Energy management and control scheduling method and system

Abstract

The invention discloses an energy management and control scheduling method and system, and belongs to the technical field of power supply and distribution, and the method comprises the steps: setting a first time period, dividing the first time period into a plurality of second time periods, and enabling each second time period to comprise a plurality of sub time periods; predicting a first demand quantity of each sub-time period for the first energy, and generating a working sequence of a second time period; calculating a basic value for generating a second energy source when the target equipment operates in the second mode in the sub-time period, predicting a second demand quantity of each sub-time period for the second energy source, defining a target time period for the sub-time periods of which the second demand quantity is greater than the basic value and the sub-time periods of which the second demand quantity is greater than the basic value and which operate in the first mode, and calculating a storage amount before the target time period; and if the sum of the storage amount and the basic value is smaller than the second demand amount of the target time period, adjusting the mode before the target time period. The combined heat and power generation equipment can operate in a high-efficiency mode as much as possible, and the requirement of a user side for heat energy can be met.

Description

Technical Field

[0001] The present invention belongs to the technical field of power supply and distribution, and specifically relates to an energy management and dispatching method and system. Background Art

[0002] Cogeneration (CHP) is a technology that converts the chemical energy of fuel into both electricity and heat. It offers numerous advantages, including high energy efficiency and environmental protection. Compared to traditional coal-fired power generation, CHP generates electricity while also providing heat, significantly reducing emissions of carbon dioxide and other harmful gases, thus contributing to environmental protection.

[0003] Cogeneration is often used in conjunction with other energy supply methods, such as wind and solar energy, to ensure that electricity or heat is available to consumers. To improve the utilization of these resources, existing technologies have proposed technical solutions. For example, Chinese patent application "CN106532782B" discloses a method and device for optimizing the operation of a cogeneration unit to improve wind power utilization. This method establishes a heat-to-electricity output relationship model for the cogeneration unit to determine the unit's thermal output regulation range. Within this range, the method performs combined optimization of the heat and electricity outputs, outputting the optimal solution for the cogeneration unit's operation mode. This solution can improve wind power utilization.

[0004] The above solution, by incorporating constraints based on the building's own characteristics, reduces the CHP unit's processing power during certain time periods, thereby maximizing wind power generation and improving wind power utilization. However, since CHP equipment has a low resource utilization rate at low output, the economic benefits of the CHP equipment are poor. Summary of the Invention

[0005] To solve the above problems, the present invention provides an energy management and scheduling method and system to solve the problem in the prior art that resources cannot be efficiently utilized during cogeneration.

[0006] In order to achieve the above-mentioned object of the invention, the present invention proposes an energy management and scheduling method, comprising: Setting a first time period, dividing the first time period into a plurality of second time periods, each second time period including a plurality of sub-time periods; predicting a first demand for the first energy source in each sub-time period of the second time period, and generating an operation sequence for the second time period based on the first demand, wherein the target device operates in a first mode in the sub-time period when the first demand is less than a critical threshold, and operates in a second mode in the sub-time period when the first demand is greater than or equal to the critical threshold; Calculate the basic value of the second energy generated when the target device operates in the second mode during the sub-time period, predict the second demand for the second energy in each sub-time period during the second time period, define the target time periods for those sub-time periods where the second demand is greater than the basic value and for those sub-time periods operating in the first mode, and calculate the storage amount before the k-th target time period based on the first formula , the first formula is: , where x is the basic value, P is the storage amount of the second energy at the start of the second time period 1, is the second demand for the n-th sub-time period, is the loss coefficient; If the sum of the storage amount and the basic value is less than the second demand for the k-th target time period, it is determined that there is an energy shortage in the target time period, and the mode before the k-th target time period is adjusted.

[0007] Further, the mode before the k-th target time period is adjusted based on the following steps: Define the sub-time periods before the k-th target time period as adjustment time periods, and calculate the adjustment value for the m-th adjustment time period before the k-th target time period based on the second formula , the second formula is: , where g is the critical threshold, is the second demand for the k-th target time period, is the preset conversion coefficient; Adjust the mode of the adjustment time period based on the basic value. Among them, if the first demand for the adjustment time period is less than the basic value, it operates in the first mode; if it is greater than or equal to the first demand, it operates in the second mode.

