Nuclear power energy control method and system based on fused salt energy storage

Abstract

The invention discloses a nuclear power energy control method and system based on fused salt energy storage, and relates to the technical field of energy storage. The method comprises the following steps: calculating a temperature difference value consumed in a fused salt conveying process of each pipeline sub-section in a historical detection period and an included angle value formed between an external wind speed direction and a fused salt conveying direction of each pipeline sub-section, and detecting a historical bending degree and a historical section concentration degree of a bending sub-section in the pipeline sub-sections; according to the historical characteristic factors I and II, extracting a correlation coefficient I between the fused salt temperature loss value and the historical bending degree of the pipeline sub-section and a correlation coefficient II between the fused salt temperature comprehensive loss value and the historical section concentration ratio of the energy storage conveying pipeline to be measured; therefore, the temperature loss degree of the actual fused salt conveyed in the to-be-measured energy storage conveying pipeline at present and the actual required flow velocity can be predicted. According to the nuclear power energy control method and system based on fused salt energy storage, the energy storage efficiency can be improved.

Description

Technical Field

[0001] This application relates to the technical field of energy storage, and particularly to a nuclear power energy control method and system based on molten salt energy storage. Background Art

[0002] With the development of the global economy and the growth of the population, the demand for energy is increasing continuously. As a clean and efficient energy source, nuclear power occupies an important position in energy supply.

[0003] In traditional technologies, there are large errors in predicting the degree of energy loss during the nuclear power energy conversion control process of molten salt energy storage. Because only the energy loss caused by the influence of the flow rate and temperature of molten salt on the temperature change in the external environment is often considered, and the influence of the wind speed in the external environment is not considered and analyzed. As a result, the accuracy of the prediction result of the energy loss degree value is low, and the flow rate and output temperature of molten salt cannot be effectively regulated, resulting in energy waste in the nuclear power energy conversion and energy storage processes, as well as low efficiency of the entire energy storage control work. Summary of the Invention

[0004] In order to overcome the deficiencies of the above-mentioned prior art, this application provides a nuclear power energy control method and system based on molten salt energy storage.

[0005] In the first aspect, a nuclear power energy control method based on molten salt energy storage provided by this application includes:

[0006] Step S1: Divide the pipeline of the energy storage to be measured into several equal subsections to obtain pipeline subsections, and count the temperature differences of each pipeline subsection belonging to the molten salt transportation process loss during the historical detection period, and output the first historical characteristic factor;

[0007] Step S2: Count the included angle value formed between the wind direction of each pipeline subsection belonging to the outside and the molten salt transportation direction, and output the second historical characteristic factor;

[0008] Step S3: Detect the historical bending degree of the bent subsections and the historical section concentration degree of the bent sections in the pipeline subsections, and extract the first correlation coefficient between the molten salt temperature loss value and the historical bending degree of the pipeline subsections according to the first historical characteristic factor, the second historical characteristic factor and the historical bending degree;

[0009] Step S4: Extract the second correlation coefficient between the comprehensive molten salt temperature loss value of the pipeline of the energy storage to be measured and the historical section concentration degree;

[0010] Step S5: Detect the preprocessing feature set to which the pipeline sub-section belongs in the current period. Based on the first correlation coefficient set, the second correlation coefficient, and the preprocessing feature set, predict the actual temperature loss degree of the molten salt transported in the pipeline to be tested for energy storage and the actual required flow rate, so as to regulate the operating parameters of the molten salt energy storage process and output the energy storage control result.

[0011] Preferably, obtain the pipeline to be tested for energy loss detection, and divide the pipeline to be tested for energy storage into several equal sub-sections to obtain pipeline sub-sections;

[0012] Statistically calculate the temperature difference between the ambient temperature value of the outside of each pipeline sub-section and the molten salt temperature value of the molten salt transported by each pipeline sub-section in the historical detection period. If the ambient temperature value is greater than or equal to the molten salt temperature value, output a positive temperature difference value. If the ambient temperature value is less than the molten salt temperature value, output a negative temperature difference value. The positive temperature difference value and the negative temperature difference value are combined into the first historical feature factor.

