Thermoelectric load optimization scheduling method based on multi-source coupling heat supply system

Abstract

The invention relates to the field of heat supply scheduling optimization, and aims to solve the problems that a sufficient fluctuation space cannot be reserved during unit operation, unit start-stop or heat throttling output needs to be performed and energy waste is serious due to the fact that a heat supply system directly performs feedback adjustment according to load requirements. The invention specifically relates to a thermoelectric load optimization scheduling method based on a multi-source coupling heat supply system. According to the method, the historical data are classified in a double-cycle set statistical mode, double-cycle set nested application is achieved, historical load data can be called more accurately, the subsequent adjustment fluctuation amplitude is predicted through the historical load database, adjustment modes are selected according to the current adjustment amplitude and the homodirectivity of the subsequent adjustment amplitude, and the adjustment efficiency is improved. The output curves of the multiple heat supply units in the heat source are intelligently selected to be adjusted or the heat supply units are partially started and stopped, so that the starting and stopping interval of the heat supply units is lengthened, meanwhile, the heat supply units can reserve more fluctuation allowance, and coupling adjustment can be conducted according to the load requirement.

Description

Technical Field

[0001] The present invention relates to the field of heat supply scheduling optimization, and in particular to a method for optimizing thermal power load scheduling based on a multi-source coupled heat supply system. Background Art

[0002] The heat network is the main component of the central heating system and is responsible for the transmission of heat energy. The system form of the heat network depends on the relative positions of the heat medium, heat source and heat users, the types of heat users in the heating area, the size and nature of the heat load, etc. The principles to be followed in selecting the heat network system form are safe heating and economic efficiency.

[0003] Steam is mainly used as a heat medium for the production process heat supply of factories. The heat users are mainly the various production equipment of the factory, which are relatively concentrated and small in number. Therefore, the heat network system with a single steam pipe and condensate pipe is the most commonly used method. At the same time, a branch pipe network layout is adopted. When the production process heat supply of the factory cannot be interrupted, a heat network system with double-line steam pipe heating can be adopted. When the steam pressure required by each user of the factory is greatly different or the seasonal heat load accounts for a large proportion of the total load, a heat network system with double steam pipes or multiple steam pipes can be considered.

[0004] Currently, the existing heating system still has shortcomings. Traditional thermal power load scheduling is based on feedback adjustment based on the load demand of the centralized steam heating network. During adjustment, the design load is generally higher than the actual load to reserve fluctuations. During operation, heat output is adjusted by throttling, resulting in some energy waste and failing to improve heat utilization efficiency.

[0005] In response to the above technical problems, this application proposes a solution. Summary of the Invention

[0006] The present invention calculates according to the load change at the heat end to obtain the adjustment amplitude of the current heating capacity, searches through the statistical historical load database, predicts the subsequent adjustment fluctuation amplitude, and selects the adjustment mode according to the unidirectionality of the current adjustment amplitude and the subsequent adjustment amplitude, thereby intelligently selecting the output curve adjustment of multiple heating units inside the heat source or the partial start and stop of the heating units, so that the start and stop intervals of the heating units are lengthened, and at the same time, the heating units can reserve more fluctuation margins, so that coupling adjustment can be performed according to load demand, so as to solve the problem that the heating system directly performs feedback adjustment according to the load demand when providing heat, thereby failing to reserve sufficient fluctuation margin for the operation of the unit, requiring the unit to be started and stopped or heat throttling output, resulting in serious energy waste. A thermal power load optimization scheduling method based on a multi-source coupled heating system is proposed.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A method for optimizing thermal power load scheduling based on a multi-source coupled heating system includes a load supervision module, which is used to obtain the heat-using end load and record it as a heat load. It also obtains the heat loss coefficient during the heating process and calculates the heat demand based on the heat loss coefficient. The load supervision module sends the heat demand to a historical load statistics module and an output balance scheduling module.

[0009] A historical load statistics module, which collects statistics on heat demand and adds time codes;

[0010] A multi-source heat supply scheduling module, which can collect statistics on the heat supply units, obtain the current heat output and the heat output of each sub-unit in the heat supply unit in real time, and record them as sub-source output details;

[0011] An output balancing and scheduling module, which can obtain the current heat output and the output details of each source through the multi-source heat supply scheduling module. After obtaining the heat demand, the output balancing and scheduling module compares it with the current heat output to obtain the heat adjustment amount;

[0012] A scheduling and accounting module, which obtains the heat regulation amount and the sub-source output details through the output balance scheduling module, and obtains the historical heat demand through the historical load statistics module. The scheduling and accounting module allocates and adjusts the heat regulation amount based on the sub-source output details, obtains the adjustment method, and feeds the adjustment method back to the output balance scheduling module;

[0013] The output balancing scheduling module sends the adjustment mode to the multi-source heat supply scheduling module and adjusts the heat output of each sub-unit.

