A load frequency control method for interconnected power systems with hybrid energy storage systems based on event triggering and preset performance

Abstract

The application provides a regional interconnected power system load frequency control method based on event triggering and preset performance, aiming at solving the problem of frequency stability and control quality decline caused by actuator saturation, unknown disturbance and limited communication resources in a multi-regional power system containing a hybrid energy storage system. The method builds a multi-regional load frequency control model containing a hybrid energy storage system, and establishes a state space equation considering input saturation and composite disturbance; the transient and steady-state performance of the regional control error is constrained by using a preset performance function, and it is converted into an unconstrained form through error transformation; the unknown disturbance of the system is estimated and compensated online by using a projection adaptive law, and a dynamic event triggering mechanism is combined to reduce the update frequency of the control signal, thereby saving network communication resources. Through Lyapunov theory analysis, the control method proposed in this paper can not only ensure the boundedness of the system signal, but also constrain the tracking error within the preset range, and there is no Zeno behavior. Simulation results show that compared with traditional PID control and model predictive control (MPC), the strategy can better suppress frequency and power fluctuations, and reduce communication burden.

Description

Technical Field

[0001] This invention belongs to the field of power system automation and stability control technology, specifically relating to a load frequency control method applicable to multi-regional interconnected power grids, and more particularly to a preset performance event-triggered control strategy that comprehensively considers actuator saturation, unknown time-varying disturbances and communication resource constraints under the condition of hybrid energy storage system participation, which can be used for secondary frequency regulation of power grids in scenarios with a high proportion of new energy access. Background Technology

[0002] Power system frequency stability is a key indicator for ensuring the safe operation of the power grid, and its essence lies in the dynamic balance of active power between generation and load. In recent years, with the advancement of the "dual carbon" target, the penetration rate of renewable energy sources such as wind power and photovoltaics in the power system has been continuously increasing. However, renewable energy output is characterized by strong randomness, volatility, and low inertia, leading to a decline in system frequency regulation capability and a significant increase in the rate of frequency change. Traditional frequency regulation resources based on thermal and hydropower face severe challenges in terms of response speed and regulation accuracy. A series of power grid accidents both domestically and internationally demonstrate that frequency instability has become one of the main threats to the safe operation of modern power systems.

[0003] I. Current Status and Shortcomings of Load Frequency Control Research

[0004] Currently, while various technical approaches have emerged in load frequency control research, they all have significant limitations. Traditional PID control and parameter tuning methods based on intelligent optimization algorithms, though simple in structure, struggle to adapt to system nonlinearity and strong uncertainty, resulting in limited dynamic response quality. Methods based on advanced theories such as sliding mode control and adaptive control, while improving robustness, generally suffer from two shortcomings: first, they fail to actively constrain and strictly guarantee dynamic performance aspects such as transient overshoot and convergence speed of the control error (ACE), making them prone to tie-line power exceeding limits under disturbances; second, most neglect the actual output power saturation constraint of the energy storage system, leading to a mismatch between control commands and actual execution capabilities, potentially causing instability or equipment overload. Furthermore, existing strategies lack the ability to online estimate and compensate for complex unknown disturbances such as wind and solar power fluctuations and sudden load changes, and often rely on continuous or high-frequency communication, resulting in reliability degradation and resource waste when network bandwidth is limited. Therefore, a novel control method is urgently needed that can collaboratively address dynamic performance constraints, actuator saturation, disturbance suppression, and communication optimization.

[0005] II. The core problem to be solved by this invention

[0006] This invention aims to systematically solve four key technical challenges in the current load frequency control of interconnected power grids containing hybrid energy storage systems:

[0007] 1. The problem of the inability to preset and constrain the dynamic performance of regional control error: Existing control methods are difficult to integrate and strictly guarantee the transient overshoot, convergence speed and steady-state accuracy of ACE, which makes it prone to excessive fluctuations under disturbances, threatening the safety of tie lines and regulation efficiency.

[0008] 2. Mismatch between control strategies and physical operating constraints of energy storage systems: Most advanced control algorithms do not fully consider the output power saturation characteristics of energy storage systems, resulting in the inability to fully execute theoretical commands. This not only leads to performance degradation and instability risks, but may also accelerate equipment aging.

[0009] 3. Problem of insufficient robustness of system under complex unknown disturbances: Faced with multiple uncertainties such as new energy fluctuations, sudden load changes and model errors, the disturbance suppression capability of traditional methods is limited, which can easily lead to tracking errors exceeding the limit and slow frequency recovery.

