Dynamic balance adjusting method for heat supply pipe network system based on load prediction

Abstract

The invention discloses a heat supply pipe network system dynamic balance adjusting method based on load prediction, and relates to the technical field of energy engineering, the method comprises the following steps: counting simultaneous adjusting links and different adjusting links, when the operation sequence of the simultaneous adjusting links is before the operation sequence of the different adjusting links, outputting a first adjusting operation mode, and when the operation sequence is before the operation sequence of the different adjusting links, outputting a second adjusting operation mode; predicting a total load loss value of the first adjustment operation mode to obtain a first total load compensation value, outputting a second adjustment operation mode when the operation sequence of the simultaneous adjustment links is behind the operation sequence of the different simultaneous adjustment links, and predicting a total load loss value of the second adjustment operation mode to obtain a second total load compensation value; and according to the group with the minimum total load compensation value in the first total load compensation value and the second total load compensation value, a pre-used adjustment operation mode is correspondingly selected, and dynamic balance adjustment is conducted on the heat supply pipe network system. According to the heat supply pipe network system dynamic balance adjusting method based on load prediction, the efficiency of dynamic balance adjusting work can be improved.

Description

Technical Field

[0001] The present application relates to the field of energy engineering technology, and in particular to a method for dynamic balance regulation of a heating pipe network system based on load forecasting. Background Art

[0002] Dynamic balance regulation of the heating network system based on load forecasting refers to adjusting the operating parameters of the heating system by predicting the heat load to achieve supply and demand balance and stable operation in the heating network.

[0003] In the prior art, the dynamic balance adjustment of the heating pipe network system only adjusts the parameters of each load operation parameter management link according to the predicted load parameters in accordance with the original system adjustment order and method, without further considering the large error of the final overall link balance adjustment caused by different degrees of parameter loss or additional growth during the operation of each link, and ultimately fails to make corresponding changes in the adjustment order and method according to the error value that needs to be compensated for the overall operation parameters in real time, thereby reducing the efficiency of the dynamic balance adjustment of the heating pipe network system. Summary of the invention

[0004] In order to overcome the above-mentioned deficiencies of the prior art, the present application provides a dynamic balance adjustment method for a heating pipe network system based on load forecasting.

[0005] In a first aspect, the present application provides a method for dynamic balance adjustment of a heating pipe network system based on load forecasting, the method comprising: Obtaining a demand load forecast result of a user's needs, and according to the demand load forecast result, counting simultaneous adjustment links and non-simultaneous adjustment links, outputting a first adjustment operation mode when the operation sequence of the simultaneous adjustment links is before the operation sequence of the non-simultaneous adjustment links, and predicting the total load loss value of the simultaneous adjustment links in the first adjustment operation mode to obtain a first compensation load value of one; Extracting the influence degree of the load loss correlation between the non-simultaneous adjustment links and the simultaneous adjustment links in the first adjustment operation mode to obtain a first influence coefficient, and predicting the total value of the load loss in the first adjustment operation mode to obtain a first total load compensation value according to the first influence coefficient and the first compensation load value; When the operation sequence of the simultaneous adjustment link is after the operation sequence of the non-simultaneous adjustment link, a second adjustment operation mode is output, and the total value of the load loss of the non-simultaneous adjustment link in the second adjustment operation mode is predicted to obtain a second compensation load value of one; The load loss correlation influence degree between the simultaneous adjustment links and the non-simultaneous adjustment links in the second adjustment operation mode is extracted and then averaged to obtain a second influence coefficient, and the total load loss value of the second adjustment operation mode is predicted according to the second influence coefficient and the second compensation load value to obtain a second total load compensation value; A group with the smallest total load compensation value is selected from the first total load compensation value and the second total load compensation value to obtain a pre-processing total compensation value. According to the pre-processing total compensation value, a pre-use adjustment operation mode is selected, and the pre-use adjustment operation mode is implemented to perform dynamic balance adjustment on the heating pipe network system, and the dynamic balance adjustment result is output.

