Zero-carbon park smart energy management and control system and method

Abstract

The invention relates to the technical field of zero-carbon parks, and discloses a zero-carbon park smart energy management and control system and method.The system comprises a sensing layer, a network layer, a platform layer and an application layer, and the sensing layer collects energy data of a zero-carbon park; the network layer comprises a communication network and a security protection system, the communication network transmits energy data in a hierarchical manner, and the security protection system encrypts a data transmission process; the platform layer comprises a digital twinborn platform and an algorithm platform, the digital twinborn platform establishes a zero-carbon park digital twinborn model based on energy data, and the algorithm platform generates an optimization scheme; according to the invention, multi-source energy data is collected in a unified manner through the sensing layer, the problem of traditional data islands is effectively solved, the intercommunity of various types of data in the park is improved, data processing is carried out through the platform layer, the control instruction is issued through the application layer, and the data processing efficiency is improved. A closed loop of perception-analysis-decision-execution-feedback is realized, and resource data are effectively integrated.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of zero-carbon park, in particular to a zero-carbon park intelligent energy management and control system and method. BACKGROUND

[0002] At present, as the core carrier of energy consumption and carbon emission, the zero-carbon transformation of the park has become a key link to promote the upgrading of energy structure. With the rapid popularization of diversified energy facilities such as distributed energy (such as photovoltaic, wind power, energy storage), electric vehicle charging piles, waste heat recovery, etc. in the park, the coupling of energy flow, information flow and business flow is increasingly close, and the traditional single energy management mode has been unable to meet the demand of multi-energy collaboration. Therefore, how to build a management and control system that can integrate resource data has become a key problem. SUMMARY

[0003] The present application provides a zero-carbon park intelligent energy management and control system and method to solve the problem of how to build a management and control system that can integrate resource data.

[0004] In the first aspect, the present application provides a zero-carbon park intelligent energy management and control system, which comprises a perception layer, a network layer, a platform layer and an application layer, wherein, The perception layer is used to collect energy data of the zero-carbon park, and the energy data includes energy production data, energy consumption data, environment and working condition data and carbon emission data; The network layer includes a communication network module and a security protection system, the communication network module is used for hierarchical transmission of energy data, and the security protection system is used for encryption of the data transmission process; The platform layer includes a digital twin platform and an algorithm platform, the digital twin platform is used to establish a digital twin model of the zero-carbon park based on the energy data, and the algorithm platform is used to generate an optimization scheme; The application layer is used to convert the optimization scheme into a control instruction and issue the control instruction to a park energy equipment controller.

[0005] The present application collects multi-source energy data through the perception layer, effectively solves the problem of traditional data island, improves the interoperability of various types of data in the park, transmits data hierarchically through the network layer and encrypts data transmission, improves the stability and security of data transmission, cooperates through the digital twin platform and the algorithm platform of the platform layer, realizes data processing, model construction and optimization calculation, and issues the control instruction converted from the optimization scheme to the park energy equipment controller through the application layer to realize the closed loop of perception-analysis-decision-execution-feedback, effectively integrates resource data, and provides operability for zero-carbon park management.

[0006] In an optional implementation, the communication network module comprises a wired communication network module and a wireless communication network module, the wired communication network module comprises a single-mode optical fiber, and the single-mode optical fiber is used for transmitting the park equipment control instruction; and the wireless communication network module supports Lora protocol, NB-IoT protocol and Wi-Fi transmission.

[0007] The application transmits core data by using the advantage of strong transmission stability of wired communication, and solves the problem of low adaptability of single protocol by using wireless communication to support multiple protocols.

[0008] In an optional implementation, the Lora protocol is used to transmit the data collected by the park peripheral sensors, the NB-IoT protocol is used to transmit the data collected by the scattered meters in the park buildings, and the Wi-Fi is used to transmit the terminal device data.

[0009] The application transmits the data collected by the park peripheral sensors by using the advantage of long distance and low power consumption of the Lora protocol, transmits the data collected by the scattered meters in the park buildings by using the advantage of mass connection and low cost of the NB-IoT protocol, and transmits the terminal device data by using the advantage of high bandwidth and low delay of the Wi-Fi, so as to support multiple protocols of wireless communication and match different data transmission scenes and improve adaptability.

