Island AC micro-grid distributed secondary privacy protection control method and system

Abstract

The invention provides a distributed secondary privacy protection control method and system for an island alternating current microgrid. The method comprises the following steps: establishing a dynamic model of a distributed generator and a microgrid economic dispatching model; carrying out encryption protection on the real state of the island AC micro-grid to obtain an encrypted sub-state; based on the encrypted sub-state, constructing a dynamic event triggering consistency controller for voltage and frequency recovery; and constructing a dynamic event triggering consistency controller with optimal power distribution. According to the method, the secondary distributed controller is designed for the dynamic model of the distributed generator and the microgrid economic dispatching model, so that the voltage and frequency stability can be maintained, the optimal economic operation is realized, and the method has the advantages of small communication burden, high convergence speed and capability of realizing accurate consistency; the privacy information is protected by reducing the number of times of real-time state transmission and a state decomposition mechanism, so that the problem of privacy information protection when external attacks exist is solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of distributed power generation control of an isolated AC microgrid, and specifically, relates to a distributed secondary privacy protection control method and system for an isolated AC microgrid, in particular, a distributed secondary privacy protection control method for a microgrid based on dynamic event triggering and state decomposition. Background Art

[0002] As an important part of smart grid, AC microgrid is an effective solution for smoothly integrating a large number of distributed energy sources. It can operate in grid-connected or island mode. When operating in island mode, the most important issue is to maintain the stability of system frequency and voltage while achieving optimal economic operation. Due to the flexible plug-and-play capability and strong robustness of distributed control, it has been widely used in frequency and voltage control of island AC microgrid.

[0003] The existing distributed consensus algorithm based on multi-agents requires real-time information exchange between adjacent power generation units through the communication network, but this will inevitably cause privacy information leakage. When external intruders try to steal real-time sensitive information through the communication network channel and design attack signals to destroy the consistency, it will seriously affect the safe operation of the microgrid and may cause the entire system to become unstable.

[0004] In order to solve the privacy leakage problem caused by information exchange, existing technologies mainly deal with it through methods including differential privacy, homomorphic encryption and affine transformation. However, the above solutions have problems such as heavy communication burden, slow convergence speed and inability to achieve precise consistency.

[0005] The patent document "Isolated Microgrid Privacy Protection Distributed Economic Dispatching Method Based on Encryption Strategy" (CN115834022A) discloses that a group obtains its own information and the information of other adjacent generators in the communication network through a confidential interaction protocol. However, its encryption strategy is to encrypt the transmitted state using a homomorphic encryption strategy, that is, to convert the transmitted state into ciphertext, and then send it to neighbors in the form of ciphertext. The transmission state needs to be continuously encrypted and decrypted, which will seriously increase the computational burden and be inefficient.

[0006] In addition, the above methods are mainly considered from the perspective of privacy data encryption, and rarely protect privacy information from the number of times the privacy data is transmitted through the communication network. Therefore, it is difficult to solve the problem of privacy protection information when there is an external attack. Summary of the invention

[0007] In view of the defects in the prior art, the object of the present invention is to provide a distributed secondary privacy protection control method and system for an isolated AC microgrid.

[0008] A distributed secondary privacy protection control method for an isolated AC microgrid provided by the present invention includes:

[0009] Step S1: construct a dynamic model of distributed generators and an economic dispatch model of microgrids;

[0010] Step S2: Encrypt and protect the real state of the isolated AC microgrid to obtain an encrypted sub-state;

[0011] Step S3: constructing a voltage controller and a frequency recovery controller based on the encrypted sub-state;

[0012] Step S4: constructing an optimal power distribution controller based on the encrypted sub-states;

[0013] Step S5: The optimal output active power is obtained according to the frequency recovery controller and the optimal power allocation controller, and the voltage controller adjusts the voltage.

[0014] Preferably, the island AC microgrid in step S1 includes a distributed generator.

[0015] The step S1 comprises:

[0016] Step S1.1: construct a dynamic model of distributed generators;

[0017] Step S1.2: Construct an economic dispatch model for the island AC microgrid.

[0018] The step S1.1 comprises:

[0019] Step S1.1.1: Construct the droop control equation for frequency ω i (t) = ω ni (t)-m i P i (t) and the voltage droop control equation v oi (t) = V ni (t)-k i Q i (t);

[0020] Among them, ω i (t),ω ni (t) represent the output angular frequency and primary control reference angular frequency of the i-th distributed generator, respectively;

[0021] v oi (t), V ni (t) represent the output voltage amplitude and primary control reference voltage amplitude of the i-th distributed generator, respectively;

[0022] P i (t), Q i(t) represent the active power and reactive power output by the i-th distributed generator respectively;

[0023] m i , k i They represent the active power droop coefficient and reactive power droop coefficient of the i-th distributed generator respectively;

[0024] t represents time.

[0025] Step S1.1.2: Coordinate transformation to obtain the improved voltage droop control equation v odi (t) = V ni (t)-k i Q i (t) and v oqi (t) = 0;

[0026] Among them, v odi (t), v oqi (t) respectively represent the output voltage amplitude v oi The direct axis part and the cross axis part of (t),

[0027] Step S1.1.3: Construct the frequency dynamic equation and voltage dynamic equation of the distributed generator:

[0028]

[0029] in, Respectively represent ω i (t),ω ni (t), P i The first derivative of (t);

[0030] Respectively represent v odi (t), V ni (t), Q i The first derivative of (t);

[0031] u ωi (t),u vi (t),u pi (t) represent the secondary control input signals of frequency recovery, voltage recovery and optimal power allocation respectively;

[0032] Indicates the cutoff frequency of the low-pass filter;

[0033] i odi (t), i oqi (t) respectively represent the output current amplitude i oi The direct axis part and the cross axis part of (t),

[0034]

[0035] Step S1.1.4: Calculate the primary control reference angular frequency ω ni (t) and the primary control reference voltage amplitude V ni (t);

[0036]

[0037] The step S1.2 comprises:

[0038] Step S1.2.1: Construct the power generation cost function model C i (P i (t)) = a i (P i (t)) 2 +c i P i (t)+γ i ;

[0039] Among them, C i (P i (t)) is the power generation cost function of the i-th distributed generator;

[0040] a i 、c i , γ i Denote the three generation cost coefficients of the i-th distributed generator.

[0041] Step S1.2.2: Construct the economic dispatch model of the microgrid:

[0042]

[0043] P min_i ≤P i ≤P max_i ;

[0044] Where C(P(t)) represents the total power generation cost of the microgrid system;

[0045] P i (t0) represents the initial active power output by the i-th distributed generator;

[0046] t0 represents the initial time;

[0047] n means there are n distributed generators in total;

[0048] P D Represents the total active power of the microgrid system load;

[0049] P min_i , P max_iThey respectively represent the minimum active power and maximum active power that the i-th distributed generator can output.

[0050] Preferably, step S2 comprises:

[0051] Step S2.1: The real state x of the distributed generator i (t) is divided into two sub-states

[0052] in, Represents two decomposition coefficients.

[0053] Step S2.2: Construct the encrypted frequency and voltage dynamic equations of distributed generators:

[0054]

[0055] in, Represents ω i (t) has two sub-states, Respectively The first derivative of ;

[0056] Indicates v odi (t) has two sub-states, Respectively The first derivative of ;

[0057] Indicates P i (t) has two sub-states, Respectively The first derivative of ;

[0058] Indicates u ωi Two sub-states of (t);

[0059] Indicates u vi Two sub-states of (t);

[0060] Indicates u pi (t) has two sub-states.

[0061] Preferably, step S3 comprises:

[0062] Step S3.1: Build a dynamic event-triggered consistency controller for voltage and frequency recovery:

[0063] Frequency Restoration Controller

[0064] Voltage Controller

[0065]

[0066] Among them, c g represents the control gain coefficient;

[0067] a ij The weighted adjacency matrix A represents the communication topology of the isolated AC microgrid. ij ), if the i-th distributed generator can receive information from the j-th distributed generator, then a ij =1, if not, then a ij =0;

[0068] b i represents the gain coefficient. If the i-th distributed generator can obtain the reference value information, then b i =1, if not, then b i =0;

[0069] is the gain coefficient between the two sub-states of the i-th distributed generator;

[0070] ω nom 、v nom Respectively represent frequency and voltage ratings;

[0071] Indicates the frequency sub-state of the i-th generator The estimated status of

[0072] Indicates the frequency sub-state of the i-th generator The estimated status of

[0073] Represents the voltage sub-state of the i-th generator The estimated status of

[0074] Represents the voltage sub-state of the i-th generator The estimated status of

[0075] Indicates the frequency sub-state of the jth generator The estimated status of

[0076] Indicates the voltage sub-state of the jth generator The estimated status of

[0077] Respectively represent the frequency sub-state of the i-th generator In the kth αThe trigger state and frequency sub-state of each trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…;

[0078] Represent the voltage sub-state of the i-th generator In the kth α The trigger state and voltage sub-state at the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,….