[0008] Further, after completing the adjustment of all work sequences, the following steps are also included: Calculate the overflow amount of the second energy for the a-th work sequence based on the third formula , the third formula is: , where b is the number of times the second mode appears in the a-th work sequence, and y is the sum of the second demands for each sub-time period within the second time period a; Accumulate the overflow amounts of each working sequence and the storage amount of the second energy at the start of the first time period in sequence to obtain the cumulative values obtained from each accumulation. Set the storage space for storing the second energy. During the accumulation process, if the cumulative value is greater than the storage space, obtain the second time period in which the storage amount has been accumulated, delete the second time period that already includes the adjustment time period, and define the remaining second time period as the overflow time period; Calculate the evaluation value of each overflow time period based on the fourth formula , and the fourth formula is: , where and are the third weight and the fourth weight respectively, i is the number of the second modes in the working sequence of the overflow time period, j is the number of consecutive second modes in the working sequence of the overflow time period. Locate the overflow time period with the highest evaluation value and reduce the number of the second modes in the overflow time period; After the adjustment is completed, recalculate and accumulate the storage amounts of the second energy for each working sequence until the cumulative value during the accumulation process is not greater than the storage space. Integrate all the finally generated working sequences into the optimal working mode for the first time period.

[0009] Furthermore, after experiencing multiple first time periods, store the working sequences included in each optimal working mode in the scheduling database, and label each stored working sequence with a first label, a second label, and a third label. The first label is the storage amount before the start of the working sequence, the second label is the date type of the working sequence, and the third label is the generation amount of the second energy in the working sequence; At the start of a new second time period, obtain the first search result. The first search result includes multiple working sequences, and the first label of the working sequence is the same as the current storage amount, and the second label is the same as the date type of the second time period. Obtain the working sequences in the first search result whose generation amount is greater than the sum of the second demand amounts in the second time period as the second search result. Finally, screen out the working sequences without energy shortage as the target sequences for use. If there is no target sequence, generate it in real time according to the first demand amount and the second demand amount.

[0010] Furthermore, predict the first demand amount of the sub-time period based on the following steps: Obtain historical data consistent with the current date type, extract the first electricity consumption data identical to the k-th sub-time period and the second electricity consumption data of the k - 1-th sub-time period from the historical data, and calculate the first demand amount of the k-th sub-time period based on the sixth formula , and the sixth formula is: , where is the first demand quantity in the current (k - 1)-th sub-time period and are respectively the first demand quantities in the k-th and (k - 1)-th sub-time periods in the z-th historical data, and Z is the quantity of the historical data.

[0011] The present invention also provides an energy management and scheduling system, which is used to implement the above-mentioned energy management and scheduling method. The system includes: A setting module, which is used to set a first time period, divide the first time period into N second time periods, and each second time period includes multiple sub-time periods; A plan generation module, which is used to predict the first demand quantity of the first energy in each sub-time period in the second time period, generate a working sequence of the second time period based on the first demand quantity. In the working sequence, the target device operates in a first mode in the sub-time periods where the first demand quantity is less than the critical threshold, and operates in a second mode in the sub-time periods where the first demand quantity is greater than or equal to the critical threshold; A calculation module, which is used to calculate the basic value of generating the second energy when the target device operates in the second mode in the sub-time period, predict the second demand quantity of the second energy in each sub-time period in the second time period, define the sub-time periods where the second demand quantity is greater than the basic value and the sub-time periods operating in the first mode as target time periods, and calculate the storage quantity before the k-th target time period based on the first formula , and the first formula is: , where x is the basic value, P is the storage quantity of the second energy at the start of the second time period, is the second demand quantity in the n-th sub-time period, is the loss coefficient; An adjustment module. If the sum of the storage quantity and the basic value is less than the second demand quantity in the k-th target time period, it is determined that there is an energy shortage in the target time period, and the mode before the k-th target time period is adjusted.