[0010] 4. Resource waste and reliability reduction caused by reliance on continuous communication: When network bandwidth is limited, control architecture based on periodic updates will generate a lot of unnecessary communication, which will aggravate network congestion and reduce control performance when data packet loss or delay occurs.

[0011] Therefore, this invention aims to propose an integrated control method that can collaboratively achieve ACE dynamic preset, intrinsic anti-saturation compensation, adaptive disturbance suppression and event-triggered communication optimization, so as to improve system reliability and engineering practicality while ensuring high-performance frequency modulation. Summary of the Invention

[0012] The purpose of this application is to provide a load frequency control method for interconnected power systems containing hybrid energy storage systems based on event triggering and preset performance, comprising:

[0013] S1: Construct a load frequency control model for a multi-region interconnected power system that includes a hybrid energy storage system;

[0014] S2: Establish the system state-space equations considering input saturation and unknown combined disturbances;

[0015] S3: Design a preset performance controller, use a preset performance function to constrain the transient and steady-state performance of the regional control error, and use the projection adaptive law to estimate and compensate for the unknown composite disturbance online;

[0016] S4: Introduce a dynamic event triggering mechanism to generate actual control signals, thereby reducing the controller update frequency and communication burden;

[0017] A load frequency control method for an interconnected power system with hybrid energy storage system based on event triggering and preset performance, characterized in that step S1 includes:

[0018] An LFC system was constructed, and its components, including the prime mover, governor, generator-load, and tie lines, were modeled. A reheat turbine was selected as the prime mover, and its model is as follows:

[0019] (1)

[0020] In the above equation (1): Kr is the proportion of power generated by steam in the high-pressure cylinder; Tr is the reheater time coefficient; Tt is the steam chamber time coefficient; s is the Laplace transform operator;

[0021] By linearizing the speed governor, a speed governor model with a dead zone can be obtained:

[0022] (2)

[0023] (3)

[0024] In equations (2) and (3): Tg is the time constant of the speed controller; N1 and N2 are linearization coefficients;

[0025] The system consists of control region i and control region j. An energy storage system is added to the i-th and j-th control regions. The control commands output by the controller are used as the input signals of the energy storage system to establish a regional interconnected power system (LFC) model with energy storage. In the LFC system of a single region, only the thermal power unit unit exists, which mainly consists of three parts: governor, reheat turbine and generator.

[0026] Each of these components plays a unique role in the dynamic adjustment of the system frequency deviation, and through multi-level collaborative control, achieves system frequency stability and load balance.

[0027] The output signal of each control region is transmitted to another region through interconnection lines, thereby coordinating the adjustment of the frequency deviation between the two regions.

[0028] A load frequency control method for an interconnected power system with a hybrid energy storage system based on event triggering and preset performance, characterized in that step S2 includes:

[0029] The state-space equation and state of region i for:

[0030] (4)

[0031] (5)

[0032] In (4), and These are the system's state variables, outputs, and inputs, respectively. , , and These are the system's state matrix, input matrix, disturbance matrix, and output matrix, respectively, in the following forms:

[0033] (6)

[0034] (7)

[0035] (8)

[0036] (9)

[0037] (10)

[0038] In (6), For unknown disturbances in the power system, among which Unknown interference with user load Let be the power synchronization coefficient of the tie line between region i and region j. For incremental frequency offset in the interconnected power systems of regions i and j; This is the tie-line power adjustment, which is the power exchanged with the outside area through the tie-line due to frequency offset, used to compensate for disturbances.

[0039] A load frequency control method for an interconnected power system with a hybrid energy storage system based on event triggering and preset performance, characterized in that step S31 includes:

[0040] The system incorporates a saturation function to constrain the input signal, preventing overload or runaway of the energy storage device due to the control signal exceeding the system's tolerance range.

[0041] (11)

[0042] The saturation function is obtained through the above equation (11). The limiting function intercepts control signals that exceed the allowed upper or lower limits, thereby preventing input signals from exceeding the capacity limits of the energy storage system. However, Since the function is a non-smooth function, the backstepping method used in this invention requires all functions to be differentiable. Therefore, a smooth function is used to approximate the saturated function with a bounded approximation error, and anti-saturation processing is performed through equations (12) and (13):

[0043] (12)

[0044] (13)

[0045] In the above formula (13) Approximate saturation function With saturation function The error between them can be known from equation (14). Bounded;

[0046] (14)

[0047] The transformed state equation is shown in equation (15):

[0048] (15)

[0049] In the above formula (15)

[0050] (16)

[0051] The error in equation (13) and unknown disturbances in the system Integrating into a total unknown disturbance ;in , A positive constant;

[0052] The system's ACE value needs to be as low as possible. Therefore, the control objective is to make... And set the reference value to At time t, the expected output of the system is... Able to compare with reference value Maintain consistency. Definition To track errors, If each element in the equation evolves strictly within a specified region constrained by the performance function, then the specified performance can be achieved.

