CN115264580A - Fuzzy set-based multi-heat-source heat supply amount calculation control method in uncertain heating period - Google Patents
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Abstract
The invention relates to a fuzzy set-based multi-heat-source heat supply amount calculation control method in an uncertain heating period. Firstly, calculating a heat load index according to the heat user characteristic weighting, and simultaneously drawing and determining a heat load duration chart by utilizing a piecewise linear formula method; then, quantifying the uncertain heating duration time based on a fuzzy set theory; thirdly, giving a thermalization coefficient, and obtaining uncertain heat supply quantity born by each heat source under the fuzzy condition through integration of the heat load to the duration time when the alpha-cut level is 0 and 1 respectively; based on the obtained fuzzy heat supply amount, calculating the interval heat supply amount of each heat source in the multi-heat-source central heat supply system under different alpha-cut intercept levels, and realizing the effective quantification of the uncertain heat supply amount of the heat source; finally, a decision maker in the production field can select the interval result under the corresponding possibility according to the actual preference, adjust the actual heat supply amount of the heat source in the interval and control the production heat of the production field equipment.
Description
Technical Field
The invention relates to the field of quantitative characterization and analysis of heating heat supply uncertainty, in particular to a multi-heat-source heat supply calculation control method based on a fuzzy set in an uncertain heating period.
Background
For residents in high and medium latitude areas, heat supply is performed, and the basic social public service directly influences the life quality and the social service satisfaction during the heating period in winter. The energy structure mainly based on coal in China enables a large amount of greenhouse gases and atmospheric pollutants to be discharged during heating by using fossil fuel every year. Therefore, the heat demand of the heating users in communities, schools, hospitals and businesses is reasonably and effectively quantified and predicted and used for actual production control, so that the energy waste on the supply side can be reduced, the greenhouse gas and the atmospheric pollutants are reduced, the urgent desire of energy utilization cost reduction and efficiency improvement can be quickly achieved, and the technical problem to be solved at present is urgently solved. In recent years, related researches have been conducted to quantify and predict the amount of heat supplied by a heat source or the amount of heat required by a user from the perspective of physical mechanism simulation and data-driven statistical paradigm, however, these methods requiring a large amount of data support may cause technical application obstacles to partial heating areas, especially heating areas lacking historical meteorological and architectural data. It should be noted that the objective existence of uncertainty will seriously affect the accurate prediction of the heat supply amount assumed by each heat source, such as the determination of the heating duration, and if the uncertainty is ignored, the uncertainty will result in mismatching of the heat supply and demand at the heating demand side and the heat supply side, and even cause the risk of wrong heat supply decision. Therefore, the method is important for accurately representing uncertainty around the heat demand of heating users or the heat supply amount of a heat source and bringing the uncertainty into an analysis frame to realize effective quantification and control of production and heat supply amount, and is also an important technical research and development direction in the future heat supply system research field.
Disclosure of Invention
Aiming at the defects of the existing uncertain heat supply quantitative characterization technology borne by the heat source, the invention provides a multi-heat-source heat supply calculation control method based on a fuzzy set in an uncertain heating period, and aims to solve the problem that the uncertain heat source heat supply or the heat required by a user cannot be effectively characterized and quantified.
The technical scheme adopted by the invention for realizing the purpose is as follows:
the multi-heat-source heat supply amount calculation control method under the uncertain heating period based on the fuzzy theory comprises the following steps:
step 1: weighting and calculating the heating design heat load of the area in the current jurisdiction according to different heat user characteristics;
step 2: designing a heat load based on regional heating, and drawing a piecewise linear heating heat load-duration standard curve;
and step 3: based on the evaluation results of experts and operating personnel of a heating system, calculating four peak heat supply values when the corresponding membership degree alpha-cut levels of the trapezoidal fuzzy number are 1 and 0 respectively by utilizing the trapezoidal fuzzy number of a fuzzy set theory, and performing uncertain quantitative characterization on the heating duration time to construct a fuzzy membership function of the fuzzy heating duration time;
and 4, step 4: calculating the vertex values of fuzzy heat supply load of each heat source under a given thermalization coefficient by using the vertex values of the fuzzy heating duration time and a drawn segmental linear heating heat load-duration time standard curve and by using the integral and fuzzy number calculation rule of the heat load on the heating duration time as the fuzzy heat supply load born by each heat source;
and 5: based on the obtained heat demand of the fuzzy heat user, calculating the heating period main and auxiliary heat source district heating load corresponding to different membership degree alpha-cut intercept levels under the given thermalization coefficient
And
step 6: according to the heat supply quantity between the main and auxiliary heat source regions
And
controlling the production heat of the production field.
