CN117826907B - Control method of cascade cogeneration device - Google Patents
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Abstract
The invention discloses a control method of a cascade cogeneration device, which belongs to the field of cogeneration and comprises the following steps: firstly, collecting temperature data in real time by deploying a thermistor temperature sensor, and processing the data by utilizing a self-adaptive correction algorithm; determining a target temperature variation trend by analyzing the collected temperature data; executing corresponding operation according to the set target temperature, and adjusting the operation of the cogeneration device; calculating an optimal control point based on the heat supply output percentages of the generator set and the afterburning module; the method comprises the steps of periodically evaluating the running condition of the device, and simultaneously adjusting a target temperature set value, a heat supply output percentage parameter of a generator set and a post-combustion module by checking the abrasion and blockage condition of a component so as to ensure the stability and the performance optimization of the system; the whole method comprehensively utilizes the sensing technology, data analysis and operation adjustment strategy, realizes the intelligent control of the cascade cogeneration device, and improves the efficiency and energy conservation of the system.
Description
Technical Field
The invention relates to the field of cogeneration, in particular to a control method of a cascade cogeneration device.
Background
The cogeneration device is an energy device capable of simultaneously generating electric energy and heat energy, and mainly utilizes fuel gas to generate electricity and waste heat generated in the electricity generation process to supply heat; the cogeneration device is widely applied in the fields of industry, commerce, residence and the like, and can be used in steel plants, chemical plants and the like in industry; the business field includes large business centers, hotels, hospitals, etc. With the development of new technologies and the application of renewable energy sources, cogeneration devices are also evolving continuously.
The existing cogeneration technology mainly adopts a generator set to generate power, and heat generated by the generator set is used for providing heat and electricity in a heat exchange mode, so that the problems of slow heat generation, low heat supply temperature and instability exist, and when the generator set cannot normally operate, heat cannot be safely and stably supplied, and meanwhile, the problems of peak regulation difference and poor economy exist.
Accordingly, the current cogeneration plant control methods require more advanced techniques to address these issues, while an overlapping cogeneration plant control method of the present invention provides a completely new, more efficient solution.
Disclosure of Invention
The invention aims at: a control method of a cascade cogeneration device is provided to solve the problems set forth in the background art.
In order to solve the technical problems, the invention provides the following technical scheme: a control method of a cascade cogeneration apparatus, the method comprising the steps of:
s1, collecting temperature data of an overlapping type cogeneration device in real time, and carrying out self-adaptive correction on the collected temperature data;
s2, analyzing and determining a target temperature change trend based on the collected temperature data;
S3, executing corresponding operation according to the set target temperature to adjust the operation of the cogeneration device;
S4, obtaining an optimal control point based on the heat supply output percentage of the generator set and the heat supply output percentage of the afterburning module;
s5, the running condition of the device is evaluated regularly, and adjustment is carried out in real time.
In step S1, the method of collecting temperature data in the cascade cogeneration device in real time adopts a manner of deploying a thermistor temperature sensor, the thermistor temperature sensor is very sensitive to temperature variation, relatively high precision and resolution can be provided, so that small variation of the temperature inside the device can be captured, the thermistor temperature sensor can monitor the temperature variation in real time, timely data feedback is provided, and the method is very important for timely adjusting the operation parameters of the cogeneration device and realizing the optimal energy-saving manner.
The temperature data is adaptively corrected by adopting the following algorithm:
Is provided with Temperature sensors of thermistors, respectively measured at/>，/>，…，/>，/>=1,2,…，/>The corresponding weights are/>, respectively，/>，…，/>And meet/>=1, Calculate corrected temperature data：
=/>；
Wherein the method comprises the steps ofRepresents the/>Weight of individual thermistor temperature sensor,/>Represents the/>The temperature measured by each thermistor temperature sensor.
