermal limit conditions are compared. It is worth noting that the static thermal limit is defined as V... w The value was obtained under the assumption that the speed is 0.5 m / s; T a =40℃; D w =330°; ω=0°; N=258. Substituting all conservative values ​​into equations (36) and (1), the static power transfer limit can be obtained. The simulation results for a typical day are as follows: Figure 5 As shown.

[0179] exist Figure 5 In this context, the static evaluation method calculates the power transmission limit based on traditional environmental parameters. T_static is the line temperature at which the transmitted power reaches the static power transmission limit. From... Figure 5 Observations revealed that T_static remained consistently low. Using a static evaluation method would waste transmission resources. Conversely, a dynamic evaluation method calculates power transmission limits based on real-time environmental parameters. T_Dynamic is the temperature at which the power transmitted on a dedicated overhead transmission line reaches its dynamic power transmission limit. Figure 5As can be seen, T_Dynamic remains around 100℃ but does not exceed 100℃, indicating that the dynamic evaluation method can fully utilize the transmission capacity of the line. Specifically, around 16:30, the allowable transmission power of the dynamic evaluation method begins to fall below the actual output, at which point energy storage needs to be activated. Furthermore, due to wind fluctuations, the time for wind power output to reach and maintain its peak load is not very long, generally relatively short. Therefore, because the line operates under light load for most of the time, it is not fully utilized.

[0180] Given limited transmission resources, improving line utilization to integrate larger-scale wind farms into the system remains an unresolved issue. The peak power generation of ultra-large-scale wind farms can lead to transmission congestion on some dedicated overhead transmission lines with limited capacity. Integrating energy storage into wind farms to form integrated wind power plants is an option to address the conflict between asynchronous power generation and transmission. However, considering the synergistic effects of integrated wind and energy storage systems, an analysis of the optimal system size is still necessary.

[0181] A 375MW wind farm was selected as the research object, with energy storage configured from 0% to 55% of the wind farm's installed capacity. The maximum transmission capacity of the relevant lines was used as the decision variable to control the operation of the energy storage device. When the wind farm's output exceeds its maximum transmission capacity, wind power generation is stored; otherwise, the energy storage operates in a discharge state. The scheme based on the line's DTR (Direct Transmission Rate) is called the dynamic energy storage control scheme, and the scheme based on STR (Speed ​​Transmission Rate) is called the static energy storage control scheme. The wind curtailment results under different energy storage ratios are as follows: Figure 6 As shown. E CDTR E represents the amount of wind curtailment using a dynamic energy storage control scheme. CSTR This indicates the amount of wind curtailment that is controlled using a static energy storage scheme.

[0182] like Figure 6 As shown, increasing the energy storage configuration in wind farms can significantly reduce wind curtailment. When the energy storage capacity reaches approximately 20% of the wind farm's installed capacity, E CDTR This can be reduced to a stable, lower level. Therefore, configuring the energy storage capacity of a wind farm to be around 20% of its installed capacity is reasonable. When the energy storage ratio is 20%, E CSTR Significantly greater than E CDTR This indicates that a DTR-based operating scheme can optimize system performance. However, this also means that STR-based energy storage capacity decisions for power lines will lead to inefficient investment. Figure 7 Detailed simulation results involving coordinated control of energy storage are shown.

[0183] As observed, when wind power output is less than the line's maximum allowable transmission power, the energy storage discharge time is from 8:45 to 9:45. However, due to charging and discharging power limitations, the output of the integrated wind and energy storage system will not always equal the line's transmission capacity. Due to SOC constraints, the energy storage device remains in reserve between 8:45 and 16:15. After 16:15, because wind power output exceeds the line's maximum allowable transmission power, the energy storage device discharges. Therefore, the application of energy storage reduces wind curtailment and improves grid utilization through power flow buffering.

[0184] B. Validation of the wind farm size assessment algorithm

[0185] The wind farm size assessment methodology is validated as follows. In this case study, costs include the cost of constructing and operating the wind power generation system, the cost of an additional transmission line, and electricity sales revenue (negative costs). The operation and maintenance and investment costs per unit capacity of the wind farm and a newly constructed transmission line are discounted to the first year and calculated separately in the LCC. w and LCC l Considering the middle. Set LT = 20 years; E price =470 yuan / MW; LCC w =1×108 yuan / MW; LCC l =2 × 10⁸ yuan / MW; Z = 7%. Three planning and investment schemes, DLR, SLR1, and SLR2, were designed, corresponding to using dynamic standards, using static standards with no new lines, and using static standards with new lines, respectively. The results of the economic simulation algorithm are as follows: Figure 8 As shown.