[0014] As a preferred embodiment of the present invention, the historical load statistics module creates a dual-period set when performing statistics on heat demand, and calculates the heat demand contained in the subset in each period set to obtain the heat demand mean of each subset as the regular heat demand change corresponding to the subset;

[0015] The historical load statistics module stores the double-period set to facilitate the dispatching and accounting module to retrieve it.

[0016] As a preferred embodiment of the present invention, the dual-cycle set created by the historical load statistics module includes a long cycle set and a short cycle set, wherein one cycle in the short cycle set is a data collection point in the long cycle set;

[0017] The short cycle set obtains the set short cycle and the collection time within the cycle, and obtains and records the heat demand corresponding to each collection time to obtain the heat demand change of a short cycle. The short cycle set obtains the heat demand change of multiple short cycles, and performs arithmetic averaging on the heat demand change of the same collection time in each short cycle to obtain the average heat demand, thereby constructing the average heat demand change of a complete short cycle.

[0018] The long cycle set obtains a set long cycle and the collection time within the cycle, where the interval between the collection times is a short cycle. The long cycle set calculates the heat demand corresponding to the collection time within a long cycle, and performs arithmetic averaging on the heat demand at the same collection time in multiple long cycles to construct an average heat demand change for a complete long cycle.

[0019] As a preferred embodiment of the present invention, when the multi-source heating scheduling module performs statistics on the heating unit, it labels each sub-unit and records it as sub-unit i, and the heat output of each sub-unit is recorded as qi. The multi-source heating scheduling module records the overall heat output of the heating unit as Q.

[0020] As a preferred embodiment of the present invention, the output balance scheduling module records the acquired heat demand as QX, calculates the difference between the current heat output Q of the multi-source heat supply scheduling module and the heat demand QX, and obtains the heat regulation amount J.

[0021] As a preferred embodiment of the present invention, the scheduling and accounting module obtains the current time when obtaining the heat adjustment amount J, and the scheduling and accounting module obtains the sample heat demand of the corresponding time through the double-period set according to the current time;

[0022] The method for the scheduling and calculation module to obtain the sample heat demand is:

[0023] The scheduling and accounting module obtains the average heat demand at the corresponding time in the long period set, records it as y0, and records the average heat demand at other times in the long period set as yn;

[0024] The scheduling and accounting module obtains the average heat demand of the corresponding time through the short cycle set, which is recorded as x0. The scheduling and accounting module calculates the sample heat demand x through the formula,

[0025] As a preferred embodiment of the present invention, the scheduling and accounting module obtains the average heat demand behind the sample heat demand in the short cycle set and records it as the subsequent predicted heat demand. The scheduling and accounting module calculates the difference between the current heat output Q and the subsequent predicted heat demand to obtain the heat regulation amount J′. The scheduling and accounting module calculates the size of J and J′. If J′>J>0, or J′<J<0, the strong regulation mode is operated, otherwise, the buffer regulation mode is operated.

[0026] As a preferred embodiment of the present invention, when the scheduling and accounting module operates in the buffer adjustment mode, the sub-unit i whose sub-unit heat output qi in the sub-source output details is between the maximum heat output and the minimum heat output is recorded as an adjustable unit, and the heat adjustment amount J is preferentially evenly distributed among the adjustable units. When the heat output qi of the sub-unit i is about to exceed the range of the maximum heat output and the minimum heat output, the sub-unit i is de-identified as an adjustable unit, and the remaining adjustable units continue to be adjusted. If no adjustable units exist, the sub-unit is started or stopped.

[0027] When the scheduling and accounting module operates in the stressed regulation mode, the maximum heat output and the minimum heat output of the sub-unit are calculated by retaining the coefficient to obtain the upper and lower control limits of the heat output, and the sub-units whose heat output qi is between the upper and lower control limits of the heat output are recorded as adjustable units, and the same allocation adjustment as in the buffer regulation mode is performed.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] 1. In the present invention, when regulating the heat supply of a multi-source coupled heating system, calculations are performed based on the load changes at the heat-using end to obtain the regulation amplitude of the current heating capacity, and a search is performed through the statistical historical load database to predict the subsequent regulation fluctuation amplitude. The regulation method is selected based on the unidirectionality of the current regulation amplitude and the subsequent regulation amplitude, thereby intelligently selecting the output curve adjustment of multiple heating units within the heat source or the partial start and stop of the heating units, thereby lengthening the start and stop intervals of the heating units and enabling the heating units to reserve more fluctuation margins, thereby enabling coupled regulation according to load demand.