The cascade cogeneration device comprises an engine unit, a afterburning module and a heat exchange module; the power generation unit is used for generating power through work and supplying heat to the municipal power grid, and the afterburning module and the heat exchange module are arranged in parallel to realize bidirectional safe heat supply; the afterburner module supplies heat solely when the engine block fails and the engine block supplies heat solely when the afterburner module fails.
Firstly, an engine unit is used as a core component to generate electricity through operation, and electric energy is supplied to a municipal power grid to realize output of electric power; meanwhile, by combining the heat exchange module, waste heat generated by the engine unit is used for heating, so that the dual utilization of energy is realized, and the utilization efficiency of the whole energy is improved. In the system design, the afterburning module and the heat exchange module are arranged in parallel, so that a bidirectional safe heating system is formed. This means that when the engine block fails, the system can be quickly switched to the individual heating state of the afterburning module, guaranteeing the continuity of heating. Also, when the afterburning module fails, the system can be switched to an independent heat supply state of the engine unit, so that the system can provide stable and reliable heat supply service under any condition. The bidirectional safety heat supply design enhances the stability of the system and effectively addresses possible fault conditions of the equipment.
In step S2, the algorithm for determining the target temperature variation trend based on the collected temperature data analysis is as follows:
s201, storing corrected temperature data as a time sequence data set;
S202, performing outlier processing on a temperature data set;
s203, fitting and analyzing the temperature data by using a smooth rate index algorithm to obtain a target temperature change curve;
s204, judging the rising or falling trend of the temperature according to the fitting result;
S205, outputting a change trend of the target temperature, and predicting a temperature range in a future period of time.
In step S202, an outlier processing algorithm is performed on the temperature dataset as follows:
first, for each data point in the acquired time series data set Calculate it relative to the previous data pointTrend change index/>：
=/>；
Then, calculating an expected value alpha and a medium error beta of the trend change index;
α=；
β=；
Wherein the method comprises the steps of Representing the trend change index/>, as found in a time series data setNumber of/>Represents the/>Trend change index,/>=1,2，…，/>-1；
Next, defining a lower threshold delta and an upper threshold epsilon of the abnormal value;
δ=α-γβ；
ε=α+γβ；
where γ is a user-defined threshold multiple, and for each data point, if its trend change index exceeds a defined threshold range, it is marked as an outlier for removal processing.
In step S203, the algorithm for fitting and analyzing the temperature data using the smooth rate index algorithm is as follows:
First, initial temperature values in time series data sets are obtained Let the initial smoothing rate be/>The initial smoothing parameter is ρ, substituted into the following formula:
=ρ*|/>|+（1-ρ）/>；
=（1-/>）*/>+/>*/>；
Wherein the method comprises the steps of Expressed at/>Predicted temperature value of time,/>Expressed at/>Actual temperature value of time,/>Shown at/>Predicted temperature value of time,/>Is the smoothing rate, ρ is a smoothing parameter that controls the smoothing rate, and ρ e0, 1,The representation is the smoothing rate at the last instant;
and finally, updating each target moment to predict the temperature value at the future moment and obtain a target temperature change curve.
In step S205, the trend of the output target temperature is predicted, the temperature range within a period of time in the future is predicted, the SAS data analysis software is used to perform data visualization and statistical analysis processing on the collected target temperature data, the time is used as an independent variable, the temperature is used as a dependent variable, and a trend line of the temperature change is fitted.
In step S3, according to the set target temperature, the following algorithm is adopted to execute corresponding operation to adjust the operation of the cogeneration device to realize the optimal energy saving mode:
set the target temperature range of the target temperature as ~/>And/>＜/>＜/>＜/>When the actual temperature is lower than the minimum target temperature range/>At this point, indicated as being in zone ①, where the engine block and afterburner module are both activated; once started, when the actual temperature is at/>~/>The range is indicated as being in the ②、③ region, where the engine block and the afterburner module are operated simultaneously; when the actual temperature is at/>~/>And is shown in zone ④, at which time the afterburner module is turned off; when the actual temperature is higher than/>At this point, indicated as being in zone ⑤, where the engine block and the afterburner module are simultaneously turned off;
when the required heat demand becomes larger, the actual temperature continuously decreases, and when the actual temperature < When the power generation unit is started; when the actual temperature isAnd simultaneously starting the generator set and the afterburning module.
