Building energy consumption operation decision method based on energy budget allocation

Abstract

The application discloses a building energy consumption operation decision method based on energy budget allocation, and particularly relates to the technical field of building energy consumption operation decision, which comprises the following steps: obtaining operation data of a real estate building on the same operation day, writing the room temperature change formed by the budget occupancy and the air conditioner power into an observation row according to the sampling time, and generating a service sequence according to the air conditioner service boundary; processing the service sequence through a hidden semi-Markov model algorithm, establishing a state chain according to the order of space vacancy, temperature drop, temperature preservation, consumption and stability in sequence, and obtaining an observation cost by adding the absolute value of the air conditioner power difference, the absolute value of the room temperature difference and the occupancy turnover value of adjacent observation rows; arranging the building operation data into the service sequence under the same sampling order, identifying the temperature surplus transfer relationship between the pre-cooling section and the surplus consumption section, and solving the budget return quantity and the subsequent operation arrangement after recalculation based on the transfer relationship.

Description

Technical Field

[0001] This invention relates to the field of building energy consumption operation decision-making technology, and more specifically, to a building energy consumption operation decision-making method based on energy budget allocation. Background Technology

[0002] Existing building energy consumption operation decisions mainly revolve around cycle budget control, time-of-use electricity pricing, and equipment operating cost reduction. In the implementation of the project, energy consumption quotas are generally allocated according to floors, tenants, departments, or equipment circuits, and operation strategies are arranged based on air conditioning set temperatures, chiller start-up and shutdown plans, lighting turn-on times, and meeting reservation information. In large office buildings or commercial complexes, property management often pre-cools meeting areas, public areas and adjacent office areas during the low-load period in the morning to ensure that the room temperature remains within a comfortable range when there are concentrated meetings, customer traffic or overtime work in the afternoon. At the same time, it is also necessary to control the frequent start-up and shutdown of the chiller and the budget assessment boundaries of each tenant. In such scenarios, the low-temperature margin formed by pre-cooling does not remain during the period of power consumption, but is gradually consumed when people enter, access control is opened, meetings begin, or customer flow gathers. The existing method of deducting budget based on power consumption time, metering loop, or space area easily includes the pre-cooling energy consumption in the morning in the facility side or low-occupancy area, but fails to include the activity area that actually consumes the temperature margin in the afternoon in the corresponding budget. This mismatch can be directly observed through the time sequence differences between the room temperature recovery curve, access control records, reservation records, and chiller power changes. The technical problem this application aims to solve is: how to identify the actual consumers of temperature surplus across time periods in the building energy consumption budget allocation, and how to deduct the corresponding budget and transfer it back to the operating units that will benefit from it. Summary of the Invention

[0003] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a building energy consumption operation decision-making method based on energy budget allocation. This method organizes building operation data into service sequences under the same sampling order, identifies the temperature margin connection between the pre-cooling section and the surplus section, and solves the budget re-load amount and recalculates subsequent operation arrangements based on the connection relationship, thereby solving the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a building energy consumption operation decision-making method based on energy budget allocation, comprising: S1. Obtain the operational data of the real estate building on the same operating day, write the changes in room temperature and occupancy caused by the budget occupancy and air conditioning power as observation rows according to the sampling time, and generate service sequences according to the air conditioning service boundaries; S2. The service sequence is processed by the hidden semi-Markov model algorithm. The state chain is established according to the order of cooling, heat preservation, consumption and stabilization after the space is vacant. The observation cost is obtained by adding the absolute value of the air conditioning power difference, the absolute value of the room temperature difference and the occupancy reversal value of the adjacent observation rows. The dwell cost is obtained by multiplying the state sampling number by the average value of the observation cost of the state segment. The pre-cooling segment and the consumption segment are output by Witte segment recursion. S3. For the precooling section and the waste section, generate cooling chain and warming chain according to the sampling order. Use dynamic time warping algorithm to recursively accumulate the absolute value of the temperature difference at the same position of the two chains, and generate the connecting chain by tracing back along the last accumulated cost. S4. Establish a linear programming strategy optimization table based on the support chain, take the budget deduction of the pre-cooling section as the amount to be re-attached, so that the amount allocated to the re-attached position is limited by the remaining budget and the total amount allocated is limited by the amount to be re-attached. The budget re-attached amount is obtained through simplex iteration and the re-attached record is generated. S5. Based on the reattachment record, deduct the remaining budget of the corresponding reattachment position of the receiving chain, recalculate the subsequent occupancy start and end positions and the early running time of the air conditioner according to the remaining budget after deduction, and output the building energy consumption operation decision results.

[0005] In a preferred embodiment, S1 includes: S1-1. Obtain the operation data of the real estate building on the same operation day, establish the operation row based on the sampling time, write the budget unit that the sampling time falls into the space occupancy start and end position into the budget occupancy position, and output the operation row with the budget occupancy position. The process of establishing a running row based on the sampling time is as follows: using the sampling time in the building operation data as a unique row number, the space occupancy record, budget record, air conditioning power record and room temperature record corresponding to the same sampling time are written into the same row; if there are multiple space occupancy records at the same sampling time, running rows are generated separately according to the space number; The space occupancy start and end positions refer to the two sampling positions in the space occupancy record used to indicate the start and end of the use of the target space for a certain budget unit. The start of use corresponds to the occupancy start position, and the end of use corresponds to the occupancy end position. A budget unit refers to an object that independently bears the energy budget deduction in the operation of a real estate building. It is specifically determined by the tenant number, department number, or functional area number in the building operation ledger, and the budget amount corresponding to the same number is used as the deduction object. S1-2. Based on the running row with budget occupancy bits, perform the subtraction of the previous value from the next value of the air conditioner power at adjacent sampling times, write the power difference into the corresponding running row, and output the power difference running row.

[0006] In a preferred embodiment, S1 further includes: S1-3. Based on the power difference, perform the subtraction of the previous value from the subsequent value of the room temperature at adjacent sampling times, and write the change of space occupancy from none to one or from one to none into the occupancy flip bit, and output the observation row. S1-4. Read the air conditioning terminal control address corresponding to the observation row, and concatenate the observation rows with the same control address in ascending order according to the sampling time to generate a service sequence. The air conditioning terminal control address refers to the address field used in the building automation system to uniquely identify the control object of the air conditioning terminal equipment. This address field corresponds to the control point of the same fan coil unit, air conditioning box outlet branch, or variable air volume terminal.

