Adaptive controller for controlling fuel processing devices of power plants

Abstract

The utility model relates to automatic control systems, in particular to adaptive controllers for operating fuel processing devices in a wide range of thermal power plants (TPPs) burning liquid fuel. The controller comprises a microprocessor module 1, non-volatile memory 2, a data acquisition and communication unit 3, and an output interface unit 4, all installed in a housing. Memory 2 stores a hierarchy of operational task priorities, and the microprocessor module software-implements analysis 5, prioritization 6, and mode selection 7 units, which cyclically receive data from sensors, identify relevant tasks, select a priority task based on the hierarchy, and generate a corresponding command for the fuel processing device. The technical result is the creation of a universal specialized controller with a ready-made hardware and software platform for intelligent adaptive control of the fuel pre-treatment process in various types of TPPs. 11 c.p.f-ly, 2 tables, 2 years.

Description

[0001] Technical field

[0002] This utility model relates to the field of automatic control systems, specifically adaptive controllers and control units for fuel pretreatment systems in thermal power and process plants (TPPs). It can be used to control fuel treatment devices (such as fuel modifiers, activators, and ionizers) to optimize the operation of a wide range of TPPs burning liquid hydrocarbon fuels—internal combustion engines, boiler units, industrial furnaces, furnaces, and gas turbines—under various climatic conditions, including extreme ones.

[0003] Technology Level

[0004] Programmable logic controllers (PLCs) and electronic engine control units (ECUs) are known in the art for controlling injection, ignition, and turbocharging parameters. Automatic control systems (ACS) for boilers and furnaces are known for managing the fuel-air ratio and draft. Fuel treatment devices (e.g., molecular modifiers) are also known, which may have simple integrated control devices.

[0005] For example, a method is known for monitoring and controlling fuel combustion in a piston engine, carried out by a monitoring and control device containing monitoring means in the form of a complex of ionization sensors, a control unit and an actuator (fuel injector), which increases or decreases the duration of fuel supply depending on the sensor readings (patent RU 2438070, F23N 5 / 12, published 12 / 27 / 2011).

[0006] A drawback of existing controllers and control systems is their narrow specialization and lack of functionality for intelligent control of the fuel pre-modification process as a universal optimization tool. Boiler ECUs and control systems directly control combustion or feed parameters, but lack built-in algorithms for identifying and resolving conflicts between multiple operational objectives (e.g., between the requirement for maximum boiler efficiency and the need to reduce NOx / soot emissions, or between internal combustion engine power and overheating prevention) and generating specialized commands for the fuel treatment unit based on these conflicts. Existing solutions either directly control the fuel supply or are general-purpose PLCs that require complex programming for a specific task, without offering a ready-made specialized hardware and software platform for adaptive control of the fuel treatment unit in heterogeneous installations.

[0007] Therefore, there is a need to create a specialized universal controller that would be initially designed to implement task prioritization algorithms and adaptive control of a fuel processing device, regardless of the type of power plant.

[0008] The essence of the utility model

[0009] The technical objective of the claimed solution is to create a specialized hardware and software device (controller) that provides automatic adaptive adjustment of the operating mode of a universal fuel processing device in various types of thermal power and process units (TPU) based on the analysis of multiple parameters of the unit and the environment and the resolution of conflicts between operational tasks.

[0010] The technical result is to increase the functionality, versatility and intelligence of the control device.

[0011] The specified technical problem is solved, and the technical result is achieved by creating an adaptive controller for controlling a fuel processing device of a power plant (PP), containing a microprocessor module installed in a housing, non-volatile memory, a data collection and communication unit for connecting to the PP and environmental sensors, and an output interface unit for communicating with the fuel processing device, wherein a pre-established hierarchy of priorities for a plurality of operational tasks is stored in the non-volatile memory, and the microprocessor module is software implemented as a set of functionally interacting blocks, including an analysis unit configured to receive data from sensors through a data collection and communication unit and identify current operational tasks based on a comparison of these data with pre-established threshold values, a prioritization unit functionally connected to the analysis unit and the non-volatile memory,configured to select one priority task from several identified on the basis of said priority hierarchy, and a mode selection unit operatively connected to the prioritization unit and non-volatile memory, configured to generate a control command for the fuel processing device in accordance with the selected priority task and transmit this command through the output interface unit, wherein the analysis unit, the prioritization unit and the mode selection unit are configured to cyclically repeat the operations of receiving data, identifying tasks, selecting a priority task and generating a control command, thereby ensuring adaptive control of the fuel processing device in real time.

