Monitoring, control systems and methods for environmental and economic dispatch of integrated energy systems

Abstract

This invention provides a monitoring and control system and method for environmental and economic dispatching of integrated energy systems, relating to the field of integrated energy system technology. The system and method involve a distributed network of multiple intelligent terminals, an edge server monitoring system, and an integrated energy system. The intelligent terminals monitor the real-time operating status of the integrated energy system, collect operating data from each device within the system and upload it to the edge server monitoring system. They establish data transmission links with neighboring intelligent terminals to transmit the output power and incremental cost values ​​of local devices controlled by the current intelligent terminal within the integrated energy system. An environmental and economic optimization dispatching algorithm solves for the optimal incremental cost and optimal output power of local devices and issues control commands to the integrated energy system for adjustment. The edge server monitoring system receives and displays real-time operating status data of the integrated energy system, and simultaneously generates historical data reports, performs operational economic analysis, and monitors energy topology.

Description

Technical Field

[0001] This invention relates to the field of integrated energy system technology, and in particular to a monitoring and control system and method for environmental and economic dispatching of integrated energy systems. Background Technology

[0002] The world is facing increasing pressure to conserve energy and protect the environment. How to reduce environmental pollution while ensuring a sustainable energy supply is a problem that the entire world must consider. Integrated energy systems are one of the main ways to integrate various distributed renewable energy sources, and are of great significance for promoting the integration of various renewable energy sources and establishing new green and low-carbon power systems. Integrated energy systems deeply integrate multiple energy sources with information technology, utilizing advanced cyber-physical technologies and innovative management models, and employing various energy coupling devices to achieve coordinated planning, management, and optimized operation among multiple energy subsystems. This can effectively improve energy utilization and promote sustainable energy development. In recent years, with the growing demand for integrated energy systems to replace traditional energy systems, research on various key technologies and theories related to integrated energy systems has received widespread attention from researchers in the field of power systems worldwide.

[0003] Economic dispatch has always been a hot topic in power and energy system research. Economic dispatch, under the premise of ensuring safety and energy quality, aims to minimize total cost through the rational utilization of energy and equipment. It can be equivalently described as a planning problem that minimizes the cost function while satisfying the output power constraints of each unit and the system power balance constraints. Traditional centralized control methods suffer from drawbacks such as high communication requirements and computational complexity, and vulnerability to attacks. Compared to centralized algorithms, distributed algorithms have lower communication resource requirements and offer higher robustness and information security.

[0004] There are two existing methods for the economic optimization scheduling problem of integrated energy systems: 1. Establish an optimization scheduling model and call a solver to solve it, which can solve day-ahead interval optimization scheduling; 2. Construct the cost function of each scheduling device, and use a distributed consensus algorithm to iteratively solve it and give the optimal output power of each unit.

[0005] However, while using a solver can improve the solution speed to some extent, current optimized scheduling is insufficient to meet the needs of real-time scheduling. On the other hand, using traditional consensus algorithms for real-time solutions significantly increases the number of iterations required for solving complex systems, and the solution time also increases significantly, leading to greater errors in real-time scheduling. Furthermore, it is difficult to balance the goals of economic operation and environmental friendliness. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a monitoring and control system and method for environmental and economic dispatch of integrated energy systems, which addresses the shortcomings of the prior art and realizes the monitoring and control of integrated energy systems.

[0007] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0008] On the one hand, the present invention provides a monitoring and control system for environmental and economic dispatch of integrated energy systems, comprising: a distributed system of multiple intelligent terminals, an edge server monitoring system, and an integrated energy system;

[0009] The intelligent terminal monitors the real-time operation status of the integrated energy system, collects the operating data of each device in the integrated energy system and uploads it to the edge server monitoring system. It establishes data transmission links with neighboring intelligent terminals to transmit the output power and incremental cost values ​​of the local devices controlled by the current intelligent terminal in the integrated energy system. The environmental economic optimization scheduling algorithm solves for the optimal incremental cost and optimal output power of the local devices and issues control commands to the integrated energy system for adjustment. The environmental economic optimization scheduling algorithm includes a finite-time consistent average power solution algorithm and a finite-time consistent optimal incremental cost solution algorithm. The edge server monitoring system receives the real-time operating status data of the integrated energy system collected by the distributed intelligent terminals, displays it in the corresponding interface and updates it in real time. It also realizes the functions of generating historical data reports, operating economic analysis and energy topology monitoring. The integrated energy system provides the intelligent terminals with the output power and incremental cost data of the local devices and sends the real-time operating status data of the integrated energy system to the edge server monitoring system. At the same time, as the controlled object of multiple distributed intelligent terminals, it receives the control commands issued by them and makes adjustments. The devices in the integrated energy system include various power generation and heat generation units, various cogeneration units, and various distributed renewable energy sources and various energy storage devices.

[0010] Preferably, the distributed intelligent terminal includes a data acquisition module, a data processing module, a data storage module, a GPS positioning module, a multi-terminal collaboration module, a communication module, and a liquid crystal display module;

[0011] The data acquisition module communicates with each device in the integrated energy system, collecting real-time output power data of each unit and communication topology data of the integrated energy system. The data processing module processes the collected output power data of each unit into incremental cost variables to participate in the environmental and economic optimization scheduling algorithm iteration. The data storage module stores the output power and incremental cost data of each unit, data received from neighboring smart terminals, and historical data of the integrated energy system operation, and retrieves the output power and incremental cost data of each unit and the historical data of the integrated energy system operation when displayed in real-time on the smart LCD display module and the edge server monitoring system. The GPS positioning module uses the real-time positioning function of Beidou / GPS to determine the location of each smart terminal. The location of the device is displayed in real time in the edge server monitoring system; the multi-terminal collaboration module sends the incremental cost variables and local smart terminal information of the local smart terminal to the neighboring smart terminals, and receives information from the neighboring smart terminals through this module, and runs the environmental economic optimization scheduling algorithm to solve for the optimal incremental cost and optimal output power of the local device; the communication module establishes a point-to-point long-distance data transmission link between each smart terminal through LoRa communication technology, and establishes LoRa network distributed communication between smart terminals; the intelligent LCD display module displays the operating status of each device in the integrated energy system monitored and controlled by each smart terminal, the control results of the environmental economic optimization scheduling algorithm, and the historical operating curves of each device in real time by calling the data stored in the storage module.

