Comprehensive energy system economic model prediction control method with periodic characteristics

Abstract

The invention relates to an economic model predictive control method for an integrated energy system with periodic characteristics, which comprises the following steps of: modeling components of the integrated energy system, defining a state quantity, a continuous control quantity, a discrete control quantity and a disturbance quantity of the integrated energy system, and establishing a state space model of the system; establishing a target function based on the operation of the integrated energy system, and establishing constraint conditions according to the limitation and periodic characteristics of the system operation; and solving a finite time domain constraint optimization problem with periodic characteristics in a rolling optimization manner to obtain an optimal solution meeting the optimal period operation of the integrated energy system, and applying the optimal solution to the control of the integrated energy system. According to the invention, the operation of the integrated energy system is optimized, and load tracking and economic optimization are realized to meet user requirements at any time; for periodic optimal operation of a constraint system, prior calculation of an optimal track is not needed, dynamic real-time optimization and control are carried out in a frame for simultaneous optimization, recursion feasibility is guaranteed, and system output is converged to a new periodic optimal track.

Description

Technical Field

[0001] The present invention relates to the technical field of calculation, extrapolation or counting, and in particular to a prediction and control method of an economic model of an integrated energy system with periodic characteristics. Background Art

[0002] The integrated energy system is an integrated system of production, supply and consumption with the power system as the core, coupling multiple energy subsystems and new energy equipment. Its characteristics of multi-energy complementarity and coordinated optimization are regarded as a key way to reduce carbon emissions and improve energy utilization efficiency.

[0003] The difficulties of predictive control of integrated energy systems are mainly reflected in:

[0004] (1) The system usually contains multiple energy forms. When building the model, it is necessary to consider the uncertainty caused by the external environment. In addition, the coupling relationship between multiple energy forms also increases the complexity of the model;

[0005] (2) The goal of system operation is no longer to focus solely on control performance that meets user needs, but also to take into account the economic performance of system operation, and considering constraints makes solving problems more difficult.

[0006] In fact, for the microgrid off-grid integrated energy system that includes power supply system and cooling system, its operating goal is to meet the time-varying user electricity and temperature demands, while optimizing the economic cost of system operation. In addition, for users of the integrated energy system, their daily behaviors and demands usually do not change suddenly, which results in the user's needs often changing periodically. The system needs to solve this periodic demand and meet the system's periodic economic optimality. Summary of the invention

[0007] The present invention solves the problems existing in the prior art and provides an economic model predictive control (EMPC) method for an integrated energy system with periodic characteristics.

[0008] The technical solution adopted by the present invention is a predictive control method for an economic model of an integrated energy system with periodic characteristics. The method models the components of the integrated energy system, defines the state quantity, continuous control quantity, discrete control quantity and disturbance quantity of the integrated energy system, and establishes a state space model of the system; establishes an objective function based on the operation of the integrated energy system, and establishes constraints according to the limitations and periodic characteristics of the system operation; solves the finite time domain constrained optimization problem with periodic characteristics in a rolling optimization manner, obtains the optimal solution that satisfies the optimal periodic operation of the integrated energy system and applies it to the control of the integrated energy system.

[0009] Preferably, the integrated energy system includes a power supply network and a cooling network; the power supply network includes a photovoltaic power generation device, a fuel cell, a micro-turbine, and a battery, and the output end of the power supply network is an electric refrigerator, a water pump, and a local user; the cooling network includes a chilled water tank that cooperates with the electric refrigerator, the electric refrigerator interacts with the local user through the water pump, and the output end of the chilled water tank is the local user.

[0010] Preferably, the electric power provided to users by the integrated energy system satisfies:

[0011] P sl =P pv +P fc +P ma +P bat -P cp -P pmp

[0012] Among them, P pv is the photovoltaic output power, P fc is the fuel cell output power, P ma is the output power of the micro-turbine, P bat is the battery output power, P cp is the power consumption of the compressor, P pmp is the electrical power of the water pump;

[0013] State variable x = [C soc ,C sot ,t br ] T , C soc is the state of charge of the battery, C sot is the storage status of the chilled water tank, t br is the user's ambient temperature;

[0014] Continuous control variable u=[G fc , G ma , N ec , G stu , P bat ] T , G fc is the mass flow rate of natural gas in the fuel cell, G ma is the natural gas mass flow rate of the micro-turbine, N ec is the compressor frequency of the electric refrigerator, G stu is the absolute value of the water flow in the chilled water tank;

