A method for intelligent monitoring and optimal adjustment of thermal and electric loads of a combined heat and power unit

Abstract

The present application belongs to the field of thermal power load optimization, and discloses a kind of cogeneration unit thermal power load intelligent monitoring and optimization adjustment method, the present application is by collecting the temperature, pressure, flow, electric heating load, oxygen content, coal supply amount and environment temperature of cogeneration unit and other multi-source operation data, and the pre-processing of collected data, can form unified, continuous and easy-to-analyze standardized operation data, provide reliable data basis for subsequent state evaluation and load optimization. Through coal consumption characteristic analysis of coal supply amount data and electric heating load data, the coupling relationship between coal consumption change and electric load change, thermal load change is determined, the thermal power coal consumption correlation coefficient is obtained, which can reflect the dynamic correlation between thermal load, electric load and coal consumption of the unit under different operating conditions, and overcome the problem that fixed load distribution curve is difficult to adapt to variable operating conditions.

Description

Technical Field

[0001] The invention belongs to the field of thermoelectric load optimization, and particularly relates to an intelligent monitoring and optimized adjustment method for thermoelectric load of a cogeneration unit. Background Art

[0002] With the continuous expansion of the operation scale of cogeneration units and the continuous improvement of requirements for power grid peak shaving, central heating and energy conservation and consumption reduction, cogeneration units not only need to adjust power generation load according to power grid dispatching instructions, but also need to synchronously adjust heat load combined with changes in heating demand. Since the power generation process and the heating process share the boiler, steam turbine and steam system, there is a strong coupling relationship between electric load and heat load. When one type of load changes, it usually causes linkage changes of operating parameters such as steam pressure, steam flow, coal feed amount, furnace oxygen content and unit coal consumption. Therefore, how to meet the requirements of electric load and heat load while taking into account unit operation safety, environmental emission and fuel consumption has become an important issue in the operation control of cogeneration units.

[0003] Existing thermoelectric load adjustment methods usually determine the distribution ratio of electric load and heat load based on unit thermal characteristic test results, historical operation data and preset load distribution curves, and are manually adjusted by operators based on information such as main steam pressure, temperature, heating flow and external air temperature. Some prior art collects coal consumption data under different operation modes, different unit loads and different heating loads, performs fitting, cleaning and expansion on original data, establishes a unit coal consumption prediction model, and provides guidance suggestions for unit operation modes and thermoelectric load distribution based on the prediction results.

[0004] However, during actual operation, cogeneration units are affected by various factors such as unit load changes, heating demand fluctuations, equipment status and environmental temperature changes. Load adjustment schemes formed based on historical test data or fixed distribution curves can hardly timely reflect the dynamic coupling relationship between heat load, electric load and coal consumption under current working conditions. At the same time, the prior art often focuses on coal consumption prediction and operation scheme analysis, and independently judges safety parameters such as pressure and flow, environmental protection parameters such as oxygen content, and heating demand corresponding to environmental temperature, which makes it difficult to form comprehensive constraints that take into account safety boundaries, environmental protection status and heating matching degree. In addition, existing prediction results are usually used to generate analysis reports or assist operators to formulate adjustment schemes, lacking a closed-loop adjustment process that performs real-time deviation comparison between optimized load distribution results and the current actual load of the unit and further forms control instructions. Summary of the Invention

[0005] The purpose of the present invention is to overcome the above deficiencies and provide an intelligent monitoring and optimized adjustment method for thermoelectric load of a cogeneration unit.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for intelligent monitoring and optimized regulation of the thermal and power load of a combined heat and power unit, comprising the following steps: Collect temperature, pressure, flow, electrical and thermal load, oxygen, coal feed, and ambient temperature data from the cogeneration unit, and preprocess the collected data to obtain standardized operating data. Based on the coal feed data and power and heat load data in the standardized operation data, coal consumption characteristics are analyzed to determine the coupling relationship between coal consumption changes and power load changes and heat load changes, and the correlation coefficient of thermal power coal consumption is obtained. Based on the pressure, flow, and ambient temperature data in the standardized operating data, an operational safety boundary analysis is performed to obtain a dynamic safety assessment coefficient; based on the flow, oxygen, and ambient temperature data in the standardized operating data, an environmental protection status and heating status analysis is performed to obtain an environmental protection heating detection coefficient. With the total coal consumption of the cogeneration unit as the optimization objective and the dynamic safety assessment coefficient and environmental heating detection coefficient as constraints, a cogeneration load optimization allocation model is constructed based on the cogeneration coal consumption correlation coefficient and the current electricity load demand and heat load demand. The optimal load allocation strategy is obtained by solving the cogeneration load optimization allocation model. The optimal load allocation strategy is compared with the current actual electrical load and actual heat load of the cogeneration unit to obtain the load allocation deviation. Based on the load allocation deviation, a load control command is generated and sent to the control system of the cogeneration unit.

[0007] A further improvement of this invention lies in the following method for collecting temperature data, pressure data, flow rate data, electrical and thermal load data, oxygen content data, coal feed rate data, and ambient temperature data from a combined heat and power (CHP) unit, and preprocessing the collected data to obtain standardized operating data: Collect temperature data, pressure data, flow data, electrical and thermal load data, oxygen content data, coal feed data, and ambient temperature data of the combined heat and power unit; According to the preset sampling frequency, the temperature data, pressure data, flow data, electric heating load data, oxygen data, coal feed data and ambient temperature data are timestamped to form runtime sequence data; Identify and remove abnormal data in runtime sequence data, and interpolate and fill in the missing time sequence nodes corresponding to the abnormal data. The interpolated runtime sequence data is normalized to obtain standardized runtime data.