[0007] In a preferred embodiment, S2 includes: S2-1. Read the service sequence, establish a chain table according to the sampling order, write the idle, pre-cooling, reserve maintenance, consumption and stabilization as incremental state numbers, stipulate that the current state number can only continue the current state number or the next state number, and delete the remaining continuation path in the cumulative cost table. The process of establishing the chain bit table is as follows: based on the ascending order of the sampling time of the observation rows in the service sequence, the first observation row is written as the first chain bit, and each subsequent observation row is written into the next chain bit in ascending order of the sampling time. In each chain bit, the budget occupancy bit, air conditioning power difference, room temperature difference and occupancy flip value corresponding to the observation row are retained. S2-2. For each state number and the first and last positions of each group of segments, a candidate segment is formed. The state matching cost is calculated according to each observation row in the candidate segment. Among them, the empty corresponding budget occupancy bit is empty and the air conditioning power is zero. The pre-cooling corresponding budget occupancy bit is empty and the room temperature difference is negative. The margin maintenance corresponding budget occupancy bit is empty and the absolute value of the room temperature difference is included in the cost. The surplus corresponding budget occupancy bit is not empty and the room temperature difference is positive. The recovery corresponding occupancy flip bit is zero and the absolute value of the room temperature difference is included in the cost. The process of calculating the state matching cost is as follows: each observation row in the candidate segment is assigned a value according to the corresponding state number. When the observation row meets the field conditions of the corresponding state, the state matching cost is recorded as zero. When the observation row does not meet the field conditions of the corresponding state, the number of fields that are not met is taken as the state matching cost. The state matching costs of each observation row in the candidate segment are added together to obtain the state matching cost of the candidate segment.

[0008] In a preferred embodiment, S2 further includes: S2-3. Based on the candidate segment, the absolute value of the air conditioning power difference, the absolute value of the room temperature difference, the occupancy flip value and the state matching cost of each observation row in the segment are added together to obtain the observation cost. The sum of the observation costs is used as the dwell cost. The cumulative cost of the previous state number in the previous order of the segment is added to the dwell cost to obtain the candidate cumulative cost. The occupancy flip value refers to writing 1 when the budget occupancy bit of adjacent sampling positions within the same air conditioning service boundary changes from empty to non-empty or from non-empty to empty, and writing 0 when the budget occupancy bit does not change. S2-4. For candidate cumulative costs under the same state number and the same segment tail position, take the first one in ascending order of value and write it into the cumulative cost table, and write the corresponding segment head position and the previous state number into the predecessor table. S2-5. After writing the stabilization state number at the end of the chain position table, write the state number of each observation row back along the predecessor table in reverse. Write the sampling order corresponding to the pre-cooling state number into the pre-cooling section and write the sampling order corresponding to the consumption state number into the consumption section. The stable state refers to the state after the surplus state, where the budget occupancy position remains non-empty or becomes empty, and the absolute value of the room temperature difference between adjacent observation rows participates in the dwell cost calculation. It is used to indicate the termination segment where temperature change enters the budget back-hanging calculation.

[0009] In a preferred embodiment, S3 includes: S3-1. Read the room temperature values ​​of adjacent observation rows in the pre-cooling section, subtract the next room temperature value from the previous room temperature value to generate the cooling share, write zero when the cooling share is negative, and write it into the cooling chain according to the sampling order. S3-2. Read the room temperature values ​​of adjacent observation rows within the surplus segment, subtract the previous room temperature value from the next room temperature value to generate the recovery share. Write zero when the recovery share is negative, and write the recovery share to the corresponding budget occupancy bit according to the sampling order.

[0010] In a preferred embodiment, S3 further includes: S3-3. Establish a regularization table with the chain position of the cooling chain as the regularization row and the chain position of the reheating chain as the regularization column. Write the absolute value of the difference between the cooling share and the reheating share in the current regularization cell as the cell cost. Then compare the cumulative costs of the source cells to the left, top, and top left of the current regularization cell in turn. Add the cumulative cost of the first source cell in ascending order to the cell cost and write it into the current regularization cell. S3-4. When writing the cumulative cost in the current regularized cell, write the row and column positions of the first source cell in ascending order to the backtrack position, and read backward from the last row and last column of the regularized table along the backtrack position to the first row and first column to generate a pairing path between the cooling chain and the warming chain. S3-5. Read the cooling share balance and the warming share balance bit by bit along the pairing path, write the first bit of the two in ascending order of value as the acceptance amount, and write the acceptance amount back to the budget occupancy bit corresponding to the current warming chain bit, and output the acceptance chain.

[0011] In a preferred embodiment, S4 includes: S4-1. Read the acceptance chain, accumulate the acceptance quantity corresponding to the same budget occupancy position to the total acceptance quantity of the corresponding budget occupancy position, and write the budget occupancy positions with a non-zero total acceptance quantity into the back-attached position table. S4-2. Read the back-hanging position table, establish a budget back-hanging amount variable for each back-hanging position, and limit the value range of the budget back-hanging amount variable to zero to the total amount accepted by the corresponding back-hanging position and the first value in the remaining budget.

[0012] In a preferred embodiment, S4 further includes: S4-3. Subtract the sum of each budget return variable from the pre-cooling section budget deduction to obtain the unreturned amount, and use the unreturned amount as the target variable of the simplex target row to generate the initial simplex table. The budget deduction refers to the sum of the budget deduction values ​​for air conditioning energy consumption corresponding to each observation row in the pre-cooling section. The budget deduction value for air conditioning energy consumption of a single observation row is obtained by multiplying the air conditioning power of the observation row by the sampling interval to obtain the power consumption, and then converting it into the budget deduction value according to the electricity price corresponding to the current operating day of the target building. S4-4. Perform simplex iteration in the initial simplex table. Select the column containing the negative test number in the target row as the infeed column. Select the right-hand side of the positive coefficient of the infeed column as the quotient obtained by dividing the positive coefficient of the infeed column by the positive coefficient of the infeed column as the outfeed row. After the outfeed row is normalized and the infeed column is eliminated, the updated simplex table is obtained until the negative test number in the target row is empty. S4-5. Read and update the simplex table, write the right-hand side quantity corresponding to the basic variable as the budgeted back-hanging quantity of the corresponding back-hanging position, write the budgeted back-hanging quantity corresponding to the non-basic variable as zero, and generate back-hanging records according to the back-hanging position and budgeted back-hanging quantity. The basic variable refers to the budgeted slack variable or the unit column in the simplex tableau. The unit column takes a value of 1 in one row and a value of zero in the other rows. The current value of the basic variable is the right-hand value of the same row.

