CN114726005B - Wind power plant double-layer frequency control method considering fan power optimization distribution - Google Patents
Wind power plant double-layer frequency control method considering fan power optimization distribution Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/48—Controlling the sharing of the in-phase component
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/381—Dispersed generators
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/28—The renewable source being wind energy
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/70—Wind energy
- Y02E10/76—Power conversion electric or electronic aspects
Abstract
The invention discloses a wind power plant double-layer frequency control method considering fan power optimization allocation, which utilizes a wind power plant centralized controller to execute centralized prediction control according to a fixed period, predicts the frequency of a power system and the future state of each fan, generates a wind power plant with each power set point and active power reference values of each fan according to the predicted frequency, and transmits the reference values to each fan controller; and each fan controller executes real-time correction control at fixed intervals, and correction of active power instructions of the fans is realized through distributed iteration, so that the rotating speeds of the fans are ensured to be within a safe range while the power of the wind power plant and the power of the fans are close to a set value issued by a wind power plant centralized controller. The invention can meet the requirement of rapid frequency control of the wind power plant and can also meet the overall characteristics of the wind power plant and the aim of reasonable power distribution among fans.
Description
Technical Field
The invention relates to the technical field of operation and control of power systems, in particular to a double-layer frequency control method for a wind power plant.
Background
Renewable energy power generation is increasingly becoming the clean energy alternative under the dual pressures of energy shortage and environmental pollution. Among them, wind power generation has been rapidly developed in recent years, and the structure and operation mode of the conventional power system have been greatly changed. Uncertainty in wind resources itself may adversely affect the frequency stability of the power system, since most wind farms operate in maximum output power tracking mode to maximize power generation efficiency, and fluctuations in wind power cause significant changes in the power generated by the power system. Meanwhile, most of novel fans are connected with a power grid through a power electronic converter, the rotating speed of fan rotors is decoupled from the system frequency, and along with the improvement of the wind power duty ratio, the inertia of a power system is relatively reduced, and the problem of frequency fluctuation under power fluctuation is increasingly highlighted.
In fact, as a rotating device, the kinetic energy stored in the fan blades and the flexibility of the power electronic converter control provide the possibility for wind power to participate in the frequency regulation. The active output of the power electronic converter can be quickly adjusted by adjusting the power electronic converter at the rotor side of the fan, and the kinetic energy stored by the fan is utilized to provide quick frequency control service for the power system. However, most fans currently participate in power system frequency control using a "decentralized" approach, i.e., a single fan independently provides simulated inertia and sag characteristics based on its measured frequency. However, in the operation in the power system, the wind farm should simulate the frequency modulation characteristic of the traditional thermal power generating unit as a whole, so as to realize the frequency control target of the power system. However, if the wind farm is used as a whole to respond to the frequency change of the power system, how to reasonably distribute power among all fans in the wind farm becomes a main problem for restricting frequency control. Aiming at the problem, the prior art generally needs to adopt a centralized optimization control method, a centralized optimization model is established and solved according to the frequency change of the electric power system and the running state of each fan of the wind power plant, and then an adjustment instruction of the active power of each fan is issued. However, as the large-scale wind power plants have a large number of fans and are in far geographical distribution, the communication time and the calculation time required by centralized control are long, and the large delay exists, the method has great dependence on the accuracy of fan model parameters and the prediction accuracy of wind speed, if the model parameters or the wind speed errors are large, the power distribution among the fans is unreasonable, and if the model parameters or the wind speed errors are serious, the fans are disconnected. Since centralized model maintenance and optimization calculations will take a lot of time, such methods are not suitable for frequency control where the response speed is very demanding.
Therefore, on the basis of the advantages of the rapid response of the distributed control and the power optimization distribution of the centralized control, it is highly desirable to provide a frequency control method capable of considering the rapid response of the wind power plant frequency control, the overall frequency control characteristic of the wind power plant and the power optimization distribution among fans, considering the limitation of the actual communication and hardware conditions of the wind power plant on the control time interval and the calculation speed, and avoiding the dependence of the traditional frequency control mode on model parameters and wind speed prediction.
Disclosure of Invention
Based on the technical problems in the prior art, the invention provides a wind power plant double-layer frequency control method considering the optimal distribution of fan power, and a double-layer control architecture is utilized to realize that fan controllers of all nodes are controlled among fans through distributed communication and real-time correction, so that the wind power plant and all fans track active power reference values, and the operation safety of all fans is ensured.
