A method for optimizing the control of the device state of a regional energy system

Abstract

The present invention discloses a method for optimizing the control of the state of equipment in a district energy system, including: evaluating the operating states of each internal device in the district energy system and whether the system reaches power balance according to the acquired data information; performing optimization calculations considering the operating states of the entire system and its internal devices and issuing control instructions; after the control execution device receives the regulation instruction, it is necessary to judge whether the adjustable capacity is sufficient; if so, proceed to the next step; if not, the device is made to maintain its current state, and after re-performing the optimization calculation, the regulation instruction is issued again. The present invention enables energy system managers to monitor and judge the start-stop states of controlled objects in the energy system and the operating state of the system in real time, which is beneficial to the real-time and effective maintenance of equipment; during the regulation process, it can consider whether the real-time adjustable capacity of the unit can meet the requirements of real-time regulation, effectively improving the accuracy and effectiveness of the optimization control instruction.

Description

Technical Field

[0001] The present invention relates to the technical field of energy system optimization, and particularly relates to a method for optimizing the control of the state of equipment in a regional energy system. Background Art

[0002] When the proportion of renewable energy in the regional integrated energy system is very high, the dynamic observation and tracking control technology of the operating states of various power generation units and load units is extremely important. The traditional control method of formulating plans based on renewable energy prediction data and load prediction data is difficult to adapt to the access of a high proportion of renewable energy in the regional integrated energy system.

[0003] At present, scholars at home and abroad have carried out many studies on the optimization control problem of the regional integrated energy system, mainly focusing on system planning, system modeling, and improvement of optimization solution algorithms with the goals of economic operation and new energy consumption. There are many current improvement methods for the model. There is a two-layer site selection and sizing planning model with the minimum upper-layer network loss and the optimal economy within the full life cycle of the lower layer. There is also a TES economic benefit model constructed considering energy storage, renewable energy output, and P2G in the regional integrated energy system. Some scholars have considered electricity storage, gas storage, electric network topology, gas network topology, and P2G to establish a collaborative planning model. Some scholars start from another aspect, considering the coupling of multiple energy types such as electricity-gas, electricity-heat, and electricity-heat-gas, and conduct modeling research on the system optimization control with the goal of economic optimization. Everyone has further analyzed the complementary characteristics and collaborative optimization potential of each energy subsystem and established an integrated energy flow solution model. Some scholars have also established a joint control model including new energy, energy storage, and CCHP systems, which can effectively reflect the impact of the randomness of new energy output on the system, or use information entropy to measure the particle richness, and propose an improved particle swarm optimization algorithm based on particle dimension entropy combined with a greedy mutation strategy.

[0004] In the process of researching and practicing this method, the inventor of the present invention found the following deficiencies: ① Energy system managers cannot monitor and judge the start-stop state of controlled objects in the energy system and the operating state of the system in real time, which is not conducive to accurately controlling the energy system in real time; ② In the control process, the real-time adjustable capacity of the unit is not considered to meet the needs of real-time control, and real-time effective control cannot be achieved. Summary of the Invention

[0005] The present invention provides a method for optimizing the control of the equipment state of a regional energy system, which can monitor the start-stop states of regional power generation equipment and load equipment throughout the process. Its regulation strategy can achieve the traction control of the operating states of each unit throughout the process and complete the optimization and balance control of the system at the second level. Moreover, this method can fully consider whether the adjustable capacity of the controlled object can meet the requirements of real-time regulation during the actual regulation process, so as to achieve reasonable, accurate and effective real-time optimization regulation. The monitoring of the power generation unit and the load unit in the present invention refers to the observation of the operating state and the tracking control of the state regulation process, which is conducive to considering the start-stop change state, real-time active power and capacity information of the equipment in the region, maintaining the real-time power balance of the regional integrated energy system, and completing the accurate and effective traction of the optimal state of the controlled object in the entire operation process of the energy system.

[0006] The present invention provides a method for optimizing the control of the equipment state of a regional energy system, including:

[0007] Step 1: At the specified regulation moment, obtain the output power, equipment capacity information, adjustable state variables and relevant constraint conditions of each physical node of the regional integrated energy system.