[0010] In an optional implementation, the security protection system comprises network boundary protection, core node protection and data transmission and data storage protection, the network boundary protection is deployed with a firewall, the core node protection is deployed with an intrusion detection system and an intrusion prevention system, the data transmission and data storage protection comprises a transmission layer and a storage layer, the transmission layer adopts a TLS protocol for data transmission protection, and the storage layer adopts an AES encryption algorithm for data storage protection.

[0011] The application intercepts external risks by network boundary protection, discovers potential risks in time by core node protection, actively blocks risk behaviors, ensures data security by data transmission and data storage protection, guarantees stable operation of the system, and improves security.

[0012] In an optional implementation, the digital twin platform is used to combine a BIM model and a GIS platform to build a park digital mirror image, the park digital mirror image is used to restore a three-dimensional model of a physical space and energy facilities of the park, and the digital twin platform is also used to build an energy flow model and a carbon flow model, the energy flow model is used to simulate a transmission path and loss of electric power, heat and cold, and the carbon flow model is used to represent a carbon emission distribution.

[0013] The application utilizes a digital twin platform to construct a digital mirror image of the park, restores a three-dimensional model of the physical space and energy facilities of the park, intuitively grasps the actual situation of the park, realizes energy flow transparency by using an energy flow model, and realizes carbon emission full-link tracing by using a carbon flow model.

[0014] In an optional embodiment, the algorithm platform is used to construct a physical model library, a data-driven model library, and a multi-objective optimizer, the physical model library includes an energy equipment efficiency model, a power grid power flow calculation model, and a carbon emission accounting model, the data-driven model library is used to train a model based on historical data, and the multi-objective optimizer is used to generate an optimization scheme with the goals of minimum energy consumption cost, minimum carbon emission, and maximum energy utilization rate.

[0015] The application constructs a physical model library, a data-driven model library, and a multi-objective optimizer through an algorithm platform, ensures that the optimization scheme conforms to engineering practice, and takes into account energy consumption cost, carbon emission, and energy utilization rate, thereby providing data support for the application layer.

[0016] In an optional embodiment, the application layer includes a park total cable module, a scheduling management module, a monitoring decision module, an operation optimization module, and an intelligent operation and maintenance module, wherein, The scheduling management module includes a day-ahead scheduling module and a real-time scheduling module, the day-ahead scheduling module is used to generate a next-day scheduling scheme, and the real-time scheduling module is used to generate a scheduling scheme every preset time interval; The monitoring decision module is used to generate an early warning signal when a device operation index exceeds a device operation threshold and / or a carbon emission operation index exceeds a carbon emission threshold; The operation optimization module is used to dynamically regulate and control energy-using equipment; The intelligent operation and maintenance module is used to evaluate a device health state and generate an operation and maintenance work order according to the device health state evaluation result.

[0017] The application provides visualization through the park total cable module, adapts to changes in park energy supply and demand through the scheduling management module, realizes double early warning through the monitoring decision module, reduces abnormal risk, improves energy utilization efficiency through the operation optimization module, and realizes predictive maintenance through the intelligent operation and maintenance module, thereby reducing operation and maintenance costs.

[0018] In a second aspect, the application provides a zero-carbon park intelligent energy management and control method applied to the zero-carbon park intelligent energy management and control system of the first aspect or any of the corresponding embodiments, and the method includes: Collecting energy data of the zero-carbon park, the energy data including energy production data, energy consumption data, environment and working condition data, and carbon emission data; Transmitting the energy data in stages and encrypting the data transmission process; Establishing a digital twin model of the zero-carbon park based on the energy data and generating an optimization scheme; The optimization scheme is converted into control instructions, and the control instructions are issued to the park energy equipment controller.

[0019] In a third aspect, the present application provides an electronic device, comprising a memory and a processor, the memory and the processor are connected to each other in communication, the memory stores computer instructions, and the processor executes the computer instructions to perform the zero-carbon park smart energy management and control method of the second aspect.