[0006] Preferably, a demand load forecast result of a user's needs is obtained, and according to the demand load forecast result, all links that need to be adjusted for load parameter balance are counted to obtain links to be adjusted; Classify the to-be-adjusted links into same-time adjustment links and different-time adjustment links to obtain simultaneous adjustment links and different-time adjustment links; The operation order of the simultaneous adjustment link and the non-simultaneous adjustment link is judged, and when the operation order of the simultaneous adjustment link is before the operation order of the non-simultaneous adjustment link, a first adjustment operation mode is output; Obtain a historical load database of user demand, and train a load simulation prediction model based on the historical load database; Inputting the simultaneous adjustment link and demand load forecasting results in the first adjustment operation mode into the load simulation prediction model to perform load data difference value test of each link in the simultaneous adjustment link to obtain the load difference of the first difference link; Determine whether the load differences of each difference link in the first difference link load difference are balanced. If so, output the zero compensation load value. If not, numerically integrate the load differences of each difference link in the first difference link load difference to obtain a first compensation load value one. The first compensation load value one is the result of offsetting integration or additive integration of the load differences of each difference link.

[0007] Preferably, the influence coefficient 1 is obtained by extracting the influence degree of the load loss correlation between each link in the non-simultaneous adjustment link and each differential load link in the simultaneous adjustment link; Extract the influence degree of load loss correlation between each link in different regulation links to obtain influence coefficient 2; The influence coefficient 1 and the influence coefficient 2 are summed up accordingly to obtain a first influence coefficient; According to the first influence coefficient and the first compensation load value 1, a load loss value of the first operating link in different adjustment links is predicted to obtain a first compensation load value 2; According to the load loss value 1 and the first influence coefficient, the load loss values ​​of the remaining operating links except the first operating link in different adjustment links are predicted to obtain the first compensation load value 3; The first compensation load value one, the first compensation load value two and the first compensation load value three are integrated to obtain a first total load compensation value.

[0008] Preferably, when the running order of the simultaneous adjustment link is after the running order of the non-simultaneous adjustment link, the second adjustment operation mode is output; The forecast results of the different adjustment links and demand loads in the second adjustment operation mode are input into the load simulation prediction model to perform load data difference value tests of each link in the different adjustment links to obtain the second difference link load difference, and the load differences of each difference link in the second difference link load difference are numerically integrated to obtain the second compensation load value one, which is the result of superimposed integration of the load differences of each difference link.

[0009] Preferably, the influence coefficient three is obtained by extracting the influence degree of the load loss correlation between each link in the simultaneous adjustment link and each differential load link in the non-simultaneous adjustment link; Extract the influence degree of load loss correlation between each link in the simultaneous regulation link to obtain influence coefficient 4; The influence coefficient three and the influence coefficient four are summed up to obtain a second influence coefficient; According to the second influence coefficient and the second compensation load value 1, predicting the load loss value of each operating link in the simultaneous adjustment link to obtain the second compensation load value 2; The second compensation load value 1 and the second compensation load value 2 are integrated to obtain a second total load compensation value.

[0010] Preferably, a group with the smallest total load compensation value is selected from the first total load compensation value and the second total load compensation value to obtain a preprocessing total compensation value; According to the preprocessing total compensation value, a group of regulating operation modes are selected from the first regulating operation mode and the second regulating operation mode as the regulating operation mode for best saving load loss, and the pre-use regulating operation mode is output; The demand load forecast result is preprocessed to compensate the difference of the total compensation value to obtain the actual required load forecast value; According to the actual load forecast value, a pre-adjustment operation mode is implemented to perform dynamic balance adjustment on the heating pipe network system, and a dynamic balance adjustment result is output.

