Campus integrated energy system hierarchical control method and system

Abstract

The present application is directed to the optimization control problem of the park comprehensive energy system under the coupling of multiple energy forms, and proposes a park comprehensive energy system hierarchical control method and system. The park comprehensive energy system is divided into a system layer, a device aggregation layer and an element control layer. By aggregating the energy devices, load terminals and control elements in the park according to the energy supply form, energy use characteristics, spatial position and the like, the energy subsystems are used as the energy subsystems to participate in the upper layer "system-device" operation strategy optimization. The energy subsystems of the device aggregation decompose the upper layer control strategy into internal executable commands according to the internal energy structure, so as to realize the control execution of the "device-element" layer.

Description

Technical Field

[0001] This invention belongs to the field of integrated energy system control technology, specifically relating to a hierarchical control method and system for an integrated energy system in a park. Background Technology

[0002] Against the backdrop of dwindling fossil fuel resources, booming renewable energy, and increasingly prominent environmental pollution, the concept of the Energy Internet has emerged and gained widespread acceptance. The Energy Internet can be categorized based on its spatial coverage, such as industrial park energy internet, urban energy internet, and more. Constructing new power system structures and building new energy forms through energy interconnection are currently major research directions. As an important component of the Energy Internet, the integrated industrial park energy system integrates distributed energy production, transmission, conversion, storage, and consumption. Based on a smart grid network, it couples multiple energy systems such as heat, electricity, and gas, and is extensively integrated with internet information technology to achieve on-site consumption of distributed energy in a smart energy network.

[0003] The integrated energy system of the park involves the coordinated operation of various energy sources. These energy types interact through energy conversion devices, resulting in a tightly coupled system. While this enhances the interrelationships between energy types and the flexibility of system operation, it also makes the system's hierarchical structure more complex, leading to more intricate operational analysis. For hierarchical control optimization of the integrated energy system, planning a multi-energy supply subnetwork can meet the diverse needs of users for electricity, gas, cooling, and heating, improve energy efficiency, and promote the coordinated, optimized, and rational utilization of energy resources.

[0004] However, the coordinated control of traditional integrated energy systems mostly focuses on the control of multiple energy systems, achieving complementary utilization of source-end equipment, or comprehensively considering the complementary utilization of energy sources, grids, loads, and storage. Research on such control strategies can provide auxiliary guidance for the operation and control of integrated energy systems, but surveys of domestic integrated energy system demonstration projects in recent years have revealed that most current integrated energy systems only provide strategic guidance and rarely achieve automated control. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a hierarchical control method and system for an integrated energy system in a park. By proposing a hierarchical control method, the optimization control strategy of the integrated energy system is implemented through hierarchical control, step-by-step execution, and closed-loop feedback, guiding the energy optimization control and automated operation of the integrated energy system in the park.

[0006] The present invention adopts the following technical solution:

[0007] This invention provides a hierarchical control method for an integrated energy system in a park, comprising:

[0008] Step 1: Design the hierarchical control structure of the integrated energy system, namely "component-equipment-system", and determine the optimized control task functions and interaction parameters of each layer;

[0009] Step 2: At the system level, the LightGBM algorithm is used to predict the output and electrical, cooling, and heating loads of the renewable energy system.

[0010] Step 3: Aggregate energy equipment, load terminals, and control components according to energy supply form, energy consumption characteristics, and spatial location to obtain energy subsystems and construct intraday-day two-layer optimization model;

[0011] Step 4: Build an equipment operation strategy optimization model at the "equipment-system" layer, and the park's integrated energy system executes the equipment operation strategy;

[0012] Step 5: Based on the characteristics of equipment aggregation in the energy subsystem, design the control execution method for the energy subsystem.

[0013] Preferably, in step 1, a hierarchical control structure of "component-equipment-system" for the integrated energy system is designed, dividing the integrated energy system into a system layer, an equipment aggregation layer, and a component control layer;

[0014] The top layer is the system layer, which is used to formulate the overall energy management strategy for the integrated energy system;

[0015] The middle layer is the device aggregation layer, which is used to coordinate the operation of various energy subsystems. Each energy subsystem will distribute the control commands of each subsystem to the corresponding components or devices in the component layer based on the coordination strategy.

[0016] The bottom layer is the component layer, which is used to execute control commands for components and devices.

[0017] Preferably, in step 3, the energy supply form includes electrical power, cooling power, and heating power, and the energy consumption characteristics include electricity consumption and natural gas consumption. An energy coupling unit is used as a single energy subsystem. The energy coupling unit is a unit that performs energy form conversion. The energy subsystem includes a combined cooling, heating, and power system, a transferable load aggregation system, a park photovoltaic system, a direct-fired refrigeration system, a ground source heat pump system, a terminal air conditioning system, and an electric energy storage system.

[0018] Preferably, in step 3, the intraday-pre-day two-layer optimization model includes:

[0019] Day-ahead scheduling phase: Based on the predicted information of the cooling, heating, and electrical loads of the integrated energy system and the power supply from renewable energy sources within a day, with the goal of minimizing carbon emissions, an optimized scheduling plan is formulated for each hour of the 24-hour period of the integrated energy system. The power provided by each energy subsystem in each hour of the 24-hour period is used as the optimization variable, and the capacity constraints of the equipment, the power constraints during operation, and the power balance constraints of the integrated energy system are used as the constraints. The objective function is formulated according to the specific optimization objective. The input data for solving the problem is the predicted values ​​of the power, heating, and cooling loads and renewable energy sources for 24 hours, as well as the constraints of each piece of equipment during operation and the objective function. The output obtained by the solver is the scheduling plan of the equipment for each hour of the 24-hour period.

[0020] Intraday scheduling phase: Based on the day-ahead scheduling, the output of equipment is adjusted according to the real-time changes in source load. The source load refers to the energy load in the form of electricity, gas, and heat generated by renewable energy sources such as wind turbines and photovoltaic systems. The fluctuating power of the equipment is added to the optimization variables, and the penalty cost caused by the equipment's adjustment due to fluctuation is added to the objective function. Different penalty coefficients are set for different equipment, with the lowest cost as the optimization objective.

[0021] Preferably, step 3 further includes, for the day-ahead scheduling phase, using the data from the previous 12 hours to predict the data for the next hour, and for the intraday rolling optimization phase, using the data from the previous 3 hours to predict the data for the next 15 minutes.

