Bistable distributed regional collaborative control method for intelligent building energy management system

Abstract

The present invention discloses a bistable distributed regional collaborative control method for an intelligent building energy management system, comprising the following steps: establishing a positive multi-agent system state space model of the intelligent building energy management system; designing a positive multi-agent system observer of the intelligent building energy management system; establishing an observer-based PID control protocol for the intelligent building energy management system; designing conditions for the stable operation of the intelligent building energy management system; verifying the positivity of the intelligent building energy management system; and verifying the regional consistency of the intelligent building energy management system. The present invention considers the multi-equilibrium point characteristics in the intelligent building energy management system, designs and embeds a bistable distributed PID control protocol, and realizes real-time monitoring and control of the status of different equipment inside the building through the Luenberger observer and other control algorithms.

Description

Technical Field

[0001] The present invention belongs to the field of automation control technology, and in particular relates to a bistable distributed regional collaborative control method for an intelligent building energy management system. Background Art

[0002] With the intensification of the global energy crisis and the improvement of environmental protection awareness, intelligent buildings, as an important way to save energy and reduce emissions, are receiving more and more attention. Intelligent Building Energy Management System (IBEMS) integrates and optimizes the use of energy in buildings to achieve intelligent monitoring and control of high-energy-consuming equipment such as HVAC, lighting, and elevators to achieve energy saving and improve comfort. In recent years, with the rapid development of building intelligence and energy management technology, intelligent building energy management system (IBEMS) has become a key means to achieve the goals of improving building energy efficiency, optimizing user comfort, and environmental sustainability.

[0003] Traditional energy management systems are often designed for a single balance point. Due to the complexity of the building's internal environment, the diversity of user needs, and the influence of external environmental factors, the system often exhibits multi-balance point characteristics. For example, under the premise of meeting the indoor temperature and humidity comfort requirements, the air-conditioning system may select different operating modes (such as cooling, heating, dehumidification, ventilation, etc.) and set values ​​according to various factors such as season, weather, sunshine, building thermal inertia, indoor heat source distribution, etc., to form multiple stable energy consumption balance points. Similarly, other subsystems such as lighting systems, elevator systems, and hot water supply systems will also present multiple balance states according to their respective usage patterns, energy-saving strategies, and changes in external conditions. This requires the system to be able to adapt to multiple stable states and achieve flexible energy allocation and regulation. When dealing with such multi-balance point systems, traditional PID control may fail to effectively identify and respond to the multimodal behavior of the system, resulting in problems such as low energy management efficiency, substandard comfort, or excessive equipment wear, which limits its application in complex systems. Summary of the invention

[0004] The present invention introduces an advanced state observation and identification method, which can accurately identify the current equilibrium state of the system in real time and respond quickly to changes in external conditions, so that the system can smoothly transition to different equilibrium states. This capability is crucial to dealing with the multimodal behavior of building energy systems, ensuring that the system can always adapt to changing internal and external conditions. In addition, the design of the observer gain matrix adopts matrix decomposition technology. This technology can optimize the dynamic response of the observer, enhance its sensitivity to changes in system states and its anti-interference ability, especially when switching between multiple equilibrium points, and can quickly and accurately track the transition of system states. By carefully designing the gain matrix, it is ensured that the observer can provide high-quality system state estimates under various operating conditions, which is crucial to achieving accurate energy management.

[0005] Traditional PID control protocols are widely used in intelligent building energy management systems because they can provide good control performance and robustness. However, traditional PID control protocols often have difficulty handling multi-balance point systems. In intelligent buildings, energy management systems may need to switch between multiple energy generation and consumption modes, each of which can be regarded as a balance point of the system. Traditional PID control protocols may not be sufficient to maintain the stability of the system when handling such dynamic changes, especially when energy supply and demand change rapidly. The bistable distributed PID control protocol of the present invention is designed in the form of linear programming to ensure that the states of all subsystems are always within a reasonable, non-negative range. In the intelligent building energy management system, this means that the air conditioning temperature setting should be kept within the human comfort range, the lighting brightness should not be too high or too low, and the elevator operation should avoid frequent start and stop, etc. Through linear programming, the protocol can coordinate the control actions of each subsystem so that while meeting their respective performance constraints, they can jointly drive the entire building energy system towards a preset energy-saving area, such as an annual energy consumption budget, a green building certification standard, or a user-customized energy consumption target.