[0011] Second, the dynamic balance regulation system of the heating network system based on load forecasting includes: The operation link classification unit is used to obtain the demand load prediction result of the user demand, and according to the demand load prediction result, count the simultaneous adjustment links and the non-simultaneous adjustment links, and when the operation sequence of the simultaneous adjustment links is before the operation sequence of the non-simultaneous adjustment links, output the first adjustment operation mode, and predict the total load loss value of the simultaneous adjustment links in the first adjustment operation mode to obtain a first compensation load value of one; The first load loss prediction unit is used to extract the load loss correlation influence degree between the non-simultaneous adjustment links and the simultaneous adjustment links in the first adjustment operation mode to obtain a first influence coefficient, and predict the total load loss value of the first adjustment operation mode according to the first influence coefficient and the first compensation load value to obtain a first total load compensation value; The operation mode distinction judgment unit is used to judge that when the operation sequence of the simultaneous adjustment link is after the operation sequence of the non-simultaneous adjustment link, output the second adjustment operation mode, and predict the total value of the load loss of the non-simultaneous adjustment link in the second adjustment operation mode to obtain a second compensation load value of one; A second load loss prediction unit is used to extract the load loss correlation influence degree between the simultaneous adjustment links and the non-simultaneous adjustment links in the second adjustment operation mode and then calculate the average value to obtain a second influence coefficient, and predict the total load loss value of the second adjustment operation mode according to the second influence coefficient and the second compensation load value to obtain a second total load compensation value; A dynamic balance adjustment unit is implemented to select a group of the smallest total load compensation values ​​from the first total load compensation value and the second total load compensation value to obtain a pre-processed total compensation value, and a pre-use adjustment operation mode is selected according to the pre-processed total compensation value. The pre-use adjustment operation mode is implemented to perform dynamic balance adjustment on the heating pipe network system, and the dynamic balance adjustment result is output.

[0012] Compared with the prior art, the present invention has the following characteristics and beneficial effects: The load loss value of each operating link is predicted by simulating the operating sequence of the originally set adjustment links, and the overall total load loss value is statistically analyzed. In this statistical process, it is necessary to consider the different degrees of influence of the mutual correlation of load losses between various operating links, and conduct differentiated analysis. The different operating sequences between different operating links will also lead to large differences in the overall load loss value. Two differentiated situations are mainly analyzed here, that is, according to the demand load forecast results of user needs, all operating links that need to be adjusted are classified into two major operating links at different operating time points, one is the simultaneous adjustment link and the other is the non-simultaneous adjustment link. The subsequent judgment of the operating sequence of these two major links is used to improve the impact value of the overall load loss value under various conditions. A more comprehensive consideration is given to the diverse factors that affect the error change, that is, avoiding unifying the hidden influencing factors into non-interfering information. For this reason, the errors of the operating load parameter adjustment results of each adjustment link are greatly increased. Through the above-mentioned situation-by-situation processing, it is determined which of the two dynamic balance adjustment operation modes of the heating pipe network system is the most effective and energy-saving, and the best set of operation modes is selected for the demand load forecast results of the current user needs to dynamically balance the heating pipe network system. Through the above-mentioned processing method, the degree of mutual correlation and influence between each operating link is fully considered, which further improves the efficiency of the final dynamic balance adjustment work, reduces the load loss in the overall adjustment process, and improves the prediction accuracy of the error compensation value of the adjustment load parameter value of each operating link. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a flowchart of the steps of the dynamic balance adjustment method of the heating pipe network system based on load forecasting mainly embodied in this embodiment.

[0014] Figure 2 It is a structural block diagram of the dynamic balance adjustment system of the heating network system based on load forecasting mainly embodied in this embodiment. DETAILED DESCRIPTION

[0015] The present invention is further described in detail below in conjunction with the following examples.

[0016] Reference Figure 1 A method for dynamic balance adjustment of a heating pipe network system based on load forecasting, the method comprising the following steps: S1. Obtain the demand load forecast result of the user's needs, and according to the demand load forecast result, count the simultaneous adjustment links and the non-simultaneous adjustment links. When the operation sequence of the simultaneous adjustment links is before the operation sequence of the non-simultaneous adjustment links, output the first adjustment operation mode, and predict the total load loss value of the simultaneous adjustment links in the first adjustment operation mode to obtain the first compensation load value one.

[0017] S2. Extract the correlation influence degree of load loss between non-simultaneous adjustment links and simultaneous adjustment links in the first adjustment operation mode to obtain a first influence coefficient, and predict the total load loss value of the first adjustment operation mode according to the first influence coefficient and the first compensation load value to obtain a first total load compensation value.

[0018] S3. When the operation sequence of the simultaneous adjustment link is after the operation sequence of the non-simultaneous adjustment link, a second adjustment operation mode is output, and the total load loss value of the non-simultaneous adjustment link in the second adjustment operation mode is predicted to obtain a second compensation load value of one.

[0019] S4. The load loss correlation influence degree between the simultaneous adjustment links and the non-simultaneous adjustment links in the second adjustment operation mode is extracted and the average value is calculated to obtain a second influence coefficient. According to the second influence coefficient and the second compensation load value, the total load loss value of the second adjustment operation mode is predicted to obtain a second total load compensation value.