[0008] The output power of each unit is specifically expressed as:

[0009] 1. The expressions for the output electric power, thermal power and cooling power of a combined cooling, heating and power (CCHP) unit are as follows:

[0010]

[0011]

[0012]

[0013]

[0014] Among them, is the electric power output by the CCHP unit, is the thermal power output by the CCHP unit, is the cooling power output by the CCHP unit, is the gas-electric conversion efficiency of the gas turbine, is the thermoelectric conversion efficiency after passing through the waste heat boiler and heat exchanger, is the cooling power conversion efficiency after passing through the waste heat boiler and absorption refrigeration unit, is the percentage of the volume of natural gas input to the gas turbine in the total volume of natural gas, represents the heat generated by the combustion conversion of natural gas input to the combined heat and power system. V is the volume of natural gas, is the calorific value of natural gas (using the lower calorific value of natural gas, 37.62 MJ / m3 (approximate calculation).

[0015] 2. The output power of the fan is:

[0016]

[0017] where represents the electric power output by the fan; is the air volume (unit: ); is the total pressure of the fan (unit: ); is the internal efficiency coefficient of the fan, generally taking 0.75 - 0.85, is the mechanical efficiency coefficient, and the value varies with different connection methods of the blades and the motor, generally taking 0.85 - 1; the calculated is in the unit of kw.

[0018] 3. The output power of the photovoltaic array is:

[0019]

[0020] where is the electric power output by the photovoltaic array, and N is the number of photovoltaic panels; is the surface area of the photovoltaic panel; is the standard light intensity; is the photoelectric conversion efficiency; is the fill factor, generally taking 80% for estimation.

[0021] 4. Heat load model:

[0022]

[0023] where represents the time, represents the user's heating / cooling power demand, represents the operating state of the heat load.

[0024] 5. Electric load model:

[0025]

[0026] where represents the time, represents the active power demand of the load, represents the operating state of the load.

[0027] Step 2: Evaluate the operating status of each device within the regional energy system and whether the system reaches power balance based on the acquired data information; if so, issue a regulation command to maintain the current operating status of each physical node; if not, perform an optimization calculation on the output power of each device according to the calculated unbalanced power and issue a regulation command to each device. The judgment of the operating status of each unit and the calculation of the unbalanced power are specifically expressed as follows:

[0028] a. Wind turbine generator:

[0029]

[0030] Define the operating status of the wind turbine generator as , indicating the driving wind speed of the wind turbine at time

[0031] b. Photovoltaic panel:

[0032]

[0033] Define the operating status of the photovoltaic panel as , indicating the light intensity received by the photovoltaic panel at time and

[0034]

[0035]

[0036] In the formula, indicates the operating status of the combined cooling, heating and power unit, indicating the real-time active power of the controlled object unit ; indicates the rated electrical load in the system;

[0037] d. Electrical load:

[0038]

[0039] Define the operating status of the electrical load as , and it can be divided into adjustable load and non-adjustable load according to whether the electrical load can perform demand response.

[0040] e. Thermal load:

[0041]

[0042] Define the operating status of the thermal load as , according to whether the heat load can perform demand response, it is divided into adjustable and non - adjustable loads.

[0043] f. Calculate the unbalanced power of the power supply system and the heating / cooling system respectively, and then judge the operating state of the energy system, which is specifically expressed as:

[0044] ① Calculate the unbalanced power

[0045] The unbalanced power of the system at the sampling moment is , represents the real - time active power of the controlled object unit ; is the row vector composed of the active power combinations of the associated nodes of the controlled object in the data storage unit at this sampling moment; if the node type is a generator, the power value is positive; if the node type is a load, the power value is negative.

[0046] ② Power supply system

[0047]

[0048] Among them, represents the total load in the control area where the controlled object is located.

[0049] ③ Heating / cooling system

[0050]

[0051] Among them, represents the total load in the control area where the controlled object is located.

[0052] Step 3: After the control execution device receives the regulation instruction, judge whether the regulation capacity is sufficient; if so, go to the next step; if not, keep the device in its current state, re - perform the optimization calculation and then issue the regulation instruction again.

[0053] The judgment of whether the capacity is sufficient is specifically expressed as follows:

[0054]

[0055] In the formula, represents the real - time active power of the controlled object ; represents the optimized calculation regulation power of the decision - making unit; represents the upper capacity limit of the controlled object .