In step S4, the optimal control point is obtained by using the following algorithm formula based on the heat supply output percentage of the generator set and the heat supply output percentage of the afterburning module:
Wherein the method comprises the steps of Representing the heat supply output percentage of the afterburning module,/>Representing the heat supply output percentage of the generator set,/>Representing rated heat supply capacity of generator set,/>Indicating the rated heat supply capacity of the afterburner module,Representing the heat demand,/>Representing the water supply flow rate,/>Representing the target temperature,/>Representing the current actual temperature,/>Is a constant;
establishing a two-dimensional coordinate system, wherein the abscissa is Ordinate is/>The horizontal axis is X axis, the vertical axis is Y axis, the right direction and the upward direction are positive directions, and the method is that/>、Get/>The square area surrounded by the X axis and the Y axis is the total heat supply quantity of the generator set and the afterburning module;
When in straight line =-/>+/>When the square is cut, the area on the left side of the straight line in the square represents that the heat supply quantity is smaller than the minimum heat demand quantity, the area on the right side of the straight line in the square represents that the heat supply quantity is larger than the minimum heat demand quantity, the area outside the square represents that the heat demand quantity exceeds the rated heat supply quantity, at the moment, the generator set and the afterburning module run at full load, and the position of the intersection point of the straight line and the side of the square is the optimal control point according to the method of solving the optimal value of the convex function.
In step S5, the device operation conditions are periodically evaluated, and the operation parameters are adjusted, including evaluating component wear and blockage conditions of the cogeneration device, and simultaneously adjusting the target temperature set value, the heat supply output percentage of the generator set, and the heat supply output percentage parameter of the afterburner module.
Compared with the prior art, the invention has the following beneficial effects:
1. in the design of the cogeneration device, the bidirectional heat supply characteristics of the generator set and the afterburning module are considered, and the safety and stability of the operation of the equipment are ensured. Even if one module fails, the other module can supply heat independently, the reliability of the device is enhanced, the double heat sources are designed in parallel, the safety and the stability are high, and the device can supply heat at a high temperature for 24 hours without interruption and simultaneously supply electric energy.
2. The peak regulation is performed through the corresponding control method, so that the energy consumption is saved, the energy waste is reduced, the utilization efficiency of energy is improved, the flexibility of products is improved, the requirements of customers are met, and the economical efficiency is improved.
3. And obtaining the heat supply output percentage of the generator set and the heat supply output percentage of the afterburning module based on data analysis, extracting an optimal control point, and realizing reasonable utilization of resources. The method based on data analysis can continuously optimize the running state of the equipment, and further improve the efficiency.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a schematic flow chart of the control method of the cascade cogeneration device according to the invention;
fig. 2 is a schematic diagram of a target temperature algorithm of a control method of an cascade cogeneration apparatus according to the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Fig. 1-2, the present invention provides the technical scheme:
a control method of a cascade cogeneration apparatus, the method comprising the steps of:
S1, collecting temperature data of an overlapping type cogeneration device in real time, and carrying out self-adaptive correction on the collected temperature data;
s2, analyzing and determining a target temperature change trend based on the collected temperature data;
S3, executing corresponding operation according to the set target temperature to adjust the operation of the cogeneration device;
S4, obtaining an optimal control point based on the heat supply output percentage of the generator set and the heat supply output percentage of the afterburning module;
s5, the running condition of the device is evaluated regularly, and adjustment is carried out in real time.