The area heating design heat load Q 'of the current district'nThe calculation is as follows:
wherein, Q'nDesigning heat load for heating, wherein MW and I are different sub-areas in a heating area, the number of the sub-areas is I in the district, J is different building energy-saving types, J is 1 for an energy-saving building, J is 2 for a non-energy-saving building, J is 2, po is the population number of the heating area, ao is the per-living area of the heating area, rb is the proportion of the area of the different energy-saving buildings to the area of all residential buildings in the district, and Qw is a heating design heat index of the different energy-saving buildings, and the heating design heat index is set according to actual conditions when the heating system is used.
The heating heat load-duration standard curve is drawn by a piecewise linear function between variables, and the formula is as follows:
wherein, the related parameters are as follows:
in the above formulas, QnHeating thermal load, MW; t is tnCalculating the indoor temperature in the heating period at DEG C; generally taking the temperature to be 18 ℃; t'wThe temperature is calculated outdoors in the heating period at the temperature of DEG C, different cities are determined according to climatic weather conditions, and the average daily temperature which is not guaranteed for five days in average over the years is generally adopted as a calculation standard; t is tp·jDetermining the average outdoor temperature at the heating period, namely the temperature, of different cities according to historical temperature data of the heating period; n is continuation days, namely the outdoor air temperature is equal to or lower than t 'in the heating period'wAverage days, of the year; n is a radical ofzhDetermining the total days and days in the heating period, wherein different cities are determined according to historical temperature data in the heating period; b is RnIndex value of (a), p.u.; beta is a0Temperature correction factor, p.u.; μ is the correction factor over the course of days (hours), p.u.; rnIs caused by nothingThe next consecutive days, p.u.
Fuzzy delay days of heating
The membership function μ (N) of (a) is as follows:
wherein, the four vertex values of the trapezoidal fuzzy number are respectivelyN zh，
And
N zhand
the heat value is supplied to the corresponding boundary when the alpha-cut level is 0 respectively,
and
and supplying heat values to corresponding boundaries when the alpha-cut levels are respectively 1.
The calculation formula of the fuzzy heat supply load born by each heat source is as follows:
heat supply Q in heating period of main heat sourcena：
Total heat supply Q in peak-shaving heat source heating periodnb：
Wherein γ is a thermalization systemThe number represents the ratio of the maximum heating load of the main heat source to the total heating load designed by the system, p.u.; n is a radical of hydrogenγIs the total continuous days,
Qnaand QnbThe main heat source and the peak-shaving heat source respectively bear the heat supply when the thermalization coefficient is gamma, and the GJ is the heat supply.
Under the given thermalization coefficient (gamma), the section heat supply quantity borne by each heat source under different alpha-cut level truncations is calculated as follows:
wherein, the trapezoidal fuzzy heat supply four peak values of the main heat source
AndQ na，
and
corresponding to the endpoint values between the time zones of alpha =0 and alpha =1 respectively, thereby forming the main heat source bearing the heat supply of the zone
Four peak values of trapezoidal fuzzy heat supply load of peak-shaving heat source
AndQ nb，
and
respectively corresponding to end point values between time zones of alpha =0 and alpha =1, thereby forming a section peak-shaving heat source bearing heat supply quantity
The invention has the following beneficial effects and advantages:
1. compared with the traditional prediction method, the method for quantitatively characterizing and controlling the heat supply quantity of the multi-heat-source centralized heating system in the heating period under the fuzzy uncertainty can be effectively coped with. By means of quantification of alpha-cut intercept, the method can generate heat source bearing heat supply interval values under variable thermalization coefficients of heating periods with different possibility levels.