[0056] The constraint conditions and objective function required for generating the regulation instruction are specifically expressed as follows:

[0057] (1)Objective function

[0058]

[0059] Among them, is the weighted matrix, representing the energy supply shares of different measurement nodes for the regional integrated energy system; is the real-time output power of each node, that is, the sampled value; represents the ideal planned output power of each node. The optimization objective function is the weighted least squares of the residuals between the real-time output power and the ideal planned output power.

[0060] (2) Constraint conditions

[0061] It includes the inequality constraints of the unit operating status and the capacity inequality constraints of the information system equipment, which are specifically as follows:

[0062] 1) Energy generation unit

[0063] i. Wind turbine

[0064] The output of the wind turbine is restricted:

[0065]

[0066] In the formula, , respectively represent the minimum and maximum output powers of the wind turbine; represents the active power injected by the wind turbine into the power system at this moment.

[0067] ii. Photovoltaic panel

[0068] The output of the photovoltaic panel is restricted:

[0069]

[0070] In the formula, , respectively represent the minimum and maximum output powers of the photovoltaic panel; represents the active power injected by the photovoltaic panel into the power system at this moment.

[0071] iii. Cogeneration unit

[0072] The cogeneration unit is subject to output and ramping rate limitations:

[0073]

[0074]

[0075]

[0076] In the formula, , respectively represent the minimum and maximum power outputs of the combined heat and power unit 、 respectively represent the minimum and maximum heat outputs of the combined heat and power unit represents the maximum ramp rate of the combined heat and power unit

[0077] 2) Energy transmission network

[0078] 2A. Power grid model

[0079] Consider the energy transmission limit of the line:

[0080] wherein, represents the transmission capacity of the line between node i and node j at time t, represents the energy transmission capacity limit of the line between the two nodes

[0081] 2B. Heat network model

[0082] Consider the energy transmission limit of the heat network:

[0083] wherein, represents the heat energy transmitted by the line between node i and node j at time t, represents the heat energy transmission limit of the line between the two nodes

[0084] 2C. Cold network model

[0085] Consider the energy transmission limit of the cold network:

[0086] wherein, represents the cooling power transmitted by the line between node i and node j at time t, represents the cooling capacity transmission limit of the line between the two nodes

[0087] Step Four: After the control execution device receives and completes the achievable regulation instruction, it waits to enter the next regulation moment

[0088] Beneficial effects: As can be seen from the above technical solutions, since the embodiment of the present invention adopts a method for optimizing the control of the state of regional energy system equipment, it can realize real-time state monitoring of regional energy equipment, complete the regulation of each unit at the second level, achieve the traction control of the equipment throughout the whole process and all time periods, and improve the supply capacity of regional energy equipment to the load section and the consumption capacity of new energy

[0089] Among them, step one can realize the real-time monitoring of the operation of the regional integrated energy system and obtain the start-stop state and adjustment state of the controlled objects in the energy system; step two decides whether optimization calculation is needed and issues optimization control instructions by judging the operation states of all devices and the whole system in the regional energy system; step three can ensure that all control instructions obtained from real-time optimization calculation are within the adjustment capacity range of the unit operation, thereby realizing effective power regulation control; after step four completes the real-time regulation during this period, it continues to enter the optimization control of the equipment state of the regional energy system in the next period to ensure that the state of the equipment in the whole operation domain is always in the best state. BRIEF DESCRIPTION OF THE DRAWINGS

[0090] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for description in the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0091] Figure 1 is a flowchart of a method for optimizing the control of the equipment state of a regional energy system according to the present invention;

[0092] Figure 2 is a power grid structure diagram;

[0093] Figure 3 is a heat network structure diagram. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0094] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0095] As shown in Example 1, the present invention provides a method for optimizing the control of the equipment state of a regional energy system, which can realize the real-time monitoring and regulation of energy equipment in the region. Embodiments of the present invention also provide corresponding example analyses, which will be described in detail below.

[0096] In the considered regional integrated energy system, the power generation units mainly rely on clean energy, supplemented by the public power grid. The natural gas input is connected to the public gas network. The physical information of each unit in the power grid and the cold / hot network is collected, and the corresponding node topology diagram is constructed. The electric load parameters are represented by a typical bar chart based on the daily electricity consumption in summer in the park, adopting the typical "three peaks and three valleys" characteristics of the summer load. For simplicity, it is considered that the electric load remains unchanged within each hour, and the daily load curves of each load node are the same.