[0012] Preferably, the edge server monitoring system includes: a communication topology interface, which receives communication topology data of the integrated energy system uploaded by smart terminals, displays the communication topology diagram between each device and terminal in real time, and monitors the disconnection / reconnection, switching out / connection status of each device and terminal; an operation status monitoring interface, which retrieves real-time data collected by each smart terminal, displays the online status, output power, and incremental cost parameters of each device in the integrated energy system, and updates them in real time; a control query interface, which queries the control commands issued by each smart terminal in real time, as well as the operation curves of each device in the integrated energy system adjusting its power after receiving the control commands; and a historical data query interface, which retrieves historical data stored by smart terminals, and queries historical data reports and curves for any day within the recorded range.

[0013] On the other hand, the present invention also provides a monitoring and control method for environmental and economic dispatch of integrated energy systems, comprising the following steps:

[0014] Step 1: The smart terminal collects the output power data of the power generation, heat generation and cogeneration units controlled by the local smart terminal, as well as the online status of each device, through the data acquisition module;

[0015] Step 2: The intelligent terminal, through its data processing module, first standardizes and normalizes the collected data; then, it builds a solution model for the environmental and economic optimization scheduling problem of the integrated energy system. Based on the model and the cost function coefficients and output power of each unit, it calculates the incremental electricity cost μ corresponding to the output power of each unit. P With incremental cost of heat μ H Specifically, it includes the following steps:

[0016] Step 2.1: Determine the operating costs and gas emission costs of each unit in the integrated energy system;

[0017] The operating costs of each unit are shown in the following formula:

[0018] C cost =C P +C C +C H +μ0P M

[0019]

[0020]

[0021]

[0022] In the formula, C cost C P C C C H These represent the total operating cost of the integrated energy system, the total operating cost of the generating units, the total operating cost of the combined heat and power (CHP) units, and the total operating cost of the heat-generating units, respectively; μ0 is the electricity price in the distribution network; P M The electrical power exchanged between the integrated energy system and the distribution network; N P N C N H These respectively represent the collection of generator sets, combined heat and power units, and heat-generating units; These represent the operating costs of the generator set, combined heat and power unit, and heat-generating unit controlled by the intelligent terminal i, respectively. This represents the electrical output power of the generator set controlled by the intelligent terminal i. This represents the electrical output power of the combined heat and power unit controlled by the intelligent terminal i. This represents the heat output power of the combined heat and power unit controlled by the intelligent terminal i. This represents the heat output power of the heat-generating unit controlled by the intelligent terminal i; All are operating cost coefficients for integrated energy systems;

[0023] The gas emission costs of each unit are shown in the following formula:

[0024]

[0025]

[0026]

[0027]

[0028] In the formula, C emission , These represent the total emission cost of the integrated energy system, the total emission cost of the generator set, the total emission cost of the combined heat and power unit, and the total emission cost of the heat-generating unit, respectively. These represent the total cost of carbon dioxide emissions for generator sets, combined heat and power units, and heat-generating units, respectively. These represent the total cost of nitrogen oxide and sulfur oxide emissions from generator sets, combined heat and power units, and heat-generating units, respectively. All are emission cost coefficients for integrated energy systems;

[0029] Step 2.2: Determine the power balance constraints and upper and lower limits of output power for each unit in the integrated energy system;

[0030] The power balance constraints for each unit are shown in the following formula:

[0031]

[0032]

[0033] In the formula, P L With Q L P represents the total electricity and heat load demand of the integrated energy system, respectively. M The exchange power obtained from the distribution network when the integrated energy system is operating in grid-connected mode;

[0034] The upper and lower limits of the output power of each unit are constrained by the following formulas:

[0035]

[0036]

[0037] In the formula, and These represent the lower and upper limits of the electrical output power of the generator set controlled by the intelligent terminal i, respectively. and These are the lower and upper limits of the heat output power of the heat-generating unit controlled by the intelligent terminal i, respectively.

[0038] Step 2.3: Determine the environmental and economic dispatch optimization objectives for the integrated energy system;

[0039] The optimization objective for the environmental and economic dispatch of the integrated energy system is shown in the following formula:

[0040] min[C cost C emission ]

[0041] The multi-objective optimization problem above is transformed into a single-objective optimization problem using the linear weighted sum method. The transformed environmental economic scheduling optimization objective is shown in the following formula:

[0042] min[w1C cost +w2C emission ]

[0043] In the formula, w1 and w2 are the weight factors of the corresponding optimization objectives, and 0≤w1≤1, 0≤w2≤1, w1+w2=1.

[0044] Step 2.4: Solve for the incremental costs of each unit in the integrated energy system;

[0045] The incremental costs of each unit in the integrated energy system are shown in the following formula:

[0046]

[0047]

[0048]

[0049]

[0050] In the formula, These are the incremental costs of electricity generated by generator sets, the incremental costs of electricity generated by combined heat and power (CHP) units, the incremental costs of heat generated by CHP units, and the incremental costs of heat-generating units.

[0051] Step 3: The smart terminal communicates with neighboring smart terminals through the communication module to obtain the online status of each smart neighbor terminal, constructs a LoRa distributed communication network, and generates the power communication topology matrix of the entire integrated energy system. and thermal communication topology matrix

[0052] Step 4: The smart terminal stores the output power and online status of each unit collected in Step 1, as well as the two communication topology matrices of the integrated energy system generated in Step 3, through the data storage module. This data serves as the data source for the LCD display module and the edge server monitoring system display interface. At the same time, the data collection time is stored as historical data.

[0053] Step 5: The smart terminal sends the incremental cost data and output power data of the current smart terminal to the neighboring smart terminal through the multi-terminal collaboration module, and receives the incremental cost data and output power data sent by the neighboring smart terminal.

[0054] Step 6: The smart terminal, through the multi-terminal collaboration module, uses the output power data of neighboring smart terminals and the current smart terminal from Step 5 to execute a finite-time consistent average power calculation algorithm, making the output power data of each smart terminal tend to be consistent; and updates the output power data of the current smart terminal according to the calculation results, and estimates the global electrical output power P of the integrated energy system based on the updated output power data of the current smart terminal. total (t) and global thermal output power Q total (t), global electrical power deviation ΔP(t) and global thermal power deviation ΔQ(t); specifically including the following steps:

[0055] Step 6.1: Determine the weight update factors for the power network and the heating network;

[0056] Based on the Laplacian matrices of the power network and heat network generated in step 3 The weight update factors for the power network and the heating network are expressed as follows:

[0057]

[0058]

[0059] In the formula, These are the weighting factors for the power network and the heating network, respectively. Represents the Laplacian matrix The (k+1)th eigenvalue, Represents the Laplacian matrix The (k+1)th eigenvalue, n P With n Q N represents the number of smart terminals in the power grid and the heating grid, respectively. i Let D be the set of all neighboring terminals of smart terminal i. i Let i be the degree of smart terminal i, that is, the number of smart terminals connected to smart terminal i.