[0008] A further improvement of this invention lies in the following method for analyzing coal consumption characteristics based on coal feed rate data and electrical / thermal load data from standardized operating data, determining the coupling relationship between coal consumption changes and electrical / thermal load changes, and obtaining the correlation coefficient between thermal power coal consumption: The coal consumption change rate is calculated based on the coal feed rate data in the standardized operation data, and the electrical load change rate and thermal load change rate are calculated based on the electrical and thermal load data in the standardized operation data, respectively. Within the same time window, the coal consumption change rate is matched with the change rates of electricity load and heat load respectively to obtain the first synchronous change ratio of the coal consumption change rate relative to the change rate of electricity load, and the second synchronous change ratio of the coal consumption change rate relative to the change rate of heat load. The first synchronous change ratio and the second synchronous change ratio are weighted and calculated to obtain the correlation coefficient of thermal power coal consumption.

[0009] A further improvement of this invention lies in the following method for obtaining dynamic safety assessment coefficients through operational safety boundary analysis based on pressure data, flow data, and ambient temperature data from standardized operational data: Calculate the pressure difference between the preset pressure safety threshold and the current pressure value, and determine the pressure safety margin as the ratio of the pressure difference to the preset pressure safety threshold. Calculate the flow difference between the preset flow safety limit and the current flow value, and determine the flow safety margin as the ratio of the flow difference to the preset flow safety limit; The smaller value between the pressure safety margin and the flow safety margin is selected to obtain the basic safety boundary margin; Based on ambient temperature data and the preset mapping relationship between ambient temperature and unit back pressure, a temperature correction factor is obtained. The dynamic safety assessment coefficient is then calculated based on the basic safety boundary margin and the temperature correction factor.

[0010] A further improvement of this invention lies in the following method for obtaining the environmental protection heating detection coefficient by analyzing the environmental protection status and heating status based on the flow rate data, oxygen content data, and ambient temperature data in the standardized operating data: Calculate the oxygen difference between the current oxygen level and the preset environmental compliance oxygen level benchmark value, and determine the ratio of the oxygen difference to the preset environmental compliance oxygen level benchmark value as the environmental deviation degree; Input the ambient temperature data into the preset air temperature and heating mapping model to obtain the demand baseline flow value corresponding to the current ambient temperature; Calculate the flow deviation between the current heating flow rate and the baseline demand flow rate, and determine the ratio of the flow deviation to the baseline demand flow rate as the supply-demand deviation degree. The environmental protection deviation and the supply-demand deviation are weighted and calculated to obtain the environmental protection heating detection coefficient.

[0011] A further improvement of this invention lies in that, taking the total coal consumption of the combined heat and power (CHP) unit as the optimization objective and the dynamic safety assessment coefficient and environmental heating detection coefficient as constraints, a CHP load optimization allocation model is constructed based on the CHP coal consumption correlation coefficient and the current electricity load demand and heat load demand. The specific method for solving the CHP load optimization allocation model to obtain the optimal load allocation strategy is as follows: Using the current electricity load demand and the current heat load demand as load allocation variables, the objective function is to minimize the predicted total coal consumption of the cogeneration unit. Safety constraints are set based on dynamic safety assessment coefficients, and environmental protection heating constraints are set based on environmental protection heating detection coefficients. A thermal power load optimization allocation model is then established. Adjust the distribution ratio between electrical load and heat load according to the correlation coefficient of thermal power coal consumption, and calculate the predicted total coal consumption, predicted dynamic safety assessment coefficient and predicted environmental protection heating detection coefficient corresponding to different distribution ratios. From the allocation ratios that meet both safety and environmental protection heating constraints, the allocation ratio with the minimum predicted total coal consumption is selected to obtain the optimal load allocation strategy.

[0012] A further improvement of this invention lies in the following method for obtaining the deviation of the heat and power load allocation by performing a deviation analysis between the optimal load allocation strategy and the current actual electrical and thermal loads of the cogeneration unit: The difference between the target electrical load in the optimal load allocation strategy and the current actual electrical load of the cogeneration unit is calculated to obtain the electrical load deviation. The difference between the target heat load in the optimal load allocation strategy and the current actual heat load of the cogeneration unit is calculated to obtain the heat load deviation. The absolute values ​​of the electrical load deviation and the thermal load deviation are weighted and calculated to obtain the thermal load distribution deviation value. The corresponding load adjustment direction is determined according to the positive and negative directions of the electrical load deviation and the thermal load deviation.

[0013] A further improvement of this invention lies in the following method for generating a heat and power load control command based on the heat and power load distribution deviation and sending the heat and power load control command to the control system of the cogeneration unit: Compare the thermal load distribution deviation value with the preset command trigger threshold; When the deviation value of the thermoelectric load distribution is greater than the preset command trigger threshold, a thermoelectric load control command including the electric load adjustment amount and the heat load adjustment amount is generated according to the electric load deviation, the heat load deviation and the corresponding load adjustment direction; The cogeneration load control command is sent to the distributed control system of the cogeneration unit, which then controls the corresponding load regulation actuators based on the electrical load regulation and thermal load regulation.

[0014] Secondly, the present invention provides a combined heat and power unit heat and power load monitoring and optimization regulation system, comprising: The data acquisition module is used to collect temperature data, pressure data, flow data, electrical and thermal load data, oxygen data, coal feed data, and ambient temperature data of the cogeneration unit. The collected data is preprocessed to obtain standardized operating data. The coal consumption correlation analysis module is used to analyze coal consumption characteristics based on coal feed data and electric and heat load data in standardized operating data, determine the coupling relationship between coal consumption changes and changes in electric load and heat load, and obtain the thermal power coal consumption correlation coefficient. The safety assessment module is used to perform operational safety boundary analysis based on pressure data, flow data, and ambient temperature data in standardized operating data to obtain dynamic safety assessment coefficients; and to perform environmental protection status and heating status analysis based on flow data, oxygen data, and ambient temperature data in standardized operating data to obtain environmental protection heating detection coefficients. The load optimization module is used to construct a combined heat and power load optimization allocation model based on the total coal consumption of the combined heat and power unit as the optimization objective, the dynamic safety assessment coefficient and the environmental protection heating detection coefficient as constraints, the correlation coefficient of coal consumption of heat and power and the current electricity load demand and heat load demand, and solve the optimized load allocation model to obtain the optimal load allocation strategy. The control command generation module is used to perform deviation analysis between the optimal load allocation strategy and the current actual electrical load and actual heat load of the cogeneration unit to obtain the load allocation deviation. Based on the load allocation deviation, the module generates load control commands for the cogeneration unit and sends the load control commands to the control system of the cogeneration unit.