The invention is realized by the following technical scheme:
a wind power plant double-layer frequency control method considering fan power optimization distribution specifically comprises the following steps:
step 1-1, in the centralized predictive control period T WF In the method, a prediction model of the frequency of each power setting time point of the power system is defined as follows:
wherein t represents the sequence number of the power setting time point, each centralized predictive control period is cleared at the beginning, f (t) represents the predictive frequency of the t power setting time point, f (t+1) represents the predictive frequency of the t+1 power setting time point, and K f And K in Respectively representing sag coefficient and inertia coefficient of wind power plant participating in frequency modulation, f * Representing rated frequency of the power system, and H represents equivalent inertia of the power system;
step 1-2, calculating an active power reference value of the wind power plant at each power set time point, wherein the formula is as follows:
wherein P is ref (t) represents an active power reference value of a t power setting time point of the wind power plant,
representing active power when the wind power plant does not participate in frequency modulation;
step 1-3, alternately calculating a fan rotating speed predicted value and a fan active power reference value of each power set time point according to the following steps:
step 1-3-1, calculating a fan rotating speed predicted value of a t power setting time point, wherein the formula is as follows:
wherein omega i,ref (t) the ith fan rotational speed prediction value, J, representing the tth power setting time point i Representing the moment of inertia, P, of the ith fan i,ref (t-1) an i-th typhoon machine active power reference value representing a t-1-th power setting time point, P i,m,ref (t-1) represents an i-th fan input wind power prediction value at a t-1-th power setting time point, and the calculation formula is as follows:
wherein ρ represents air density, R represents fan blade radius, v w Representing wind speed of wind farm, C i,ref (t-1) represents the predicted value of the wind energy capture coefficient of the ith fan at the t-1 th power setting time point, and the formula is as follows:
wherein omega i,ref (t-1) represents an i-th fan rotational speed predicted value at a t-1-th power setting time point, and beta represents a fan pitch angle;
step 1-3-2, calculating the energy state predicted value of each fan at the t power setting time point, wherein the formula is as follows:
wherein SOE is i,ref (t) the ith station fan energy state prediction value, ω, representing the tth power setting time point max And omega min Respectively representing an upper limit value and a lower limit value of the rotating speed of the fan;
step 1-3-3, calculating the active power reference value of each fan at the t power setting time point, wherein the formula is as follows:
step 1-3-4, returning to step 1-3-1 until the central prediction control period T WF Calculating the predicted value of the rotating speed of each fan and the active power reference value of the fan at all power setting time points;
step 1-4, predicting the control period T in a centralized manner WF Wind farm active power reference value P of each power set time point ref (t) active Power reference value P of each Fan i,ref (t) fan controllers issued to each node;
step 1-5, achieving a centralized predictive control period T WF When the time is over, the step 1-1 is returned, and the timing is restarted;
step 2-1, calculating an energy state distribution index x of the kth real-time correction control of the ith fan according to the active power output and the actual rotating speed of the kth real-time correction control of the corresponding fan i (k) The calculation formula is as follows:
wherein P is i (k) Representing the active power output, omega of the ith fan corrected and controlled in real time in the kth step i (k) Representing the actual rotating speed of the ith fan corrected and controlled in real time in the kth step, P i,m (k) The input wind power of the ith fan representing the k-step real-time correction control is calculated according to the following formula:
wherein C is i (k) The calculation formula of the wind energy capture coefficient of the ith fan representing the k-step real-time correction control is as follows:
step 2-2, electrically connecting any two adjacent fans in the wind power plant, and exchanging energy state distribution indexes x by corresponding fan controllers i (k)；
Step 2-3, calculating a second-order gradient H of the kth-step real-time correction control of the ith fan i (k) The calculation formula is as follows:
wherein K is 1 、K 2 And K 3 Penalty coefficients corresponding to wind field active power deviation, fan active power deviation and power distribution deviation among fans are represented respectively, and N (i) represents a fan set adjacent to the ith fan in electrical connection;
step 2-4, calculating a first-order Jacobian gradient g of the kth step real-time correction control of the ith fan i (k) The calculation formula is as follows:
step 2-5, calculating the iterative direction d of the kth-step real-time correction control of the ith fan i (k) The calculation formula is as follows:
d i (k)＝-H i (k) -1 ·g i (k) (13)
step 2-6, calculating an energy state distribution index x of the (i) fan in the (k+1) th step real-time correction control i (k+1) as follows:
x i (k+1)＝x i (k)+ε·d i (k) (14)
wherein epsilon is the iteration step length;
step 2-7, calculating a fan active power set value P of the ith fan in real time correction control in the (k+1) th step i (k+1) as follows:
step 2-8, according to the active power set value P i (k+1) controlling the active power output of the blower;
step 2-9, achieving the real-time correction control interval T WT And (5) returning to the step 2-1 and restarting timing.