[0022] Preferably, step 3 further includes:

[0023] During the intraday scheduling phase, the start-stop status of the equipment is added to the optimization problem as a 0-1 optimization variable. The start-stop status of the equipment over 24 hours is obtained through optimization and the equipment is controlled accordingly. 0 represents shutdown, in which case the equipment stops running during the time period, and 1 represents startup, in which case the equipment restarts during the time period.

[0024] Preferably, step 4 includes:

[0025] Step 4.1: Based on the predicted value of the source load, the "equipment-system" layer plans the start-up, shutdown and power output of the equipment in each energy subsystem and sends the plan to the control center of each energy subsystem.

[0026] Step 4.2, the "component-equipment" layer decomposes and executes instructions from the "equipment-system" layer for specific energy equipment.

[0027] Preferably, step 5 includes:

[0028] Based on the characteristics of equipment aggregation in the energy subsystem, the design of control execution methods for the energy subsystem is carried out. Meters are added for data monitoring or automatic control systems are used. Energy storage systems are controlled by BMS systems, and geothermal heat pump systems, air source heat pump systems, and lithium bromide units are controlled by PLC systems.

[0029] Preferably, step 5 further includes:

[0030] At the "component-equipment" layer, PID control is used to automatically execute tasks based on the component's execution status. Feedback parameters from monitoring devices of underlying components or equipment are received and corrected. A closed-loop control algorithm is used, and sensors monitor the system's output signal. When an error is detected, the controller's output signal is adjusted according to the magnitude and direction of the error. The control system monitors the switching status, operating status, and instrument parameters of the energy subsystems in real time. Based on the execution status of each energy subsystem, the daily scheduling is adjusted. Each energy subsystem monitors whether the underlying components are operating according to the plan through the control system in real time. If non-execution is detected, an alarm is triggered and manual operation is switched. At the same time, the equipment operation strategy is replanned in the next scheduling period.

[0031] This invention also provides a hierarchical control system for an integrated energy system in a park, the system being the same as the aforementioned hierarchical control method for an integrated energy system in a park, characterized in that it includes:

[0032] The component control layer is used to execute control commands for components and devices.

[0033] The equipment aggregation layer, as the control unit of the upper "equipment-system" layer, is used to comprehensively manage the internal components of each energy subsystem using the corresponding monitoring or control system;

[0034] The system layer is used to design low-carbon collaborative control systems for upper-level energy systems, as well as control and execution systems for lower-level component equipment.

[0035] The beneficial effects of this invention are that, compared with the prior art, by means of the above technical solution, this invention provides a hierarchical control method and system for a park integrated energy system of "component-equipment-system", and this invention has the following beneficial effects:

[0036] 1) This invention addresses the optimization control problem of multiple coupled energy forms in a park's integrated energy system by proposing a hierarchical "component-equipment-system" control method. The integrated energy system is divided into a system layer, an equipment aggregation layer, and a component control layer. Energy equipment, load terminals, and control components within the park are aggregated according to energy supply form, energy consumption characteristics, and spatial location, participating as energy subsystems in the upper-level "system-equipment" operation strategy optimization.

[0037] 2) The energy subsystem of the aggregated equipment decomposes the upper-level control strategy into internal executable commands based on its internal energy structure, realizing control execution at the "equipment-component" level. By proposing a hierarchical control method, the optimized control strategy of the integrated energy system achieves hierarchical control, step-by-step execution, and closed-loop feedback, guiding the energy optimization control and automated operation of the park's integrated energy system. Attached Figure Description

[0038] Figure 1 This is a schematic diagram of the hierarchical control structure of the integrated energy system in the park according to the present invention, which consists of "components-equipment-system".

[0039] Figure 2 This is a schematic diagram of the day-to-day dual-layer optimization model in this invention;

[0040] Figure 3 This is a schematic diagram of the optimized control structure at the "device-system" layer in this invention;

[0041] Figure 4 This is a flowchart of the photovoltaic maximum power point tracking method control in this invention;

[0042] Figure 5 This is a schematic diagram of the PID control process in this invention;

[0043] Figure 6 This is a schematic diagram of the day-ahead dispatching of electrical load in this invention;

[0044] Figure 7 This is a schematic diagram of the day-ahead scheduling of cooling load output in this invention;

[0045] Figure 8 This is a schematic diagram of the daily power load dispatching from 12:00 to 13:45 in this invention;

[0046] Figure 9 This is a schematic diagram illustrating the daily scheduling of cooling load output from 12:00 to 13:45 in this invention.

[0047] Figure 10 This is a schematic diagram of the system layer workflow in this invention. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The embodiments described in this application are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, other embodiments obtained by those skilled in the art without creative effort are all within the protection scope of this invention.

[0049] like Figure 1 As shown, Embodiment 1 of the present invention provides a hierarchical control method for a park integrated energy system, characterized in that it includes:

[0050] Step 1: Design the hierarchical control structure of the park's integrated energy system, and determine the optimization control tasks and interaction parameters of each layer;

[0051] Before formulating an optimization strategy, it is necessary to clarify the specific structure of the system, including the types of equipment it contains, etc. Based on the system structure, modeling and problem description should be carried out, and then comprehensive management should be carried out based on the solution results.

[0052] The design of the park's integrated energy system features a hierarchical control structure of "component-equipment-system". The control structure of the park's integrated energy system divides the integrated energy system into a system layer, an equipment aggregation layer, and a component control layer.

[0053] System layer design includes: designing a low-carbon collaborative control system for the upper-level energy system and a control and execution system for the lower-level components and equipment to achieve low-carbon automated control of the integrated energy system;

[0054] The equipment aggregation layer includes: the energy subsystem of the equipment aggregation layer acts as the specific control unit of the upper "equipment-system" layer and participates in the upper-level optimization strategy; for each energy subsystem, the corresponding internal monitoring system or control system is used to comprehensively manage its internal components, such as BMS system and PLC system, and based on the upper-level guidance strategy, the upper-level control strategy is implemented according to the control characteristics within each energy subsystem.

[0055] The control characteristics include the ability of the geothermal heat pump system to adjust power consumption, efficiency, cooling / heating power, water temperature / flow rate, and start / stop status, and the ability of the gas-fired lithium bromide unit to adjust cooling / heating power and water temperature / flow rate.