[0079] Step S3.2: Construct a trigger function for updating the frequency and voltage sub-states:

[0080]

[0081] in, represents the local measurement error, ξ∈(ω,v);

[0082] represents the tracking error;

[0083] represents the consistency error;

[0084] μ ξi ,θ ξi , π ξi is a constant greater than 0;

[0085] Indicates the kth frequency or voltage update of the i-th generator i +1 trigger moment, k i =0,1,2,…;

[0086] Indicates the kth frequency or voltage update of the i-th generator i A trigger moment;

[0087] d ξi (t) is the internal adaptive dynamic variable;

[0088] The internal adaptive dynamic variable d ξi (t) Satisfaction

[0089] Among them, l ξ1 , l ξ2 , d ξi (0) are all constants greater than 0;

[0090] Indicates d ξi The first derivative of (t).

[0091] Preferably, step S4 comprises:

[0092] Step S4.1: Calculate the incremental cost sub-state of the distributed generators:

[0093]

[0094] in, Denotes the incremental cost λ i Two sub-states of (t);

[0095] Represents C i (P i (t)) has two sub-states.

[0096] Step S4.2: Construct a dynamic event-triggered consistency controller for optimal active power distribution:

[0097]

[0098]

[0099] Among them, c v is the control gain coefficient;

[0100] Represents the incremental cost sub-state of the i-th generator The estimated status of

[0101] Represents the incremental cost sub-state of the i-th generator The estimated status of

[0102] Represents the incremental cost sub-state of the i-th generator In the kth α The trigger state and cost sub-state of the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…;

[0103] Indicates P i (t0) has two sub-states.

[0104] Step S4.3: Construct a trigger function for updating the incremental cost sub-state:

[0105]

[0106] in, Indicates sub-state Column vector of ;

[0107] Indicates estimated state Column vector of ;

[0108] Indicates the active power sub-state Column vector of ; represents the local measurement error;

[0109] represents the tracking error;

[0110] represents the consistency error;

[0111] μ λi ,θ λi , π λi All are constants greater than 0;

[0112] d λi (t) is the internal adaptive dynamic variable;

[0113] The internal adaptive dynamic variable d λi (t) Satisfaction Among them, l λ1 , l λ2 , d λi (0) are all constants greater than 0;

[0114] Indicates d λi The first derivative of (t).

[0115] Step S4.4: Solve the economic dispatch model:

[0116]

[0117] Among them, λ ★ represents the optimal incremental cost considering both the power balance constraint and the generation capacity constraint;

[0118]

[0119] Where Φ represents the set of distributed generators whose optimal output power violates the generation capacity constraint;

[0120] λ * represents the optimal incremental cost when only the power balance constraint is considered.

[0121] Step S4.5: Construct two auxiliary controllers to achieve optimal active power distribution.

[0122] Step S4.6: Update ψ i (t),δ i (t) Two estimated states of the substate:

[0123]

[0124] in, represents the local measurement error;

[0125] represents the consistency error;

[0126] μ δi ,θ δi , π δi All represent constants greater than 0;

[0127] and d δi (t) is the internal adaptive dynamic variable;

[0128] l δ1 , l δ2 , d δi (0) are all constants greater than 0;

[0129] Respectively d δi The first derivative of (t).

[0130] In step S4.5, two auxiliary variables ψ are introduced i (t) and δ i (t),

[0131] Two auxiliary controllers are constructed to achieve the optimal active power allocation under power generation constraints:

[0132]

[0133] in, Indicates sub-state Column vector of ;

[0134] Indicates sub-state Column vector of ;

[0135] Indicates estimated state Column vector of ;

[0136] Indicates estimated state Column vector of ;

[0137]

[0138] c ψ 、c δ represents the control gain coefficient;

[0139] Represents ψ i Two sub-states of (t);

[0140] Represents δ i Two sub-states of (t);

[0141] express The estimated status of

[0142] express The estimated status of

[0143] express The estimated status of

[0144] express The estimated status of

[0145] Represents sub-states In the kth α The trigger state and sub-state of the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…;

[0146] Represents sub-states In the kth α The trigger state and sub-state of the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,….

[0147] In step S5, the primary control block diagram of the distributed generator includes five parts: a power calculation module, a low-pass filter, a droop controller and a voltage and current controller.

[0148] The main circuit of the distributed generator includes a VSC inverter, an LC filter and an LC output connection unit.

[0149] The control input signal generated by the optimal power distribution controller The control input signal generated by the frequency recovery controller Superposition, the primary control reference angular frequency ω is obtained through the integrator ni (t), generate PWM signal according to voltage and current double closed-loop control, and solve the final optimal output active power by controlling the switch of the inverter

[0150]

[0151] Among them, P i * represents the optimal active power of the i-th generator.

[0152] According to the present invention, a distributed secondary privacy protection control system for an isolated AC microgrid is provided, comprising:

[0153] Module M1: Construct the dynamic model of distributed generators and the economic dispatch model of microgrids;

[0154] Module M2: encrypt and protect the real state of the isolated AC microgrid to obtain the encrypted sub-state;

[0155] Module M3: constructs voltage controller and frequency recovery controller based on the encrypted sub-state;

[0156] Module M4: construct an optimal power allocation controller based on the encrypted sub-states;

[0157] Module M5: The optimal output active power is obtained according to the frequency recovery controller and the optimal power allocation controller, and the voltage controller adjusts the voltage.

[0158] Preferably, the island AC microgrid in module M1 includes a distributed generator;

[0159] The module M1 comprises:

[0160] Module M1.1: Establish the dynamic model of distributed generators;

[0161] Module M1.2: Establish an economic dispatch model for isolated AC microgrids.

[0162] The module M1.1 comprises:

[0163] Module M1.1.1: Establishing the frequency droop control equation ω i (t) = ω ni (t)-m i P i (t) and the voltage droop control equation v oi (t) = V ni(t)-k i Q i (t);

[0164] Among them, ω i (t),ω ni (t) represent the output angular frequency and primary control reference angular frequency of the i-th distributed generator, respectively;

[0165] v oi (t), V ni (t) represent the output voltage amplitude and primary control reference voltage amplitude of the i-th distributed generator, respectively;

[0166] P i (t), Q i (t) represent the active power and reactive power output by the i-th distributed generator respectively;

[0167] m i , k i They represent the active power droop coefficient and reactive power droop coefficient of the i-th distributed generator respectively;

[0168] t represents time;

[0169] Module M1.1.2: Coordinate transformation to obtain the improved voltage droop control equation v odi (t) = V ni (t)-k i Q i (t) and v oqi (t) = 0;

[0170] Among them, v odi (t), v oqi (t) respectively represent the output voltage amplitude v oi The direct axis part and the cross axis part of (t),

[0171]

[0172] Module M1.1.3: Construct frequency dynamic equations and voltage dynamic equations of distributed generators:

[0173]

[0174]

[0175] in, Respectively represent ω i (t),ω ni (t), P i The first derivative of (t);

[0176] Respectively represent vodi (t), V ni (t), Q i The first derivative of (t);

[0177] u ωi (t),u vi (t),u pi (t) represent the secondary control input signals of frequency recovery, voltage recovery and optimal power allocation respectively;

[0178] Indicates the cutoff frequency of the low-pass filter;

[0179] i odi (t), i oqi (t) respectively represent the output current amplitude i oi The direct axis part and the cross axis part of (t),

[0180]

[0181] Module M1.1.4: Calculation of primary control reference angular frequency ω ni (t) and the primary control reference voltage amplitude V ni (t);

[0182]

[0183]

[0184] The module M1.2 includes:

[0185] Module M1.2.1: Constructing the power generation cost function model C i (P i (t)) = a i (P i (t)) 2 +c i P i (t)+γ i ;

[0186] Among them, C i (P i (t)) is the power generation cost function of the i-th distributed generator;

[0187] a i 、c i , γ i Denote the three generation cost coefficients of the i-th distributed generator.

