Feed-forward double fuzzy control water turbine primary frequency modulation method adapting to working condition change

Abstract

The invention discloses a water turbine primary frequency modulation method adopting feedforward double fuzzy control and adapting to working condition changes, which comprises the following steps of: firstly, inputting a frequency deviation into a PID (Proportion Integration Differentiation) controller when the frequency deviation exceeds a primary frequency modulation dead zone, inputting a water head signal and a power signal into a fuzzy controller I, and outputting PID controller parameter Kp, Ki and Kd values after fuzzification, fuzzy reasoning and defuzzification; the PID output and the feed-forward signal are added and then converted into a hydraulic signal through an electro-hydraulic converter; and then the opening degree deviation signal and the derivative of the signal are input into a fuzzy controller II, an input electric signal of an electro-hydraulic converter is output, a movable guide vane is operated through a hydraulic execution mechanism to control the output of the water turbine, and a primary frequency modulation action is completed. According to the method, adaptability improvement is carried out on different working conditions of the water turbine governor based on fuzzy logic, meanwhile, in order to limit the water hammer effect, the second fuzzy controller is added in front of the electro-hydraulic converter, and the adaptability, quickness and stability of the primary frequency modulation process are effectively improved.

Description

Technical Field

[0001] The present application relates to the field of primary frequency regulation control of hydraulic turbines, and particularly to a primary frequency regulation control method for hydraulic turbines with feedforward double fuzzy control adaptable to operating condition changes. Background Art

[0002] With the promulgation of the new version of the grid frequency regulation rules, new requirements are put forward for the contribution rate, regulation accuracy, regulation time, regulation stability, etc. of hydropower units to primary frequency regulation. It is required that the contribution rate of primary frequency regulation is higher, the regulation speed is faster, and the power reverse regulation is smaller. Therefore, it is necessary to optimize and improve the speed governors of hydropower units.

[0003] Currently, traditional PID microcomputer speed governors are generally adopted for hydropower units, and the guide vane opening is controlled through a hydraulic actuator to complete the unit power control. Generally speaking, a set of fixed PID parameters are adopted during the normal operation of the unit connected to the grid. However, under different operating conditions and water heads of the unit, the operating characteristics of the hydraulic turbine are different. When operating deviating from the rated operating condition point, the fixed PID parameters often result in a decline in control performance, leading to a large water hammer effect or a slow regulation rate.

[0004] In order to improve the adaptability of the speed governor to different water heads and different operating conditions, and to accelerate the primary frequency regulation rate and reduce the power reverse regulation, a primary frequency regulation control method for hydraulic turbines with feedforward double fuzzy control adaptable to operating condition changes is proposed. Summary of the Invention

[0005] The purpose of the present invention is to provide a primary frequency regulation method for hydraulic turbines with feedforward double fuzzy control adaptable to operating condition changes, so as to solve the problems of poor adaptability of the existing speed governor to operating conditions, slow regulation rate and large power reverse regulation.

[0006] To solve the above problems, the present invention is realized through the following solutions:

[0007] A primary frequency regulation method for hydraulic turbines with feedforward double fuzzy control adaptable to operating condition changes, comprising the following steps:

[0008] Step S1: Real-time monitor the grid frequency deviation Δf, and collect the current water head signal h of the unit, the real-time active power Pt and the actual opening u of the guide vane actual , and when the frequency deviation Δf exceeds the dead zone, perform primary frequency regulation;

[0009] Step S2: Take the collected current water head signal h and real-time active power Pt of the unit as the inputs of the first fuzzy controller; after fuzzyfication, fuzzy inference and defuzzyfication, output the coefficient K of the feedforward path f , as well as the parameters K p , K i , K d of the PID controller;

[0010] Step S3: Input the frequency deviation Δf into the PID controller with adjusted control parameters K p , K i , K d and the feed-forward path with adjusted coefficient K f ;