[0013] In a preferred embodiment, S5 includes: S5-1. Read the back-up record, deduct the back-up amount from the remaining budget of the same budget occupancy position using the back-up position as the index. If the value after deduction is negative, write the remaining budget to zero and write the absolute value of the negative number to the arrears position. Output the deduction budget table. S5-2. Based on the deduction budget table, the service sequence is read by sampling according to the subsequent occupancy start position. The air conditioning power, sampling interval and daily operating price are multiplied to obtain the sampling budget value. The sampling budget value is deducted sequentially from the remaining budget. The last sampling position of the remaining budget before deduction that is not lower than the sampling budget value is written as the recalculation occupancy termination position. S5-3. Read the pre-cooling segment backward from the starting position of the subsequent occupation, multiply the air conditioning power, sampling interval and daily operating price of each pre-cooling sample to obtain the pre-cooling sampling budget value, and deduct the pre-cooling sampling budget value from the remaining budget digit by digit until the remaining budget is lower than the next pre-cooling sampling budget value, generate the air conditioning advance running time according to the deducted pre-cooling sampling number, and output the building energy consumption operation decision result.

[0014] The technical effects and advantages of this invention are as follows: 1. This solution identifies the pre-cooling section and the surplus section and generates a connection chain, mapping the temperature surplus across time periods to the actual consumption budget occupancy position, thereby relatively alleviating the budget mismatch where pre-cooling energy consumption is included in the facility side or low-occupancy area. 2. Using the sampling time as a unified index to generate observation rows, budget occupancy, air conditioning power change, room temperature change, and occupancy reversal are placed in the same calculation order, which relatively improves the problem of difficulty in aligning multi-source operation records; 3. Perform hidden semi-Markov segmentation on the service sequence to form a traceable state path of idling, pre-cooling, margin maintenance, consumption, and stabilization, which relatively improves the segmentation interpretability of pre-cooling behavior and consumption behavior. 4. In the dynamic time warping recursion, the cooling chain and the warming chain are paired to establish a connection between the temperature drop share and the subsequent warming share, thereby reducing the deviation caused by allocating the budget according to the power consumption time. 5. Establish a linear programming strategy optimization table based on the acceptance chain, so that the budget reversal amount is jointly limited by the total acceptance amount, the remaining budget and the budget deduction amount of the pre-cooling section, thereby relatively improving the executability of the budget deduction results. Attached Figure Description

[0015] Figure 1 This is a technical roadmap for temperature margin acceptance and budget rewinding in this invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Refer to the instruction manual appendix Figure 1 The present invention provides a building energy consumption operation decision-making method based on energy budget allocation, comprising: S1. Obtain the operational data of the real estate building on the same operating day, write the changes in room temperature and occupancy caused by the budget occupancy and air conditioning power as observation rows according to the sampling time, and generate service sequences according to the air conditioning service boundaries; To enable the budget responsibility, air conditioning operation, room temperature change and space occupancy recorded separately within the same operating day of real estate buildings to be included in subsequent segmented calculations, this implementation method first establishes a traceable operating line according to the sampling time, then writes the air conditioning power change, room temperature change and occupancy into the same observation structure, and finally forms a service sequence according to the air conditioning terminal control address. The running data must include at least the sampling time, space number, space occupancy start and end positions, budget unit number, budget amount, air conditioning terminal control address, air conditioning power, and room temperature value. If the fields that support subsequent difference calculation are missing, the corresponding running row will not enter the observation row generation process. After the operational data of a real estate building on the same operating day is entered into S1-1, an operational row is established based on the sampling time: the sampling time is used as the row number, and the space occupancy record, budget record, air conditioning power record and room temperature record under the same sampling time are written into the same operational row; when there are multiple space occupancy records at the same sampling time, operational rows are generated separately according to the space number. The start and end positions of space occupancy are two sampling positions for the budget unit to start and end the use of the target space. The start of use corresponds to the start position of occupancy, and the end of use corresponds to the end position of occupancy. The budget unit is the object that independently bears the energy budget deduction in the operation of real estate buildings, and is determined by the tenant number, department number or functional area number in the building operation ledger. When the sampling time falls within the start and end positions of space occupancy, the budget occupancy bit is written with the corresponding budget unit number; when the sampling time does not fall within the start and end positions of space occupancy, the budget occupancy bit is written as empty. When multiple budget units correspond to the same space and the same sampling time, run lines are generated separately according to the space occupancy record, and multiple budget unit numbers are written in parallel in different run lines. The changes in air conditioning operation are generated in S1-2 by the operation line with budget occupancy bit: first, the operation line is grouped according to the space number and the air conditioning terminal control address, and then arranged in ascending order according to the sampling time within each group; Starting from the second sampling time, the power difference is obtained by subtracting the air conditioning power of the previous running row from the air conditioning power of the current running row, and the power difference is written to the current running row; if there is no previous running row in the first running row of each group, the power difference is written to zero. When the air conditioner power field is missing, a power missing item flag is written to the corresponding running line and the generation of subsequent observation lines is stopped; when the air conditioner power field is the shutdown power code in the building automation system or electricity meter record, it is written as zero. Room temperature changes and occupancy status are combined into observation rows in S1-3: using the space number and air conditioning terminal control address grouping results, room temperature values ​​are read in ascending order of sampling time within each group; Starting from the second sampling time, the room temperature difference is generated by subtracting the room temperature value of the previous run from the room temperature value of the current run and written to the current run; the room temperature difference is written to zero for the first run of each group if there is no previous run. The occupied flip bit is determined by the budget occupied bit of the adjacent sampling sequence: empty bit is changed to non-empty bit and written as 1, non-empty bit is changed to empty bit and written as 1, and other changes are written as zero. When the room temperature value is missing, a missing room temperature flag is written to the corresponding run line and the generation of observation lines is stopped; a run line with complete fields forms an observation line with the budget occupied bits, power difference, room temperature difference, and occupied flip bits. The service sequence is formed in S1-4 according to the air conditioning service boundary: read the air conditioning terminal control address of each observation row. The air conditioning terminal control address is the address field that uniquely identifies the control object of the air conditioning terminal equipment in the building automation system, corresponding to the control point of the same fan coil unit, air conditioning box outlet branch or variable air volume terminal; observation rows with the same control address are grouped into the same air conditioning service boundary and concatenated in ascending order according to the sampling time. When multiple spatial numbers exist at the same sampling time, they are concatenated in ascending order according to the spatial numbers; when the spatial numbers are the same, they are concatenated in ascending order according to the budget unit numbers. When an observation row lacks an air conditioning terminal control address, a record for the missing address is written to the corresponding observation row, and it is not included in the service sequence; after the serialization is completed, the service sequence is written to the S2 read position; After processing by S1, the budget occupancy bit, power difference, room temperature difference, occupancy flip bit, and air conditioner terminal control address form a unified sequence relationship, and S2 can then directly read the service sequence to perform hidden semi-Markov segmentation. When the information is recorded at the property operation site: a meeting room on the third floor of an office building is used by tenant T01 from 09:00 to 11:00. 09:00 is written as the start of occupancy and 11:00 is written as the end of occupancy. The air conditioning terminal control address is VAV-3F-05. The system generates running rows by sampling every 5 minutes. The budget occupancy bits from 09:00 to 11:00 are written into T01, and the bits before 09:00 are written as empty bits. Then, the power difference, room temperature difference, and occupancy flip bits are calculated row by row. Finally, the observation rows corresponding to VAV-3F-05 are concatenated into a service sequence for subsequent identification of the pre-cooling section, the surplus section, and the budget re-attachment object.