[0020] In a fourth aspect, the present application provides a computer readable storage medium, the computer readable storage medium stores computer instructions, and the computer instructions are used to make a computer execute the zero-carbon park smart energy management and control method of the second aspect. BRIEF DESCRIPTION OF DRAWINGS

[0021] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the drawings needed in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0022] Figure 1 is the overall schematic diagram of the zero-carbon park smart energy management and control system according to the embodiment of the present application; Figure 2 is the schematic diagram of the distribution of each layer in the zero-carbon park smart energy management and control system according to the embodiment of the present application; Figure 3 is the flowchart of the zero-carbon park smart energy management and control method according to the embodiment of the present application; Figure 4 is the hardware structure schematic diagram of the electronic device of the embodiment of the present application. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical scheme and advantages of the embodiments of the present application more clear, the technical scheme in the embodiments of the present application will be described clearly and completely below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0024] It can be understood that before using the technical solutions disclosed in the embodiments of the present application, the user should be informed of the type, use range, use scene, etc. of the personal information involved in the present application and obtain the authorization of the user in a proper manner according to relevant laws and regulations.

[0025] Currently, the park energy system has evolved from the traditional single power supply mode to a comprehensive energy system that integrates photovoltaic, energy storage, power grid, and multi-energy load.

[0026] However, the current park energy system has the following problems: (1) Serious data island phenomenon: Traditional park energy systems are mostly built independently for a single energy type (such as electricity, gas, and heat). The data standards of each system are not unified, and the interfaces are not compatible, resulting in scattered storage of energy data on different platforms. It is difficult to achieve comprehensive aggregation and correlation analysis of multi-energy data, and it is difficult to support global optimization decisions; (2) Insufficient adaptability of control algorithms: Traditional park energy systems rely on single data-driven models (such as machine learning algorithms) and lack the integration of knowledge of park energy system physical laws and operating rules. When the type of park energy facilities increases or the external environment (such as weather and load) changes dramatically, the model has poor generalization ability and is prone to deviate from the actual operating requirements; (3) Poor coordination of functional modules: Existing systems focus more on energy monitoring or simple scheduling, and lack a full-cycle function of "overview - scheduling - monitoring - optimization - operation and maintenance". For example, it can only display energy consumption data and cannot optimize operation in combination with carbon emission indicators, or the operation and maintenance module is disconnected from the monitoring module, making it difficult to achieve predictive maintenance of faults; (4) Weak adaptability to zero-carbon goals: Traditional energy management systems focus on "energy saving and consumption reduction" and do not include zero-carbon-related functions such as carbon flow analysis, carbon footprint tracking, and carbon quota management in the system architecture, making it difficult to achieve linked management and control of energy consumption and carbon emissions.

[0027] Based on the above problems, the embodiment of the present application provides a zero-carbon park smart energy management system, which is built based on a "four-layer two-platform" architecture, with coordinated linkage of functions at each level, achieving intelligent management and control of the entire life cycle of park energy and carbon emission reduction goals.

[0028] The embodiment provides a zero-carbon park smart energy management system, as shown in Figure 1 and Figure 2 , the system includes a perception layer, a network layer, a platform layer, and an application layer.

[0029] The perception layer, as the "nerve ending" of the system, is responsible for real-time collection of park energy and related data, providing a data foundation for subsequent analysis and control. The perception layer is used to collect energy data of the zero-carbon park, covering the entire energy chain and environmental conditions. Energy data includes energy production data, energy consumption data, environmental and working condition data, and carbon emission data.

[0030] The network layer, as the "aorta" of data transmission, is composed of a communication network module and a security protection system, and is used to ensure the stability and security of data transmission. The communication network module is used for hierarchical transmission of energy data, and the security protection system is used for encryption of the data transmission process.

[0031] The platform layer, as the "brain center" of the system, realizes data processing, model building and optimization calculation through the cooperation of the digital twin platform and the algorithm platform, and provides data support for the application layer. The digital twin platform is used to establish a zero-carbon park digital twin model based on energy data, and the algorithm platform is used to generate optimization schemes.

[0032] The application layer, as the "functional outlet" of the system, develops park overview module, dispatching management module, monitoring and decision-making module, operation optimization module and intelligent operation and maintenance module to cover the whole process of monitoring, dispatching, optimization and operation and maintenance. The application layer is used to convert the optimization scheme into control instructions and issue the control instructions to the park energy equipment controller.