[0011] Step S4: Superimpose the output signal u PID of the PID controller and the feed-forward signal u ff to obtain the total control signal u total , and convert it into a hydraulic signal through an electro-hydraulic converter to drive the servomotor to adjust the guide vane opening to the target value u ref ;

[0012] Step S5: Compare the actually collected guide vane opening u actual with the target opening u ref to obtain the opening deviation Δu. Use the opening deviation Δu and the change rate of the opening deviation Δu' as the inputs of the second fuzzy controller. The output of the second fuzzy controller is the electro-hydraulic converter control signal u. Control the output of the water turbine by controlling the opening and closing of the movable guide vanes, and finally eliminate the frequency deviation, thus completing a primary frequency modulation process.

[0013] For further optimization, in the said Step S1, the input signal r pid (t) of the PID controller is:

[0014] r pid (t) = Δf(t) - b p u(t)

[0015] where t is time, Δf(t) is the frequency deviation, b p is the regulation coefficient, and u pid (t) is the PID feedback signal;

[0016] The output signal of the PID controller is:

[0017] For further optimization, the said feed-forward path is a proportional link with a proportional coefficient of K f ; The output signal u ff of the feed-forward path = K f Δf.

[0018] For further optimization, the PID parameter adjustment rule of the first fuzzy controller in the said Step S2 is:

[0019]

[0020] In the formula, K p (t), K i (t), Kd (t) and K f (t) respectively represent the control parameters of the PID controller and the feed - forward path at the current moment; K p (t - 1), K i (t - 1), K d (t - 1) and K f (t - 1) respectively represent the control parameters of the PID controller and the feed - forward path at the previous moment; ΔK p , ΔK i , ΔK d and ΔK f respectively represent the control parameter adjustment amounts; the control parameter adjustment amounts ΔK p , ΔK i , ΔK d and ΔK f are inferred by the fuzzy inference engine according to the preset fuzzy inference rules in the fuzzy rule base. The specific inference rules are designed according to the actual unit situation.

[0021] Further optimized, the ΔK p , ΔK i , ΔK d and ΔK f are generated by a 7×7 fuzzy rule matrix. The fuzzy subsets are {NB, NM, NS, ZE, PS, PM, PB}, and the membership function adopts a triangular distribution; where NB, NM, NS, ZE, PS, PM, PB respectively represent negative large, negative medium, negative small, zero, positive small, positive medium and positive large.

[0022] Further optimized, the relational expression between the target opening and the total control signal: u ref = f(u total ) = f(u PID + u ref ); where f(.) is the transfer function of the actuator;

[0023] The opening deviation Δu = u actual - f(u PID + u ref );

[0024] The change rate of the opening deviation

[0025] where, is affected by the dynamic characteristics of the electro - hydraulic converter and the servomotor.

[0026] Further optimized, in the step S5, the fuzzy control rules of the second fuzzy controller are determined according to the specific motion characteristics of the hydraulic system, and its purpose is to limit the change rate of the guide vane opening when the guide vane movement speed is large and suppress the water hammer effect.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] 1. The primary frequency regulation method of the water turbine with feedforward double fuzzy control adapting to working condition changes according to the present invention improves the adaptability of the water turbine governor to the power at different water heads and also has good control ability when the water turbine operates deviating from the rated working condition point.

[0029] 2. The primary frequency regulation method of the water turbine with feedforward double fuzzy control adapting to working condition changes according to the present invention greatly speeds up the regulation time, reduces the reverse power regulation caused by the water hammer effect, and improves the primary frequency regulation contribution rate and regulation stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 is a flow chart of the primary frequency regulation method of the water turbine with feedforward double fuzzy control adapting to working condition changes according to the present invention;

[0031] Figure 2 is a control structure diagram of the primary frequency regulation of the water turbine with feedforward double fuzzy control adapting to working condition changes according to the present invention;

[0032] Figure 3 is the torque characteristic curve of the water turbine adopted in Embodiment 1;

[0033] Figure 4 is the flow characteristic curve of the water turbine adopted in Embodiment 1;

[0034] Figure 5 is the triangular membership function adopted in Embodiment 1;

[0035] Figure 6 is the power step response curve diagram of the traditional PID control method;

[0036] Figure 7 is the power step response diagram adopting feedforward double fuzzy control. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0037] Next, the method of the present invention will be further described in combination with embodiments.