[0060] Based on the above formula, the weight factor matrices for the power network and the heat network are obtained as follows:

[0061] Step 6.2: Execute the finite-time consistent average power solution algorithm to make the output power data of each smart terminal tend to be consistent, as shown in the following formula:

[0062]

[0063]

[0064] In the formula, A vector representing net electrical output power. A vector representing net thermal output power;

[0065] After a finite number of iterations, the output power data of each smart terminal will tend to be consistent, even if the output power data of each smart terminal becomes the average value of the output power of each smart terminal.

[0066] Step 6.3: Calculate the global output power and global power deviation of the integrated energy system;

[0067] Because the number of smart terminals in the power grid and the heating grid are n respectively. P With n Q The finite-time consistent average power solution algorithm then goes through n... P -1 and n Q After -1 iterations, the system converges, and the global electrical output power P of the integrated energy system is... total (t) and global thermal output power Q total (t) are respectively:

[0068] P total (t)=n P P(n P )

[0069] Q total (t)=n Q Q(n Q )

[0070] In the formula, P(n) P ) and Q(n Q The finite-time consistent average power solution algorithm takes n steps. P -1 and n Q The convergence value after -1 iterations;

[0071] The global power deviation ΔP and global power deviation ΔQ of the integrated energy system are shown in the following formulas:

[0072] ΔP=P L -P total

[0073] ΔQ=Q L -Q total

[0074] The power deviation is solved in step 7 to obtain the optimal incremental cost. and This will be used as a feedback quantity to coordinate the output power of the equipment in order to achieve power balance.

[0075] Step 7: The smart terminal, through the multi-terminal collaboration module, uses the incremental cost data of the neighboring smart terminal and the local smart terminal in Step 5 and the global power deviation data in Step 6 to execute the finite-time consistency optimal incremental cost solution algorithm, solve and update the local incremental cost data, and calculate the optimal output power of each unit.

[0076] Step 7.1: The smart terminal uses the collaboration module to receive incremental cost data from neighboring terminals, and combines it with global power deviation data to execute a finite-time consistency optimal incremental cost solution algorithm to update the local incremental cost;

[0077]

[0078]

[0079] In the formula, Incremental cost μ P The differential, Incremental cost μ H The derivative, μ0 is the distribution network electricity price, α P and α H It is the control gain, sig(x) m =sgn(x)·|x| m ,0 <m<1;ε P and ε H It is the power regulation coefficient;

[0080] If smart terminal i is connected to the power distribution network, then otherwise The control signal c = 0 indicates that the integrated energy system is connected to the distribution network; if c = 1, the integrated energy system is not connected to the distribution network.

[0081] Step 7.2: Calculate the output power of each unit based on the incremental cost;

[0082] Considering the upper and lower power limits of the solution model for the environmental and economic optimization scheduling problem of the integrated energy system, the electric power of the generator set is calculated according to the following formula. Electric power of cogeneration units Thermal power of cogeneration units and the thermal power of the heat-generating unit

[0083]

[0084]

[0085]

[0086]

[0087] Step 7.3: Calculate the incremental cost of the integrated energy system and the output power of each unit under different weight combinations by changing the weight values ​​of the optimization objectives. Determine whether the output power of each unit is within the constraint range. If it is within the constraint range, the output power is the optimal output power of the unit. If it is not within the constraint range, if it exceeds the upper limit, the upper limit power is taken as the optimal output power of the unit. If it is below the lower limit, the lower limit power is taken as the optimal output power of the unit.

[0088] Step 8: The smart terminal uses the multi-terminal collaboration module to determine whether the error between the updated local incremental cost and the incremental cost of the neighboring terminal exceeds the set threshold ε. If so, steps 5 to 8 are repeated; otherwise, step 9 is executed.

[0089] Step 9: Based on the optimal output power of each unit calculated by each intelligent terminal in Step 7, the corresponding control commands are sent to the corresponding equipment of the integrated energy system through the ARM processor of the multi-terminal collaboration module to adjust its output power.

[0090] Step 10: The smart terminal stores the intermediate data generated by the iteration of the two finite-time consensus algorithms in Step 6 and Step 7, as well as the optimal output power of each unit in Step 9, through the storage module, as the data source for the edge server control query interface.

[0091] Step 11: The LCD display module of the smart terminal and the edge server monitoring system display the operating status of the integrated energy system, the communication topology, and the convergence process of the two finite-time consensus algorithms in real time according to the received data.

[0092] The beneficial effects of adopting the above technical solution are as follows: The monitoring, control, and method for environmental and economic dispatching of integrated energy systems provided by this invention address the problem that existing technologies, when modeling and solving the economic dispatching problem of integrated energy systems, generally only consider the optimization objective of minimizing operating costs, without considering the impact of pollutant emission costs on the optimal result. This results in a certain deviation between the obtained optimal solution and the actual operating conditions. In order to minimize the deviation and make the optimization result closer to the actual situation, while taking into account both the optimization objectives of operational economy and environmental friendliness, this invention proposes an environmental and economic optimization dispatching strategy and control algorithm for integrated energy systems. The original problem is extended to a multi-objective optimization problem, and a control algorithm is designed to adjust the output power of each unit in the integrated energy system.