Compared with the prior art, the invention can achieve the following beneficial technical effects:
1) The energy stored in the fan blades and the active power adjustment capability of the fan can be fully utilized, and on the premise of ensuring the operation safety of the fan, the whole wind power plant participates in the frequency adjustment of the power system and presents stable sagging and inertia characteristics, thereby being beneficial to the stability of the frequency of the power system;
2) The time required by the actual communication of the wind power plant is fully considered, the integral frequency modulation characteristic of the wind power plant and the power optimization distribution among fans are met through the centralized prediction control of the wind power plant centralized controller, so that the kinetic energy stored by each fan tends to be uniform, the real-time correction control is carried out through the fan controller, and the requirement of the integral frequency modulation rapid control of the wind power plant is met; the requirements of rapid frequency control of the wind power plant can be met, and the overall characteristics of the wind power plant and the aim of reasonable power distribution among fans can be also met;
3) The adopted time correction control method realizes the rapid correction of the active power of the fans through distributed communication and iteration, and does not depend on accurate model parameters of each fan, so that good frequency control effect can be ensured under the scene of inaccurate model parameters.
Drawings
FIG. 1 is a flowchart of a wind farm double-layer frequency control method taking optimal allocation of fan power into consideration.
Detailed Description
The technical scheme of the invention is described in detail below with reference to the accompanying drawings and specific embodiments.
As shown in FIG. 1, the overall flow chart of the wind farm double-layer frequency control method taking the optimal distribution of fan power into consideration specifically comprises the following steps:
step 1-1, in the centralized predictive control period T WF In the method, a prediction model of the frequency of each power setting time point of the power system is defined as follows:
wherein t represents the sequence number of the power setting time point, each centralized predictive control period is cleared at the beginning, f (t) represents the predictive frequency of the t power setting time point, f (t+1) represents the predictive frequency of the t+1 power setting time point, and K f And K in Sag and inertia coefficients, respectively representing the frequency modulation involved in a wind farm, typically specified by the power system, f * Representing the rated frequency of the power system, wherein the value is 50Hz, H represents the equivalent inertia of the power system, and the value is sent to a wind power plant centralized controller through a power system dispatching center;
step 1-2, calculating an active power reference value of the wind power plant at each power set time point, wherein the formula is as follows:
wherein P is ref (t) represents an active power reference value of a t power setting time point of the wind power plant,
representing active power when the wind power plant does not participate in frequency modulation;
step 1-3, alternately calculating a fan rotating speed predicted value and a fan active power reference value of each power set time point according to the following steps:
step 1-3-1, calculating a fan rotating speed predicted value of a t power setting time point, wherein the formula is as follows:
wherein omega i,ref (t) the ith fan rotational speed prediction value, J, representing the tth power setting time point i Representing the rotational inertia of the ith fan, obtained by a fan design manual, P i,ref (t-1) an i-th typhoon machine active power reference value representing a t-1-th power setting time point, P i,m,ref (t-1) represents an i-th fan input wind power prediction value at a t-1-th power setting time point, and the calculation formula is as follows:
wherein ρ represents air density, R represents fan blade radius, v w Representing wind speed of wind farm, C i,ref (t-1) represents the predicted value of the wind energy capture coefficient of the ith fan at the t-1 th power setting time point, and the formula is as follows:
wherein omega i,ref (t-1) ith fan rotation representing the t-1 th power setting time pointAnd the speed predicted value, beta represents the pitch angle of the fan.
