Internet of things communication-based park power grid energy comprehensive management and control system and management and control method

Abstract

The invention relates to a system for electric energy comprehensive regulation and control of a park power grid and a regulation and control method using the system, and the regulation and control method comprises the steps: S1, a data collection module of a terminal collection and regulation system collects environment data related to energy efficiency, and transmits the data to an energy management system through a communication module, thereby achieving real-time data synchronization; s2, the energy management system receives and gathers the energy consumption data transmitted by the terminal acquisition and regulation system, and performs data analysis; s3, the energy management system predicts photovoltaic power generation and load power based on historical data, environmental data and market information; s4, the park energy management system gives a dynamic time-of-use electricity price according to the day-ahead net load power prediction curve in combination with the supply-demand relationship and each distributed energy price; s5, based on a pre-established model, combining the dynamic time-of-use electricity price, and adopting a master-slave game method to solve a scheduling scheme; and S6, the terminal acquisition and regulation system receives the control instruction issued by the energy management system.

Description

Technical Field

[0001] The energy comprehensive control system and control method of the park power grid based on Internet of Things communication of the present invention relate to a system for comprehensive electric energy control of the park power grid, and a method for control using the system. Background Art

[0002] With the development of society, the consumption of electric energy is getting higher and higher, both at the production and consumption ends. At the same time, with the rise of new energy power generation technology, higher requirements are put forward for the stable operation of the power grid. However, due to the natural instability of new energy power generation and the uncertainty of power consumption, such as tight urban electricity consumption and large-scale power outages, the mismatch between planned electricity consumption and power generation, and uneven electricity load periods, there is a contradiction between supply and demand and waste of resources. When the power grid is running, it is necessary to improve the comprehensive energy utilization rate, reduce operating costs, and smooth out the peaks and fill the valleys. For the State Grid, the peak-to-valley difference of load can be reduced and the voltage and frequency fluctuations can be alleviated, thereby maintaining the safe and stable operation of the grid side. At present, there is no technical solution that can well carry out comprehensive regulation of the power grid, so it is necessary to design a new technical solution to meet the actual regulation needs. Summary of the invention

[0003] In view of this, the present invention provides a park-level comprehensive energy management and control terminal procurement and dispatching system based on Internet of Things communication and edge computing, so as to solve the problems of traditional park energy management systems with single functions, lack of intelligent scheduling management methods, and single communication methods and poor scalability of terminal procurement and dispatching systems, and has good use and promotion effects.

[0004] The present invention is based on the integrated power management system of the park power grid based on the Internet of Things communication, including an energy management system (EMS for short), a terminal procurement and dispatching system and an energy storage system (ESS for short); wherein the management system is electrically connected to the terminal procurement and dispatching system and the energy storage system respectively, the terminal procurement and dispatching equipment collects relevant data from the consumer end, and uploads the data to the energy management system, and the energy management system combines the data from the consumer end and the data from the energy storage system for comprehensive analysis and regulation.

[0005] The energy management system includes a data processing module, a prediction module, and an intelligent scheduling module, wherein the data processing module is responsible for receiving data uploaded by the terminal device and passing the processed results to the prediction module; the prediction module obtains the processing result data from the data processing module and passes the prediction results to the intelligent scheduling module; the intelligent scheduling module calculates the optimized scheduling plan instructions based on the prediction results and sends them to the terminal procurement and dispatching system.

[0006] The data processing module is responsible for receiving and summarizing the real-time energy consumption data collected by the terminal acquisition and dispatching system, and cleaning, formatting and analyzing the data to ensure the accuracy and completeness of the data.

[0007] The prediction module generates dynamic prediction results of future energy consumption and cost based on historical data, provides a basis for formulating reasonable scheduling plans, and realizes accurate planning of energy supply and intelligent regulation of load.

[0008] The intelligent scheduling module dynamically generates energy distribution and load control plans within the park based on real-time data, prediction results and optimization algorithms to achieve load balancing and energy saving and consumption reduction.

[0009] The terminal acquisition and dispatching system includes a data acquisition module, a communication module, and a control execution module. The data acquisition module collects external data and uploads the data to the energy management system in real time through the communication module. The energy management system sends the dispatching instructions to the control execution module through the communication module, and the control execution module adjusts the operating status of the equipment according to the dispatching instructions.