[0053] Traditional performance functions depend on initial errors, but from a practical perspective, initial errors are usually uncertain, and their precise values ​​are difficult to obtain. To facilitate PPC-based control design, a performance function that does not depend on initial errors is selected:

[0054] (17)

[0055] In the above formula (11) These are all normal values ​​from the design, and then error transformation is performed based on PPC theory:

[0056] (18)

[0057] right Differentiation yields:

[0058] (19)

[0059] in

[0060] (20)

[0061] A load frequency control method for an interconnected power system with a hybrid energy storage system based on event triggering and preset performance, characterized in that step S32 includes:

[0062] The unknown disturbance described in this invention is estimated and constrained using a projection function; the disturbance estimation error is defined as follows: Therefore, the projection function in this invention is as follows:

[0063] (twenty one)

[0064] In equation (21):

[0065] (twenty two)

[0066] (twenty three)

[0067] (twenty four)

[0068] In the above formula (23) For the designed positive constants; thus, we obtain:

[0069] (25)

[0070] A load frequency control method for an interconnected power system with a hybrid energy storage system based on event triggering and preset performance is characterized in that, in step S4, the dynamic event triggering mechanism is designed as follows:

[0071] Define the continuous-time virtual control law as follows: The actual control signal updated and applied to the actuator is ;

[0072] Define the event triggering error as:

[0073] (26)

[0074] The event triggering condition is set as follows:

[0075] (27)

[0076] Once the triggering condition is met, the control signal is immediately updated to:

[0077] (28)

[0078] in, It satisfies the positive constant. , , . and It is a time-varying parameter and satisfies , .

[0079] The controller design includes the following steps:

[0080] Choose the Lyapunov function;

[0081] (29)

[0082] The continuous controller is derived by combining the backstepping method with the anti-saturation function;

[0083] (30)

[0084] in:

[0085] Actual controller :

[0086] (31)

[0087] Stability analysis is performed using the properties of the projection operator.

[0088] Choosing Lyapunov functions

[0089] (32)

[0090] when , hour, have

[0091] (33)

[0092] because ,in They all have boundaries, therefore Bounded; For the design of positive constants, Ultimately bounded; therefore, according to Barbalat's lemma and the properties of projection functions, When it approaches 0, for As t approaches infinity, we have It tends to 0. (Based on PPC conclusions) It can be constrained within a preset range;

[0093] when , hour, ;

[0094] (34)

[0095] Therefore, according to the PPC conclusion The exponential convergence to zero It can be constrained within a preset range.

[0096] Avoid proving Zeno behavior;

[0097] Prove that the event triggering interval has a strictly positive lower bound. ,Right now .Depend on We can obtain:

[0098] (35)

[0099] in:

[0100] (36)

[0101] All are bounded functions composed of bounded values, and have an upper bound. Make Therefore, the lower bound of the execution interval is derived. Must meet This eliminates Zeno behavior and ensures the feasibility of the mechanism.

[0102] Compared with the prior art, the beneficial effects of the present invention are:

[0103] 1. By using preset performance control technology, strict dynamic constraints are achieved on the control error (ACE) of the region, ensuring that the system frequency recovers to the allowable range quickly and smoothly, effectively avoiding overshoot and continuous oscillation, and significantly improving the accuracy and reliability of secondary frequency modulation.

[0104] 2. The online parameter estimation method based on projection operators can identify and compensate for time-varying uncertainties in real time, enabling the hybrid energy storage system to maintain good performance under different operating conditions and disturbances, thereby improving the system's adaptability and robustness.

[0105] 3. An event-triggered mechanism is introduced, which triggers controller updates only when the system state meets specific conditions. This significantly reduces data transmission frequency and computational burden, saves communication bandwidth and hardware resources, and reduces the risk of failures caused by frequent communication. Attached Figure Description

[0106] Figure 1 is a flowchart illustrating the steps of a load frequency control method for an interconnected power system containing a hybrid energy storage system based on event triggering and preset performance, according to the present invention.