[0015] Discrete control variable z = [z fc , z ma , z ec , z st ] T , z fcis the start and stop state of the fuel cell, z ma is the start and stop state of the micro-turbine, z ec is the start and stop state of the electric refrigerator, z st The switch status of the chilled water storage device;

[0016] Disturbance w = [T a , S, Q other ] T , T a is the ambient temperature, S is the solar irradiance, Q other The cooling load of the user;

[0017] Let the system output y = [P sl , t br ] T , establish the state space model at time k

[0018] x(k+1)=f(x(k),u(k),z(k),w(k))

[0019] y(k)=h(x(k),u(k),z(k),w(k))

[0021] Preferably, the prediction time domain N is set equal to the operation period T, and a finite time domain optimal control problem with periodic characteristics is constructed by combining the prediction model, the objective function and the constraint conditions. The economic MPC method is used to solve the finite time domain optimal control problem with periodic characteristics, and the optimal control sequence of the entire optimization problem is obtained. The optimal control sequence The first element is applied to the system, the latest state is measured, and the rolling optimization solution is repeated.

[0022] Preferably, an objective function is established based on the output tracking performance and economic optimization criteria of the integrated energy system operation to meet

[0023]

[0024] Among them, u k =[u 0|k ,u 1|k ,…u N-1|k ] T ,u i|k represents the predicted value at time k for time k+i, N represents the prediction time domain, a is a weight coefficient greater than zero that reflects the economic performance of the system, and R is a symmetric positive definite weight matrix that reflects the output tracking performance of the system; u 1 and u 2 are the first and second elements of the continuous control variable u, y is the system output, and y sp Given the expected output of the trace.

[0025] Preferably, a constraint set including state constraints, control variable constraints and cycle constraints of the system is established;

[0026] The state constraints are satisfied,

[0027] x min ≤x k ≤x max

[0028] Among them, x min =[C soc,min ,C sot,min ,t br,min ] T is the corresponding lower limit of the state quantity, x max =[C soc,max ,C sot,max ,t br,max ] T is the upper limit of the corresponding state quantity;

[0029] The control variable constraints are satisfied,

[0030] u min ≤u k ≤u max

[0031] Among them, u min =[G fc,min ,G ma,min ,N ec,min ,G stu,min ,P bat,min ] T is the lower limit of the corresponding control quantity, u max =[G fc,max ,G ma,max ,N ec,max ,G stu,max ,P bat,max ] T is the upper limit of the corresponding control amount;

[0032] The period constraint is satisfied,

[0033] y k =y k+T

[0034] Where T is the period of system operation.

[0035] Preferably, the change value of the control quantity at adjacent moments satisfies △u min ≤△u k ≤△u max , where Δu k =u k -u k-1 .

[0036] Preferably, the cycle economic model predictive controller of the integrated energy system is

[0037]

[0038] stx i+1|k =f(x i|k ,u i|k ,z i|k ,w i|k ),i∈I 0:N-1

[0039] x 0|k =x 0 ,x min ≤x k ≤x max

[0040] u min ≤u k ≤u max ,△u min ≤△u k ≤△u max

[0041] y 0|k =y N|k

[0042] Among them, I 0:N-1 Represents an integer in [0, N-1].

[0043] Preferably, the optimal control sequence The first element of is the control law applied to the system, Repeat the optimization run on a rolling basis on the time axis in cycles.

[0044] The present invention relates to a predictive control method for an economic model of an integrated energy system with periodic characteristics. The method comprises the following steps: modeling components of the integrated energy system, defining state quantities, continuous control quantities, discrete control quantities and disturbance quantities of the integrated energy system, and establishing a state space model of the system; establishing an objective function based on the operation of the integrated energy system, and establishing constraint conditions according to the limitations and periodic characteristics of the system operation; solving a finite time domain constraint optimization problem with periodic characteristics in a rolling optimization manner, obtaining an optimal solution that satisfies the optimal periodic operation of the integrated energy system, and applying the solution to the control of the integrated energy system.