[0038] This is as Figure 1 shown. The steps of the primary frequency regulation method of the water turbine with feedforward double fuzzy control adapting to working condition changes are as follows:

[0039] Step S1: Real-time monitor the grid frequency deviation Δf, and collect the current water head signal h of the unit, the real-time active power Pt and the actual opening u of the guide vane actual , and when the frequency deviation Δf exceeds the dead zone, perform primary frequency regulation;

[0040] Step S2: Take the current head signal h and the real-time active power Pt of the collection unit as the inputs of the first fuzzy controller; after fuzzification, fuzzy inference, and defuzzification, output the coefficient K of the feedforward path f , as well as the parameters K p , K i , K d of the PID controller;

[0041] Step S3: Input the frequency deviation Δf into the PID controller with adjusted control parameters K p , K i , K d and the feedforward path with adjusted coefficient K f ;

[0042] Step S4: Superimpose the output signal u PID of the PID controller and the feedforward signal u ff to obtain the total control signal u total , and convert it into a hydraulic signal through an electro-hydraulic converter to drive the servomotor to adjust the guide vane opening to the target value u ref ;

[0043] Step S5: Compare the actually collected guide vane opening u actual with the target opening u ref to obtain the opening deviation Δu, and take the opening deviation Δu and the opening deviation change rate Δu’ as the inputs of the second fuzzy controller. The output of the second fuzzy controller is the electro-hydraulic converter control signal u, and the output of the water turbine is controlled by controlling the opening and closing of the movable guide vanes, finally eliminating the frequency deviation, thus completing a primary frequency modulation process.

[0044] Example 1:

[0045] As Figure 2 shown, establish a simulation model of the water turbine and governor. The transfer function G y (s) of the hydraulic actuator part of the governor is:

[0046]

[0047] where T y is the servomotor response time constant, and s is the S-domain operator.

[0048] The water diversion system adopts an elastic water hammer model, and the transfer function is:

[0049]

[0050] where Δh is the relative value of the water pressure deviation; Δq is the relative value of the flow deviation; T w is the water flow inertia time constant; T r is the water hammer phase long time constant, and α = 0.125.

[0051] The water turbine adopts a non - linear model based on the overall characteristic curve:

[0052]

[0053] In this embodiment, the overall characteristic curve of the water turbine adopted is as Figure 3 and Figure 4 shown. Among them, the abscissa is the unit speed n of the water turbine 11 , and the ordinates are the unit torque M 11 and the unit flow rate Q 11 respectively; the order of the lines in the figure from bottom to top corresponds to the guide vane opening from 0° to 30° in the legend. For example Figure 3 in the right - hand legend in, 30 means the guide vane opening is 30 degrees, that is, the top - most curve. Figure 3 , 4 the point corresponding to "*" in is the point obtained from the model characteristic curve and the runaway characteristic curve; the unit speed n 11 , the unit torque M 11 and the unit flow rate Q 11 correspond to the conversion relationships with the actual speed n, actual torque M t and actual flow rate Q of the water turbine as follows:

[0054]

[0055] D1 is the runner diameter.

[0056] The fuzzy controller 1 receives the current head and the current power given signal fed back from the power station, takes the head signal and the power given signal as the input variables of fuzzy inference, and through the fuzzy relationships between the four parameters of the PID controller and the feed - forward stored in the fuzzy rule base and the two input variables, infers the four - parameter adjustment fuzzy variables. After defuzzification processing, it acts on the four parameters of the PID controller and the feed - forward, realizing the on - line adjustment of the PID controller parameters and the feed - forward signal, so that the controller obtains better dynamic and static performance.