[0030] 2. In the present invention, when performing statistics on historical load data, the historical data is classified through the statistical method of dual-period sets, so that the load fluctuation situation is refined through short-period sets, making the statistics of historical load data more precise, and the overall load changes are statistically analyzed through long-period sets, and the short-period sets are corrected twice according to the long-period sets, thereby realizing the nested application of dual-period sets, making the historical load data more accurate when retrieved, and providing a more accurate data model for the adjustment of the heating unit.

[0031] 3. In the present invention, by retrieving and analyzing historical load data, the upper and lower operating limits of the heating unit are intelligently adjusted. When continuous fluctuations in the same direction occur, the upper and lower operating limits are contracted to reasonably control the start and stop operations of the heating unit and increase the maximum adjustment capacity. When repeated fluctuations occur, the upper and lower operating limits are expanded to provide a larger fluctuation adjustment margin, improve the adjustment speed, and avoid frequent start and stop of the heating unit. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] To facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0033] Figure 1 is a system block diagram of the present invention;

[0034] Figure 2 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0035] The following is a clear and complete description of the technical solutions of the present invention in conjunction with the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0036] Example 1:

[0037] See also Figure 1 - Figure 2 As shown, the thermal power load optimization scheduling method based on the multi-source coupled heating system includes a load supervision module, a historical load statistics module, a multi-source heating scheduling module, a scheduling accounting module and an output balance scheduling module;

[0038] The load supervision module can obtain the heat-using end load and record it as the heat load. At the same time, it can obtain the heat loss coefficient in the heating process. The heat loss coefficient is determined according to the pipeline transportation distance, pipeline material, and the temperature difference between the inside and outside of the pipeline based on actual measurement and thermodynamic heat transfer model. The heat demand is calculated based on the heat loss coefficient. The load supervision module sends the heat demand to the historical load statistics module and the output balance scheduling module at the same time.

[0039] The historical load statistics module counts the heat demand and adds time codes to obtain heat demand with time information. When counting the heat demand, the historical load statistics module creates a double-period set and calculates the heat demand contained in the subset in each period set to obtain the heat demand mean of each subset as the regular heat demand change corresponding to the subset.

[0040] The historical load statistics module stores the double-period collection to facilitate the dispatching and accounting module to retrieve it;

[0041] The multi-source heating scheduling module can perform statistics on the heating units. When performing statistics on the heating units, each sub-unit is numbered and recorded as sub-unit i. The current heat output and the heat output of each sub-unit in the heating unit are obtained in real time. The overall heat output of the heating unit is recorded as Q, the heat output of each sub-unit is recorded as qi, and the details of the sub-unit output are recorded as source-specific outputs.

[0042] The output balance scheduling module can obtain the current heat output and the sub-source output details through the multi-source heat supply scheduling module. The output balance scheduling module records the obtained heat demand as QX. After obtaining the heat demand, the output balance scheduling module calculates the difference between the current heat output Q of the multi-source heat supply scheduling module and the heat demand QX to obtain the heat adjustment amount J;

[0043] The scheduling and accounting module obtains the heat regulation amount and the sub-source output details through the output balance scheduling module. When obtaining the heat regulation amount J, the scheduling and accounting module obtains the current time. Based on the current time, the scheduling and accounting module obtains the sample heat demand at the corresponding time through the double-cycle set. The scheduling and accounting module allocates and adjusts the heat regulation amount based on the sub-source output details, obtains the adjustment method, and feeds the adjustment method back to the output balance scheduling module.

[0044] The scheduling and accounting module performs allocation adjustment and obtains the adjustment method as follows:

[0045] Step 1: Obtain the average heat demand behind the sample heat demand in the short-term set and record it as the subsequent predicted heat demand. The scheduling and accounting module calculates the difference between the current heat output Q and the subsequent predicted heat demand to obtain the heat adjustment amount J′;

[0046] Step 2: The scheduling and accounting module calculates the size of J and J'. If J'>J>0, or J'<J<0, the strong regulation mode is executed; otherwise, the buffer regulation mode is executed.