Step 1-3-2, calculating the energy state predicted value of each fan at the t power setting time point, wherein the formula is as follows:
wherein SOE is i,ref (t) the ith station fan energy state prediction value, ω, representing the tth power setting time point max And omega min Respectively representing an upper limit value and a lower limit value of the rotating speed of the fan;
step 1-3-3, calculating the active power reference value of each fan at the t power setting time point, wherein the formula is as follows:
step 1-3-4, returning to step 1-3-1 until the central prediction control period T WF Calculating the predicted value of the rotating speed of each fan and the active power reference value of the fan at all power setting time points;
step 1-4, predicting the control period T in a centralized manner WF Wind farm active power reference value P of each power set time point ref (t) active Power reference value P of each Fan i,ref (t) fan controllers issued to each node;
step 1-5, achieving a centralized predictive control period T WF When the time is over, the step 1-1 is returned, and the timing is restarted;
step 2-1, let the real-time correction control start step be k=0;
step 2-2, calculating an energy state allocation index x of the kth real-time correction control of the ith fan according to the active power output and the actual rotating speed of the corresponding fan in the kth real-time correction control step i (k) The calculation formula is as follows:
wherein P is i (k) Represents the active power output omega of the ith fan in the kth real-time correction control step i (k) Representing the actual rotating speed of the ith fan in the kth real-time correction control step, P i,m (k) The calculation formula represents the input wind power of the ith fan in the kth real-time correction control step as follows:
wherein C is i (k) Representing the wind energy capture coefficient of the ith fan in the kth real-time correction control step, and calculating the following formula:
step 2-3, electrically connecting any two adjacent fans in the wind power plant, and exchanging energy state distribution indexes x by corresponding fan controllers i (k)；
Step 2-4, calculating a second-order gradient H of the kth real-time correction control step of the ith fan i (k) The calculation formula is as follows:
wherein K is 1 、K 2 And K 3 Penalty coefficients respectively representing the active power deviation of the corresponding wind field, the active power deviation of the fans and the power distribution deviation among the fans can be selected as 1, N (i) represents and i-th fanAdjacent fan assemblies in electrical connection;
step 2-5, calculating a first-order Jacobian gradient g of the kth real-time correction control step of the ith fan i (k) The calculation formula is as follows:
step 2-6, calculating the iteration direction d of the kth real-time correction control step of the ith fan i (k) The calculation formula is as follows:
d i (k)＝-H i (k) -1 ·g i (k) (13)
step 2-7, calculating an energy state distribution index x of the (k+1) th real-time correction control step of the ith fan i (k+1) as follows:
x i (k+1)＝x i (k)+ε·d i (k) (14)
wherein epsilon is an iteration step length, and the value range can be set to be 0.01-0.1.
Step 2-8, calculating a fan active power set value P of the (k+1) th real-time correction control step of the (i) th fan i (k+1) as follows:
step 2-9, according to the active power set value P i (k+1) controlling the active power output of the blower;
step 2-10, reaching the real-time correction control interval T WT When the real-time correction control step k=k+1 is executed, the process returns to step 2-2, and the timing is restarted.
In summary, the invention fully utilizes the energy stored in the fan blades and the fan adjusting capability in the wind power plant to control the active power output by the fan, so that the total active power of the wind power plant can be quickly adjusted, and the active power response is provided according to the frequency change of the power system, thereby ensuring the safe operation of the power system. The invention is characterized in that a double-layer control architecture is adopted, a wind farm centralized controller collects the running state of each fan by utilizing centralized communication, predicts the frequency of a power system and the future state of each fan, adopts a worse centralized prediction control period, calculates the active power reference value of each fan and each wind farm in a rolling way, and sends the obtained result to each fan controller, and each fan controller aims at the inaccuracy of model parameters and the influence of the change of wind speed on the control effect of the centralized controller, so that the wind farm and each fan track the active power reference value through distributed communication and real-time correction control among the fans, and the running safety of each fan is ensured.
