Energy storage system and method for storing energy by using waste heat

Abstract

The invention discloses an energy storage system and method for storing energy by using waste heat, and relates to the technical field of waste heat power generation, and the method comprises the steps: obtaining an operation parameter of each energy storage link through calling a historical energy storage record, and determining an energy conversion rate threshold value of each energy storage process according to the numerical value condition of the operation parameter; screening abnormal records, calculating change rates of operation parameters in the abnormal records, determining the abnormal change rates, and determining characteristic parameters of the energy storage process according to the quantity condition of the abnormal change rates; counting feature records, calculating feature scores of sampling time periods in the feature records, and constructing a feature curve graph of the energy storage process; and drawing a real-time characteristic curve graph of the energy storage process, calculating the system score of the energy storage system by combining the characteristic curve graph of the energy storage process, and judging the early warning state according to the conditions of the system score and the system score threshold, thereby improving the stability of the system.

Description

Technical Field

[0001] The present invention relates to the technical field of waste heat power generation, and in particular to an energy storage system and method for storing energy using waste heat. Background Art

[0002] At present, the world's energy structure is still dominated by fossil energy. The electricity sources in most regions mainly rely on the combustion of fossil energy. The carbon dioxide emitted by the combustion of fossil fuels is the main source of greenhouse gases. Due to technical limitations, the utilization rate of fossil energy is not high at present, which also causes damage to the environment. With the progress of society, humans can improve the overall energy utilization efficiency by recycling and utilizing the waste heat generated by the combustion of fossil energy, converting the heat energy that would otherwise be wasted into electrical energy, thereby reducing the demand for fossil fuels, thereby reducing the emission of greenhouse gases such as carbon dioxide, and promoting environmental protection and sustainable development; Waste heat energy storage uses waste heat to melt metal salts to electrolyze elemental metals, and then uses the elemental metals and air to form metal-air batteries to generate electricity, forming an electrolysis-power generation cycle to achieve efficient use of waste heat. However, during the electrolysis and power generation process, the conversion rate will fluctuate. If the conversion rate drops, the system will be adjusted, which will affect the overall performance. Therefore, how to determine whether the system needs to be adjusted becomes the key to ensuring the efficiency of the waste heat energy storage system, avoiding energy waste or excessive load, and improving the stability of the system. Summary of the invention

[0003] The object of the present invention is to provide an energy storage system and method for storing energy using waste heat, so as to solve the problems raised in the prior art.

[0004] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for storing energy using waste heat, the method comprising: Step S100: In different energy storage links, corresponding sensors are arranged to monitor the operating parameters of the energy storage links, and the operating parameters of each energy storage link are obtained by retrieving historical energy storage records. According to the numerical conditions of the operating parameters, the energy conversion rate threshold of each energy storage process is determined; Step S200: screening abnormal records, calculating the change rate of the operating parameters in the abnormal records, determining the abnormal change rate, and determining the characteristic parameters of the energy storage process according to the quantity of the abnormal change rate; Step S300: Counting feature records, calculating feature scores of sampling time periods in the feature records, and constructing a feature curve diagram of the energy storage process by calculating the average feature score of the sampling time periods; Step S400: draw a real-time characteristic curve diagram of the energy storage process, calculate the system score of the energy storage system in combination with the characteristic curve diagram of the energy storage process, and determine the warning state according to the system score and the system score threshold.

[0005] Furthermore, step S100 includes: Step S101: setting two adjacent energy storage links with correlation as an energy storage process, wherein the correlation is that the energy and material output by the previous energy storage link is directly used as the input of the next energy storage link, and setting the previous energy storage link in the energy storage process as the first link, and the next energy storage link as the second link; obtaining a historical energy storage record of a certain energy storage process, and obtaining the value of each operating parameter corresponding to all links in the energy storage process in a certain historical energy storage record; Step S102: Obtain the difference between the operating parameters of a link before and after operation, and calculate the equivalent energy of a link according to the following formula: ; Among them, E represents the equivalent energy of a certain link, A a It is expressed as the difference of the ath operating parameter, It is represented as the weight of the ath operating parameter, and b is represented as the total number of operating parameters in a certain link; Step S103: Obtain the equivalent energy of all links in the energy storage process, and calculate the energy conversion rate of a certain energy storage process according to the following energy conversion rate formula: ; Wherein, N represents the energy conversion rate of a certain energy storage process, E1 represents the equivalent energy of the first link in a certain energy storage process, and E2 represents the equivalent energy of the second link in a certain energy storage process; Step S104: Obtain the energy conversion rates of all historical energy storage records in a certain energy storage process, obtain the average value of the energy conversion rate as c and the standard deviation as d, and calculate the energy conversion rate threshold of a certain energy storage process according to the following formula: P=c+d*e; Wherein, P represents the energy conversion rate threshold, and e represents a preset constant; The waste heat energy storage system includes electrolysis and metal power generation, and the operating parameters include temperature, metal weight, etc. By calculating the equivalent energy of each energy storage link, the impact of operating parameters on link performance can be quantified, and quantitative analysis of the performance of a single link in the energy storage system can be achieved; by setting a reasonable energy conversion rate threshold, the process operation status can be monitored, providing data support for subsequent analysis.