[0045] The beneficial effects of the present invention are that the operation of the integrated energy system is optimized, load tracking and economic optimization are achieved simultaneously, and the energy production of the integrated energy system is effectively managed while taking into account economic benefits to meet the needs of users at any time; there is no need to calculate the optimal trajectory a priori for the periodic optimal operation of the constrained integrated energy system, and dynamic real-time optimization and control are optimized simultaneously within a framework, while ensuring recursive feasibility and making the system output converge to a new periodic optimal trajectory. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 is a flow chart of the method of the present invention;

[0047] Figure 2 It is a schematic diagram of the off-grid integrated energy system structure of the power supply system and cooling system of the present invention. DETAILED DESCRIPTION

[0048] The present invention is further described in detail below in conjunction with embodiments, but the protection scope of the present invention is not limited thereto.

[0049] The present invention relates to a predictive control method for an economic model of an integrated energy system with periodic characteristics. The method models components of the integrated energy system, defines state quantities, continuous control quantities, discrete control quantities and disturbance quantities of the integrated energy system, and establishes a state space model of the system; establishes an objective function based on the operation of the integrated energy system, and establishes constraint conditions according to the limitations and periodic characteristics of the system operation; solves a finite time domain constraint optimization problem with periodic characteristics in a rolling optimization manner, obtains an optimal solution that satisfies the optimal periodic operation of the integrated energy system, and applies the optimal solution to the control of the integrated energy system.

[0050] Specifically, the method of the present invention comprises the following steps:

[0051] (1) Establish a state space model of the system;

[0052] (2) Establishing the objective function based on the operation of the integrated energy system;

[0053] (3) Establish constraints;

[0054] (4) Solve the optimization problem with limited time domain constraints and periodic characteristics by rolling optimization;

[0055] (5) Obtain the optimal solution that satisfies the optimal cycle operation of the integrated energy system and apply it to the control of the integrated energy system.

[0056] (1) Establish a state space model of the system;

[0057] The comprehensive energy system includes a power supply network and a cooling network; the power supply network includes a photovoltaic power generation device, a fuel cell, a micro-turbine, and a battery, and the output end of the power supply network is an electric refrigerator, a water pump, and a local user; the cooling network includes a chilled water tank that cooperates with the electric refrigerator, the electric refrigerator interacts with the local user through the water pump, and the output end of the chilled water tank is the local user.

[0058] Firstly, the photovoltaic power generation device, battery, chilled water tank and user temperature are modeled respectively;

[0059] According to historical weather conditions, the ambient temperature and solar irradiance are predicted by combining the LSTM neural network, and the photovoltaic output power is obtained by combining the photovoltaic model, that is,

[0060]

[0061] Among them, P pv (k) is the photovoltaic power generation, S(k) is the solar irradiance, T a (k) is the ambient temperature, P STC is the maximum test power under standard test conditions, S STC is the solar irradiance under standard test conditions, k 1 is the power temperature coefficient, k 2 is the solar irradiance coefficient, T STC is the reference temperature under standard test conditions, and k represents the current moment.

[0062] The dynamic model of the battery is:

[0063]

[0064] Among them, C soc is the state of charge of the battery, η is the battery charge and discharge coefficient, T s is the sampling time, C max is the maximum battery capacity, k represents the current moment, P bat (k) is the power provided by the battery at the current moment, P bat When (k) is positive, the battery discharges P bat When (k) is negative, the battery is charging, and k represents the current time.

[0065] In the integrated energy system, the chilled water tank stores chilled water in the water tank. According to the law of conservation of mass and energy, the dynamics of the chilled water storage device is described as follows:

[0066]

[0067] Among them, C sot is the storage status of the chilled water tank, z st is the switch state of the chilled water storage device, Mst is the maximum mass capacity of the cold water tank, T s is the sampling time, G stu is the absolute value of the water flow in the chilled water tank, and k represents the current moment.

[0068] Dynamic changes in temperature provided to the user br It can be expressed as

[0069]

[0070] Among them, U br is the heat transfer coefficient, T a is the ambient temperature, C br is the heat capacity, T s is the sampling time, k represents the current time; P ma is the output power of the micro-turbine, which satisfies P ma =k ma G ma ;Q ec is the cooling power of the electric refrigerator, which satisfies Q ec =k ec N ec , k ma , k ec , k st is the corresponding conversion factor, Q other The cooling load of the user.

[0071] The electric power provided by the comprehensive energy system to users meets the requirements.