2. The method solves the problem that the heat source heating load (the heat required by the user) facing the uncertain duration time cannot be effectively quantified, and meanwhile, based on the fuzzy set theory, the calculated heat source heating load has the characteristics that the higher the system possibility (alpha-cut value), the narrower the prediction interval, the lower the system possibility (alpha-cut value) and the wider the prediction interval.
3. A decision maker on the production site by using the method can select the interval result under the corresponding possibility according to the actual preference and adjust the actual heat supply amount of the heat source in the interval.
4. In addition, the method can also provide potential compromise analysis between system possibility and selectable heat supply range for a heat supply system manager, and provides decision support and reference for further energy conservation, consumption reduction and energy consumption optimization.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
FIG. 2 is a trapezoidal fuzzy number representation.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
In order to make the aforementioned objects, features and advantages of the present invention more comprehensible, embodiments accompanying figures are described in detail below. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, but rather should be construed as modified in the spirit and scope of the present invention as set forth in the appended claims.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.
The embodiment is as follows:
a central heating system with multiple heat sources for a city in northern China comprises main and auxiliary heat sources, provides heating service for residents in a community, and has a heating service area of 5.97 multiplied by 106m2. The heating period of the previous year lasts for about 5 months, the heat supply area ratio of the non-energy-saving building to the energy-saving building is 13, and the correspondingly designed heat supply load indexes are respectively 64 and 45W/m2. The average outdoor temperature in the heating period and the calculated outdoor temperature in the heating period are respectively-5.7 ℃, 19 ℃ below zero and 18 ℃. Expert and operator advised fuzzy heating duration of
The following describes the implementation steps of the present invention in detail with reference to specific procedures.
Fig. 1 shows a flow chart of the method of the present invention.
The method mainly adopts weighting calculation, piecewise linear function and trapezoidal fuzzy number (formed by membership function) and corresponding algorithm to calculate, and comprises the following steps:
the method comprises the following steps: and (4) weighting and calculating regional heat load indexes according to different heat user characteristics (building types, energy conservation and the like) to be used as heating design heat loads.
Step two: and in order to quantify the heat supply born by different heat sources of the heat supply system, drawing a piecewise linear heating heat load-duration standard curve based on the regional heating design heat load calculated in the step one.
Step three: according to local climate conditions and current-year meteorological condition characteristics of the past year, based on the evaluation results of experts, stakeholders and multi-year heat supply system operators, trapezoidal fuzzy numbers (shown in figure 2) in the fuzzy set theory are utilized, 4 vertex values when alpha-cut levels corresponding to the trapezoidal fuzzy numbers are 1 and 0 respectively are calculated, uncertain quantitative representation is conducted on heating duration time, and fuzzy heating duration time is constructed.
Step four: and (2) calculating the vertex values of the fuzzy heating duration time calculated in the step three and the standard curve of the segmental linear heating load-duration time drawn in the step two by utilizing the heating duration time of the heat load to obtain the standard heat supply load borne by each heat source, and then calculating the vertex values of the fuzzy heat supply load of each heat source under the given thermalization coefficient by utilizing a fuzzy number calculation rule (or by utilizing a multiplication rule of fuzzy numbers) to form the fuzzy heat supply load borne by each heat source.
Step five: based on the obtained fuzzy heat user heat demand, calculating the heating load between the main heat source and the auxiliary heat source in the heating period corresponding to different alpha-cut (membership degree) interception levels under the given thermalization coefficient gamma
And
step six: according to the heat supply quantity between the main and auxiliary heat source regions
And
controlling the production heat of the production field.