[0012] The output interface block may contain an analog output for generating a signal selected from the group: 0-5 V, 0-10 V or 4-20 mA, where the signal level corresponds to the selected priority task or operating mode of the fuel processing device.

[0013] The output interface block may additionally contain a digital communication interface selected from the group: CAN, RS-485, Modbus RTU, for exchanging data with the fuel processing device.

[0014] The data collection and communication unit may contain analog inputs for connecting sensors with an output signal selected from the group: 0-5 V, 0-10 V, 4-20 mA; discrete inputs / outputs; industrial communication interfaces selected from the group: CAN, J1939, Modbus, Proflbus, for connecting to the standard control system of the power plant and to external sensors.

[0015] Non-volatile memory can contain several preset operating profiles, each of which includes a specified priority hierarchy and a set of control maps optimized for a specific type of power plant selected from the group: internal combustion engine, boiler unit, industrial furnace, gas turbine.

[0016] The control maps contain data on the correspondence of the parameter values ​​received from the input interface block to the parameters of the control command, and the controller is configured to adjust the command parameters based on environmental data according to the rules laid down in the control map.

[0017] The controller may additionally contain a predictive analysis module configured to predict changes in the parameters of the power plant based on the analysis of trends in historical data organized in the form of time series, the formation of predictive events when predicting the achievement of a threshold value by the controlled parameter, and the transmission of predictive events for the advance formation of control commands.

[0018] The non-volatile memory can store preset threshold values ​​to identify current operational tasks, and the threshold values ​​can be different for different types of power plants.

[0019] The analysis unit can be configured to normalize and filter the data received from the sensors before identifying the relevant tasks.

[0020] The mode selection unit may be configured to select a control card from a set stored in the non-volatile memory and generate a control command based on the selected card.

[0021] The housing can have a protection rating of at least IP54 and can be made with fasteners for mounting on a DIN rail.

[0022] The microprocessor module can be implemented on the basis of a 32-bit microcontroller with an ARM Cortex-M4 core.

[0023] Thus, the specified technical result is achieved in the present utility model by implementing, in a specialized hardware and software environment of the controller, built-in means for:

[0024] • receiving and processing data from various sensors typical for different installations (speed, temperature, steam pressure, flue gas composition, network parameters, etc.);

[0025] • identifying conditions for activating several potentially conflicting operational tasks specific to a particular type of installation (optimization of boiler efficiency, reduction of internal combustion engine emissions, uniformity of furnace heating);

[0026] • Automatic conflict resolution based on a pre-set priority hierarchy that can be customized for the installation type;

[0027] formation and issuance of the corresponding command to the controlled fuel processing device.

[0028] Brief description of drawings

[0029] Fig. 1 shows a structural block diagram of an adaptive controller for controlling a fuel processing device according to the present utility model (arrows indicate information flows between blocks and directions of data transfer);

[0030] Fig. 2 is a block diagram of the operating algorithm of the proposed adaptive controller.

[0031] Implementation of a utility model

[0032] The adaptive controller (hereinafter referred to as the controller) is a specialized electronic device, designed as a standalone module in a protected enclosure. The enclosure has a protection rating of at least IP54 and is equipped with DIN rail mounting brackets, allowing installation in standard electrical cabinets and control panels near the power plant.

[0033] The controller consists of the following main components (see Fig. 1):

[0034] 1. Microprocessor module (1) is the central computing element, based on a 32-bit microcontroller with an ARM Cortex-M4 core, clocked at at least 120 MHz, with integrated ADC, DAC, timers, and hardware communication interfaces. The microprocessor module implements all data processing algorithms and generates control commands.

[0035] 2. Non-volatile memory (2) - a storage device based on flash technology with a capacity of at least 4 MB, connected to the microprocessor module and storing:

[0036] • controller executable program;

[0037] • pre-set hierarchy of priorities for a variety of operational tasks (e.g., accident prevention, parameter stabilization, emission reduction, fuel consumption optimization, etc.);

[0038] • threshold values ​​of parameters for identifying relevant tasks;

[0039] • several preset operating profiles, each of which is optimized for a specific type of power plant (internal combustion engine, boiler unit, industrial furnace, gas turbine) and includes a corresponding priority hierarchy and a set of control maps;

[0040] • control cards, which are tabular or functional dependencies that link the values ​​of input parameters (received from sensors) with the parameters of the output control command;

[0041] • historical data for trend analysis and predictive management;

[0042] • Event log for logging.