[0006] Further, step S200 includes: Step S201: comparing the energy conversion rates of all historical energy storage records in a certain energy storage process with the energy conversion rate threshold of the energy storage process, setting the historical energy storage records below the energy conversion rate threshold as abnormal records, and summarizing the abnormal records of a certain energy storage process; Step S202: In a set of abnormal records of a certain energy storage process, the value of the qth operating parameter at the tth sampling time point in a certain abnormal record is obtained as Q (q, t), and an operating curve diagram of the qth operating parameter in the abnormal record is drawn. The operating curve diagram takes the sampling time point as the abscissa and the value of the operating parameter as the ordinate. The change rate of the operating parameter in a certain sampling time period is calculated according to the following formula: ; Where R(q, t') represents the rate of change of the qth operating parameter in the t'th sampling time period, Q(q, t+1) represents the value of the qth operating parameter at the t+1th sampling time point, It is expressed as the time interval of the t'th sampling period; Step S203: setting a change rate threshold of a certain operating parameter, comparing each change rate of a certain operating parameter in a certain abnormal record with the change rate threshold of the operating parameter, and if the change rate threshold is not met, setting the change rate as an abnormal change rate; Step S204: Count the number of abnormal change rates of a certain operating parameter in all abnormal records of a certain energy storage process as B, obtain the total number of abnormal change rates in a certain energy storage process as D, and calculate the occurrence frequency of the abnormal change rate of a certain operating parameter as B / D; Step S205: setting an occurrence frequency threshold, comparing the occurrence frequency of a certain operating parameter with the occurrence frequency threshold, and if it exceeds the occurrence frequency threshold, setting the operating parameter as a characteristic parameter; By setting the energy conversion rate threshold, abnormal energy storage records with low energy conversion efficiency can be effectively screened out, thereby improving the accuracy of abnormal data identification; Calculate the change rate of operating parameters and set the change rate threshold to achieve quantitative determination of abnormal change rate, which helps to more accurately identify abnormal operation status of equipment. By counting the number and frequency of abnormal change rates, it can fully reflect the severity and distribution of abnormal conditions, thus supporting more comprehensive abnormal analysis. Based on the frequency threshold of the abnormal change rate, it can automatically identify key parameters that frequently appear in abnormal records and set them as characteristic parameters, which will help with subsequent equipment maintenance. Moreover, based on data statistics and change rate calculations, it can provide data-driven decision support for the maintenance strategy of the energy storage system and reduce human judgment errors.

[0007] Furthermore, step S300 includes: Step S301: select a number of consecutive days as a training cycle, obtain the energy conversion rate of any energy storage process in each energy storage record, compare the energy conversion rate of a certain energy storage process with the energy conversion rate threshold of the energy storage process, and if it exceeds the energy conversion rate threshold, set the energy storage record as a feature record, and summarize the feature records of a certain energy storage process; Step S302: In a feature record set of a certain energy storage process, obtain the equivalent energy corresponding to a certain energy storage link in a certain feature record in a certain collection time period, calculate the energy conversion rate of the collection time period through the energy conversion rate formula, obtain the change rate of the feature parameter of the collection time period, and calculate the feature score according to the following formula: ; Where X(ts) represents the feature score of the ts-th acquisition time period, N(ts) represents the energy conversion rate of the ts-th acquisition time period, Q(i, ts) represents the change rate of the i-th feature parameter in the ts-th acquisition time period, and W N Expressed as the weight of energy conversion rate, W Q（i） It is represented as the weight of the change rate of the i-th characteristic parameter, and r is represented as the total number of characteristic parameters; Step S303: Summarize the feature scores corresponding to all feature records of a certain energy storage process in a certain collection time period to obtain an average feature score of the energy storage process in the collection time period; draw a feature curve diagram of a certain energy storage process, wherein the feature curve diagram takes the average feature score of the energy storage process as the ordinate and the collection time period as the abscissa; By comparing with the energy conversion rate threshold, high-quality energy storage records exceeding the energy conversion rate threshold can be effectively screened out and classified as feature records, thus avoiding the interference of inefficient energy records on the analysis results; In the characteristic record, the energy conversion rate and the rate of change of characteristic parameters are calculated based on a specific acquisition time period, which can fully reflect the operating efficiency of the energy storage process and the dynamic changes of key indicators, and improve the comprehensiveness of the analysis; By introducing the characteristic scoring calculation formula, the energy conversion rate and characteristic parameter change rate and their weights are comprehensively considered, and a quantitative evaluation index is given to each acquisition time period, which helps to scientifically evaluate the pros and cons of the energy storage process; The average characteristic score of the energy storage process is calculated and a characteristic curve is drawn. With the average characteristic score and the acquisition time period as coordinates, the performance trend of the energy storage process over time can be intuitively displayed, which is convenient for monitoring and diagnosis.

[0008] Furthermore, step S400 includes: Step S401: obtaining real-time characteristic scores of a certain energy storage process in all acquisition time periods, drawing a real-time characteristic curve diagram of the energy storage process, mapping the real-time characteristic curve diagram to the characteristic curve diagram of the energy storage process, if the real-time characteristic curve is higher than the characteristic curve in a certain acquisition time period, setting the acquisition time period as a first time period, if the real-time characteristic curve is lower than the characteristic curve in a certain acquisition time period, setting the acquisition time period as a second time period; Step S402: Summarize the first time period and the second time period of a certain energy storage process. In a certain time period set, collect the real-time characteristic score corresponding to a certain time period in the real-time characteristic curve diagram as X1, obtain the characteristic score corresponding to the time period in the characteristic curve diagram as X2, and calculate the fluctuation value of the time period as ; Step S403: set several fluctuation levels, obtain the fluctuation value range corresponding to each fluctuation level, determine the fluctuation level corresponding to all time periods in a certain energy storage process, assign a value to each fluctuation level, and calculate the system score of the energy storage system according to the following formula: ; Wherein, Y represents the system score of the energy storage system, K(n,u) represents the fluctuation level value of the u-th time period in the first time period of the n-th energy storage process, H(n,u) represents the weight of the fluctuation level of the u-th time period in the first time period of the n-th energy storage process, K(n,g) represents the fluctuation level value of the g-th time period in the second time period of the n-th energy storage process, H(n,g) represents the weight of the fluctuation level of the g-th time period in the second time period of the n-th energy storage process, nf represents the total number of the first time period in the n-th energy storage process, nj represents the total number of the second time period in the n-th energy storage process, and m represents the total number of energy storage processes; Step S404: setting a system score threshold, comparing the system score of the energy storage system with the system score threshold, and if it exceeds the system score threshold, issuing an alarm to remind staff to conduct an inspection; During all acquisition time periods, real-time characteristic curves are drawn and compared with characteristic curves, which can dynamically capture the performance fluctuations of the energy storage process and evaluate the operating status of the energy storage process in real time; By comparing the real-time characteristic curve with the characteristic curve, the acquisition time period is divided into the first time period and the second time period, which realizes the accurate classification of the performance fluctuation of the energy storage process and provides a data basis for subsequent fluctuation analysis; Calculate the fluctuation value of each time period and divide the fluctuation level based on the fluctuation value, which can quantify the performance fluctuation degree of the energy storage process and facilitate the analysis and tracking of the stability of the energy storage system; The system score is compared with the set score threshold. If it exceeds the threshold, an alarm will be automatically issued to remind the operation and maintenance personnel to check. This can provide early warning of abnormal situations and avoid major accidents or performance degradation.