[0015] A further improvement of the present invention is that the data acquisition module is connected to the distributed control system of the cogeneration unit and the meteorological monitoring equipment installed outside the cogeneration unit. The data acquisition module obtains temperature data, pressure data, flow data, electrical and heating load data, oxygen data, and coal feed data through the bottom-level measuring points of the distributed control system, and obtains ambient temperature data through meteorological monitoring equipment; The control command generation module is connected to the distributed control system and is used to send a thermoelectric load control command, including electrical load adjustment and thermal load adjustment, to the distributed control system when the thermoelectric load distribution deviation value is greater than the preset command trigger threshold.

[0016] Compared with the prior art, the present invention has the following beneficial effects: This invention collects multi-source operational data from combined heat and power (CHP) units, including temperature, pressure, flow rate, electrical and thermal load, oxygen content, coal feed rate, and ambient temperature. By preprocessing the collected data, it generates standardized operational data that is unified, continuous, and easy to analyze, providing a reliable data foundation for subsequent condition assessment and load optimization. Through coal consumption characteristic analysis of coal feed rate and electrical and thermal load data, the coupling relationship between coal consumption changes and changes in electrical and thermal loads is determined, obtaining the CHP-coal consumption correlation coefficient. This coefficient reflects the dynamic correlation between thermal load, electrical load, and coal consumption under different operating conditions, overcoming the problem that fixed load allocation curves are difficult to adapt to variable operating conditions. By combining pressure, flow rate, and ambient temperature for operational safety boundary analysis, and combining flow rate, oxygen content, and ambient temperature for environmental and heating status analysis, comprehensive constraints that consider unit operational safety, environmental requirements, and heating demand can be formed. Based on this, a CHP load optimization allocation model is constructed with total coal consumption as the optimization objective, achieving a load allocation strategy with lower coal consumption while meeting safety and environmental heating constraints. This invention analyzes the deviation between the optimal load allocation strategy and the actual electrical and thermal loads of the unit, automatically generates and sends thermal and electrical load control commands, and realizes closed-loop control from data monitoring, status assessment, optimization calculation to load regulation, thereby improving the rationality, real-time performance and economy of the unit's thermal and electrical load allocation. Attached Figure Description

[0017] Figure 1 This is a flowchart of the present invention; Figure 2 This is a system diagram of the present invention. Detailed Implementation To further understand the content of this invention, the invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments are merely illustrative and not limiting of the invention.

[0018] Example 1: See Figure 1 This embodiment includes the following steps: S1 collects temperature, pressure, flow, electrical and thermal load, oxygen, coal feed, and ambient temperature data from the cogeneration unit. The collected data is preprocessed to obtain standardized operating data.

[0019] Specifically, the data acquisition module is connected to the distributed control system of the cogeneration unit and meteorological monitoring equipment located outside the cogeneration unit. By reading the corresponding low-level measuring points of the distributed control system in real time, it acquires temperature data, pressure data, flow data, electrical load data, heat load data, oxygen data, and coal feed data during the operation of the cogeneration unit; and by reading the meteorological monitoring equipment in real time, it acquires the ambient temperature data of the area where the cogeneration unit is located.

[0020] The temperature data includes at least one of the following: main steam temperature, reheat steam temperature, feedwater temperature, and heating medium temperature; the pressure data includes at least one of the following: main steam pressure, extraction steam pressure, and heating pipeline pressure; the flow data includes at least one of the following: main steam flow rate, extraction steam flow rate, heating flow rate, and feedwater flow rate; and the electrical and heating load data includes the unit's actual electrical load, current electrical load demand, the unit's actual heat load, and current heat load demand.

[0021] According to the preset sampling frequency, the temperature data, pressure data, flow data, electric heating load data, oxygen data, coal feed data and ambient temperature data are timestamped so that different data sources have corresponding data values ​​at the same sampling time, forming runtime sequence data.

[0022] For example, the preset sampling frequency is 1Hz, and data such as main steam pressure, coal feed rate, actual electrical load, actual heat load, and ambient temperature are acquired from the distributed control system and meteorological monitoring equipment. A Unix timestamp is uniformly appended to the collected data. For data with different sampling frequencies, resampling processing can be used to convert them to a unified time scale.

[0023] Outlier identification is performed on runtime sequence data. Specifically, the Raida criterion can be used to iterate through each operational data point. When a data value at a given moment exceeds three times the standard deviation of the corresponding historical data mean, that data value is identified as outlier and removed. The outlier identification method can also be configured based on the allowable operating range of the unit equipment, the rate of data change, or the continuity of adjacent data.

[0024] For the missing time series nodes generated after the abnormal data is removed, the cubic spline interpolation algorithm is used to extract the normal data points before and after the missing time series node and perform curve fitting to obtain the interpolation filling value corresponding to the missing time series node, thereby forming continuous runtime time series data.

[0025] The interpolated runtime sequence data is then normalized. When using the min-max normalization method, the... The standardized values ​​of the item's running data are represented as follows:

[0026] In the formula, These are the normalized data values; These are the data values ​​before normalization; This represents the minimum value of the corresponding data type within a preset time range. This represents the maximum value of the corresponding data type within a preset time range.