[0010] The data acquisition module collects power generation data, energy storage charging and discharging data, park and power grid interaction data, and park users' energy load data;

[0011] Photovoltaic power generation data, energy storage charging and discharging data, park and power grid interaction data, and park users' energy load data are collected through photovoltaic inverters, energy storage converters, smart meters, and electric energy meters. The energy storage converter is connected to the park's battery energy storage equipment. When the photovoltaic power generation exceeds the park's load demand, the excess electricity is converted into direct current through the control of the energy storage converter and stored in the battery.

[0012] The communication module uses the Internet of Things communication technology to realize the connection between the energy management system and the terminal acquisition and dispatching system, and the terminal acquisition and dispatching system and the park energy equipment. The communication methods include broadband optical fiber, RS485 wired connection and ZigBee short-distance wireless network connection.

[0013] The control execution module is responsible for receiving instructions from the energy management system and implementing control operations on on-site equipment. In addition, it is also equipped with edge computing function. After obtaining the collected information, edge computing can pre-process the data, which helps to reduce the computing burden of the energy management system. In addition, edge computing completes the entire process of data analysis, decision-making and instruction issuance at the edge, shortening the response time. In the case of network delays or instability, it can still ensure the effective coordination and response of equipment within the park.

[0014] The energy storage system is a rechargeable battery.

[0015] The control method of the integrated power management system of the park power grid based on the Internet of Things communication is:

[0016] Step S1: The data acquisition module of the terminal acquisition and dispatching system collects environmental data related to energy efficiency to assist the energy management system in making optimal decisions. In addition, the operating parameters and operating status of the access in the park are collected, and the data is transmitted to the energy management system through the communication module to achieve real-time data synchronization with the energy management system;

[0017] Specifically, in step S1, the environmental data include temperature, humidity and light intensity; the operating parameters include photovoltaic, energy storage and energy load parameters.

[0018] Step S2: The energy management system receives and summarizes the energy consumption data transmitted by the terminal acquisition and dispatching system, performs data analysis, and stores the historical energy consumption data in a database to support long-term tracking and management of the data;

[0019] Step S3: The energy management system predicts the photovoltaic power generation and load power of the park on the next day based on historical data, environmental data and market information, and generates a net load power prediction curve;

[0020] Step S4: The park energy management system provides a dynamic time-of-use electricity price for users in the park based on the net load power forecast curve of the day before, combined with the current supply and demand relationship and the prices of various distributed energy sources;

[0021] S4.1 Further, the specific calculation method of dynamic time-of-use electricity price is as follows:

[0022]

[0023] in, represents the time-of-use electricity price of the park before the optimization of the price mechanism; c pv 、c ess They are photovoltaic power generation quotation and energy storage discharge quotation respectively; P t pv is the photovoltaic power at time t; P t grid is the power of the power grid at time t; K s is the unbalanced power exchange cost coefficient between the park and the external power grid;

[0024]

[0025] Among them, ρ t Indicates the time-of-use electricity price of the park after the price mechanism is optimized; the supply-demand relationship coefficient is introduced to guide the user demand side to respond to the load stabilization When the park is in a period of insufficient supply, a higher value is taken; when supply exceeds demand, a smaller value is taken to reduce the electricity price and encourage users to use electricity during the valley period of electricity price; K flu is the price fluctuation coefficient caused by load changes.

[0026] Step S5: Establish a model of the park's shiftable load, transferable load, reducible load, and energy storage charging and discharging, and combine it with dynamic time-of-use electricity prices, fully consider the interests of both the park and the user, and use the master-slave game method to solve the optimal energy scheduling plan;

[0027] Specifically, step S5 includes:

[0028] S5.1 Calculation of the power of the shiftable load before and after dispatch;

[0029] S5.2 Calculation of transferable loads

[0030] S5.3 Calculation of load that can be reduced

[0031] S5.4 Design the conditions that the charging of the ESS energy storage system should meet within an EMS dispatch cycle;

[0032] S5.5 calculates the time-of-use electricity price;

[0033] S5.6 Construct the maximum daily operating profit objective function of the park;

[0034] S5.7 Construct the minimum daily cost function.