[0009] In order to better implement the above method, an energy storage system utilizing waste heat energy storage is also proposed, the system comprising an energy conversion rate module, a characteristic parameter module, a characteristic curve diagram module and a real-time warning module; Energy conversion rate module: In different energy storage links, corresponding sensors are arranged to monitor the operating parameters of the energy storage links. By retrieving historical energy storage records, the operating parameters of each energy storage link are obtained. According to the numerical values ​​of the operating parameters, the energy conversion rate threshold of each energy storage process is determined; Characteristic parameter module: screen abnormal records, calculate the change rate of operating parameters in abnormal records, determine the abnormal change rate, and determine the characteristic parameters of the energy storage process according to the number of abnormal change rates; Characteristic curve diagram module: statistics characteristic records, calculates characteristic scores of sampling time periods in characteristic records, and constructs characteristic curve diagrams of energy storage processes by calculating average characteristic scores of sampling time periods; Real-time warning module: draws the real-time characteristic curve of the energy storage process, calculates the system score of the energy storage system based on the characteristic curve of the energy storage process, and determines the warning status based on the system score and the system score threshold.

[0010] Furthermore, the energy conversion rate module includes an equivalent energy unit and an energy conversion rate threshold determination unit: Equivalent energy unit: two adjacent energy storage links with correlation are set as energy storage process, and the previous energy storage link in the energy storage process is set as the first link, and the latter energy storage link is set as the second link; obtain the historical energy storage record of a certain energy storage process, obtain the value of each operating parameter corresponding to all links in the energy storage process in a certain historical energy storage record, obtain the difference between the operating parameters before and after the operation of a certain link, and calculate the equivalent energy of a certain link; Determine the energy conversion rate threshold unit: obtain the equivalent energy of all links in the energy storage process, calculate the energy conversion rate of a certain energy storage process, obtain the energy conversion rate of all historical energy storage records in a certain energy storage process, obtain the average value and standard deviation of the energy conversion rate, and calculate the energy conversion rate threshold of a certain energy storage process.

[0011] Furthermore, the characteristic parameter module includes a change rate calculation unit and a characteristic parameter determination unit: A change rate calculation unit: compares the energy conversion rates of all historical energy storage records in a certain energy storage process with the energy conversion rate threshold of the energy storage process, sets the historical energy storage records below the energy conversion rate threshold as abnormal records, obtains the value of the qth operating parameter at the tth sampling time point in a certain abnormal record in the abnormal record set, draws an operation curve diagram of the qth operating parameter in the abnormal record, the operation curve diagram uses the sampling time point as the horizontal coordinate and the value of the operating parameter as the vertical coordinate, and calculates the change rate of the operating parameter in a certain sampling time period; Determine the characteristic parameter unit: set a change rate threshold of a certain operating parameter, compare each change rate of a certain operating parameter in a certain abnormal record with the change rate threshold of the operating parameter, and if the change rate threshold is not met, set the change rate as the abnormal change rate; count the number of abnormal change rates of a certain operating parameter in all abnormal records of a certain energy storage process, obtain the total number of abnormal change rates in a certain energy storage process, calculate the occurrence frequency of the abnormal change rate of a certain operating parameter, set an occurrence frequency threshold, compare the occurrence frequency of a certain operating parameter with the occurrence frequency threshold, and if it exceeds the occurrence frequency threshold, set the operating parameter as the characteristic parameter.

[0012] Furthermore, the feature curve graph module includes a feature scoring calculation unit and a feature curve graph drawing unit: Calculating feature scoring unit: selecting several consecutive days as training cycles, obtaining the energy conversion rate of any energy storage process in each energy storage record, comparing the energy conversion rate of a certain energy storage process with the energy conversion rate threshold of the energy storage process, and if it exceeds the energy conversion rate threshold, setting the energy storage record as a feature record, summarizing the feature records of a certain energy storage process, obtaining the equivalent energy corresponding to a certain energy storage link in a certain feature record in a certain collection time period in the feature record set of a certain energy storage process, calculating the energy conversion rate of the collection time period through the energy conversion rate formula, obtaining the change rate of the feature parameters of the collection time period, and calculating the feature score; A characteristic curve drawing unit is provided: the characteristic scores corresponding to all characteristic records of a certain energy storage process in a certain acquisition time period are summarized to obtain the average characteristic score of the energy storage process in the acquisition time period; and a characteristic curve drawing unit is provided, wherein the characteristic curve drawing unit uses the average characteristic score of the energy storage process as the ordinate and the acquisition time period as the abscissa.

