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CN-122026353-A - Meteorological-new energy-power grid-charging four-layer coupling cooperative control method and system

CN122026353ACN 122026353 ACN122026353 ACN 122026353ACN-122026353-A

Abstract

The invention discloses a meteorological-new energy source-power grid-charging four-layer coupling cooperative control method and system, and relates to the technical field of smart power grids. The method comprises the steps of receiving real-time weather forecast data, correcting new energy output prediction based on wind gust effect and cloud shielding effect under extreme weather, outputting corrected new energy power data, calculating vulnerability indexes of a system through four-dimensional dynamic evaluation frames based on the new energy power data, real-time running data and standby capacity data of a power grid, coordinating a power grid side, a distribution network side and a load side to conduct layered optimization and power distribution by adopting the vulnerability indexes as general control languages, converting the vulnerability indexes into continuous and smooth charging power limit curves through Sigmoid mapping functions, and executing corresponding emergency plans. According to the invention, through the technologies of gust correction, cloud shielding prediction, four-dimensional vulnerability assessment, sigmoid self-adaptive control and the like, the consumption of renewable energy sources is maximized on the premise of ensuring the safety of a power grid, and the charging experience of a user is improved.

Inventors

  • LI LINLIN
  • WU WEIWEI
  • LIU XIANG

Assignees

  • IEC国际标准促进中心(南京)
  • 东南大学

Dates

Publication Date
20260512
Application Date
20260109

Claims (10)