[0012] Compared with the prior art, the beneficial effects of the present invention are at least as follows: The present invention predicts the demand for electric energy in each sub-time period, and by setting a critical threshold value of electric energy, it can be determined according to the critical threshold value which sub-time period will operate inefficiently and which sub-time period will operate efficiently, so that an initial operation plan can be generated; thereafter, according to the demand for thermal energy in each sub-time period, combined with the storage capacity of the thermal energy storage device and the thermal energy generated in each sub-time period, it is calculated which sub-time periods will have thermal energy shortages, so that the initial operation plan is adjusted again according to the situation; so that the finally generated operation plan improves the resource utilization efficiency of the equipment as much as possible while satisfying the sufficient thermal energy supply.

[0013] The present invention subdivides the first time period into multiple second time periods, shortening the time length and facilitating the subsequent generation of a calculation and adjustment work sequence; the second time period is divided into multiple sub-time periods. On the one hand, a more detailed division can improve the accuracy of subsequent predictions of future demand. On the other hand, since the lengths of the sub-time periods are the same, the electrical energy and thermal energy generated in each sub-time period are fixed, which can reduce the subsequent amount of calculations. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 This is a flow chart of the steps of energy management and scheduling of the present invention; Figure 2 This is a system structure diagram of energy management and scheduling according to the present invention. DETAILED DESCRIPTION

[0015] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0016] It is understood that the terms "first," "second," etc., used herein may be used to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish a first element from another element. For example, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script without departing from the scope of this application.

[0017] like Figure 1 As shown, an energy management and scheduling method includes: Step S1: Set a first time period, divide the first time period into multiple second time periods, and each second time period includes multiple sub-time periods.

[0018] Specifically, the first time period is set to seven days here, that is, from Monday to Sunday. Then, taking one day as a unit, the first time period is further divided into seven second time periods, and each second time period includes 24 sub-time periods, that is, the length of each sub-time period is 1 hour.

[0019] Step S2: Predict the first demand for the first energy in each sub-time period of the second time period, and generate a working sequence for the second time period based on the first demand. In the working sequence, the target device operates in the first mode in the sub-time periods where the first demand is less than the critical threshold, and operates in the second mode in the sub-time periods where the first demand is greater than or equal to the critical threshold.

[0020] Specifically, taking the prediction of the second time period 1 as an example for illustration, the target device is a device used to generate the first energy and the second energy in cogeneration. The first energy in this embodiment is electric energy, and the second energy is thermal energy. In other embodiments, the first energy can also be thermal energy, and the second energy is electric energy. Then, based on the length of the sub-time period and combined with the parameters of the target device, the basic value of the thermal energy generated when the target device operates in the second mode can be calculated. The first mode is a mode in which the target device operates with low efficiency, and the electric energy and thermal energy output are relatively low, which is ignored in this embodiment. The second mode is a high-efficiency operation mode, which generates more electric energy and thermal energy. Particularly, a thermal energy storage device is also provided in this embodiment, and the thermal energy storage device is used to store the excess thermal energy generated by the target device. An electric energy storage device can also be provided in other embodiments.

[0021] The critical threshold is a preset value. In this embodiment, the first demand for electric energy per hour in the second time period 1 is predicted, and the prediction method will be introduced in detail later. A working sequence 1 is generated according to the magnitude relationship between the critical threshold and the first demand. When the first demand is less than the critical threshold, the target device operates with low efficiency, and other power generation methods are used to meet the power supply demand, so as to improve the utilization rate of wind power generation and solar wind power generation; when the first demand is greater than or equal to the critical threshold, the target device needs to operate with high efficiency. If the demand is still not met, other power supply devices can be further combined to meet the power supply demand. Through this step, the target device only operates with high efficiency when the demand for electric energy is relatively large.

[0022] The working sequence 1 in this embodiment is 1122···11, which means that the target device operates in the first mode in the first hour and the second hour, and operates in the working mode 2 in the third hour and the fourth hour.