[0013] Furthermore, the real-time warning module includes a fluctuation value calculation unit and a judgment warning unit: A fluctuation value calculation unit: obtaining a real-time characteristic score of a certain energy storage process in all acquisition time periods, drawing a real-time characteristic curve diagram of the energy storage process, mapping the real-time characteristic curve diagram to the characteristic curve diagram of the energy storage process, if the real-time characteristic curve is higher than the characteristic curve in a certain acquisition time period, the acquisition time period is set as a first time period, if the real-time characteristic curve is lower than the characteristic curve in a certain acquisition time period, the acquisition time period is set as a second time period, summarizing the first time period and the second time period of a certain energy storage process, collecting the real-time characteristic score corresponding to a certain time period in the real-time characteristic curve diagram in a certain time period set, obtaining the characteristic score corresponding to the time period in the characteristic curve diagram, and calculating the fluctuation value of the time period; Judgment and early warning unit: set several fluctuation levels, obtain the fluctuation value range corresponding to each fluctuation level, determine the fluctuation level corresponding to all time periods in a certain energy storage process, assign values ​​to each fluctuation level, calculate the system score of the energy storage system, set the system score threshold, compare the system score of the energy storage system with the system score threshold, and if it exceeds the system score threshold, issue an alarm to remind staff to check.

[0014] Compared with the prior art, the present invention has the following beneficial effects: By real-time monitoring and analysis of the operating status of the energy storage process, early warnings can be issued in time when abnormalities occur, helping operation and maintenance personnel to respond quickly, thereby avoiding system performance degradation or failures; Dynamic monitoring of feature scoring and energy conversion rate can help monitor the operating status of energy storage systems and improve system stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A schematic flow chart of an energy storage method utilizing waste heat energy storage according to the present invention; Figure 2 The schematic diagram of the structure of an energy storage system utilizing waste heat to store energy according to the present invention. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] See also Figure 1 and Figure 2 The present invention provides a technical solution: a method for storing energy using waste heat, the method comprising: Step S100: In different energy storage links, corresponding sensors are arranged to monitor the operating parameters of the energy storage links, and the operating parameters of each energy storage link are obtained by retrieving historical energy storage records. According to the numerical conditions of the operating parameters, the energy conversion rate threshold of each energy storage process is determined; Wherein, step S100 includes: Step S101: setting two adjacent energy storage links with correlation as an energy storage process, wherein the correlation is that the energy and material output by the previous energy storage link is directly used as the input of the next energy storage link, and setting the previous energy storage link in the energy storage process as the first link, and the next energy storage link as the second link; obtaining a historical energy storage record of a certain energy storage process, and obtaining the value of each operating parameter corresponding to all links in the energy storage process in a certain historical energy storage record; Step S102: Obtain the difference between the operating parameters of a link before and after operation, and calculate the equivalent energy of a link according to the following formula: ; Among them, E represents the equivalent energy of a certain link, A a It is expressed as the difference of the ath operating parameter, It is represented as the weight of the ath operating parameter, and b is represented as the total number of operating parameters in a certain link; Step S103: Obtain the equivalent energy of all links in the energy storage process, and calculate the energy conversion rate of a certain energy storage process according to the following energy conversion rate formula: ; Wherein, N represents the energy conversion rate of a certain energy storage process, E1 represents the equivalent energy of the first link in a certain energy storage process, and E2 represents the equivalent energy of the second link in a certain energy storage process; Step S104: Obtain the energy conversion rates of all historical energy storage records in a certain energy storage process, obtain the average value of the energy conversion rate as c and the standard deviation as d, and calculate the energy conversion rate threshold of a certain energy storage process according to the following formula: P=c+d*e; Wherein, P represents the energy conversion rate threshold, and e represents a preset constant; For example, the difference of operating parameter A in the first link of the first energy storage process is 20, the difference of operating parameter B is 0.1, and the difference of operating parameter C is 5. The equivalent energy of the first link in the first energy storage process is calculated to be 120.

[0018] Step S200: screening abnormal records, calculating the change rate of the operating parameters in the abnormal records, determining the abnormal change rate, and determining the characteristic parameters of the energy storage process according to the quantity of the abnormal change rate; Wherein, step S200 includes: Step S201: comparing the energy conversion rates of all historical energy storage records in a certain energy storage process with the energy conversion rate threshold of the energy storage process, setting the historical energy storage records below the energy conversion rate threshold as abnormal records, and summarizing the abnormal records of a certain energy storage process; Step S202: In a set of abnormal records of a certain energy storage process, the value of the qth operating parameter at the tth sampling time point in a certain abnormal record is obtained as Q (q, t), and an operating curve diagram of the qth operating parameter in the abnormal record is drawn. The operating curve diagram takes the sampling time point as the abscissa and the value of the operating parameter as the ordinate. The change rate of the operating parameter in a certain sampling time period is calculated according to the following formula: ; Where R(q, t') represents the rate of change of the qth operating parameter in the t'th sampling time period, Q(q, t+1) represents the value of the qth operating parameter at the t+1th sampling time point, It is expressed as the time interval of the t'th sampling period; Step S203: setting a change rate threshold of a certain operating parameter, comparing each change rate of a certain operating parameter in a certain abnormal record with the change rate threshold of the operating parameter, and if the change rate threshold is not met, setting the change rate as an abnormal change rate; Step S204: Count the number of abnormal change rates of a certain operating parameter in all abnormal records of a certain energy storage process as B, obtain the total number of abnormal change rates in a certain energy storage process as D, and calculate the occurrence frequency of the abnormal change rate of a certain operating parameter as B / D; Step S205: setting an occurrence frequency threshold, comparing the occurrence frequency of a certain operating parameter with the occurrence frequency threshold, and if the occurrence frequency threshold is exceeded, setting the operating parameter as a characteristic parameter.