  1. 1.A meteorological-new energy source-power grid-charging four-layer coupling cooperative control method is characterized by comprising the following steps of: Receiving real-time weather forecast data, correcting new energy output prediction based on wind gust effect and cloud shielding effect under extreme weather, and outputting corrected new energy power data; Based on the new energy power data, the power grid real-time operation data and the spare capacity data, the vulnerability index of the framework computing system is dynamically estimated through four dimensions; adopting vulnerability indexes as general control languages, and coordinating a power grid side, a distribution network side and a load side to perform layered optimization and power distribution; And converting the vulnerability index into a continuous and smooth charging power limit curve through a Sigmoid mapping function, and executing a corresponding emergency plan according to a preset five-level early warning system.
  2. 2. The four-layer coupling cooperative control method of weather-new energy-power grid-charging according to claim 1, wherein the method is characterized by receiving real-time weather forecast data, correcting new energy output prediction based on wind gust effect and cloud shielding effect under extreme weather, and outputting corrected new energy power data, and specifically comprises the following steps: (21) Correcting the standard power curve according to the wind speed change rate, calculating an gust correction coefficient and outputting corrected wind power: (21.1) wind power standard power curve is as follows: In the formula, Cut in the wind speed, the minimum wind speed that the blower begins to generate electricity; rated wind speed; cutting out the wind speed, and stopping the blower to protect the maximum wind speed; Rated power of the fan; under the condition of no influence of gusts and slow change of wind speed, the actual wind power Regarded as ; (21.2) Wind power after wind gust correction: Wherein the gust correction factor The calculation of the gust correction factor is as follows: In the formula, Safety threshold, below which the wind speed can be changed immediately without correction, at this time ; When the cut-off threshold value is higher than the cut-off threshold value, the fan automatically stops for protection, and the power output is 0; attenuation coefficient; attenuation index; (22) Calculating the change rate of the photovoltaic power and the corrected photovoltaic power according to the irradiance change rate, wherein the method comprises the following steps of: (22.1) the power of the photovoltaic power generation depends on the irradiance G (t) of the horizontal plane, and the calculation formula is: In the formula, Representing instantaneous horizontal irradiance; Representing the photovoltaic area; The temperature correction coefficient is indicated as such, Wherein T is the battery temperature; representing inverter efficiency; (22.2) photovoltaic power Rate of change Ramp Rate: unit and risk classification: The unit is kW/min; the Ramp Rate is less than 100 kW/min, so that the safety is realized, and the distribution network can stably absorb the safety; 100. the Rate is less than or equal to 500 kW/min, early warning is carried out, and frequency modulation auxiliary service needs to be started; 500. Alarm, wherein the Ramp Rate is less than or equal to 1000 kW/min, and the distribution network voltage begins to flash; dangerous conditions, such as Ramp Rate not less than 1000 kW/min, can cause interference of user equipment; (23) Calculating corrected new energy power data according to the corrected wind power gust and the corrected photovoltaic power: In the formula, Indicating the corrected photovoltaic power level, And indicating the corrected wind power gust.
  3. 3. The four-layer coupling cooperative control method of weather-new energy-power grid-charging according to claim 2, wherein the vulnerability index of the framework computing system is calculated through four-dimensional dynamic evaluation based on new energy power data, power grid real-time operation data and standby capacity data The method is characterized by comprising the following steps: (31) Wherein the frequency stability The system frequency change RoCoF and steady state deviation are integrated as follows: The frequency stability comprises two components, steady state deviation And dynamic RoCoF deviation The method is characterized by comprising the following steps: Wherein the weights are ; Steady-state component calculation: dynamic component calculation: If RoCoF _max < 1.0 Hz/s, f_d=0, indicating security; if 1.0≤ RoCoF _max < 2.0 Hz/s, f_d increases linearly If RoCoF _max is greater than or equal to 2.0 Hz/s, f_d=1.0, indicating a critical condition; (32) Voltage stability Node out-of-limit penalty, specifically as follows: index of voltage stability Where N is the number of monitoring nodes, Voltage out-of-limit penalty term for node i: if all node voltages are in the range of 0.95-1.05, f_volt=0, indicating complete safety; if the voltage of a certain node reaches 0.90 (5% under-voltage), the penalty term e_i=1.0 for that node If any node voltage exceeds an extreme boundary of 0.85-1.10, f_volt=1.0, indicating a crisis; (33) Work angle stability The redundancy of CCT and protection action time is as follows: parameter definition: the value is 0.1-0.3 s through transient stability calculation; Standard action time of the protection device; When cct≡0.12 s and t_protect=0.15 s, the time margin is only 0.03 s, at the critical boundary, f_power is close to 1.0; (34) Spare capacity The backup demand assessment of meteorological drive is as follows: wherein the required standby R req is driven by the uncertainty of the load and the new energy, and is specifically calculated as follows: parameter definition: the fluctuation coefficient of the load is taken as a first moment, and 10% of the load is taken as a first moment; uncertainty coefficient of new energy; weather uncertainty coefficient; Fine day, σ=0.2; Cloudiness σ=0.5; Typhoons/storms σ=1.0; rotating the spare capacity.