[0035] S5.1 Further, for the shiftable load, due to the constraints of the production process, it can only be shifted within the shiftable time interval. The total power consumption before and after the shift remains unchanged, but the total power cost changes. The power before and after the shiftable load scheduling is as follows:

[0036]

[0037] T par.i =[t par-.i ,t par+.i ]

[0038] τ i ∈[t par-.i ,t par+.i -D par.i ]

[0039] i∈(1, 2, 3, ...)

[0040] in, represents the power distribution vector of the i-th shiftable load before dispatching, The power during the first start-up period; st i represents the start-up period of the i-th movable load before scheduling; represents the power distribution vector of the ith load after scheduling; T par.i is the dispatchable period of the ith shiftable load, t par-.i With t par+.iThey represent the beginning and end of the dispatchable period of the i-th shiftable load respectively; τ i represents the first start-up period of the ith shiftable load after scheduling; D par.i is the duration before the i-th load dispatch.

[0041] S5.2 For transferable loads such as washing machines and dishwashers:

[0042]

[0043] T tra.j =[t tra-.j ,t tra+.j ]

[0044] j∈(1, 2, 3, ...)

[0045] in, represents the power vector of the jth transferable load in one cycle before optimization; P t tra.j is the load of the jth transferable load at time t after scheduling; If the value of is 1, it means that the power of the jth device at time t has been transferred; if it is 0, it means that the power of this device at time t is 0; and Characterizes the power boundary of the transferable power of the jth device; T tra.j is the acceptable transfer period for the jth device; t tra-.j With t tra+.j They represent the beginning and end of the transfer period of the j-th device respectively.

[0046] S5.3 For loads that can be reduced to a certain extent, such as air conditioning and lighting:

[0047]

[0048] μ k ∈(0,1)

[0049] in represents the power distribution vector of the kth reducible load in one cycle before scheduling; P t cut.k* With P t cut.k Respectively represent the power of the kth device before and after scheduling in period t; μ k is the reduction degree of the kth device, which varies with the importance of the device; introduce the variable like If it is 1, it means that the kth removable device is removed in time period t, otherwise the kth device does not participate in the scheduling in time period t.

[0050] S5.4 Further, within an EMS dispatch cycle, the charging conditions of the ESS energy storage system should meet the following conditions:

[0051]

[0052] The charging rate of ESS is:

[0053]

[0054] In an EMS dispatch cycle, the discharge conditions of the ESS energy storage system should meet the following conditions:

[0055]

[0056] P t pv ≤P t load

[0057] Then the discharge rate of the ESS energy storage system is:

[0058]

[0059] in, and are the rated charging and discharging power of the energy storage unit; P t load is the actual load power at time t; P t load* is the forecast load for the day; represents the grid electricity price at time t. They represent the valley and peak values ​​of the grid electricity price respectively; Indicates the sensitivity coefficient of the energy storage system to peak and valley electricity prices, It indicates the sensitivity coefficient of the energy storage system to peak and valley loads.

[0060] The specific calculation method of S5.5 dynamic time-of-use electricity price is as follows:

[0061]

[0062] in, represents the time-of-use electricity price of the park before the optimization of the price mechanism; c pv 、c ess They are photovoltaic power generation quotation and energy storage discharge quotation respectively; P t pv is the photovoltaic power at time t; P t grid is the power of the power grid at time t; K s is the unbalanced power exchange cost coefficient between the park and the external power grid;

[0063]

[0064] Among them, ρ t Indicates the time-of-use electricity price of the park after the price mechanism is optimized; the supply-demand relationship coefficient is introduced to guide the user demand side to respond to the load stabilization When the park is in a period of insufficient supply, a higher value is taken; when supply exceeds demand, a smaller value is taken to reduce the electricity price and encourage users to use electricity during the valley period of electricity price; K flu is the price fluctuation coefficient caused by load changes.