[0093] This invention proposes two finite-time consensus algorithms for integrated energy system control. These algorithms solve for the global power deviation and the optimal output of each unit, respectively. Each algorithm includes two parallel finite-time consensus protocols, simultaneously solving for the corresponding variables of both electrical and thermal energy sources. The proposed algorithms significantly improve convergence speed and the efficiency of the monitoring and control system. Furthermore, the real-time calculation of power deviation within the algorithms, participating in feedback regulation, is of great significance for improving the stability of the entire system and maintaining power balance during the control process. Attached Figure Description

[0094] Figure 1 A block diagram of a monitoring and control system for environmental and economic dispatching of integrated energy systems provided in an embodiment of the present invention;

[0095] Figure 2 A flowchart illustrating a monitoring and control method for environmental and economic dispatching of integrated energy systems, provided as an embodiment of the present invention. Detailed Implementation

[0096] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0097] In this embodiment, a monitoring and control system for environmental and economic dispatching of integrated energy systems, such as... Figure 1 As shown, it includes: multiple distributed smart terminals, an edge server monitoring system, and an integrated energy system;

[0098] The intelligent terminal monitors the real-time operating status of the integrated energy system, collects operating data from each device in the system and uploads it to the edge server monitoring system. It establishes data transmission links with neighboring intelligent terminals (other intelligent terminals connected to it) to transmit the output power and incremental cost values ​​of local devices controlled by the currently connected intelligent terminal within the integrated energy system. An environmental economic optimization scheduling algorithm solves for the optimal incremental cost and optimal output power of the local devices, and then issues control commands to the integrated energy system for adjustment. The environmental economic optimization scheduling algorithm includes a finite-time consistent average power solution algorithm and a finite-time consistent optimal incremental cost solution algorithm. The edge server... The server monitoring system receives real-time operating status data of the integrated energy system collected by distributed intelligent terminals, displays it on the corresponding interface and updates it in real time. It also realizes the functions of generating historical data reports, operating economic analysis and energy topology monitoring. The integrated energy system provides the intelligent terminals with the output power and incremental cost data of local equipment and sends the real-time operating status data of the integrated energy system to the edge server monitoring system. At the same time, as the controlled object of multiple distributed intelligent terminals, it receives control commands issued by them and makes adjustments. The equipment in the integrated energy system includes various power generation and heat generation units, various cogeneration units, and various distributed renewable energy sources and various energy storage devices.

[0099] The distributed intelligent terminal includes a data acquisition module, a data processing module, a data storage module, a GPS positioning module, a multi-terminal collaboration module, a communication module, and an LCD display module;

[0100] The system comprises several modules: a data acquisition module, a data processing module, and a multi-terminal data storage module. The data acquisition module communicates with all equipment in the integrated energy system, collecting real-time output power data from each power generation, heat generation, and cogeneration unit, along with the integrated energy system's communication topology data. The data processing module converts the collected output power data into incremental cost variables for use in the environmental and economic optimization scheduling algorithm iteration. The data storage module stores the output power and incremental cost data of each unit, data received from neighboring smart terminals, and historical operating data of the integrated energy system. This data is then displayed in real-time on the smart LCD display module and the edge server monitoring system, allowing for the retrieval of these data. The GPS positioning module, utilizing BeiDou / GPS real-time positioning, accurately determines the location of each smart terminal and displays it in real-time on the edge server monitoring system, ensuring the safe operation of the integrated energy system. Furthermore, real-time signal transmission via BeiDou / GPS ensures synchronized operation of each smart terminal during the environmental and economic optimization scheduling algorithm iteration, preventing asynchronous iteration and bringing practical applications closer to theoretical experiments. The multi-terminal collaboration module integrates the incremental cost variables of local smart terminals with the data from local smart terminals. Information is sent to neighboring smart terminals, and information is received from neighboring smart terminals through this module. The environmental economic optimization scheduling algorithm is used to solve for the optimal incremental cost and optimal output power of local devices. In this embodiment, the FPGA chip is responsible for the computation of the multi-terminal collaborative module and the information interaction between smart terminals, while the ARM processor is responsible for collecting data from the integrated energy system devices and issuing control commands to the system. Together, they complete the specified functions of the module, improve the algorithm iteration speed and the control capability of the system. The design of this module can effectively alleviate the pressure on the CPU of smart terminals to process data, and can also intuitively reflect the collaborative operation between multiple smart terminals, realize the stable operation of the integrated energy system, and realize the vertical collaborative interaction between smart terminals and the edge server monitoring system and the horizontal collaborative interaction between each terminal. The communication module establishes a point-to-point long-distance data transmission link between smart terminals through LoRa communication technology, and establishes LoRa network distributed communication between smart terminals. The LCD display module displays the operating status of each device in the integrated energy system monitored and controlled by each smart terminal, the control results of the environmental economic optimization scheduling algorithm, and the historical operating curves of each device in real time by calling the data stored in the storage module.

[0101] The edge server monitoring system includes: a communication topology interface, which receives communication topology data of the integrated energy system uploaded by smart terminals, displays the communication topology diagram between each device and terminal in real time, and monitors the disconnection / reconnection, switching out / connection status of each device and terminal; an operation status monitoring interface, which retrieves real-time data collected by each smart terminal, displays the online status, output power, and incremental cost parameters of each device in the integrated energy system, and updates them in real time; a control query interface, which queries the control commands issued by each smart terminal in real time, as well as the operating curves of each device in the integrated energy system adjusting its power after receiving the control commands; and a historical data query interface, which retrieves historical data stored in the smart terminals, and queries historical data reports and curves for any day within the recorded range.

[0102] In this embodiment, a monitoring and control method for environmental and economic dispatching of integrated energy systems, such as... Figure 2 As shown, it includes the following steps:

[0103] Step 1: The smart terminal collects the output power data of the power generation, heat generation and cogeneration units controlled by the local smart terminal, as well as the online status of each device, through the data acquisition module;

[0104] Step 2: The intelligent terminal, through its data processing module, first standardizes and normalizes the collected data; then, it builds a solution model for the environmental and economic optimization scheduling problem of the integrated energy system. Based on the model and the cost function coefficients and output power of each unit, it calculates the incremental electricity cost μ corresponding to the output power of each unit. P With incremental cost of heat μ H Specifically, it includes the following steps:

[0105] Step 2.1: Determine the operating costs and gas emission costs of each unit in the integrated energy system;

[0106] The operating costs of each unit are shown in the following formula:

[0107] C cost =C P +C C +C H +μ0P M

[0108]

[0109]

[0110]