[0018] S2. The service sequence is processed by the hidden semi-Markov model algorithm. The state chain is established according to the order of cooling, heat preservation, consumption and stabilization after the space is vacant. The observation cost is obtained by adding the absolute value of the air conditioning power difference, the absolute value of the room temperature difference and the occupancy reversal value of the adjacent observation rows. The dwell cost is obtained by multiplying the state sampling number by the average value of the observation cost of the state segment. The pre-cooling segment and the consumption segment are output by Witte segment recursion. Based on the established service sequence, this implementation method uses a hidden semi-Markov model algorithm to break down the operation process within the same air conditioning service boundary into state segments with a fixed sequence relationship, so that pre-cooling behavior and subsequent consumption behavior can be located from the same service sequence. Instead of setting separate empirical judgment values ​​during processing, the budget occupancy, air conditioning power, air conditioning power difference, room temperature difference, and occupancy reversal value are converted into state matching cost, dwell cost, and cumulative cost, and the pre-cooling section and consumption section are obtained by writing back the predecessor table. After the service sequence enters S2-1, a chain table is first established in ascending order of sampling time: the first observation row in the service sequence is written to the first chain position, and subsequent observation rows are written to the next chain position one by one in order of sampling time; the same chain position retains the budget occupancy bit, air conditioning power, air conditioning power difference, room temperature difference and occupancy flip value. The status number is written in a fixed manner according to the meaning of operation: the first status number is when it is empty, the second status number is when it is pre-cooled, the third status number is when it is maintained, the fourth status number is when it is consumed, and the fifth status number is when it stabilizes. The cumulative cost table only retains the path that continues from the current state number or the path that continues from the next state number; other paths are not written into the cumulative cost table. To ensure that the recursion has a starting point, a starting virtual chain is set before the first chain. The cumulative cost of the first state number corresponding to the starting virtual chain is written to zero, and the cumulative cost of the other state numbers is not written. In S2-2, the candidate segment is determined by the state number and the chain position order: the first position of the segment is any chain position in the chain position table, and the last position of the segment is a chain position no earlier than the first position of the segment. The candidate segment includes all observation rows from the first position of the segment to the last position of the segment, and skipping intermediate chain positions is not allowed. For each observation row in the candidate segment, calculate the state matching cost line by line. The empty state is determined by the budget occupancy bit being empty and the air conditioning power being zero. The pre-cooling state is determined by the budget occupancy bit being empty and the room temperature difference being negative. The margin maintenance state is determined by the budget occupancy bit being empty and the absolute value of the room temperature difference being included in the subsequent observation cost. The surplus state is determined by the budget occupancy bit being non-empty and the room temperature difference being positive. The recovery state is determined by the occupancy flip bit being zero and the absolute value of the room temperature difference being included in the subsequent observation cost. Each field involved in the judgment is recorded as zero when it meets the corresponding condition and as one when it does not. The values ​​of each observation row in the candidate segment are added together to obtain the candidate segment state matching cost. The margin maintenance state is only allowed after the precooling state and before the depletion state, and the stabilization state is only allowed after the depletion state. The two are distinguished by the state order and the budget occupancy bit. In S2-3, the cost recursion transforms the local operational characteristics of the candidate segment into comparable path costs: for each observation row within the candidate segment, the absolute value of the air conditioning power difference, the absolute value of the room temperature difference, the occupancy reversal value, and the state matching cost are added together to obtain the observation cost; The observation costs of all observation rows within a candidate segment are added together to obtain the dwell cost; then the cumulative cost of the previous state number in the chain preceding the segment head is read, and this cumulative cost is added to the dwell cost of the current candidate segment to obtain the candidate cumulative cost; if the segment head is the first chain, the cumulative cost of the starting virtual chain is read. The occupancy flip value is determined by the change in the budget occupancy bit of adjacent sampling positions within the same air conditioning service boundary. When an empty bit turns into a non-empty bit, write 1; when a non-empty bit turns into an empty bit, write 1; when the budget occupancy bit remains unchanged, write 0. In S2-4, the cumulative cost table completes the path selection writing under the same segment tail position: the candidate cumulative costs generated by the same state number and the same segment tail position are arranged in ascending order of value, the first sorted value is written into the cumulative cost table, and the corresponding segment head position and the previous state number are written into the predecessor table. When the cumulative costs of candidates are the same, the first candidate is selected in ascending order of the first position of the segment. If the first positions of the segments are the same, the first candidate is selected in ascending order of the previous state number. With this write rule, each status number retains only one predecessor path at the end of each segment, and no parallel paths will appear in subsequent write-backs. After the cumulative cost of the fifth state number is written to the last position of the chain table, S2-5 performs a reverse write-back along the predecessor table: starting from the fifth state number at the end of the chain table, read the predecessor table, obtain the corresponding segment head position and the previous state number, write the observation line between the segment head position and the current segment tail position to the current state number, and then use the previous state number and the chain position before the segment head position as the new write-back position, until the write-back reaches the starting virtual chain position; After the reverse write-back is completed, the sampling sequence with the state number of the second state number is written into the pre-cooling segment, and the sampling sequence with the state number of the fourth state number is written into the consumption segment. If the cumulative cost of the fifth state sequence number is not written to the last position of the chain table, the service sequence will not output the pre-cooling segment and the remaining segment, and will write the incomplete record of the state chain for the operation personnel to check the integrity of the service sequence fields. After S2 processing is completed, the service sequence within the same air conditioning service boundary is transformed into a state path with a unique predecessor path. The pre-cooling segment corresponds to the cooling process after idling, and the waste segment corresponds to the temperature recovery process after personnel enter. Subsequently, S3 can directly read the pre-cooling segment and the waste segment to generate cooling chain and temperature recovery chain. In the context of building operations, the meeting room is pre-cooled by the air conditioner before use. The service sequence first presents the observation row where the budget occupancy position is empty and the room temperature difference is negative, and then presents the observation row where the budget occupancy position is not empty and the room temperature difference is positive. S2 uses state matching cost, dwell cost, and Witte score segment recursion to write the sampling order of early cooling into the pre-cooling segment and the sampling order of warming up after entering use into the consumption segment, providing verifiable timing basis for subsequent budget reloading.