[0023] Step S3: Calculate the basic value of the second energy generated when the target device operates in the second mode within a sub-time period, predict the second demand for the second energy in each sub-time period of the second time period, define the target time periods for those with the second demand greater than the basic value and the sub-time periods operating in the first mode, and calculate the storage amount before the k-th target time period based on the first formula , and the first formula is: , where x is the basic value, P is the storage amount of the second energy at the start of the second time period 1, is the second demand for the n-th sub-time period, is the loss coefficient.

[0024] Step S4: If the sum of the storage amount and the basic value is less than the second demand for the k-th target time period, it is determined that there is an energy shortage in the target time period, and the mode before the k-th target time period is adjusted.

[0025] The method for predicting the second demand is the same as that for predicting the first demand. After generating Work Sequence 1, first obtain the time periods where the basic value is less than the second demand, and the sub-time periods operating in the first mode, because the thermal energy generated in the sub-time periods operating in the first mode must be less than the second demand therein. After screening out the target time periods, calculate the storage amount for each target time period through the first formula. The storage amount is the amount of thermal energy already stored in the thermal energy storage device at the start of the target time period; for example, when calculating the storage amount for Target Time Period 3 in the second time period 1, k = 3, first obtain the initial cumulative storage amount at the start of the second time period 1. Since two time periods have been run before Target Time Period 3, the total amount of thermal energy generated and stored by the target device before Target Time Period 3 is obtained through 2*x + P, subtract the predicted consumption of the second demand in the previous two time periods, and then subtract the loss during thermal energy storage, and the remaining storage amount of the thermal energy storage device at the start of the 3rd target time period can be obtained.

[0026] If the sum of the storage amount and the basic value is greater than the second demand for thermal energy in Target Time Period 3, then even if the basic value is less than the second demand, the heat in the thermal energy storage device can be called for supplementary supply; conversely, if the sum of the two is less than the second demand, it indicates that even if the heat in the thermal energy storage device is called for supplementary supply, it cannot meet the demand for thermal energy in Target Time Period 3. At this time, the work sequences in Target Time Period 1 and Target Time Period 2 need to be adjusted, that is, by adjusting the work mode in the previous two time periods, so that enough heat can be accumulated in the 3rd target time period to supplement the part of the difference between the second demand and the basic value. After the adjustment is completed, continue to adjust the next target time period.

[0027] After finishing the adjustment of the working sequence 1, continue to adjust the working sequence 2 corresponding to the second time period 2 until the adjustment of the working sequence 7 is completed. Finally, before running, by predicting the future demand for electric energy and thermal energy, the optimal working mode for the next week can be obtained.

[0028] The present invention predicts the demand for electric energy in each sub-time period, and by setting the critical threshold of electric energy, it can be determined in which sub-time period the operation is inefficient and in which sub-time period the operation is efficient according to the critical threshold, so that an initial operation plan can be generated; then, according to the demand for thermal energy in each sub-time period, combined with the storage capacity of the thermal energy storage device and the amount of thermal energy generated in each sub-time period, it is calculated in which sub-time periods there will be a shortage of thermal energy, and thus the initial operation plan is adjusted again according to the situation; so that the finally generated operation plan can improve the resource utilization efficiency of the device as much as possible while ensuring sufficient thermal energy supply.

[0029] The present invention divides the first time period into multiple second time periods, shortening the time length, which is convenient for subsequent generation of adjusted working sequences; divides the second time period into multiple sub-time periods. On the one hand, more detailed division can improve the accuracy of future demand prediction, and on the other hand, since the length of each sub-time period is the same, the electric energy and thermal energy generated in each sub-time period are fixed, which can reduce the subsequent calculation amount.

[0030] It should be particularly noted that through the above technical solutions, the present invention not only enables the cogeneration equipment to operate in a high-efficiency mode as much as possible, but also can meet the demand for thermal energy at the user end.