[0111] In the formula, C cost C P C C C HThese represent the total operating cost of the integrated energy system, the total operating cost of the generating units, the total operating cost of the combined heat and power (CHP) units, and the total operating cost of the heat-generating units, respectively; μ0 is the electricity price in the distribution network; P M The electrical power exchanged between the integrated energy system and the distribution network; N P N C N H These respectively represent the collection of generator sets, combined heat and power units, and heat-generating units; These represent the operating costs of the generator set, combined heat and power unit, and heat-generating unit controlled by the intelligent terminal i, respectively. This represents the electrical output power of the generator set controlled by the intelligent terminal i. This represents the electrical output power of the combined heat and power unit controlled by the intelligent terminal i. This represents the heat output power of the combined heat and power unit controlled by the intelligent terminal i. This represents the heat output power of the heat-generating unit controlled by the intelligent terminal i; All are operating cost coefficients for integrated energy systems;

[0112] The gas emission costs of each unit are shown in the following formula:

[0113]

[0114]

[0115]

[0116]

[0117] In the formula, C emission , These represent the total emission cost of the integrated energy system, the total emission cost of the generator set, the total emission cost of the combined heat and power unit, and the total emission cost of the heat-generating unit, respectively. These represent the total cost of carbon dioxide emissions for generator sets, combined heat and power units, and heat-generating units, respectively. These represent the total cost of nitrogen oxide and sulfur oxide emissions from generator sets, combined heat and power units, and heat-generating units, respectively. All are emission cost coefficients for integrated energy systems;

[0118] Step 2.2: Determine the power balance constraints and upper and lower limits of output power for each unit in the integrated energy system;

[0119] The power balance constraints for each unit are shown in the following formula:

[0120]

[0121]

[0122] In the formula, P L With Q L P represents the total electricity and heat load demand of the integrated energy system, respectively. M The exchange power obtained from the distribution network when the integrated energy system is operating in grid-connected mode;

[0123] The upper and lower limits of the output power of each unit are constrained by the following formulas:

[0124]

[0125]

[0126] In the formula, and These represent the lower and upper limits of the electrical output power of the generator set controlled by the intelligent terminal i, respectively. and These are the lower and upper limits of the heat output power of the heat-generating unit controlled by the intelligent terminal i, respectively.

[0127] Step 2.3: Determine the environmental and economic dispatch optimization objectives for the integrated energy system;

[0128] The optimization objective for the environmental and economic dispatch of the integrated energy system is shown in the following formula:

[0129] min[C cost C emission ]

[0130] The multi-objective optimization problem above is transformed into a single-objective optimization problem using the linear weighted sum method. The transformed environmental economic scheduling optimization objective is shown in the following formula:

[0131] min[w1C cost +w2C emission ]

[0132] In the formula, w1 and w2 are the weight factors of the corresponding optimization objectives, and 0≤w1≤1, 0≤w2≤1, w1+w2=1.

[0133] Step 2.4: Solve for the incremental costs of each unit in the integrated energy system;

[0134] The incremental costs of each unit in the integrated energy system are shown in the following formula:

[0135]

[0136]

[0137]

[0138]

[0139] In the formula, These are the incremental costs of electricity generated by generator sets, the incremental costs of electricity generated by combined heat and power (CHP) units, the incremental costs of heat generated by CHP units, and the incremental costs of heat-generating units.

[0140] Step 3: The smart terminal communicates with neighboring smart terminals through the communication module to obtain the online status of each smart neighbor terminal, constructs a LoRa distributed communication network, and generates the power communication topology matrix of the entire integrated energy system. and thermal communication topology matrix

[0141] Based on the constructed LoRa distributed communication network, all power generating units and all heat generating units in the integrated energy system are separated. The communication network of the integrated energy system is divided into topological matrices of power networks and thermal networks, and the corresponding Laplacian matrices are represented as follows: Power communication topology matrix Thermal communication topology matrix Where smart terminal i and smart terminal j are neighboring terminals, then or =1, otherwise or It is 0.

[0142] Step 4: The smart terminal stores the output power and online status of each unit collected in Step 1, as well as the two communication topology matrices of the integrated energy system generated in Step 3, through the data storage module. This data serves as the data source for the LCD display module and the edge server monitoring system display interface. At the same time, the data collection time is stored as historical data.

[0143] Step 5: The smart terminal sends the incremental cost data and output power data of the current smart terminal to the neighboring smart terminal through the multi-terminal collaboration module, and receives the incremental cost data and output power data sent by the neighboring smart terminal.

[0144] Step 6: The smart terminal, through the multi-terminal collaboration module, uses the output power data of neighboring smart terminals and the current smart terminal from Step 5 to execute a finite-time consistent average power calculation algorithm, making the output power data of each smart terminal tend to be consistent; and updates the output power data of the current smart terminal according to the calculation results, and estimates the global electrical output power P of the integrated energy system based on the updated output power data of the current smart terminal. total (t) and global thermal output power Q total (t), global electrical power deviation ΔP(t) and global thermal power deviation ΔQ(t); specifically including the following steps:

[0145] Step 6.1: Determine the weight update factors for the power network and the heating network;

[0146] Based on the Laplacian matrices of the power network and heat network generated in step 3 The weight update factors for the power network and the heating network are expressed as follows:

[0147]

[0148]

[0149] In the formula, These are the weighting factors for the power network and the heating network, respectively. Represents the Laplacian matrix The (k+1)th eigenvalue, Represents the Laplacian matrix The (k+1)th eigenvalue, n P With n Q N represents the number of smart terminals in the power grid and the heating grid, respectively. i Let D be the set of all neighboring terminals of smart terminal i. i Let i be the degree of smart terminal i, that is, the number of smart terminals connected to smart terminal i.

[0150] Based on the above formula, the weight update factor matrix for the power network and the heating network is obtained as follows: and

[0151] Step 6.2: Execute the finite-time consistent average power solution algorithm to make the output power data of each smart terminal tend to be consistent, as shown in the following formula:

[0152]

[0153]

[0154] In the formula, A vector representing net electrical output power. A vector representing net thermal output power;

[0155] After a finite number of iterations, the output power data of each smart terminal will tend to be consistent, even if the output power data of each smart terminal becomes the average value of the output power of each smart terminal.