[0107] Figure 2 is a model diagram of load frequency control (LFC) for the two-region interconnected power system of the present invention.

[0108] Figure 3 This is a diagram illustrating the physical meaning of the load frequency control (LFC) model parameters for the two-region interconnected power system of this invention.

[0109] Figure 4 is a flowchart of the controller design for a load frequency control method for an interconnected power system with a hybrid energy storage system based on event triggering and preset performance, according to the present invention.

[0110] Figure 5 This is a simulation diagram showing the frequency variation of a load frequency control method for an interconnected power system with a hybrid energy storage system based on event triggering and preset performance, according to the present invention.

[0111] Figure 6 This is a simulation diagram of the system state variables in this invention.

[0112] Figure 7 This is a simulation diagram of the ACE response curve in this invention.

[0113] Figure 8 The event interval time diagram for event triggering in this invention.

[0114] Figure 9 This is a frequency deviation diagram of region 1 under long-term random load disturbance according to the present invention.

[0115] Figure 10 This is the ACE response curve of region 1 under long-term random load disturbance of the present invention. Detailed Implementation

[0116] The present invention will be further described in detail below with reference to the embodiments and figures, but the embodiments of the present invention are not limited thereto.

[0117] like Figure 1 The diagram shows the steps of a load frequency control method for an interconnected power system with a hybrid energy storage system based on event triggering and preset performance, according to the present invention.

[0118] A load frequency control method for regional interconnected power systems based on event triggering and preset performance, characterized by comprising the following steps:

[0119] S1: Construct a load frequency control model for a multi-region interconnected power system that includes a hybrid energy storage system;

[0120] S2: Establish the system state-space equations considering input saturation and unknown combined disturbances;

[0121] S3: Design a preset performance controller, use a preset performance function to constrain the transient and steady-state performance of the regional control error, and use the projection adaptive law to estimate and compensate for the unknown composite disturbance online;

[0122] S4: Introduce a dynamic event triggering mechanism to generate actual control signals, thereby reducing the controller update frequency and communication burden;

[0123] like Figure 2 The diagram shows the load frequency control (LFC) model of the two-region interconnected power system of the present invention constructed in step S1.

[0124] The system consists of a prime mover, governor, generator-load connection, and tie lines; a reheat turbine is selected as the prime mover, and its model is as follows:

[0125] (1)

[0126] In the formula (1): Kr is the proportion of power generated by steam in the high-pressure cylinder; Tr is the reheater time coefficient; Tt is the steam chamber time coefficient; s is the Laplace transform operator.

[0127] By linearizing the speed governor, a speed governor model with a dead zone can be obtained:

[0128] (2)

[0129] (3)

[0130] In equations (2) and (3): N is the time constant of the speed controller; N1 and N2 are linearization coefficients.

[0131] The system consists of control region i and control region j. An energy storage system is added to the i-th and j-th control regions, and the control commands output by the controller are used as input signals for the energy storage system to establish an LFC (Locally Connected Power System) model with energy storage. In a single-region LFC system, only the thermal power unit unit exists, mainly consisting of a governor, a reheat turbine, and a generator. These three parts play unique roles in the dynamic adjustment of system frequency deviation, achieving system frequency stability and load balance through multi-level coordinated control.

[0132] The output signal of each control zone is transmitted to another zone through interconnection lines, thereby coordinating the adjustment of the frequency deviation between the two zones.

[0133] like Figure 3 The diagram shows the physical meaning of the load frequency control (LFC) model parameters of the two-region interconnected power system of this invention. Figure 2 Each parameter in Figure 3There are corresponding explanations in each of them.

[0134] Step S2 includes:

[0135] The state-space equation and state of region i for:

[0136] (4)

[0137] (5)

[0138] In equation (4), and These are the system's state variables, outputs, and inputs, respectively. , , and These are the system's state matrix, input matrix, disturbance matrix, and output matrix, respectively, in the following forms:

[0139] (6)

[0140] (7)

[0141] (8)

[0142] (9)

[0143] (10)

[0144] In equation (6), For unknown disturbances in the power system, among which Unknown interference with user load Let be the power synchronization coefficient of the tie line between region i and region j. For incremental frequency offset in the interconnected power systems of regions i and j; This is the tie-line power adjustment, which is the power exchanged with the outside area through the tie-line due to frequency offset, used to compensate for disturbances.

[0145] Step S31 includes:

[0146] The system incorporates a saturation function to constrain the input signal, preventing overload or runaway of the energy storage device due to the control signal exceeding the system's tolerance range.