[0031] In this embodiment, the mode before the kth target time period is adjusted based on the following steps: Define the sub-time period before the kth target time period as the adjustment time period, and calculate the adjustment value of the mth adjustment time period before the kth target time period based on the second formula , and the second formula is: , where g is the critical threshold, is the second demand of the kth target time period, is the preset conversion coefficient; Adjust the mode of the adjustment time period based on the basic value. Among them, if the first demand of the adjustment time period is less than the basic value, it operates in the first mode, and if it is greater than or equal to the first demand, it operates in the second mode.

[0032] Specifically, if the target time period 4 is adjusted, then the target time periods 1, 2, and 3 are adjustment time periods, which are defined here as adjustment time period 1, adjustment time period 2, and adjustment time period 3. The following explains the second formula. In the second formula, the units of thermal energy and electrical energy are both energy units, i.e., kilowatt-hours; by calculating how much more energy is needed to meet the thermal energy gap of the target time period 4. Since there is energy loss during the storage of thermal energy, a conversion coefficient is multiplied to expand the value. The conversion coefficient can be set according to the actually measured loss ratio; m is the interval between the adjustment time period itself and the target time period. For example, the interval m between adjustment time period 1 and target time period 4 is 4 - 1 = 3. It can be inferred that the smaller the number of the adjustment time period, the closer the obtained adjustment value is to the original critical threshold.

[0033] After changing the critical threshold of each sub-time period after calculation to the adjustment value, adjustment time period 3 is the time period closest to target time period 4, so its adjustment value is the smallest. Adjustment time period 1 is the time period farthest from target time period 4, so its adjustment value is the largest. Then, when comparing the first demand and the adjustment value, the adjustment time period closer to target time period 4 is more likely to be adjusted from the first mode to the second mode. The advantage of this solution is that it can avoid accumulating heat prematurely and reduce heat loss during the storage process. It should be noted that if the thermal energy demand of target time period 4 still cannot be met after adjustment, other heating equipment is needed for support. If a certain sub-time period is adjusted from the first mode to the second mode, the electrical energy output of other equipment needs to be correspondingly reduced.

[0034] In this embodiment, after completing the adjustment of all work sequences, the following steps are further included: Calculating the overflow of the second energy of the a-th work sequence based on the third formula , and the third formula is: , where b is the number of times the second mode appears in the a-th work sequence, and y is the sum of the second demands of each sub-time period within the second time period a.

[0035] Specifically, assume that the calculation target is the second time period 2, which corresponds to work sequence 2. Work sequence 2 has 24 sub-time periods, and there are 10 second modes among them. Then b = 10. Through the third formula, it can be calculated whether there will be energy overflow in each work sequence. Particularly, the overflow can be positive or negative.

[0036] Cumulatively add the overflow amounts of each working sequence and the storage amount of the second energy at the start of the first time period to obtain the cumulative value obtained from each addition. Set the storage space for storing the second energy. During the accumulation process, if the cumulative value is greater than the storage space, obtain the second time period with the already accumulated storage amount, delete the second time periods that already include the adjustment time period, and the remaining second time periods are defined as the overflow time periods.

[0037] Suppose the storage amount of the second energy at the start of the first time period is 10, the storage space is 20, and the overflow amounts of working sequences 1, 2, and 3 are -3, 8, and 6 respectively. From the accumulation process, it can be seen that when adding the overflow amount of working sequence 3, it exceeds the storage space, and the time periods that have participated in the accumulation are the second time periods 1, 2, and 3. Among them, since there is an energy shortage time period, that is, the adjustment time period, in the second time period 1, it is therefore excluded, and the remaining second time periods 2 and 3 are defined as the overflow time periods.

[0038] Calculate the evaluation value of each overflow time period based on the fourth formula , and the fourth formula is: , where and are the third weight and the fourth weight respectively, i is the number of the second modes in the working sequence of the overflow time period, j is the number of consecutive second modes in the working sequence of the overflow time period. Locate the overflow time period with the highest evaluation value and reduce the number of the second modes in the overflow time period.