[0019] Step S300: Counting feature records, calculating feature scores of sampling time periods in the feature records, and constructing a feature curve diagram of the energy storage process by calculating the average feature score of the sampling time periods; Wherein, step S300 includes: Step S301: select a number of consecutive days as a training cycle, obtain the energy conversion rate of any energy storage process in each energy storage record, compare the energy conversion rate of a certain energy storage process with the energy conversion rate threshold of the energy storage process, and if it exceeds the energy conversion rate threshold, set the energy storage record as a feature record, and summarize the feature records of a certain energy storage process; Step S302: In a feature record set of a certain energy storage process, obtain the equivalent energy corresponding to a certain energy storage link in a certain feature record in a certain collection time period, calculate the energy conversion rate of the collection time period through the energy conversion rate formula, obtain the change rate of the feature parameter of the collection time period, and calculate the feature score according to the following formula: ; Where X(ts) represents the feature score of the ts-th acquisition time period, N(ts) represents the energy conversion rate of the ts-th acquisition time period, Q(i, ts) represents the change rate of the i-th feature parameter in the ts-th acquisition time period, and W N Expressed as the weight of energy conversion rate, W Q（i） It is represented as the weight of the change rate of the i-th characteristic parameter, and r is represented as the total number of characteristic parameters; Step S303: Summarize the feature scores corresponding to all feature records of a certain energy storage process in a certain collection time period to obtain an average feature score of the energy storage process in the collection time period; draw a feature curve diagram of a certain energy storage process, wherein the feature curve diagram takes the average feature score of the energy storage process as the ordinate and the collection time period as the abscissa; For example, in the first acquisition time period, the energy conversion rate is 0.9, the change rate of characteristic parameter 1 is 0.05, and the change rate of characteristic parameter 2 is 0.08. The characteristic score of the first acquisition time period is calculated to be 0.563.

[0020] Step S400: draw a real-time characteristic curve diagram of the energy storage process, calculate the system score of the energy storage system in combination with the characteristic curve diagram of the energy storage process, and determine the warning state according to the system score and the system score threshold; Wherein, step S400 includes: Step S401: obtaining real-time characteristic scores of a certain energy storage process in all acquisition time periods, drawing a real-time characteristic curve diagram of the energy storage process, mapping the real-time characteristic curve diagram to the characteristic curve diagram of the energy storage process, if the real-time characteristic curve is higher than the characteristic curve in a certain acquisition time period, setting the acquisition time period as a first time period, if the real-time characteristic curve is lower than the characteristic curve in a certain acquisition time period, setting the acquisition time period as a second time period; Step S402: Summarize the first time period and the second time period of a certain energy storage process. In a certain time period set, collect the real-time characteristic score corresponding to a certain time period in the real-time characteristic curve diagram as X1, obtain the characteristic score corresponding to the time period in the characteristic curve diagram as X2, and calculate the fluctuation value of the time period as ; Step S403: set several fluctuation levels, obtain the fluctuation value range corresponding to each fluctuation level, determine the fluctuation level corresponding to all time periods in a certain energy storage process, assign a value to each fluctuation level, and calculate the system score of the energy storage system according to the following formula: ; Wherein, Y represents the system score of the energy storage system, K(n,u) represents the fluctuation level value of the u-th time period in the first time period of the n-th energy storage process, H(n,u) represents the weight of the fluctuation level of the u-th time period in the first time period of the n-th energy storage process, K(n,g) represents the fluctuation level value of the g-th time period in the second time period of the n-th energy storage process, H(n,g) represents the weight of the fluctuation level of the g-th time period in the second time period of the n-th energy storage process, nf represents the total number of the first time period in the n-th energy storage process, nj represents the total number of the second time period in the n-th energy storage process, and m represents the total number of energy storage processes; Step S404: setting a system score threshold, comparing the system score of the energy storage system with the system score threshold, and if it exceeds the system score threshold, sounding an alarm to remind staff to conduct an inspection.

[0021] In order to better implement the above method, an energy storage system utilizing waste heat energy storage is also proposed, the system comprising an energy conversion rate module, a characteristic parameter module, a characteristic curve diagram module and a real-time warning module; Energy conversion rate module: In different energy storage links, corresponding sensors are arranged to monitor the operating parameters of the energy storage links. By retrieving historical energy storage records, the operating parameters of each energy storage link are obtained. According to the numerical values ​​of the operating parameters, the energy conversion rate threshold of each energy storage process is determined; The energy conversion rate module includes an equivalent energy unit and an energy conversion rate threshold determination unit: Equivalent energy unit: two adjacent energy storage links with correlation are set as energy storage process, and the previous energy storage link in the energy storage process is set as the first link, and the latter energy storage link is set as the second link; obtain the historical energy storage record of a certain energy storage process, obtain the value of each operating parameter corresponding to all links in the energy storage process in a certain historical energy storage record, obtain the difference between the operating parameters before and after the operation of a certain link, and calculate the equivalent energy of a certain link; Determine the energy conversion rate threshold unit: obtain the equivalent energy of all links in the energy storage process, calculate the energy conversion rate of a certain energy storage process, obtain the energy conversion rate of all historical energy storage records in a certain energy storage process, obtain the average value and standard deviation of the energy conversion rate, and calculate the energy conversion rate threshold of a certain energy storage process.