[0006] Finally, the positivity problem of the intelligent building energy management system and the stability problem of the observer are uniformly transformed into the regional stability problem of the augmented system. This means that when designing and implementing the control protocol, not only the stability and performance indicators of a single subsystem are considered, but also the global stability of the entire building energy system and the interaction effects between the subsystems are considered. By analyzing and optimizing the regional stability of the augmented system, it is ensured that even when switching between multiple equilibrium points or under the influence of external disturbances, the system can still maintain stable operation within the preset energy-saving area, without excessive energy consumption, large fluctuations in comfort, or excessive stress on the equipment. The importance of regional collaborative control lies in ensuring that the states of all subsystems are always within a reasonable and non-negative range through the preset energy-saving area or performance boundary, and can collaboratively drive the entire building energy system to operate stably in the predetermined target area. This control method is not only conducive to the efficient use of energy, but also effectively prevents excessive stress on equipment and system performance degradation.

[0007] Based on the above analysis, the bistable distributed regional collaborative control method of the intelligent building energy management system of the present invention constructs a bistable distributed PID control protocol framework for multiple equilibrium points in the intelligent building energy management system; secondly, a set of regional collaborative proportional-integral-differential control strategies based on the system state observer is proposed; finally, the process of reaching consensus in the system is deeply analyzed through matrix decomposition, positive Lyapunov function theory and linear programming methods. In summary, in the context of intelligent building energy management systems, bistable distributed regional collaborative control technology is a key innovation aimed at improving building energy efficiency and system stability.

[0008] In order to achieve the above object, the specific technical scheme of the present invention is as follows:

[0009] The bistable distributed regional collaborative control method of the intelligent building energy management system comprises the following steps:

[0010] Step 1: Establish a state space model of a multi-agent system for an intelligent building energy management system;

[0011] Step 2: Design a positive multi-agent system observer for the intelligent building energy management system;

[0012] Step 3: Establish the observer-based PID control protocol for the intelligent building energy management system;

[0013] Step 4: Design the conditions for the smooth operation of the intelligent building energy management system;

[0014] Step 5: Verify the positivity of the smart building energy management system;

[0015] Step 6: Verify the regional consistency of the smart building energy management system.

[0016] Preferably, the construction of the state space model of the multi-agent system of the intelligent building energy management system in step 1 is in the following form:

[0017]

[0018]

[0019] in, They represent the energy consumption state of the i-th system in the building at time k, the control signal input obtained by the i-th system of the intelligent building energy management at time k, and the data directly sensed or read by the system state variables of the i-th system of the intelligent building energy management at time k, i∈1,2,...,N, N represents n-dimensional, w-dimensional, s-dimensional matrices and a set of positive integers, respectively. and is the state and output equilibrium point of the agent, and the switching signal σ(k) is , switching is performed between J multi-agent systems and each multi-agent system has N agents. The known system matrix satisfies A σ(k) >0,B σ(k) >0 and C σ(k) >0.

[0020] Preferably, step 2 designs a positive multi-agent system observer of the intelligent building energy management system, and its design form is as follows:

[0021] Constructing observer-based PID regional consensus, the positive multi-agent system observer of the intelligent building energy management system is designed as follows:

[0022]

[0023]

[0024] in, are the state, input and output of the ith observer, respectively. is the observer gain matrix, is the error signal, which can be rewritten as:

[0025] s i (k+1)=(A σ(k) -G σ(k) C σ(k) )s i (k).