[0188] Module M1.2.2: Constructing an economic dispatch model for microgrids:

[0189]

[0190] Where C(P(t)) represents the total power generation cost of the microgrid system;

[0191] P i (t0) represents the initial active power output by the i-th distributed generator;

[0192] t0 represents the initial time;

[0193] n means there are n distributed generators in total;

[0194] P D Represents the total active power of the microgrid system load;

[0195] P min_i , P max_i They respectively represent the minimum active power and maximum active power that the i-th distributed generator can output.

[0196] Preferably, module M2 comprises:

[0197] Module M2.1: The real state of distributed generators x i (t) is divided into two sub-states

[0198] in, Represents two decomposition coefficients.

[0199] Module M2.2: Establish the frequency and voltage dynamic equations of distributed generators after encryption:

[0200]

[0201] in, Represents ω i (t) has two sub-states, Respectively The first derivative of ;

[0202] Indicates v odi (t) has two sub-states, Respectively The first derivative of ;

[0203] Indicates P i (t) has two sub-states, Respectively The first derivative of ;

[0204] Indicates u ωi Two sub-states of (t);

[0205] Indicates u vi Two sub-states of (t);

[0206] Indicates u pi (t) has two sub-states.

[0207] Preferably, module M3 comprises:

[0208] Module M3.1: Building a dynamic event-triggered consistency controller for voltage and frequency recovery:

[0209] Frequency Restoration Controller

[0210] Voltage Controller

[0211]

[0212] Among them, c g represents the control gain coefficient;

[0213] a ij The weighted adjacency matrix A represents the communication topology of the isolated AC microgrid. ij ), if the i-th distributed generator can receive information from the j-th distributed generator, then a ij =1, if not, then a ij =0;

[0214] b i represents the gain coefficient. If the i-th distributed generator can obtain the reference value information, then b i =1, if not, then b i =0;

[0215] is the gain coefficient between the two sub-states of the i-th distributed generator;

[0216] ω nom 、v nom Respectively represent frequency and voltage ratings;

[0217] Indicates the frequency sub-state of the i-th generator The estimated status of

[0218] Indicates the frequency sub-state of the i-th generator The estimated status of

[0219] Represents the voltage sub-state of the i-th generator The estimated status of

[0220] Represents the voltage sub-state of the i-th generator The estimated status of

[0221] Indicates the frequency sub-state of the jth generator The estimated status of

[0222] Indicates the voltage sub-state of the jth generator The estimated status of

[0223] Respectively represent the frequency sub-state of the i-th generator In the kth α The trigger state and frequency sub-state of each trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…;

[0224] Represent the voltage sub-state of the i-th generator In the kth α The trigger state and voltage sub-state at the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,….

[0225] Module M3.2: Construct trigger functions for updating frequency and voltage sub-states:

[0226]

[0227] in, represents the local measurement error, ξ∈(ω,v);

[0228] represents the tracking error;

[0229] represents the consistency error;

[0230] μ ξi ,θ ξi , π ξi is a constant greater than 0;

[0231] Indicates the kth frequency or voltage update of the i-th generator i +1 trigger moment, k i =0,1,2,…;

[0232] Indicates the kth frequency or voltage update of the i-th generator i A trigger moment;

[0233] d ξi (t) is the internal adaptive dynamic variable;

[0234] The internal adaptive dynamic variable d ξi (t) Satisfaction

[0235] Among them, l ξ1 , l ξ2 , d ξi (0) are all constants greater than 0;

[0236] Indicates d ξi The first derivative of (t).

[0237] Preferably, module M4 comprises:

[0238] Module M4.1: Calculate incremental costs for distributed generators Substates:

[0239]

[0240] in, Denotes the incremental cost λ i Two sub-states of (t);

[0241] Represents C i (P i (t)) has two sub-states.

[0242] Module M4.2: Building a dynamic event-triggered consistency controller for optimal active power distribution:

[0243]

[0244]

[0245] Among them, c v is the control gain coefficient;

[0246] Represents the incremental cost sub-state of the i-th generator The estimated status of

[0247] Represents the incremental cost sub-state of the i-th generator The estimated status of

[0248] Represents the incremental cost sub-state of the i-th generator In the kth α The trigger state and cost sub-state of the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…;

[0249] Indicates P i (t0) has two sub-states.

[0250] Module M4.3: Construct a trigger function for updating the incremental cost sub-state:

[0251]

[0252] in, Indicates sub-state Column vector of ;

[0253] Indicates estimated state Column vector of ;

[0254] Indicates the active power sub-state Column vector of ;

[0255] represents the local measurement error;

[0256] represents the tracking error;

[0257] represents the consistency error;

[0258] μ λi ,θ λi , π λi All are constants greater than 0;

[0259] d λi (t) is the internal adaptive dynamic variable;

[0260] The internal adaptive dynamic variable d λi (t) Satisfaction

[0261] Among them, l λ1 , l λ2 , d λi (0) are all constants greater than 0;

[0262] Indicates d λi The first derivative of (t).

[0263] Module M4.4: Solving Economic Dispatch Models:

[0264]

[0265] Among them, λ ★ represents the optimal incremental cost considering both the power balance constraint and the generation capacity constraint;

[0266]

[0267] Where Φ represents the set of distributed generators whose optimal output power violates the generation capacity constraint;

[0268] λ * represents the optimal incremental cost when only the power balance constraint is considered.

[0269] Module M4.5: Build two auxiliary controllers to achieve optimal active power distribution;

[0270] Module M4.6: Update ψ i (t),δ i (t) Two estimated states of the substate:

[0271]

[0272] in, represents the local measurement error;

[0273] represents the consistency error;

[0274] μ δi ,θ δi , π δi All represent constants greater than 0;

[0275] and d δi (t) is the internal adaptive dynamic variable;

[0276] l δ1 , l δ2 , d δi (0) are all constants greater than 0;

[0277] Respectively d δi The first derivative of (t).

[0278] In the module M4.5, two auxiliary variables ψ are introduced i (t) and δi (t),

[0279]

[0280] Two auxiliary controllers are constructed to achieve the optimal active power allocation under power generation constraints:

[0281]

[0282] in, Indicates sub-state Column vector of ; Indicates sub-state Column vector of ;

[0283] Indicates estimated state Column vector of ;

[0284] Indicates estimated state Column vector of ;

[0285]

[0286] c ψ 、c δ represents the control gain coefficient;

[0287] Represents ψ i Two sub-states of (t);

[0288] Represents δ i Two sub-states of (t);

[0289] express The estimated status of

[0290] express The estimated status of

[0291] express The estimated status of

[0292] express The estimated status of

[0293] Represents sub-states In the kth α The trigger state and sub-state of the trigger moment In the kth β The trigger state at the trigger moment, k α , kβ =0,1,2,…;

[0294] Represents sub-states In the kth α The trigger state and sub-state of the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,….

[0295] In the module M5, the primary control block diagram of the distributed generator includes five parts: a power calculation module, a low-pass filter, a droop controller and a voltage and current controller.

[0296] The main circuit of the distributed generator includes a VSC inverter, an LC filter and an LC output connection unit.

[0297] The control input signal generated by the optimal power distribution controller The control input signal generated by the frequency recovery controller Superposition, the primary control reference angular frequency ω is obtained through the integrator ni (t), generate PWM signal according to voltage and current double closed-loop control, and solve the final optimal output active power by controlling the switch of the inverter

[0298] Among them, P i * represents the optimal active power of the i-th generator.

[0299] Compared with the prior art, the present invention has the following beneficial effects:

[0300] 1. The present invention designs a secondary controller through the frequency-voltage dynamics model of distributed generators and the economic dispatch model of microgrids, which can maintain voltage and frequency stability and achieve optimal economic operation.

[0301] 2. The present invention designs a controller based on a dynamic event trigger mechanism, which has a small communication burden and a fast convergence speed, and can achieve precise consistency.

[0302] 3. The present invention protects privacy information by reducing the number of real-time state transmissions and the state decomposition mechanism, thereby solving the problem of privacy protection information when there is an external attack. BRIEF DESCRIPTION OF THE DRAWINGS

[0303] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0304] Figure 1Schematic diagram of the isolated AC microgrid system.

[0305] Figure 2 Schematic diagram of the primary control block diagram of a distributed generator.

[0306] Figure 3 Schematic diagram of the distributed quadratic privacy protection method for microgrids.

[0307] Figure 4 Schematic diagram of secondary voltage frequency recovery and optimal power allocation control block diagram of distributed generators. DETAILED DESCRIPTION

[0308] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0309] According to the present invention, a distributed secondary privacy protection control method for an isolated AC microgrid includes the following steps:

[0310] Step S1: Establish a dynamic model of distributed generators and an economic dispatch model of microgrids.