[0027] Through normalization, the various operational data are mapped to... The interval eliminates the differences in dimensions and orders of magnitude between data such as temperature, pressure, flow rate, electrical load, thermal load, and coal feed rate, and obtains standardized operating data.

[0028] S2. Based on the coal feed data and electrical and thermal load data in the standardized operation data, coal consumption characteristics are analyzed to determine the coupling relationship between coal consumption changes and electrical load changes and thermal load changes, and to obtain the thermal-electricity coal consumption correlation coefficient.

[0029] Specifically, a time window is set for coal consumption characteristic analysis. For example, the time window is set to 60 seconds. Within this time window, the coal consumption change rate is calculated based on the coal feed data in the standardized operating data, and the electrical load change rate and thermal load change rate are calculated based on the electrical and thermal load data, respectively.

[0030] The rate of change in coal consumption can be expressed as:

[0031] The rate of change of electrical load can be expressed as:

[0032] The rate of change of heat load can be expressed as:

[0033] In the formula, This represents the rate of change in coal consumption. The rate of change of electrical load; This represents the rate of change of heat load. and These represent the coal feed rates at adjacent sampling times; and These represent the electrical loads at adjacent sampling times; and These represent the heat load at adjacent sampling times; This represents the time interval between adjacent sampling times.

[0034] Within the same time window, the coal consumption change rate is matched with the change rates of electricity load and heat load, respectively, in terms of direction. When the change direction of coal feed is consistent with the change direction of electricity load, the first synchronous change ratio is calculated based on the coal consumption change rate and the change rate of electricity load; when the change direction of coal feed is consistent with the change direction of heat load, the second synchronous change ratio is calculated based on the coal consumption change rate and the change rate of heat load.

[0035] The first synchronous change ratio can be expressed as:

[0036] The second synchronous change ratio can be expressed as:

[0037] In the formula, The first synchronous change ratio is used to characterize the dynamic response amplitude of coal consumption corresponding to a unit change in electrical load; This is the second synchronous change ratio, used to characterize the dynamic response amplitude of coal consumption corresponding to a unit change in heat load.

[0038] When the rate of change of electrical load or the rate of change of thermal load is zero, the corresponding synchronous change ratio can be set to a preset value, or the data at that sampling time can be excluded from the calculation of the synchronous change ratio of the current time window to avoid a division by zero.

[0039] Based on historical operating data, performance test results, or operating experience, electrical load weights and thermal load weights are set. The first synchronous change ratio and the second synchronous change ratio are weighted and calculated to obtain the thermal power coal consumption correlation coefficient.

[0040] in:

[0041] In the formula, The correlation coefficient between thermal power coal consumption; Weighting based on electrical load; This represents the heat load weight.

[0042] For example, if the weight of electrical load is set to 0.4 and the weight of thermal load is set to 0.6, then the correlation coefficient between thermal power coal consumption is:

[0043] The aforementioned thermal power coal consumption correlation coefficient comprehensively characterizes the dynamic coupling degree between changes in electrical load, thermal load, and coal consumption under current variable operating conditions.

[0044] S3 performs operational safety boundary analysis based on pressure, flow, and ambient temperature data from standardized operational data to obtain dynamic safety assessment coefficients.

[0045] Specifically, a pressure safety threshold and a flow safety limit are preset. The pressure safety threshold can be determined based on the maximum allowable working pressure specified in the equipment nameplate, design parameters, and operating procedures of the key pressure-bearing components of the unit; the flow safety limit can be determined based on the maximum design flow capacity of the heating pipeline or steam pipeline.

[0046] Calculate the pressure difference between the preset pressure safety threshold and the current pressure value, and determine the ratio of the pressure difference to the preset pressure safety threshold as the pressure safety margin:

[0047] In the formula, For pressure safety margin; Preset pressure safety threshold; This represents the current pressure value.

[0048] For example, if the current main steam pressure is 24 MPa and the preset pressure safety threshold is 25 MPa, then the pressure safety margin is:

[0049] Calculate the flow difference between the preset flow safety limit and the current flow value, and determine the flow safety margin as the ratio of the flow difference to the preset flow safety limit.

[0050] In the formula, For traffic safety margin; Preset traffic safety limits; This represents the current traffic volume.

[0051] The smaller value between the pressure safety margin and the flow safety margin is selected as the basic safety boundary margin:

[0052] In the formula, Based on the basic safety boundary margin.

[0053] For example, if the pressure safety margin is 0.04 and the flow safety margin is 0.03, then the basic safety boundary margin is 0.03.

[0054] Based on the design characteristics of the cold-end system of the combined heat and power (CHP) unit, historical operating data, or performance test data, a mapping relationship between ambient temperature and unit back pressure is established in advance. This mapping relationship can be expressed as a table of ambient temperature and back pressure correspondences, or as a function curve fitted from historical data.

[0055] The current ambient temperature is obtained and compared with a preset reference temperature to obtain the ambient temperature deviation value. The corresponding back pressure change ratio is then found in the linear interpolation data table based on this deviation value, or the ambient temperature deviation value is input into a preset fitting function to obtain the back pressure change ratio. The temperature correction factor is then obtained based on the back pressure change ratio.

[0056] In the formula, This is a temperature correction factor; This represents the percentage change in back pressure corresponding to ambient temperature.

[0057] For example, if the reference temperature is set to 20℃, and the back pressure change ratio is calculated to be 20% based on the deviation between the current ambient temperature and the reference temperature, then the temperature correction factor is:

[0058] Calculate the dynamic safety assessment coefficient based on the basic safety boundary margin and temperature correction factor:

[0059] In the formula, This is the dynamic safety assessment coefficient.

[0060] For example, if the basic safety margin is 0.03 and the temperature correction factor is 1.2, then the dynamic safety assessment coefficient is:

[0061] Therefore, by combining the unit's internal operating parameters such as pressure and flow rate with the changes in unit back pressure caused by ambient temperature, a safety boundary evaluation result that changes with real-time operating conditions is formed.