[0013] Preferably, obtain the wind speed value and wind direction of the outside of each pipeline sub-section in the historical detection period. Statistically calculate the included angle value with the same orientation formed between the wind direction and the molten salt transportation direction in the pipeline sub-section, and output a positive included angle value. Statistically calculate the included angle value with the opposite orientation formed between the wind direction and the molten salt transportation direction in the pipeline sub-section, and output a negative included angle value. The wind speed value, the positive included angle value, and the negative included angle value are combined into the second historical feature factor.

[0014] Preferably, detect the historical bending degree of the bent sub-section in the pipeline sub-section in the historical detection period, and evaluate the concentration degree of the bent sub-section in the pipeline sub-section to obtain the historical section concentration degree;

[0015] Detect the molten salt temperature difference change value and the molten salt flow rate difference change value of each pipeline sub-section affected by external environmental factors in the historical detection period;

[0016] According to the molten salt temperature difference change value, the first historical feature factor, the second historical feature factor, and the historical bending degree, respectively extract the correlation coefficients between the molten salt temperature difference change value and the first historical feature factor, the second historical feature factor, and the historical bending degree to obtain the first correlation coefficient set.

[0017] Preferably, detect the comprehensive molten salt temperature loss value of the pipeline to be tested for energy storage affected by external environmental factors in the historical detection period;

[0018] According to the comprehensive molten salt temperature loss value, the molten salt temperature difference change value, and the historical section concentration degree, extract the correlation coefficient between the comprehensive molten salt temperature loss value and the section concentration degree to obtain the second correlation coefficient.

[0019] Preferably, detect the current characteristic factor one, current characteristic factor two, current bending degree, and current section concentration of the pipeline sub-section in the current period. The current characteristic factor one, current characteristic factor two, and current bending degree are combined into a preprocessing characteristic set;

[0020] According to the first set of correlation coefficients and the preprocessing characteristic set, predict the degree of molten salt temperature loss to which each pipeline sub-section in the current period belongs to obtain a sub-prediction value of temperature loss;

[0021] According to the second set of correlation coefficients, the preprocessing characteristic set, and the sub-prediction value of temperature loss, predict the comprehensive degree of actual molten salt temperature loss to which the pipeline sub-section in the current period belongs to obtain a total prediction value of actual temperature loss;

[0022] Extract the correlation degree between the molten salt temperature difference change value and the molten salt flow rate difference change value to obtain a proportional correlation value;

[0023] According to the total prediction value of actual temperature loss and the proportional correlation value, predict the actual molten salt flow rate required for the pipeline for energy storage to be measured to obtain a predicted value of actual molten salt flow rate;

[0024] According to the total prediction value of actual temperature loss and the predicted value of actual molten salt flow rate, adjust the operating parameters of the molten salt energy storage process and output an energy storage control result.

[0025] In a second aspect, a nuclear power energy control system based on molten salt energy storage includes:

[0026] A first characteristic statistics unit is configured to divide the pipeline for energy storage to be measured into a plurality of equal-section sub-sections to obtain pipeline sub-sections, and statistically obtain the temperature difference values of the losses in the molten salt transportation process to which each pipeline sub-section belongs in the historical detection period, and output a first historical characteristic factor;

[0027] A second characteristic statistics unit is configured to statistically obtain the included angle value formed between the wind direction outside each pipeline sub-section belongs to and the molten salt transportation direction, and output a second historical characteristic factor;

[0028] A first coefficient extraction unit is configured to detect the historical bending degree of the bent sub-section in the pipeline sub-section and the historical section concentration of the bent section, and extract a first correlation coefficient between the molten salt temperature loss value of the pipeline sub-section and the historical bending degree according to the first historical characteristic factor, the second historical characteristic factor, and the historical bending degree;

[0029] A second coefficient extraction unit is configured to extract a second correlation coefficient between the comprehensive molten salt temperature loss value of the pipeline for energy storage to be measured and the historical section concentration;

[0030] A prediction and regulation unit is used to detect the preprocessing feature set to which the pipeline sub-section belongs in the current period. According to the first correlation coefficient set, the second correlation coefficient set, and the preprocessing feature set, it predicts the actual temperature loss degree and the actual required flow rate of the molten salt transported in the energy storage pipeline to be measured, so as to regulate the operating parameters of the molten salt energy storage process and output an energy storage control result.