[0311] Step S1.1: Establish the dynamic model of distributed generators. Figure 1 For example, an islanded AC microgrid includes multiple distributed generators.

[0312] by Figure 2 For example, the primary control block diagram of the distributed generator includes five parts: power calculation module, low-pass filter, droop controller and voltage and current controller. The main circuit includes VSC inverter, LC filter and LC output connection unit.

[0313] Step S1.1.1: Droop control is used to adjust the frequency and voltage of the island AC microgrid system in the present invention. For the i-th distributed generator, the droop control equations of its frequency and voltage are established:

[0314] ω i (t) = ω ni (t)-m i P i (t) (1)

[0315] v oi (t) = V ni (t)-k i Q i (t)(2)

[0316] Among them, ωi (t),ω ni (t) represent the output angular frequency and primary control reference angular frequency of the i-th distributed generator, respectively;

[0317] v oi (t), V ni (t) represent the output voltage amplitude and primary control reference voltage amplitude of the i-th distributed generator, respectively;

[0318] P i (t), Q i (t) represent the active power and reactive power output by the i-th distributed generator respectively;

[0319] m i , k i They represent the active power droop coefficient and reactive power droop coefficient of the i-th distributed generator respectively;

[0320] t represents the current time.

[0321] Step S1.1.2: Perform ABC to dqO coordinate transformation on formula (2) to obtain the improved voltage droop control equation:

[0322] v odi (t) = V ni (t)-k i Q i (t)(3)

[0323] v oqi (t)=0 (4)

[0324] Among them, v odi (t), v oqi (t) respectively represent the output voltage amplitude v oi The direct axis part and the cross axis part of (t) satisfy

[0325] Step S1.1.3: According to formula (1) and formula (3), establish the frequency and voltage dynamic equations of the distributed generator:

[0326]

[0327] in, Respectively represent ω i (t),ω ni (t), P i The first derivative of (t);

[0328] Respectively represent v odi (t), V ni (t), Q iThe first derivative of (t);

[0329] u ωi (t),u vi (t),u pi (t) represent the secondary control input signals of frequency recovery, voltage recovery and optimal power allocation respectively;

[0330] Indicates the cutoff frequency of the low-pass filter;

[0331] i odi (t), i oqi (t) respectively represent the output current amplitude i oi The direct axis part and the cross axis part of (t) satisfy

[0332] Step S1.1.4: From formulas (5)-(8), the primary control reference angular frequency ω of the i-th distributed generator can be obtained: ni (t) and the primary control reference voltage amplitude V ni (t) is:

[0333]

[0334]

[0335] Step S1.2: Establish an economic dispatch model for the island AC microgrid.

[0336] Step S1.2.1: The microgrid not only needs to maintain voltage and frequency stability, but also needs to achieve optimal economic operation by adjusting active power. For the i-th distributed generator, its power generation cost function model can be expressed as:

[0337] C i (P i (t)) = a i (P i (t)) 2 +c i P i (t)+γ i (11)

[0338] Among them, C i (P i (t)) is the power generation cost function of the i-th distributed generator;

[0339] a i 、c i , γ i Denote the three generation cost coefficients of the i-th distributed generator.

[0340] Step S1.2.2: According to formula (11), establish the economic dispatch model of the microgrid:

[0341]

[0342] P min_i ≤P i ≤P max_i (14)

[0343] Where C(P(t)) represents the total power generation cost of the microgrid system;

[0344] P i (t0) represents the initial active power output by the i-th distributed generator;

[0345] t0 represents the initial time;

[0346] n means there are n distributed generators in total;

[0347] P D Represents the total active power of the microgrid system load;

[0348] P min_i , P max_i They respectively represent the minimum active power and maximum active power that the i-th distributed generator can output.

[0349] Step S2: Based on the privacy protection method of the state decomposition mechanism, the real state of the island AC microgrid is encrypted and protected.

[0350] Specifically, the real state is protected according to the encryption strategy, which is to prevent the initial value of the real state of the microgrid system from being stolen by external attackers.

[0351] Step S2.1: Figure 3 For example, in the privacy protection method, the true state x of each distributed generator i (t) is divided into two sub-states These two sub-states satisfy:

[0352]

[0353] in, Represents two decomposition coefficients.

[0354] Step S2.2: According to formula (15), the frequency and voltage dynamic equations of the distributed generator after encryption are established:

[0355]

[0356] in, Representative i (t) has two sub-states, They are The first derivative of ;

[0357] Represents v odi (t) has two sub-states, They are The first derivative of ;

[0358] Represents P i (t) has two sub-states, They are The first derivative of ;

[0359] Represents u ωi Two sub-states of (t);

[0360] Represents u vi Two sub-states of (t);

[0361] Represents u pi (t) has two sub-states.

[0362] Step S3: Based on the encrypted sub-states, a dynamic event-triggered consistency controller is constructed to achieve voltage and frequency recovery.

[0363] Step S3.1: Figure 4 Take the overall control block diagram of the secondary control of the i-th distributed generator as an example. In order to compensate for the voltage and frequency deviations caused by the primary control, a dynamic event-triggered consistency controller for voltage and frequency recovery is first constructed:

[0364] Frequency Restoration Controller

[0365] Voltage Controller

[0366] Among them, c g represents the control gain coefficient;

[0367] a ij The weighted adjacency matrix A represents the communication topology of the isolated AC microgrid. ij ), if the i-th distributed generator can receive information from the j-th distributed generator, then a ij =1, otherwise a ij =0;

[0368] b i represents the gain coefficient. If the i-th distributed generator can obtain the reference value information, then b i =1, otherwise bi =0;

[0369] is the gain coefficient between the two sub-states of the i-th distributed generator;

[0370] ω nom 、v nom Respectively represent frequency and voltage ratings;

[0371]

[0372] Indicates the frequency sub-state of the i-th generator The estimated status of

[0373] Indicates the frequency sub-state of the i-th generator The estimated status of

[0374] Represents the voltage sub-state of the i-th generator The estimated status of

[0375] Represents the voltage sub-state of the i-th generator The estimated status of

[0376] Indicates the frequency sub-state of the jth generator The estimated status of

[0377] Indicates the voltage sub-state of the jth generator The estimated status of

[0378] Respectively represent the frequency sub-state of the i-th generator In the kth α The trigger state and frequency sub-state of each trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…;

[0379] Represent the voltage sub-state of the i-th generator In the kth α The trigger state and voltage sub-state at the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…, which can be updated by formula (21).

[0380] Step S3.2: In order to reduce the communication burden of the microgrid and reduce the amount of privacy data leakage, a trigger function for updating the frequency and voltage sub-states is constructed according to formulas (21) and (22):

[0381]

[0382] in, represents the local measurement error, ξ∈(ω,v);

[0383] represents the tracking error;

[0384] represents the consistency error;

[0385] μ ξi ,θ ξi , π ξi All are constants greater than 0;

[0386] Indicates the kth frequency or voltage update of the i-th generator i +1 trigger moment, k i =0,1,2,…;

[0387] Indicates the kth frequency or voltage update of the i-th generator i A trigger moment;

[0388] d ξi (t) is an internal adaptive dynamic variable that satisfies the following equation:

[0389]

[0390] Among them, l ξ1 , l ξ2 , d ξi (0) are all constants greater than 0;

[0391] Indicates d ξi The first derivative of (t).

[0392] Step S4: Based on the encrypted sub-states, a dynamic event-triggered consistency controller is constructed to achieve optimal power allocation.

[0393] Specifically, in order to minimize the total generation cost of the microgrid system, the incremental cost of each distributed generator should remain consistent.

[0394] Step S4.1: According to formula (11), the incremental cost sub-state of each distributed generator is obtained:

[0395]

[0396] in, Denotes the incremental cost λ i Two sub-states of (t);

[0397] Represents C i (P i (t)) has two sub-states.

[0398] Step S4.2: Only consider the power balance constraint (13) and ignore the generation capacity constraint (14). According to formula (23), a dynamic event-triggered consistency controller is constructed to achieve optimal useful power allocation:

[0399]

[0400] Among them, c v is the control gain coefficient;

[0401]

[0402] Represents the incremental cost sub-state of the i-th generator The estimated status of

[0403] Represents the incremental cost sub-state of the i-th generator The estimated status of

[0404] Represents the incremental cost sub-state of the i-th generator In the kth α The trigger state and cost sub-state of the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…, which can be updated by formula (25);

[0405] Indicates P i (t0) has two sub-states.