[0097] The present invention discloses a method for optimizing the control of the equipment state in a regional energy system, which specifically includes the following steps:

[0098] Step 1: At the specified regulation moment, obtain the output power, equipment capacity information, adjustable state variables, and relevant constraint conditions of each physical node in the regional integrated energy system.

[0099] The output power of each unit is specifically expressed as:

[0100] 1. The expressions for the output electric power, thermal power, and cooling power of the combined cooling, heating, and power (CCHP) unit are as follows:

[0101]

[0102]

[0103]

[0104]

[0105] Among them, is the electric power output by the CCHP unit, is the thermal power output by the CCHP unit, is the cooling power output by the CCHP unit, is the gas-electric conversion efficiency of the gas turbine, is the thermoelectric conversion efficiency after passing through the waste heat boiler and heat exchanger, is the cooling power conversion efficiency after passing through the waste heat boiler and absorption chiller, is the percentage of the volume of natural gas input to the gas turbine in the total volume of natural gas, represents the heat generated by the combustion conversion of natural gas input into the combined heat and power system. V is the volume of natural gas, is the calorific value of natural gas (approximately calculated using the lower calorific value of natural gas, 37.62 MJ / m 3 ).

[0106] 2. The output power of the fan is:

[0107]

[0108] Among them, represents the electric power output by the fan; is the air volume (unit: ); is the total pressure of the fan (unit: ); is the internal efficiency coefficient of the fan, generally taking 0.75 - 0.85, is the mechanical efficiency coefficient, with different values for different connection methods of the blades and the motor, generally taking 0.85 - 1; the calculated is in the unit of kW.

[0109] 3. The output power of the photovoltaic array is:

[0110]

[0111] Among them, is the electric power output by the photovoltaic array, is the number of photovoltaic panels; is the surface area of the photovoltaic panel; is the standard light intensity; is the photoelectric conversion efficiency; is the fill factor, generally taking 80% for estimation.

[0112] 4. Heat load model:

[0113]

[0114] Among them represents the time, represents the user's heating / cooling power demand, represents the operating state of the heat load.

[0115] 5. Electric load model:

[0116]

[0117] Among them represents the time, represents the active power demand of the load, represents the operating state of the load.

[0118] Taking the electric network as an example, based on the typical bar chart of the daily electricity consumption in the park in summer and using the above information - physical fusion regional integrated energy state optimization control model, the power source node state information is as follows:

[0119]

[0120] From this, the physical information of the operating states of each output unit in the region can be clearly obtained.

[0121] Step 2: Evaluate the operating status of each device within the regional energy system and whether the system reaches power balance based on the acquired data information; if so, issue a regulation command to maintain the current operating status of each physical node; if not, optimize the output power of each device according to the calculated unbalanced power and issue a regulation command to each device. The judgment of the operating status of each unit and the calculation of the unbalanced power are specifically expressed as follows:

[0122] a. Wind turbine generator:

[0123]

[0124] Define the operating status of the wind turbine generator as , indicating the driving wind speed of the wind turbine at time

[0125] b. Photovoltaic panel:

[0126]

[0127] Define the operating status of the photovoltaic panel as , indicating the light intensity received by the photovoltaic panel at time and

[0128] c. CCHP unit:

[0129]

[0130] In the formula, indicates the operating status of the CCHP unit, indicates the real-time active power of the controlled object unit and represents the rated electrical load in the system;

[0131] d. Electrical load

[0132]

[0133] Define the operating status of the electrical load as , and it can be divided into adjustable load and non-adjustable load according to whether the electrical load can perform demand response.

[0134] e. Thermal load

[0135]

[0136] Indicates the operating state of the heat load, which is divided into adjustable and non - adjustable loads according to whether the heat load can perform demand response.

[0137] Based on the typical bar chart of the daily electricity consumption in the park in summer and using the above - mentioned cyber - physical integrated regional integrated energy state optimization control model, the load node state information is as follows in the table:

[0138]

[0139] Thus, the real - time operating states of various devices in the region at the current moment can be clearly obtained.