[0019] S3. For the precooling section and the waste section, generate cooling chain and warming chain according to the sampling order. Use dynamic time warping algorithm to recursively accumulate the absolute value of the temperature difference at the same position of the two chains, and generate the connecting chain by tracing back along the last accumulated cost. After the precooling section and the consumption section have been given by S2, this implementation method converts the "temperature margin formed by pre-cooling" and "temperature recovery consumed after personnel enter" into a pairable numerical chain, and then determines the connection relationship between the two through a dynamic time warping algorithm, so that the subsequent budget re-attachment is not assigned according to the time of power consumption, but according to the budget occupancy position of the temperature margin being consumed. The temperature drop is obtained starting from the observation row in the pre-cooling section, corresponding to S3-1. The room temperature values ​​of two adjacent observation rows are read according to the sampling order, and the cooling share is generated by subtracting the next room temperature value from the previous room temperature value. When the calculation result is negative, the cooling share should be written as zero; when the calculation result is zero or positive, the original value should be written. The cooling share calculated from the nth observation row and the (n+1)th observation row is written into the sampling order corresponding to the (n+1)th observation row, so that the cooling share maintains the same order caliber as the subsequent chain positions; If any observation row in the precooling section lacks a room temperature value, the corresponding adjacent difference will not generate a cooling share, and will be written into the cooling missing item record, and will not enter the cooling chain; The recovery amount in the residual section is obtained in the opposite direction in S3-2: the room temperature values ​​of two adjacent observation rows in the residual section are read according to the sampling order, and the recovery share is generated by subtracting the previous room temperature value from the subsequent room temperature value; when the calculation result is negative, the recovery share is written to zero, and when the calculation result is zero or positive, it is written according to the original value. The recovery share calculated from the nth observation row and the (n+1)th observation row is written into the budget occupancy bit corresponding to the (n+1)th observation row; If the budget occupancy bit of the (n+1)th observation row is empty, the warm-up share is only retained in the warm-up chain and does not participate in subsequent budget occupancy bit write-back; after completion, each link in the warm-up chain has at least the sampling order, warm-up share and budget occupancy bit; The dynamic time warping calculation is carried out in S3-3. First, the chain position of the cooling chain is used as the warping row and the chain position of the reheating chain is used as the warping column to build a warping table. For each warping cell, the cooling fraction and the reheating fraction in the same cell are read, and the absolute value of the difference between the two is written as the cell cost. The cumulative cost of the first row and first column of the normalization table is equal to the cell cost of the same normalized cell; normalized cells in the first row can only read the cell from the left source, and normalized cells in the first column can only read the cell from the top source; The remaining regularized cells sequentially read the cumulative costs from the source cells on the left, top, and top left, and sort the cumulative costs in ascending order. The cumulative cost of the first source cell in the sorted order is added to the cost of the current cell and written into the current regularized cell. If multiple source cells have the same cumulative cost, they are written into the source cells in the order of top left, left, and top. The reading of the regularized path is completed by S3-4: when writing the cumulative cost in each regularized cell, the row and column positions of the first source cell of the sorting are simultaneously written to the backtrack position; After the cumulative cost is written to the last row and last column of the regularization table, read backwards from the last row and last column until the first row and first column are read. Then, reverse the order according to the reverse reading result to generate a pairing path from the starting position of the cooling chain to the ending position of the warming chain. If the regularization table is missing the cumulative cost in the last row and last column, it means that the cooling chain or the warming chain is empty. S3 will not output the receiving chain and will write the missing receiving item record. The acceptance quantity is written back bit by bit along the pairing path in S3-5: each cooling chain bit first uses the corresponding cooling share as the cooling share balance, and each warming chain bit first uses the corresponding warming share as the warming share balance. When reading the current cooling chain position and the current warming chain position on the pairing path, sort the cooling share balance and the warming share balance in ascending order of value, and write the first sorting position as the receiving quantity; After the acceptance amount is written into the budget occupancy bit corresponding to the current warming chain position, the acceptance amount is simultaneously deducted from the cooling share balance of the current cooling chain position, and the acceptance amount is also deducted from the warming share balance of the current warming chain position; chain positions with a balance of zero will no longer generate acceptance amount in subsequent pairing paths. The output receiving chain includes at least the cooling chain position, the reheating chain position, the budget occupancy position, the sampling sequence, and the receiving quantity, which are used by S4 to merge the budget return quantity according to the budget occupancy position; After S3 processing, the cooling share in the precooling section no longer stays at the moment when the air conditioner consumes energy, but is written back to the corresponding budget occupancy position in the surplus section through the regularization table, backtracking position and load capacity; When the meeting room was brought to the building's operational site, it was cooled down in advance between 08:30 and 09:00, creating multiple cooling zones. After tenants entered at 09:00, it was cooled down in multiple warming zones. The dynamic time warping algorithm pairs the two numerical chains according to the temperature change pattern, and the amount of acceptance is written into the budget occupancy bit to be used. S4 can then use this to attach the pre-cooling budget deduction back to the budget unit of the actual consumed temperature margin.