[0033] Specifically, the data collected by the perception layer includes the following four types: (1) Energy production data: focusing on the output and state monitoring of distributed energy, such as distributed photovoltaic power station collecting real-time output through power sensor of inverter (accuracy up to ±0.5%), combined with irradiance sensor to correct output deviation; wind power collects rotor speed, pitch angle and actual output power through wind turbine controller, and records wind turbine operating status synchronously; energy storage system collects charging and discharging current, voltage, SOC (state of charge) and charging and discharging efficiency to ensure the available capacity and operation health of energy storage; (2) Energy consumption data: different energy consumption scenarios in the park are collected, building energy consumption is collected by three-phase intelligent electric meters (supporting 0.2S level accuracy, remote meter reading interval 1 minute), ultrasonic heat meters and electromagnetic flow meters deployed in power distribution rooms and heat inlet to collect electricity, heat and cold; charging piles collect charging load and duration through metering module built-in pile body; industrial equipment collects real-time energy consumption of each section of production line by connecting PLC system to realize "device level" energy consumption monitoring; (3) Environmental and working condition data: temperature and humidity sensors (measurement range -40~85℃, accuracy ±0.3℃), light intensity sensors (0~200000 lux) and wind speed sensors (0~60 m / s) are deployed at key positions such as roof, green belt and building facade to provide environmental basis for energy regulation; at the same time, core working condition parameters of energy equipment are collected, such as boiler flue gas temperature and thermal efficiency (real-time calculation deviation ≤2%), air conditioner COP (coefficient of performance) and return air temperature, to ensure the monitoring of equipment operating efficiency; (4) Carbon emission data: Based on the collection of "source-hub" two ends, the "source end" collects the consumption of fossil energy through intelligent gas meters and fuel meters, and calculates the basic carbon emissions combined with the carbon emission coefficient released by the state (such as the carbon emission coefficient of natural gas 2.16 kgCO2 / m³); The "sink end" collects renewable energy generation (converted carbon emission reduction) and carbon capture equipment capture, realizing "full caliber" statistics of carbon emissions. The selection of sensing layer equipment considers functionality and economy, using intelligent sensors, edge computing gateways (supporting edge preprocessing such as data filtering and preliminary anomaly value judgment), and compatible with LoRa (low power, long distance, suitable for park edge sensors, transmission distance 1~3km), NB-IoT (massive connection, suitable for intelligent meters, single base station can connect 100,000 devices), 4G / 5G (high-speed transmission, suitable for high-frequency data collection of industrial equipment, etc. ) Protocol, according to the type of data, flexible setting of collection frequency (such as device working condition data 1 minute / second, environmental data 5 minutes / second), balance real-time and bandwidth cost.

[0034] Specifically, the communication network module in the network layer includes a wired communication network module and a wireless communication network module, which adopts "wired + wireless" fusion networking to form a "core backbone wired, terminal access wireless" architecture.

[0035] Among them, the wired communication network module includes a single-mode optical fiber, and the core data (such as park device control instructions, digital twin model update data, etc.) is transmitted through the single-mode optical fiber, with a bandwidth of 1000Mbps and a transmission distance ≤20Km, which can avoid the delay of instructions caused by wireless interference.

[0036] Among them, the terminal sensing data (such as sensor, intelligent meter data, etc.) is transmitted through the wireless communication network module, and the wireless communication network module supports Lora protocol, NB-IoT protocol and Wi-Fi transmission. Lora protocol is used to transmit data collected by peripheral sensors outside the park, NB-IoT protocol is used to transmit data collected by scattered meters inside the park building, and Wi-Fi (5G band) is used to transmit data of near-distance, high-bandwidth terminal equipment, such as charging piles. In addition, edge gateways are deployed at the network edge to preliminarily compress the collected data (compression rate ≥50%) to reduce the transmission pressure of the backbone network.

[0037] Specifically, the security protection system in the network layer constructs a three-layer protection mechanism, including network boundary protection, core node protection, and data transmission and data storage protection.

[0038] Among them, the network boundary protection deploys next-generation firewall (NGFW), which supports deep packet inspection and intrusion prevention, and can intercept common threats such as SQL, DDoS attacks, etc.

[0039] Among them, the core node protection department deploys intrusion detection system (IDS) and intrusion prevention system (IPS), which monitors network traffic anomalies in real time, such as abnormal data transmission frequency, illegal IP access, etc. Once the risk is found, it will be blocked immediately.

[0040] Among them, data transmission and data storage protection adopts encryption protection, including transmission layer and storage layer. The transmission layer is encrypted based on TLS 1.3 protocol, and the storage layer is encrypted by AES-256. At the same time, through the setting of RBAC (role-based access control) authority, such as the operation and maintenance personnel only have data viewing authority, the administrator has parameter modification authority, to prevent data leakage and unauthorized operation.