[0020] S5. Select a group with the smallest total load compensation value from the first total load compensation value and the second total load compensation value to obtain a pre-processing total compensation value. According to the pre-processing total compensation value, select a pre-use adjustment operation mode, implement the pre-use adjustment operation mode to perform dynamic balance adjustment on the heating pipe network system, and output the dynamic balance adjustment result.

[0021] Specifically, the load loss value of each operating link is predicted by simulating the operating sequence of the originally set adjustment links, and the overall total load loss value is statistically analyzed. In this statistical process, it is necessary to consider the different degrees of mutual correlation between the load losses of various operating links, and conduct differentiated analysis. The different operating sequences between different operating links will also lead to large differences in the overall load loss value. Two differentiated situations are mainly analyzed here, that is, according to the demand load forecast results of user needs, all operating links that need to be adjusted are classified into two major operating links at different operating time points, one is the simultaneous adjustment link and the other is the non-simultaneous adjustment link. The subsequent judgment of the operating sequence of these two major links is carried out to improve the impact of various conditions on the overall load loss value. The different diverse factors that affect the change of the response value error are comprehensively considered, that is, avoiding the unification of hidden influencing factors into non-interfering information. For this reason, the errors of the operating load parameter adjustment results of each adjustment link are greatly increased. Through the above-mentioned situation-by-situation processing, it is determined which of the two dynamic balance adjustment operation modes of the heating pipe network system is the most effective and energy-saving, and the best set of operation modes is selected for the demand load forecast results of the current user needs to dynamically balance the heating pipe network system. Through the above-mentioned processing method, the degree of mutual correlation and influence between each operating link is fully considered, which further improves the efficiency of the final dynamic balance adjustment work, reduces the load loss in the overall adjustment process, and improves the prediction accuracy of the error compensation value of the adjustment load parameter value of each operating link.

[0022] The specific step S1 includes the following sub-steps: Obtain the demand load forecast results of user needs, and based on the demand load forecast results, count all links that require load parameter balance adjustment to obtain the links to be adjusted.

[0023] The links to be adjusted are classified into the links adjusted at the same time and the links adjusted at different times to obtain the links adjusted at the same time and the links adjusted at different times.

[0024] The operation order of the simultaneous adjustment link and the non-simultaneous adjustment link is judged, and when the operation order of the simultaneous adjustment link is before the operation order of the non-simultaneous adjustment link, the first adjustment operation mode is output.

[0025] Obtain the historical load database of user needs, and train a load simulation prediction model based on the historical load database.

[0026] The simultaneous adjustment links and demand load forecast results in the first adjustment operation mode are input into the load simulation prediction model to perform load data difference value tests of each link in the simultaneous adjustment link to obtain the load difference of the first difference link.

[0027] Determine whether the load differences of each difference link in the load difference of the first difference link are balanced. If so, output the zero compensation load value. If not, numerically integrate the load differences of each difference link in the load difference of the first difference link to obtain the first compensation load value one. The first compensation load value one is the result of offsetting integration or additive integration of the load differences of each difference link.