[0031] Compared with the prior art, the present invention has the following characteristics and beneficial effects:

[0032] By detecting the temperature value lost during the molten salt transportation in the molten salt transportation pipeline in the energy storage link, it is convenient to effectively regulate the temperature value and flow rate of the molten salt output in real time and reduce the loss degree value in the energy conversion process. Among them, by considering the influence characteristics of the temperature and wind speed in the external environment on the temperature change of the energy storage pipeline to be measured, a full analysis of the correlation degree between diverse influencing factors is realized, so as to reduce the misjudgment of the control of the molten salt output temperature and flow rate parameters in the energy storage process ultimately. In order to improve the accuracy of the entire feature factor statistics, the energy storage pipeline to be measured is segmented into several sections, so as to conduct statistics on the temperature difference, the included angle value between the wind speed direction and the molten salt transportation direction in each section of the segmented pipeline sub-section, avoiding the single analysis of the external environment characteristics belonging to the unified overall pipeline in the traditional technology. Whether the wind speed direction and the molten salt transportation direction are the same or not determines whether the molten salt temperature is affected positively or negatively. By combining the comprehensive effects of the above various influencing factors on the molten salt temperature and flow rate in the energy storage pipeline to be measured, the actual required molten salt temperature and flow rate in the current period are predicted for timely regulation, so as to reduce energy loss and improve the efficiency of the entire energy storage control work. Description of the Drawings

[0033] Figure 1 It is a step block diagram of a nuclear power energy control method based on molten salt energy storage mainly embodied in this embodiment.

[0034] Figure 2 It is a structural block diagram of a nuclear power energy control system based on molten salt energy storage mainly embodied in this embodiment. Detailed Embodiment

[0035] The following further describes the present invention in detail in conjunction with the following embodiments.

[0036] Refer to Figure 1 , a nuclear power energy control method based on molten salt energy storage, the method includes the following steps:

[0037] Step S1: Divide the energy storage pipeline to be measured into several equal - sized sub - sections to obtain pipeline sub - sections, and count the temperature differences of each pipeline sub - section belonging to the loss during the molten salt transportation process in the historical detection period, and output the first historical characteristic factor.

[0038] Step S2: Count the included angle values formed between the wind speed direction of the outside of each pipeline sub - section and the molten salt transportation direction, and output the second historical characteristic factor.

[0039] Step S3: Detect the historical bending degree of the bent sub - sections in the pipeline sub - sections and the historical section concentration degree of the bending sections. According to the first historical characteristic factor, the second historical characteristic factor and the historical bending degree, extract the correlation coefficient one between the molten salt temperature loss value and the historical bending degree of the pipeline sub - sections.

[0040] Step S4: Extract the correlation coefficient two between the comprehensive molten salt temperature loss value of the energy storage pipeline to be measured and the historical section concentration degree.

[0041] Step S5: Detect the pre - processing feature set to which the pipeline sub - sections belong in the current period. According to the first correlation coefficient set, the second correlation coefficient and the pre - processing feature set, predict the actual molten salt temperature loss degree and the actual required flow rate during the transportation in the energy storage pipeline to be measured, so as to adjust the operating parameters of the molten salt energy storage process, and output the energy storage control result.