[0043] 3. Data collection and communication unit (3) - a set of hardware for connection to sensors of the power plant and the environment. The unit includes:

[0044] • galvanically isolated analog inputs for receiving 0-5 V, 0-10 V, 4-20 mA signals from temperature, pressure, flow sensors, etc.;

[0045] • discrete inputs / outputs for receiving signals from limit switches, relays and issuing discrete commands;

[0046] • Industrial communication interfaces: CAN (including support for the J1939 protocol for connection to electronic engine control units), RS-485 with support for the Modbus RTU and Profibus DP protocols for integration into automated process control systems, Ethernet 10 / 100 for communication with the upper level.

[0047] The data collection and communication unit provides the ability to connect to both standard power plant sensors (via the appropriate protocols or analog outputs) and additional non-standard sensors, such as gas analyzers (O2, CO, NOx, SOx), smoke meters, atmospheric pressure, air temperature and humidity sensors, fuel temperature sensors, etc.

[0048] 4. Output interface block (4) is a set of hardware for transmitting control actions to the fuel processing device. The block includes:

[0049] • 0-5 V, 0-10 V or 4-20 mA analog outputs to generate a continuous signal, the level of which corresponds to the selected operating mode of the fuel treatment device or the intensity of the effect (the specific range is selected during the manufacture or configuration of the controller in accordance with customer requirements);

[0050] • pulse width modulators (PWM) for generating signals with variable duty cycle;

[0051] • relay outputs for discrete on / off switching;

[0052] • digital communication interfaces (CAN, RS-485, Modbus RTU) for two-way data exchange with the fuel processing device, including the transmission of structured commands (for example, selection of the type of action, setting the frequency, amplitude, power) and the reception of telemetry information (housing temperature, current consumption, error status).

[0053] Output interfaces can operate either simultaneously (for example, an analog signal is duplicated by a digital command) or separately, depending on the configuration of the connected fuel processing device.

[0054] 5. Power supply module (not shown in Fig. 1) - a switching power supply with a wide input range of 12-24 V DC / 85-265 V AC, 50 / 60 Hz, with protection against reverse polarity, overvoltage and short circuit.

[0055] 6. Galvanic isolation circuits (not shown in Fig. 1) - provide isolation of input / output circuits from the central processor module for operation in conditions of high electromagnetic interference.

[0056] On the front panel of the case there are LED status indicators (power, operation, error, active mode), a terminal block for connecting sensors and an actuator, industrial communication connectors (RJ45 for Ethernet, DB9 for RS-485 / CAN), a reset / setup button.

[0057] Software implementation of functional blocks

[0058] The microprocessor module (1), controlled by a program stored in non-volatile memory (2), implements the following functional blocks, implemented in the form of software modules:

[0059] Analysis block (5) - performs:

[0060] • receiving data from the data collection and communication unit (3);

[0061] • normalization and scaling of analog signals;

[0062] • digital filtering (moving average, median filtering) to suppress interference;

[0063] • data validation (range control);

[0064] • comparison of current values ​​with preset threshold values ​​stored in memory (2);

[0065] • identification of current operational tasks - those for which the current parameters have gone beyond the established limits (for example, the exhaust gas temperature has exceeded the permissible limit, the voltage frequency has dropped below the norm, the CO content in the flue gases has exceeded the threshold).

[0066] The prioritization block (6) is functionally linked to the analysis block (5) and non-volatile memory (2). Upon receipt of a list of current tasks from the analysis block, the prioritization block:

[0067] • loads from memory the priority hierarchy for the current work profile;

[0068] • if several tasks are identified, ranks them according to this hierarchy;

[0069] • takes into account additional correction factors (e.g. severity of environmental conditions, predictive events), if necessary;

[0070] • Selects one task with the highest priority for immediate resolution.

[0071] The mode selection block (7) is functionally linked to the prioritization block (6) and non-volatile memory (2). Based on the selected priority task, the mode selection block:

[0072] • selects the corresponding control card (tar) from memory;

[0073] • applies the adjustment rules embedded in the map to the basic parameters of the map (for example, increasing the intensity of the impact at low ambient temperatures);

[0074] • generates the final control command with specific parameters (voltage, PWM duty cycle, digital mode code);

[0075] • transmits a command via the output interface block (4) to the fuel processing device.

[0076] The predictive analysis module (8) (optional) is designed with the ability to:

[0077] • accumulation of historical data organized in the form of time series;

[0078] • analysis of trends in changes in controlled parameters;

[0079] • forecasting the achievement of critical values ​​based on extrapolation or simplified physical and mathematical models;

[0080] • generation of predictive events that are transmitted to the prioritization block (6) for advanced consideration when selecting a task, even before the actual occurrence of an emergency situation.