[0028] Specifically, such as the demand load forecast results of user needs (through the comprehensive analysis of historical data of the heating system, current environmental parameters and future weather forecasts, to predict future heat load demand, including the following steps: data collection and preprocessing - collect historical operation data of the heating system, including past heat load, outdoor temperature, indoor temperature, supply and return water temperature, etc., clean and preprocess the collected data, remove abnormal values ​​and outliers, and ensure the accuracy and reliability of the data; analysis of influencing factors - such as outdoor temperature, wind speed, sunshine hours, working day type (such as weekends or holidays), etc.; establish a prediction model - use multiple linear regression, BP neural network, GRNN neural network, ELMAN neural network and other algorithms to establish a heat load Load prediction model, if the value of the demand load prediction result is H0), the link to be adjusted (refers to the need to adjust all the operating links such as pipelines or gate valve parameters in the heating network system according to H0, which is understood as a path or step here. If the link to be adjusted includes: B1, B2, B3, b1, b2, b3, b4), then each operating link in the link to be adjusted will be matched with the operating load parameters set accordingly. If they are: h1, h2, h3, h4, h5, h6, h7, the simultaneous adjustment link and the non-simultaneous adjustment link (the simultaneous adjustment link refers to the operation of each operating link at the same time point - with simultaneity, on the contrary, the non-simultaneous adjustment link refers to the operation of each operating link at different time points - with There is connectivity, if B1, B2, and B3 are simultaneous adjustment links, and b1, b2, b3, and b4 are non-simultaneous adjustment links), the operation order of the simultaneous adjustment links and the non-simultaneous adjustment links is judged (due to different operation order arrangements, the load damage values ​​caused during the operation are likely to be quite different, and the degree of correlation and influence of load loss between the various operation links is also very different, so it is necessary to make a detailed judgment on the operation order in order to facilitate the differential analysis of various conditions and consider diversity), the first adjustment operation mode (B1, B2, and B3 are the first operation batch, and b1, b2, b3, and b4 are the second operation batch, and are connected after B1, B2, and B3), historical load database (including The historical demand load forecast results, the operating sequence characteristics of the historical control operation links, the historical load loss values, the correlation influence degree between the historical control operation links), the load simulation forecasting model (that is, the same as the explanation of establishing the forecasting model used in the above explanation of the demand load forecasting results of user needs, that is, using the historical load database as a training set to train a load simulation forecasting model that can predict the actual operating load parameters of each operating link, that is, the actual load parameters after loss during the operation process, if it is f1, f2, f3, f4, f5, f6, f7), the first difference link load difference (that is, the load difference between f1, f2, f3 and h1, h2, h3 respectively, if they are: c1, c2, c3),Zero compensation load value (if c1 is zero, it means that the B1 operation link has a very small loss value; if c2 is a parameter value increase, it means that the B2 operation link has an increase in the operating parameter value; if c3 is a parameter value decrease, it means that the B3 operation link has a loss. At this time, the parameter value changes between c2 and c3 are comprehensively calculated to see whether they can offset or complement each other. If c2+c3 is equal to zero, it means that the overall load loss of B1, B2, and B3 is balanced, that is, the zero compensation load value), the first compensation load value one (if c2 is greater than or less than c3, there is a difference between the two. The difference between the two is calculated. If it is Z1, it will have a correlation effect on the loss of the operating load parameters of the subsequent remaining and different adjustment links). ,

[0029] The specific step S2 includes the following sub-steps: The influence coefficient 1 is obtained by extracting the load loss correlation influence degree between each link in the non-simultaneous regulation link and each different load link in the simultaneous regulation link.

[0030] The influence coefficient 2 is obtained by extracting the correlation influence degree of load loss between each link in different regulation links.

[0031] The first influence coefficient is obtained by summing the influence coefficient one and the influence coefficient two accordingly.

[0032] According to the first influence coefficient and the first compensation load value one, the load loss value of the first operating link in different adjustment links is predicted to obtain the first compensation load value two.

[0033] According to the load loss value one and the first influence coefficient, the load loss values ​​of the remaining operating links except the first operating link in different adjustment links are predicted to obtain the first compensation load value three.

[0034] The first compensation load value one, the first compensation load value two and the first compensation load value three are integrated to obtain a first total load compensation value.