[0406] Step S4.3: Also in order to reduce the communication burden and reduce the amount of privacy data leakage, according to formula (25), a trigger function for updating the incremental cost sub-state is constructed:

[0407]

[0408] in, Indicates sub-state Column vector of ;

[0409] Indicates estimated state Column vector of ;

[0410] Indicates the active power sub-state Column vector of ;

[0411] represents the local measurement error;

[0412] represents the consistency error;

[0413] μ λi ,θ λi , π λi All are constants greater than 0;

[0414] The kth incremental cost update of the i-th generator i +1 trigger moment, k i =0,1,2,…;

[0415] The kth incremental cost update of the i-th generator i A trigger moment;

[0416] d λi (t) is an internal adaptive dynamic variable that satisfies the following equation:

[0417]

[0418] Among them, l λ1 , l λ2 , d λi (0) are all constants greater than 0;

[0419] Indicates d λi The first derivative of (t).

[0420] The transmission state is decomposed into two sub-states, and only one of the sub-states is sent to the neighbor, and the other sub-state serves as an encryption function.

[0421] Step S4.4: Considering the power balance constraint (13) and the generation capacity constraint (14) simultaneously, the solution of the economic dispatch model (12)-(14) is:

[0422]

[0423] Among them, λ ★It represents the optimal incremental cost when considering both the power balance constraint (13) and the generation capacity constraint (14).

[0424] Let Φ represent the set of distributed generators whose optimal output power violates the generation capacity constraint. According to formulas (13), (14) and (27), we can obtain:

[0425]

[0426] Among them, λ * represents the optimal incremental cost when only the power balance constraint (13) is considered.

[0427] Step S4.5: To handle the power generation constraint (14), two auxiliary variables ψ are introduced i (t) and δ i (t), whose initial value satisfies the following conditions:

[0428]

[0429] According to formula (29), two auxiliary controllers are constructed to achieve the optimal active power allocation under power generation constraints:

[0430]

[0431] Among them, c ψ 、c δ represents the control gain coefficient;

[0432] Represents ψ i Two sub-states of (t);

[0433] Represents δ i Two sub-states of (t);

[0434] Indicates sub-state Column vector of ;

[0435] Indicates sub-state Column vector of ;

[0436] Indicates estimated state Column vector of ;

[0437] Indicates estimated state Column vector of ;

[0438]

[0439] express The estimated status of

[0440] express The estimated status of

[0441] express The estimated status of

[0442] express The estimated status of

[0443] Represents sub-states In the kth α The trigger state and sub-state of the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…;

[0444] Represents sub-states In the kth α The trigger state and sub-state of the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…, which can be updated according to formulas (32) and (33).

[0445] Step S4.6: Update ψ i (t),δ i (t) Two estimated states of the substate:

[0446]

[0447] in, represents the local measurement error;

[0448] represents the consistency error;

[0449] μ δi ,θ δi , π δi All represent constants greater than 0;

[0450] and d δi (t) is an internal adaptive dynamic variable that satisfies the following equation:

[0451]

[0452] in, l δ1 , l δ2 , d δi (0) are all constants greater than 0;

[0453] Respectively d δi The first derivative of (t).

[0454] Step S5: According to formulas (27)-(35), the optimal output active power under the simultaneous existence of power balance constraint (13) and power generation capacity constraint (14) can be finally obtained as;

[0455]

[0456] Among them, P i * represents the optimal active power of the i-th generator.

[0457] The control input signal generated by the optimal power allocation controller (24) is The control input signal generated by the frequency recovery controller (19) Superposition, the primary control reference angular frequency ω is obtained through the integrator ni (t), thereby changing the output angular frequency, and generating a PWM signal according to the voltage and current double closed-loop control, and finally achieving the goals of frequency recovery and optimal power distribution at the same time by controlling the switching of the inverter. Once the frequency recovery controller (19) loses stability or fails to restore the frequency to the rated value, the optimal power distribution cannot be achieved.

[0458] The state decomposition method adopted by the present invention only requires simple addition and subtraction operations on the transmission state, and still only allows one sub-state to be transmitted, so the computational burden is relatively small; further, a dynamic event trigger mechanism is adopted, and the transmission state is sent to the neighbor only when certain conditions are met, thereby further reducing the computational burden and communication burden.

[0459] According to the present invention, a distributed secondary privacy protection control system for an isolated AC microgrid is provided, comprising:

[0460] Module M1: Construct the dynamic model of distributed generators and the economic dispatch model of microgrids;

[0461] Module M2: encrypt and protect the real state of the isolated AC microgrid to obtain the encrypted sub-state;

[0462] Module M3: constructs voltage controller and frequency recovery controller based on the encrypted sub-state;

[0463] Module M4: construct an optimal power allocation controller based on the encrypted sub-states;

[0464] Module M5: The optimal output active power is obtained according to the frequency recovery controller and the optimal power allocation controller, and the voltage controller adjusts the voltage.

[0465] In more preferred embodiments, the island AC microgrid in module M1 includes a distributed generator;

[0466] The module M1 comprises:

[0467] Module M1.1: Establish the dynamic model of distributed generators;

[0468] Module M1.2: Establish an economic dispatch model for isolated AC microgrids.

[0469] The module M1.1 comprises:

[0470] Module M1.1.1: Establishing the frequency droop control equation ω i (t) = ω ni (t)-m i P i (t) and the voltage droop control equation v oi (t) = V ni (t)-k i Q i (t);

[0471] Among them, ω i (t),ω ni (t) represent the output angular frequency and primary control reference angular frequency of the i-th distributed generator, respectively;

[0472] v oi (t), V ni (t) represent the output voltage amplitude and primary control reference voltage amplitude of the i-th distributed generator, respectively;

[0473] P i (t), Q i (t) represent the active power and reactive power output by the i-th distributed generator respectively;

[0474] m i , k i They represent the active power droop coefficient and reactive power droop coefficient of the i-th distributed generator respectively;

[0475] t represents time;

[0476] Module M1.1.2: Coordinate transformation to obtain the improved voltage droop control equation v odi (t) = V ni (t)-ki Q i (t) and v oqi (t) = 0;

[0477] Among them, v odi (t), v oqi (t) respectively represent the output voltage amplitude v oi The direct axis part and the cross axis part of (t),

[0478] Module M1.1.3: Construct frequency dynamic equations and voltage dynamic equations of distributed generators:

[0479]

[0480] in, Respectively represent ω i (t),ω ni (t), P i The first derivative of (t);

[0481] Respectively represent v odi (t), V ni (t), Q i The first derivative of (t);

[0482] u ωi (t),u vi (t),u pi (t) represent the secondary control input signals of frequency recovery, voltage recovery and optimal power allocation respectively;

[0483] Indicates the cutoff frequency of the low-pass filter;

[0484] i odi (t), i oqi (t) respectively represent the output current amplitude i oi The direct axis part and the cross axis part of (t),

[0485]

[0486] Module M1.1.4: Calculation of primary control reference angular frequency ω ni (t) and the primary control reference voltage amplitude V ni (t);

[0487]

[0488]

[0489] The module M1.2 includes:

[0490] Module M1.2.1: Constructing the power generation cost function model C i (P i (t)) = a i (P i (t)) 2 +c i P i (t)+γ i ;

[0491] Among them, C i (P i (t)) is the power generation cost function of the i-th distributed generator;

[0492] a i 、c i , γ i Denote the three generation cost coefficients of the i-th distributed generator.

[0493] Module M1.2.2: Constructing an economic dispatch model for microgrids:

[0494]

[0495] P min_i ≤P i ≤P max_i ;

[0496] Where C(P(t)) represents the total power generation cost of the microgrid system;

[0497] P i (t0) represents the initial active power output by the i-th distributed generator;

[0498] t0 represents the initial time;

[0499] n means there are n distributed generators in total;

[0500] P D Represents the total active power of the microgrid system load;

[0501] P min_i , P max_i They respectively represent the minimum active power and maximum active power that the i-th distributed generator can output.

[0502] In more preferred embodiments, module M2 includes:

[0503] Module M2.1: The real state of distributed generators x i (t) is divided into two sub-states

[0504] in, Represents two decomposition coefficients.

[0505] Module M2.2: Establish the frequency and voltage dynamic equations of distributed generators after encryption:

[0506]

[0507]

[0508] in, Represents ω i (t) has two sub-states, Respectively The first derivative of ;

[0509] Indicates v odi (t) has two sub-states, Respectively The first derivative of ;

[0510] Indicates P i (t) has two sub-states, Respectively The first derivative of ;

[0511] Indicates u ωi Two sub-states of (t);

[0512] Indicates u vi Two sub-states of (t);

[0513] Indicates u pi (t) has two sub-states.