In the first step, according to different energy-saving types, building areas and corresponding heat load indexes of the residence, the total heat load of the community is calculated by weighted summation according to the following formula (1):
wherein, Q'nDesigning heat load for heating, wherein MW and I are different sub-areas in a heating area, I are total sub-areas in a district, J is different building energy-saving types, J is 1 to represent energy-saving buildings, J is 2 to represent non-energy-saving buildings, J is 2, po is the population number of the heating area, ao is the living area of people in the heating area, and Rb is the proportion of the area of the building with different energy-saving types to the area of all residential buildings (for example, rb is the area of the building with different energy-saving types)1Rb represents the proportion of the energy-saving building occupying the whole building area in the district2Representing the proportion of the non-energy-saving buildings occupying the whole building area in the jurisdiction), and Qw is the heating design heat index of different energy-saving buildings, and is determined according to the actual situation when in use.
And step two, drawing an outdoor temperature-heating heat load-duration standard curve by using the duration time, the outdoor temperature and the piecewise linear function between the duration time and the corresponding heat load. The piecewise linear formula is as follows:
(1) Duration as a function of outdoor temperature:
(2) Duration as a function of the corresponding thermal load:
(3) The calculation process involves the following relevant parameters:
of the formulae above, Q'nDesigning heat load, MW, for heating; qnAt a certain outdoor temperature twLower heating heat load, MW; t is twA certain outdoor temperature, DEG C; t is tnIndoor temperature is calculated in the heating period; generally taking the temperature to be 18 ℃; t'wThe temperature is calculated outdoors in the heating period at the temperature of DEG C, different cities are determined according to climatic weather conditions, and the average daily temperature which is not guaranteed for five days in average over the years is generally adopted as a calculation standard; t is tp·jThe average outdoor temperature and the temperature in the heating period are determined by different cities according to historical temperature data in the heating period; n is continuation days, namely the outdoor air temperature is equal to or lower than t 'in the heating period'wAverage days, of the year; n is a radical ofzhDetermining the total days and days in the heating period and different cities according to historical temperature data in the heating period; b is RnP.u. index value of (d); beta is a beta0Temperature correction factor, p.u.; μ is the correction factor for the duration of the day (hours), p.u.: rnDimensionless number of days on, p.u.; ( Note: the design and calculation days of heating are determined according to the total days that the average daily temperature is stably lower than or equal to the critical outdoor temperature of heating. For general civil buildings and industrial buildings, the heating outdoor critical temperature is preferably 5 ℃. )
According to the piecewise linear function in the formula, an outdoor temperature-heating load-duration time graph in the heating period can be drawn.
In the third step, through the experience knowledge of experts in the field of heat supply research and operators of a multi-year heat supply system, the duration time (days) of four vertexes under the most probable (alpha = 1) and least probable (alpha = 0) situations is evaluated, and then the average value is obtained as four vertex values of the trapezoidal fuzzy numberN zh，
And
meanwhile, a fuzzy membership function (shown as the following) is constructed according to the positions of all points on the coordinate axis position, so as to form trapezoidal fuzzy delay heat supply days,
wherein, four vertex values of trapezoidal fuzzy durationN zhAnd
and
corresponding to the end-point duration values between time zones α =0 and α =1 respectively,N zhand
the heat value is supplied to the corresponding boundary when the alpha-cut level is 0 respectively,
and
and supplying heat values to corresponding boundaries when the alpha-cut levels are respectively 1.
In the fourth step, the standard heat supply amount born by each heat source is obtained by integrating the heating duration time through the heat load by utilizing the calculation results of the first two steps, and the calculation formula is as follows:
heat supply Q in heating period of main heat sourcena：
Integration can give:
total heat supply Q in peak-regulating heat source heating periodnb：
Integration can give:
wherein gamma is a thermalization coefficient, which represents the ratio of the maximum heating load of the main heat source to the total heating load of the system design, p.u.; n is a radical of hydrogenγIs the total duration days,
Qnaand QnbThe heat supply is borne by a main heat source and the heat supply is borne by a peak-shaving heat source in the heating period when the thermalization coefficient is gamma.