[0039] The following explains the fourth formula. The fourth formula scores based on the number of the second modes in the working sequence and the number of consecutive second modes. The number of consecutive second modes refers to the number of consecutive occurrences of the second mode. If the working sequence is 12221, then the number of consecutive second modes is 3; the more the number of the second modes, the more heat energy generated by this working sequence. Reducing the number of the second modes in such a working sequence has a greater operating space. And the larger the number of consecutive second modes, such as 22221, if it is adjusted to 12121, the original stable working mode will be changed to a fluctuating working mode, which will cause the device to switch frequently. Therefore, try not to adjust such a working sequence. After determining the working sequence to be adjusted, in this embodiment, first change the last second mode in the working sequence to the first mode. If this mode cannot be adjusted due to actual on-site restrictions, or if there is still an overflow after adjustment, continue to adjust the penultimate second mode until there is no overflow. After the second mode is changed to the first mode, the corresponding power gap is supplied by other power equipment.

[0040] After the adjustment is completed, recalculate the storage amount of the second energy for each work sequence and accumulate it until the accumulated value does not exceed the storage space during the accumulation process. Integrate all the finally generated work sequences into the optimal working mode for the first time period.

[0041] It should be specifically noted that this step is not contradictory to the above adjustment of the first mode to the second mode. Because the energy overflow is the result of long-term accumulation, if there is an energy shortage, the stored thermal energy will be used, and thus there will be no situation of energy overflow.

[0042] After experiencing multiple first time periods, store the work sequences included in each optimal working mode in the scheduling database, and label each stored work sequence with a first label, a second label, and a third label. The first label is the storage amount before the start of the work sequence, the second label is the date type of the work sequence, and the third label is the generation amount of the second energy in the work sequence.

[0043] Specifically, the optimal working mode includes multiple work sequences. When storing, label each work sequence with a first label and a second label. The first label is the storage amount before the start of the work sequence. For example, when work sequence 2 is being executed and there is 10 kwh of energy in the thermal energy storage device, the first label of work sequence 2 is 10, and the second label is, for example, January, Monday. The generation amount of the third label can be determined by the product of the number of the second mode and the base value.

[0044] At the start of a new second time period, obtain the first search result. The first search result includes multiple work sequences, and the first label of the work sequence is the same as the current storage amount, and the second label is the same as the date type of the second time period. Obtain the work sequences in the first search result whose generation amount is greater than the sum of the second demands of the second time period as the second search result. Finally, screen out the work sequences without energy shortage as the target sequences for use. If there are no target sequences, generate them in real time according to the first demand and the second demand.

[0045] For example, if you want to generate the optimal working mode for Monday in January currently, first retrieve the work sequences of the first sub-time period. First, obtain the storage amount at the start of the second time period, retrieve the first label that is the same as this storage amount, and extract the work sequences including the second label of Monday in January from this, as the first search result. Then calculate the second demand for the second energy in the first sub-time period, and obtain the work sequences whose second energy generation amount is greater than the second demand as the second search result; then, based on the demand for the second energy in each sub-time period of the first sub-time period, verify whether there is an energy shortage in each second search result. The verification method can refer to step S3 and step S4, and use the work sequences with energy shortage as the target sequences. If no target sequences are obtained, regenerate the optimal working mode according to the above steps.

[0046] Since the demand for electric energy and the demand for heat energy generally do not fluctuate greatly on the same date and time period, the working sequence retrieved in this way generally can also meet the supply of electric energy. If not, it will be appropriately improved according to the actual situation and then used, thus reducing the subsequent calculation amount.

[0047] In this embodiment, the first demand for a sub-time period is predicted based on the following steps: Obtain historical data of the same type as the current date, extract the first electricity consumption data identical to the k-th sub-time period and the second electricity consumption data of the (k - 1)-th sub-time period from the historical data, and calculate the first demand for the k-th sub-time period based on the sixth formula The sixth formula is: where, is the first demand for the current (k - 1)-th sub-time period, 、 are respectively the first demands for the k-th and (k - 1)-th sub-time periods in the z-th historical data, and Z is the number of historical data.