[0072] P sl =P pv +P fc +P ma +P bat -P cp -P pmp (5)

[0073] Among them, P pv is the photovoltaic output power, P fc is the fuel cell output power, P ma is the output power of the micro-turbine, P bat is the battery output power, P cp is the power consumption of the compressor, P pmp is the electrical power of the water pump;

[0074] Among them, P pv is the photovoltaic output power calculated by the photovoltaic model; P fc is the fuel cell output power, which satisfies P fc =k fc G fc , k fcis the conversion factor; P cp is the power consumption of the compressor, which satisfies P cp =k cp N ec ;P pmp is the electrical power of the water pump, which satisfies P pmp =z ec G ec0 +G stu , G ec0 is the chilled water flow constant in the electric refrigerator under nominal conditions.

[0075] The T in the upper right corner of the following vectors indicates transpose.

[0076] State variable x = [C soc ,C sot ,t br ] T , C soc is the state of charge of the battery, C sot is the storage status of the chilled water tank, t br is the user's ambient temperature;

[0077] Continuous control variable u=[G fc , G ma , N ec , G stu , P bat ] T , G fc is the mass flow rate of natural gas in the fuel cell, G ma is the natural gas mass flow rate of the micro-turbine, N ec is the compressor frequency of the electric refrigerator, G stu is the absolute value of the water flow in the chilled water tank;

[0078] Discrete control variable z = [z fc , z ma , z ec , z st ] T , z fc is the start and stop state of the fuel cell, z ma is the start and stop state of the micro-turbine, z ec is the start and stop state of the electric refrigerator, z st The switch status of the chilled water storage device;

[0079] Disturbance w = [t a , S, Q other ] T , T a is the ambient temperature, S is the solar irradiance, Q other The cooling load of the user;

[0080] Let the system output y = [P sl , t br ] T , let x(k) be x k , u(k) is u k , z(k) is z k , w(k) is w k , y(k) is y k , establish the state space model at time k

[0081] x(k+1)=f(x(k),u(k),z(k),w(k))

[0082] y(k)=h(x(k),u(k),z(k),w(k)) (6)

[0084] Set the prediction time domain N equal to the operation period T, combine the prediction model, objective function and constraints to construct a finite time domain optimal control problem with periodic characteristics, use the economic MPC method to solve the finite time domain optimal control problem with periodic characteristics, and obtain the optimal control sequence of the entire optimization problem The optimal control sequence The first element is applied to the system, the latest state is measured, and the rolling optimization solution is repeated.

[0085] In the actual operation of the integrated energy system, its primary goal is to meet the user's electricity demand and provide the user with the corresponding cooling load to meet the user's temperature demand. Secondly, the economic performance of the system operation must be guaranteed. In addition, the system's operating constraints and cycle constraints must be met during the optimization process.

[0086] (2) Establishing the objective function based on the operation of the integrated energy system;

[0087] The objective function is established based on the output tracking performance and economic optimization criteria of the integrated energy system operation to meet

[0088]

[0089] Among them, u k =[u 0|k ,u 1|k ,…u N-1|k ] T ,u i|k represents the predicted value at time k for time k+i, N represents the prediction time domain, a is a weight coefficient greater than zero that reflects the economic performance of the system, and R is a symmetric positive definite weight matrix that reflects the output tracking performance of the system; u 1 and u 2 are the first and second elements of the continuous control variable u, y is the system output, and y spGiven the expected output of the trace.

[0090] Corresponding to the first additional item, the consumption of natural gas reflects the economic performance of the system, that is, the mass flow rate of natural gas corresponding to the fuel cell and the mass flow rate of natural gas corresponding to the micro-turbine;

[0091] Corresponding to the second additional item, during the operation of the integrated energy system, it is necessary to ensure that the output power accurately tracks the user load demand and the temperature meets the comfortable temperature required by the user.

[0092] (3) Establish constraints;

[0093] Establish a constraint set including system state constraints, control variable constraints and cycle constraints;

[0094] In order to reduce the loss of batteries and extend their service life, the SOC level of the batteries is usually limited to the optimal operating range. At the same time, the cold water capacity of the cold water tank should also vary within the allowable load range, and the temperature provided to the user should be within the comfort range. The state constraints are met.

[0095] x min ≤x k ≤x max (8)

[0096] Among them, x min =[C soc,min ,C sot,min ,t br,min ] T is the corresponding lower limit of the state quantity, x max =[C soc,max ,C sot,max ,t br,max ] T is the upper limit of the corresponding state quantity;

[0097] Due to the physical limitations of the actuators and the accuracy of the control, the control variables need to be constrained within a certain range. The control variable constraints are satisfied.