[0042] Specifically, by detecting the temperature value lost during the molten salt transportation in the transportation molten salt pipeline in the energy storage link, it is convenient to effectively adjust the temperature value and flow rate of the molten salt output in real - time and reduce the loss degree value in the energy conversion process. Among them, by considering the influence of the temperature and wind speed in the external environment on the temperature change characteristics of the energy storage pipeline to be measured, the full analysis of the correlation degree between various influencing factors is realized, so as to reduce the misjudgment of the control of the molten salt output temperature and flow rate parameters in the energy storage process. In order to improve the accuracy of the entire characteristic factor statistics, the energy storage pipeline to be measured is divided into several sections, so as to count the temperature difference between each section in the divided pipeline sub - sections and the included angle value formed between the wind speed direction and the molten salt transportation direction in the external environment, avoiding the single - factor analysis of the external environment characteristics comprehensively belonging to the unified overall pipeline in the traditional technology. Whether the wind speed direction and the molten salt transportation direction are the same or not determines whether it has a positive or negative impact on the molten salt temperature. By combining the comprehensive effects of the above - mentioned various influencing factors on the molten salt temperature and flow rate in the energy storage pipeline to be measured, the actual required molten salt temperature and flow rate in the current period are predicted for timely adjustment, so as to reduce energy loss and improve the efficiency of the entire energy storage control work.

[0043] Specifically, step S1 includes the following sub - steps:

[0044] Obtain the energy storage pipeline to be tested that requires energy loss detection, and divide the energy storage pipeline to be tested into several equal-section segments to obtain pipeline sub-segments;

[0045] Statistically calculate the temperature difference between the ambient temperature value of the outside to which each pipeline sub-segment belongs and the molten salt temperature value of the molten salt transported by each pipeline sub-segment during the historical detection period. If the ambient temperature value is greater than or equal to the molten salt temperature value, output a positive temperature difference value; if the ambient temperature value is less than the molten salt temperature value, output a negative temperature difference value. The positive temperature difference value and the negative temperature difference value are combined into a historical characteristic factor one.

[0046] Specifically, for pipeline sub-segments (if divided into A, B, C, D, E), the positive temperature difference value and the negative temperature difference value (if the molten salt temperatures transported inside each of A, B, C, D, E are w1, w2, w3, w4, w5, and the temperature values in the outside environment where they are located are W1, W2, W3, W4, W5. For example, if the molten salt temperature in A is higher than the temperature in the outside environment, then the value of w1 - W1 is a positive influence factor, that is, greater than zero, and the prefix symbol is "+", otherwise, the value of w1 - W1 is a negative influence factor, that is, less than zero, and the prefix symbol is "-").

[0047] Specifically, step S2 includes the following sub-steps:

[0048] Obtain the wind speed value and wind direction of the outside to which each pipeline sub-segment belongs during the historical detection period. Statistically calculate the included angle value with the same orientation formed between the wind direction and the molten salt transportation direction in the pipeline sub-segment, and output a positive included angle value. Statistically calculate the included angle value with the opposite orientation formed between the wind direction and the molten salt transportation direction in the pipeline sub-segment, and output a negative included angle value. The wind speed value, the positive included angle value, and the negative included angle value are combined into a historical characteristic factor two.

[0049] Specifically, taking the positive and negative included angle values as an example (taking section A as an example, if the molten salt transportation direction is the y-axis, and if the wind speed direction is the same as the y-axis and horizontal, the included angle value is 0°, and the converted degree ratio is 1. In this case, the wind speed value and the wind speed direction have the greatest influence on the molten salt temperature. If the wind speed value is F, then the influence degree value of the wind speed on the molten salt temperature in this case is F and the prefix symbol is "+", if the wind speed direction is the same as the y-axis and there is an included angle relationship, if the included angle value is 30°, the converted degree ratio is 0.03, then the influence degree value of the wind speed on the molten salt temperature in this case is 0.03F and the prefix symbol is "+", if the wind speed direction is opposite to the y-axis and horizontal, the included angle value is 180°, the converted degree ratio is 1. In this case, the wind speed value and the wind speed direction have the greatest influence on the molten salt temperature, and the influence degree value of the wind speed on the molten salt temperature in this case is F and the prefix symbol is "-", if the wind speed direction is opposite to the y-axis and there is an included angle relationship, if the included angle value is 30°, the converted degree ratio is 0.03, then the influence degree value of the wind speed on the molten salt temperature in this case is 0.03F and the prefix symbol is "-". The same detection is carried out for sections B, C, D, and E).