In step S1, the temperature data in the cascade cogeneration device is collected in real time by adopting a manner of deploying a thermistor temperature sensor, the thermistor temperature sensor is very sensitive to temperature variation, relatively high precision and resolution can be provided, so that small variation of the temperature inside the device can be captured, the thermistor temperature sensor can monitor the temperature variation in real time, and timely data feedback is provided, which is very important for timely adjusting the operation parameters of the cogeneration device and realizing the optimal energy-saving manner.
The following algorithm is adopted for self-adaptive correction of the temperature data:
Is provided with Temperature sensors of thermistors, respectively measured at/>，/>，…，/>，/>=1,2,…，/>The corresponding weights are/>, respectively，/>，…，/>And meet/>=1, Calculated as corrected temperature data/>：
=/>；
Wherein the method comprises the steps ofRepresents the/>Weight of individual thermistor temperature sensor,/>Represents the/>The temperature measured by each thermistor temperature sensor.
The cascade cogeneration device comprises an engine unit, a afterburning module and a heat exchange module; the power generation unit is used for generating power through work and supplying heat to the municipal power grid, and the afterburning module and the heat exchange module are arranged in parallel to realize bidirectional safe heat supply; the afterburner module supplies heat solely when the engine block fails and the engine block supplies heat solely when the afterburner module fails.
Firstly, an engine unit is used as a core component to generate electricity through operation, and electric energy is supplied to a municipal power grid to realize output of electric power; meanwhile, by combining the heat exchange module, waste heat generated by the engine unit is used for heating, so that the dual utilization of energy is realized, and the utilization efficiency of the whole energy is improved. In the system design, the afterburning module and the heat exchange module are arranged in parallel, so that a bidirectional safe heating system is formed. This means that when the engine block fails, the system can be quickly switched to the individual heating state of the afterburning module, guaranteeing the continuity of heating. Also, when the afterburning module fails, the system can be switched to an independent heat supply state of the engine unit, so that the system can provide stable and reliable heat supply service under any condition. The bidirectional safety heat supply design enhances the stability of the system and effectively addresses possible fault conditions of the equipment.
In step S2, the target temperature change trend algorithm is determined based on the collected temperature data analysis as follows:
s201, storing corrected temperature data as a time sequence data set;
S202, performing outlier processing on a temperature data set;
s203, fitting and analyzing the temperature data by using a smooth rate index algorithm to obtain a target temperature change curve;
s204, judging the rising or falling trend of the temperature according to the fitting result;
S205, outputting a change trend of the target temperature, and predicting a temperature range in a future period of time.
In step S202, the outlier processing algorithm for the temperature dataset is as follows:
first, for each data point in the acquired time series data set Calculate it relative to the previous data pointTrend change index/>：
=/>；
Then, calculating an expected value alpha and a medium error beta of the trend change index;
α=；
β=；
Wherein the method comprises the steps of Representing the trend change index/>, as found in a time series data setNumber of/>Represents the/>Trend change index,/>=1,2，…，/>-1；
Next, defining a lower threshold delta and an upper threshold epsilon of the abnormal value;
δ=α-γβ；
ε=α+γβ；
where γ is a user-defined threshold multiple, and for each data point, if its trend change index exceeds a defined threshold range, it is marked as an outlier for removal processing.
In step S203, an algorithm for fitting and analyzing temperature data using the smoothing rate index algorithm is as follows:
First, initial temperature values in time series data sets are obtained Let the initial smoothing rate be/>The initial smoothing parameter is ρ, substituted into the following formula:
=ρ*|/>|+（1-ρ）/>；
=（1-/>）*/>+/>*/>；
Wherein the method comprises the steps of Expressed at/>Predicted temperature value of time,/>Expressed at/>Actual temperature value of time,/>Shown at/>Predicted temperature value of time,/>Is the smoothing rate, ρ is a smoothing parameter that controls the smoothing rate, and ρ e0, 1,The representation is the smoothing rate at the last instant;
and finally, updating each target moment to predict the temperature value at the future moment and obtain a target temperature change curve.