[0065] The total operating profit objective function of the park energy system under the time-of-use electricity price mechanism mainly includes the park's electricity sales revenue, maintenance costs, operating costs, and the cost of unbalanced power exchange with the external power grid. Maintenance costs include the maintenance costs of new energy power generation and ESS energy storage system maintenance costs, and operating costs include the cost of purchasing electricity from the power grid. S5.6 Further, the maximum daily operating profit objective function of the park is constructed as:

[0066]

[0067] In the formula, In the formula, In the formula,

[0068] where F ems represents the daily total revenue function of the park under EMS scheduling; F ess Represents the charging cost of the energy storage unit; F ma is the maintenance cost; F grid K is the cost of unbalanced power exchange with the external grid; pv K is the photovoltaic array maintenance cost coefficient; ess.c With K ess.d Respectively represent the depreciation and maintenance cost coefficient of the energy storage unit; ρ t grid It is the time-of-use electricity price of the power grid.

[0069] S5.7 The minimum daily cost function for users is:

[0070]

[0071] in, is the electricity cost of the nth user in a cycle; is the power consumption of the i-th user in period t; is the electricity price of the i-th user in period t.

[0072] The master-slave game method is used to balance the interests of the two main bodies, the park and the user. The park acts as a leader and the user acts as a follower. The park can maximize its profits by predicting the degree of user response and optimizing its own strategy; the user adjusts its energy consumption according to the park strategy to minimize the cost; by solving the Stackelberg equilibrium point, a strategy combination that can meet the needs of both parties is found.

[0073] Step S6: The terminal acquisition and dispatching system receives the control instructions issued by the energy management system, ensures that the instructions are transmitted to the control execution module in a timely and accurate manner, and the communication module sends the control instructions to various energy devices in the park to achieve control.

[0074] A computer device includes a memory and a processor, wherein the memory stores a computer program, and is characterized in that the memory stores the computer program, and when the processor executes the computer program, the control method of the energy comprehensive control system of the campus power grid based on Internet of Things communication is implemented.

[0075] A computer-readable storage medium having a computer program stored thereon, wherein the storage medium includes a stored program, wherein when the program is running, the device where the storage medium is located is controlled to execute the control method of the energy comprehensive control system of the campus power grid based on Internet of Things communication. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below.

[0077] Figure 1 It is a flow chart of the coordinated control between the terminal acquisition and dispatching system and the energy management system in an embodiment of the present invention.

[0078] Figure 2 It is a block diagram of the architecture of a park-level comprehensive energy management and control terminal acquisition and dispatching system based on Internet of Things communication and edge computing provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0079] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the following will be combined with the appended drawings of the embodiments. Figure 1-2 , a clear and complete description of the technical solutions in the embodiments of the present invention is given.

[0080] Refer to the attached Figure 2 The present invention provides an integrated power management system for a park power grid based on Internet of Things communication, including: a terminal acquisition and dispatching system including a data acquisition module, a communication module, and a control execution module; an energy management system including a data processing module, a prediction module, and an intelligent dispatching module.

[0081] Furthermore, the photovoltaic array is connected to the photovoltaic inverter through a power transmission line, and the photovoltaic inverter is connected to the energy management system through a communication transmission line; the ESS energy storage system is connected to the energy storage converter through a power transmission line, and the energy storage converter is connected to the energy management system through a communication transmission line; the external power grid is connected to the smart meter through a power transmission line, and the smart meter is connected to the energy management system through a communication transmission line; the rigid load and flexible load of each park user are connected to the electric energy meter deployed on the user, and then the electric energy meter is connected to the energy management system through a communication transmission line.

[0082] Combine the following Figure 1 The control method of the integrated power management system of the park power grid based on the Internet of Things communication of the present invention is described in detail, which specifically includes the following steps:

[0083] Step S1: The data acquisition module of the terminal acquisition and dispatching system collects environmental data related to energy efficiency to assist the energy management system in making optimal decisions. In addition, the operating parameters and operating status of the access in the park are collected, and the data is transmitted to the energy management system through the communication module to achieve real-time data synchronization with the energy management system;

[0084] Step S2: The energy management system receives and summarizes the energy consumption data transmitted by the terminal acquisition and dispatching system, performs data analysis, and stores the historical energy consumption data in a database to support long-term tracking and management of the data;

[0085] Step S3: The energy management system predicts the photovoltaic power generation and load power of the park on the next day based on historical data, environmental data and market information, and generates a net load power prediction curve;

[0086] Step S4: The park energy management system provides a dynamic time-of-use electricity price for users in the park based on the net load power forecast curve of the day before, combined with the current supply and demand relationship and the prices of various distributed energy sources;

[0087] Furthermore, the specific calculation method of dynamic time-of-use electricity price is as follows:

[0088]

[0089] in, represents the time-of-use electricity price of the park before the optimization of the price mechanism; c pv 、c ess They are photovoltaic power generation quotation and energy storage discharge quotation respectively; P t pv is the photovoltaic power at time t; P t grid is the power of the power grid at time t; K s is the unbalanced power exchange cost coefficient between the park and the external power grid.