  4. 4. The weather-new energy-power grid-charging four-layer coupling cooperative control method of claim 3, wherein the vulnerability index is used as a general control language to coordinate the layered optimization and power distribution of a power grid side, a distribution network side and a load side, and the method is characterized by comprising the following steps: (41) Cost minimization goal for grid side L1: Wherein: First item Representing the running cost of the quick start unit; Second item The start-stop cost of the slow start unit is represented, and x g is a 0-1 start-stop decision variable; Third item The opportunity cost of renewable energy source power rejection is represented; constraint conditions: Power balance constraint: spare abundance constraint: vulnerability constraint, constraint threshold for L1 layer: namely, the grid side should ensure that the vulnerability index is not more than 0.5; the power constraint is as follows: based on the vulnerability assessment, L1 calculates the maximum power that can be allocated to the distribution network and charging: Where P avail,grid is the grid available generated and scheduled power, and P margin,grid is the emergency margin that must be reserved; (42) Power distribution optimization of distribution network side L2 After receiving the power constraint P limit,L1 issued by the L1, the distribution network needs to maximize the power distributed to charging through energy storage buffering and reactive power optimization; distribution network power availability: Wherein: Energy storage buffer strategy: constraint conditions: Upper limit of charge-discharge power: ; SOC (state of charge) range: ; charge and discharge efficiency: ; Reactive power optimization to reduce line loss: distribution network line loss model: the reactive power distribution is optimized by adjusting the reactive power injection Q_i of each node, so that the loss is reduced; (43) Load side L3 space-time transfer optimization The load side L3 receives the power distribution P_s of the distribution network side L2 and is responsible for transferring and guiding the charging time and place of the user so as to maximize the response of the system; multi-objective optimization problem of space-time transfer: Wherein: The acceptance degree of the user u to the place and time transfer is represented; Representing a transition decision variable; Representing the cost of time transfer; Representing the cost of site transfer; Compensation mechanism for time transfer: Carbon-row-targeting-based user compensation Wherein: Representing the compensation proportion, wherein the compensation is 0.2 yuan/kWh for each reduction of 1 g/kWh carbon row; Representing the charge quantity of a user; representing a reference marginal carbon number factor; The carbon rejection factor representing the actual charging time.
  5. 5. The four-layer coupling cooperative control method of weather-new energy-power grid-charging according to claim 4, wherein the vulnerability index is converted into a continuous smooth charging power limit curve through a Sigmoid mapping function, and a corresponding emergency plan is executed according to a preset five-level early warning system, and the method is specifically as follows: sigmoid power quota mapping: In the formula, Representing the maximum charge power allowed by the system; The steepness of Sigmoid; Sigma (& gt) represents a standard Sigmoid function and a value range (0, 1); derivative of Sigmoid and response speed: Derivative of P limit on F Wherein z=f-f_thresh; the maximum slope occurs at z=0, i.e. f=f_thresh, when: For p_max=500 mw, k=20, the maximum slope is 2500 MW per unit vulnerability, which means that when the vulnerability increases by 0.05 around 0.3, the charging power will decay rapidly from 95% to 50%, the response speed is fast enough; definition and triggering of a five-stage emergency plan: early warning level judgment function Green early warning F < 0.2, maintaining 100% charging power, and response time >5 minutes; The yellow early warning is that F is more than or equal to 0.2 and less than or equal to 0.4, limiting the power to 95 percent, and starting the quick start unit to stand by; The orange early warning is that F is more than or equal to 0.4 and less than or equal to 0.6, limiting the power to 60%, starting energy storage discharge and 40% user space-time transfer; The red early warning is that F is more than or equal to 0.6 and less than or equal to 0.8, limiting the power to 20 percent, and executing automatic load shedding; And the black early warning F is more than or equal to 0.8, limiting the power to 5%, and stopping all non-emergency charging.