In step S205, a trend of the target temperature is output, the temperature range in a future period is predicted, the collected target temperature data is subjected to data visualization and statistical analysis by using SAS data analysis software, the time is taken as an independent variable, the temperature is taken as a dependent variable, and a trend line of the temperature change is fitted.
In step S3, according to the set target temperature, a corresponding operation is performed to adjust the operation of the cogeneration device to achieve the optimal energy saving mode, and the following algorithm is adopted:
set the target temperature range of the target temperature as ~/>And/>＜/>＜/>＜/>When the actual temperature is lower than the minimum target temperature range/>At this point, indicated as being in zone ①, where the engine block and afterburner module are both activated; once started, when the actual temperature is at/>~/>The range is indicated as being in the ②、③ region, where the engine block and the afterburner module are operated simultaneously; when the actual temperature is at/>~/>And is shown in zone ④, at which time the afterburner module is turned off; when the actual temperature is higher than/>At this point, indicated as being in zone ⑤, where the engine block and the afterburner module are simultaneously turned off;
when the required heat demand becomes larger, the actual temperature continuously decreases, and when the actual temperature < When the power generation unit is started; when the actual temperature isAnd simultaneously starting the generator set and the afterburning module.
In step S4, based on the heat supply output percentage of the generator set and the heat supply output percentage of the afterburning module, the best control point is obtained by adopting the following algorithm formula:
Wherein the method comprises the steps of Representing the heat supply output percentage of the afterburning module,/>Representing the heat supply output percentage of the generator set,/>Representing rated heat supply capacity of generator set,/>Indicating the rated heat supply capacity of the afterburner module,Representing the heat demand,/>Representing the water supply flow rate,/>Representing the target temperature,/>Representing the current actual temperature,/>Is a constant;
establishing a two-dimensional coordinate system, wherein the abscissa is Ordinate is/>The horizontal axis is X axis, the vertical axis is Y axis, the right direction and the upward direction are positive directions, and the method is that/>、Get/>The square area surrounded by the X axis and the Y axis is the total heat supply quantity of the generator set and the afterburning module;
When in straight line =-/>+/>When the square is cut, the area on the left side of the straight line in the square represents that the heat supply quantity is smaller than the minimum heat demand quantity, the area on the right side of the straight line in the square represents that the heat supply quantity is larger than the minimum heat demand quantity, the area outside the square represents that the heat demand quantity exceeds the rated heat supply quantity, at the moment, the generator set and the afterburning module run at full load, and the position of the intersection point of the straight line and the side of the square is the optimal control point according to the method of solving the optimal value of the convex function.
In step S5, the device operation conditions are periodically evaluated, and the operation parameters are adjusted, including evaluating component wear and blockage conditions of the cogeneration device, and simultaneously adjusting the target temperature set point, the heat supply output percentage of the generator set, and the heat supply output percentage parameters of the afterburner module.
Embodiment one:
Assuming 3 thermistor sensors, the corresponding temperatures are respectively =25℃，/>=30℃，/>=28 ℃, Weights are/>, respectively=0.2，/>=0.3，/>=0.3, Substituting to obtain device real-time temperature data/>：
=/>=27.4℃；
Obtaining temperature datasets { 25,26,27,26,30,28,25,24,26,100,25} of different time compositions;
Calculating trend change index of each data point relative to the previous data point ={0.04,0.038,−0.037,0.154,−0.067,−0.107,−0.04,0.083,2.846,−0.75}；
Then, calculating an expected value alpha and a medium error beta of the trend change index;
α=≈0.133；
β=≈0.932；
next, defining a lower threshold delta and an upper threshold epsilon of the abnormal value;
δ=α-γβ≈−1.731；
ε=α+γβ≈2.997；
from the threshold range, the trend change index 2.846 for the 10 th data point 100 was found to exceed the upper threshold, and was therefore marked as an outlier for removal processing.