[0514] In more preferred embodiments, module M3 includes:

[0515] Module M3.1: Building a dynamic event-triggered consistency controller for voltage and frequency recovery:

[0516] Frequency Restoration Controller

[0517] Voltage Controller

[0518]

[0519] Among them, c g represents the control gain coefficient;

[0520] a ij The weighted adjacency matrix A represents the communication topology of the isolated AC microgrid. ij), if the i-th distributed generator can receive information from the j-th distributed generator, then a ij =1, if not, then a ij =0;

[0521] b i represents the gain coefficient. If the i-th distributed generator can obtain the reference value information, then b i =1, if not, then b i =0;

[0522] is the gain coefficient between the two sub-states of the i-th distributed generator;

[0523] ω nom 、v nom Respectively represent frequency and voltage ratings;

[0524] Indicates the frequency sub-state of the i-th generator The estimated status of

[0525] Indicates the frequency sub-state of the i-th generator The estimated status of

[0526] Represents the voltage sub-state of the i-th generator The estimated status of

[0527] Represents the voltage sub-state of the i-th generator The estimated status of

[0528] Indicates the frequency sub-state of the jth generator The estimated status of

[0529] Indicates the voltage sub-state of the jth generator The estimated status of

[0530] Respectively represent the frequency sub-state of the i-th generator In the kth α The trigger state and frequency sub-state of each trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…;

[0531] Represent the voltage sub-state of the i-th generator In the kth αThe trigger state and voltage sub-state at the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,….

[0532] Module M3.2: Construct trigger functions for updating frequency and voltage sub-states:

[0533]

[0534] in, represents the local measurement error, ξ∈(ω,v);

[0535] represents the tracking error;

[0536] represents the consistency error;

[0537] μ ξi ,θ ξi , π ξi is a constant greater than 0;

[0538] Indicates the kth frequency or voltage update of the i-th generator i +1 trigger moment, k i =0,1,2,…;

[0539] Indicates the kth frequency or voltage update of the i-th generator i A trigger moment;

[0540] d ξi (t) is the internal adaptive dynamic variable;

[0541] The internal adaptive dynamic variable d ξi (t) Satisfaction

[0542] Among them, l ξ1 , l ξ2 , d ξi (0) are all constants greater than 0;

[0543] Indicates d ξi The first derivative of (t).

[0544] In more preferred embodiments, module M4 includes:

[0545] Module M4.1: Calculate incremental costs for distributed generators Substates:

[0546]

[0547] in, Denotes the incremental cost λ i Two sub-states of (t);

[0548] Represents C i (P i (t)) has two sub-states.

[0549] Module M4.2: Building a dynamic event-triggered consistency controller for optimal active power distribution:

[0550]

[0551]

[0552] Among them, c v is the control gain coefficient;

[0553] Represents the incremental cost sub-state of the i-th generator The estimated status of

[0554] Represents the incremental cost sub-state of the i-th generator The estimated status of

[0555] Represents the incremental cost sub-state of the i-th generator In the kth α The trigger state and cost sub-state of the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…;

[0556] Indicates P i (t0) has two sub-states.

[0557] Module M4.3: Construct a trigger function for updating the incremental cost sub-state:

[0558]

[0559] in, Indicates sub-state Column vector of ;

[0560] Indicates estimated state Column vector of ;

[0561] Indicates the active power sub-state Column vector of ;

[0562] represents the local measurement error;

[0563] represents the tracking error;

[0564] represents the consistency error;

[0565] μ λi ,θ λi , π λi All are constants greater than 0;

[0566] d λi (t) is the internal adaptive dynamic variable;

[0567] The internal adaptive dynamic variable d λi (t) Satisfaction

[0568] Among them, l λ1 , l λ2 , d λi (0) are all constants greater than 0;

[0569] Indicates d λi The first derivative of (t).

[0570] Module M4.4: Solving Economic Dispatch Models:

[0571]

[0572] Among them, λ ★ represents the optimal incremental cost considering both the power balance constraint and the generation capacity constraint;

[0573]

[0574] Where Φ represents the set of distributed generators whose optimal output power violates the generation capacity constraint;

[0575] λ * represents the optimal incremental cost when only the power balance constraint is considered.

[0576] Module M4.5: Build two auxiliary controllers to achieve optimal active power distribution;

[0577] Module M4.6: Update ψ i (t),δ i (t) Two estimated states of the substate:

[0578]

[0579]

[0580] in, represents the local measurement error;

[0581] represents the consistency error; μ δi ,θ δi , π δi All represent constants greater than 0;

[0582] is an internal adaptive dynamic variable;

[0583] l δ1 , l δ2 , d δi (0) are all constants greater than 0;

[0584] Respectively d δi The first derivative of (t).

[0585] In the module M4.5, two auxiliary variables ψ are introduced i (t) and δ i (t),

[0586]

[0587] Two auxiliary controllers are constructed to achieve the optimal active power allocation under power generation constraints:

[0588]

[0589]

[0590] in, Indicates sub-state Column vector of ;

[0591] Indicates sub-state Column vector of ;

[0592] Indicates estimated state Column vector of ;

[0593] Indicates estimated state Column vector of ;

[0594]

[0595] c ψ 、c δ represents the control gain coefficient;

[0596] Represents ψ i Two sub-states of (t);

[0597] Represents δ i Two sub-states of (t);

[0598] express The estimated status of

[0599] express The estimated status of

[0600] express The estimated status of

[0601] express The estimated status of

[0602] Represents sub-states In the kth α The trigger state and sub-state of the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…;

[0603] Represents sub-states In the kth α The trigger state and sub-state of the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,….

[0604] In the module M5, the primary control block diagram of the distributed generator includes five parts: a power calculation module, a low-pass filter, a droop controller and a voltage and current controller.

[0605] The main circuit of the distributed generator includes a VSC inverter, an LC filter and an LC output connection unit.

[0606] The control input signal generated by the optimal power distribution controller The control input signal generated by the frequency recovery controller Superposition, the primary control reference angular frequency ω is obtained through the integrator ni (t), generate PWM signal according to voltage and current double closed-loop control, and solve the final optimal output active power by controlling the switch of the inverter

[0607] Among them, P i * represents the optimal active power of the i-th generator.

[0608] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A distributed secondary privacy protection control method for an isolated AC microgrid, characterized in that: include: Step S1: construct a dynamic model of distributed generators and an economic dispatch model of microgrids; Step S2: Encrypt and protect the real state of the isolated AC microgrid to obtain an encrypted sub-state; Step S3: constructing a voltage controller and a frequency recovery controller based on the encrypted sub-state; Step S4: constructing an optimal power distribution controller based on the encrypted sub-states; Step S5: The optimal output active power is obtained according to the frequency recovery controller and the optimal power allocation controller, and the voltage controller adjusts the voltage.

2. The distributed secondary privacy protection control method for isolated island AC microgrid according to claim 1 is characterized in that: The island AC microgrid in step S1 includes a distributed generator; The step S1 comprises: Step S1.1: construct a dynamic model of distributed generators; Step S1.2: construct an economic dispatch model for the island AC microgrid; The step S1.1 comprises: Step S1.1.1: Construct the droop control equation for frequency ω i (t) = ω ni (t)-m i P i (t) and the voltage droop control equation v oi (t) = V ni (t)-k i Q i (t); Among them, ω i (t),ω ni (t) represent the output angular frequency and primary control reference angular frequency of the i-th distributed generator, respectively; v oi (t), V ni (t) represent the output voltage amplitude and primary control reference voltage amplitude of the i-th distributed generator, respectively; P i (t), Q i (t) represent the active power and reactive power output by the i-th distributed generator respectively; m i , k i They represent the active power droop coefficient and reactive power droop coefficient of the i-th distributed generator respectively; t represents time; Step S1.1.2: Coordinate transformation to obtain the improved voltage droop control equation v odi (t) = V ni (t)-k i Q i (t) and v oqi (t) = 0; Among them, v odi (t), v oqi (t) respectively represent the output voltage amplitude v oi The direct axis part and the cross axis part of (t), Step S1.1.3: Construct the frequency dynamic equation and voltage dynamic equation of the distributed generator: in, Respectively represent ω i (t),ω ni (t), P i The first derivative of (t); Respectively represent v odi (t), V ni (t), Q i The first derivative of (t); u ωi (t),u vi (t),u pi (t) represent the secondary control input signals of frequency recovery, voltage recovery and optimal power allocation respectively; Indicates the cutoff frequency of the low-pass filter; i odi (t), i oqi (t) respectively represent the output current amplitude i oi The direct axis part and the cross axis part of (t), Step S1.1.4: Calculate the primary control reference angular frequency ω ni (t) and the primary control reference voltage amplitude V ni (t); ω ni (t)=∫(u ωi (t)+m i u pi (t))dt; The step S1.2 comprises: Step S1.2.1: Construct the power generation cost function model C i (P i (t)) = a i (P i (t)) 2 +c i P i (t)+γ i ; Among them, C i (P i (t)) is the power generation cost function of the i-th distributed generator; a i 、c i , γ i represents the three generation cost coefficients of the i-th distributed generator; Step S1.2.2: Construct the economic dispatch model of the microgrid: P min_i ≤P i ≤P max_i ; Where C(P(t)) represents the total power generation cost of the microgrid system; P i (t0) represents the initial active power output by the i-th distributed generator; t0 represents the initial time; n means there are n distributed generators in total; P D Represents the total active power of the microgrid system load; P min_i , P max_i They respectively represent the minimum active power and maximum active power that the i-th distributed generator can output.