[0050] Specifically, step S3 includes the following sub-steps:

[0051] Detect the historical bending degree of the bent sub-section in the pipeline sub-section during the historical detection period, and evaluate the concentration degree of the bent sub-section in the pipeline sub-section to obtain the historical section concentration degree;

[0052] Detect the molten salt temperature difference change value and the molten salt flow rate difference change value of each pipeline sub-section affected by external environmental factors during the historical detection period;

[0053] According to the molten salt temperature difference change value, historical feature factor one, historical feature factor two, and historical bending degree, respectively extract the correlation coefficients between the molten salt temperature difference change value and historical feature factor one, historical feature factor two, and historical bending degree to obtain the first set of correlation coefficients.

[0054] Specifically, such as the historical bending degree (for example, taking section A as an example, if there is a bending situation, then detect the bending angle value of section A: if the included angle value formed by the molten salt transportation direction is 120°, it is converted into a degree ratio of 0.12, which is the historical bending degree, if marked as q), the historical section concentration (if there is also a bending situation in section C, then count the continuity between section A and section C. If the positions are A "1 / 5", B "2 / 5", C "3 / 5", D "4 / 5", E "1", and the distance between A and C is one "1 / 5", then the continuity between section A and section C is "4 / 5", that is, the historical section concentration is 4 / 5), the molten salt temperature difference change value (referring to the molten salt temperature loss degree values actually belonging to each of sections A, B, C, D, and E. For example: the original molten salt transportation temperature of section A is N1, and after being affected by the external environment, the molten salt temperature changes to N2, then N1 - N2 is the molten salt temperature difference change value of section A, if it is a1, and the same detection is carried out for sections B, C, D, and E, if they are a2, a3, a4, and a5 respectively) and the molten salt flow rate difference change value (referring to the molten salt flow rate loss degree values actually belonging to each of sections A, B, C, D, and E. For example: the original molten salt flow rate of section A is V1, and after being affected by the external environment, the molten salt flow rate changes to V2, then V1 - V2 is the molten salt flow rate difference change value of section A, if it is b1, and the same detection is carried out for sections B, C, D, and E, if they are b2, b3, b4, and b5 respectively), the correlation coefficient set one (such as M = k1 * x1 + k2 * x2 + k3 * x3, where M refers to the molten salt temperature difference change value, k1 refers to the historical feature factor one, k2 refers to the historical feature factor two, k3 refers to the historical bending degree, x1 refers to the correlation coefficient between the molten salt temperature difference change value and the historical feature factor one, x2 refers to the correlation coefficient between the molten salt temperature difference change value and the historical feature factor two, x3 refers to the correlation coefficient between the molten salt temperature difference change value and the historical bending degree. Arbitrarily extract the molten salt temperature difference change value, historical feature factor one, historical feature factor two, and historical bending degree belonging to three sections from A, B, C, D, and E for data substitution, and the correlation coefficient set one can be obtained).

[0055] Specifically, step S4 includes the following sub - steps:

[0056] Detect the comprehensive molten salt temperature loss value of the to - be - measured energy storage pipeline affected by external environmental factors during the historical detection period;

[0057] According to the comprehensive molten salt temperature loss value, the molten salt temperature difference change value, and the historical section concentration, extract the correlation coefficient between the comprehensive molten salt temperature loss value and the section concentration to obtain the correlation coefficient two.