[0140] f. Calculate the unbalanced power of the power supply system and the heating / cooling system respectively, and then judge the operating state of the energy system, which is specifically expressed as:

[0141] ① Calculate the unbalanced power

[0142] The unbalanced power of the system at the sampling moment is , represents the real - time active power of the controlled object unit ; is the row vector composed of the active power of the associated nodes of the controlled object in the data storage unit at this sampling moment. If the node type is a generator, the power value is positive; if the node type is a load, the power value is negative

[0143] ② Power supply system

[0144]

[0145] Among them, represents the total load in the regulation area where the controlled object is located.

[0146] ③ Heating / cooling system

[0147]

[0148] Among them, represents the total load in the regulation area where the controlled object is located.

[0149] Step 3: After the control execution device receives the regulation instruction, judge whether the adjustment capacity is sufficient; if so, go to the next step; if not, keep the device in its current state, re - perform the optimization calculation, and then send the regulation instruction again.

[0150] Based on the typical bar chart of the daily electricity consumption in the park in summer and using the above - mentioned cyber - physical integrated regional integrated energy state optimization control model, according to the real - time information of the power generation side and the load, analyze the network power balance situation, calculate and send the regulation instruction as follows:

[0151]

[0152] The calculated adjustment command can achieve real-time precise control of the energy system. If the capacity is sufficient, a "completion of adjustment" signal is sent, and the responding unit completes the output adjustment. If the capacity is insufficient, a "insufficient adjustment capacity" signal is sent, the corresponding unit maintains the current state, and the decision-making unit recalculates the control plan. The judgment of whether the capacity is sufficient is specifically expressed as follows:

[0153]

[0154] In the formula, represents the real-time active power of the controlled object unit ; represents the optimized calculated adjustment power of the decision-making unit; represents the controlled object 's capacity upper limit.

[0155] The specific constraints and objective functions required for generating the control command are as follows:

[0156] (1) Objective function

[0157]

[0158] Among them, is the weighting matrix, representing the energy supply share of different measurement nodes in the regional integrated energy system; is the real-time output power of each node, that is, the sampled value; represents the ideal planned output power of each node. The optimization objective function is the weighted least squares of the residual between the real-time output power and the ideal planned output power.

[0159] (2) Constraints

[0160] It includes inequality constraints on the operating state of the unit and capacity inequality constraints on the information system equipment, which are specifically as follows:

[0161] 1) Energy generation unit

[0162] i. Wind turbine generator

[0163] The output of the wind turbine generator is restricted:

[0164]

[0165] In the formula, and respectively represent the minimum and maximum output powers of the wind turbine generator; represents the active power injected by the wind turbine into the power system at this moment.

[0166] ii. Photovoltaic panel

[0167] The output of the photovoltaic power generation panel is limited:

[0168]

[0169] In the formula, 、 respectively represent the minimum and maximum output powers of the photovoltaic power generation panel; represents the active power injected by the photovoltaic power generation panel into the power system at this moment.

[0170] iii. Cogeneration unit

[0171] The cogeneration unit is subject to output and ramp rate limitations:

[0172]

[0173]

[0174]

[0175] In the formula, 、 respectively represent the minimum and maximum powers of the electric energy output by the cogeneration unit, 、 respectively represent the minimum and maximum powers of the thermal energy output by the cogeneration unit, represents the maximum ramp rate of the cogeneration unit.

[0176] 2) Energy transmission network

[0177] 2A. Power grid model

[0178] Consider the energy transmission limit of the line:

[0179] Among them, represents the i and j transmission capacity of the line between nodes at t time, represents the transmission capacity limit of the line between two nodes.

[0180] 2B. Heat network model

[0181] Consider the energy transmission limit of the heat network:

[0182] Among them, represents the i and j transmission thermal energy of the line between nodes at t time, Indicates the limit of heat energy transmission in the line between two nodes.

[0183] 2C. Cold network model

[0184] Consider the limit of energy transmission in the cold network:

[0185] Wherein, represents the cold power transmission of the line between node i and node j at time t, represents the limit of refrigerating capacity transmission in the line between two nodes.