[0057] The final control output of the fuzzy controller 1 is:

[0058]

[0059] In this embodiment, the initial values of Kp, Ki, Kd, and Kf are 6, 3, 3, and 25 respectively, and their adjustment amounts ΔK p , ΔK i , ΔK d and ΔK fThe basic domains are [-3, 3], [-3, 3], [-3, 3], [-6, 6] respectively, and their fuzzy domains are: {-3, -2, -1, 0, 1, 2, 3}, {-3, -2, -1, 0, 1, 2, 3}, {-3, -2, -1, 0, 1, 2, 3}, {-6, -4, -2, 0, 2, 4, 6}, and the corresponding fuzzy subsets are {NB, NM, NS, ZE, PS, PM, PB}. The membership function adopts a triangular distribution, as Figure 5 shown. Among them, NB, NM, NS, ZE, PS, PM, and PB represent negative large, negative medium, negative small, zero, positive small, positive medium, and positive large respectively.

[0060] The control parameter adjustment amounts ΔK p , ΔK i , ΔK d and ΔK f are obtained by the fuzzy inference machine according to the preset fuzzy inference rules in the fuzzy rule base. The specific inference rules are designed according to the actual unit situation.

[0061] In this embodiment, the fuzzy rules of the control parameter Kp are shown in Table 1, the fuzzy rules of the control parameter Ki are shown in Table 2, the fuzzy rules of the control parameter Kd are shown in Table 3, and the fuzzy rules of the feedforward control parameter Kf are shown in Table 4.

[0062] Table 1 Fuzzy Rules of Control Parameter Kp

[0063]

[0064] Table 2 Fuzzy Rules of Control Parameter Ki

[0065]

[0066] Table 3 Fuzzy Rules of Control Parameter Kd

[0067]

[0068] Table 4 Fuzzy Rules of Feedforward Control Parameter Kf

[0069]

[0070]

[0071] The two input quantities of the fuzzy controller are the guide vane opening deviation Δu and the opening deviation change rate Δu'; the output is the relative value u of the electro-hydraulic converter control signal, and its basic domain is [-1, 1]. The fuzzy rules of the electro-hydraulic converter input quantity u in the second fuzzy controller are shown in Table 5.

[0072] Table 5 Fuzzy Rules of Electro-Hydraulic Converter Input Quantity u in the Second Fuzzy Controller

[0073]

[0074] In this embodiment, the defuzzification of the two fuzzy controllers adopts the centroid method, and the specific algorithm is as follows:

[0075]

[0076] where c' is the output variable value obtained through fuzzy inference; f is the membership function, which is related to the water head h and the unit power P t ; n is the number of singleton sets; c i is the output variable value corresponding to the singleton point.

[0077] In this embodiment, the initial operating condition of the unit is 0.8 times the rated power. Frequency disturbances of 0.16 Hz are given to the unit at three water heads h = 140 m, h = 170 m, and h = 200 m respectively. Finally, the step response power curves of the two models are compared as Figure 6 and Figure 7 shown, where Figure 6 is the power step response curve diagram of the traditional PID control method, Figure 7 is the power step response diagram of the feedforward dual fuzzy control. It can be seen from Figure 7 that the proposed feedforward dual fuzzy control method for primary frequency regulation of hydraulic turbines that adapts to working condition changes significantly speeds up the primary frequency regulation rate of the unit and has good control effects at different water heads and powers.

[0078] The preferred embodiments of the present invention have been described, but it should be emphasized that those skilled in the art can make several improvements and adjustments without departing from the basic principles and spirit of the invention. These possible improvements and adjustments should also be considered within the protection scope of the present invention.