[0041] Specifically, the digital twin platform in the platform layer combines BIM (Building Information Modeling) + GIS (Geographic Information System) to build a digital mirror of the park, which is used to restore the three-dimensional model of the park's physical space (buildings, roads, energy pipeline network) and energy facilities (photovoltaic power station, energy storage, boiler). At the same time, energy flow model and carbon flow model are built. The energy flow model is used to track the transmission path of electricity, heat and cold from production to consumption, and to calculate the loss at each link (such as pipeline heat loss, line loss). The carbon flow model is associated with energy consumption data and carbon emission coefficient, and dynamically displays the carbon emission distribution, such as the carbon emission proportion of a building or a certain type of equipment.

[0042] In addition, the digital twin platform has three core functions: (1) data standard processing: using the 3σ principle to eliminate outliers, and converting different formats of electricity and gas meter data into JSON format; (2) multi-source data fusion: fusing perception layer data and park management data, such as information of enterprises settled in the park, production plans, etc.; (3) three-dimensional visualization display, supporting WebGL technology, which can rotate 360 degrees to view the energy status of the park, and click on the equipment to display real-time parameters.

[0043] Specifically, the algorithm platform in the platform layer integrates knowledge-driven and data-driven dual engines, and builds a multi-dimensional algorithm library, including physical model library, data-driven model library and multi-objective optimizer.

[0044] Among them, the physical model library includes energy equipment efficiency model (such as boiler efficiency curve model changing with load), power grid flow calculation module (using Newton-Raphson method, suitable for 10kV distribution network in the park), carbon emission accounting model.

[0045] Among them, the data-driven model library is based on historical data to train the model, such as LSTM (Long Short-Term Memory Network) load forecasting model (input historical load, weather, holiday data, prediction accuracy ≥ 90%), random forest equipment fault diagnosis model (through the analysis of equipment vibration, temperature and other parameters, fault recognition rate ≥ 95%).

[0046] Among them, the multi-objective optimizer sets the constraint condition (such as the energy storage charging and discharging power ≤500kW, the upper limit of the grid power purchase ≤1000kW), and solves based on NSGA-Ⅱ (non-dominated sorting genetic algorithm Ⅱ), taking into account the balance of the three (such as the trade-off between cost and carbon emission reduction), output a set of Pareto optimal solution, and obtain the optimization scheme.

[0047] Specifically, the application layer develops five modular functions of park total cable module, dispatching management module, monitoring decision module, operation optimization module and intelligent operation and maintenance module.

[0048] Among them, the park total cable module: taking the digital twin visualization interface as the core, displays the park core indicators (total energy production / consumption, carbon emission intensity, renewable energy proportion, equipment perfect rate), supports multi-dimensional data drilling-clicking on the "building energy consumption" indicator, can drill down to the energy consumption details of a building, a floor and a room; support time dimension filtering (day / week / month / year), compare the energy consumption and carbon emission changes in different periods, and assist managers to master the park energy operation trend.

[0049] Among them, the dispatching management module realizes multi-energy collaborative scheduling, including day-ahead scheduling module and real-time scheduling module. The day-ahead scheduling module combines LSTM load prediction, photovoltaic / wind power output prediction (based on weather forecast) before 16:00 every day to develop the next day's scheduling plan, such as preferentially using photovoltaic power during the photovoltaic output peak period (10:00-15:00), and storing excess power in energy storage. The real-time scheduling module updates data every 5 minutes to generate a scheduling scheme, and when the actual load is higher than the predicted value, triggers the energy storage discharge or adjusts the gas turbine output to ensure supply and demand balance and avoid voltage fluctuations.

[0050] Among them, the monitoring decision module sets a double early warning mechanism, generates a warning signal when the device operating threshold exceeds the device operating threshold (such as boiler flue gas temperature ≥200℃, air conditioner COP ≤2.5), and / or carbon emission operating indicators exceed the carbon emission threshold (such as daily carbon emission exceeds 10%), triggers the alarm, automatically performs sound and light alarm, adopts the way of central control room alarm light + sound prompt, reminds the operation and maintenance personnel. At the same time, push the early warning information to the operation and maintenance personnel mobile terminal, which includes fault location, abnormal parameters and possible reasons for this situation, etc., such as "1# boiler flue gas temperature exceeds the standard, suggest to check the flue ash", so as to shorten the fault response time.