[0026] Preferably, in step 3, an observer-based PID control protocol for an intelligent building energy management system is established, and its construction form is as follows:

[0027]

[0028] Among them, K σ(k) ,H σ(k) ,F σ(k) and M σ(k) are the gain matrices to be designed, a (σ(k)) is a constant related to the communication topology related to the switching signal between agents. If the i-th agent can communicate with the j-th agent, then otherwise, Its dimension is related to the number of agents in the multi-agent system;

[0029] It is an integral part of the PID control protocol.

[0030] Preferably, the conditions for the stable operation of the intelligent building energy management system in step 4 are constructed as follows: design constants 0<δ≤1, 0<ρ<1, λ>1, vector and The vector makes

[0031]

[0032]

[0033]

[0034]

[0035]

[0036]

[0037]

[0038]

[0039]

[0040]

[0041]

[0042]

[0043] For the convenience of writing, the switching signal σ(k) is denoted as p. and If it is established, then, under the observer-based PID control protocol in step 3, the intelligent building energy management system achieves positivity and consistency, and the gain matrix is:

[0044]

[0045] And meet

[0046]

[0047] in, τ * is the average residence time and satisfies 1 w represents a w-dimensional column vector whose elements are all 1, represents a w-dimensional column vector whose ιth element is 1 and the rest are 0, 1 n represents an n-dimensional column vector whose elements are all 1, represents an n-dimensional column vector whose ιth element is 1 and the rest of the elements are 0, A represents an n-dimensional row vector whose elements are all 1, and 0 represents a vector or matrix whose elements are all 0. p >0,B p >0 and C p >0 is the known system matrix, a (p) is a constant related to the communication topology related to the switching signal between agents. The agent can communicate with the jth agent, then otherwise, Its dimension is related to the number of agents in the multi-agent system. vector is the Laplace matrix The left eigenvector corresponding to the zero eigenvalue of p ≥1 N , vector Superscript in + Indicates that all elements of the vector are positive, and the vector Superscript in - Indicates that all elements of this vector are negative.

[0048] Preferably, in step 5, the positivity of the intelligent building energy management system is verified, and its construction form is as follows:

[0049] Step 5.1 Order

[0050]

[0051]

[0052] According to the state space model of the intelligent building energy management system established in step 1 and the observer-based PID control protocol in step 3, we can get

[0053]

[0054]

[0055]

[0056] in, is a Kronecker product operator, I N and I s are the identity matrices of N×N and s×s dimensions respectively,

[0057] Step 5.2: From step 5.1, we can get

[0058]

[0059] in,

[0060] Step 5.3 From conditions (11), (12) and (14) in step 4, we can obtain:

[0061]

[0062] From conditions (1) and (2) in step 4, we can get

[0063] A p -G p C p ≥0,G p C p ≥0,

[0064] pass We can get:

[0065]

[0066] The following inequality can be determined from condition (14) in step 4:

[0067]

[0068]

[0069] From conditions (3) and (4) in step 4, we can obtain:

[0070]

[0071] Given conditions (5) and (6) in step 4, we have Bp F p ≥0,-B p M p ≥0, through r p ≥1 N ,get By A p -G p C p ≥0, indicating Therefore, the intelligent building energy management system is positive.

[0072] Preferably, in step 6, the regional consistency of the intelligent building energy management system is verified, and its construction form is as follows:

[0073] Step 6.1 Definition So,

[0074] Pass conditions and then

[0075]

[0076] pass You can get:

[0077]

[0078] From conditions (15) and (16) in step 6.1, we can deduce:

[0079]

[0080] Step 6.2 Definition Then we have:

[0081]

[0082] in,

[0083]

[0084] Therefore, system (18) is positive,

[0085] Step 6.3 Select the linear copositive Lyapunov function

[0086] in, The difference is:

[0087]

[0088] in,

[0089]

[0090] and

[0091]

[0092] From condition (14) in step 4, we can obtain:

[0093]

[0094] Step 6.4 By combining (19), (20) and (7)-(10), we can deduce:

[0095]

[0096] in, Therefore, V p (k+1)≤ρV p (k)+γ, arbitrarily select a switching sequence: 0≤k0≤k1≤…,k∈[k m ,k m+1 ),m∈N, from condition (12) in step 4, we have:

[0097]

[0098] Considering the condition λ>1, equation (21) can be transformed into:

[0099]

[0100] make Among them, φ pi Yes p The i-th element of σ(k) The definition of (k) can be obtained Combined with formula (22), we can establish:

[0101]

[0102] and then

[0103]

[0104] in,

[0105] Therefore, the energy management system of an intelligent building is regionally consistent, that is, when designing and implementing the control system, the system can ensure that all relevant energy subsystems in the building can operate in a coordinated and consistent manner while meeting their respective functional requirements, thereby achieving an overall optimization effect.

[0106] Based on the above technical solution, the beneficial effects of the present invention are as follows: the method of the present invention first uses a positive multi-agent system to establish a state space model of the intelligent building energy management system. In multiple subsystems or regions of the system, coordination and synchronization of energy use and management are achieved. This means that energy demand, supply and control strategies in different regions can cooperate with each other to optimize overall energy efficiency and meet comfort requirements inside the building. Regional consistency ensures that the system can maintain an efficient and stable operating state even in the face of multiple equilibrium points and dynamic changes in the system.

[0107] A bistable distributed PID control protocol based on Luenberger observer and multiple equilibrium points is proposed. The protocol is designed in the form of linear programming, which can ensure that the states of all agents are non-negative and driven to a specific area. It realizes the effective management and precise control of the state of the intelligent agent, ensures the smooth transition and stable operation of the system between multiple equilibrium points, and has significant application value and broad prospects for improving the energy efficiency of intelligent buildings, ensuring user comfort, extending equipment life and promoting sustainable development of buildings. BRIEF DESCRIPTION OF THE DRAWINGS

[0108] Figure 1 It is a diagram of smart building energy management system;

[0109] Figure 2 It is a structural diagram of the mathematical model based on the intelligent building energy management system. DETAILED DESCRIPTION

[0110] The purpose of this invention is to design and implement a bistable distributed regional collaborative control strategy for the multi-balance point problem in the intelligent building energy management system. By designing an observer and a PID control protocol, the control problem of the intelligent building energy system when switching the balance point under different operating modes and load conditions is effectively solved to ensure the stability and efficient operation of the system. A bistable distributed regional collaborative control method for an intelligent building energy management system is provided, and the steps are as follows:

[0111] Step 1: Consider a building energy management system such as Figure 1As shown in the figure, the architecture diagram of an intelligent building energy management system is divided into three layers: application business layer, collection and control layer, and data perception layer. In the application business layer, the management center and the data center are connected by a dotted line, indicating the information exchange between the two. The data center is connected to another management center to form a closed-loop information flow. In the collection and control layer, there are three energy consumption data collectors, which are responsible for collecting various types of energy consumption data and sending them to the application business layer of the upper layer. These data may include aspects such as energy consumption metering, parameter monitoring and intelligent control. In the data perception layer, there is an energy station energy efficiency management system, which manages and optimizes the energy use of the entire building by analyzing and processing the collected data. This system can provide real-time energy consumption metering, parameter monitoring and intelligent control functions to help users better understand and manage their energy usage. In general, Figure 1 It presents a complete intelligent building energy management system framework. From data collection to data analysis to final energy management, each link is closely linked, forming an efficient and intelligent energy management system.

[0112] Figure 2 It is a mathematical model structure diagram based on the intelligent building energy management system. First, data is collected through sensors, and then transmitted to each intelligent system through the communication topology. The intelligent system will perform multi-equilibrium point analysis, and then controlled by the PID control protocol. Finally, bistable regional coordinated control is performed through state feedback and correction. Specifically, there is a multi-agent system, including multiple intelligent agents, each of which has a PID control protocol. Data is collected through sensors, transmitted through the communication topology, multi-equilibrium point analysis is performed, observers are designed, and bistable regional coordinated control is performed through state feedback and correction.