[0020] S4. Establish a linear programming strategy optimization table based on the support chain, take the budget deduction of the pre-cooling section as the amount to be re-attached, so that the amount allocated to the re-attached position is limited by the remaining budget and the total amount allocated is limited by the amount to be re-attached. The budget re-attached amount is obtained through simplex iteration and the re-attached record is generated. After the support chain is generated, this implementation method converts the support relationship of the temperature margin into a budget back-hanging problem. First, the support quantities under the same budget occupancy position are merged. Then, the remaining budget and the total support quantity are used to jointly limit the budget back-hanging quantity variable. Finally, the un-backed quantity is used as the object to be compressed and simplex iteration is performed so that the budget deduction of the pre-cooling section can be written into the back-hanging record according to the actual surplus object. When the receiving chain enters the merging process, the budget occupancy position and receiving quantity in the receiving chain are read one by one according to S4-1; the receiving quantities with the same budget occupancy position are accumulated, and the accumulation result is written as the total receiving quantity; Budget occupancy bits with a total amount of zero are not included in subsequent solutions. Budget occupancy bits with a total amount of non-zero are written into the back-hanging bit table and used as back-hanging bits. If there are any acceptance quantities with empty budget occupancy slots within the acceptance chain, the corresponding acceptance quantities will not participate in the merging and will be written into the empty slot acceptance record to avoid writing unaccepted temperature margins into the budget deduction object. After the return position table is formed, S4-2 establishes a budget return amount variable for each return position; the remaining budget reads the budget balance of the return position in the same operating day before the return record is generated, and the total amount and remaining budget are arranged in ascending order of value. The first position is used as the upper bound of the budget return amount variable, and zero is used as the lower bound of the budget return amount variable. Therefore, each budget rewind variable can only take a value between zero and the upper limit, neither exceeding the temperature margin acceptance result nor the budget balance that can be deducted at the rewind position. The budget deduction for the pre-cooling section is written into the simplex solution objective in S4-3: For each observation row in the pre-cooling section, the power consumption is obtained by multiplying the air conditioning power by the sampling interval, and then converted into the air conditioning energy consumption budget deduction value according to the electricity price corresponding to the current operating day of the target building; the air conditioning energy consumption budget deduction values ​​of each observation row are added together to obtain the budget deduction for the pre-cooling section. Then, the sum of all budgeted return variables is subtracted from the pre-cooling section budget deduction to obtain the unreturned amount, and the unreturned amount is written as the target variable of the simplex target row; Each budget revert quantity variable is set with an upper bound slack variable, and the right-hand side quantity is written into the upper bound of the budget revert quantity variable to generate an initial simplex table; if the operating daily electricity price is missing, the pre-cooling segment budget deduction quantity is not generated, S4 stops and writes the electricity price missing item record; In S4-4, the simplex iteration is updated according to the values ​​in the table: the target row of the initial simplex table is read, and the first column in ascending order of the column number containing the negative test number is selected as the input basis column; Next, read the row containing the positive coefficients in the input base column, divide the right-hand value by the positive coefficients in the input base column to obtain the quotient value, and use the first row in ascending order of the quotient value as the output base row; When normalizing the out-of-basic row, divide all the values ​​of the out-of-basic row by the value of the cell where the in-basic column intersects with the out-of-basic row; when eliminating variables in the in-basic column, for each row except the out-of-basic row, subtract the coefficient of the in-basic column multiplied by the normalized out-of-basic row from that row to obtain the updated simplex tableau. The iteration stops when the negative test number in the target row is empty; if the input column has no positive coefficients, S4 stops and writes to the unbounded solution record. The solution result reading stage corresponds to S4-5: In the simplex tableau after stopping iteration, the budget back-hanging quantity variable or slack variable corresponding to the unit column is written as the basic variable. The unit column takes a value of 1 in one row and a value of zero in the other rows. The basic variable takes the value at the right end of the same row. For budget repatriation variables that become basic variables, the right-hand side is written as the budget repatriation amount for that repatriation position; for budget repatriation variables that do not become basic variables, they are written as zero. After reading is complete, a back-hanging record is generated according to the back-hanging position and the budget back-hanging amount, and the un-back-hanging amount is synchronously written into the back-hanging record for S5 to deduct the budget and recalculate the start and end positions of subsequent occupation; After S4 is completed, the temperature margin acceptance relationship in the acceptance chain is converted into an executable budget back-up record. The budget back-up amount is simultaneously constrained by the total acceptance amount, the remaining budget, and the budget deduction amount of the pre-cooling section. In the context of building operations, if meeting room A and training room B both consume the temperature margin formed by the same pre-cooling section, S4 first accumulates the total capacity of meeting room A and training room B respectively, and then uses their respective remaining budgets to limit the budget back-hanging quantity variable. After simplex iteration, the budget back-hanging quantity of each back-hanging position is generated, so that the pre-cooling energy consumption no longer remains on the facility side, but is written into the budget occupancy position of the actual consumed temperature margin.

[0021] S5. Based on the reattachment record, deduct the remaining budget of the corresponding reattachment position of the receiving chain, recalculate the subsequent occupancy start and end positions and the early running time of the air conditioner according to the remaining budget after deduction, and output the building energy consumption operation decision results. After the re-attachment record is generated, this implementation method incorporates the budget re-attachment amount into subsequent operational decisions. First, the remaining budget of the re-attachment position is updated, then the subsequent occupancy termination position is recalculated according to the updated remaining budget, and finally, the air conditioning advance operation time that can still be undertaken is calculated in reverse, so that the budget re-attachment result is transformed into an executable building energy consumption operation decision result. Budget deductions in S5-1 are performed based on the backlog records: read the backlog position and budget backlog amount in the backlog record, use the backlog position as an index to find the remaining budget for the same budget position on the current operating day, and subtract the budget backlog amount from the remaining budget to obtain the remaining budget after deduction; If the remaining budget after deduction is not less than zero, it is directly written into the deduction budget table; if the remaining budget after deduction is less than zero, the remaining budget in the deduction budget table is written as zero, and the absolute value of the remaining budget after deduction is written into the arrears position. The outstanding balance is only used to mark the undeducted portion of the outstanding balance that exceeds the remaining budget in the backlog record. It is not included in the recalculation of the subsequent occupancy termination position to prevent negative values ​​from continuing to be included in the calculation of operating time. The start and end positions of subsequent occupancy are redefined in S5-2 according to the deduction budget table: the start position of subsequent occupancy is the first occupancy start position of the budget unit corresponding to the back-hanging position after the time of back-hanging record generation; Starting from the subsequent occupancy start position, the service sequence is read line by line according to the sampling order. The air conditioning power of the current observation line is multiplied by the sampling interval and then multiplied by the daily operating price to obtain the sampling budget value. The sampling budget value is then deducted sequentially from the remaining budget after deduction. Before each deduction, if the remaining budget is not lower than the current sampled budget value, the current sampled priority is written as the available priority; continue reading until the remaining budget is lower than the next sampled budget value; The last available occupancy position is written as the recalculation occupancy termination position; if the first sampled budget value has exceeded the remaining budget after deduction before deduction, the recalculation occupancy termination position is written to the previous sampled position of the subsequent occupancy start position; The sampling interval is the time difference between the current sampling time and the previous sampling time, and the daily operating price is the electricity price record corresponding to the current operating day of the target building; The air conditioner's advance start time is obtained by reverse reading the pre-cooling segment from S5-3: starting from the subsequent occupancy start position, search for the pre-cooling segment within the same air conditioner service boundary, and read the pre-cooling sample in order from the nearest to the farthest distance from the subsequent occupancy start position; The air conditioning power for each pre-cooling sample is multiplied by the sampling interval and then by the daily operating price to obtain the pre-cooling sample budget value, which is then deducted from the remaining budget after deductions. If the remaining budget before deduction is not lower than the current pre-cooling sampling budget value, then the pre-cooling sample is included in the deducted pre-cooling sample count; if the remaining budget is lower than the current pre-cooling sampling budget value, then reverse reading stops. The advance running time of the air conditioner is equal to the deducted pre-cooling sampling number multiplied by the sampling interval. The output building energy consumption operation decision results include the budget unit number, the remaining budget after deduction, the start and end positions of the recalculation occupation, the advance running time of the air conditioner, and the outstanding amount. After processing by S5, the budget revert record no longer stops at the cost allocation result, but continues to constrain the subsequent occupancy time and the early start time of the air conditioner; In the context of office building operations, when a tenant's meeting room usage is reverted to the pre-cooling budget, the system first deducts the reverted budget from the tenant's remaining budget, then calculates the subsequent affordable air conditioning operation budget based on the remaining budget, and finally obtains a new occupancy termination position. Meanwhile, the system reads pre-cooling samples backward from the start of the meeting, calculates the still manageable advance running time, and finally generates building energy consumption operation decision results that can be directly used for reservation adjustments and air conditioning start-stop plans.