[0056] Step 2: At the system level, the LightGBM algorithm is used to predict the output and electrical, cooling, and heating loads of the renewable energy system.

[0057] Step 3: Aggregate the energy equipment, load terminals and control components in the park according to the energy supply form, energy consumption characteristics and spatial location, and carry out comprehensive management of the aggregated energy subsystems to build a two-level optimization model for intraday and day-to-day.

[0058] Typically, three factors are considered: energy supply form, energy consumption characteristics, and spatial location. The energy supply form includes electric / cooling / heating power, and the energy consumption characteristics include electricity and natural gas consumption. A complete energy coupling unit is considered as a single energy subsystem. The coupling unit can convert one form of energy into another. For example, a combined heat and power system includes an internal combustion engine, a waste heat recovery device, and an absorption chiller, which can convert gas into cooling power and heating power.

[0059] The integrated management refers to generating optimized scheduling schemes for different energy subsystems and different time periods of the energy subsystems. The optimized scheduling schemes are mainly divided into day-ahead scheduling and intraday scheduling. The specific steps are as follows: First, based on the forecast of renewable energy output and load, the output of each device is set for each hour of the next 24 hours on the previous day. On the second day, the current renewable energy output and load forecast is updated in real time at a 15-minute cycle, and the output of each device is dynamically adjusted in real time according to the formulated day-ahead scheduling scheme.

[0060] Preferably, the energy aggregation subsystem in step 3 may include, but is not limited to, combined cooling, heating and power systems, transferable load aggregation systems, park photovoltaic systems, direct-fired refrigeration systems, ground source heat pump systems, terminal air conditioning systems, electric energy storage systems and other similar energy systems. Each system is aggregated and classified according to its energy characteristics such as energy supply characteristics, energy consumption characteristics, or spatial location.

[0061] The energy subsystem exhibits input-output relationships of different energy forms. The system layer needs to perform mathematical descriptions based on the physical models of each energy subsystem and use a modeling method based on energy buses to describe the energy coupling form of the entire integrated energy system. Each type of bus connects multiple energy supply devices. Among them, the power bus covers energy supply devices such as internal combustion engines, renewable energy photovoltaic power generation, renewable energy wind power generation, and batteries. The cold and heat energy bus covers energy supply devices such as direct-fired engines, waste heat recovery devices, cold and heat storage devices, electric chillers, and ice storage air conditioners.

[0062] The term "transferable load aggregate" refers to a whole comprised of multiple transferable loads, such as a resource collection of multiple electric vehicle charging stations within a park.

[0063] Among them, the combined energy subsystem includes a combined cooling, heating and power system, which consists of an internal combustion engine power generation unit and an absorption cooling and heating unit. This system has the characteristic of simultaneously meeting the supply of electrical load and air conditioning load by consuming natural gas.

[0064] Among them, the photovoltaic system in the park has the characteristics of clean power generation and unstable power supply;

[0065] Specifically, solar energy is a renewable and clean energy source, and photovoltaic systems cause minimal environmental pollution during operation. However, their power generation is affected by various factors such as weather and sunshine duration.

[0066] Among them, the direct-fired refrigeration system has the characteristics of gas-fired refrigeration and energy supply;

[0067] Specifically, direct-fired engines generate electricity by using the high-temperature flue gas from the combustion of combustion gases to drive the turbine. Meanwhile, the waste heat recovered by the waste heat recovery device can supply the heat load or be further converted into cooling power to supply the cooling load.

[0068] Among them, the transferable load aggregate includes an energy-consuming group composed of electric vehicle charging piles in the park, which has the characteristic of transferable electricity consumption;

[0069] Specifically, this means that, while keeping the total electricity consumption constant, the charging power of electric vehicles and the load during electricity consumption periods can be flexibly adjusted based on information such as time-of-use pricing.

[0070] Among them, the electric energy storage system has the characteristic of energy storage.

[0071] Specifically, this is reflected in the fact that electric energy storage, as an energy storage device, can both output electrical power and store input electrical power.

[0072] Based on the characteristics of the equipment or its internal components, they are aggregated into energy subsystems.

[0073] Preferred, such as Figure 2 As shown, in step 3, the intraday-pre-day two-layer optimization model includes:

[0074] Day-ahead scheduling phase: Based on the predicted information of the cooling, heating, and electrical loads of the integrated energy system and the power supply from renewable energy sources within a day, with the goal of minimizing carbon emissions, an optimized scheduling plan is formulated for each hour of the 24-hour period of the integrated energy system. The power provided by each energy subsystem in each hour of the 24-hour period is used as the optimization variable, and the capacity constraints of the equipment, the power constraints during operation, and the power balance constraints of the integrated energy system are used as the constraints. The objective function is formulated according to the specific optimization objective. The input data for solving the problem is the predicted values ​​of the power, heating, and cooling loads and renewable energy sources for 24 hours, as well as the constraints of each piece of equipment during operation and the objective function. The output obtained by the solver is the scheduling plan of the equipment for each hour of the 24-hour period.

[0075] Intraday scheduling phase: Based on the day-ahead scheduling, the output of equipment is adjusted according to the real-time changes in source load. The source load refers to the energy load in the form of electricity, gas, and heat generated by renewable energy sources such as wind turbines and photovoltaic systems. The fluctuating power of the equipment is added to the optimization variables, and the penalty cost caused by the equipment's adjustment due to fluctuation is added to the objective function. Different penalty coefficients are set for different equipment, with the lowest cost as the optimization objective.

[0076] For the day-ahead scheduling phase, the forecast value used is to predict the data for the next hour using data from the previous 12 hours. For the intraday scheduling phase, the forecast value used is to predict the data for the next 15 minutes using data from the previous 3 hours.

[0077] During the intraday scheduling phase, the start-stop status of the equipment is added to the optimization problem as a 0-1 optimization variable. The start-stop status of the equipment over 24 hours is obtained through optimization and the equipment is controlled accordingly. 0 represents shutdown, in which case the equipment stops running during the time period, and 1 represents startup, in which case the equipment restarts during the time period.