[0186] Wind curtailment caused by power transmission restrictions, such as Figure 9 As shown, the wind energy cut always increases with the size of the wind farm. Furthermore, the wind energy cut can be significantly higher when using traditional static methods than with dynamic methods. The results indicate that applying dynamic strategies can increase the integration of renewable energy and improve network utilization.

[0187] Fluctuations in wind power can lead to low utilization rates of dedicated transmission lines connecting wind farms and the power system, increasing the difficulty of system operation and planning. To resolve the conflict between wind power generation and transmission, energy storage systems are configured within wind farms; this embodiment defines it as a wind-storage integrated system. By coordinating wind power generation, maximizing transmission potential, and the energy storage system, it is hoped that investment economics and operational performance can be optimized in the integrated wind power system. Transmission capacity assessment based on environmental condition changes rather than traditional static parameters is considered a more effective method for guiding energy storage operation in integrated wind power systems.

[0188] To address this, this embodiment proposes a transmission capacity assessment model that considers the real-time electrothermal coupling effect of overhead transmission lines. This model is applied to wind farm energy storage control schemes. Energy storage adjustments mitigate wind power flow fluctuations, fully utilize transmission capacity, and enable grid connection of larger-scale wind farms. Simulation models of wind power generation, transmission, and energy storage operation established based on this model and method can be used to analyze the maximization of wind power integration scale and economic optimization under conditions of limited transmission resources.

[0189] Example 2

[0190] This embodiment provides a capacity assessment system for an integrated wind and storage system based on dynamic thermal settling, including:

[0191] The data acquisition module is configured to acquire the output power of the integrated wind and storage system and the actual environmental variables of the pre-installed unit location;

[0192] The data processing module is configured to calculate the electro-thermal coupling relationship between the wind-storage integrated system and the main power system through overhead transmission lines based on dynamic thermal setpoints.

[0193] The transmission capacity analysis module is configured to analyze the power transmission status of overhead transmission lines based on the obtained electro-thermal coupling relationship and the actual environmental variables of the pre-installed location;

[0194] The evaluation module is configured to determine the output capacity of the integrated wind and energy storage system based on the power transmission status of the overhead transmission line and the initial capacity of the integrated wind and energy storage system.

[0195] The examples and application scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the content disclosed in Embodiment 1 above. It should be noted that the above modules, as part of the system, can be executed in a computer system such as a set of computer-executable instructions.

[0196] The descriptions of each embodiment in the above embodiments have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0197] The proposed system can be implemented in other ways. For example, the system embodiments described above are merely illustrative, and the division of modules described above is only a logical functional division. In actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed.

[0198] Example 3

[0199] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in the capacity assessment method for an integrated wind-storage system based on dynamic thermal setpoints as described in Embodiment 1 above.

[0200] Example 4

[0201] This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the capacity assessment method for an integrated wind and storage system based on dynamic thermal setpoints as described in Embodiment 1 above.

[0202] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0203] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0204] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0205] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0206] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0207] 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 capacity assessment method for an integrated wind and storage system based on dynamic thermal settling, characterized in that, include: Obtain the output power of the integrated wind and storage system and the actual environmental variables of the pre-installed unit location; Based on dynamic thermal setpoints, the electro-thermal coupling relationship of overhead transmission lines between the integrated wind and energy storage system and the main power system is calculated; Based on the obtained electro-thermal coupling relationship and the actual environmental variables of the pre-installed equipment location, the power transmission status of the overhead transmission line is analyzed, including: Input the parameters at the start and end of the sampling time interval to complete the linearization process, and use a dynamic method to simulate the operation of overhead transmission lines; Based on the obtained electro-thermal coupling relationship and the actual environmental variables of the pre-installed equipment location, the maximum line temperature is determined. Tm The maximum phase angle difference between complex voltage and complex current θm ; If the circuit temperature exceeds 100°C, reduce the step factor setting. θm, Will θm Substitute into the dynamic method and solve until... T ( n +1)= Tm ; Otherwise, increase the step size factor. θm until the temperature T (n+1)= Tm ; The phase angle difference between the complex voltage and complex current obtained by the above dynamic method θ Substitute the power calculation formula of the power node unit of the overhead transmission line into the calculation formula to calculate the maximum wind power generation that can be integrated under real-time operation. Based on the power transmission status of the overhead transmission line and the initial capacity of the integrated wind and energy storage system, the output capacity of the integrated wind and energy storage system is determined, including: 1) Input the initial capacity of the wind farm P rate and maximum allowed access capacity P max Set the initial value of the expansion factor to 0; 2) The installed capacity of the wind farm is P rate Under the premise that, in the first Calculated in the year respectively in the year Annual maintenance costs and the Annual operating revenue Among them, the first Annual operating revenue By examining the first All sampling periods within the year Summation is performed; then, the above calculation is repeated until completion is confirmed. LT Simulation in; 3) Then calculate the investment cost. C A And determine whether the current capacity level of the integrated wind and storage system is lower than that of the wind and storage system. P max If so, increase proportionally. P rate Then repeat steps 2 and 3; otherwise, output with different capacity sizes. C A .