[0022] exist Figure 1 It should be noted that the diagram illustrates the complete technical route of a building energy consumption operation decision-making method based on energy budget allocation. The overall approach starts with the operational data of a real estate building on the same operating day. First, in S1, observation rows and service sequences are generated according to the sampling time, ensuring that budget occupancy, air conditioning power, room temperature changes, space occupancy, and air conditioning terminal control addresses are all included in the same time-series calculation basis. Then, in S2, a hidden semi-Markov model algorithm is used to divide the service sequences into vacant, pre-cooling, margin maintenance, consumption, and stabilization states, outputting the pre-cooling and consumption segments. Next, in S3, a cooling chain is generated from the pre-cooling segment, and a warming chain is generated from the consumption segment. A dynamic time warping algorithm is then used to generate a transition chain, indicating which subsequent budget occupancy position actually consumes the temperature margin formed by pre-cooling. Then, in S4, a linear programming strategy optimization table is established based on the transition chain, and the budget rollback amount is obtained through simplex iteration, generating rollback records. Finally, in S5, the remaining budget is deducted based on the rollback records, the start and end positions of subsequent occupancy and the early running time of air conditioning are recalculated, and the building energy consumption operation decision results are output. The solid arrows in the diagram represent the main processing flow and data progression relationship, where the output of the previous stage serves as the input for the next stage. The solid lines pointing from S2 to the pre-cooling section, the surplus section, and then to the pairing of the cooling chain and the reheat chain represent the expansion relationship from the state segmentation results to the receiving calculation. The dashed arrows represent auxiliary explanations and feedback constraints. S5 points to the core logic explanation, indicating that the final operational decision result is used to verify whether the budget rollback target has been achieved. The core logic explanation then points to S1, indicating that subsequent operational days can continue to re-enter the observation row and service sequence generation process according to the same data structure, thus forming a continuous operational decision-making process for cross-time period temperature surplus acceptance and budget rollback.

[0023] Working principle: This solution first organizes the building operation data within the same operating day into observation rows according to the sampling time, so that budget occupancy, air conditioning power changes, room temperature changes, and space occupancy are flipped into the same service sequence; then, the hidden semi-Markov model algorithm is used to identify the pre-cooling segment and the consumption segment according to the operation sequence of vacancy, pre-cooling, margin maintenance, consumption, and stabilization; then, the dynamic time warping algorithm is used to sequentially pair the cooling chain of the pre-cooling segment with the warming chain of the consumption segment to obtain the receiving chain of which budget occupancy position takes over the temperature margin; finally, a linear programming strategy optimization table is established based on the receiving chain to solve and allocate the budget deduction of the pre-cooling segment among each return position, generate return records, and recalculate the subsequent occupancy start and end positions and the early running time of the air conditioner, so that the budget consumption generated by early pre-cooling no longer stays on the facility side or the power consumption time, but is returned to the budget unit of actual temperature margin consumption; For example, in the operation of office building conference rooms, the property management turns on the air conditioning in advance before the meeting starts to lower the temperature of the conference room. However, the actual consumption of the temperature margin is by the tenants who enter the conference room after the meeting has started. The system records the changes in air conditioning power, room temperature, and tenant occupancy at the sampling time. It first identifies the pre-cooling period before the meeting, and then identifies the temperature recovery period after people enter. It matches the temperature drop and temperature recovery to determine how much pre-cooling margin the tenant actually received. Then, the system transfers the corresponding pre-cooling budget from the original air conditioning energy consumption time to the tenant's budget, and recalculates the sustainable occupancy time of the meeting and the duration for which the air conditioning can be turned on in advance next time based on the remaining budget after deduction. This results in a building energy consumption operation decision that is more in line with the actual benefit relationship.

[0024] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A building energy consumption operation decision-making method based on energy budget allocation, characterized in that, include: S1. Obtain the operational data of the real estate building on the same operating day, write the changes in room temperature and occupancy caused by the budget occupancy and air conditioning power as observation rows according to the sampling time, and generate service sequences according to the air conditioning service boundaries; S2. The service sequence is processed by the hidden semi-Markov model algorithm. The state chain is established according to the order of cooling, heat preservation, consumption and stabilization after the space is vacant. The observation cost is obtained by adding the absolute value of the air conditioning power difference, the absolute value of the room temperature difference and the occupancy reversal value of the adjacent observation rows. The dwell cost is obtained by multiplying the state sampling number by the average value of the observation cost of the state segment. The pre-cooling segment and the consumption segment are output by Witte segment recursion. S3. For the precooling section and the waste section, generate cooling chain and warming chain according to the sampling order. Use dynamic time warping algorithm to recursively accumulate the absolute value of the temperature difference at the same position of the two chains, and generate the connecting chain by tracing back along the last accumulated cost. S4. Establish a linear programming strategy optimization table based on the support chain, take the budget deduction of the pre-cooling section as the amount to be re-attached, so that the amount allocated to the re-attached position is limited by the remaining budget and the total amount allocated is limited by the amount to be re-attached. The budget re-attached amount is obtained through simplex iteration and the re-attached record is generated. S5. Based on the reattachment record, deduct the remaining budget of the corresponding reattachment position of the receiving chain, recalculate the subsequent occupancy start and end positions and the early running time of the air conditioner according to the remaining budget after deduction, and output the building energy consumption operation decision results.

2. The building energy consumption operation decision-making method based on energy budget allocation according to claim 1, characterized in that: S1 includes: S1-1. Obtain the operation data of the real estate building on the same operation day, establish the operation row based on the sampling time, write the budget unit that the sampling time falls into the space occupancy start and end position into the budget occupancy position, and output the operation row with the budget occupancy position. S1-2. Based on the running row with budget occupancy bits, perform the subtraction of the previous value from the next value of the air conditioner power at adjacent sampling times, write the power difference into the corresponding running row, and output the power difference running row.