[0078] Step 4: Taking the optimization of the park's low-carbon economic operation as the optimization goal, design an optimization model for the equipment operation strategy at the upper-level "equipment-system" layer;

[0079] like Figure 10 As shown, the system layer constructs a two-level optimization model based on intraday and day-to-day conditions. Each energy subsystem provides electrical / cooling / heating power to the electrical / cooling / heating load. The day-to-day frequency is hourly, and the intraday frequency is every 15 minutes. The solution formulation process is as follows: First, it is necessary to clarify the energy conversion form of each energy subsystem and the constraints during operation, which serve as constraints for the optimization problem (the energy conversion of the entire system should remain balanced). Then, the objective function (cost / low carbon / optimal energy consumption) is formulated, and the output (electrical / cooling / heating power) of each energy subsystem is used as the solution objective. Mathematical optimization methods are then used to solve the problem.

[0080] The energy subsystem obtains power changes from the system level, but it also needs to be accurate down to the control level of each device. However, the control systems used at the underlying level of different energy subsystems are different. Therefore, it is necessary to adjust the control according to different characteristics, such as using PLC control or microcontroller control. At the same time, the parameters to be controlled involved in different devices are also different.

[0081] Preferably, in step 4, with the optimization goal of low-carbon economic operation of the park, the design of the equipment operation strategy optimization model at the upper-level "equipment-system" layer is carried out. The execution process of the low-carbon operation control strategy of the park's integrated energy system includes: the upper-level "equipment-system" strategy control layer, with low carbon as the optimization goal, plans the start-up, shutdown, and output of equipment in each energy subsystem based on short-term and ultra-short-term load forecasts, and distributes the plans to the control centers of each energy subsystem; when optimizing control, the upper-level "equipment-system" strategy control layer needs to comprehensively consider the energy characteristics of each energy subsystem and the interaction between systems, and consider the optimization goal of minimizing the overall carbon emissions and operating costs of the park, so as to achieve the optimization of the overall control strategy of the park's energy system.

[0082] The lower-level "component-equipment" control execution layer, for specific energy equipment, decomposes and executes according to the instructions of the upper level. The energy subsystem is usually regulated by its own automatic control system. For example, the control of the three-generation system is carried out by PLC: The PLC automatic control system can realize the following functions: (1) The user can specify the operating conditions at will, and the control system will automatically control the CCHP to complete the corresponding operating condition conversion and can operate safely under the specified operating conditions; (2) It can realize the acquisition of all parameters of the CCHP system; (3) The user can control the CCHP system to operate in local or remote state. In manual state, only the power distribution cabinet (manual operation cabinet) can be used to realize the system operation; in automatic state, the system will be controlled by the PLC control cabinet or the central monitoring platform.

[0083] Energy efficiency feedback parameters are set in the hierarchical control structure of the "component-equipment-system" of the integrated energy system in the park. These parameters reflect the working status of the component layer, equipment layer, and system layer. When the energy efficiency feedback parameters do not meet the set values, it is determined that the predicted value obtained by the system layer in the integrated energy system of the park has an error. Error information is sent to the "equipment-system" layer, and the predicted values ​​obtained in the structure and system layer of the integrated energy system of the park are corrected according to the energy efficiency feedback parameters.

[0084] The algorithm for predicting new energy output and load uses an LSTM neural network, and feature engineering methods are used to filter the features of the input model to improve the expressive power of the data.

[0085] Equipment start-up and shutdown are typically controlled by setting start-up and shutdown 0-1 variables to participate in the optimization solution process of the model.

[0086] Preferably, in step 4, the specific steps of designing the upper-level equipment operation strategy optimization model include: performing equipment mathematical modeling for each energy subsystem, establishing constraints, defining the objective function, and solving it using a solver. Here, we take... Figure 3 The integrated energy system shown is illustrated, and the modeling method is described in detail:

[0087] Currently, domestic carbon emission allowances are generally allocated on a non-compensatory basis, and the allowances are calculated using a baseline method. Assuming all purchased electricity comes from coal-fired power plants, the main carbon emission sources are: the upstream power grid (coal-fired power plants) and CCHP (CCHP) units. The calculation method is as follows:

[0088]

[0089] E a =E a,grid +E a,CCHP

[0090] In the formula: T is the scheduling period; E a This represents the total initial carbon allowance for the integrated energy system; E a,grid E a,CCHP These are the electricity purchased from higher authorities and the free carbon allowances from CCHP, respectively. These represent the electricity purchased during time period t, the electrical output power of the gas turbine, and the energy supplied (heating or cooling) by the absorption lithium bromide unit; ε e ε h These are the carbon emission allowances per unit of electricity and per unit of heat, respectively, with values ​​of 0.728 t / MWh and 0.102 t / GJ. The conversion factor for converting electricity generation into heat supply is set at 6 MJ / kWh.

[0091] The actual carbon emission sources of the integrated energy system in the park also mainly include coal-fired power units and CCHP units. The calculation method is as follows:

[0092]

[0093] E r =E r,grid +E r,CCHP

[0094] In the formula: E r E represents the actual carbon emissions of the business park. r,grid E r,CCHP These represent the actual carbon emissions of coal-fired power units and CCHP units, respectively; ε r,e ε r,h These are the actual carbon emission coefficients for the power generation of coal-fired power units and the equivalent heat of CCHP units, respectively, with values ​​of 1.08 t / MWh and 0.065 t / GJ.

[0095] The carbon trading cost of an integrated energy system can be expressed as:

[0096]

[0097] In the formula: Let E be the price of carbon trading during period t. r >E a hour, A positive value indicates that the park needs to purchase carbon allowances from the carbon trading market; E r <E a hour, A negative value indicates a surplus of carbon allowances, which can be sold to generate revenue.

[0098] Electric vehicles are studied as transferable loads, assuming that the charging piles are unidirectional and the dispatchable time period is from 9:00 to 18:00.

[0099]

[0100] In the formula, t beg t end These are the start and end times for electric vehicles participating in the scheduling process; P is the charging power of electric vehicles in the time period t before scheduling; ev,c,max The maximum charging power for electric vehicles.

[0101] To avoid frequent equipment start-ups and shutdowns affecting user energy satisfaction, the minimum continuous operating time T needs to be determined. tran,min Apply constraints:

[0102]

[0103] Its power constraint is:

[0104]

[0105] In the formula, t0 represents the starting period for statistical analysis; The variable P represents the load transfer status during time period t, where 1 indicates transfer and 0 indicates no transfer. tran,min P tran,max These represent the minimum transfer power and the maximum transfer power, respectively.

[0106] Compensation cost for transferable load F tran It can be represented as:

[0107]

[0108] In the formula, C tran The compensation cost per unit of transferable load. It is transferred for time period t.