[0035] Specifically, such as influence coefficient 1 (i.e., the load loss correlation influence degree between b1, b2, b3, b4 and B2, B3 is extracted respectively. If the weight value of each operation link is used, the associated knowledge graph tree diagram can be constructed to mark the degree of correlation influence between each operation link according to the position correlation connection degree and weight value between each operation link in the constructed knowledge graph tree diagram. Here, percentage values ​​are used for identification), influence coefficient 2 (i.e., the load loss correlation influence degree between b1, b2, b3, b4 is extracted. The explanation is the same as that of influence coefficient 1, so no further explanation is given here). The influence coefficient (that is, the influence coefficients in the influence coefficient 1 and the influence coefficients in the influence coefficient 2 are numerically summed up accordingly. It should be noted that the influence coefficients in the influence coefficient 1 obtained here that belong to b1, b2, b3, b4 and B2 are the influence coefficients of the parameter increase value. "+" is used to indicate the positive direction: the load parameter increases. The influence coefficients in the influence coefficient 1 that belong to b1, b2, b3, b4 and B3 are the influence coefficients of the parameter increase value. "-" is used to indicate the negative direction: the load parameter decreases. There is a balance between the two. The first influence coefficient: for example, the influence coefficients between b1, b2, b3, b4 and B2, The influence coefficients of b1, b2, b3, and b4 are summed up respectively. Here, the influence coefficients of b1, b2, b3, and b4 are positively correlated with the influence coefficients of b1, b2, b3, and b4 with B2. Conversely, the influence coefficients of b1, b2, b3, and b4 are negatively correlated with the influence coefficients of b1, b2, b3, and b4 with B3. Finally, the influence coefficients obtained by the two summations are summed up again. At this time, the positive and negative directions can be balanced to offset part of the values, and the number that is not offset is the first influence coefficient), the first compensation load value two (that is, if b1 is the first operating link, then b1 is affected by the first compensation The parameter value changes caused by the continuous load parameter influence of load value one are estimated, for example, the influence coefficient attributable to b1 is y1, then Z1*y1=Z11, which is the compensation load value of b1, and the value of Z11 is greater than Z1), the first compensation load value three (similarly, the remaining b2, b3, and b4 run in the order after b1, then the parameter value changes caused by the influence of b2, b3, and b4 depend on the loss value of b1: Z11, and the loss values ​​of b2, b3, and b4 are summed, if it is Z12, Z12 is greater than Z11), the first total load compensation value (that is, Z1+Z11+Z12, if it is K1, it is the first total load compensation value).

[0036] The specific step S3 includes the following sub-steps: When the running sequence of the simultaneous regulating link is behind the running sequence of the non-simultaneous regulating link, the second regulating operation mode is output.

[0037] The forecast results of the different adjustment links and demand loads in the second adjustment operation mode are input into the load simulation prediction model to perform load data difference test of each link in the different adjustment links to obtain the load difference of the second difference link, and the load difference of each difference link in the second difference link load difference is numerically integrated to obtain the second compensation load value one, which is the result of superimposed integration of the load differences of each difference link.

[0038] Specifically, such as the second adjustment operation mode (that is, b1, b2, b3, b4 are the first operation batch, B1, B2, B3 are the second operation batch, and are connected to b1, b2, b3, b4), the second difference link load difference, the second compensation load value one (the explanation is the same as the first difference link load difference and the first compensation load value one. It should be noted that: if b1, b2, b3, b4 are operated in sequence, then the corresponding difference link load difference in the second difference link load difference is affected by the difference link load difference of the previous operation link in sequence, and the values ​​increase in sequence, all in the same positive or negative direction, the second compensation load value one: that is, the sum of the load data difference values ​​of b1, b2, b3, b4 is calculated, if it is Z2).

[0039] The specific step S4 includes the following sub-steps: The influence coefficient three is obtained by extracting the load loss correlation influence degree between each link in the simultaneous adjustment link and each different load link in the non-simultaneous adjustment link.

[0040] The influence coefficient four is obtained by extracting the correlation influence degree of load loss between each link in the simultaneous regulation link.

[0041] The second influence coefficient is obtained by summing up the corresponding influence coefficients of the influence coefficient three and the influence coefficient four.

[0042] According to the second influence coefficient and the second compensation load value one, the load loss value of each operating link in the simultaneous adjustment link is predicted to obtain the second compensation load value two.

[0043] The second compensation load value 1 and the second compensation load value 2 are integrated to obtain a second total load compensation value.

[0044] Specifically, such as influence coefficient three, influence coefficient four (the interpretation of influence coefficient three is the same as that of influence coefficient one, and the interpretation of influence coefficient four is the same as that of influence coefficient two. It should be noted that the influence coefficients here are all in the same positive or negative direction), the second influence coefficient (for example, the influence coefficients between B1 and B2 and B3 respectively, and the influence coefficients between B1 b1, b2, b3, and b4 are calculated in total), the second compensation load value two (that is, the parameter value changes of B1, B2, and B3 caused by the continuous load parameter of the second compensation load value one are estimated in turn. For example, the influence coefficient attributed to B1 is Y1, then Z2*Y1=Z21, which is the compensation load value of B1. The value of Z21 is greater than Z2, and so on. The same analysis is performed on B2 and B3. If Z22 and Z23 are obtained respectively, then Z21+Z22+Z23=K2, which is the second total load compensation value).

[0045] The specific step S5 includes the following sub-steps: A group of the smallest total load compensation values ​​is selected from the first total load compensation values ​​and the second total load compensation values ​​to obtain a preprocessed total compensation value.