[0156] Step 6.3: Calculate the global output power and global power deviation of the integrated energy system;

[0157] Because the number of smart terminals in the power grid and the heating grid are n respectively. P With n QThe finite-time consistent average power solution algorithm then goes through n... P -1 and n Q After -1 iterations, the system converges, and the global electrical output power P of the integrated energy system is... total (t) and global thermal output power Q total (t) are respectively:

[0158] P total (t)=n P P(n P )

[0159] Q total (t)=n Q Q(n Q )

[0160] In the formula, P(n) P ) and Q(n Q The finite-time consistent average power solution algorithm takes n steps. P -1 and n Q The convergence value after -1 iterations;

[0161] The global power deviation ΔP and global power deviation ΔQ of the integrated energy system are shown in the following formulas:

[0162] ΔP=P L -P total

[0163] ΔQ=Q L -Q total

[0164] The power deviation is solved in step 7 to obtain the optimal incremental cost. and This will be used as a feedback quantity to coordinate the output power of the equipment in order to achieve power balance.

[0165] Step 7: The smart terminal, through the multi-terminal collaboration module, uses the incremental cost data of the neighboring smart terminal and the local smart terminal in Step 5 and the global power deviation data in Step 6 to execute the finite-time consistency optimal incremental cost solution algorithm, solve and update the local incremental cost data, and calculate the optimal output power of each unit.

[0166] Step 7.1: The smart terminal uses the collaboration module to receive incremental cost data from neighboring terminals, and combines it with global power deviation data to execute a finite-time consensus optimal incremental cost solution algorithm to update the local incremental cost. The specific consensus algorithm is as follows:

[0167]

[0168]

[0169] In the formula, Incremental cost μ P The differential, Incremental cost μ H The derivative, μ0 is the distribution network electricity price, α P and α H It is the control gain, sig(x) m =sgn(x)·|x| m ,0 <m<1;ε P and ε H It is the power regulation coefficient;

[0170] If smart terminal i is connected to the power distribution network, then otherwise The control signal c = 0 indicates that the integrated energy system is connected to the distribution network; if c = 1, the integrated energy system is not connected to the distribution network.

[0171] Step 7.2: Calculate the output power of each unit based on the incremental cost;

[0172] Considering the upper and lower power limits of the solution model for the environmental and economic optimization scheduling problem of the integrated energy system, the electric power of the generator set is calculated according to the following formula. Electric power of cogeneration units Thermal power of cogeneration units and the thermal power of the heat-generating unit

[0173]

[0174]

[0175]

[0176]

[0177] Step 7.3: Calculate the incremental cost of the integrated energy system and the output power of each unit under different weight combinations by changing the weight values ​​of the optimization objectives. Determine whether the output power of each unit is within the constraint range. If it is within the constraint range, the output power is the optimal output power of the unit. If it is not within the constraint range, if it exceeds the upper limit, the upper limit power is taken as the optimal output power of the unit. If it is below the lower limit, the lower limit power is taken as the optimal output power of the unit.

[0178] Step 8: The smart terminal uses the multi-terminal collaboration module to determine whether the error between the updated local incremental cost and the incremental cost of the neighboring terminal exceeds the set threshold ε. If so, steps 5 to 8 are repeated; otherwise, step 9 is executed.

[0179] Step 9: Based on the optimal output power of each unit calculated by each intelligent terminal in Step 7, the corresponding control commands are sent to the corresponding equipment of the integrated energy system through the ARM processor of the multi-terminal collaboration module to adjust its output power.

[0180] Step 10: The smart terminal stores the intermediate data generated by the iteration of the two finite-time consensus algorithms in Step 6 and Step 7, as well as the optimal output power of each unit in Step 9, through the storage module, as the data source for the edge server control query interface.

[0181] Step 11: The LCD display module of the smart terminal and the edge server monitoring system display the operating status of the integrated energy system, the communication topology, and the convergence process of the two finite-time consensus algorithms in real time according to the received data.

[0182] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope defined by the claims of the present invention.

Claims

1. A monitoring and control system for environmental and economic dispatching of integrated energy systems, characterized in that: include: Distributed multiple smart terminals, edge server monitoring systems, and integrated energy systems; The intelligent terminal monitors the operation status of the integrated energy system in real time, collects the operation data of each device in the integrated energy system and uploads it to the edge server monitoring system, establishes a data transmission link with neighboring intelligent terminals to transmit the output power and incremental cost value of the local device controlled by the current intelligent terminal in the integrated energy system, and uses the operating environment economic optimization scheduling algorithm to solve the optimal incremental cost and optimal output power of the local device, and sends control commands to the integrated energy system for adjustment. The environmental economic optimization scheduling algorithm includes a finite-time consistent average power solution algorithm and a finite-time consistent optimal incremental cost solution algorithm. The edge server monitoring system receives real-time operating status data of the integrated energy system collected by distributed intelligent terminals, displays it in the corresponding interface and updates it in real time, and at the same time realizes the functions of generating historical data reports, analyzing the economic efficiency of operation and monitoring energy topology. The integrated energy system provides local device output power and incremental cost data to smart terminals and sends real-time operating status data of the integrated energy system to the edge server monitoring system. At the same time, as a controlled object of multiple distributed smart terminals, it receives control commands issued by them and makes adjustments. The operational environment economic optimization scheduling algorithm solves for the optimal incremental cost of local devices, including: Determine the operating costs and gas emission costs of each unit in the integrated energy system; The operating costs of each unit are shown in the following formula: ； ； ； ； In the formula, , , , These represent the total operating cost of the integrated energy system, the total operating cost of the generator set, the total operating cost of the combined heat and power unit, and the total operating cost of the heat-generating unit, respectively. For distribution network electricity price; The electrical power exchanged between the integrated energy system and the distribution network; , , These respectively represent the collection of generator sets, combined heat and power units, and heat-generating units; , , They represent smart terminals respectively. The operating costs of the controlled generator sets, cogeneration units, and heat-generating units; Indicates smart terminal The electrical output power of the controlled generator set, Indicates smart terminal The electrical output power of the controlled cogeneration unit, Indicates smart terminal The heat output power of the controlled cogeneration unit, Indicates smart terminal The heat output power of the controlled heat-generating unit; , , , , , , , , , , , All are operating cost coefficients for integrated energy systems; The gas emission costs of each unit are shown in the following formula: ； ； ； ； In the formula, , , , These represent the total emission cost of the integrated energy system, the total emission cost of the generator set, the total emission cost of the combined heat and power unit, and the total emission cost of the heat-generating unit, respectively. , , These represent the total cost of carbon dioxide emissions for generator sets, combined heat and power units, and heat-generating units, respectively. , , These represent the total cost of nitrogen oxide and sulfur oxide emissions from generator sets, combined heat and power units, and heat-generating units, respectively. , , , , , , , , , , , , , , , All are emission cost coefficients for integrated energy systems; Determine the environmental and economic dispatch optimization objectives for the integrated energy system; The optimization objective for the environmental and economic dispatch of the integrated energy system is shown in the following formula: ； The multi-objective optimization problem above is transformed into a single-objective optimization problem using the linear weighted sum method. The transformed environmental economic scheduling optimization objective is shown in the following formula: ； In the formula, and For the weight factors corresponding to the optimization objective, and , , ; Solve for the incremental costs of each unit in the integrated energy system; The incremental costs of each unit in the integrated energy system are shown in the following formula: ； ； ； ； In the formula, , , , These are the incremental costs of electricity generated by generator sets, the incremental costs of electricity generated by combined heat and power (CHP) units, the incremental costs of heat generated by CHP units, and the incremental costs of heat-generating units.