[0098] u min ≤u k ≤u max (9)

[0099] Among them, u min =[G fc,min ,G ma,min ,N ec,min ,G stu,min ,P bat,min ] T is the lower limit of the corresponding control quantity, u max =[G fc,max ,G ma,max ,N ec,max ,Gstu,max ,P bat,max ] T is the upper limit of the corresponding control amount;

[0100] For a system with periodic operation characteristics, in addition to satisfying its inherent state and control constraints, the system should also satisfy the constraints of periodic operation.

[0101] y k =y k+T (11)

[0102] Where T is the period of system operation.

[0103] In order to protect the equipment from extreme operation of components, the change value of the control quantity at adjacent moments should not be too large, and the change value of the control quantity at adjacent moments should meet

[0104] △u min ≤△u k ≤△u max (10)

[0105] Among them, Δu k =u k -u k-1 .

[0106] (4) Solve the optimization problem with limited time domain constraints and periodic characteristics by rolling optimization;

[0107] The predictive controller of the periodic economic model of the integrated energy system is

[0108]

[0109] stx i+1|k =f(x i|k ,u i|k ,z i|k ,w i|k ),i∈I 0:N-1 (12b)

[0110] x 0|k =x 0 ,x min ≤x k ≤x max (12c)

[0111] u min ≤u k ≤u max ,△u min ≤△u k ≤△u max (12d)

[0112] y 0|k =yN|k (12e)

[0113] Among them, constraint (12b) is the system prediction model, I 0:N-1 represents an integer in [0, N-1]; constraint (12c) represents the state initial value and state constraint; constraint (12d) represents the control constraint and control increment constraint; constraint (12e) represents the system period constraint.

[0114] (5) Obtain the optimal solution that satisfies the optimal cycle operation of the integrated energy system and apply it to the control of the integrated energy system;

[0115] Optimal Control Sequence The first element of is the control law applied to the system, Let k=k+1, and repeat the rolling optimization operation on the time axis.

[0116] In order to implement the above-mentioned embodiment, a computer-readable storage medium is proposed, on which a prediction control program for an economic model of an integrated energy system with periodic characteristics is stored. When the prediction control program for an economic model of an integrated energy system with periodic characteristics is executed by a processor, the prediction control method for an economic model of an integrated energy system with periodic characteristics is implemented.

[0117] In order to implement the above-mentioned embodiments, a computer device is also proposed, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the predictive control method for the economic model of the integrated energy system with periodic characteristics as described above is implemented.

[0118] When the present invention is applied to the predictive control of an integrated energy system, especially when the integrated energy system is in off-grid operation, the system needs to continuously adjust the control to meet the user's electricity load demand and cooling load demand, taking into account the uncertainty of renewable energy and the needs of consumers, while making the system operate in a more economical way. Different from the traditional hierarchical method in which the upper layer calculates the economic optimal trajectory and the lower layer tracks the reference trajectory, the present invention combines dynamic real-time optimization and control in a framework for simultaneous optimization, and takes into account periodic characteristics. The proposed controller ensures that the closed loop converges to the optimal periodic trajectory, minimizes the average operating cost of a given economic standard, and does not require a priori calculation of the optimal trajectory.

[0119] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A predictive control method for an economic model of an integrated energy system with periodic characteristics, characterized in that: The method models the components of the integrated energy system, defines the state quantity, continuous control quantity, discrete control quantity and disturbance quantity of the integrated energy system, and establishes a state space model of the system; establishes an objective function based on the operation of the integrated energy system, and establishes constraint conditions according to the limitations and periodic characteristics of the system operation; solves the finite time domain constraint optimization problem with periodic characteristics in a rolling optimization manner, obtains the optimal solution that satisfies the optimal periodic operation of the integrated energy system, and applies it to the control of the integrated energy system.

2. The method for predicting and controlling an economic model of an integrated energy system with periodic characteristics according to claim 1, characterized in that: The comprehensive energy system includes a power supply network and a cooling network; the power supply network includes a photovoltaic power generation device, a fuel cell, a micro-turbine, and a battery, and the output end of the power supply network is an electric refrigerator, a water pump, and a local user; the cooling network includes a chilled water tank that cooperates with the electric refrigerator, the electric refrigerator interacts with the local user through the water pump, and the output end of the chilled water tank is the local user.