[0047] When the scheduling and accounting module is operating in the buffer adjustment mode, the sub-unit i whose sub-unit heat output qi is between the maximum heat output and the minimum heat output in the sub-source output details is recorded as an adjustable unit, and the heat adjustment amount J is preferentially evenly distributed among the adjustable units. When the heat output qi of the sub-unit i is about to exceed the range of the maximum heat output and the minimum heat output, the adjustable unit status of the sub-unit i is cancelled, and the remaining adjustable units are continued to be adjusted. When there is no adjustable unit, the sub-unit is started and stopped.

[0048] When the scheduling and accounting module operates in the strong regulation mode, it calculates the maximum and minimum heat output of the sub-units by using the retention coefficient to obtain the upper and lower control limits of the heat output. It then records the sub-units whose heat output qi is between the upper and lower control limits as adjustable units and performs the same allocation adjustment as in the buffer regulation mode.

[0049] The output balance scheduling module sends the adjustment mode to the multi-source heating scheduling module and adjusts the heat output of each sub-unit.

[0050] Example 2:

[0051] See also Figure 1 - Figure 2 As shown, the dual-cycle set created by the historical load statistics module includes a long-cycle set and a short-cycle set. For example, the long-cycle set has a year as a cycle and includes 12 sets of data in total, with each month as a data collection point. The short-cycle set has a month as a cycle and includes 30 sets of data in total, with each day as a data collection point, so that one cycle in the short-cycle set is a data collection point in the long-cycle set.

[0052] The short-cycle collection obtains the set short cycle and the collection time within the cycle, and obtains and records the heat demand corresponding to each collection time. That is, the daily heat demand required for 30 consecutive days is collected to obtain the heat demand change of a short cycle. The short-cycle collection obtains the heat demand change of multiple short cycles, and takes the arithmetic average of the heat demand change at the same collection time in each short cycle to obtain the average heat demand, and constructs the average heat demand change of a complete short cycle. For example, the heat demand is collected for multiple months, and the arithmetic average of the heat demand of the same days in each month is taken, that is, the average heat demand on the 1st of each month, the average heat demand on the 2nd of each month, and so on, to finally construct the average heat demand for each day of the month;

[0053] The long-period collection obtains the set long period and the collection time within the period. The interval between collection times is a short period, that is, the interval between each collection is one month. The long-period collection calculates the heat demand corresponding to the collection time within a long period, and takes the arithmetic average of the heat demand at the same collection time in multiple long periods to construct the average heat demand change for a complete long period. For example, the heat demand for 12 months of each year over multiple years is collected, and the heat demand for the same month is averaged to construct the average heat demand for each month of the year.

[0054] The method by which the scheduling and accounting module obtains the sample heat demand at the corresponding time through the double-period set is:

[0055] The scheduling and accounting module obtains the average heat demand at the corresponding time in the long-period set and records it as y0, and records the average heat demand at other times in the long-period set as yn;

[0056] The scheduling and accounting module obtains the average heat demand of the corresponding time through the short-term collection, which is recorded as x0. The scheduling and accounting module calculates the sample heat demand x through the formula,

[0057] The above thresholds or preset values, preset ranges, etc. are set for result comparison and analysis in order to determine whether they are good or bad. The values ​​of these thresholds are set for entry and storage based on a combination of large-scale model analysis of sample data and manual experience, and can also be appropriately adjusted based on seasonal or common sense influencing conditions.

[0058] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to specific embodiments. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A thermal power load optimization scheduling method based on a multi-source coupled heating system, characterized in that: It includes a load supervision module, which is used to obtain the heat end load and record it as the heat load. At the same time, it obtains the heat loss coefficient in the heating process and calculates the heat demand based on the heat loss coefficient. The load supervision module sends the heat demand to the historical load statistics module and the output balance scheduling module at the same time; A historical load statistics module, which collects statistics on heat demand and adds time codes; A multi-source heat supply scheduling module, which can collect statistics on the heat supply units, obtain the current heat output and the heat output of each sub-unit in the heat supply unit in real time, and record them as sub-source output details; An output balancing and scheduling module, which can obtain the current heat output and the output details of each source through the multi-source heat supply scheduling module. After obtaining the heat demand, the output balancing and scheduling module compares it with the current heat output to obtain the heat adjustment amount; A scheduling and accounting module, which obtains the heat regulation amount and the sub-source output details through the output balance scheduling module, and obtains the historical heat demand through the historical load statistics module. The scheduling and accounting module allocates and adjusts the heat regulation amount based on the sub-source output details, obtains the adjustment method, and feeds the adjustment method back to the output balance scheduling module; The output balancing scheduling module sends the adjustment mode to the multi-source heat supply scheduling module and adjusts the heat output of each sub-unit.