[0109] The heat load is adjustable within a certain range and can participate in optimized scheduling as a flexible load. Heat load Qh during time period t. r t can be represented as:

[0110]

[0111] In the formula, S is the heating area, m²; ω is the heat dissipation coefficient due to the temperature difference between the inside and outside of the building, with a value of 1.037 × 10⁻⁶. 5 J / ㎡℃; These represent the indoor and outdoor temperatures during time period t, respectively.

[0112] To ensure human comfort and user satisfaction with energy consumption, indoor temperature needs to be controlled.

[0113]

[0114] In the formula, These are the upper and lower limits of indoor temperature to meet human comfort, taken as 24℃ and 27.5℃ respectively.

[0115] Thermal flexible loads can be considered as loads that can be reduced, and their compensation cost F cut It can be represented as:

[0116]

[0117] In the formula, C cut Compensation costs for load reduction per unit; These represent the power output before and after load reduction during time period t.

[0118] Considering the impact of carbon trading and flexible loads, the objective function is to minimize the sum of the system's daily energy purchase cost, carbon trading cost, and compensation cost for dispatching flexible loads.

[0119]

[0120] F k =F tran +F cut

[0121] In the formula, F fuel , F k These are energy purchase costs, carbon trading costs, and demand response compensation costs; These are the electricity price and natural gas price for time period t, respectively. These represent the electricity and gas purchased during time period t, respectively.

[0122] Integrated energy systems need to meet overall power balance constraints:

[0123]

[0124] In the formula, Let t be the predicted photovoltaic power generation during time period t; This is the base electrical load for time period t, and it is not adjustable. The charging amount of electric vehicles after the scheduling in time period t. This represents the electrical power consumed by the chiller unit during time period t.

[0125] At the same time, the integrated energy system needs to meet the overall cooling power balance constraint:

[0126]

[0127] In the formula, The cooling capacity of the direct-fired turbine and the chiller unit during time period t are respectively. The basic cooling load for time period t.

[0128] After establishing the optimization variables, objective function, and constraints, a solver is used to solve the optimization problem.

[0129] Step 5: Based on the characteristics of equipment aggregation in the energy subsystem, design the control execution method for the energy subsystem.

[0130] Preferably, in step 5, based on the equipment aggregation characteristics of the energy subsystem, the energy subsystem control execution method is designed, and meters are added for data monitoring or an automatic control system is used. For example, the energy storage system is controlled by a BMS system, and the geothermal heat pump system, air source heat pump system, and lithium bromide unit are controlled by a PLC system.

[0131] In the lower-level "component-device" control execution layer, this invention selects proportional-integral-derivative (PID) control, which automatically executes tasks based on the closed-loop control principle of the underlying components and the execution status of the components. By continuously receiving feedback parameters from underlying components or equipment monitoring devices, and continuously correcting the feedback, precise power control is achieved. Using a closed-loop control algorithm, sensors continuously monitor the system's output signal and compare it with the target value. If an error is detected, the system adjusts the controller's output signal according to the magnitude and direction of the error. The actuator controls the system's behavior based on the controller's output signal, gradually bringing the output signal closer to the expected target. The energy subsystem needs to statistically calculate the execution status of upper-level commands. The control system monitors the switching status, operating status, and measuring instrument parameters of the energy subsystem in real time, and compares whether they are consistent with the expected adjustment effect of the upper-level commands. It provides real-time feedback in the daily plan. Based on the execution status of upper-level commands by each energy subsystem, the daily control strategy is adjusted. Each energy subsystem monitors whether the underlying components are operating according to the plan through the control system in real time. If non-execution is detected, an alarm is triggered and manual operation is switched. At the same time, in the next scheduling time cycle, the equipment re-operation strategy is re-planned to achieve real-time control optimization of the strategy.

[0132] Automatic control systems are typically used to automatically switch operating conditions in energy subsystems. A power logic controller (PLC) is a suitable controller for industrial applications, possessing excellent programming capabilities and anti-interference abilities. It can be used to achieve automatic control and operating condition adjustment of the system. Different energy subsystems employ different control execution methods. For example, photovoltaic systems use maximum power point tracking (MPPT) control, automatically adjusting the operating point of the solar panels based on sunlight conditions to achieve maximum photoelectric conversion efficiency. Heat pump closed-loop control systems specifically employ PID control, changing the refrigerant mass flow rate by adjusting the compressor speed, thereby altering the heat exchange in the condenser and ensuring the heat pump's output power tracks changes in the power setpoint. A diagram of the heat pump's power closed-loop control structure is shown below. Figure 5 As shown.

[0133] For specific control parameters at the control level, the underlying equipment parameters of a heat pump system include compressor speed (r / s), power (kW), outlet hot water temperature (°C), outlet flow rate (kg / s), and feed water flow rate (kg / s). For a combined cooling, heating, and power (CCHP) system, the underlying equipment parameters of the internal combustion engine include fuel quantity (kg / s), power (kW), exhaust gas temperature (°C), flue gas flow rate (kg / s), cylinder liner water inlet temperature (°C), and cylinder liner water outlet temperature (°C). The system-level day-ahead and day-ahead equipment output information is as follows: Figure 6-9 As shown, for example, during the period from 12:00 to 13:45, the charging load of electric vehicles was transferred and the cooling load was reduced. At the equipment control level, it is necessary to adjust the start and stop of electric vehicle charging piles and the charging power, as well as the air supply temperature and air volume of flexible air conditioners. The control details of each equipment parameter obtained by the equipment aggregation layer based on the output are shown in the table below.

[0134] 12:00-13:45 Control parameter details for flexible air conditioning

[0135]

[0136] 12:00-13:45 Control Parameter Details of Electric Vehicle Charging Stations

[0137] Details of control parameters for the chiller unit during the time period 12:00-13:45

[0138]

[0139] Example 2 provides a specific case study based on a grid-connected integrated energy system in a certain industrial park. The load in this park consists of electrical load and air conditioning load, and the relevant integrated energy equipment includes photovoltaics, charging piles, direct-fired turbines, chillers, or other integrated energy equipment.

[0140] The energy systems are categorized and grouped according to their energy supply characteristics, energy consumption characteristics, or spatial location within the park. The resulting energy subsystems include photovoltaic systems, electric vehicle controllable load systems, direct-fired turbine systems, chiller systems, and flexible air conditioning terminal systems.