2. The capacity assessment method for an integrated wind and storage system based on dynamic thermal settling as described in claim 1, characterized in that, The actual environmental variables at the pre-installed location include phase angle difference, wind direction, wind speed, ambient temperature, and hour angle.

3. The capacity assessment method for an integrated wind and storage system based on dynamic thermal settling as described in claim 1, characterized in that, The calculation of the electro-thermal coupling relationship between the wind-storage integrated system and the main power system based on dynamic thermal setpoints includes: Based on the correlation between line temperature and resistance, the electrothermal behavior of three-phase overhead transmission lines with the same environmental parameters in different phases is determined. Based on the electrothermal behavior of three-phase overhead transmission lines with the same environmental parameters in different phases, the electrothermal coupling relationship and dynamic thermal behavior of overhead transmission lines are determined.

4. The capacity assessment method for an integrated wind and storage system based on dynamic thermal settling as described in claim 1, characterized in that, The formula for calculating the power of generator units at power nodes in overhead transmission lines is as follows: P w It is the active power output of the wind farm; r and x These are the resistance and reactance values ​​per unit length of an overhead transmission line; L It is the length of the line; correspondingly, R and X These are the series resistance and reactance of the transmission line; It is the phase angle difference between complex voltage and complex current; U G and U S These are node G and node S The voltage at that point.

5. The capacity assessment method for an integrated wind and storage system based on dynamic thermal settling as described in claim 1, characterized in that, The output power of the integrated wind and energy storage system is specifically as follows: in ， In the formula, Z B This is the baseline value for reactance; P w and P s It is the active power output and received by the wind farm; P loss and I It refers to the active power loss and the current flowing through the line; r and x These are the resistance and reactance values ​​per unit length of an overhead transmission line; L It is the length of the line; correspondingly, R and X These are the series resistance and reactance of the transmission line. It is the phase angle difference between complex voltage and complex current; U G , U w and U S These are nodes G and G, W and nodes S The voltage at that point.

6. A capacity assessment system for an integrated wind and storage system based on dynamic thermal settling, characterized in that, include: The data acquisition module is configured to acquire the output power of the integrated wind and storage system and the actual environmental variables of the pre-installed unit location; The data processing module is configured to calculate the electro-thermal coupling relationship between the wind-storage integrated system and the main power system through overhead transmission lines based on dynamic thermal setpoints. The transmission capacity analysis module is configured to analyze the power transmission status of overhead transmission lines based on the obtained electro-thermal coupling relationship and the actual environmental variables of the pre-installed location, including: Input the parameters at the start and end of the sampling time interval to complete the linearization process, and use a dynamic method to simulate the operation of overhead transmission lines; Based on the obtained electro-thermal coupling relationship and the actual environmental variables of the pre-installed equipment location, the maximum line temperature is determined. Tm The maximum phase angle difference between complex voltage and complex current θm ; If the circuit temperature exceeds 100°C, reduce the step factor setting. θm, Will θm Substitute into the dynamic method and solve until... T ( n +1)= Tm ; Otherwise, increase the step size factor. θm until the temperature T (n+1)= Tm ; The phase angle difference between the complex voltage and complex current obtained by the above dynamic method θ Substitute the power calculation formula of the power node unit of the overhead transmission line into the calculation formula to calculate the maximum wind power generation that can be integrated under real-time operation. The evaluation module is configured to determine the output capacity of the integrated wind and energy storage system based on the power transmission status of the overhead transmission line and the initial capacity of the integrated wind and energy storage system, including: 1) Input the initial capacity of the wind farm P rate and maximum allowed access capacity P max Set the initial value of the expansion factor to 0; 2) The installed capacity of the wind farm is P rate Under the premise that, in the first Calculated in the year respectively in the year Annual maintenance costs and the Annual operating revenue Among them, the first Annual operating revenue By examining the first All sampling periods within the year Summation is performed; then, the above calculation is repeated until completion is confirmed. LT Simulation in; 3) Then calculate the investment cost. C A And determine whether the current capacity level of the integrated wind and storage system is lower than that of the wind and storage system. P max If so, increase proportionally. P rate Then repeat steps 2 and 3; otherwise, output with different capacity sizes. C A .

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps in the capacity assessment method for an integrated wind and storage system based on dynamic thermal setpoints as described in any one of claims 1-5.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the wind-storage integrated system capacity assessment method based on dynamic thermal setpoint as described in any one of claims 1-5.

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