[0051] Among them, the operation optimization module dynamically regulates the energy-using equipment based on the optimization scheme output by the algorithm platform. For example, the lighting system automatically adjusts according to the light intensity. When the light intensity is greater than or equal to 500 lux, the indoor main light is turned off, and the emergency light is retained. When the light intensity is less than or equal to 200 lux, the main light is turned on and the brightness is adjusted to 80%. The energy storage system combines time-of-use electricity price (such as a peak-valley electricity price difference of 0.5 yuan / degree) and photovoltaic output, charges at low electricity price (such as 23:00-7:00) and photovoltaic peak period, and discharges at high electricity price (8:00-11:00, 18:00-22:00), thereby reducing electricity cost and reducing grid electricity purchase (indirectly reducing carbon emissions).

[0052] Among them, the intelligent operation and maintenance module realizes predictive maintenance based on the equipment health state evaluation model. Real-time analysis of equipment operation data (such as fan bearing temperature, electric meter error), when the evaluation result is "sub-health", automatically generate operation and maintenance work order (including equipment number, maintenance project, required spare parts), push to operation and maintenance personnel mobile terminal. After the operation and maintenance is completed, the operation and maintenance personnel record the maintenance process (such as bearing model replacement, test result), the system updates the equipment operation and maintenance archives, forms a "monitoring-evaluation-maintenance-recording" closed loop, prolongs the service life of the equipment, and reduces the unplanned downtime.

[0053] The zero-carbon park smart energy management and control system provided in the embodiment effectively solves the problem of traditional data island, improves the interoperability of various types of data in the park, improves the stability and security of data transmission through hierarchical data transmission and data transmission encryption, realizes data processing, model construction and optimization calculation through the cooperation of the digital twin platform and the algorithm platform of the platform layer, and effectively integrates resource data to provide operability for zero-carbon park management.

[0054] In the embodiment, a zero-carbon park smart energy management and control method is provided, Figure 3 The flowchart of the zero-carbon park smart energy management and control method according to the embodiment of the present application is shown in Figure 3 As shown in the figure, the flowchart includes the following steps: Step S301, collecting energy data of the zero-carbon park.

[0055] Step S302, hierarchical transmission of energy data, and encryption of the data transmission process.

[0056] Step S303, establishing a zero-carbon park digital twin model based on the energy data, and generating an optimization scheme.

[0057] Step S304, converting the optimization scheme into a control instruction, and issuing the control instruction to the park energy equipment controller.

[0058] In the embodiment of the present application, first, the energy data of the zero-carbon park is collected through the perception layer, including energy production data, energy consumption data, environmental and working condition data, and carbon emission data, and the energy data is encrypted and transmitted to the platform layer through the network layer.

[0059] Then, the energy data is cleaned, standardized and completed by the platform layer, wherein the standardization processing is to convert non-standard data of different devices (such as kW·h of electric meter and GJ of heat meter) into a unified unit, the completion processing is to complete the disconnected data by interpolation method, for example, if the sensor is offline for 5 minutes, the data of the previous and next 10 minutes of the sensor is used for linear completion. Fusion of multi-source data (such as association of environmental temperature and humidity with building energy consumption), forming a high-quality data set.

[0060] The digital twin platform in the platform layer updates the park energy system model every 5 minutes, updates the energy equipment parameters (such as real-time efficiency of boiler, air conditioning return air temperature, etc.), energy flow path (such as real-time flow of pipe network, etc.), carbon flow data (such as real-time carbon emission increment), and simulates the current running state.

[0061] The simulation outputs two types of results: one is energy consumption distribution (such as energy consumption proportion of each building and each device, finding out high energy consumption nodes), and the other is carbon emission trajectory (such as which type of device causes the peak value of carbon emission in a certain period), providing a targeted direction for subsequent optimization.

[0062] The multi-objective optimizer in the platform layer completes the optimization calculation through the following two steps, first, calling the physical model and data-driven model, taking historical data and next-day weather forecast as input, outputting predicted future 24-hour park energy load (outputting a predicted value every 1 hour) and renewable energy output (such as photovoltaic output peak period, wind power output fluctuation range). Then, taking the minimum energy consumption cost, the lowest carbon emission and the highest energy utilization rate as the target, setting the constraint condition, outputting the optimal solution, and generating the optimization scheme. For example, optimization scheme A: cost 30,000 yuan / day, carbon emission 5 tons / day; optimization scheme B: cost 32,000 yuan / day, carbon emission 4.5 tons / day), then according to the priority of the park (such as zero-carbon target priority, then select scheme B) to determine the final optimization scheme as optimization scheme B.