[0058] Specifically, for the comprehensive loss value of molten salt temperature (if it is H), the correlation coefficient two (e.g., H = (a1 + a2 + a3 + a4 + a5) * q * x4, where q is the historical bending degree detected above, and x4 refers to the correlation coefficient between the comprehensive loss value of molten salt temperature and the section concentration degree, and thus the correlation coefficient two can be obtained).

[0059] Specifically, step S5 includes the following sub-steps:

[0060] Detect the current characteristic factor one, current characteristic factor two, current bending degree, and current section concentration degree of the pipeline sub-section in the current period. The current characteristic factor one, current characteristic factor two, and current bending degree are combined into a preprocessing feature set;

[0061] According to the first set of correlation coefficients and the preprocessing feature set, predict the molten salt temperature loss degree to which each pipeline sub-section in the current period belongs to obtain a sub-predicted temperature loss value;

[0062] According to the second correlation coefficient, the preprocessing feature set, and the sub-predicted temperature loss value, predict the actual comprehensive loss degree of the molten salt temperature to which the pipeline sub-section in the current period belongs to obtain an actual total predicted temperature loss value;

[0063] Extract the correlation degree between the molten salt temperature difference change value and the molten salt flow rate difference change value to obtain a proportional correlation value;

[0064] According to the actual total predicted temperature loss value and the proportional correlation value, predict the actual molten salt flow rate required for the energy storage pipeline to be tested to obtain an actual predicted molten salt flow rate value;

[0065] According to the actual total predicted temperature loss value and the actual predicted molten salt flow rate value, adjust and control the operating parameters of the molten salt energy storage process, and output an energy storage control result.

[0066] Specifically, for the predicted value of temperature loss element (for example, if the current characteristic factors one, two, and the current bending degree in section A are d1, d2, and d3 respectively, substitute them into M = k1*x1 + k2*x2 + k3*x3 for calculation, and the predicted value of temperature loss element belonging to section A can be obtained. And so on, the same analysis is carried out for sections B, C, D, and E), the total predicted value of actual temperature loss (that is, substitute the predicted values of temperature loss elements predicted for sections A, B, C, D, and E respectively and the detected current section concentration into H = (a1 + a2 + a3 + a4 + a5)*q*x4 for calculation, and the total predicted value of actual temperature loss belonging to the energy storage pipeline to be measured can be obtained), the proportional correlation value (since the setting of the molten salt flow rate parameter is determined by the change of the temperature value during the molten salt transportation process. For example, calculate the ratio of the change degree value between the molten salt temperature difference change value a1 and the molten salt flow rate difference change value b1 in section A. If it is z1, and so on, the same analysis is carried out for sections B, C, D, and E. If they are z2, z3, z4, and z5 respectively, then (z1 + z2 + z3 + z4 + z5) / 5, if equal to Z, is the proportional correlation value), the predicted value of actual molten salt flow rate (if the total predicted value of actual temperature loss is H1, then H1 / Z, if equal to V0, is the predicted value of actual molten salt flow rate), and the energy storage control result (that is, according to the predicted total predicted value of actual temperature loss H1 and the predicted value of actual molten salt flow rate V0, correspondingly adjust the temperature parameter and flow rate parameter of the molten salt energy storage transportation by increasing or decreasing their values, so as to reduce the loss degree during the energy conversion process and improve the energy utilization rate).