3. The method for predicting and controlling an economic model of an integrated energy system with periodic characteristics according to claim 2, characterized in that: The electric power provided by the comprehensive energy system to users meets the requirements. P sl =P pv +P fc +P ma +P bat -P cp -P pmp Among them, P pv is the photovoltaic output power, P fc is the fuel cell output power, P ma is the output power of the micro-turbine, P bat is the battery output power, P cp is the power consumption of the compressor, P pmp is the electrical power of the water pump; State variable x = [C soc ,C sot ,t br ] T , C soc is the state of charge of the battery, C sot is the storage status of the chilled water tank, t br is the user's ambient temperature; Continuous control variable u=[G fc , G ma , N ec , G stu , P bat ] T , G fc is the mass flow rate of natural gas in the fuel cell, G ma is the natural gas mass flow rate of the micro-turbine, N ec is the compressor frequency of the electric refrigerator, G stu is the absolute value of the water flow in the chilled water tank; Discrete control variable z = [z fc , z ma , z ec , z st ] T , z fc is the start and stop state of the fuel cell, z ma is the start and stop state of the micro-turbine, z ec is the start and stop state of the electric refrigerator, z st The switch status of the chilled water storage device; Disturbance w = [T a , S, Q other ] T , T a is the ambient temperature, S is the solar irradiance, Q other The cooling load of the user; Let the system output y = [P sl , t br ] T , establish the state space model at time k x(k+1)=f(x(k),u(k),z(k),w(k)) y(k)=h(x(k),u(k),z(k),w(k)).

4. The method for predicting and controlling an economic model of an integrated energy system with periodic characteristics according to claim 3 is characterized in that: Set the prediction time domain N equal to the operation period T, combine the prediction model, objective function and constraints to construct a finite time domain optimal control problem with periodic characteristics, use the economic MPC method to solve the finite time domain optimal control problem with periodic characteristics, and obtain the optimal control sequence of the entire optimization problem The optimal control sequence The first element is applied to the system, the latest state is measured, and the rolling optimization solution is repeated.

5. The method for predicting and controlling an economic model of an integrated energy system with periodic characteristics according to claim 4, characterized in that: The objective function is established based on the output tracking performance and economic optimization criteria of the integrated energy system operation to meet Among them, u k =[u 0|k ,u 1|k ,…u N-1|k ] T ,u i|k represents the predicted value at time k for time k+i, N represents the prediction time domain, a is a weight coefficient greater than zero that reflects the economic performance of the system, R is a symmetric positive definite weight matrix that reflects the output tracking performance of the system; u1 and u2 are the first and second elements in the continuous control variable u, y is the system output, y sp Given the expected output of the trace.

6. The method for predicting and controlling an economic model of an integrated energy system with periodic characteristics according to claim 5, characterized in that: Establish a constraint set including system state constraints, control variable constraints and cycle constraints; The state constraints are satisfied, x min ≤x k ≤x max Among them, x min =[C soc,min ,C sot,min ,t br,min ] T is the corresponding lower limit of the state quantity, x max =[C soc,max ,C sot,max ,t br,max ] T is the upper limit of the corresponding state quantity; The control variable constraints are satisfied, in min in k in max Among them, u min =[G fc,min ,G ma,min ,N ec,min ,G stu,min ,P bat,min ] T is the lower limit of the corresponding control quantity, u max =[G fc,max ,G ma,max ,N ec,max ,G stu,max ,P bat,max ] T is the upper limit of the corresponding control amount; The period constraint is satisfied, and k =and k+T Where T is the period of system operation.

7. The method for predicting and controlling an economic model of an integrated energy system with periodic characteristics according to claim 6, characterized in that: The change value of the control quantity at adjacent moments satisfies △u min ≤△u k ≤△u max , where Δu k =u k -u k-1 .

8. The method for predicting and controlling an economic model of an integrated energy system with periodic characteristics according to claim 7, characterized in that: The predictive controller of the periodic economic model of the integrated energy system is s.t.x i+1|k =f(x i|k ,u i|k ,z i|k ,w i|k ),i∈I 0:N-1 x 0|k =x0,x min ≤x k ≤x max in min in k in max ,△u min ≤△u k ≤△u max and 0|k =and N|k Among them, I 0:N-1 Represents an integer in [0, N-1].

9. The integrated energy system with periodic characteristics according to claim 8 The economic model predictive control method is characterized by: Optimal Control Sequence The first The elements are the control laws applied to the system. Repeat periodically at Optimized rolling operation on the intermediate axis.

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