[0081] Work profiles and control cards

[0082] To ensure versatility, several preset operating profiles are stored in non-volatile memory (2), each optimized for a specific power plant type (the "ICE / DG" profile, the "Boiler Room" profile, the "Industrial Furnace" profile, and the "GTU" (Gas Turbine Unit) profile). Each profile includes a corresponding priority hierarchy and a set of control maps. An example of the priority hierarchy for various power plant types is shown in Table 1.

[0083] Control maps (maps) are pre-installed functional dependencies or tables in memory (2) that link input parameters (from sensors) to output parameters of the control command. Table 2 shows example maps for various types of control units.

[0084]

[0085] Fig. 2 shows the sequence of operations performed by the microprocessor module (1) when implementing the claimed control method: cyclic polling of sensors via the data collection and communication unit (3); normalization and filtering of the received data in the analysis unit (5); identification of current operational tasks by comparing data with preset threshold values; if there are several tasks, their prioritization in the prioritization unit (6) based on the priority hierarchy stored in the non-volatile memory (2); selection of the priority task; formation of a control command in the mode selection unit (7) in accordance with the selected task and the control card; transmission of the command via the output interface unit (4) to the fuel processing device. The block diagram illustrates the cyclic nature of the controller operation - after issuing a command, the algorithm returns to the beginning to process new data from the sensors. The controller operates as follows.After power is applied and initialization is performed, the following operations are performed:.

[0086] 1. Reading data, the microprocessor module (1) through the data collection and communication unit (3) polls all connected sensors (standard and non-standard), receiving the current values ​​of the operating parameters of the power plant and environmental conditions.

[0087] 2. Normalization and filtering analysis block (5) converts the obtained data to uniform units of measurement, applies digital filters and checks the reliability.

[0088] 3. Identifying current tasks - the analysis block (5) compares the processed data with threshold values ​​stored in memory (2). If the current value of any parameter exceeds the acceptable limits, the corresponding task is included in the list of current tasks.

[0089] 4. Prioritization - if there is more than one task in the list, the prioritization block (6) loads from memory the priority hierarchy corresponding to the current work profile and selects the task with the highest priority. If there is only one task, it is selected automatically. If the predictive analysis module (8) is present, the prioritization block also takes into account predicted events.

[0090] 5. Command generation - the mode selection block (7) selects the appropriate control map from memory based on the selected task, adjusts its parameters taking into account the current conditions (e.g. ambient temperature and pressure) and generates a control command.

[0091] 6. Command transmission - the generated command is transmitted via the output interface block (4) to the fuel processing device. Depending on the interface type, this can be an analog signal, a PWM signal, a relay switch, or a digital data packet.

[0092] 7. Alloying and telemetry - key events (task change, command parameters, emergency situations) are recorded in a log in non-volatile memory (2). If two-way communication with the fuel processing device is enabled, the controller can receive and record telemetry information from it.

[0093] 8. Return to Cycle Start - After completing the cycle, control returns to the data reading stage. This cyclic operation ensures continuous monitoring and adaptive control in real time.

[0094] When the controller is connected to the power plant sensors and the fuel processing unit, a closed control loop is created: changing the operating mode of the fuel processing unit under the controller's control changes the physical and chemical properties of the fuel, which affects the combustion process in the power plant and alters the monitored parameters, which are then recorded by the sensors and fed to the controller's input. Thus, the entire system (controller + sensors + fuel processing unit + power plant) implements closed-loop adaptive control, with the controller serving as its intelligent core.

[0095] Controller Operation Examples

[0096] Example 1. Diesel Generator Set (DGS) in High Altitude Conditions. A controller with the active "ICE / DGS" profile receives data on crankshaft speed, coolant temperature, and boost pressure from the engine control unit via the CAN interface. External sensors also provide atmospheric pressure (low, 65 kPa) and air temperature (-15°C). The analysis unit records a drop in the generated voltage frequency below 49 Hz (the "Frequency Stabilization" task) and overheating predicted by the model due to low pressure (the "Thermal Protection" task). According to the profile hierarchy, the prioritization unit selects the "Thermal Protection" task as the highest priority. The mode selection unit, using the "Thermal Protection at High Altitude" map, generates a command: an analog signal of 3.2 V and a digital packet with the mode code "PWR_STAB_COLD, intensity 8". The command is transmitted to the fuel processing device, which activates the appropriate physical action.After the thermal state has normalized, priority is automatically switched to frequency stabilization.