[0141] They can be classified according to the characteristics of energy supply, such as supplying electrical load, gas load, cooling load, and heating load; the characteristics of energy consumption, such as whether the energy input on the primary side of the equipment is electrical energy or gas; and the spatial location can be distinguished as indoor or outdoor.

[0142] In this system, all the photovoltaic panels in the park are connected to the park's power system through a single inverter, and the photovoltaic system is controlled by the inverter.

[0143] To ensure that photovoltaic cells maximize power output under various environmental conditions, the Maximum Power Point Tracking (MPPT) method can be used. This involves adjusting the voltage of the photovoltaic array under different ambient temperatures and light conditions to position the photovoltaic power generation system at its maximum power point. Common MPPT control methods include the perturbation-observation method and the incremental conduction method. The perturbation-observation method actively applies a small perturbation to the current voltage and uses the direction of change in output power to determine the location of the maximum power point. The incremental conduction method is based on the fact that the output power-voltage relationship curve has only one extreme point; the maximum power point is determined by the rate of change of the output power versus voltage curve.

[0144] Among them, the electric vehicle charging piles in the park are aggregated into a unified controllable load system for scheduling by the upper-level energy system;

[0145] Among them, the direct-fired turbine system and the chiller system include their respective power supply units and their supporting water pumps, electric valves, temperature control equipment, cooling tower systems, monitoring equipment, etc.

[0146] Among them, the flexible air conditioning terminal system includes the central air conditioning system in each area of ​​the building, covering equipment components such as thermostats, fan coil units, fans, and monitoring devices;

[0147] The design includes a hierarchical control structure for the park's integrated energy system, comprising "components-equipment-systems," defining the optimized control tasks and interaction parameters for each layer. The hierarchical control structure is as follows: Figure 1 As shown, the aggregated equipment system in the equipment aggregation layer includes a photovoltaic system, a controllable load system for electric vehicles, a direct-fired turbine system, a chiller system, and a flexible air conditioning terminal system. The system layer distributes the output and start-up / shutdown strategies of each energy subsystem to the respective subsystems. Each subsystem decomposes the strategy instructions into control instructions for each component or internal device for execution. Components within each subsystem feed back control information to the energy system through monitoring devices, and the energy subsystems then feed back the power control results to the system strategy layer.

[0148] The top layer is the system layer, responsible for formulating the overall energy management strategy for the integrated energy system, including scheduling and optimization of different energy subsystems and different time periods within the system, and transmitting strategy instructions to the equipment aggregation layer. The middle layer is the equipment aggregation layer, responsible for coordinating the operation of various energy subsystems, ensuring they operate according to the guidance strategy of the system layer. Simultaneously, each energy subsystem will distribute control instructions to specific components or devices in the component layer based on the coordination strategy. The bottom layer is the component layer, responsible for executing the control of specific components and devices. For the system layer, the interaction parameters are the established day-ahead and intraday power output plans; for the component layer, the interaction parameters are the monitoring data at the bottom level of the equipment components. The energy aggregation layer is responsible for the intermediate conversion.

[0149] The start-stop strategy determines whether to enable a device by adding a device start-stop variable when defining the optimal scheduling at the system level. This is typically a two-dimensional variable, where 1 represents start and 0 represents stop. During the optimization process, the power control result is obtained through mathematical optimization methods.

[0150] Different energy subsystems contain different equipment, and the data collected will also differ. For example, the underlying equipment parameters of a heat pump system include compressor speed (r / s), power (kW), outlet hot water temperature (°C), outlet flow rate (kg / s), and feed water flow rate (kg / s). The underlying equipment parameters of the internal combustion engine in a combined cooling, heating, and power system include fuel quantity (kg / s), power (kW), exhaust gas temperature (°C), flue gas flow rate (kg / s), cylinder liner water inlet temperature (°C), and cylinder liner water outlet temperature (°C).

[0151] The power control result is the equipment operating status data collected by the acquisition device, which usually compares whether the current output is consistent with the set value.

[0152] Among these, with the optimization goal of low-carbon economic operation of the park, the design of an equipment operation strategy optimization model for the upper-level "equipment-system" layer was carried out. The optimization control structure of the "equipment-system" layer is as follows: Figure 3 As shown, considering both carbon trading costs and the operating costs of each energy subsystem, a two-tiered optimization model (intraday-day and day-ahead) is constructed to optimize the system's power output strategy.

[0153] In the aforementioned intraday-day dual-layer optimization model, the intraday optimization is the upper layer, with a scheduling cycle of 24 hours. This means that based on forecast data, the output of each device for each hour of the following day is determined the day before. The intraday optimization is the lower layer, typically with a scheduling cycle of 1 hour or 15 minutes. Based on the intraday scheduling, it adjusts the device output in real-time for a specific time period within a day, taking into account real-time changes in source load. The source load refers to the energy load in the form of electricity, gas, and heat generated by renewable energy sources such as wind turbines and photovoltaic systems. In practice, intraday scheduling is performed first, followed by intraday scheduling based on the results of the intraday scheduling. Electricity prices vary at different times, and different devices have different energy consumption characteristics. The costs of all energy subsystems are calculated and summarized separately, serving as the objective function for system scheduling to solve the optimization problem.

[0154] Specifically, during the day-ahead scheduling phase, the optimization objective is to minimize carbon trading costs and the operating costs of each energy subsystem, thereby optimizing the hourly output strategy of each energy subsystem. For the intraday optimization strategy, the output strategy is continuously optimized based on the intraday load fluctuations, referencing the day-ahead optimization results.

[0155] Using the current output of each device as the variable to be optimized, the carbon emissions of each energy subsystem are calculated and summarized according to the emission factor method. The optimization objective is to minimize the total carbon emissions, and the optimization solution is obtained.

[0156] For the intraday scheduling phase, fluctuation amounts are set, and a certain penalty is imposed on these fluctuations. The penalty cost is also included in the objective function for joint optimization. The intraday fluctuation of equipment output power is added as an optimization variable to the solution of the optimization problem. A certain fluctuation penalty is set for the power fluctuation of each device. Specifically, power fluctuations will cause equipment adjustments, and adjusting equipment requires a certain cost. The penalty cost is the sum of the fluctuation power of all energy subsystems multiplied by the adjustment cost. The penalty cost is added to the optimization objective. In the optimization solution process, in order to minimize the objective function, the fluctuation of equipment output power will be minimized as much as possible, so that the energy subsystems operate with the minimum deviation from the daily plan.