Then, the fuzzy number calculation rule is used to calculate the vertex value of fuzzy heat supply quantity of each heat source under the given thermalization coefficient (or the multiplication rule of fuzzy number) and form the trapezoidal fuzzy heat supply quantity born by the main and auxiliary heat sources
And
in the fifth step, the interval heating load born by the heat source is calculated under the given thermalization coefficient gamma by using different alpha-cut (membership degree) intercept interval calculation formulas, wherein the formulas are as follows:
wherein, the trapezoidal fuzzy heat supply four peak values of the main heat source
AndQ na，
and
corresponding to the endpoint values between the time zones of alpha =0 and alpha =1 respectively, thereby forming the main heat source of the interval to bear the heat supply
Four peak values of trapezoidal fuzzy heat supply quantity of peak regulation (auxiliary) heat source
AndQ nb，
and
corresponding to the end point values between the time zones of alpha =0 and alpha =1 respectively, thereby forming the interval peak-shaving heat source bearing the heat supply
Finally, the heating load between the main and auxiliary heat source areas in the heating period corresponding to different alpha-cut (membership degree) interception levels under the given thermalization coefficient gamma is obtained
And
as shown in table 1 below.
TABLE 1 fuzzy heating duration each heat source heating load (unit: PJ)
The step six of controlling the production site to produce heat comprises the following steps: for example, a certain heat source plant adopts coal for heat supply, and can bear the heat supply according to the interval peak-shaving heat source
And
and calculating the reserve value of coal, and changing the quantity of boilers producing heat simultaneously, the opening degree of a valve for supplying oxygen to the boilers, the heating time and other parameters, thereby changing the heat supply quantity of production. If the heat source plant is electric heating or solar energy, the corresponding energy consumption can be calculated.
In summary, the invention firstly calculates the heat load index according to the heat user characteristics (building type, energy conservation and the like) in a weighting way, and simultaneously draws a definite heat load-duration chart by utilizing a piecewise linear method; then, according to the local climate condition of the past year and the meteorological condition of the current year, based on the fuzzy set theory, the uncertain heating duration time is quantized; thirdly, giving a thermalization coefficient, and obtaining uncertain heat supply quantity born by each heat source under the fuzzy condition through integration of the heat load to the duration time when the alpha-cut level is 0 and 1 respectively; and finally, calculating the interval heat supply amount of each heat source in the multi-heat-source centralized heat supply system corresponding to different alpha-cut intercept levels based on the obtained fuzzy heat supply amount membership function, and finally realizing the effective quantification of the heat-source uncertain heat supply amount. The method can solve the problem that the heat source heat supply amount (the heat required by the user) can not be effectively quantified under the uncertain duration, and meanwhile, the calculated heat source heat supply amount of the interval under different alpha-cut sets can provide potential compromise analysis between system possibility and selectable heat supply amount ranges for a heat supply system manager, so that the method has important significance for further saving energy, reducing consumption and optimizing energy consumption cost decision.
The above description is only an embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, improvement, extension, etc. made within the spirit and principle of the present invention are included in the protection scope of the present invention.
Claims (6)
1. The method for calculating and controlling the heat supply quantity of the multiple heat sources in the uncertain heating period based on the fuzzy set is characterized by comprising the following steps of:
step 1: calculating the heating design heat load of the area of the current district according to the different heat user characteristics in a weighted manner;
and 2, step: designing a heat load based on regional heating, and drawing a piecewise linear heating heat load-duration standard curve;
and step 3: based on the evaluation results of experts and operating personnel of a heating system, calculating four peak heat supply values when the corresponding membership degree alpha-cut levels of the trapezoidal fuzzy number are 1 and 0 respectively by utilizing the trapezoidal fuzzy number of a fuzzy set theory, and performing uncertain quantitative characterization on the heating duration time to construct a fuzzy membership function of the fuzzy heating duration time;
and 4, step 4: calculating the vertex values of fuzzy heat supply load of each heat source under a given thermalization coefficient by using the vertex values of the fuzzy heating duration time and a drawn segmental linear heating heat load-duration time standard curve and by using the integral and fuzzy number calculation rule of the heat load on the heating duration time as the fuzzy heat supply load born by each heat source;
and 5: based on the obtained heat demand of the fuzzy heat user, calculating the heating period main and auxiliary heat source district heating load corresponding to different membership degree alpha-cut intercept levels under the given thermalization coefficient
And
step 6: according to the heat supply quantity between the main and auxiliary heat source regions
And
controlling the production heat of the production field.