[0067] A nuclear power energy control system based on molten salt energy storage, by applying a nuclear power energy control method based on molten salt energy storage as described above, includes a feature statistics unit one, a feature statistics unit two, a coefficient extraction unit one, a coefficient extraction unit two, and a prediction and regulation unit, referring to Figure 2, the energy storage pipeline to be measured is divided into several equal sub - sections by the feature statistics unit one to obtain pipeline sub - sections, and the temperature differences of the pipeline sub - sections belonging to the loss of the molten salt transportation process in the historical detection period are counted, and the historical feature factor one is output; the feature statistics unit two counts the included angle values formed between the wind direction of the outside of each pipeline sub - section and the molten salt transportation direction, and outputs the historical feature factor two; the coefficient extraction unit one detects the historical bending degree of the bent sub - sections in the pipeline sub - sections and the historical section concentration degree of the bending sections, and extracts the correlation coefficient one between the molten salt temperature loss value and the historical bending degree of the pipeline sub - sections according to the historical feature factor one, the historical feature factor two and the historical bending degree; the coefficient extraction unit two extracts the correlation coefficient two between the comprehensive molten salt temperature loss value of the energy storage pipeline to be measured and the historical section concentration degree; the prediction and regulation unit detects the pre - processing feature set to which the pipeline sub - sections belong in the current period, and predicts the actual molten salt temperature loss degree and the actual required flow rate of the molten salt transported in the energy storage pipeline to be measured according to the correlation coefficient set one, the correlation coefficient two and the pre - processing feature set, so as to regulate the operating parameters of the molten salt energy storage process and output the energy storage control result.

[0068] The above are all the preferred embodiments of the present application. The protection scope of the present application is not limited by this. Therefore, all equivalent changes made according to the structure, shape and principle of the present application should be covered within the protection scope of the present application.

Claims

1. A nuclear power energy control method based on molten salt energy storage, characterized in that, Including the following steps: Step S1: Divide the energy storage pipeline to be measured into several equal-section segments to obtain pipeline sub-segments, count the temperature differences of each pipeline sub-segment belonging to the molten salt transportation process loss during the historical detection period, and output the first historical characteristic factor; Step S2: Count the included angle values formed between the wind speed direction of the outside of each pipeline sub-segment and the molten salt transportation direction, and output the second historical characteristic factor; Step S3: Detect the historical bending degree of the bent sub-segments in the pipeline sub-segments and the historical segment concentration degree of the bending segments. According to the first historical characteristic factor, the second historical characteristic factor and the historical bending degree, extract the first correlation coefficient between the molten salt temperature loss value and the historical bending degree of the pipeline sub-segments; Step S4: Extract the second correlation coefficient between the comprehensive molten salt temperature loss value of the energy storage pipeline to be measured and the historical segment concentration degree; Step S5: Detect the preprocessing feature set to which the pipeline sub-segments belong in the current period. According to the first correlation coefficient set, the second correlation coefficient and the preprocessing feature set, predict the actual molten salt temperature loss degree and the actual required flow rate of the molten salt transported in the energy storage pipeline to be measured, so as to adjust the operating parameters of the molten salt energy storage process, and output the energy storage control result.

2. The method for controlling nuclear power energy based on molten salt energy storage according to claim 1, wherein Step S1 is specifically as follows: Obtain the energy storage pipeline to be measured that needs to detect energy loss, and divide the energy storage pipeline to be measured into several equal-section segments to obtain pipeline sub-segments; Count the temperature difference between the environmental temperature value of the outside of each pipeline sub-segment during the historical detection period and the molten salt temperature value of the molten salt transportation to which each pipeline sub-segment belongs. If the environmental temperature value is greater than or equal to the molten salt temperature value, output a positive temperature difference value. If the environmental temperature value is less than the molten salt temperature value, output a negative temperature difference value. The positive temperature difference value and the negative temperature difference value are combined into the first historical characteristic factor.

3. The nuclear power energy control method based on molten salt energy storage according to claim 2, characterized in that, Step S2 is specifically as follows: Obtain the wind speed value and wind speed direction of the outside of each pipeline sub-segment during the historical detection period, count the included angle value with the same direction formed between the wind speed direction and the molten salt transportation direction in the pipeline sub-segment, and output a positive included angle value. Count the included angle value with the opposite direction formed between the wind speed direction and the molten salt transportation direction in the pipeline sub-segment, and output a negative included angle value. The wind speed value, the positive included angle value and the negative included angle value are combined into the second historical characteristic factor.