[0157] Among them, for the energy subsystem layer, it accepts the energy control strategy of each energy subsystem from the upper layer for intraday optimization and decomposes it into the control execution strategy of internal components.

[0158] Upper-level strategies typically refer to the output of each device, usually a certain amount of electrical, cooling, and heating power. The energy subsystem needs to further map power changes to the device control level based on the operating principles of each device. After knowing the system's output changes, the system layer will convert the power changes into adjustments to the state of the underlying components according to specific formulas. Taking heat load as an example, if the heat load is reduced, it will affect the various energy systems that provide heat power. The system will recalculate and adjust the output of each energy system, ultimately resulting in a decrease in the gas / electricity consumption of the equipment, or a decrease in the supply and return water temperature of the water pump or a reduction in water flow.

[0159] For photovoltaic (PV) systems, the PLC controller's control model for the inverter is divided into MPPT (Maximum Power Point Tracking) control and CVC (Constant Voltage Control). Upper-level control commands for the PV system include switching control modes and controlling internal power. For internal power control, the following algorithm is used: by continuously monitoring the PV's voltage and current to calculate the current power output, the voltage value is continuously adjusted to achieve maximum power point tracking. The specific control flow of this algorithm is as follows: Figure 4 As shown.

[0160] The specific formula is as follows:

[0161]

[0162] In flexible air conditioning terminal systems, load control strategy commands issued by the upper level to the air conditioning terminals are realized by controlling the air supply volume. When the load issued by the upper level changes or the indoor environmental parameter setpoints change, the system will automatically adjust the air supply volume and adjust the controlled area to a stable state according to the setpoints of environmental parameters such as temperature and humidity.

[0163] The formula for calculating the air volume of a variable air volume (VAV) air conditioning system is as follows:

[0164]

[0165] In the formula, Q represents the air supply volume, in meters (m³). 2 / h,L k ρ represents the indoor cooling load, in kW; ρ is the air density, in m³. 2 / kg, where c is the specific heat capacity of air at constant pressure, in kJ / (kg·℃); t n t s The room temperature and supply air temperature are in °C.

[0166] In the electric vehicle controllable load system, the charging status of each charging pile is monitored in real time. Power commands from the upper layer are then applied to each charging pile according to the rules of evenly distributed or cyclic charging, enabling specific start-stop and power control. The charging pile control system outputs a PWM signal with a variable duty cycle to the on-board charging device via the control guide circuit. Adjusting the PWM duty cycle adjusts the continuous power supply current output by the charging pile. According to national standard GB / T18487.1, when the duty cycle is within the range of 10% to 85%, the charging current provided by the AC charging pile is linearly proportional to its output duty cycle, thereby adjusting the output power of the electric vehicle. In practice, the charging pile can be controlled by directly issuing target current information, achieving charging power control through target current control. The mathematical equations of the PWM rectifier can be used to describe the on and off times of the switching devices. Assuming the switching frequency of the PWM rectifier is f and the on time is T... on The disconnection time is T. off Then a complete switching cycle is T = T on +T off According to the definition of PWM, the on-time T on and disconnection time T off The relationship with a period T can be expressed by the following formula.

[0167] T on =D×T

[0168] T off = (1-D)×T

[0169] Where D is the duty cycle, representing the on-time T of the switching device. on The duty cycle D, which occupies a period T, can be adjusted by controlling the width of the PWM signal, thereby controlling the output current of the PWM rectifier. The output current of the PWM rectifier can be calculated using the following mathematical equation:

[0170]

[0171] Among them, V peak The peak voltage of the input AC current is given by V, and L is the inductance value of the filter inductor. peak When L is constant, the output current I of the PWM rectifier out The relationship between the duty cycle D and the duty cycle is linear.

[0172] For direct-fired chiller systems and chiller systems, the upper level typically issues cooling or heating power commands to each energy subsystem. For air conditioning main unit systems, comprehensive control of the combined equipment is generally required. When the chiller main unit power changes, the power of its supporting cooling tower fans, the frequency of cooling water circulating pumps, etc., must be adjusted accordingly. Equipment manufacturers generally equip auxiliary equipment such as cooling towers with a control system that automatically adjusts based on the main unit power. Therefore, the control command execution for direct-fired chiller systems and chiller systems only focuses on the start-up and shutdown and power control of the main unit, and the start-up and shutdown control of the cooling tower system. The control function table is shown below:

[0173]

[0174] The formula is as follows:

[0175]

[0176] In the formula, △T refers to the temperature difference between the inlet and outlet water of the chiller unit, and FL W This refers to the inlet and outlet water flow rates, 4.2 × 10⁻⁶. 3 It is the specific heat capacity of water, 3.5991 × 10⁻⁶. 3 It is the conversion factor between Joules and kilowatts. When the water flow rate is constant, the temperature difference determines the cooling power.

[0177] Embodiment 3 of the present invention provides a hierarchical control system for a park integrated energy system, comprising:

[0178] The component control layer is used to execute control commands for components and devices.

[0179] The equipment aggregation layer, as the control unit of the upper "equipment-system" layer, is used to comprehensively manage the internal components of each energy subsystem using the corresponding monitoring or control system;

[0180] The system layer is used to design low-carbon collaborative control systems for upper-level energy systems, as well as control and execution systems for lower-level component equipment.

[0181] The beneficial effect of this invention is that, compared with the prior art, by means of the above technical solution, this invention provides a hierarchical control method and system for a park integrated energy system, namely, "component-equipment-system".

[0182] 1) This invention addresses the optimization control problem of multiple coupled energy forms in a park's integrated energy system by proposing a hierarchical "component-equipment-system" control method. The integrated energy system is divided into a system layer, an equipment aggregation layer, and a component control layer. Energy equipment, load terminals, and control components within the park are aggregated according to energy supply form, energy consumption characteristics, and spatial location, participating as energy subsystems in the upper-level "system-equipment" operation strategy optimization.

[0183] 2) The energy subsystem of the aggregated equipment decomposes the upper-level control strategy into internal executable commands based on its internal energy structure, realizing control execution at the "equipment-component" level. By proposing a hierarchical control method, the optimized control strategy of the integrated energy system achieves hierarchical control, step-by-step execution, and closed-loop feedback, guiding the energy optimization control and automated operation of the park's integrated energy system.