2. The method for calculating and controlling heat supply quantity of multiple heat sources in uncertain heating periods based on fuzzy sets as claimed in claim 1, wherein the regional heating design heat load Q 'of the current district'nThe calculation is as follows:
wherein, Q'nDesigning heat load for heating, wherein MW and I are different sub-areas in a heating area, the number of the sub-areas is I in the district, J is different building energy-saving types, J is 1 for an energy-saving building, J is 2 for a non-energy-saving building, J is 2, po is the population number of the heating area, ao is the per-living area of the heating area, rb is the proportion of the area of the different energy-saving buildings to the area of all residential buildings in the district, and Qw is a heating design heat index of the different energy-saving buildings, and the heating design heat index is set according to actual conditions when the heating system is used.
3. The method for calculating and controlling the heat supply quantity of the multiple heat sources in the uncertain heating period based on the fuzzy set as claimed in claim 1, wherein a standard curve of heating heat load-duration is drawn by a piecewise linear function between variables, and the formula is as follows:
wherein, the related parameters are as follows:
in the above formulas, QnHeating thermal load, MW; t is tnIndoor temperature is calculated in the heating period; generally taking the temperature to be 18 ℃; t'wFor heatingCalculating the outdoor temperature at the later stage, wherein different cities are determined according to climatic weather conditions, and the average daily temperature which is not guaranteed for five days in the past year is generally adopted as a calculation standard; t is tp·jThe average outdoor temperature and the temperature in the heating period are determined by different cities according to historical temperature data in the heating period; n is continuation days, namely the outdoor air temperature is equal to or lower than t 'in the heating period'wAverage days of the year, days; n is a radical of hydrogenzhDetermining the total days and days in the heating period and different cities according to historical temperature data in the heating period; b is RnP.u. index value of (d); beta is a0Temperature correction factor, p.u.; μ is the correction factor over the course of days (hours), p.u.; r isnDimensionless continuation days, p.u.
4. The method for controlling heat supply amount calculation under multiple heat sources in uncertain heating periods based on fuzzy set as claimed in claim 1, wherein fuzzy delay heating days
The membership function μ (N) of (a) is as follows:
wherein, the four vertex values of the trapezoidal fuzzy number are respectivelyN zh，
And
N zhand
the heat value is supplied to the corresponding boundary when the alpha-cut level is 0 respectively,
and
and the heat supply value of the corresponding boundary is 1 when the alpha-cut level is respectively.
5. The fuzzy set-based multi-heat-source heat supply amount calculation control method in the uncertain heating period as claimed in claim 1, wherein the fuzzy heat supply amount calculation formula born by each heat source is as follows:
heat supply Q in heating period of main heat sourcena：
Total heat supply Q in peak-regulating heat source heating periodnb：
Wherein gamma is a thermalization coefficient, which represents the ratio of the maximum heating load of a main heat source to the total heating load of a system design, p.u.; n is a radical ofγIs the total continuous days,
Qnaand QnbThe main heat source and the peak-shaving heat source respectively bear the heat supply when the thermalization coefficient is gamma, and the GJ is the heat supply.
6. The fuzzy set-based method for controlling heat supply calculation of multiple heat sources in an uncertain heating period as claimed in claim 1, wherein the section heat supply amounts under different alpha-cut level cut sets born by each heat source under a given thermalization coefficient (gamma) are calculated as follows:
wherein, the trapezoidal fuzzy heat supply four peak values of the main heat source
AndQ na，
and
corresponding to the endpoint values between the time zones of alpha =0 and alpha =1 respectively, thereby forming the main heat source of the interval to bear the heat supply
Four peak values of trapezoidal fuzzy heat supply load of peak-shaving heat source
AndQ nb，
and
respectively corresponding to end point values between time zones of alpha =0 and alpha =1, thereby forming a section peak-shaving heat source bearing heat supply quantity
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| CN105202623A (en) * | 2015-09-21 | 2015-12-30 | 国家电网公司 | Method for predicting heating peak modulation capacity of heat supply unit |
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