4. A nuclear power energy control method based on molten salt energy storage according to claim 3, characterized in that, Step S3 is specifically as follows: Detect the historical bending degree of the bent sub-segments in the pipeline sub-segments during the historical detection period, and evaluate the concentration degree of the bent sub-segments in the pipeline sub-segments to obtain the historical segment concentration degree; Detect the molten salt temperature difference change value and the molten salt flow rate difference change value to which each pipeline sub-segment belongs after being affected by external environmental factors during the historical detection period; According to the molten salt temperature difference change value, the first historical characteristic factor, the second historical characteristic factor and the historical bending degree, respectively extract the correlation coefficients between the molten salt temperature difference change value and the first historical characteristic factor, the second historical characteristic factor, and the historical bending degree to obtain the first correlation coefficient set.

5. A nuclear power energy control method based on molten salt energy storage according to claim 4, characterized in that, Step S4 is specifically as follows: Detect the comprehensive molten salt temperature loss value to which the energy storage pipeline to be measured belongs after being affected by external environmental factors during the historical detection period; According to the comprehensive loss value of the molten salt temperature, the change value of the molten salt temperature difference, and the historical section concentration, the correlation coefficient between the comprehensive loss value of the molten salt temperature and the section concentration is extracted to obtain the second correlation coefficient.

6. The nuclear power energy control method based on molten salt energy storage according to claim 5, characterized in that, Step S5 is specifically as follows: Detect the current characteristic factor 1, current characteristic factor 2, current bending degree, and current section concentration of the pipeline sub-section in the current period. The current characteristic factor 1, current characteristic factor 2, and current bending degree are combined into a preprocessing feature set; According to the first correlation coefficient set and the preprocessing feature set, predict the molten salt temperature loss degree to which each pipeline sub-section belongs in the current period to obtain a sub-predicted temperature loss value; According to the second correlation coefficient, the preprocessing feature set, and the sub-predicted temperature loss value, predict the actual comprehensive loss degree of the molten salt temperature to which the pipeline sub-section belongs in the current period to obtain an actual total predicted temperature loss value; Extract the correlation degree between the change value of the molten salt temperature difference and the change value of the molten salt flow rate to obtain a proportional correlation value; According to the actual total predicted temperature loss value and the proportional correlation value, predict the actual molten salt flow rate required for the energy storage pipeline to be measured to obtain an actual predicted molten salt flow rate value; According to the actual total predicted temperature loss value and the actual predicted molten salt flow rate value, adjust the operating parameters of the molten salt energy storage process, and output an energy storage control result.

7. A nuclear power energy control system based on molten salt energy storage, characterized in that, The system is used to implement a nuclear power energy control method based on molten salt energy storage according to any one of claims 1-6, including: A first feature statistics unit, which is used to divide the energy storage pipeline to be measured into several equal-section segments to obtain pipeline sub-sections, and count the temperature difference of the loss in the molten salt transportation process to which each pipeline sub-section belongs in the historical detection period, and output the historical feature factor 1; A second feature statistics unit, which is used to count the included angle value formed between the wind direction outside each pipeline sub-section belongs to and the molten salt transportation direction, and output the historical feature factor 2; A first coefficient extraction unit, which is used to detect the historical bending degree of the bent sub-section in the pipeline sub-section and the historical section concentration of the bent section. According to the historical feature factor 1, historical feature factor 2, and historical bending degree, extract the first correlation coefficient between the molten salt temperature loss value of the pipeline sub-section and the historical bending degree; A second coefficient extraction unit, which is used to extract the second correlation coefficient between the comprehensive loss value of the molten salt temperature of the energy storage pipeline to be measured and the historical section concentration; A prediction and regulation unit, which is used to detect the preprocessing feature set to which the pipeline sub-section belongs in the current period. According to the first correlation coefficient set, the second correlation coefficient, and the preprocessing feature set, predict the actual molten salt temperature loss degree and the actual required flow rate during the transportation in the energy storage pipeline to be measured, so as to adjust the operating parameters of the molten salt energy storage process and output an energy storage control result.

Images