[0090]

[0091] Among them, ρ t Indicates the time-of-use electricity price of the park after the price mechanism is optimized; the supply-demand relationship coefficient is introduced to guide the user demand side to respond to the load stabilization When the park is in a period of insufficient supply, a higher value is taken; when supply exceeds demand, a smaller value is taken to reduce the electricity price and encourage users to use electricity during the valley period of electricity price; K flu is the price fluctuation coefficient caused by load changes.

[0092] Step S5: Based on the pre-established model of the park's shiftable load, transferable load, reducible load, and energy storage charging and discharging, combined with dynamic time-of-use electricity prices, and taking full account of the interests of both the park and the user, the master-slave game method is used to solve the optimal energy scheduling plan;

[0093] Furthermore, for the shiftable load, due to the constraints of the production process, it can only be shifted within the shiftable time interval. The total power consumption before and after the shift remains unchanged, but the total power cost changes. The power before and after the shiftable load scheduling is as follows:

[0094]

[0095] T par.i =[t par-.i ,t par+.i ]

[0096] τ i ∈[t par-.i ,t par+.i -D par.i ]

[0097] i∈(1, 2, 3, ...)

[0098] in, represents the power distribution vector of the i-th shiftable load before dispatching, The power during the first start-up period; st i represents the start-up period of the i-th movable load before scheduling; represents the power distribution vector of the ith load after scheduling; T par.i is the dispatchable period of the ith shiftable load, t par-.i With t par+.i They represent the beginning and end of the dispatchable period of the i-th shiftable load respectively; τ i represents the first start-up period of the ith shiftable load after scheduling; D par.i is the duration before the i-th load dispatch.

[0099] For transferable loads such as washing machines, dishwashers, etc.:

[0100]

[0101] T tra.j =[t tra-.j ,t tra+.j ]

[0102] j∈(1, 2, 3, ...)

[0103] in, represents the power vector of the jth transferable load in one cycle before optimization; P t tra.j is the load of the jth transferable load at time t after scheduling; If the value of is 1, it means that the power of the jth device at time t has been transferred; if it is 0, it means that the power of this device at time t is 0; and Characterizes the power boundary of the transferable power of the jth device; T tra.j is the transfer period acceptable to the jth device; t tra-.j With t tra+.j They represent the beginning and end of the transfer period of the j-th device respectively.

[0104] For loads that can be reduced to a certain extent, such as air conditioning and lighting:

[0105]

[0106] μ k ∈(0,1)

[0107] in represents the power distribution vector of the kth reducible load in one cycle before scheduling; P t cut.k* With P t cut.k Respectively represent the power of the kth device before and after scheduling in period t; μ k is the reduction degree of the kth device, which varies with the importance of the device; introduce the variable like If it is 1, it means that the kth removable device is removed in time period t, otherwise the kth device does not participate in the scheduling in time period t.

[0108] Furthermore, within an EMS dispatch cycle, the charging conditions of the ESS energy storage system should meet the following conditions:

[0109]

[0110] The charging rate of ESS is:

[0111]

[0112] In an EMS dispatch cycle, the discharge conditions of the ESS energy storage system should meet the following conditions:

[0113]

[0114] P t pv ≤P t load

[0115] Then the discharge rate of the ESS energy storage system is:

[0116]

[0117] in, and are the rated charging and discharging power of the energy storage unit; P t load is the actual load power at time t; P t load* is the forecast load for the day; represents the grid electricity price at time t. They represent the valley and peak values ​​of the grid electricity price respectively; Indicates the sensitivity coefficient of the energy storage system to peak and valley electricity prices, It indicates the sensitivity coefficient of the energy storage system to peak and valley loads.