[0062] S4 analyzes the environmental and heating status based on the flow rate, oxygen content, and ambient temperature data in the standardized operation data to obtain the environmental heating detection coefficient.

[0063] Specifically, an environmental compliance oxygen level benchmark value is set based on environmental emission requirements and the unit's historical best combustion test results. The oxygen level difference between the current oxygen level and the environmental compliance oxygen level benchmark value is calculated, and the ratio of the oxygen level difference to the environmental compliance oxygen level benchmark value is determined as the environmental deviation degree.

[0064] In the formula, Environmental deviation degree; This is the current oxygen level. To preset the baseline value for oxygen content to meet environmental protection standards.

[0065] For example, if the baseline oxygen content for environmental compliance is set at 3.5%, and the current oxygen content is 4.2%, then the environmental deviation is:

[0066] A temperature-heating mapping model is constructed in advance based on the heat load prediction curves of the heating network under different ambient temperatures. This temperature-heating mapping model outputs the baseline demand flow value corresponding to the current ambient temperature, and can be implemented using a data table, piecewise function, or linear function.

[0067] In one implementation, the temperature-heating mapping model is represented as follows:

[0068] In the formula, This is the baseline flow rate for demand, expressed in t / h. The current ambient temperature is expressed in °C.

[0069] For example, if the current ambient temperature is -10℃, then the baseline flow rate demand is:

[0070] Calculate the flow deviation between the current heating flow rate and the baseline demand flow rate, and determine the supply-demand deviation ratio as the ratio of the flow deviation to the baseline demand flow rate.

[0071] In the formula, The degree of deviation between supply and demand; This represents the current heating flow rate.

[0072] For example, if the current heating flow rate is 50 t / h and the baseline demand flow rate is 55 t / h, then the supply-demand deviation is:

[0073] Based on preset environmental protection weights and heating weights, the environmental protection deviation and supply-demand deviation are weighted and calculated to obtain the environmental protection heating detection coefficient:

[0074] in:

[0075] In the formula, Environmental heating testing coefficient; Environmental weighting; For heating weight.

[0076] For example, if the environmental protection weight is set to 0.6 and the heating weight is set to 0.4, then:

[0077] By using the environmentally friendly heating detection coefficient, the matching status of combustion environmental protection and heating demand corresponding to the current ambient temperature is converted into a unified quantitative detection result.

[0078] S5 takes the total coal consumption of the cogeneration unit as the optimization objective and the dynamic safety assessment coefficient and environmental protection heating detection coefficient as constraints. Based on the correlation coefficient of cogeneration coal consumption and the current electricity load demand and heat load demand, a cogeneration load optimization allocation model is constructed. The cogeneration load optimization allocation model is solved to obtain the optimal load allocation strategy.

[0079] Specifically, the current electricity load demand and current heat load demand are input into the heat and power load optimization allocation model, with the electricity load allocation value and heat load allocation value as load allocation variables, and the minimum predicted total coal consumption is set as the objective function:

[0080] In the formula, Distribute values ​​to electrical load and heat load distribution value The corresponding predicted total coal consumption.

[0081] Load demand constraints are set based on current electrical and thermal load demands, and load boundary constraints are set based on the allowable electrical and thermal load ranges of the units. Safety constraints are set based on dynamic safety assessment coefficients, and environmental protection heating constraints are set based on environmental protection heating monitoring coefficients.

[0082]

[0083] In the formula, The predicted dynamic security assessment coefficient corresponding to the current load allocation ratio; The lower limit of the safety constraint threshold; The predicted environmental protection heating detection coefficient corresponding to the current load allocation ratio; The upper limit threshold for environmentally friendly heating.

[0084] The lower safety limit constraint threshold is set according to the minimum safety margin bottom line specified in the unit operation procedure, while the upper environmental protection heating limit constraint threshold is set according to the environmental emission assessment requirements and the allowable deviation range of heating.

[0085] The adjustment direction or step size of the distribution ratio between electrical load and heat load is determined based on the correlation coefficient between thermal power coal consumption, and iterative calculations are performed for different electrical load distribution values ​​and heat load distribution values. In each iteration, the predicted total coal consumption, predicted dynamic safety assessment coefficient, and predicted environmental protection heating detection coefficient corresponding to the current load distribution ratio are calculated.

[0086] The algorithm determines whether the predicted dynamic safety assessment coefficient is greater than or equal to the lower safety limit constraint threshold, and whether the predicted environmentally friendly heating detection coefficient is less than or equal to the upper environmentally friendly heating limit constraint threshold. When both constraints are met, the algorithm records the current electrical load allocation value, the heat load allocation value, and the corresponding predicted total coal consumption. When either constraint is not met, the algorithm adjusts the allocation ratio between electrical load and heat load according to the thermal-electricity coal consumption correlation coefficient, and proceeds to the next iteration.

[0087] After completing the preset number of iterations or reaching the preset convergence condition, the load allocation results that meet all safety constraints and environmental protection heating constraints are compared, and the load allocation ratio with the minimum predicted total coal consumption is selected. The target electrical load and target thermal load corresponding to this load allocation ratio are taken as the optimal load allocation strategy.

[0088] For example, if the current electricity load demand is 300MW and the current heat load demand is 500GJ, the lower safety limit constraint threshold is set to 0.03, and the upper environmental protection heating limit constraint threshold is set to 0.084. In the first iteration, the electricity load allocation value is set to 150MW and the heat load allocation value is set to 250GJ, and the predicted total coal consumption, predicted dynamic safety assessment coefficient, and predicted environmental protection heating detection coefficient corresponding to the current load allocation ratio are calculated.