[0147] (11)

[0148] The saturation function is obtained through the above equation (11). The limiting function intercepts control signals that exceed the allowed upper or lower limits, thereby preventing input signals from exceeding the capacity limits of the energy storage system. However, Since the function is a non-smooth function, the backstepping method used in this invention requires all functions to be differentiable. Therefore, a smooth function is used to approximate the saturated function with a bounded approximation error, and anti-saturation processing is performed through equations (12) and (13):

[0149] (12)

[0150] (13)

[0151] In formula (13) Approximate saturation function With saturation function The error between them can be known from equation (14). Bounded.

[0152] (14)

[0153] The transformed state equation is shown in equation (15):

[0154] (15)

[0155] In formula (15)

[0156] (16)

[0157] The error in equation (13) and unknown disturbances in the system Integrating into a total unknown disturbance ;in , It is a positive constant.

[0158] The system's ACE value needs to be as low as possible. Therefore, the control objective is to make... And set the reference value to At time t, the expected output of the system is... Able to compare with reference value Maintain consistency. Definition To track errors, If each element in the equation evolves strictly within a specified region constrained by the performance function, then the specified performance can be achieved.

[0159] The performance function is selected as follows:

[0160] (17)

[0161] In formula (11) These are all normal values ​​from the design, and then error transformation is performed based on PPC theory:

[0162] (18)

[0163] right Differentiation yields:

[0164] (19)

[0165] in

[0166] (20)

[0167] Step S32 includes:

[0168] For unknown disturbances, the present invention uses a projection function to estimate and constrain them; the disturbance estimation error is defined as... Therefore, the projection function in this invention is as follows:

[0169] (twenty one)

[0170] (21) Where:

[0171] (twenty two)

[0172] (twenty three)

[0173] (twenty four)

[0174] In equation (23) For the designed positive constants; thus, we obtain:

[0175] (25)

[0176] Step S4 includes:

[0177] Define the continuous-time virtual control law as follows: The actual control signal updated and applied to the actuator is ;

[0178] Define the event triggering error as:

[0179] (26)

[0180] The event triggering condition is set as follows:

[0181] (27)

[0182] Once the triggering condition is met, the control signal is immediately updated to:

[0183] (28)

[0184] in, It satisfies the positive constant. , , . and It is a time-varying parameter and satisfies , .

[0185] The controller design includes the following steps:

[0186] Choose the Lyapunov function;

[0187] (27)

[0188] The controller is derived by using the backstepping method combined with the anti-saturation function;

[0189] (27)

[0190] in:

[0191] Actual controller :

[0192] (31)

[0193] Stability analysis is performed using the properties of the projection operator.

[0194] Choosing Lyapunov functions

[0195] (29)

[0196] when , hour, have

[0197] (30)

[0198] because ,in They all have boundaries, therefore Bounded; For the design of positive constants, Ultimately bounded; therefore, according to Barbalat's lemma and the properties of projection functions, When it approaches 0, for As t approaches infinity, we have It tends to 0. (Based on PPC conclusions) It can be constrained within a preset range.

[0199] when , hour,

[0200] (42)

[0201] Therefore, according to the PPC conclusion The exponential convergence to zero It can be constrained within a preset range.

[0202] Avoid proving Zeno behavior;

[0203] Prove that the event triggering interval has a strictly positive lower bound. ,Right now .Depend on We can obtain:

[0204] (35)

[0205] in:

[0206] (36)

[0207] All are bounded functions composed of bounded values, and have an upper bound. Make Therefore, the lower bound of the execution interval is derived. Must meet This eliminates Zeno behavior and ensures the feasibility of the mechanism.

[0208] like Figure 4 The diagram shown is a controller design flowchart for a load frequency control method for an interconnected power system with a hybrid energy storage system based on event triggering and preset performance, according to the present invention.

[0209] First, calculate the tracking error between the actual output of the calculation system and the reference signal. This serves as the starting point for control. Subsequently, to handle the output power constraint of the energy storage system, a smooth hyperbolic tangent function is employed. Approximates saturation characteristics and establishes a model containing lumped unknown perturbations. The system state-space equations are then derived. Next, an adaptive control law is designed based on this model. With continuous controller The projection operator is used to estimate the unknown disturbance online, and the estimated value is obtained. Then, a dynamic event triggering mechanism is used to determine whether the current state meets the triggering conditions: if it does, the continuous controller is updated; if not, the original control signal is maintained. Finally, the updated control command is processed by an anti-saturation function, and the output is the actual power signal acting on the energy storage system. The entire design process, through series error calculation, anti-saturation modeling, adaptive disturbance suppression, and event-triggered decision-making, effectively handles actuator saturation, suppresses unknown disturbances, and saves communication resources while ensuring preset dynamic performance, thus enhancing the robustness and practicality of load frequency control in complex power grid environments.