Obtaining an initial temperature value as=25, Initial smoothing rate/>=0.2 And the smoothing parameter ρ=0.5, substituted into the following formula:
=（1-/>）*/>+/>*/>；
=ρ*|/>|+（1-ρ）/>；
For the following =2，
=0.5*|/>|+（1-0.5）*0.2≈0.35；
=（1-0.35）*26+0.35*27≈26.6；
And updating each target moment to predict the temperature value at the future moment and obtain a target temperature change curve.
If a customer needs to obtain hot water with the temperature of 56-65 ℃, setting T1 to 53 ℃, setting T2 to 56 ℃, setting T3 to 65 ℃ and setting T4 to 67 ℃, when the actual temperature is less than 53 ℃, simultaneously starting the generator set and the afterburning module, when the actual temperature is lower than 65 ℃ and higher than 53 ℃, keeping the state of all opening, when the actual temperature is higher than 65 ℃ and lower than 67 ℃, closing the afterburning module, when the actual temperature is higher than 67 ℃, closing the engine module, if the heat demand is continuously present, the temperature tends to drop, when the temperature drops to less than 56 ℃, starting the generator set, if the heat production capacity of the generator set can meet the current demand, namely, the actual temperature is not lower than 53 ℃, only starting the generator set, if the overheat demand increases, when the actual temperature drops to less than 53 ℃, the afterburning module is also started to make up for the shortage of the heat supply, and the generator set and the afterburning module are simultaneously operated, and the generator set is cycled backwards in sequence, so as to meet the change of the heat demand, and the device is more stable and reliable in operation.
If rated heat supply quantity of generator set45KW, rated gas consumption/>Rated heat supply amount/>, of the afterburning module is 7 m/hRated gas consumption/>, 120kW12 M/h/(=1.163；
When the target water temperature is 60 ℃, the flow is 10 m/h and the actual temperature is 20 ℃, the heat demand is at the moment= (60-20) ×10×1.163=465.2 KW, the total heat supply amount of the generator set and the afterburning module is 165kW, and according to the above model algorithm,=100%，/>100%, Namely the output of the generator set and the afterburning module is 100%, and the full load operation is performed at this time because the heat supply quantity is far smaller than the demand quantity;
When the target water temperature is 60 ℃, the flow is 10 m/h and the actual temperature is 30 ℃, at the moment = (60-30) ×10X1.163=348 kW, the total heat supply of the generator set and the afterburning module is 165kW, according to the above model algorithm,/>=100%，/>100%, Namely the output of the generator set and the afterburning module is 100%, and the full load operation is performed at this time because the heat supply quantity is far smaller than the demand quantity;
When the target water temperature is 60 ℃, the flow is 10 m/h and the actual temperature is 40 ℃, at the moment = (60-40) ×10X1.163=232 kW, the total heat supply of the generator set and the afterburning module is 165kW, according to the above model algorithm,/>=100%，/>The power generation unit and the afterburning module output 100%, because the heat supply quantity approaches the demand quantity but does not reach the demand quantity yet, the full load operation is performed at the moment;
when the target water temperature is 60 ℃, the flow is 10 m/h and the actual temperature is 48 ℃, the heat demand is at the moment = (60-48) ×10×1.163= 139.56KW, the total heat supply of the generator set and the afterburning module is 165kW, according to the above model algorithm,=100%，/>=78.8% Or/>=43.47%，/>The value of 100% is the optimal value, the cost is the most saved, the generator set outputs 100%, and the afterburning module outputs 78.8% to operate;
When the target water temperature is 60 ℃, the flow is 10 m/h and the actual temperature is 50 ℃, the heat demand is at the moment = (60-50) ×10×1.163=116.3 KW, the total heat supply amount of the generator set and the afterburning module is 165kW, and according to the above model algorithm,=100%，/>=59.42% Or/>=0%，/>The value of the fuel is 96.92% which is the optimal value, the cost is the most saved, the generator set outputs 100%, and the afterburning module outputs 59.42% to run; /(I)
When the target water temperature is 60 ℃, the flow is 10 m/h and the actual temperature is 58 ℃, the heat demand is at the moment= (60-55) ×10×1.163=23.26 KW, the total heat supply amount of the generator set and the afterburning module is 165kW, and according to the above model algorithm,=51.69%，/>=0% Or/>=0%，/>=19.38% Is the optimal value, the cost is most saved, the generator set outputs 51.69%, and the afterburning module outputs 0% of operation;