  6. 6. A weather-new energy-power grid-charging four-layer coupling cooperative control system for implementing the weather-new energy-power grid-charging four-layer coupling cooperative control method as set forth in any one of claims 1 to 5, comprising: the weather-new energy coupling modeling layer is used for receiving real-time weather forecast data, correcting new energy output prediction based on the wind gust effect and the cloud shielding effect under extreme weather, and outputting corrected new energy power data; The vulnerability index evaluation layer is in communication connection with the meteorological-new energy coupling modeling layer and is used for calculating the vulnerability index of the system through four-dimensional dynamic evaluation frames based on new energy power data, power grid real-time operation data and spare capacity data; The three-side collaborative optimization layer is in communication connection with the vulnerability index evaluation layer and comprises a power grid side scheduling module, a power distribution network side power distribution module and a load side demand response module, wherein the three-side modules perform layered optimization and power distribution by taking the vulnerability index as a unified constraint condition; The charging power emergency control layer is in communication connection with the three-side layered collaborative optimization layer, and is used for converting the vulnerability index into a continuous smooth charging power limit curve through a Sigmoid mapping function and executing a corresponding emergency plan according to a preset five-level early warning system.
  7. 7. The four-layer coupling cooperative control system of weather-new energy source-power grid-charging as set forth in claim 6, wherein the weather-new energy source coupling modeling layer comprises: the wind power gust power correction module is used for correcting a standard power curve according to the wind speed change rate, calculating a gust correction coefficient and outputting corrected wind power, and specifically comprises the following steps: The wind power standard power curve is as follows: In the formula, Cut in the wind speed, the minimum wind speed that the blower begins to generate electricity; rated wind speed; cutting out the wind speed, and stopping the blower to protect the maximum wind speed; Rated power of the fan; under the condition of no influence of gusts and slow change of wind speed, the actual wind power Regarded as ; (21.2) Power after wind gust correction Wherein the gust correction factor The calculation of the gust correction factor is as follows: In the formula, Safety threshold, below which the wind speed can be changed immediately without correction, at this time ; When the cut-off threshold value is higher than the cut-off threshold value, the fan automatically stops for protection, and the power output is 0; attenuation coefficient; attenuation index; The photovoltaic power correction module is used for calculating the change rate of the photovoltaic power and corrected photovoltaic power according to the change rate of irradiance, and specifically comprises the following steps: the power of photovoltaic power generation depends on the irradiance G (t) of the horizontal plane, and the calculation formula is as follows: In the formula, Representing instantaneous horizontal irradiance; Representing the photovoltaic area; The temperature correction coefficient is indicated as such, Wherein T is the battery temperature; representing inverter efficiency; photovoltaic power Rate of change Ramp Rate: unit and risk classification: The unit is kW/min; The method comprises the steps of safety of the Ramp Rate < 100 kW/min, stable absorption of a distribution network, early warning of the Ramp Rate < 500 kW/min which is not more than 100, starting of frequency modulation auxiliary service, alarm of the Ramp Rate < 1000 kW/min which is not more than 500, starting of flickering of the distribution network voltage, emergency of the Ramp Rate which is not less than 1000 kW/min, and interference of user equipment; the new energy power data calculation module is used for calculating corrected new energy power data according to the corrected wind power gust and the photovoltaic power: In the formula, Indicating the corrected photovoltaic power level, And indicating the corrected wind power gust.
  8. 8. The four-layer coupling cooperative control system for meteorological-new energy-power grid-charging as set forth in claim 6, wherein in said vulnerability index assessment layer, vulnerability index The calculation is specifically as follows: (31) Wherein the frequency stability The system frequency change RoCoF and steady state deviation are integrated as follows: The frequency stability comprises two components, steady state deviation And dynamic RoCoF deviation The method is characterized by comprising the following steps: Wherein the weights are ; Steady-state component calculation: dynamic component calculation: If RoCoF _max < 1.0 Hz/s, f_d=0, indicating security; if 1.0≤ RoCoF _max < 2.0 Hz/s, f_d increases linearly If RoCoF _max is greater than or equal to 2.0 Hz/s, f_d=1.0, indicating a critical condition; (32) Voltage stability Node out-of-limit penalty, specifically as follows: index of voltage stability Where N is the number of monitoring nodes, Voltage out-of-limit penalty term for node i: if all node voltages are in the range of 0.95-1.05, f_volt=0, indicating complete safety; if the voltage of a certain node reaches 0.90 (5% under-voltage), the penalty term e_i=1.0 for that node If any node voltage exceeds an extreme boundary of 0.85-1.10, f_volt=1.0, indicating a crisis; (33) Work angle stability The redundancy of CCT and protection action time is as follows: parameter definition: the value is 0.1-0.3 s through transient stability calculation; Standard action time of the protection device; When cct≡0.12 s and t_protect=0.15 s, the time margin is only 0.03 s, at the critical boundary, f_power is close to 1.0; (34) Spare capacity The backup demand assessment of meteorological drive is as follows: wherein the required standby R req is driven by the uncertainty of the load and the new energy, and is specifically calculated as follows: parameter definition: the fluctuation coefficient of the load is taken as a first moment, and 10% of the load is taken as a first moment; uncertainty coefficient of new energy; weather uncertainty coefficient; Fine day, σ=0.2; Cloudiness σ=0.5; Typhoons/storms σ=1.0; rotating the spare capacity.