[0022] Characteristic parameter module: screen abnormal records, calculate the change rate of operating parameters in abnormal records, determine the abnormal change rate, and determine the characteristic parameters of the energy storage process according to the number of abnormal change rates; Among them, the characteristic parameter module includes a change rate calculation unit and a characteristic parameter determination unit: A change rate calculation unit: compares the energy conversion rates of all historical energy storage records in a certain energy storage process with the energy conversion rate threshold of the energy storage process, sets the historical energy storage records below the energy conversion rate threshold as abnormal records, obtains the value of the qth operating parameter at the tth sampling time point in a certain abnormal record in the abnormal record set, draws an operation curve diagram of the qth operating parameter in the abnormal record, the operation curve diagram uses the sampling time point as the horizontal coordinate and the value of the operating parameter as the vertical coordinate, and calculates the change rate of the operating parameter in a certain sampling time period; Determine the characteristic parameter unit: set a change rate threshold of a certain operating parameter, compare each change rate of a certain operating parameter in a certain abnormal record with the change rate threshold of the operating parameter, and if the change rate threshold is not met, set the change rate as the abnormal change rate; count the number of abnormal change rates of a certain operating parameter in all abnormal records of a certain energy storage process, obtain the total number of abnormal change rates in a certain energy storage process, calculate the occurrence frequency of the abnormal change rate of a certain operating parameter, set an occurrence frequency threshold, compare the occurrence frequency of a certain operating parameter with the occurrence frequency threshold, and if it exceeds the occurrence frequency threshold, set the operating parameter as the characteristic parameter.

[0023] Characteristic curve diagram module: statistics characteristic records, calculates characteristic scores of sampling time periods in characteristic records, and constructs characteristic curve diagrams of energy storage processes by calculating average characteristic scores of sampling time periods; The feature curve graph module includes a feature scoring calculation unit and a feature curve graph drawing unit: Calculating feature scoring unit: selecting several consecutive days as training cycles, obtaining the energy conversion rate of any energy storage process in each energy storage record, comparing the energy conversion rate of a certain energy storage process with the energy conversion rate threshold of the energy storage process, and if it exceeds the energy conversion rate threshold, setting the energy storage record as a feature record, summarizing the feature records of a certain energy storage process, obtaining the equivalent energy corresponding to a certain energy storage link in a certain feature record in a certain collection time period in the feature record set of a certain energy storage process, calculating the energy conversion rate of the collection time period through the energy conversion rate formula, obtaining the change rate of the feature parameters of the collection time period, and calculating the feature score; A characteristic curve drawing unit is provided: the characteristic scores corresponding to all characteristic records of a certain energy storage process in a certain acquisition time period are summarized to obtain the average characteristic score of the energy storage process in the acquisition time period; and a characteristic curve drawing unit is provided, wherein the characteristic curve drawing unit uses the average characteristic score of the energy storage process as the ordinate and the acquisition time period as the abscissa.

[0024] Real-time warning module: draws the real-time characteristic curve of the energy storage process, calculates the system score of the energy storage system based on the characteristic curve of the energy storage process, and determines the warning status according to the system score and the system score threshold; Among them, the real-time warning module includes a fluctuation value calculation unit and a judgment warning unit: A fluctuation value calculation unit: obtaining a real-time characteristic score of a certain energy storage process in all acquisition time periods, drawing a real-time characteristic curve diagram of the energy storage process, mapping the real-time characteristic curve diagram to the characteristic curve diagram of the energy storage process, if the real-time characteristic curve is higher than the characteristic curve in a certain acquisition time period, the acquisition time period is set as a first time period, if the real-time characteristic curve is lower than the characteristic curve in a certain acquisition time period, the acquisition time period is set as a second time period, summarizing the first time period and the second time period of a certain energy storage process, collecting the real-time characteristic score corresponding to a certain time period in the real-time characteristic curve diagram in a certain time period set, obtaining the characteristic score corresponding to the time period in the characteristic curve diagram, and calculating the fluctuation value of the time period; Judgment and early warning unit: set several fluctuation levels, obtain the fluctuation value range corresponding to each fluctuation level, determine the fluctuation level corresponding to all time periods in a certain energy storage process, assign values ​​to each fluctuation level, calculate the system score of the energy storage system, set the system score threshold, compare the system score of the energy storage system with the system score threshold, and if it exceeds the system score threshold, issue an alarm to remind staff to check.

[0025] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A method for storing energy using waste heat, characterized in that: Methods include: Step S100: In different energy storage links, corresponding sensors are arranged to monitor the operating parameters of the energy storage links, and the operating parameters of each energy storage link are obtained by retrieving historical energy storage records. According to the numerical conditions of the operating parameters, the energy conversion rate threshold of each energy storage process is determined; Step S200: screening abnormal records, calculating the change rate of the operating parameters in the abnormal records, determining the abnormal change rate, and determining the characteristic parameters of the energy storage process according to the quantity of the abnormal change rate; Step S300: Counting feature records, calculating feature scores of sampling time periods in the feature records, and constructing a feature curve diagram of the energy storage process by calculating the average feature score of the sampling time periods; Step S400: draw a real-time characteristic curve diagram of the energy storage process, calculate the system score of the energy storage system in combination with the characteristic curve diagram of the energy storage process, and determine the warning state according to the system score and the system score threshold.

2. The energy storage method using waste heat to store energy according to claim 1, characterized in that: The step S100 includes the following steps: Step S101: setting two adjacent energy storage links with correlation as an energy storage process, wherein the correlation is that the energy and material output by the previous energy storage link is directly used as the input of the next energy storage link, and setting the previous energy storage link in the energy storage process as the first link, and the next energy storage link as the second link; obtaining a historical energy storage record of a certain energy storage process, and obtaining the value of each operating parameter corresponding to all links in the energy storage process in a certain historical energy storage record; Step S102: Obtain the difference between the operating parameters of a link before and after operation, and calculate the equivalent energy of a link according to the following formula: ； Among them, E represents the equivalent energy of a certain link, A a It is expressed as the difference of the ath operating parameter, It is represented as the weight of the ath operating parameter, and b is represented as the total number of operating parameters in a certain link; Step S103: Obtain the equivalent energy of all links in the energy storage process, and calculate the energy conversion rate of a certain energy storage process according to the following energy conversion rate formula: ； Wherein, N represents the energy conversion rate of a certain energy storage process, E1 represents the equivalent energy of the first link in a certain energy storage process, and E2 represents the equivalent energy of the second link in a certain energy storage process; Step S104: Obtain the energy conversion rates of all historical energy storage records in a certain energy storage process, obtain the average value of the energy conversion rate as c and the standard deviation as d, and calculate the energy conversion rate threshold of a certain energy storage process according to the following formula: P=c+d*e; Wherein, P represents the energy conversion rate threshold, and e represents a preset constant.