[0210] like Figure 5 The figure shown is a frequency change comparison simulation diagram of a load frequency control method for an interconnected power system with a hybrid energy storage system based on event triggering and preset performance, according to the present invention.

[0211] The red curve represents the frequency deviation curve of region 1 under the control strategy implemented in this invention, the black curve represents the frequency deviation curve of region 1 under the PID controller control strategy tuned by the fixed K method, and the blue curve represents the frequency deviation curve of region 1 under the MPC control strategy.

[0212] During the transient simulation from 0 to 10 seconds, Scheme 3 (red curve, the control strategy of this invention) showed the best control effect on the frequency deviation in region 1: it only produced a slight dip under initial disturbance, with no obvious overshoot or oscillation, and then smoothly converged to near the zero axis, exhibiting stable dynamic response and the highest steady-state accuracy. In contrast, Scheme 2 (blue curve, MPC control strategy) had a slightly larger initial dip, a smooth recovery process, but a slightly slower convergence speed than the strategy of this invention; Scheme 1 (black curve, fixed-K PID control strategy) had the most severe initial oscillation, with multiple fluctuations, the largest overshoot, and a slow convergence process, resulting in the worst control performance. Overall, the control strategy of this invention showed significant advantages in suppressing transient oscillations and accelerating convergence speed, comprehensively outperforming the comparative schemes and better ensuring the stable operation of the system frequency. Figure 6 The figure shown is a simulation diagram of the system state variables in this invention.

[0213] The meaning of each different colored curve is as follows: Figure 3 The simulation structure is shown in the figure. Within 10 seconds, under the load frequency preset performance control method of the regional interconnected power system considering output power constraints and unknown disturbances of the present invention, all state variables of the power system in region 1 can be converged.

[0214] like Figure 7 The figure shown is a simulation diagram of the ACE response curve in this invention.

[0215] The red curve represents the response curve of Region 1 ACE under the control strategy implemented in this invention, the black curve represents the response curve of Region 1 ACE under the PID controller control strategy tuned by the fixed-K method, and the blue curve represents the response curve of Region 1 ACE based on the MPC control strategy.

[0216] Simulation results show that during the 0-10s transient simulation, Scheme 3 (red curve, the control strategy of this invention) exhibits the best control performance for region 1 ACE: it only produces a slight dip under initial disturbance, with no significant overshoot or oscillation, and then smoothly converges to near the zero axis, demonstrating the best steady-state accuracy and stability, while strictly meeting the PPB constraint requirements throughout. In contrast, Scheme 2 (blue curve, MPC control strategy) has a slightly larger initial dip and a slightly slower convergence speed; although it can maintain stability, its dynamic performance is slightly inferior to the strategy of this invention. Scheme 1 (black curve, fixed-K PID control strategy) exhibits severe initial oscillation, the largest overshoot with multiple fluctuations, a slow convergence process, and the worst control performance. Overall, the control strategy of this invention demonstrates significant advantages in suppressing transient oscillations, improving dynamic response speed, and steady-state control accuracy, comprehensively outperforming the comparative schemes and better meeting the ideal control objective of the PPB constraint.

[0217] Figure 8 This is a time interval diagram of event triggering in this invention.

[0218] The system updates its input signals using an event-triggered mechanism, rather than the traditional continuous or periodic sampling method. Specifically, the controller only performs the update operation when preset trigger conditions are met. This mechanism effectively reduces the controller's computational load and communication frequency, thereby improving the system's practicality and engineering applicability while ensuring dynamic performance.

[0219] Figure 9 This is a simulation diagram of the ACE response curve under long-term random load disturbance of the present invention.

[0220] The red curve represents the response curve of Region 1 ACE under the control strategy implemented in this invention, the black curve represents the response curve of Region 1 ACE under the PID controller control strategy tuned by the fixed-K method, and the blue curve represents the response curve of Region 1 ACE based on the MPC control strategy.

[0221] Within the simulation period of 0~2000s, Scheme 3 (red curve, control strategy of this invention) showed the best control effect on ACE in region 1: its response amplitude was the smallest and the fluctuation was the smoothest. During the local magnification periods of 350~450s and 1000~1200s, the ACE deviation was effectively suppressed to a very small range and quickly converged to near the zero axis, demonstrating extremely strong anti-interference ability and steady-state control accuracy.