[0186] Based on the above constraints and capacity limitations, the adjustment results at the current moment are as follows, and the time for the electrical network to complete the above regulation process is 1508.21 milliseconds:

[0187]

[0188] It can be seen from this table that the method of the present invention can consider whether the real-time adjustable capacity of the unit can meet the requirements of real-time regulation, and thus achieve real-time effective regulation.

[0189] Step 4: After the control execution device receives and completes the achievable regulation instruction, it waits to enter the next regulation moment.

[0190] It should be noted that the information interaction, execution process, etc. between the various units in the above device and system, due to being based on the same concept as the embodiment of the method of the present invention, the specific content can be referred to the description in the embodiment of the method of the present invention, and will not be elaborated here.

[0191] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium can include: read-only memory (ROM, Read Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disk, etc.

[0192] The above has introduced in detail a method for optimizing the control of the state of a regional energy system device provided by the embodiments of the present invention. Specific examples are used in this article to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. A method for optimizing the control of the state of a regional energy system device, characterized in that, Including: Step 1: At the specified regulation moment, obtain the output power, equipment capacity upper limit information, adjustable state variables, and relevant constraint conditions of each physical node of the regional integrated energy system; Step 2: Evaluate the operating status of each device within the regional energy system based on the data information obtained in Step 1 to facilitate real-time observation of the device operation; meanwhile, determine whether the regional energy system reaches power balance; if the regional energy system is power balanced, issue a regulation instruction to maintain the current operating status of each physical node; if the regional energy system is power unbalanced, optimize the output power of each device according to the calculated unbalanced power and issue a regulation instruction to each device; Step 3: After the control execution device receives the regulation instruction, determine whether the adjustment capacity is sufficient; if so, proceed to the next step; If not, keep the device in its current state, recalculate the regulation plan after optimization, and issue the regulation instruction again; Step 4: After the control execution device receives and completes the achievable regulation instruction, wait to enter the next regulation moment; The unbalanced power of the system at the sampling moment is , is the active power of the controlled object unit at the sampling moment, is the row vector formed by the active power of the associated nodes of the controlled object in the data storage unit at this sampling moment; if the node type is a generator, the power value is positive; if the node type is a load, the power value is negative; Power supply system ， Among them, represents the total load within the regulation area where the controlled object is located; Heating / cooling system ， Among them, represents the total load in the regulation area where the controlled object is located.

2. The method for optimizing the control of the equipment state of the district energy system according to claim 1, wherein: In Step 2, determine the start-stop status and adjustable status of wind turbines, photovoltaic panels, and combined heat and power units within the regional energy system, and real-time judge the operation of each physical device, which is specifically expressed as: a. Wind turbine: ， In the formula, represents the driving wind speed of the wind turbine at time is the operating state of the wind power generation unit; b. Photovoltaic panel: ， In the formula, represents the light intensity received by the photovoltaic power generation panel at a certain moment, is the minimum light intensity for starting the photovoltaic power generation panel, is the operating state of the photovoltaic power generation panel; c. Combined heat and power unit: ， In the formula, represents the operating state of the combined cooling, heating and power unit, represents the controlled object unit of the real-time active power; represents the rated electrical load in the system; d. Electrical load ， Define the operating state of the electrical load as , and classify it into adjustable load and non-adjustable load according to whether the electrical load can perform demand response; e. Heat load ， Indicates the operating status of the heat load, which is divided into adjustable and non-adjustable loads according to whether the heat load can perform demand response.

3. The method for optimizing the control of the equipment state of the district energy system according to claim 1, wherein: In Step 3, if the capacity is sufficient, send a "regulation completed" signal, and the response unit completes the output regulation; if the capacity is insufficient, send a "insufficient regulation capacity" signal, the corresponding unit maintains its current state, and the decision-making unit recalculates the regulation plan; the method for the control execution device to determine whether the regulation capacity is sufficient is as follows: ， In the formula, represents the real-time active power of the controlled object unit ; represents the optimized calculation regulation power of the decision-making unit; represents the upper limit of the capacity of the controlled object.

4. The method for optimizing the control of the equipment state of the district energy system according to claim 1, characterized in that: Fully consider the real-time start-stop and regulation status of each physical operating device within the regional energy system, can reflect the operating status of the regional energy system at any time and perform optimized regulation, making the control of energy system devices more accurate and effective.

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