[0113] Identify all energy subsystems and equipment covered by the intelligent building energy management system, including hardware facilities such as various sensors, controllers and communication networks, and then collect the physical property data of the building, as well as the performance parameters, operating data and environmental data of various energy equipment to establish a positive multi-agent system state space model of the intelligent building energy management system.

[0114] The construction of the state space model of the multi-agent system of its intelligent building energy management system is as follows:

[0115]

[0116]

[0117] in, They represent the energy consumption state of the i-th system in the building at time k, the control signal input obtained by the i-th system of the intelligent building energy management at time k, and the data directly sensed or read by the system state variables of the i-th system of the intelligent building energy management at time k, i∈1,2,...,N, N represents n-dimensional, w-dimensional, s-dimensional matrices and a set of positive integers, respectively. and is the state and output equilibrium point of the agent, and the switching signal σ(k) is , switching is performed between J multi-agent systems and each multi-agent system has N agents. The known system matrix satisfies A σ(k) >0,B σ(k) >0 and C σ(k) >0.

[0118] Step 2: Design a positive multi-agent system observer for the intelligent building energy management system. The design form is as follows:

[0119] Constructing observer-based PID regional consensus, the positive multi-agent system observer of the intelligent building energy management system is designed as follows:

[0120]

[0121]

[0122] in, are the state, input and output of the ith observer, respectively. is the observer gain matrix, is the error signal, which can be rewritten as:

[0123] s i (k+1)=(A σ(k) -G σ(k) C σ(k) )s i (k).

[0124] Step 3: Establish the observer-based PID control protocol for the intelligent building energy management system, which is constructed as follows:

[0125]

[0126] Among them, K σ(k) ,H σ(k) ,F σ(k) and M σ(k) are the gain matrices to be designed, a (σ(k)) is a constant related to the communication topology related to the switching signal between agents. If the i-th agent can communicate with the j-th agent, then otherwise, Its dimension is related to the number of agents in the multi-agent system;

[0127] It is an integral part of the PID control protocol.

[0128] Step 4: Design the conditions for the smooth operation of the intelligent building energy management system. The construction method is as follows:

[0129] Design constants 0<δ≤1,0<ρ<1,λ>1, vector and The vector makes

[0130]

[0131]

[0132]

[0133]

[0134]

[0135]

[0136]

[0137]

[0138]

[0139]

[0140]

[0141]

[0142]

[0143] For the convenience of writing, let the switching signal σ(k) be denoted by p. and If it is established, then, under the observer-based PID control protocol in step 3, the intelligent building energy management system achieves positivity and consistency, and the gain matrix is:

[0144]

[0145] And meet

[0146]

[0147] in, τ * is the average residence time and satisfies 1 w represents a w-dimensional column vector whose elements are all 1, represents a w-dimensional column vector whose ιth element is 1 and the rest are 0, 1 n represents an n-dimensional column vector whose elements are all 1, represents an n-dimensional column vector whose ιth element is 1 and the rest of the elements are 0, A represents an n-dimensional row vector whose elements are all 1, and 0 represents a vector or matrix whose elements are all 0. p >0,B p >0 and C p >0 is the known system matrix, a (p) is a constant related to the communication topology related to the switching signal between agents. The agent can communicate with the jth agent, then otherwise, Its dimension is related to the number of agents in the multi-agent system. vector is the Laplace matrix The left eigenvector corresponding to the zero eigenvalue of p ≥1 N , vector Superscript in + Indicates that all elements of the vector are positive, and the vector Superscript in - Indicates that all elements of this vector are negative.