[0063] The application layer is used to convert the optimization scheme into control instructions, such as charging the energy storage system from 9:00 to 15:00 and discharging from 18:00 to 22:00, and increasing the air conditioning temperature to 26℃. The application layer sends the control instructions to the energy equipment controller through the MQTT protocol.

[0064] At the same time, the perception layer collects the running data of the equipment after execution in real time, such as the actual charging and discharging power of energy storage, the actual energy consumption of air conditioner and the like, and feeds back to the platform layer, the platform layer compares the optimization target value with the actual value, calculates the error value, such as the target carbon emission is 5 tons / day, the actual carbon emission is 5.2 tons / day, the error is 4%, corrects the optimization model parameters, such as adjusting the weight of the load prediction model, improving the optimization accuracy of the next time, to form a closed loop of "execution-feedback-correction".

[0065] The zero-carbon park intelligent energy management and control method provided by the embodiment effectively solves the problem of traditional data island by collecting multi-source energy data, improves the interoperability of various types of data in the park, transmits data in stages, encrypts data transmission, improves the stability and security of data transmission, processes data, builds models and optimizes calculations, and issues control instructions converted from optimization schemes to park energy equipment controllers to realize a closed loop of perception-analysis-decision-execution-feedback, effectively integrates resource data, and provides operability for zero-carbon park management.

[0066] Figure 4 A structural diagram of an electronic device is provided for the embodiment of the present application.

[0067] The following will be specifically referred to Figure 4 which shows a structural diagram of an electronic device suitable for implementing the electronic device in the embodiment of the present application. The electronic device can include a processor (such as a central processor, a graphics processor, etc.) 401, which can perform various appropriate actions and processes according to programs stored in a read-only memory (ROM) 402 or programs loaded from a memory 408 into a random access memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the electronic device are also stored. The processor 401, the ROM 402, and the RAM 403 are connected to each other through a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0068] Generally, the following devices can be connected to the I / O interface 405: input devices 406 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 407 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a memory 408 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 409. The communication device 409 can allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Although Figure 4 The electronic device with various devices is shown, but it should be understood that it is not required to implement or have all the shown devices, and more or fewer devices can be alternatively implemented or possessed.

[0069] In particular, the processes described above with reference to the flowcharts can be implemented as a computer software program according to embodiments of the present application. For example, embodiments of the present application include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods illustrated by the flowcharts. In such embodiments, the computer program can be downloaded and installed from the network via the communication device 409, or installed from the memory 408, or installed from the ROM 402. When the computer program is executed by the processor 401, the above-mentioned functions defined in the zero-carbon park smart energy management method according to embodiments of the present application are performed.

[0070] Figure 4 The electronic device shown is merely an example and should not impose any limitation on the functions and use range of embodiments of the present application.

[0071] Embodiments of the present application also provide a computer-readable storage medium, and the above-mentioned method according to embodiments of the present application can be implemented in hardware or firmware, or recorded in a storage medium, or stored in a remote storage medium or a non-transitory machine-readable storage medium and stored in a local storage medium by downloading from a network, so that the method described herein can be processed by such software stored on a storage medium using a general-purpose computer, a special-purpose processor, or programmable or special-purpose hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk or a solid state disk, etc.; further, the storage medium can also include a combination of the above-mentioned types of memories. It can be understood that the computer, processor, microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code, which, when accessed and executed by the computer, processor or hardware, implements the zero-carbon park smart energy management method shown in the above embodiments.

[0072] Part of the present application can be applied as a computer program product, for example, computer program instructions, when executed by a computer, the operation of the computer can invoke or provide the method and / or technical solutions according to the present application. Those skilled in the art should understand that the form of computer program instructions in computer-readable medium includes but is not limited to source files, executable files, installation package files, etc., and accordingly, the way the computer program instructions are executed by the computer includes but is not limited to: the computer directly executes the instructions, or the computer executes the corresponding compiled program after compiling the instructions, or the computer reads and executes the instructions, or the computer reads and installs the instructions and then executes the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to the computer.

[0073] Although embodiments of the present application have been described in conjunction with the accompanying drawings, various modifications and changes can be suggested to one skilled in the art, and it is intended that the present application encompass such modifications and changes as fall within the scope of the appended claims.