3. The energy storage method using waste heat to store energy according to claim 2, characterized in that: The step S200 includes the following steps: Step S201: comparing the energy conversion rates of all historical energy storage records in a certain energy storage process with the energy conversion rate threshold of the energy storage process, setting the historical energy storage records below the energy conversion rate threshold as abnormal records, and summarizing the abnormal records of a certain energy storage process; Step S202: In a set of abnormal records of a certain energy storage process, the value of the qth operating parameter at the tth sampling time point in a certain abnormal record is obtained as Q (q, t), and an operating curve diagram of the qth operating parameter in the abnormal record is drawn. The operating curve diagram takes the sampling time point as the abscissa and the value of the operating parameter as the ordinate. The change rate of the operating parameter in a certain sampling time period is calculated according to the following formula: ； Among them, R (q, t') represents the rate of change of the qth operating parameter in the t'th sampling time period, Q (q, t+1) represents the value of the qth operating parameter at the t+1th sampling time point, It is expressed as the time interval of the t'th sampling period; Step S203: setting a change rate threshold of a certain operating parameter, comparing each change rate of a certain operating parameter in a certain abnormal record with the change rate threshold of the operating parameter, and if the change rate threshold is not met, setting the change rate as an abnormal change rate; Step S204: Count the number of abnormal change rates of a certain operating parameter in all abnormal records of a certain energy storage process as B, obtain the total number of abnormal change rates in a certain energy storage process as D, and calculate the occurrence frequency of the abnormal change rate of a certain operating parameter as B / D; Step S205: setting an occurrence frequency threshold, comparing the occurrence frequency of a certain operating parameter with the occurrence frequency threshold, and if the occurrence frequency threshold is exceeded, setting the operating parameter as a characteristic parameter.

4. The energy storage method using waste heat to store energy according to claim 3, characterized in that: The step S300 includes the following steps: Step S301: select a number of consecutive days as a training cycle, obtain the energy conversion rate of any energy storage process in each energy storage record, compare the energy conversion rate of a certain energy storage process with the energy conversion rate threshold of the energy storage process, and if it exceeds the energy conversion rate threshold, set the energy storage record as a feature record, and summarize the feature records of a certain energy storage process; Step S302: In a feature record set of a certain energy storage process, obtain the equivalent energy corresponding to a certain energy storage link in a certain feature record in a certain collection time period, calculate the energy conversion rate of the collection time period through the energy conversion rate formula, obtain the change rate of the feature parameter of the collection time period, and calculate the feature score according to the following formula: ； Where X(ts) represents the feature score of the ts-th acquisition time period, N(ts) represents the energy conversion rate of the ts-th acquisition time period, Q(i, ts) represents the change rate of the i-th feature parameter in the ts-th acquisition time period, and W N Expressed as the weight of energy conversion rate, W Q（i） It is represented as the weight of the change rate of the i-th characteristic parameter, and r is represented as the total number of characteristic parameters; Step S303: Summarize the feature scores corresponding to all feature records of a certain energy storage process in a certain collection time period to obtain the average feature score of the energy storage process in the collection time period; draw a feature curve diagram of a certain energy storage process, wherein the feature curve diagram takes the average feature score of the energy storage process as the ordinate and the collection time period as the abscissa.

5. The energy storage method using waste heat to store energy according to claim 4, characterized in that: The step S400 includes the following steps: Step S401: obtaining real-time characteristic scores of a certain energy storage process in all acquisition time periods, drawing a real-time characteristic curve diagram of the energy storage process, mapping the real-time characteristic curve diagram to the characteristic curve diagram of the energy storage process, if the real-time characteristic curve is higher than the characteristic curve in a certain acquisition time period, setting the acquisition time period as a first time period, if the real-time characteristic curve is lower than the characteristic curve in a certain acquisition time period, setting the acquisition time period as a second time period; Step S402: Summarize the first time period and the second time period of a certain energy storage process. In a certain time period set, collect the real-time characteristic score corresponding to a certain time period in the real-time characteristic curve diagram as X1, obtain the characteristic score corresponding to the time period in the characteristic curve diagram as X2, and calculate the fluctuation value of the time period as ; Step S403: set several fluctuation levels, obtain the fluctuation value range corresponding to each fluctuation level, determine the fluctuation level corresponding to all time periods in a certain energy storage process, assign a value to each fluctuation level, and calculate the system score of the energy storage system according to the following formula: ； Wherein, Y represents the system score of the energy storage system, K(n,u) represents the fluctuation level value of the u-th time period in the first time period of the n-th energy storage process, H(n,u) represents the weight of the fluctuation level of the u-th time period in the first time period of the n-th energy storage process, K(n,g) represents the fluctuation level value of the g-th time period in the second time period of the n-th energy storage process, H(n,g) represents the weight of the fluctuation level of the g-th time period in the second time period of the n-th energy storage process, nf represents the total number of the first time period in the n-th energy storage process, nj represents the total number of the second time period in the n-th energy storage process, and m represents the total number of energy storage processes; Step S404: setting a system score threshold, comparing the system score of the energy storage system with the system score threshold, and if it exceeds the system score threshold, sounding an alarm to remind staff to conduct an inspection.