  9. 9. The four-layer coupling cooperative control system for meteorological-new energy-power grid-charging according to claim 8, wherein the three-side cooperative optimization layer coordinates the layered optimization and power distribution of the power grid side, the power distribution side and the load side, and is characterized by comprising the following specific steps: Cost minimization goal for grid side L1: Wherein: First item Representing the running cost of the quick start unit; Second item The start-stop cost of the slow start unit is represented, and x g is a 0-1 start-stop decision variable; Third item The opportunity cost of renewable energy source power rejection is represented; constraint conditions: Power balance constraint: spare abundance constraint: vulnerability constraint, constraint threshold for L1 layer: namely, the grid side should ensure that the vulnerability index is not more than 0.5; the power constraint is as follows: based on the vulnerability assessment, L1 calculates the maximum power that can be allocated to the distribution network and charging: Where P avail,grid is the grid available generated and scheduled power, and P margin,grid is the emergency margin that must be reserved; power distribution optimization of distribution network side L2 After receiving the power constraint P limit,L1 issued by the L1, the distribution network needs to maximize the power distributed to charging through energy storage buffering and reactive power optimization; distribution network power availability: Wherein: Energy storage buffer strategy: constraint conditions: Upper limit of charge-discharge power: ; SOC (state of charge) range: ; charge and discharge efficiency: ; Reactive power optimization to reduce line loss: distribution network line loss model: the reactive power distribution is optimized by adjusting the reactive power injection Q_i of each node, so that the loss is reduced; Load side L3 space-time transfer optimization The load side L3 receives the power distribution P_s of the distribution network side L2 and is responsible for transferring and guiding the charging time and place of the user so as to maximize the response of the system; multi-objective optimization problem of space-time transfer: Wherein: The acceptance degree of the user u to the place and time transfer is represented; Representing a transition decision variable; Representing the cost of time transfer; Representing the cost of site transfer; Compensation mechanism for time transfer: Carbon-row-targeting-based user compensation Wherein: Representing the compensation proportion, wherein the compensation is 0.2 yuan/kWh for each reduction of 1 g/kWh carbon row; Representing the charge quantity of a user; representing a reference marginal carbon number factor; The carbon rejection factor representing the actual charging time.
  10. 10. The four-layer coupling cooperative control system of weather-new energy-power grid-charging according to claim 9, wherein in the charging power emergency control layer, vulnerability index is converted into a continuous smooth charging power quota curve through a Sigmoid mapping function, and corresponding emergency plans are executed according to a preset five-level early warning system, and the four-layer coupling cooperative control system is characterized in that: sigmoid power quota mapping: In the formula, Representing the maximum charge power allowed by the system; The steepness of Sigmoid; Sigma (& gt) represents a standard Sigmoid function and a value range (0, 1); derivative of Sigmoid and response speed: Derivative of P limit on F Wherein z=f-f_thresh; the maximum slope occurs at z=0, i.e. f=f_thresh, when: For p_max=500 mw, k=20, the maximum slope is 2500 MW per unit vulnerability, which means that when the vulnerability increases by 0.05 around 0.3, the charging power will decay rapidly from 95% to 50%, the response speed is fast enough; definition and triggering of a five-stage emergency plan: early warning level judgment function Green early warning F < 0.2, maintaining 100% charging power, and response time >5 minutes; The yellow early warning is that F is more than or equal to 0.2 and less than or equal to 0.4, limiting the power to 95 percent, and starting the quick start unit to stand by; The orange early warning is that F is more than or equal to 0.4 and less than or equal to 0.6, limiting the power to 60%, starting energy storage discharge and 40% user space-time transfer; The red early warning is that F is more than or equal to 0.6 and less than or equal to 0.8, limiting the power to 20 percent, and executing automatic load shedding; And the black early warning F is more than or equal to 0.8, limiting the power to 5%, and stopping all non-emergency charging.