[0148] Step 5: Verify the positivity of the intelligent building energy management system, which is constructed as follows:

[0149] Step 5.1 Order

[0150]

[0151]

[0152] According to the state space model of the intelligent building energy management system established in step 1 and the observer-based PID control protocol in step 3, we can get

[0153]

[0154]

[0155]

[0156] in, is a Kronecker product operator, I N and I s are the identity matrices of N×N and s×s dimensions respectively,

[0157] Step 5.2: From step 5.1, we can get

[0158]

[0159] in,

[0160]

[0161] Step 5.3 From conditions (11), (12) and (14) in step 4, we can obtain:

[0162]

[0163] From conditions (1) and (2) in step 4, we can get

[0164] A p -G p C p ≥0,G p C p ≥0,

[0165] pass We can get:

[0166]

[0167] The following inequality can be determined from condition (14) in step 4:

[0168]

[0169] From conditions (3) and (4) in step 4, we can obtain:

[0170]

[0171] Given conditions (5) and (6) in step 4, we have B p F p ≥0,-B p M p ≥0, through r p ≥1 N ,get By A p -G p C p ≥0, indicating Therefore, the intelligent building energy management system is positive.

[0172] Step 6: Verify the regional consistency of the smart building energy management system, which is constructed as follows:

[0173] Step 6.1 Definition So, Pass conditions and then

[0174]

[0175] pass You can get:

[0176]

[0177] From conditions (15) and (16) in step 6.1, we can deduce:

[0178]

[0179] Step 6.2 Definition Then we have:

[0180]

[0181] in,

[0182]

[0183] Therefore, system (18) is positive,

[0184] Step 6.3 Select the linear copositive Lyapunov function

[0185] in, The difference is:

[0186]

[0187] in,

[0188] and

[0189]

[0190]

[0191] From condition (14) in step 4, we can obtain:

[0192]

[0193] Step 6.4 By combining (19), (20) and (7)-(10), we can deduce:

[0194]

[0195] in, Therefore, V p (k+1)≤ρV p (k)+γ, arbitrarily select a switching sequence: 0≤k0≤k1≤…,k∈[k m ,k m+1 ),m∈N, from condition (12) in step 4, we have:

[0196]

[0197] Considering the condition λ>1, equation (21) can be transformed into:

[0198]

[0199] make Among them, φ pi Yes p The i-th element of σ(k) The definition of (k) can be obtained Combined with formula (22), we can establish:

[0200]

[0201] and then

[0202]

[0203] in,

[0204] Therefore, the energy management system of an intelligent building is regionally consistent, that is, when designing and implementing the control system, the system can ensure that all relevant energy subsystems in the building (such as air conditioning, lighting, elevators, heating, power supply, etc.) can meet their respective functional requirements while their operating status can be coordinated and consistent to achieve an overall optimization effect.