[0048] Specifically, for example, to predict the demand for electric energy from 15:00 to 16:00 on Monday. Now the predicted demand for electric energy from 14:00 to 15:00 on Monday is known, and here it is defined as data 1. Then obtain the actual consumption of electric energy from 14:00 to 15:00 and from 15:00 to 16:00 on each Monday in the past 4 weeks, which are respectively defined as data 2 and data 3. Calculate the difference between adjacent data 2 and data 3, and obtain the average value, so as to obtain the increment trend of the electricity quantity between 14:00 to 15:00 and 15:00 to 16:00. Then add the increment trend to data 1 to obtain the first demand for 14:00 to 15:00 to be predicted; when predicting the demand for electric energy from 16:00 to 17:00, add the increment trend between 15:00 to 16:00 and 16:00 to 17:00 obtained to the first demand for 14:00 to 15:00 obtained before.

[0049] As Figure 2 shown, the present invention also provides an energy management and dispatching system, which is used to implement the above-mentioned energy management and dispatching method. The system includes: A setting module, configured to set a first time period, divide the first time period into N second time periods, and each second time period includes multiple sub-time periods; A plan generation module, configured to predict a first demand for a first energy in each sub-period of a second period, generate a work sequence for the second period based on the first demand. In the work sequence, the target device operates in a first mode in sub-periods where the first demand is less than a critical threshold, and operates in a second mode in sub-periods where the first demand is greater than or equal to the critical threshold; A calculation module, configured to calculate a basic value of generating a second energy when the target device operates in the second mode in a sub-period, predict a second demand for the second energy in each sub-period of the second period, define target periods as those where the second demand is greater than the basic value and the sub-periods operating in the first mode, and calculate the storage amount before the k-th target period based on a first formula The first formula is: where x is the basic value, P is the storage amount of the second energy at the start of the second period, is the second demand for the n-th sub-period, is the loss coefficient; An adjustment module, if the sum of the storage amount and the basic value is less than the second demand for the k-th target period, determines that there is an energy shortage in the target period and adjusts the mode before the k-th target period.

[0050] It should be understood that although the steps in the flowcharts of the embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed sequentially in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least some of the steps in each embodiment may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same moment, but can be executed at different moments. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or sub-steps or stages of other steps.

[0051] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The above program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in this application can include non-volatile and / or volatile memories. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0052] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0053] The above embodiments only represent several implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention should be subject to the appended claims.

[0054] The above is only the preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An energy management and scheduling method, characterized in that: include: Setting a first time period, dividing the first time period into a plurality of second time periods, each second time period including a plurality of sub-time periods; predicting a first demand for the first energy source in each sub-time period of the second time period, and generating an operation sequence for the second time period based on the first demand, wherein the target device operates in a first mode in the sub-time period when the first demand is less than a critical threshold, and operates in a second mode in the sub-time period when the first demand is greater than or equal to the critical threshold; Calculate the base value of the second energy generated by the target device when it operates in the second mode within the sub-time period, predict the second demand for the second energy in each sub-time period in the second time period, define the sub-time period in which the second demand is greater than the base value and operates in the first mode as a target time period, and calculate the storage capacity before the kth target time period based on the first formula , the first formula is: , where x is the base value, and P is the storage amount of the second energy at the beginning of the second time period 1, is the second demand in the nth sub-time period, is the loss coefficient; If the storage If the sum of the second demand and the basic value is less than the second demand in the kth target time period, it is determined that energy shortage occurs in the target time period, and the mode before the kth target time period is adjusted.

2. The energy management and scheduling method according to claim 1, characterized in that: The pattern before the k-th target time period is adjusted based on the following steps: The sub-time period before the k-th target time period is defined as an adjustment time period, and the adjustment value of the m-th adjustment time period before the k-th target time period is calculated based on the second formula: , the second formula is: , where g is the critical threshold, is the second demand in the kth target time period, is the preset conversion factor; The mode of the adjustment time period is adjusted based on the basic value, wherein if the first demand in the adjustment time period is less than the basic value, the system operates in the first mode; if it is greater than or equal to the first demand, the system operates in the second mode.