[0046] According to the preprocessing total compensation value, a group of regulating operation modes are selected from the first regulating operation mode and the second regulating operation mode as the regulating operation mode for best saving load loss, and the pre-use regulating operation mode is output.

[0047] The demand load forecast result is preprocessed and the difference compensation of the total compensation value is compensated to obtain the actual required load forecast value.

[0048] According to the actual load forecast value, the pre-adjustment operation mode is implemented to dynamically balance the heating pipe network system and output the dynamic balance adjustment result.

[0049] Specifically, such as the pre-processing total compensation value (if the value of K1 is less than K2, K1 is the pre-processing total compensation value), the pre-adjustment operation mode (that is, the first adjustment operation mode: B1, B2, B3 are the first operation batch, b1, b2, b3, b4 are the second operation batch, and are connected to B1, B2, B3), the actual required load forecast value (that is, H0+K1=H1, the dynamic balance adjustment result: that is, the corresponding operation parameters h1, h2, h3, h4, h5, h6, and h7 are adjusted: according to the original quota allocation rules of each link operating parameter, h1, h2, h3, h4, h5, h6, and h7 are compensated for the difference in turn. If the difference compensation is h11, h12, h13, h14, h15, h16, and h17, finally B1, B2, B3, b1, b2, b3, and b4 operate the heating network system according to their adjusted operating parameters h11, h12, h13, h14, h15, h16, and h17.

[0050] The dynamic balance regulation system of the heating pipe network system based on load prediction, by applying the dynamic balance regulation method of the heating pipe network system based on load prediction as mentioned above, includes an operation link classification unit, a load loss first prediction unit, an operation mode distinction judgment unit, a load loss second prediction unit and a dynamic balance regulation unit, referring to Figure 2, obtain the demand load forecast result of the user's demand through the operation link classification unit, and according to the demand load forecast result, count the simultaneous adjustment links and the non-simultaneous adjustment links. When the operation sequence of the simultaneous adjustment links is before the operation sequence of the non-simultaneous adjustment links, output the first adjustment operation mode, and predict the total load loss of the simultaneous adjustment links in the first adjustment operation mode to obtain a first compensation load value of one; extract the load loss correlation influence degree between the non-simultaneous adjustment links and the simultaneous adjustment links in the first adjustment operation mode through the load loss first prediction unit to obtain a first influence coefficient, and predict the total load loss value of the first adjustment operation mode according to the first influence coefficient and the first compensation load value of one to obtain a first total load compensation value; judge through the operation mode distinction judgment unit that when the operation sequence of the simultaneous adjustment links is before the operation sequence of the non-simultaneous adjustment links, the load loss of the first adjustment operation mode is less than the total load compensation value. After the sequence, the second regulating operation mode is output, and the total load loss value of the non-simultaneous regulating links in the second regulating operation mode is predicted to obtain a second compensation load value one; the second load loss second prediction unit extracts the load loss correlation influence degree between the simultaneous regulating links and the non-simultaneous regulating links in the second regulating operation mode, and then calculates the average value to obtain the second influence coefficient; according to the second influence coefficient and the second compensation load value one, the total load loss value of the second regulating operation mode is predicted to obtain the second total load compensation value; by implementing the dynamic balance adjustment unit, a group with the smallest total load compensation value is selected from the first total load compensation value and the second total load compensation value to obtain a pre-processing total compensation value; according to the pre-processing total compensation value, a pre-use regulating operation mode is selected, and the pre-use regulating operation mode is implemented to perform dynamic balance adjustment on the heating pipe network system, and the dynamic balance adjustment result is output.