Claims

1. A bistable distributed regional collaborative control method for an intelligent building energy management system, characterized in that: The steps include: Step 1: Establish a state space model of the multi-agent system of the intelligent building energy management system, which is in the following form: in, They represent the energy consumption state of the i-th system in the building at time k, the control signal input obtained by the i-th system of the intelligent building energy management at time k, and the data directly sensed or read by the system state variables of the i-th system of the intelligent building energy management at time k, i∈1,2,...,N, N represents n-dimensional, w-dimensional, s-dimensional matrices and a set of positive integers, respectively. and is the state and output equilibrium point of the agent, and the switching signal σ(k) is , switching is performed between J multi-agent systems and each multi-agent system has N agents. The known system matrix satisfies A σ(k) >0,B σ(k) >0 and C σ(k) >0; Step 2: Design a positive multi-agent system observer for the intelligent building energy management system. The design form is as follows: Construct a PID regional consensus based on the observer. The positive multi-agent system observer for the intelligent building energy management system is designed as follows: in, They represent the internal state of the i-th observer in the intelligent building energy management system at time k, the control command input received by the observer, and the output data directly perceived or collected by the observer according to the system state. is the observer gain matrix, is the error signal, which can be rewritten as: s i (k+1)=(A σ(k) -G σ(k) C σ(k) )s i (k); Step 3: Establish the observer-based PID control protocol for the intelligent building energy management system, which is constructed as follows: Among them, K σ(k) ,H σ(k) ,F σ(k) and M σ(k) are the gain matrices to be designed, a (σ(k)) is a constant related to the communication topology related to the switching signal between agents. If the i-th agent can communicate with the j-th agent, then otherwise, Its dimension is related to the number of agents in the multi-agent system; It is an integral part of the PID control protocol; Step 4: Design the conditions for the smooth operation of the intelligent building energy management system. The construction method is as follows: Design constants vector and vector Make For the convenience of writing, the switching signal σ(k) is denoted as p. and If it is established, then, under the observer-based PID control protocol in step 3, the intelligent building energy management system achieves positivity and consistency, and the gain matrix is: And meet in, is the average residence time and satisfies 1 w represents a w-dimensional column vector whose elements are all 1, represents a w-dimensional column vector whose ιth element is 1 and the rest are 0, 1 n represents an n-dimensional column vector whose elements are all 1, represents an n-dimensional column vector whose ιth element is 1 and the rest of the elements are 0, A represents an n-dimensional row vector whose elements are all 1, and 0 represents a vector or matrix whose elements are all 0. p >0,B p >0 and C p >0 is the known system matrix, a (p) is a constant related to the communication topology related to the switching signal between agents. The agent can communicate with the jth agent, then otherwise, Its dimension is related to the number of agents in the multi-agent system. vector is the Laplace matrix The left eigenvector corresponding to the zero eigenvalue of vector Superscript in + Indicates that all elements of the vector are positive, and the vector Superscript in - Indicates that all elements of the vector are negative; Step 5: Verify the positivity of the smart building energy management system; Step 6: Verify the regional consistency of the smart building energy management system.

2. The bistable distributed regional collaborative control method of the intelligent building energy management system according to claim 1 is characterized in that: In step 5, the positivity of the intelligent building energy management system is verified, and its construction form is as follows: Step 5.1 Order According to the state space model of the intelligent building energy management system established in step 1 and the observer-based PID control protocol in step 3, we can get in, is a Kronecker product operator, I N and I s are the identity matrices of N×N and s×s dimensions respectively, Step 5.2: From step 5.1, we can get in, Step 5.3 From conditions (11), (12) and (14) in step 4, we can obtain: From conditions (1) and (2) in step 4, we can get A p -G p C p ≥0,G p C p ≥0, pass We can get: The following inequality can be determined from condition (14) in step 4: From conditions (3) and (4) in step 4, we can obtain: Given conditions (5) and (6) in step 4, we have B p F p ≥0,-B p M p ≥0, through r p ≥1 N ,get By A p -G p C p ≥0, indicating Therefore, the intelligent building energy management system is positive.

3. The bistable distributed regional collaborative control method of the intelligent building energy management system according to claim 2 is characterized in that: In step 6, the regional consistency of the smart building energy management system is verified. Step 6.1 Definition So, Pass conditions and then pass You can get: From conditions (15) and (16) in step 6.1, we can deduce: Step 6.2 Definition Then we have: in, Therefore, system (18) is positive, Step 6.3 Select the linear copositive Lyapunov function in, V p The difference of (k) is: in, and From condition (14) in step 4, we can obtain: Step 6.4 By combining (19), (20) and (7)-(10), we can deduce: in, Therefore, V p (k+1)≤ρV p (k)+γ, arbitrarily select a switching sequence: 0≤k0≤k1≤…,k∈[k m ,k m+1 ),m∈N, from condition (12) in step 4, we have: Considering the condition λ>1, equation (21) can be transformed into: make Among them, φ pi Yes p The i-th element of σ(k) The definition of (k) can be obtained Combined with formula (22), we can establish: and then in, Therefore, the energy management system of an intelligent building is regionally consistent, that is, when designing and implementing the control system, the system can ensure that all relevant energy subsystems in the building can operate in a coordinated and consistent manner while meeting their respective functional requirements, thereby achieving an overall optimization effect.

Images