Claims (1)
1. The wind power plant double-layer frequency control method considering fan power optimization distribution is characterized by comprising the following steps of:
step 1, a centralized controller of a wind power plant calculates to obtain a centralized prediction control period T WF The wind farm active power reference value and the fan active power reference value of each power set time point in the system are issued to each fan controller, and the specific execution flow is as follows:
step 1-1, in the centralized predictive control period T WF In the method, a prediction model of the frequency of each power setting time point of the power system is defined as follows:
wherein t represents the sequence number of the power setting time point, each centralized predictive control period is cleared at the beginning, f (t) represents the predictive frequency of the t power setting time point, f (t+1) represents the predictive frequency of the t+1 power setting time point, and K f And K in Respectively representing sag coefficient and inertia coefficient of wind power plant participating in frequency modulation, f * Representing rated frequency of the power system, wherein H represents equivalent inertia of the power system;
step 1-2, calculating an active power reference value of the wind power plant at each power set time point, wherein the formula is as follows:
wherein P is ref (t) represents an active power reference value of a t power setting time point of the wind power plant,
representing active power when the wind power plant does not participate in frequency modulation;
step 1-3, alternately calculating a fan rotating speed predicted value and a fan active power reference value of each power set time point according to the following steps:
step 1-3-1, calculating a fan rotating speed predicted value of a t power setting time point, wherein the formula is as follows:
wherein omega i,ref (t) the ith fan rotational speed prediction value, J, representing the tth power setting time point i Representing the moment of inertia, P, of the ith fan i,ref (t-1) an i-th typhoon machine active power reference value representing a t-1-th power setting time point, P i,m,ref (t-1) represents an i-th fan input wind power prediction value at a t-1-th power setting time point, and the calculation formula is as follows:
wherein ρ represents air density, R represents fan blade radius, v w Representing wind speed of wind farm, C i,ref (t-1) represents the predicted value of the wind energy capture coefficient of the ith fan at the t-1 th power setting time point, and the formula is as follows:
wherein omega i,ref (t-1) represents an i-th fan rotational speed predicted value at a t-1-th power setting time point, and beta represents a fan pitch angle;
step 1-3-2, calculating the energy state predicted value of each fan at the t power setting time point, wherein the formula is as follows:
wherein SOE is i,ref (t) the ith station fan energy state prediction value, ω, representing the tth power setting time point max And omega min Respectively representing an upper limit value and a lower limit value of the rotating speed of the fan;
step 1-3-3, calculating the active power reference value of each fan at the t power setting time point, wherein the formula is as follows:
step 1-3-4, returning to step 1-3-1 until the central prediction control period T WF Calculating the predicted value of the rotating speed of each fan and the active power reference value of the fan at all power setting time points;
step 1-4, predicting the control period T in a centralized manner WF Wind farm active power reference value P of each power set time point ref (t) active Power reference value P of each Fan i,ref (t) fan controllers issued to each node;
step 1-5, achieving a centralized predictive control period T WF When the time is over, the step 1-1 is returned, and the timing is restarted;
step 2, fan controllers of all nodes send out wind power plant active power reference values P according to the received wind power plant active power reference values P sent out by the wind power plant centralized controller ref (t) active Power reference value P of each Fan i,ref (T) at the corresponding power setting time point interval T ref At intervals of time T WT Performing real-time correction control, specifically performingThe flow is as follows:
step 2-1, let the real-time correction control start step be k=0;
step 2-2, calculating an energy state allocation index x of the kth real-time correction control of the ith fan according to the active power output and the actual rotating speed of the corresponding fan in the kth real-time correction control step i (k) The calculation formula is as follows:
wherein P is i (k) Represents the active power output omega of the ith fan in the kth real-time correction control step i (k) Representing the actual rotating speed of the ith fan in the kth real-time correction control step, P i,m (k) The calculation formula represents the input wind power of the ith fan in the kth real-time correction control step as follows:
wherein C is i (k) Representing the wind energy capture coefficient of the ith fan in the kth real-time correction control step, and calculating the following formula:
step 2-3, electrically connecting any two adjacent fans in the wind power plant, and exchanging energy state distribution indexes x by corresponding fan controllers i (k)；
Step 2-4, calculating a second-order gradient H of the kth real-time correction control step of the ith fan i (k) The calculation formula is as follows:
wherein K is 1 、K 2 And K 3 Penalty coefficients respectively representing the active power deviation of the corresponding wind field, the active power deviation of the fans and the power distribution deviation among the fans are all selected to be 1, and N (i) represents a fan set adjacent to the ith fan in electrical connection;
step 2-5, calculating a first-order Jacobian gradient g of the kth real-time correction control step of the ith fan i (k) The calculation formula is as follows:
step 2-6, calculating the iteration direction d of the kth real-time correction control step of the ith fan i (k) The calculation formula is as follows:
d i (k)＝-H i (k) -1 ·g i (k) (13)
step 2-7, calculating an energy state distribution index x of the (k+1) th real-time correction control step of the ith fan i (k+1) as follows:
x i (k+1)＝x i (k)+ε·d i (k) (14)
wherein epsilon is an iteration step length, and the value range is set to be 0.01-0.1;
step 2-8, calculating a fan active power set value P of the (k+1) th real-time correction control step of the (i) th fan i (k+1) as follows:
step 2-9, according to the active power set value P i (k+1) controlling the active power output of the blower;
step 2-10, reaching the real-time correction control interval T WT When the real-time correction control step k=k+1 is executed, the process returns to step 2-2, and the timing is restarted.
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| CN111064206A (en) * | 2020-01-02 | 2020-04-24 | 重庆大学 | Power system frequency emergency control method based on dynamic load shedding of doubly-fed wind turbine generator |
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