2. The monitoring and control system for environmental and economic dispatching of integrated energy systems according to claim 1, characterized in that: The distributed intelligent terminal includes a data acquisition module, a data processing module, a data storage module, a GPS positioning module, a multi-terminal collaboration module, and a communication module. 3.The monitoring control system for economic dispatch of integrated energy system environment according to claim 2, characterized in that: The data acquisition module communicates with each device in the integrated energy system and collects the output power data of each unit in the integrated energy system and the communication topology data of the integrated energy system in real time. The data processing module processes the collected output power data of each unit into incremental cost variables to participate in the iteration of the environmental and economic optimization scheduling algorithm. The data storage module stores the output power and incremental cost data of each unit, the data received from the neighbor's smart terminal, and the historical data of the integrated energy system operation. When the smart LCD display module and the edge server monitoring system display the data in real time, the output power and incremental cost data of each unit and the historical data of the integrated energy system operation are called up. The GPS positioning module uses the real-time positioning function of Beidou / GPS to determine the location of each smart terminal and displays it in real time in the edge server monitoring system; The multi-terminal collaboration module sends the incremental cost variables and local smart terminal information of the local smart terminal to the neighboring smart terminals, and receives information from the neighboring smart terminals through the module. The operating environment economic optimization scheduling algorithm solves for the optimal incremental cost and optimal output power of the local device. The communication module establishes point-to-point long-distance data transmission links between smart terminals through LoRa communication technology, thereby establishing LoRa network distributed communication between smart terminals.

4. The monitoring control system for economic dispatch of integrated energy systems according to claim 3, characterized in that: The data acquisition module also includes an LCD display module, which displays the operating status of each device in the integrated energy system monitored and controlled by each intelligent terminal, the control results of the environmental and economic optimization scheduling algorithm, and the historical operating curves of each device in real time by calling the data stored in the storage module.

5. The monitoring and control system for environmental and economic dispatching of integrated energy systems according to claim 1, characterized in that: The edge server monitoring system includes: a communication topology interface, which receives communication topology data of the integrated energy system uploaded by smart terminals, displays the communication topology diagram between each device and terminal in real time, and monitors the disconnection / reconnection, switching out / connection status of each device and terminal; an operation status monitoring interface, which retrieves real-time data collected by each smart terminal, displays the online status, output power, and incremental cost parameters of each device in the integrated energy system, and updates them in real time; a control query interface, which queries the control commands issued by each smart terminal in real time, as well as the operation curves of each device in the integrated energy system adjusting its power after receiving the control commands; and a historical data query interface, which retrieves historical data stored by smart terminals, and queries historical data reports and curves for any day within the recorded range.

6. A monitoring and control method for environmental and economic dispatch of integrated energy systems, implemented based on the monitoring and control system described in claim 1, characterized in that: Includes the following steps: Step 1: The intelligent terminal collects the output power data of the power generation, heat generation, and combined heat and power units controlled by the local intelligent terminal, as well as the online status of each device; Step 2: The intelligent terminal first standardizes and normalizes the collected data; then, it builds a solution model for the environmental and economic optimization scheduling problem of the integrated energy system. Based on the model and the cost function coefficients and output power of each unit, it solves for the incremental electricity cost corresponding to the output power of each unit. With heat increment cost ; Step 3: the intelligent terminal communicates with neighbor intelligent terminals, obtains online states of each intelligent neighbor terminal, constructs a Lora distributed communication network, and generates a power communication topology matrix of the entire integrated energy system and a heat communication topology matrix ; Step 4: The intelligent terminal stores the output power and online status of each unit collected in Step 1, as well as the two communication topology matrices of the integrated energy system generated in Step 3, as the data source for the display interface of the LCD module and the edge server monitoring system. At the same time, the data collection time is stored as historical data. Step 5: The smart terminal sends the current incremental cost data and output power data of the smart terminal to the neighboring smart terminal, and receives the incremental cost data and output power data sent by the neighboring smart terminal; Step 6: The smart terminal uses the output power data of neighboring smart terminals and the current smart terminal from Step 5 to execute the finite-time consistent average power solution algorithm to make the output power data of each smart terminal tend to be consistent; and updates the output power data of the current smart terminal according to the calculation results, and estimates the global output power and global power deviation of the integrated energy system based on the updated output power data of the current smart terminal. Step 7: The smart terminal, through the multi-terminal collaboration module, uses the incremental cost of the neighboring smart terminal and the local smart terminal in Step 5 and the global power deviation data in Step 6 to execute the finite-time consistency optimal incremental cost solution algorithm, solve and update the local incremental cost data, and calculate the output power of each unit. Step 8: The intelligent terminal judges whether the error between the updated local incremental cost and the incremental cost of the neighbor terminal exceeds the set threshold through the multi-terminal cooperation module , and if yes, repeats steps 5 to 8, otherwise, executes step 9; Step 9: Based on the optimal output power of each unit calculated by each intelligent terminal in Step 7, the corresponding control commands are sent to the corresponding equipment of the integrated energy system through the ARM processor of the multi-terminal collaboration module to adjust its output power. Step 10: The smart terminal stores the intermediate data generated by the iteration of the two finite-time consensus algorithms in Step 6 and Step 7, as well as the optimal output power of each unit in Step 9, through the storage module, as the data source for the edge server control query interface. Step 11: The LCD display module of the smart terminal and the edge server monitoring system display the operating status of the integrated energy system, the communication topology, and the convergence process of the two finite-time consensus algorithms in real time according to the received data.