3. The energy management and scheduling method according to claim 2, characterized in that: After completing the adjustment of all work sequences, the following steps are also included: Calculate the overflow of the second energy in the ath working sequence based on the third formula , the third formula is: , where b is the number of times the second mode appears in the a-th working sequence, and y is the sum of the second demand quantities in each of the sub-time periods in the second time period a; The overflow amount of each working sequence and the storage amount of the second energy at the beginning of the first time period are sequentially accumulated, an accumulated value obtained in each accumulation is obtained, and a storage space for storing the second energy is set. During the accumulation process, if the accumulated value is greater than the storage space, a second time period in which the storage amount has been accumulated is obtained, the second time period in which the adjustment time period is included is deleted, and the remaining second time period is defined as the overflow time period; The evaluation value of each overflow time period is calculated based on the fourth formula: , the fourth formula is: ,in, and are the third weight and the fourth weight respectively, i is the number of the second modes in the overflow time period working sequence, j is the number of the second modes in consecutive positions in the overflow time period working sequence, the overflow time period with the highest evaluation value is located, and the number of the second modes in the overflow time period is reduced; After the adjustment is completed, the storage amount of the second energy of each working sequence is recalculated and accumulated until the accumulated value is not greater than the storage space during the accumulation process, and all the working sequences finally generated are integrated into the optimal working mode for the first time period.

4. The energy management and scheduling method according to claim 3, characterized in that: After a plurality of first time periods, the work sequences included in each optimal work mode are stored in a scheduling database, and each stored work sequence is labeled with a first tag, a second tag, and a third tag, wherein the first tag is a storage amount before the start of the work sequence, the second tag is a date type of the work sequence, and the third tag is a generated amount of the second energy in the work sequence; At the beginning of a new second time period, a first search result is obtained, which includes multiple work sequences, and the first label of the work sequence is the same as the current storage amount, and the second label is the same as the date type of the second time period. In the first search result, a work sequence whose generation amount is greater than the sum of the second demand amount in the second time period is obtained as the second search result. Finally, a work sequence without energy shortage is screened out for use as a target sequence. If there is no target sequence, it is generated in real time according to the first demand amount and the second demand amount.

5. The energy management and scheduling method according to claim 1, characterized in that: The first demand quantity in the sub-time period is predicted based on the following steps: Obtain historical data consistent with the current date type, extract the first power consumption data that is the same as the kth sub-time period and the second power consumption data of the k-1th sub-time period from the historical data, and calculate the first demand of the kth sub-time period based on the sixth formula , the sixth formula is: ,in, is the first demand quantity in the current k-1th sub-time period, 、 are respectively the first demand quantities of the kth and k-1th sub-time periods in the zth historical data, and Z is the number of the historical data.

6. An energy management and scheduling system, used to implement an energy management and scheduling method according to any one of claims 1 to 5, characterized in that: include: A setting module, configured to set a first time period, divide the first time period into N second time periods, each second time period including a plurality of sub-time periods; a plan generating module, configured to predict a first demand for a first energy source in each sub-time period of a second time period, and generate an operation sequence for the second time period based on the first demand, wherein the target device operates in a first mode in the sub-time period when the first demand is less than a critical threshold, and operates in a second mode in the sub-time period when the first demand is greater than or equal to the critical threshold; a calculation module configured to calculate a base value of the second energy generated by the target device when the target device operates in the second mode within the sub-time period, predict a second demand for the second energy in each sub-time period within the second time period, define the sub-time period in which the second demand is greater than the base value and operates in the first mode as a target time period, and calculate the storage capacity before the kth target time period based on the first formula; , the first formula is: , where x is the base value, and P is the storage amount of the second energy at the beginning of the second time period, is the second demand in the nth sub-time period, is the loss coefficient; Adjust the module, if the storage If the sum of the second demand and the basic value is less than the second demand in the kth target time period, it is determined that energy shortage occurs in the target time period, and the mode before the kth target time period is adjusted.

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