Description

Meteorological-new energy-power grid-charging four-layer coupling cooperative control method and system Technical Field The invention relates to the technical field of smart grids, in particular to a weather-new energy-power grid-charging four-layer coupling cooperative control system method and system. Background With the continuous improvement of permeability of wind power, photovoltaic and other intermittent renewable energy sources in an electric power system and the large-scale growth of charging loads of electric automobiles, the operation and control of the electric power system face unprecedented challenges. Especially under extreme meteorological conditions, the contradiction between the severe fluctuation of the new energy output and the safe and stable operation of the power grid is increasingly prominent. Currently, the technical solution to this problem mainly has the following drawbacks: The current mainstream new energy power prediction model is mostly based on a standard power curve or a statistical learning method. For example, wind power predictions often use standard wind speed-power (v-P) curves, and photovoltaic power predictions are dependent on historical irradiance data. However, under extreme meteorological conditions such as typhoons, strong convection, etc., severe sudden changes in wind speed and irradiance can occur in the order of seconds or minutes, producing significant "gust effects" and "cloud cover effects". The existing model can not be effectively coupled with weather forecast data with high space-time resolution, particularly dynamic parameters such as wind speed change rate (dv/dt) and irradiance change rate (dG/dt), so that the predicted power and the actual output deviate seriously; In the field of system stability evaluation, the traditional method mainly relies on single or double-dimensional discrete indexes such as frequency, voltage and the like, and offline analysis is performed through a transient stability calculation tool (such as DIGSILENT, PSCAD). The method has high computational complexity and slow response, and is difficult to meet the requirements of real-time quantification and rapid early warning on the vulnerability of the system in a high-proportion new energy permeation scene. In recent years, students propose a unified evaluation system of comprehensive energy storage indexes and the like, but the indexes often lack a definite physical basis, are difficult to calibrate parameters, and cannot effectively integrate multidimensional risk information such as a frequency change rate (RoCoF), a voltage out-of-limit, a power angle stability margin, a reserve capacity adequacy margin and the like. Therefore, the invention provides a meteorological-new energy source-power grid-charging four-layer coupling cooperative control system method and system. Disclosure of Invention The invention aims to provide a weather-new energy source-power grid-charging four-layer coupling cooperative control system method and system, which maximize the consumption of renewable energy sources and improve the charging experience of users on the premise of ensuring the safety of a power grid through the technologies of gust correction, cloud shielding forecast, four-dimensional vulnerability assessment, sigmoid self-adaptive control and the like. According to the first aspect of the invention, in order to achieve the above purpose, the invention provides a technical scheme that the weather-new energy source-power grid-charging four-layer coupling cooperative control system comprises the following steps: Receiving real-time weather forecast data, correcting new energy output prediction based on wind gust effect and cloud shielding effect under extreme weather, and outputting corrected new energy power data; Based on the new energy power data, the power grid real-time operation data and the spare capacity data, the vulnerability index of the framework computing system is dynamically estimated through four dimensions; adopting vulnerability indexes as general control languages, and coordinating a power grid side, a distribution network side and a load side to perform layered optimization and power distribution; And converting the vulnerability index into a continuous and smooth charging power limit curve through a Sigmoid mapping function, and executing a corresponding emergency plan according to a preset five-level early warning system. Further, receiving real-time weather forecast data, correcting new energy output prediction based on wind gust effect and cloud shielding effect under extreme weather, and outputting corrected new energy power data, wherein the method comprises the following steps: (21) Correcting the standard power curve according to the wind speed change rate, calculating an gust correction coefficient and outputting corrected wind power: (21.1) wind power standard power curve is as follows: In the formula, Cut in the wind speed, the minimum wind speed that the