[0089] When the predicted dynamic safety assessment coefficient is less than 0.03 or the predicted environmentally friendly heating detection coefficient is greater than 0.084, the load allocation ratio is adjusted according to the correlation coefficient between thermal power coal consumption. When the predicted dynamic safety assessment coefficient is greater than or equal to 0.03 and the predicted environmentally friendly heating detection coefficient is less than or equal to 0.084, the current predicted total coal consumption is recorded and the iteration continues. After multiple iterations, the result with the minimum predicted total coal consumption is extracted from the load allocation results that meet the constraints. For example, if the corresponding target electrical load is 200MW and the target thermal load is 350GJ, then the target electrical load of 200MW and the target thermal load of 350GJ are taken as the optimal load allocation strategy.

[0090] S6 performs a deviation analysis between the optimal load allocation strategy and the current actual electrical and thermal loads of the cogeneration unit to obtain the load allocation deviation. Based on the load allocation deviation, it generates a load control command for the cogeneration unit and sends the load control command to the control system of the cogeneration unit.

[0091] Specifically, the difference between the target electrical load in the optimal load allocation strategy and the current actual electrical load is calculated to obtain the electrical load deviation:

[0092] In the formula, This is the electrical load deviation; For the target electrical load; This represents the current actual electrical load.

[0093] The heat load deviation is obtained by calculating the difference between the target heat load in the optimal load allocation strategy and the current actual heat load:

[0094] In the formula, This is due to the deviation in heat load. The target heat load; This represents the current actual heat load.

[0095] The corresponding load adjustment direction is determined based on the positive and negative directions of the electrical load deviation and the thermal load deviation. When the electrical load deviation is positive, the direction of electrical load adjustment is to increase; when the electrical load deviation is negative, the direction of electrical load adjustment is to decrease. When the thermal load deviation is positive, the direction of thermal load adjustment is to increase; when the thermal load deviation is negative, the direction of thermal load adjustment is to decrease.

[0096] The absolute values ​​of the electrical load deviation and the thermal load deviation are weighted and calculated to obtain the thermal-electric load distribution deviation value:

[0097] in:

[0098] In the formula, This refers to the deviation value for the distribution of thermal and electrical loads. Weighting for electrical load deviation; This represents the weighting of the heat load deviation.

[0099] The deviation value of the thermoelectric load distribution is compared with a preset command trigger threshold. The command trigger threshold can be set according to the minimum insensitivity zone allowed by the distributed control system and the anti-jitter requirements of frequent actuator movements.

[0100] When the deviation value of the thermal and electrical load distribution is less than or equal to the preset command trigger threshold, no new thermal and electrical load control command is generated, and the current operating status of the unit is maintained; when the deviation value of the thermal and electrical load distribution is greater than the preset command trigger threshold, a thermal and electrical load control command including the electrical load adjustment amount and the thermal load adjustment amount is generated according to the electrical load deviation, the thermal load deviation and the corresponding load adjustment direction.

[0101] For example, if the target electrical load in the optimal load allocation strategy is 200MW and the target thermal load is 350GJ, and the current actual electrical load of the cogeneration unit is 180MW and the current actual thermal load is 360GJ, then:

[0102]

[0103] The direction of electrical load adjustment is increasing, and the direction of thermal load adjustment is decreasing. Setting both the electrical load deviation weight and the thermal load deviation weight to 0.5, the thermal-electric load distribution deviation value is:

[0104] The preset command trigger threshold is set to 10. Since the thermal load distribution deviation value of 15 is greater than the preset command trigger threshold of 10, a thermal load control command of "electric load increase by 20MW and thermal load decrease by 10GJ" is generated.

[0105] The heat and power load control command is sent to the distributed control system of the cogeneration unit. The distributed control system controls the turbine regulating valve, the heating extraction regulating valve, the coal feeding mechanism, and the underlying actuators related to the heat and power load adjustment to complete the load adjustment based on the electrical load adjustment and the heat load adjustment.

[0106] After executing the cogeneration load control command, the temperature, pressure, flow, electric and heat load, oxygen, coal feed, and ambient temperature data of the cogeneration unit are collected again. The cogeneration coal consumption correlation coefficient, dynamic safety assessment coefficient, environmental heating detection coefficient, and optimal load allocation strategy are recalculated according to the above steps, thus forming a closed-loop regulation process of cogeneration load monitoring, optimization calculation, control command generation, and operation feedback.

[0107] Example 2: See Figure 2 This embodiment also provides a cogeneration unit heat and power load monitoring and optimization regulation system, including a data acquisition module, a coal consumption correlation analysis module, a safety assessment module, a load optimization module, and a control command generation module.

[0108] The data acquisition module is connected to the distributed control system of the cogeneration unit and the meteorological monitoring equipment located outside the cogeneration unit. The data acquisition module obtains temperature, pressure, flow, electrical and thermal load, oxygen, and coal feed data through the bottom-level measuring points of the distributed control system, and acquires ambient temperature data through the meteorological monitoring equipment. It then performs timestamp alignment, anomaly identification and removal, interpolation to fill missing time-series nodes, and normalization processing on the acquired data to obtain standardized operating data.

[0109] The coal consumption correlation analysis module is connected to the data acquisition module. It is used to calculate the coal consumption change rate based on the coal feed data in the standardized operation data, calculate the electrical load change rate and the heat load change rate based on the electrical and heat load data, match the change direction of the coal consumption change rate, electrical load change rate and heat load change rate, and obtain the thermal-electricity coal consumption correlation coefficient based on the first synchronous change ratio and the second synchronous change ratio.

[0110] The safety assessment module is connected to the data acquisition module and is used to perform operational safety boundary analysis based on pressure data, flow data, and ambient temperature data in the standardized operation data to obtain dynamic safety assessment coefficients. The safety assessment module is also used to perform environmental protection status and heating status analysis based on flow data, oxygen data, and ambient temperature data in the standardized operation data to obtain environmental protection heating detection coefficients.