[0222] In comparison, the ACE response fluctuation of Scheme 2 (blue curve, MPC control strategy) is significantly greater than that of Scheme 3. Although it can maintain system stability, the oscillation during the adjustment process is more violent, and the control accuracy is slightly inferior. Scheme 1 (cyan curve, fixed-K PID control strategy) has the most violent deviation response, with a peak value close to ±0.06 Hz, and the weakest anti-interference ability and fluctuation smoothing ability.

[0223] Overall, the control strategy proposed in this invention demonstrates significant advantages in suppressing ACE fluctuations in region 1, ensuring system frequency stability and control accuracy. Its dynamic adjustment speed and steady-state control performance are comprehensively superior to the comparative schemes, fully verifying the effectiveness and superiority of the strategy.

[0224] Figure 10 This is a simulation diagram of the frequency deviation curve under long-term random load disturbance of the present invention.

[0225] The red curve represents the frequency deviation curve in region 1 under the control strategy implemented in this invention; the blue curve represents the frequency deviation curve in region 1 under the PID controller control strategy tuned by the fixed-K method; and the dark curve represents the frequency deviation curve in region 1 based on the MPC control strategy. Within the simulation period of 0~2000s, Scheme 3 (red curve, the control strategy of this invention) exhibits the best control effect on the frequency deviation in region 1: its response amplitude is the smallest, and the fluctuation is the smoothest. During the local amplification periods of 100~300s and 1300~1550s, the frequency deviation is quickly suppressed to a very small range and rapidly converges to near the zero axis, demonstrating stable dynamic response and high steady-state accuracy.

[0226] In comparison, Scheme 2 (blue curve, fixed-K PID control strategy) exhibits a significantly larger frequency deviation fluctuation than Scheme 3. While it maintains system stability, the oscillations during adjustment are more severe, resulting in slightly lower control accuracy. Scheme 1 (cyan curve, MPC control strategy) shows the most severe deviation response, with a peak value approaching ±0.025, exhibiting the weakest anti-interference and fluctuation smoothing capabilities. Furthermore, the PPB constraint curve (red dashed line) clearly defines the safe operating boundary for frequency deviation. Scheme 3's response consistently stays close to the zero axis and is far superior to the PPB constraint requirements, fully validating the significant advantages of the present invention's control strategy in suppressing frequency deviation in region 1, ensuring system frequency stability, and maintaining control accuracy. Its dynamic adjustment speed and steady-state control performance are comprehensively superior to the comparative schemes.

Claims

1. A load frequency control method for a regional interconnected power system based on event triggering and preset performance, characterized in that, Includes the following steps: S1: Construct a load frequency control model for a multi-region interconnected power system that includes a hybrid energy storage system; S2: Establish the system state-space equations considering input saturation and unknown combined disturbances; S3: Design a preset performance controller, use a preset performance function to constrain the transient and steady-state performance of the regional control error, and use the projection adaptive law to estimate and compensate for the unknown composite disturbance online; S4: Introduce a dynamic event triggering mechanism to generate actual control signals, thereby reducing the controller update frequency and communication burden; S5: Based on Lyapunov stability theory, analyze and prove the stability and error performance of the closed-loop system.

2. A load frequency control method for an interconnected power system containing a hybrid energy storage system based on event triggering and preset performance, characterized in that, Step S1 includes: An LFC system was constructed, and its components, including the prime mover, governor, generator-load, and tie lines, were modeled. A reheat turbine was selected as the prime mover, and its model is as follows: （1） In the above equation (1): Kr is the proportion of power generated by steam in the high-pressure cylinder; Tr is the reheater time coefficient; Tt is the steam chamber time coefficient; s is the Laplace transform operator; By linearizing the speed governor, a speed governor model with a dead zone can be obtained: （2） （3） In equations (2) and (3): Tg is the time constant of the speed controller; N1 and N2 are linearization coefficients; The system consists of control region i and control region j. An energy storage system is added to the i-th and j-th control regions. The control commands output by the controller are used as the input signals of the energy storage system to establish a regional interconnected power system (LFC) model with energy storage. In the LFC system of a single region, only the thermal power unit unit exists, which mainly consists of three parts: governor, reheat turbine and generator. Each of these components plays a unique role in the dynamic adjustment of the system frequency deviation, and through multi-level collaborative control, achieves system frequency stability and load balance. The output signal of each control region is transmitted to another region through interconnection lines, thereby coordinating the adjustment of the frequency deviation between the two regions.