6. An energy storage system utilizing waste heat energy storage, used to implement an energy storage method utilizing waste heat energy storage as described in any one of claims 1 to 5, characterized in that: The system includes an energy conversion rate module, a characteristic parameter module, a characteristic curve diagram module and a real-time warning module; The energy conversion rate module: in different energy storage links, corresponding sensors are arranged to monitor the operating parameters of the energy storage links, and the operating parameters of each energy storage link are obtained by retrieving historical energy storage records, and the energy conversion rate threshold of each energy storage process is determined according to the numerical conditions of the operating parameters; The characteristic parameter module is used to screen abnormal records, calculate the change rate of the operating parameters in the abnormal records, determine the abnormal change rate, and determine the characteristic parameters of the energy storage process according to the quantity of the abnormal change rate; The characteristic curve diagram module is used to count characteristic records, calculate characteristic scores of sampling time periods in characteristic records, and construct a characteristic curve diagram of the energy storage process by calculating the average characteristic scores of the sampling time periods; The real-time warning module draws a real-time characteristic curve diagram of the energy storage process, calculates the system score of the energy storage system in combination with the characteristic curve diagram of the energy storage process, and determines the warning state according to the system score and the system score threshold.

7. The energy storage system utilizing waste heat energy storage according to claim 6, characterized in that: The energy conversion rate module includes an equivalent energy unit and an energy conversion rate threshold determination unit: The equivalent energy unit: sets two adjacent energy storage links with correlation as an energy storage process, and sets the previous energy storage link in the energy storage process as the first link, and the next energy storage link as the second link; obtains the historical energy storage record of a certain energy storage process, obtains the value of each operating parameter corresponding to all links in the energy storage process in a certain historical energy storage record, obtains the difference between the operating parameters before and after the operation of a certain link, and calculates the equivalent energy of a certain link; The energy conversion rate threshold determination unit: obtains the equivalent energy of all links in the energy storage process, calculates the energy conversion rate of a certain energy storage process, obtains the energy conversion rate of all historical energy storage records in a certain energy storage process, obtains the average value and standard deviation of the energy conversion rate, and calculates the energy conversion rate threshold of a certain energy storage process.

8. The energy storage system utilizing waste heat energy storage according to claim 6, characterized in that: The characteristic parameter module includes a change rate calculation unit and a characteristic parameter determination unit: The change rate calculation unit: compares the energy conversion rates of all historical energy storage records in a certain energy storage process with the energy conversion rate threshold of the energy storage process, sets the historical energy storage records below the energy conversion rate threshold as abnormal records, obtains the value of the qth operating parameter at the tth sampling time point in a certain abnormal record in the abnormal record set, draws an operation curve diagram of the qth operating parameter in the abnormal record, the operation curve diagram uses the sampling time point as the horizontal coordinate and the value of the operating parameter as the vertical coordinate, and calculates the change rate of the operating parameter in a certain sampling time period; The characteristic parameter determination unit: sets a change rate threshold of a certain operating parameter, compares each change rate of a certain operating parameter in a certain abnormal record with the change rate threshold of the operating parameter, and if the change rate threshold is not met, sets the change rate as the abnormal change rate; counts the number of abnormal change rates of a certain operating parameter in all abnormal records of a certain energy storage process, obtains the total number of abnormal change rates in a certain energy storage process, calculates the occurrence frequency of the abnormal change rate of a certain operating parameter, sets an occurrence frequency threshold, compares the occurrence frequency of a certain operating parameter with the occurrence frequency threshold, and if the occurrence frequency threshold is exceeded, sets the operating parameter as the characteristic parameter.

9. The energy storage system utilizing waste heat energy storage according to claim 6, characterized in that: The characteristic curve graph module includes a characteristic scoring unit and a characteristic curve graph drawing unit: The calculation feature scoring unit: selects a number of consecutive days as a training cycle, obtains the energy conversion rate of any energy storage process in each energy storage record, compares the energy conversion rate of a certain energy storage process with the energy conversion rate threshold of the energy storage process, and if it exceeds the energy conversion rate threshold, sets the energy storage record as a feature record, summarizes the feature records of a certain energy storage process, obtains the equivalent energy corresponding to a certain energy storage link in a certain feature record in a certain collection time period in the feature record set of a certain energy storage process, calculates the energy conversion rate of the collection time period through the energy conversion rate formula, obtains the change rate of the feature parameter of the collection time period, and calculates the feature score; The characteristic curve drawing unit: summarizes the characteristic scores corresponding to all characteristic records of a certain energy storage process in a certain collection time period to obtain an average characteristic score of the energy storage process in the collection time period; A characteristic curve diagram of a certain energy storage process is drawn, wherein the characteristic curve diagram takes the average characteristic score of the energy storage process as the ordinate and takes the acquisition time period as the abscissa.

10. The energy storage system utilizing waste heat energy storage according to claim 6, characterized in that: The real-time warning module includes a fluctuation value calculation unit and a judgment warning unit: The fluctuation value calculating unit: obtains the real-time characteristic scores of a certain energy storage process in all acquisition time periods, draws a real-time characteristic curve diagram of the energy storage process, maps the real-time characteristic curve diagram to the characteristic curve diagram of the energy storage process, if the real-time characteristic curve is higher than the characteristic curve in a certain acquisition time period, the acquisition time period is set as the first time period, if the real-time characteristic curve is lower than the characteristic curve in a certain acquisition time period, the acquisition time period is set as the second time period, summarizes the first time period and the second time period of a certain energy storage process, collects the real-time characteristic score corresponding to a certain time period in the real-time characteristic curve diagram in a certain time period set, obtains the characteristic score corresponding to the time period in the characteristic curve diagram, and calculates the fluctuation value of the time period; The judgment and early warning unit: sets several fluctuation levels, obtains the fluctuation value range corresponding to each fluctuation level, determines the fluctuation levels corresponding to all time periods in a certain energy storage process, assigns values ​​to each fluctuation level, calculates the system score of the energy storage system, sets a system score threshold, compares the system score of the energy storage system with the system score threshold, and if it exceeds the system score threshold, issues an alarm to remind staff to conduct inspections.

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