Claims

1. A primary frequency regulation method for a hydraulic turbine with feedforward double fuzzy control adapting to working condition changes, characterized in that, Including the following steps: Step S1: Monitor the power grid frequency deviation Δf in real time, and collect the current head signal h of the unit, the real-time active power Pt, and the actual guide vane opening u actual , and when the frequency deviation Δf exceeds the dead zone, perform a frequency modulation once; Step S2: Take the current head signal h and real-time active power Pt of the acquisition unit as the inputs of Fuzzy Controller 1; after fuzzification, fuzzy inference, and defuzzification, output the coefficient K of the feedforward path f , as well as the parameters K p , K i , K d ; Step S3: Input the frequency deviation Δf into the PID controller after adjusting the control parameters K p , K i , K d and into the feedforward path after adjusting the coefficient K f ; Step S4: Add the output signal u of the PID controller PID to the feedforward signal u ff to obtain the total control signal u total , which is then converted into a hydraulic signal by an electro-hydraulic converter to drive the servomotor to adjust the guide vane opening to the target value u ref ; Step S5: Compare the actually collected wicket gate opening u actual with the target opening u ref to obtain the opening deviation Δu. Take the opening deviation Δu and the change rate of the opening deviation Δu' as the inputs of the second fuzzy controller. The output of the second fuzzy controller is the electro-hydraulic converter control signal u. Control the opening and closing of the movable wicket gate to control the output of the water turbine, and finally eliminate the frequency deviation, thus completing a primary frequency regulation process.

2. The primary frequency regulation method of a water turbine with feedforward double fuzzy control adapting to operating condition changes according to claim 1, characterized in that In the step S1, the input signal r pid (t) of the PID controller is as follows: r pid (t) = Δf(t) - b p u(t) where t is time, Δf(t) is the frequency deviation, and b p is the regulation coefficient, and u pid (t) is the PID feedback signal; The output signal of the PID controller is:

3. A primary frequency regulation control method for a hydraulic turbine with feedforward double fuzzy control adapting to working condition changes according to claim 2, characterized in that, The feedforward path is a proportional link with a proportionality coefficient of K f ; the output signal u of the feedforward path ff = K f Δf.

4. The primary frequency regulation method of a water turbine with feedforward double fuzzy control adapting to operating condition changes according to claim 3, characterized in that, The PID parameter adjustment rule of the first fuzzy controller in step S2 is as follows: Where, K p (t), K i (t), K d (t) and K f (t) respectively represent the control parameters of the PID controller and the feed-forward path at the current moment; K p (t - 1), K i (t - 1), K d (t - 1) and K f (t - 1) respectively represent the control parameters of the PID controller and the feed-forward path at the previous moment; ΔK p , ΔK i , ΔK d and ΔK f respectively represent the control parameter adjustment amounts; the control parameter adjustment amounts ΔK p , ΔK i , ΔK d and ΔK f are inferred by the fuzzy inference machine according to the preset fuzzy inference rules in the fuzzy rule base, and the specific inference rules are designed according to the actual unit situation by itself.

5. The primary frequency regulation method of the water turbine with feedforward double fuzzy control adapting to the change of working conditions according to claim 4, characterized in that The described ΔK p , ΔK i , ΔK d and ΔK f are generated by a 7×7 fuzzy rule matrix. The fuzzy subsets are {NB, NM, NS, ZE, PS, PM, PB}, and the membership functions adopt triangular distributions. Among them, NB, NM, NS, ZE, PS, PM, and PB represent negative large, negative medium, negative small, zero, positive small, positive medium, and positive large, respectively.

6. A primary frequency regulation control method for a hydraulic turbine with feedforward double fuzzy control adapting to working condition changes, characterized in that, The relational expression between the target opening and the total control signal: u ref = f(u total ) = f(u PID + u ref ); where f(.) is the transfer function of the actuator; Opening deviation Δu = u actual - f(u PID + u ref ); Opening deviation change rate Among them, It is affected by the dynamic characteristics of the electro-hydraulic converter and the servomotor.

7. The primary frequency regulation method of a hydraulic turbine with feedforward double fuzzy control adapted to operating condition changes according to claim 6, characterized in that In step S5, the fuzzy control rule of the second fuzzy controller is determined according to the specific motion characteristics of the hydraulic system. Its purpose is to limit the change rate of the guide vane opening when the guide vane motion rate is large, and suppress the water hammer effect.

Images