3. A load frequency control method for an interconnected power system containing a hybrid energy storage system based on event triggering and preset performance, characterized in that, Step S2 includes: The state-space equation and state of region i for: （4） （5） In (4), and These are the system's state variables, outputs, and inputs, respectively. , , and These are the system's state matrix, input matrix, disturbance matrix, and output matrix, respectively, in the following forms: （6） （7） （8） （9） （10） In (6), For unknown disturbances in the power system, among which Unknown interference with user load Let be the power synchronization coefficient of the tie line between region i and region j. For incremental frequency offset in the interconnected power systems of regions i and j; This is the tie-line power adjustment, which is the power exchanged with the outside area through the tie-line due to frequency offset, used to compensate for disturbances.

4. A load frequency control method for an interconnected power system containing a hybrid energy storage system based on event triggering and preset performance, characterized in that, Step S31 includes: The system incorporates a saturation function to constrain the input signal, preventing overload or runaway of the energy storage device due to the control signal exceeding the system's tolerance range. (11) The saturation function is obtained through the above equation (11). The limiting function intercepts control signals that exceed the allowed upper or lower limits, thereby preventing input signals from exceeding the capacity limits of the energy storage system. However, Since the function is a non-smooth function, the backstepping method used in this invention requires all functions to be differentiable. Therefore, a smooth function is used to approximate the saturated function with a bounded approximation error, and anti-saturation processing is performed through equations (12) and (13): (12) (13) In the above formula (13) Approximate saturation function With saturation function The error between them can be known from equation (14). Bounded; (14) The transformed state equation is shown in equation (15): (15) In the above formula (15) (16) The error in equation (13) and unknown disturbances in the system Integrating into a total unknown disturbance ;in , A positive constant; The system's ACE value needs to be as low as possible. Therefore, the control objective is to make... And set the reference value to At time t, the expected output of the system is... Able to compare with reference value Maintain consistency. Definition To track errors, If each element in the equation evolves strictly within a specified region constrained by the performance function, then the specified performance can be achieved. Traditional performance functions depend on initial errors, but from a practical perspective, initial errors are usually uncertain, and their precise values ​​are difficult to obtain. To facilitate PPC-based control design, a performance function that does not depend on initial errors is selected: (17) In the above formula (11) These are all normal values ​​from the design, and then error transformation is performed based on PPC theory: (18) right Differentiation yields: (19) in (20) 5. A load frequency control method for an interconnected power system containing a hybrid energy storage system based on event triggering and preset performance, characterized in that, Step S32 includes: The unknown disturbance described in this invention is estimated and constrained using a projection function; the disturbance estimation error is defined as follows: Therefore, the projection function in this article is as follows: (21) In equation (21): (22) (23) (24) In the above formula (23) For the designed positive constants; thus, we obtain: (25) 6. A load frequency control method for an interconnected power system containing a hybrid energy storage system based on event triggering and preset performance, characterized in that, In step S4, the dynamic event triggering mechanism is designed as follows: Define the continuous-time virtual control law as follows: The actual control signal updated and applied to the actuator is ; Define the event triggering error as: (26) The event triggering condition is set as follows: (27) Once the triggering condition is met, the control signal is immediately updated to: (28) in, It satisfies the positive constant. , , . and It is a time-varying parameter and satisfies , .

7. The controller design includes the following steps: S51, select the Lyapunov function; (29) S52, a continuous controller is derived by using the backstepping method combined with the anti-saturation function; (30) in: Actual controller : (31) S53, stability analysis is performed using the properties of the projection operator; Choosing Lyapunov functions (32) when , hour, have (33) because ,in They all have boundaries, therefore Bounded; For the design of positive constants, Ultimately bounded; therefore, according to Barbalat's lemma and the properties of projection functions, When it approaches 0, for As t approaches infinity, we have It tends to 0. (Based on PPC conclusions) It can be constrained within a preset range; when , hour, ; (34) Therefore, according to the PPC conclusion The exponential convergence to zero It can be constrained within a preset range. S54, proof of avoiding Zeno behavior; Prove that the event triggering interval has a strictly positive lower bound. ,Right now .Depend on We can obtain: (35) in: (36) All are bounded functions composed of bounded values, and have an upper bound. Make Therefore, the lower bound of the execution interval is derived. Must meet This eliminates Zeno behavior and ensures the feasibility of the mechanism.

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