Claims

1. A zero-carbon park area intelligent energy management and control system, characterized in that, The system comprises a perception layer, a network layer, a platform layer and an application layer, wherein, The perception layer is configured to collect energy data of the zero-carbon park, the energy data comprising energy production data, energy consumption data, environmental and working condition data and carbon emission data; The network layer comprises a communication network module and a security protection system, the communication network module being configured to hierarchically transmit the energy data, and the security protection system being configured to encrypt the data transmission process; The platform layer comprises a digital twin platform and an algorithm platform, the digital twin platform being configured to establish a digital twin model of the zero-carbon park based on the energy data, and the algorithm platform being configured to generate an optimization scheme; The application layer is configured to convert the optimization scheme into control instructions and issue the control instructions to a park energy equipment controller.

2. The system of claim 1, wherein, The communication network module comprises a wired communication network module and a wireless communication network module, the wired communication network module comprising a single-mode optical fiber configured to transmit park equipment control instructions, and the wireless communication network module supporting Lora protocol, NB-IoT protocol and Wi-Fi transmission.

3. The system of claim 2, wherein, The Lora protocol is used to transmit data collected by peripheral sensors outside the park, the NB-IoT protocol is used to transmit data collected by scattered meters inside park buildings, and the Wi-Fi transmission is used to transmit terminal equipment data.

4. The system of claim 1, wherein, The security protection system comprises network boundary protection, core node protection and data transmission and storage protection, the network boundary protection deploying a firewall, the core node protection deploying an intrusion detection system and an intrusion prevention system, and the data transmission and storage protection comprising a transmission layer and a storage layer, the transmission layer using the TLS protocol for data transmission protection, and the storage layer using the AES encryption algorithm for data storage protection.

5. The system of claim 1, wherein, The digital twin platform is configured to construct a park digital mirror in combination with a BIM model and a GIS platform, the park digital mirror being configured to restore a three-dimensional model of the physical space and energy facilities of the park, and the digital twin platform being further configured to build an energy flow model and a carbon flow model, the energy flow model being configured to simulate the transmission path and loss of electricity, heat and cold, and the carbon flow model being configured to represent the carbon emission distribution.

6. The system of claim 1, wherein, The algorithm platform is configured to construct a physical model library, a data-driven model library and a multi-objective optimizer, the physical model library comprising an energy equipment efficiency model, a power grid power flow calculation model and a carbon emission accounting model, the data-driven model library being configured to train a model based on historical data, and the multi-objective optimizer being configured to generate an optimization scheme with the minimum energy consumption cost, the lowest carbon emission and the highest energy utilization rate as the target.

7. The system of claim 1, wherein, The application layer comprises a park total cable module, a dispatching management module, a monitoring and decision-making module, an operation optimization module and an intelligent operation and maintenance module, wherein, The dispatching management module comprises a day-ahead dispatching module and a real-time dispatching module, the day-ahead dispatching module being configured to generate a next-day dispatching scheme, and the real-time dispatching module being configured to generate a dispatching scheme every preset time interval; The monitoring and decision-making module is configured to generate an early warning signal when a device operation index exceeds a device operation threshold and / or a carbon emission operation index exceeds a carbon emission threshold; and The operation optimization module is used for dynamically regulating the energy-using equipment; The intelligent operation and maintenance module is used for evaluating the equipment health state and generating an operation and maintenance work order according to the evaluation result of the equipment health state.

8. A zero-carbon park area intelligent energy management method, characterized in that, The method is applied to a zero-carbon park intelligent energy management and control system, and the method comprises the following steps: Collecting energy data of the zero-carbon park, wherein the energy data comprises energy production data, energy consumption data, environment and working condition data and carbon emission data; Transmitting the energy data in stages and encrypting the data transmission process; Establishing a digital twin model of the zero-carbon park based on the energy data and generating an optimization scheme; Converting the optimization scheme into control instructions and issuing the control instructions to a park energy equipment controller.

9. An electronic device, comprising: The zero-carbon park intelligent energy management and control method comprises the following steps: A memory and a processor are communicatively connected, the memory stores computer instructions, and the processor executes the computer instructions to perform the zero-carbon park intelligent energy management and control method.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for enabling a computer to execute the zero-carbon park intelligent energy management and control method.

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