7. The monitoring control method for economic dispatch of an integrated energy system environment according to claim 6, characterized in that: The specific method for step 2 is as follows: Step 2.1: Determine the operating costs and gas emission costs of each unit in the integrated energy system; The operating costs of each unit are shown in the following formula: ； ； ； ； In the formula, , , , These represent the total operating cost of the integrated energy system, the total operating cost of the generator set, the total operating cost of the combined heat and power unit, and the total operating cost of the heat-generating unit, respectively. For distribution network electricity price; The electrical power exchanged between the integrated energy system and the distribution network; , , These respectively represent the collection of generator sets, combined heat and power units, and heat-generating units; , , They represent smart terminals respectively. The operating costs of the controlled generator sets, cogeneration units, and heat-generating units; Indicates smart terminal The electrical output power of the controlled generator set, Indicates smart terminal The electrical output power of the controlled cogeneration unit, Indicates smart terminal The heat output power of the controlled cogeneration unit, Indicates smart terminal The heat output power of the controlled heat-generating unit; , , , , , , , , , , , All are operating cost coefficients for integrated energy systems; The gas emission costs of each unit are shown in the following formula: ； ； ； ； In the formula, , , , These represent the total emission cost of the integrated energy system, the total emission cost of the generator set, the total emission cost of the combined heat and power unit, and the total emission cost of the heat-generating unit, respectively. , , These represent the total cost of carbon dioxide emissions for generator sets, combined heat and power units, and heat-generating units, respectively. , , These represent the total cost of nitrogen oxide and sulfur oxide emissions from generator sets, combined heat and power units, and heat-generating units, respectively. , , , , , , , , , , , , , , , All are emission cost coefficients for integrated energy systems; Step 2.2: Determine the power balance constraints and upper and lower limits of output power for each unit in the integrated energy system; The power balance constraints for each unit are shown in the following formula: ； ； In the formula, and These represent the total electricity and heat load demand of the integrated energy system, respectively. The exchange power obtained from the distribution network when the integrated energy system is operating in grid-connected mode; The upper and lower limits of the output power of each unit are constrained by the following formulas: ； ； wherein, and are the lower and upper limits of the electric output power of the generator set controlled by the intelligent terminal , and are the lower and upper limits of the heat output power of the heat production set controlled by the intelligent terminal . Step 2.3: Determine the environmental and economic dispatch optimization objectives for the integrated energy system; The optimization objective for the environmental and economic dispatch of the integrated energy system is shown in the following formula: ； The multi-objective optimization problem above is transformed into a single-objective optimization problem using the linear weighted sum method. The transformed environmental economic scheduling optimization objective is shown in the following formula: ； In the formula, and For the weight factors corresponding to the optimization objective, and , , ; Step 2.4: Solve for the incremental costs of each unit in the integrated energy system; The incremental costs of each unit in the integrated energy system are shown in the following formula: ； ； ； ； In the formula, , , , These are the incremental costs of electricity generated by generator sets, the incremental costs of electricity generated by combined heat and power (CHP) units, the incremental costs of heat generated by CHP units, and the incremental costs of heat-generating units. 8.The monitoring control method for economic dispatch of an integrated energy system environment according to claim 7, characterized in that: The specific method for step 6 is as follows: Step 6.1: Determine the weight update factors for the power network and the heating network; The Laplacian matrix of the power network and the heat network generated in step 3 , , the weight update factors of the power network and the heat network are respectively represented as: ； ； In the formula, , These are the weighting factors for the power network and the heating network, respectively. Represents the Laplacian matrix The (k+1)th eigenvalue, Represents the Laplacian matrix The (k+1)th eigenvalue, and These represent the number of smart terminals in the power grid and the heating grid, respectively. Let i be the set of all neighboring terminals of smart terminal i. Let i be the degree of smart terminal i, that is, the number of smart terminals connected to smart terminal i. Based on the above formula, the weight factor matrices for the power network and the heat network are obtained as follows: and ; Step 6.2: Execute the finite-time consistent average power solution algorithm to make the output power data of each smart terminal tend to be consistent, as shown in the following formula: ； ； wherein a vector representing the electric net output power, a vector representing the thermal net output power; After a finite number of iterations, the output power data of each smart terminal will tend to be consistent, even if the output power data of each smart terminal becomes the average value of the output power of each smart terminal. Step 6.3: Calculate the global output power and global power deviation of the integrated energy system; Because the number of smart terminals in the power grid and the heating grid are respectively and The finite-time consistent average power solution algorithm is then processed by... and After several iterations, the system converges, and the global electrical output power of the integrated energy system is obtained. and global thermal output power They are respectively: ； ； In the formula, and The finite-time consistent average power solution algorithm has been passed through and The convergence value after the next iteration; Global power deviation of integrated energy system and global power deviation As shown in the formula below: ； ； The power deviation is solved for the optimal incremental cost in step 7 With will coordinate the device output power as feedback quantities to achieve power balance. 9.The monitoring control method for economic dispatch of an integrated energy system environment according to claim 8, characterized in that: The specific method for step 7 is as follows: Step 7.1: The smart terminal uses the collaboration module to receive incremental cost data from neighboring terminals, and combines it with global power deviation data to execute a finite-time consistency optimal incremental cost solution algorithm to update the local incremental cost; ； ； In the formula, For incremental costs The differential, For incremental costs The differential, For distribution network electricity price, and It is about controlling the gain. ,0 < m < 1; and It is the power regulation coefficient; If smart terminal When connected to the power distribution network, ,otherwise Control signals This indicates that the integrated energy system is connected to the distribution network. Then the integrated energy system is not connected to the distribution network; Step 7.2: Calculate the output power of each unit based on the incremental cost; Considering the upper and lower power limits of the solution model for the environmental and economic optimization scheduling problem of the integrated energy system, the electric power of the generator set is calculated according to the following formula. Electric power of cogeneration units Thermal power of cogeneration units and the thermal power of the heat-generating unit ; ； ； ； ； Step 7.3: Calculate the incremental cost of the integrated energy system and the output power of each unit under different weight combinations by changing the weight values ​​of the optimization objectives. Determine whether the output power of each unit is within the constraint range. If it is within the constraint range, the output power is the optimal output power of the unit. If it is not within the constraint range, if it exceeds the upper limit, the upper limit power is taken as the optimal output power of the unit. If it is below the lower limit, the lower limit power is taken as the optimal output power of the unit.

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