3. The distributed secondary privacy protection control method for isolated island AC microgrid according to claim 1 is characterized in that: Step S2 includes: Step S2.1: The real state x of the distributed generator i (t) is divided into two sub-states and in, represents two decomposition coefficients; Step S2.2: Construct the encrypted frequency and voltage dynamic equations of distributed generators: in, and Represents ω i (t) has two sub-states, Respectively The first derivative of ; and Indicates v odi (t) has two sub-states, Respectively The first derivative of ; P i α (t) and P i β (t) represents P i (t) has two sub-states, Respectively represent P i α (t), P i β The first derivative of (t); and Indicates u ωi Two sub-states of (t); and Indicates u vi Two sub-states of (t); and Indicates u pi (t) has two sub-states.

4. The distributed secondary privacy protection control method for isolated island AC microgrid according to claim 1 is characterized in that: Step S3 includes: Step S3.1: Build a dynamic event-triggered consistency controller for voltage and frequency recovery: Frequency Restoration Controller Voltage Controller Among them, c g represents the control gain coefficient; a ij The weighted adjacency matrix A represents the communication topology of the isolated AC microgrid. ij ), if the i-th distributed generator can receive information from the j-th distributed generator, then a ij =1, if not, then a ij =0; b i represents the gain coefficient. If the i-th distributed generator can obtain the reference value information, then b i =1, if not, then b i =0; and is the gain coefficient between the two sub-states of the i-th distributed generator; ω nom 、v nom Respectively represent frequency and voltage ratings; Indicates the frequency sub-state of the i-th generator The estimated status of Indicates the frequency sub-state of the i-th generator The estimated status of Represents the voltage sub-state of the i-th generator The estimated status of Represents the voltage sub-state of the i-th generator The estimated status of Indicates the frequency sub-state of the jth generator The estimated status of Indicates the voltage sub-state of the jth generator The estimated status of Respectively represent the frequency sub-state of the i-th generator In the kth α The trigger state and frequency sub-state of each trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…; Represent the voltage sub-state of the i-th generator In the kth α The trigger state and voltage sub-state at the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…; Step S3.2: Construct a trigger function for updating the frequency and voltage sub-states: in, represents the local measurement error, ξ∈(ω,v); represents the tracking error; represents the consistency error; μ ξi ,θ ξi , π ξi is a constant greater than 0; Indicates the kth frequency or voltage update of the i-th generator i +1 trigger moment, k i =0,1,2,…; Indicates the kth frequency or voltage update of the i-th generator i A trigger moment; d ξi (t) is the internal adaptive dynamic variable; The internal adaptive dynamic variable d ξi (t) Satisfaction Among them, l ξ1 , l ξ2 , d ξi (0) are all constants greater than 0; Indicates d ξi The first derivative of (t).

5. The distributed secondary privacy protection control method for isolated island AC microgrid according to claim 1 is characterized in that: The step S4 comprises: Step S4.1: Calculate the incremental cost sub-state of the distributed generators: in, Denotes the incremental cost λ i Two sub-states of (t); C i (P i α (t))、C i (P i β (t)) indicates C i (P i (t)) two sub-states; Step S4.2: Construct a dynamic event-triggered consistency controller for optimal active power distribution: Among them, c v is the control gain coefficient; Represents the incremental cost sub-state of the i-th generator The estimated status of Represents the incremental cost sub-state of the i-th generator The estimated status of Represents the incremental cost sub-state of the i-th generator In the kth α The trigger state and cost sub-state of the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…; P i α (t0) and P i β (t0) represents P i Two sub-states of (t0); Step S4.3: Construct a trigger function for updating the incremental cost sub-state: in, Indicates sub-state and Column vector of ; Indicates estimated state and Column vector of ; Indicates the active power sub-state P i α (t) and P i β (t) is a column vector; represents the local measurement error; represents the tracking error; represents the consistency error; μ λi ,θ λi , π λi All are constants greater than 0; d λi (t) is the internal adaptive dynamic variable; The internal adaptive dynamic variable d λi (t) Satisfaction Among them, l λ1 , l λ2 , d λi (0) are all constants greater than 0; Indicates d λi The first derivative of (t); Step S4.4: Solve the economic dispatch model: Among them, λ ★ represents the optimal incremental cost considering both the power balance constraint and the generation capacity constraint; Where Φ represents the set of distributed generators whose optimal output power violates the generation capacity constraint; λ * represents the optimal incremental cost when only the power balance constraint is considered; Step S4.5: construct two auxiliary controllers to achieve optimal active power distribution; Step S4.6: Update ψ i (t),δ i (t) Two estimated states of the substate: in, and represents the local measurement error; and represents the consistency error; μ δi ,θ δi , π δi All represent constants greater than 0; and d δi (t) is the internal adaptive dynamic variable; l δ1 , l δ2 , d δi (0) are all constants greater than 0; Respectively d δi The first derivative of (t); In step S4.5, two auxiliary variables ψ are introduced i (t) and δ i (t), Two auxiliary controllers are constructed to achieve the optimal active power allocation under power generation constraints: in, Indicates sub-state and Column vector of ; Indicates sub-state and Column vector of ; Indicates estimated state and Column vector of ; Indicates estimated state and Column vector of ; c ψ 、c δ represents the control gain coefficient; and Represents ψ i Two sub-states of (t); and Represents δ i Two sub-states of (t); express The estimated status of express The estimated status of express The estimated status of express The estimated status of Represents sub-states In the kth α The trigger state and sub-state of the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…; Represents sub-states In the kth α The trigger state and sub-state of the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…; In step S5, the primary control block diagram of the distributed generator includes five parts: a power calculation module, a low-pass filter, a droop controller and a voltage and current controller; The main circuit of the distributed generator includes a VSC inverter, an LC filter and an LC output connection unit; The control input signal generated by the optimal power distribution controller and The control input signal generated by the frequency recovery controller and Superposition, the primary control reference angular frequency ω is obtained through the integrator ni (t), generate PWM signal according to voltage and current double closed-loop control, and solve the final optimal output active power by controlling the switch of the inverter Among them, P i * represents the optimal active power of the i-th generator.

6. A distributed secondary privacy protection control system for an isolated AC microgrid, characterized in that: include: Module M1: Construct the dynamic model of distributed generators and the economic dispatch model of microgrids; Module M2: encrypt and protect the real state of the isolated AC microgrid to obtain the encrypted sub-state; Module M3: constructs voltage controller and frequency recovery controller based on the encrypted sub-state; Module M4: construct an optimal power allocation controller based on the encrypted sub-states; Module M5: The optimal output active power is obtained according to the frequency recovery controller and the optimal power allocation controller, and the voltage controller adjusts the voltage.