[0097] Example 2. Fuel oil boiler plant

[0098] The controller with the "Boiler Room" profile receives the following values ​​via Modbus from the automated process control system: furnace temperature (920°C), steam pressure (1.2 MPa), O2 (2.5%) and CO (180 ppm) content in the flue gases, as well as the fuel oil temperature (65°C, compared to a standard of 90°C). External sensors also provide atmospheric pressure (98 kPa) and outside air temperature (-5°C). The analysis unit identifies two tasks: "CO Emissions Reduction" (exceeding the 100 ppm threshold) and "Slagging Prevention" (low fuel oil temperature). According to the profile hierarchy, the slagging prevention task has a higher priority. The mode selection unit, using the "Cold Fuel Oil Spray Intensification" map, generates the "FUEL_DISPERSAL, intensity 7" command, which is transmitted via RS-485 to the fuel processing device. Once atomization has improved and the fuel oil temperature has stabilized, priority shifts to reducing emissions, and the controller issues a corresponding command.

[0099] Thus, the declared adaptive controller provides intelligent control of the fuel processing device depending on the current operating situation and the type of power plant, implementing a cyclic algorithm for data analysis, task prioritization and generation of control commands.

Claims

1. An adaptive controller for controlling a fuel processing device of a power plant (PP), containing a microprocessor module installed in a housing, non-volatile memory, a data collection and communication unit for connection to PP and environmental sensors, and an output interface unit for communication with the fuel processing device, wherein the non-volatile memory stores a preset hierarchy of priorities for a variety of operational tasks, and the microprocessor module is software-implemented as a set of functionally interacting blocks, including an analysis unit configured to receive data from sensors via a data collection and communication unit and to identify relevant operational tasks based on a comparison of this data with preset threshold values; a prioritization unit, functionally connected to the analysis unit and non-volatile memory, configured to select one priority task from several identified on the basis of the specified priority hierarchy; and a mode selection unit, operatively connected to the prioritization unit and non-volatile memory, configured to generate a control command for the fuel processing device in accordance with the selected priority task and transmit this command through the output interface unit, wherein the analysis unit, the prioritization unit and the mode selection unit are configured to cyclically repeat the operations of receiving data, identifying tasks, selecting a priority task and generating a control command, thereby ensuring adaptive control of the fuel processing device in real time.

2. The controller according to claim 1, characterized in that the output interface block contains an analog output for generating a signal selected from the group: 0–5 V, 0–10 V or 4–20 mA, where the signal level corresponds to the selected priority task or operating mode of the fuel processing device.

3. The controller according to claim 1, characterized in that the output interface block additionally contains a digital communication interface selected from the group: CAN, RS-485, Modbus RTU, for exchanging data with the fuel processing device.

4. The controller according to claim 1, characterized in that the data collection and communication unit contains analog inputs for connecting sensors with an output signal selected from the group: 0–5 V, 0–10 V, 4–20 mA; discrete inputs / outputs; industrial communication interfaces selected from the group: CAN, J1939, Modbus, Profibus, for connecting to the standard control system of the power plant and to external sensors.

5. The controller according to claim 1, characterized in that the non-volatile memory contains several preset operating profiles, each of which includes the specified hierarchy of priorities and a set of control maps optimized for a specific type of power plant selected from the group: internal combustion engine, boiler unit, industrial furnace, gas turbine.

6. The controller according to claim 5, characterized in that the control maps contain data on the correspondence of the parameter values ​​received from the input interface unit to the parameters of the control command, and the controller is configured to correct the command parameters based on environmental data according to the rules laid down in the control map.

7. The controller according to claim 1, characterized in that it additionally contains a predictive analysis module, configured to predict changes in the parameters of the power plant based on the analysis of trends in historical data organized in the form of time series, the formation of predictive events when predicting the achievement of a threshold value by the controlled parameter, and the transmission of predictive events for the advance formation of control commands.

8. The controller according to claim 1, characterized in that preset threshold values ​​for identifying current operational tasks are stored in the non-volatile memory, wherein the threshold values ​​may be different for different types of power plants.

9. The controller according to claim 1, characterized in that the analysis unit is designed with the ability to normalize and filter the data received from the sensors before identifying the relevant tasks.

10. The controller according to claim 1, characterized in that the mode selection unit is configured to select a control card from a set stored in non-volatile memory and to generate a control command based on the selected card.

11. The controller according to item 1, characterized in that the housing has a protection rating of at least IP54 and is made with fasteners for mounting on a DIN rail.

12. The controller according to paragraph 1, characterized in that the microprocessor module is based on a 32-bit microcontroller with an ARM Cortex-M4 core.

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