[0184] This disclosure can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this disclosure.

[0185] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0186] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0187] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0188] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A hierarchical control method for an integrated energy system in a park, comprising: Step 1: Design the hierarchical control structure of the integrated energy system, namely "component-equipment-system", and obtain the optimized control task functions and interaction parameters of each layer; Step 2: At the system level, the LightGBM algorithm is used to predict the output and electrical, cooling, and heating loads of the renewable energy system. Step 3: Aggregate energy equipment, load terminals, and control components according to energy supply form, energy consumption characteristics, and spatial location to obtain energy subsystems and construct intraday-day two-layer optimization model; The intraday-pre-day two-layer optimization model includes: Day-ahead scheduling phase: Based on the predicted information of the cooling, heating, and electrical loads of the integrated energy system and the power supply from renewable energy sources within a day, with the goal of minimizing carbon emissions, an optimized scheduling plan is formulated for each hour of the 24-hour period of the integrated energy system. The power provided by each energy subsystem in each hour of the 24-hour period is used as the optimization variable, and the capacity constraints of the equipment, the power constraints during operation, and the power balance constraints of the integrated energy system are used as the constraints. The objective function is formulated according to the specific optimization objective. The input data for solving the problem is the predicted values ​​of the power, heating, and cooling loads and renewable energy sources for 24 hours, as well as the constraints of each piece of equipment during operation and the objective function. The output obtained by the solver is the scheduling plan of the equipment for each hour of the 24-hour period. Intraday scheduling phase: Based on the day-ahead scheduling, the output of the equipment is adjusted according to the real-time changes of the source load. The source load refers to the energy load in the form of electricity, gas and heat generated by the renewable energy power generation of wind turbines and photovoltaic systems. The fluctuating power of the equipment is added to the optimization variables, and the penalty cost caused by the adjustment of the equipment due to the fluctuation is added to the objective function. Different penalty coefficients are set for different equipment, with the lowest cost as the optimization objective. Step 4: Build an equipment operation strategy optimization model at the "equipment-system" layer, and the park's integrated energy system executes the equipment operation strategy; Step 5: Based on the characteristics of equipment aggregation in the energy subsystem, design the control execution method for the energy subsystem.

2. The hierarchical control method for a comprehensive energy system in a park according to claim 1, characterized in that: In step 1, a hierarchical control structure of "component-equipment-system" for the integrated energy system is designed, dividing the integrated energy system into a system layer, an equipment aggregation layer, and a component control layer; The top layer is the system layer, which is used to formulate the overall energy management strategy for the integrated energy system; The middle layer is the device aggregation layer, which is used to coordinate the operation of various energy subsystems. Each energy subsystem will distribute the control commands of each subsystem to the corresponding components or devices in the component layer based on the coordination strategy. The bottom layer is the component layer, which is used to execute control commands for components and devices.

3. The hierarchical control method for a comprehensive energy system in a park according to claim 2, characterized in that: In step 3, the energy supply forms include electrical power, cooling power, and heating power, and the energy consumption characteristics include electricity consumption and natural gas consumption. An energy coupling unit is considered as a single energy subsystem. The energy coupling unit is a unit that performs energy form conversion. The energy subsystem includes a combined cooling, heating, and power system, a transferable load aggregation system, a park photovoltaic system, a direct-fired refrigeration system, a ground source heat pump system, a terminal air conditioning system, and an electric energy storage system.

4. The hierarchical control method for a comprehensive energy system in a park according to claim 3, characterized in that: Step 3 further includes, for the day-ahead scheduling phase, the prediction value used is to predict the data for the next hour using the data from the previous 12 hours; for the intraday rolling optimization phase, the prediction value used is to predict the data for the next 15 minutes using the data from the previous 3 hours.

5. A hierarchical control method for a comprehensive energy system in a park according to claim 4, characterized in that: Step 3 also includes: During the intraday scheduling phase, the start-stop status of the equipment is added to the optimization problem as a 0-1 optimization variable. The start-stop status of the equipment over 24 hours is obtained through optimization and the equipment is controlled accordingly. 0 represents shutdown, in which case the equipment stops running during the time period, and 1 represents startup, in which case the equipment restarts during the time period.

6. The hierarchical control method for a comprehensive energy system in a park according to claim 5, characterized in that: Step 4 includes: Step 4.1: Based on the predicted value of the source load, the "Equipment-System" layer plans the start-up, shutdown and power output of the equipment in each energy subsystem and sends the plan to the control center of each energy subsystem. Step 4.2: The "Component-Equipment" layer decomposes and executes instructions from the "Equipment-System" layer for specific energy equipment.

7. The hierarchical control method for a comprehensive energy system in a park according to claim 6, characterized in that: Step 5 includes: Based on the characteristics of equipment aggregation in the energy subsystem, the design of control execution methods for the energy subsystem is carried out. Meters are added for data monitoring or automatic control systems are used. Energy storage systems are controlled by BMS systems, and geothermal heat pump systems, air source heat pump systems, and lithium bromide units are controlled by PLC systems.

8. The hierarchical control method for a comprehensive energy system in a park according to claim 7, characterized in that: Step 5 further includes: At the "component-equipment" layer, PID control is used to automatically execute tasks based on the component's execution status. Feedback parameters from monitoring devices of underlying components or equipment are received and corrected. A closed-loop control algorithm is used, and sensors monitor the system's output signal. When an error is detected, the controller's output signal is adjusted according to the magnitude and direction of the error. The control system monitors the switching status, operating status, and instrument parameters of the energy subsystems in real time. Based on the execution status of each energy subsystem, the daily scheduling is adjusted. Each energy subsystem monitors whether the underlying components are operating according to the plan through the control system in real time. If non-execution is detected, an alarm is triggered and manual operation is switched. At the same time, the equipment operation strategy is replanned in the next scheduling period.

9. A hierarchical control system for an integrated energy system in a park, operating a hierarchical control method for an integrated energy system in a park as described in any one of claims 1-8, characterized in that, include: The component control layer is used to execute control commands for components and devices. The equipment aggregation layer, as the control unit of the upper "equipment-system" layer, is used to comprehensively manage the internal components of each energy subsystem using the corresponding monitoring or control system; The system layer is used to design low-carbon collaborative control systems for upper-level energy systems, as well as control and execution systems for lower-level component equipment.

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