When the target water temperature is 60 ℃, the flow is 10 m/h and the actual temperature is 62 ℃, the heat demand is at the moment 10 X 1.163 = -23.26kW, the total heat supply of the generator set and the afterburning module is 165kW, according to the above model algorithm,=0%，/>=0%, And the generator set and the afterburning module are closed to stop outputting.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. A control method of a cascade cogeneration device is characterized by comprising the following steps of: the method comprises the following steps:
S1, collecting temperature data of an overlapping type cogeneration device in real time, and carrying out self-adaptive correction on the collected temperature data;
s2, analyzing and determining a target temperature change trend based on the collected temperature data;
S3, executing corresponding operation according to the set target temperature to adjust the operation of the cogeneration device;
S4, obtaining an optimal control point based on the heat supply output percentage of the generator set and the heat supply output percentage of the afterburning module;
S5, periodically evaluating the running condition of the device and adjusting the running parameters;
in step S4, the optimal control point is obtained by using the following algorithm formula based on the heat supply output percentage of the generator set and the heat supply output percentage of the afterburning module:
Wherein the method comprises the steps of Representing the heat supply output percentage of the afterburning module,/>Representing the heat supply output percentage of the generator set,/>Representing rated heat supply capacity of generator set,/>Indicating the rated heat supply capacity of the afterburning module,/>Representing the heat demand,/>Representing the water supply flow rate,/>Representing the target temperature,/>Indicating the current actual temperature of the device,Is a constant;
establishing a two-dimensional coordinate system, wherein the abscissa is Ordinate is/>The horizontal axis is X axis, the vertical axis is Y axis, the right direction and the upward direction are positive directions, and the method is that/>、/>Get/>The square area surrounded by the X axis and the Y axis is the total heat supply quantity of the generator set and the afterburning module;
When in straight line =-/>+/>When the square is cut, the area on the left side of the straight line in the square represents that the heat supply quantity is smaller than the minimum heat demand quantity, the area on the right side of the straight line in the square represents that the heat supply quantity is larger than the minimum heat demand quantity, the area outside the square represents that the heat demand quantity exceeds the rated heat supply quantity, at the moment, the generator set and the afterburning module run at full load, and the position of the intersection point of the straight line and the side of the square is the optimal control point according to the method of solving the optimal value of the convex function.
2. The control method of a cascade cogeneration apparatus according to claim 1, wherein: in step S1, the method for collecting temperature data in the cascade cogeneration device in real time adopts a manner of deploying a thermistor temperature sensor, and the adaptive correction of the temperature data adopts the following algorithm:
Is provided with Temperature sensors of thermistors, respectively measured at/>，/>，…，/>，/>=1,2,…，/>The corresponding weights are/>, respectively，/>，…，/>And meet/>=1, Calculate corrected temperature data：
=/>；
Wherein the method comprises the steps ofRepresents the/>Weight of individual thermistor temperature sensor,/>Represents the/>The temperature measured by each thermistor temperature sensor.
3. The control method of a cascade cogeneration apparatus according to claim 2, wherein: the cascade cogeneration device comprises an engine unit, a afterburning module and a heat exchange module; the power generation unit is used for generating power through work and supplying heat to the municipal power grid, and the afterburning module and the heat exchange module are arranged in parallel to realize bidirectional safe heat supply; the afterburner module supplies heat solely when the engine block fails and the engine block supplies heat solely when the afterburner module fails.