[0111] The load optimization module is connected to the coal consumption correlation analysis module and the safety assessment module, respectively. It is used to construct a cogeneration load optimization allocation model based on the total coal consumption of the cogeneration unit as the optimization target, the dynamic safety assessment coefficient and the environmental protection heating detection coefficient as constraints, the cogeneration coal consumption correlation coefficient and the current electricity load demand and heat load demand, the iterative calculation of different electricity load and heat load allocation ratios, and the selection of the load allocation ratio with the minimum predicted total coal consumption from the load allocation ratios that meet the safety constraints and environmental protection heating constraints, so as to obtain the optimal load allocation strategy.

[0112] The control command generation module is connected to both the load optimization module and the distributed control system. It performs deviation analysis between the target electrical load and target thermal load in the optimal load allocation strategy and the current actual electrical load and current actual thermal load of the cogeneration unit, obtaining the electrical load deviation, thermal load deviation, and cogeneration load allocation deviation values. When the cogeneration load allocation deviation value exceeds a preset command trigger threshold, the control command generation module generates a cogeneration load control command, including electrical load adjustment amounts and thermal load adjustment amounts, based on the electrical load deviation, thermal load deviation, and the corresponding load adjustment direction. This command is then sent to the distributed control system.

[0113] After receiving the cogeneration load control command, the distributed control system controls the corresponding load regulation actuators according to the electrical load adjustment and heat load adjustment amounts, adjusting the actual electrical load and actual heat load of the cogeneration unit. The adjusted operating data is then resent to the data acquisition module, causing each module to operate cyclically in the order of data acquisition, coal consumption correlation analysis, safety and environmental protection heating assessment, load optimization, and control command generation, thereby achieving continuous monitoring and optimized regulation of the cogeneration unit's thermal and electrical load.

[0114] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for intelligent monitoring and optimized regulation of the heat and power load of a combined heat and power unit, characterized in that, Includes the following steps: Collect temperature, pressure, flow, electrical and thermal load, oxygen, coal feed, and ambient temperature data from the cogeneration unit, and preprocess the collected data to obtain standardized operating data. Based on the coal feed data and power and heat load data in the standardized operation data, coal consumption characteristics are analyzed to determine the coupling relationship between coal consumption changes and power load changes and heat load changes, and the correlation coefficient of thermal power coal consumption is obtained. Based on the pressure data, flow data and ambient temperature data in the standardized operating data, an operational safety boundary analysis is performed to obtain dynamic safety assessment coefficients. Based on the flow rate data, oxygen content data and ambient temperature data in the standardized operation data, the environmental protection status and heating status are analyzed to obtain the environmental protection heating detection coefficient. With the total coal consumption of the cogeneration unit as the optimization objective and the dynamic safety assessment coefficient and environmental heating detection coefficient as constraints, a cogeneration load optimization allocation model is constructed based on the cogeneration coal consumption correlation coefficient and the current electricity load demand and heat load demand. The optimal load allocation strategy is obtained by solving the cogeneration load optimization allocation model. The optimal load allocation strategy is compared with the current actual electrical load and actual heat load of the cogeneration unit to obtain the load allocation deviation. Based on the load allocation deviation, a load control command is generated and sent to the control system of the cogeneration unit.

2. The method for intelligent monitoring and optimized regulation of cogeneration unit heat and power load according to claim 1, characterized in that, The specific method for collecting temperature, pressure, flow, electrical and thermal load, oxygen, coal feed, and ambient temperature data from combined heat and power (CHP) units and preprocessing the collected data to obtain standardized operating data is as follows: Collect temperature data, pressure data, flow data, electrical and thermal load data, oxygen content data, coal feed data, and ambient temperature data of the combined heat and power unit; According to the preset sampling frequency, the temperature data, pressure data, flow data, electric heating load data, oxygen data, coal feed data and ambient temperature data are timestamped to form runtime sequence data; Identify and remove abnormal data in runtime sequence data, and interpolate and fill in the missing time sequence nodes corresponding to the abnormal data. The interpolated runtime sequence data is normalized to obtain standardized runtime data.

3. The method for intelligent monitoring and optimized regulation of cogeneration unit heat and power load according to claim 1, characterized in that, Based on the coal feed rate data and electrical / thermal load data in the standardized operating data, coal consumption characteristics are analyzed to determine the coupling relationship between coal consumption changes and electrical / thermal load changes. The specific method for obtaining the correlation coefficient between thermal power coal consumption is as follows: The coal consumption change rate is calculated based on the coal feed rate data in the standardized operation data, and the electrical load change rate and thermal load change rate are calculated based on the electrical and thermal load data in the standardized operation data, respectively. Within the same time window, the coal consumption change rate is matched with the change rates of electricity load and heat load respectively to obtain the first synchronous change ratio of the coal consumption change rate relative to the change rate of electricity load, and the second synchronous change ratio of the coal consumption change rate relative to the change rate of heat load. The first synchronous change ratio and the second synchronous change ratio are weighted and calculated to obtain the correlation coefficient of thermal power coal consumption.

4. The method for intelligent monitoring and optimized regulation of cogeneration unit heat and power load according to claim 1, characterized in that, The specific method for obtaining dynamic safety assessment coefficients through operational safety boundary analysis based on pressure, flow, and ambient temperature data from standardized operational data is as follows: Calculate the pressure difference between the preset pressure safety threshold and the current pressure value, and determine the pressure safety margin as the ratio of the pressure difference to the preset pressure safety threshold. Calculate the flow difference between the preset flow safety limit and the current flow value, and determine the flow safety margin as the ratio of the flow difference to the preset flow safety limit; The smaller value between the pressure safety margin and the flow safety margin is selected to obtain the basic safety boundary margin; Based on ambient temperature data and the preset mapping relationship between ambient temperature and unit back pressure, a temperature correction factor is obtained. The dynamic safety assessment coefficient is then calculated based on the basic safety boundary margin and the temperature correction factor.