3. The building energy consumption operation decision-making method based on energy budget allocation according to claim 2, characterized in that: S1 also includes: S1-3. Based on the power difference, perform the subtraction of the previous value from the subsequent value of the room temperature at adjacent sampling times, and write the change of space occupancy from none to one or from one to none into the occupancy flip bit, and output the observation row. S1-4. Read the air conditioning terminal control address corresponding to the observation row, and concatenate the observation rows with the same control address in ascending order according to the sampling time to generate a service sequence.

4. The building energy consumption operation decision-making method based on energy budget allocation according to claim 3, characterized in that: S2 includes: S2-1. Read the service sequence, establish a chain table according to the sampling order, write the idle, pre-cooling, reserve maintenance, consumption and stabilization as incremental state numbers, stipulate that the current state number can only continue the current state number or the next state number, and delete the remaining continuation path in the cumulative cost table. S2-2. For each state number and the first and last positions of each group of segments, a candidate segment is formed. The state matching cost is calculated according to each observation row in the candidate segment. The empty segment corresponds to an empty budget occupancy bit and zero air conditioning power. The pre-cooling segment corresponds to an empty budget occupancy bit and negative room temperature difference. The margin maintenance segment corresponds to an empty budget occupancy bit and the absolute value of the room temperature difference is included in the cost. The surplus segment corresponds to a non-empty budget occupancy bit and positive room temperature difference. The stabilization segment corresponds to an empty occupancy flip bit and the absolute value of the room temperature difference is included in the cost.

5. The building energy consumption operation decision-making method based on energy budget allocation according to claim 4, characterized in that: S2 also includes: S2-3. Based on the candidate segment, the absolute value of the air conditioning power difference, the absolute value of the room temperature difference, the occupancy flip value and the state matching cost of each observation row in the segment are added together to obtain the observation cost. The sum of the observation costs is used as the dwell cost. The cumulative cost of the previous state number in the previous order of the segment is added to the dwell cost to obtain the candidate cumulative cost. S2-4. For candidate cumulative costs under the same state number and the same segment tail position, take the first one in ascending order of value and write it into the cumulative cost table, and write the corresponding segment head position and the previous state number into the predecessor table. S2-5. After writing the stabilization state number at the end of the chain position table, write the state number of each observation row back along the predecessor table in reverse order. Write the sampling sequence corresponding to the pre-cooling state number into the pre-cooling segment, and write the sampling sequence corresponding to the consumption state number into the consumption segment.

6. The building energy consumption operation decision-making method based on energy budget allocation according to claim 5, characterized in that: S3 includes: S3-1. Read the room temperature values ​​of adjacent observation rows in the pre-cooling section, subtract the next room temperature value from the previous room temperature value to generate the cooling share, write zero when the cooling share is negative, and write it into the cooling chain according to the sampling order. S3-2. Read the room temperature values ​​of adjacent observation rows within the surplus segment, subtract the previous room temperature value from the next room temperature value to generate the recovery share. Write zero when the recovery share is negative, and write the recovery share to the corresponding budget occupancy bit according to the sampling order.

7. The building energy consumption operation decision-making method based on energy budget allocation according to claim 6, characterized in that: S3 also includes: S3-3. Establish a regularization table with the chain position of the cooling chain as the regularization row and the chain position of the reheating chain as the regularization column. Write the absolute value of the difference between the cooling share and the reheating share in the current regularization cell as the cell cost. Then compare the cumulative costs of the source cells to the left, top, and top left of the current regularization cell in turn. Add the cumulative cost of the first source cell in ascending order to the cell cost and write it into the current regularization cell. S3-4. When writing the cumulative cost in the current regularized cell, write the row and column positions of the first source cell in ascending order to the backtrack position, and read backward from the last row and last column of the regularized table along the backtrack position to the first row and first column to generate a pairing path between the cooling chain and the warming chain. S3-5. Read the cooling share balance and the warming share balance bit by bit along the pairing path, write the first bit of the two in ascending order of value as the acceptance amount, and write the acceptance amount back to the budget occupancy bit corresponding to the current warming chain bit, and output the acceptance chain.

8. The building energy consumption operation decision-making method based on energy budget allocation according to claim 7, characterized in that: S4 includes: S4-1. Read the acceptance chain, accumulate the acceptance quantity corresponding to the same budget occupancy position to the total acceptance quantity of the corresponding budget occupancy position, and write the budget occupancy positions with a non-zero total acceptance quantity into the back-attached position table. S4-2. Read the back-hanging position table, establish a budget back-hanging amount variable for each back-hanging position, and limit the value range of the budget back-hanging amount variable to zero to the total amount accepted by the corresponding back-hanging position and the first value in the remaining budget.

9. A building energy consumption operation decision-making method based on energy budget allocation according to claim 8, characterized in that: S4 also includes: S4-3. Subtract the sum of each budget return variable from the pre-cooling section budget deduction to obtain the unreturned amount, and use the unreturned amount as the target variable of the simplex target row to generate the initial simplex table. S4-4. Perform simplex iteration in the initial simplex table. Select the column containing the negative test number in the target row as the infeed column. Select the right-hand side of the positive coefficient of the infeed column as the quotient obtained by dividing the positive coefficient of the infeed column by the positive coefficient of the infeed column as the outfeed row. After the outfeed row is normalized and the infeed column is eliminated, the updated simplex table is obtained until the negative test number in the target row is empty. S4-5. Read and update the simplex table, write the right-hand side quantity corresponding to the basic variable as the budgeted return amount of the corresponding return position, write the budgeted return amount corresponding to the non-basic variable as zero, and generate return records according to the return position and budgeted return amount.

10. A building energy consumption operation decision-making method based on energy budget allocation according to claim 9, characterized in that: S5 includes: S5-1. Read the back-up record, deduct the back-up amount from the remaining budget of the same budget occupancy position using the back-up position as the index. If the value after deduction is negative, write the remaining budget to zero and write the absolute value of the negative number to the arrears position. Output the deduction budget table. S5-2. Based on the deduction budget table, the service sequence is read by sampling according to the subsequent occupancy start position. The air conditioning power, sampling interval and daily operating price are multiplied to obtain the sampling budget value. The sampling budget value is deducted sequentially from the remaining budget. The last sampling position of the remaining budget before deduction that is not lower than the sampling budget value is written as the recalculation occupancy termination position. S5-3. Read the pre-cooling segment backward from the starting position of the subsequent occupation, multiply the air conditioning power, sampling interval and daily operating price of each pre-cooling sample to obtain the pre-cooling sampling budget value, and deduct the pre-cooling sampling budget value from the remaining budget digit by digit until the remaining budget is lower than the next pre-cooling sampling budget value, generate the air conditioning advance running time according to the deducted pre-cooling sampling number, and output the building energy consumption operation decision result.

Images