4. The control method of a cascade cogeneration apparatus according to claim 1, wherein: in step S2, the algorithm for determining the trend of the target temperature change based on the collected temperature data analysis includes the following steps:
s201, storing the self-adaptive corrected temperature data as a time sequence data set;
S202, performing outlier processing on a temperature data set;
s203, fitting and analyzing the temperature data by using a smooth rate index algorithm to obtain a target temperature change curve;
s204, judging the rising or falling trend of the temperature according to the fitting result;
S205, outputting a change trend of the target temperature, and predicting a temperature range in a future period of time.
5. The control method of a cascade cogeneration apparatus according to claim 4, wherein: in step S202, the algorithm for performing outlier processing on the temperature dataset is as follows:
first, for each data point in the acquired time series data set Calculate it relative to the previous data point/>Trend change index/>：
=/>；
Then, a trend change index is calculatedAnd a median error β;
α=；
β=；
Wherein the method comprises the steps of Representing the trend change index/>, as found in a time series data setNumber of/>Represents the/>The number of trend-change indices is set,=1,2，…，/>-1；
Next, defining a lower threshold delta and an upper threshold epsilon of the abnormal value;
δ=α-γβ；
ε=α+γβ；
where γ is a user-defined threshold multiple, and for each data point, if its trend change index exceeds a defined threshold range, it is marked as an outlier for removal processing.
6. The control method of a cascade cogeneration apparatus according to claim 1, wherein: in step S203, the algorithm for fitting and analyzing the temperature data using the smooth rate index algorithm is as follows:
First, initial temperature values in time series data sets are obtained Let the initial smoothing rate be/>The initial smoothing parameter is ρ, substituted into the following formula:
=ρ*|/>|+（1-ρ）/>；
=（1-/>）*/>+/>*/>；
Wherein the method comprises the steps of Expressed at/>Predicted temperature value of time,/>Expressed at/>Actual temperature value of time,/>Shown inPredicted temperature value of time,/>Is the smoothing rate, ρ is a smoothing parameter that controls the smoothing rate, and ρ ε [0,1],/>The representation is the smoothing rate at the last instant;
and finally, updating each target moment to predict the temperature value at the future moment and obtain a target temperature change curve.
7. The control method of a cascade cogeneration apparatus according to claim 1, wherein: in step S205, the trend of the output target temperature is predicted, the temperature range within a period of time in the future is predicted, the SAS data analysis software is used to perform data visualization and statistical analysis processing on the collected target temperature data, the time is used as an independent variable, the temperature is used as a dependent variable, and a trend line of the temperature change is fitted.
8. The control method of a cascade cogeneration apparatus according to claim 1, wherein: in step S3, according to the set target temperature, the following algorithm is adopted to execute corresponding operation to adjust the operation of the cogeneration device to realize the optimal energy saving mode:
set the target temperature range of the target temperature as ~/>And/>＜/>＜/>＜/>When the actual temperature is lower than the minimum target temperature range/>At this point, indicated as being in zone ①, where the engine block and afterburner module are both activated; once started, when the actual temperature is at/>~/>The range is indicated as being in the ②、③ region, where the engine block and the afterburner module are operated simultaneously; when the actual temperature is at/>~/>And is shown in zone ④, at which time the afterburner module is turned off; when the actual temperature is higher than/>At this point, indicated as being in zone ⑤, where the engine block and the afterburner module are simultaneously turned off;
when the required heat demand becomes larger, the actual temperature continuously decreases, and when the actual temperature < When the power generation unit is started; when the actual temperature isAnd simultaneously starting the generator set and the afterburning module.
9. The control method of a cascade cogeneration apparatus according to claim 1, wherein: in step S5, the device operation conditions are periodically evaluated, and the operation parameters are adjusted, including periodically evaluating the wear condition and the blockage condition of the components of the cogeneration device, and adjusting the target temperature set value, the heat supply output percentage of the generator set, and the heat supply output percentage parameter of the afterburner module.
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