5. The method for intelligent monitoring and optimized regulation of cogeneration unit heat and power load according to claim 1, characterized in that, The specific method for obtaining the environmental protection and heating status detection coefficient by analyzing the flow rate data, oxygen content data, and ambient temperature data from standardized operational data is as follows: Calculate the oxygen difference between the current oxygen level and the preset environmental compliance oxygen level benchmark value, and determine the ratio of the oxygen difference to the preset environmental compliance oxygen level benchmark value as the environmental deviation degree; Input the ambient temperature data into the preset air temperature and heating mapping model to obtain the demand baseline flow value corresponding to the current ambient temperature; Calculate the flow deviation between the current heating flow rate and the baseline demand flow rate, and determine the ratio of the flow deviation to the baseline demand flow rate as the supply-demand deviation degree. The environmental protection deviation and the supply-demand deviation are weighted and calculated to obtain the environmental protection heating detection coefficient.

6. The method for intelligent monitoring and optimized regulation of cogeneration unit heat and power load according to claim 1, characterized in that, Taking the total coal consumption of combined heat and power (CHP) units as the optimization objective, and using dynamic safety assessment coefficients and environmental heating monitoring coefficients as constraints, a CHP load optimization allocation model is constructed based on the CHP coal consumption correlation coefficient and current electricity and heat load demands. The specific method for solving the CHP load optimization allocation model to obtain the optimal load allocation strategy is as follows: Using the current electricity load demand and the current heat load demand as load allocation variables, the objective function is to minimize the predicted total coal consumption of the cogeneration unit. Safety constraints are set based on dynamic safety assessment coefficients, and environmental protection heating constraints are set based on environmental protection heating detection coefficients. A thermal power load optimization allocation model is then established. Adjust the distribution ratio between electrical load and heat load according to the correlation coefficient of thermal power coal consumption, and calculate the predicted total coal consumption, predicted dynamic safety assessment coefficient and predicted environmental protection heating detection coefficient corresponding to different distribution ratios. From the allocation ratios that meet both safety and environmental protection heating constraints, the allocation ratio with the minimum predicted total coal consumption is selected to obtain the optimal load allocation strategy.

7. The method for intelligent monitoring and optimized regulation of cogeneration unit heat and power load according to claim 1, characterized in that, The specific method for obtaining the load allocation deviation by performing a deviation analysis between the optimal load allocation strategy and the current actual electrical and thermal loads of the cogeneration unit is as follows: The difference between the target electrical load in the optimal load allocation strategy and the current actual electrical load of the cogeneration unit is calculated to obtain the electrical load deviation. The difference between the target heat load in the optimal load allocation strategy and the current actual heat load of the cogeneration unit is calculated to obtain the heat load deviation. The absolute values ​​of the electrical load deviation and the thermal load deviation are weighted and calculated to obtain the thermal load distribution deviation value. The corresponding load adjustment direction is determined according to the positive and negative directions of the electrical load deviation and the thermal load deviation.

8. The method for intelligent monitoring and optimized regulation of cogeneration unit heat and power load according to claim 1, characterized in that, The specific method for generating heat and power load control commands based on the heat and power load distribution deviation and sending these commands to the control system of the cogeneration unit is as follows: Compare the thermal load distribution deviation value with the preset command trigger threshold; When the deviation value of the thermoelectric load distribution is greater than the preset command trigger threshold, a thermoelectric load control command including the electric load adjustment amount and the heat load adjustment amount is generated according to the electric load deviation, the heat load deviation and the corresponding load adjustment direction; The cogeneration load control command is sent to the distributed control system of the cogeneration unit, which then controls the corresponding load regulation actuators based on the electrical load regulation and thermal load regulation.

9. A cogeneration unit's heat and power load monitoring and optimization system, characterized in that, include: The data acquisition module is used to collect temperature data, pressure data, flow data, electrical and thermal load data, oxygen data, coal feed data, and ambient temperature data of the cogeneration unit. The collected data is preprocessed to obtain standardized operating data. The coal consumption correlation analysis module is used to analyze coal consumption characteristics based on coal feed data and electric and heat load data in standardized operating data, determine the coupling relationship between coal consumption changes and changes in electric load and heat load, and obtain the thermal power coal consumption correlation coefficient. The safety assessment module is used to perform operational safety boundary analysis based on pressure data, flow data, and ambient temperature data in standardized operating data, and to obtain dynamic safety assessment coefficients. Based on the flow rate data, oxygen content data and ambient temperature data in the standardized operation data, the environmental protection status and heating status are analyzed to obtain the environmental protection heating detection coefficient. The load optimization module is used to construct a combined heat and power load optimization allocation model based on the total coal consumption of the combined heat and power unit as the optimization objective, the dynamic safety assessment coefficient and the environmental protection heating detection coefficient as constraints, the correlation coefficient of coal consumption of heat and power and the current electricity load demand and heat load demand, and solve the optimized load allocation model to obtain the optimal load allocation strategy. The control command generation module is used to perform deviation analysis between the optimal load allocation strategy and the current actual electrical load and actual heat load of the cogeneration unit to obtain the load allocation deviation. Based on the load allocation deviation, the module generates load control commands for the cogeneration unit and sends the load control commands to the control system of the cogeneration unit.

10. A cogeneration unit heat and power load monitoring and optimization regulation system according to claim 9, characterized in that, The data acquisition module is connected to the distributed control system of the cogeneration unit and the meteorological monitoring equipment located outside the cogeneration unit. The data acquisition module obtains temperature data, pressure data, flow data, electrical and heating load data, oxygen data, and coal feed data through the bottom-level measuring points of the distributed control system, and obtains ambient temperature data through meteorological monitoring equipment; The control command generation module is connected to the distributed control system and is used to send a thermoelectric load control command, including electrical load adjustment and thermal load adjustment, to the distributed control system when the thermoelectric load distribution deviation value is greater than the preset command trigger threshold.

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