[0118] Furthermore, the maximum daily operating profit objective function of the park is constructed as:

[0119]

[0120] In the formula, In the formula, In the formula,

[0121] Among them, F ems represents the daily total revenue function of the park under EMS scheduling; F ess Represents the charging cost of the energy storage unit; F ma is the maintenance cost; F grid K is the cost of unbalanced power exchange with the external grid; pv K is the photovoltaic array maintenance cost coefficient; ess.c With K ess.d Respectively represent the depreciation and maintenance cost coefficient of the energy storage unit; ρ t grid It is the time-of-use electricity price of the power grid.

[0122] The user's minimum daily cost function is:

[0123]

[0124] in, is the electricity cost of the nth user in a cycle; is the power consumption of the i-th user in period t; is the electricity price of the i-th user in period t.

[0125] The master-slave game method is used to balance the interests of the park and the user. The park is the leader and the user is the follower. The park can maximize its benefits by predicting the user's response and optimizing its own strategy; the user adjusts its energy consumption according to the park's strategy to minimize costs. By solving the Stackelberg equilibrium point, a strategy combination that can meet the needs of both parties is found.

[0126] Step S06: The terminal acquisition and dispatching system receives the control instructions issued by the energy management system, ensures that the instructions are transmitted to the control execution module in a timely and accurate manner, and the communication module sends the control instructions to various energy devices in the park to achieve control.

[0127] The above description is only a preferred embodiment of the present invention. It should be pointed out that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. An integrated power management system for a park power grid based on Internet of Things communication, characterized by: It includes an energy management system, a terminal procurement and dispatching system, and an energy storage system; the management system is electrically connected to the terminal procurement and dispatching system and the energy storage system respectively, the terminal procurement and dispatching equipment collects relevant data from the consumer end and uploads the data to the energy management system, and the energy management system conducts comprehensive analysis and regulation based on the data from the consumer end and the data from the energy storage system.

2. According to claim 1, the integrated power management system of the park power grid based on Internet of Things communication is characterized by: The energy management system includes a data processing module, a prediction module, and an intelligent scheduling module, wherein the data processing module is responsible for receiving data uploaded by the terminal device and passing the processed results to the prediction module; the prediction module obtains the processing result data from the data processing module and passes the prediction results to the intelligent scheduling module; the intelligent scheduling module calculates the optimized scheduling scheme instruction according to the prediction results and sends it to the terminal acquisition and dispatching system; The data processing module is responsible for receiving and summarizing the real-time energy consumption data collected by the terminal acquisition and dispatching system, and cleaning, formatting and analyzing the data to ensure the accuracy and completeness of the data; The prediction module generates dynamic prediction results of future energy consumption and cost based on historical data, providing a basis for formulating reasonable scheduling plans, realizing accurate planning of energy supply and intelligent regulation of loads; The intelligent scheduling module dynamically generates energy distribution and load control plans within the park based on real-time data, prediction results and optimization algorithms to achieve load balancing and energy saving and consumption reduction.

3. According to claim 1, the integrated power management system of the park power grid based on Internet of Things communication is characterized by: The terminal acquisition and dispatching system includes a data acquisition module, a communication module, and a control execution module. The data acquisition module collects external data and uploads the data to the energy management system in real time through the communication module. The energy management system sends the dispatching instructions to the control execution module through the communication module, and the control execution module adjusts the operating status of the equipment according to the dispatching instructions. The data acquisition module collects power generation data, energy storage charging and discharging data, park and power grid interaction data, and park users' energy load data; The communication module uses the Internet of Things communication technology to realize the connection between the energy management system and the terminal acquisition and dispatching system, and the terminal acquisition and dispatching system and the park energy equipment. The communication methods include broadband optical fiber, RS485 wired connection method and ZigBee short-distance wireless network connection method; The control execution module is responsible for receiving instructions from the energy management system and implementing control operations on on-site equipment. In addition, it is also equipped with edge computing function. After obtaining the collected information, edge computing can pre-process the data, which helps to reduce the computing burden of the energy management system. In addition, edge computing completes the entire process of data analysis, decision-making and instruction issuance at the edge, shortening the response time. In the case of network delays or instability, it can still ensure the effective coordination and response of equipment within the park.