7. The isolated island AC microgrid distributed secondary privacy protection control system according to claim 6, characterized in that: The island AC microgrid described in module M1 includes a distributed generator; The module M1 comprises: Module M1.1: Establish the dynamic model of distributed generators; Module M1.2: Establish economic dispatch model of isolated AC microgrid; The module M1.1 comprises: Module M1.1.1: Establishing the frequency droop control equation ω i (t) = ω ni (t)-m i P i (t) and the voltage droop control equation v oi (t) = V ni (t)-k i Q i (t); Among them, ω i (t),ω ni (t) represent the output angular frequency and primary control reference angular frequency of the i-th distributed generator, respectively; v oi (t), V ni (t) represent the output voltage amplitude and primary control reference voltage amplitude of the i-th distributed generator, respectively; P i (t), Q i (t) represent the active power and reactive power output by the i-th distributed generator respectively; m i , k i They represent the active power droop coefficient and reactive power droop coefficient of the i-th distributed generator respectively; t represents time; Module M1.1.2: Coordinate transformation to obtain the improved voltage droop control equation v odi (t) = V ni (t)-k i Q i (t) and v oqi (t) = 0; Among them, v odi (t), v oqi (t) respectively represent the output voltage amplitude v oi The direct axis part and the cross axis part of (t), Module M1.1.3: Construct frequency dynamic equations and voltage dynamic equations of distributed generators: in, Respectively represent ω i (t),ω ni (t), P i The first derivative of (t); Respectively represent v odi (t), V ni (t), Q i The first derivative of (t); u ωi (t),u vi (t),u pi (t) represent the secondary control input signals of frequency recovery, voltage recovery and optimal power allocation respectively; ω i c Indicates the cutoff frequency of the low-pass filter; i odi (t), i oqi (t) respectively represent the output current amplitude i oi The direct axis part and the cross axis part of (t), Module M1.1.4: Calculation of primary control reference angular frequency ω ni (t) and the primary control reference voltage amplitude V ni (t); ω ni (t)=∫(u ωi (t)+m i u pi (t))dt; The module M1.2 includes: Module M1.2.1: Constructing the power generation cost function model C i (P i (t)) = a i (P i (t)) 2 +c i P i (t)+γ i ; Among them, C i (P i (t)) is the power generation cost function of the i-th distributed generator; a i 、c i , γ i represents the three generation cost coefficients of the i-th distributed generator; Module M1.2.2: Constructing an economic dispatch model for microgrids: P min_i ≤P i ≤P max_i ; Where C(P(t)) represents the total power generation cost of the microgrid system; P i (t0) represents the initial active power output by the i-th distributed generator; t0 represents the initial time; n means there are n distributed generators in total; P D Represents the total active power of the microgrid system load; P min_i , P max_i They respectively represent the minimum active power and maximum active power that the i-th distributed generator can output.

8. The isolated island AC microgrid distributed secondary privacy protection control system according to claim 6, characterized in that: Module M2 includes: Module M2.1: The real state of distributed generators x i (t) is divided into two sub-states and in, represents two decomposition coefficients; Module M2.2: Establish the frequency and voltage dynamic equations of distributed generators after encryption: in, and Represents ω i (t) has two sub-states, Respectively The first derivative of ; and Indicates v odi (t) has two sub-states, Respectively The first derivative of ; P i α (t) and P i β (t) represents P i (t) has two sub-states, Respectively represent P i α (t), P i β The first derivative of (t); and Indicates u ωi Two sub-states of (t); and Indicates u vi Two sub-states of (t); and Indicates u pi (t) has two sub-states.

9. The isolated island AC microgrid distributed secondary privacy protection control system according to claim 6, characterized in that: Module M3 includes: Module M3.1: Building a dynamic event-triggered consistency controller for voltage and frequency recovery: Frequency Restoration Controller Voltage Controller Among them, c g represents the control gain coefficient; a ij The weighted adjacency matrix A represents the communication topology of the isolated AC microgrid. ij ), if the i-th distributed generator can receive information from the j-th distributed generator, then a ij =1, if not, then a ij =0; b i represents the gain coefficient. If the i-th distributed generator can obtain the reference value information, then b i =1, if not, then b i =0; and is the gain coefficient between the two sub-states of the i-th distributed generator; ω nom 、v nom Respectively represent frequency and voltage ratings; Indicates the frequency sub-state of the i-th generator The estimated status of Indicates the frequency sub-state of the i-th generator The estimated status of Represents the voltage sub-state of the i-th generator The estimated status of Represents the voltage sub-state of the i-th generator The estimated status of Indicates the frequency sub-state of the jth generator The estimated status of Indicates the voltage sub-state of the jth generator The estimated status of Respectively represent the frequency sub-state of the i-th generator In the kth α The trigger state at the trigger moment, the frequency sub-state ω i β (t) at the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…; Respectively represent the voltage sub-state v of the i-th generator i α (t) at the kth α The trigger state at the trigger moment, the voltage sub-state v i β (t) at the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…; Module M3.2: Construct trigger functions for updating frequency and voltage sub-states: in, represents the local measurement error, ξ∈(ω,v); represents the tracking error; represents the consistency error; μ ξi ,θ ξi , π ξi is a constant greater than 0; Indicates the kth frequency or voltage update of the i-th generator i +1 trigger moment, k i =0,1,2,…; Indicates the kth frequency or voltage update of the i-th generator i A trigger moment; d ξi (t) is the internal adaptive dynamic variable; The internal adaptive dynamic variable d ξi (t) Satisfaction Among them, l ξ1 , l ξ2 , d ξi (0) are all constants greater than 0; Indicates d ξi The first derivative of (t).

10. The isolated island AC microgrid distributed secondary privacy protection control system according to claim 6, characterized in that: Module M4 includes: Module M4.1: Calculate incremental costs for distributed generators Substates: in, Denotes the incremental cost λ i Two sub-states of (t); C i (P i α (t))、C i (P i β (t)) indicates C i (P i (t)) two sub-states; Module M4.2: Building a dynamic event-triggered consistency controller for optimal active power distribution: Among them, c v is the control gain coefficient; Represents the incremental cost sub-state of the i-th generator The estimated status of Represents the incremental cost sub-state of the i-th generator The estimated status of Represents the incremental cost sub-state of the i-th generator In the kth α The trigger state and cost sub-state of the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…; P i α (t0) and P i β (t0) represents P i Two sub-states of (t0); Module M4.3: Construct a trigger function for updating the incremental cost sub-state: in, Indicates sub-state and Column vector of ; Indicates estimated state and Column vector of ; Indicates the active power sub-state P i α (t) and P i β (t) is a column vector; represents the local measurement error; represents the tracking error; represents the consistency error; μ λi ,θ λi , π λi All are constants greater than 0; d λi (t) is the internal adaptive dynamic variable; The internal adaptive dynamic variable d λi (t) Satisfaction Among them, l λ1 , l λ2 , d λi (0) are all constants greater than 0; Indicates d λi The first derivative of (t); Module M4.4: Solving Economic Dispatch Models: Among them, λ ＊ represents the optimal incremental cost considering both the power balance constraint and the generation capacity constraint; Where Φ represents the set of distributed generators whose optimal output power violates the generation capacity constraint; λ * represents the optimal incremental cost when only the power balance constraint is considered; Module M4.5: Build two auxiliary controllers to achieve optimal active power distribution; Module M4.6: Update ψ i (t),δ i (t) Two estimated states of the substate: in, and represents the local measurement error; and represents the consistency error; μ δi ,θ δi ,ω δi , π δi All represent constants greater than 0; and d δi (t) is the internal adaptive dynamic variable; l δ1 , l δ2 , d δi (0) are all constants greater than 0; Respectively d δi The first derivative of (t); In the module M4.5, two auxiliary variables ψ are introduced i (t) and δ i (t), Two auxiliary controllers are constructed to achieve the optimal active power allocation under power generation constraints: in, Indicates sub-state and Column vector of ; Indicates sub-state and Column vector of ; Indicates estimated state and Column vector of ; Indicates estimated state and Column vector of ; c ψ 、c δ represents the control gain coefficient; and Represents ψ i Two sub-states of (t); and Represents δ i Two sub-states of (t); express The estimated status of express The estimated status of express The estimated status of express The estimated status of Represents sub-states In the kth α The trigger state and sub-state of the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…; Represents sub-states In the kth α The trigger state and sub-state of the trigger moment In the kth β The trigger state at the trigger moment, k α , k β =0,1,2,…; In the module M5, the primary control block diagram of the distributed generator includes five parts: power calculation module, low-pass filter, droop controller and voltage and current controller; The main circuit of the distributed generator includes a VSC inverter, an LC filter and an LC output connection unit; The control input signal generated by the optimal power distribution controller and The control input signal generated by the frequency recovery controller and Superposition, the primary control reference angular frequency ω is obtained through the integrator ni (t), generate PWM signal according to voltage and current double closed-loop control, and solve the final optimal output active power by controlling the switch of the inverter Among them, P i * represents the optimal active power of the i-th generator.

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