2. The method for optimizing thermal power load scheduling based on a multi-source coupled heating system according to claim 1, characterized in that: When the historical load statistics module performs statistics on the heat demand, it creates a double-period set and calculates the heat demand contained in the subset in each period set to obtain the heat demand mean of each subset as the regular heat demand change corresponding to the subset; The historical load statistics module stores the double-period set to facilitate the dispatching and accounting module to retrieve it.

3. The method for optimizing thermal and electric load scheduling based on a multi-source coupled heating system according to claim 1, characterized in that: The dual-cycle set created by the historical load statistics module includes a long cycle set and a short cycle set, wherein one cycle in the short cycle set is a data collection point in the long cycle set; The short cycle set obtains the set short cycle and the collection time within the cycle, and obtains and records the heat demand corresponding to each collection time to obtain the heat demand change of a short cycle. The short cycle set obtains the heat demand change of multiple short cycles, and performs arithmetic averaging on the heat demand change of the same collection time in each short cycle to obtain the average heat demand, thereby constructing the average heat demand change of a complete short cycle. The long cycle set obtains a set long cycle and the collection time within the cycle, where the interval between the collection times is a short cycle. The long cycle set calculates the heat demand corresponding to the collection time within a long cycle, and performs arithmetic averaging on the heat demand at the same collection time in multiple long cycles to construct an average heat demand change for a complete long cycle.

4. The method for optimizing thermal power load scheduling based on a multi-source coupled heating system according to claim 1, characterized in that: When the multi-source heat supply scheduling module performs statistics on the heating unit, it labels each sub-unit and records it as sub-unit i, and records the heat output of each sub-unit as qi. The multi-source heat supply scheduling module records the overall heat output of the heating unit as Q.

5. The method for optimizing thermal and electric load scheduling based on a multi-source coupled heating system according to claim 1, characterized in that: The output balance scheduling module records the acquired heat demand as QX, calculates the difference between the current heat output Q of the multi-source heat supply scheduling module and the heat demand QX, and obtains the heat adjustment amount J.

6. The method for optimizing thermal power load scheduling based on a multi-source coupled heating system according to claim 1, characterized in that: When obtaining the heat adjustment amount J, the scheduling and accounting module obtains the current time, and obtains the sample heat demand of the corresponding time through the double-period set according to the current time; The method for the scheduling and calculation module to obtain the sample heat demand is: The scheduling and accounting module obtains the average heat demand at the corresponding time in the long period set, records it as y0, and records the average heat demand at other times in the long period set as yn; The scheduling and accounting module obtains the average heat demand of the corresponding time through the short cycle set, which is recorded as x0. The scheduling and accounting module calculates the sample heat demand x through the formula, 7. The method for optimizing thermal and electric load scheduling based on a multi-source coupled heating system according to claim 1, characterized in that: The scheduling and accounting module obtains the average heat demand behind the sample heat demand in the short cycle set and records it as the subsequent predicted heat demand. The scheduling and accounting module calculates the difference between the current heat output Q and the subsequent predicted heat demand to obtain the heat regulation amount J′. The scheduling and accounting module calculates the size of J and J′. If J′>J>0, or J′<J<0, the strong regulation mode is operated, otherwise, the buffer regulation mode is operated.

8. The method for optimizing thermal and electric load scheduling based on a multi-source coupled heating system according to claim 7, characterized in that: When the scheduling and accounting module operates in the buffer adjustment mode, the sub-unit i whose sub-unit heat output qi in the sub-source output details is between the maximum heat output and the minimum heat output is recorded as an adjustable unit, and the heat adjustment amount J is preferentially evenly distributed among the adjustable units. When the heat output qi of the sub-unit i is about to exceed the range of the maximum heat output and the minimum heat output, the sub-unit i is de-identified as an adjustable unit, and the remaining adjustable units are continuously adjusted. When no adjustable units exist, the sub-unit is started or stopped. When the scheduling and accounting module operates in the stressed regulation mode, the maximum heat output and the minimum heat output of the sub-unit are calculated by retaining the coefficient to obtain the upper and lower control limits of the heat output, and the sub-units whose heat output qi is between the upper and lower control limits of the heat output are recorded as adjustable units, and the same allocation adjustment as in the buffer regulation mode is performed.

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