4. The control method of the integrated power management system of the park power grid based on Internet of Things communication according to claim 1 is characterized by: step S1. The data acquisition module of the terminal acquisition and dispatching system collects environmental data related to energy efficiency to assist the energy management system in making optimal decisions. In addition, it collects the operating parameters and operating status of the access within the park, and transmits the data to the energy management system through the communication module to achieve real-time data synchronization with the energy management system. Step S2: The energy management system receives and summarizes the energy consumption data transmitted by the terminal acquisition and dispatching system, performs data analysis, and stores the historical energy consumption data in a database to support long-term tracking and management of the data; Step S3: The energy management system predicts the photovoltaic power generation and load power of the park on the next day based on historical data, environmental data and market information, and generates a net load power prediction curve; Step S4: The park energy management system provides a dynamic time-of-use electricity price for users in the park based on the net load power forecast curve of the day before, combined with the current supply and demand relationship and the prices of various distributed energy sources; Step S5: Based on the pre-established model of the park's shiftable load, transferable load, reducible load, and energy storage charging and discharging, combined with dynamic time-of-use electricity prices, and taking full account of the interests of both the park and the user, the master-slave game method is used to solve the optimal energy scheduling plan; Step S6: The terminal acquisition and dispatching system receives the control instructions issued by the energy management system, ensures that the instructions are transmitted to the control execution module in a timely and accurate manner, and the communication module sends the control instructions to various energy devices in the park to achieve control.

5. The control method of the integrated power management system of the park power grid based on Internet of Things communication according to claim 5 is characterized by: In step S1, the environmental data include temperature, humidity and light intensity; the operating parameters include photovoltaic, energy storage and energy load parameters.

6. The control method of the integrated power management system of the park power grid based on Internet of Things communication according to claim 4 is characterized by: Step S5 includes: S5.1 Calculation of the power of the shiftable load before and after dispatch; S5.2 Calculation of transferable loads S5.3 Calculation of load that can be reduced S5.4 Design the conditions that the charging of the ESS energy storage system should meet within an EMS dispatch cycle; S5.5 calculates the time-of-use electricity price; S5.6 Construct the maximum daily operating profit objective function of the park; S5.7 Construct the minimum daily cost function.

7. The control method of the integrated power management system of the park power grid based on Internet of Things communication according to claim 5 is characterized by: In S4.1, the specific calculation method of dynamic time-of-use electricity price is as follows: in, represents the time-of-use electricity price of the park before the optimization of the price mechanism; c pv 、c ess They are photovoltaic power generation quotation and energy storage discharge quotation respectively; P t pv is the photovoltaic power at time t; P t grid is the power of the power grid at time t; K s is the unbalanced power exchange cost coefficient between the park and the external power grid; Among them, ρ t Indicates the time-of-use electricity price of the park after the price mechanism is optimized; the supply-demand relationship coefficient is introduced to guide the user demand side to respond to the load stabilization When the park is in a period of insufficient supply, a higher value is taken; when supply exceeds demand, a smaller value is taken to reduce the electricity price and encourage users to use electricity during the valley period of electricity price; K flu is the price fluctuation coefficient caused by load changes.

8. The control method of the integrated power management system of the park power grid based on Internet of Things communication according to claim 7 is characterized by: In S5.1, for the shiftable load, due to the constraints of the production process, it can only be shifted within the shiftable time interval. The total power consumption before and after the shift remains unchanged, but the total power cost changes; the power before and after the shiftable load scheduling is as follows: T par.i =[t par-.i ,t par+.i ] τ i ∈[t par-.i ,t par+.i -D par.i ] i∈(1、2、3、…) in, represents the power distribution vector of the i-th shiftable load before dispatching, The power during the first start-up period; st i represents the start-up period of the i-th movable load before scheduling; represents the power distribution vector of the ith load after scheduling; T par.i is the dispatchable period of the ith shiftable load, t par-.i With t par+.i They represent the beginning and end of the dispatchable period of the i-th shiftable load respectively; τ i represents the first start-up period of the ith shiftable load after scheduling; D par.i is the duration before the i-th load dispatch.

9. The control method of the integrated power management system of the park power grid based on Internet of Things communication according to claim 7 is characterized by: In S5.2, the transferable load is: T tra.j =[t tra-.j ,t tra+.j ] j∈(1、2、3、…) in, represents the power vector of the jth transferable load in one cycle before optimization; P t tra.j is the load of the jth transferable load at time t after scheduling; If the value of is 1, it means that the power of the jth device at time t has been transferred; if it is 0, it means that the power of this device at time t is 0; and Characterizes the power boundary of the transferable power of the jth device; T tra.j is the transfer period acceptable to the jth device; t tra-.j With t tra+.j They represent the beginning and end of the transfer period of the j-th device respectively.

10. The control method of the integrated power management system of the park power grid based on Internet of Things communication according to claim 7 is characterized by: In S5.3, the load that can be reduced is: m k ∈(0,1) in represents the power distribution vector of the kth reducible load in one cycle before scheduling; With P t cut.k Respectively represent the power of the kth device before and after scheduling in period t; μ k is the reduction degree of the kth device, which varies with the importance of the device; introduce the variable like If it is 1, it means that the kth removable device is removed in time period t, otherwise the kth device does not participate in the scheduling in time period t.

11. The control method of the integrated power management system of the park power grid based on Internet of Things communication according to claim 7 is characterized by: In S5.4, within an EMS dispatch cycle, the charging conditions of the ESS energy storage system should meet the following conditions: The charging rate of ESS is: In an EMS dispatch cycle, the discharge conditions of the ESS energy storage system should meet the following conditions: P t pv ≤P t load Then the discharge rate of the ESS energy storage system is: in, and are the rated charging and discharging power of the energy storage unit; P t load is the actual load power at time t; is the forecast load for the day; represents the grid electricity price at time t; They represent the valley and peak values ​​of the grid electricity price respectively; Indicates the sensitivity coefficient of the energy storage system to peak and valley electricity prices, It indicates the sensitivity coefficient of the energy storage system to peak and valley loads.

12. The control method of the integrated power management system of the park power grid based on Internet of Things communication according to claim 7 is characterized by: In S5.5, the specific calculation method of dynamic time-of-use electricity price is as follows: in, represents the time-of-use electricity price of the park before the optimization of the price mechanism; c pv 、c ess They are photovoltaic power generation quotation and energy storage discharge quotation respectively; P t pv is the photovoltaic power at time t; P t grid is the power of the power grid at time t; K s is the unbalanced power exchange cost coefficient between the park and the external power grid; Among them, ρ t Indicates the time-of-use electricity price of the park after the price mechanism is optimized; the supply-demand relationship coefficient is introduced to guide the user demand side to respond to the load stabilization When the park is in a period of insufficient supply, a higher value is taken; when supply exceeds demand, a smaller value is taken to reduce the electricity price and encourage users to use electricity during the valley period of electricity price; K flu is the price fluctuation coefficient caused by load changes; The total operating profit objective function of the park energy system under the time-of-use electricity price mechanism includes the park's electricity sales revenue, maintenance costs, operating costs, and the cost of exchanging unbalanced power with the external power grid; maintenance costs include the maintenance costs of new energy power generation and ESS energy storage system maintenance costs; operating costs include the cost of purchasing electricity from the power grid.

13. The control method of the integrated power management system of the park power grid based on Internet of Things communication according to claim 7 is characterized by: In S5.6, the objective function for constructing the maximum daily operating revenue of the park is: In the formula, In the formula, In the formula, where F ems represents the daily total revenue function of the park under EMS scheduling; F ess Represents the charging cost of the energy storage unit; F ma is the maintenance cost; F grid K is the cost of unbalanced power exchange with the external grid; pv K is the photovoltaic array maintenance cost coefficient; ess.c With K ess.d Respectively represent the depreciation and maintenance cost coefficients of the energy storage unit; ρ t grid It is the time-of-use electricity price of the power grid.

14. The control method of the integrated power management system of the park power grid based on Internet of Things communication according to claim 7 is characterized by: In S5.7, the user's minimum daily cost function is: in, is the electricity cost of the nth user in a cycle; is the power consumption of the i-th user in period t; is the electricity price of the i-th user in period t; The master-slave game method is used to balance the interests of the two main bodies, the park and the user. The park acts as a leader and the user acts as a follower. The park can maximize its profits by predicting the degree of user response and optimizing its own strategy; the user adjusts its energy consumption according to the park strategy to minimize the cost; by solving the Stackelberg equilibrium point, a strategy combination that can meet the needs of both parties is found.

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