[0051] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A dynamic balance adjustment method for a heating network system based on load forecasting, characterized in that: The following steps are involved: Obtaining a demand load forecast result of a user's needs, and according to the demand load forecast result, counting simultaneous adjustment links and non-simultaneous adjustment links, outputting a first adjustment operation mode when the operation sequence of the simultaneous adjustment links is before the operation sequence of the non-simultaneous adjustment links, and predicting the total load loss value of the simultaneous adjustment links in the first adjustment operation mode to obtain a first compensation load value of one; Extracting the influence degree of the load loss correlation between the non-simultaneous adjustment links and the simultaneous adjustment links in the first adjustment operation mode to obtain a first influence coefficient, and predicting the total value of the load loss in the first adjustment operation mode to obtain a first total load compensation value according to the first influence coefficient and the first compensation load value; When the operation sequence of the simultaneous adjustment link is after the operation sequence of the non-simultaneous adjustment link, a second adjustment operation mode is output, and the total value of the load loss of the non-simultaneous adjustment link in the second adjustment operation mode is predicted to obtain a second compensation load value of one; The load loss correlation influence degree between the simultaneous adjustment links and the non-simultaneous adjustment links in the second adjustment operation mode is extracted and then averaged to obtain a second influence coefficient, and the total load loss value of the second adjustment operation mode is predicted according to the second influence coefficient and the second compensation load value to obtain a second total load compensation value; A group with the smallest total load compensation value is selected from the first total load compensation value and the second total load compensation value to obtain a pre-processing total compensation value. According to the pre-processing total compensation value, a pre-use adjustment operation mode is selected, and the pre-use adjustment operation mode is implemented to perform dynamic balance adjustment on the heating pipe network system, and the dynamic balance adjustment result is output.

2. The method for dynamic balance adjustment of a heating pipe network system based on load forecasting according to claim 1 is characterized in that: The steps are as follows: Obtaining a demand load forecast result of a user's needs, and according to the demand load forecast result, counting all links that require load parameter balance adjustment to obtain links to be adjusted; Classify the to-be-adjusted links into same-time adjustment links and different-time adjustment links to obtain simultaneous adjustment links and different-time adjustment links; The operation order of the simultaneous adjustment link and the non-simultaneous adjustment link is judged, and when the operation order of the simultaneous adjustment link is before the operation order of the non-simultaneous adjustment link, a first adjustment operation mode is output; Obtain a historical load database of user demand, and train a load simulation prediction model based on the historical load database; Inputting the simultaneous adjustment link and demand load forecasting results in the first adjustment operation mode into the load simulation prediction model to perform load data difference value test of each link in the simultaneous adjustment link to obtain the load difference of the first difference link; Determine whether the load differences of each difference link in the first difference link load difference are balanced. If so, output the zero compensation load value. If not, numerically integrate the load differences of each difference link in the first difference link load difference to obtain a first compensation load value one. The first compensation load value one is the result of offsetting integration or additive integration of the load differences of each difference link.

3. The method for dynamic balance adjustment of a heating pipe network system based on load forecasting according to claim 2 is characterized in that: The steps are as follows: Extracting the influence degree of load loss correlation between each link in the non-simultaneous adjustment link and each differential load link in the simultaneous adjustment link to obtain an influence coefficient of one; Extract the influence degree of load loss correlation between each link in different regulation links to obtain influence coefficient 2; The influence coefficient 1 and the influence coefficient 2 are summed up accordingly to obtain a first influence coefficient; According to the first influence coefficient and the first compensation load value 1, a load loss value of the first operating link in different adjustment links is predicted to obtain a first compensation load value 2; According to the load loss value 1 and the first influence coefficient, the load loss values ​​of the remaining operating links except the first operating link in different adjustment links are predicted to obtain the first compensation load value 3; The first compensation load value one, the first compensation load value two and the first compensation load value three are integrated to obtain a first total load compensation value.

4. The method for dynamic balance adjustment of a heating pipe network system based on load forecasting according to claim 3 is characterized in that: The steps are as follows: When the running order of the simultaneous adjustment link is after the running order of the non-simultaneous adjustment link, the second adjustment operation mode is output; The forecast results of the different adjustment links and demand loads in the second adjustment operation mode are input into the load simulation prediction model to perform load data difference value tests of each link in the different adjustment links to obtain the load difference of the second difference link, and the load differences of each difference link in the second difference link load difference are numerically integrated to obtain the second compensation load value one, which is the result of superimposed integration of the load differences of each difference link.

5. The method for dynamic balance adjustment of a heating pipe network system based on load forecasting according to claim 4 is characterized in that: The steps are as follows: The influence coefficient three is obtained by extracting the influence degree of load loss correlation between each link in the simultaneous regulation link and each differential load link in the non-simultaneous regulation link; Extract the influence degree of load loss correlation between each link in the simultaneous regulation link to obtain influence coefficient 4; The influence coefficient three and the influence coefficient four are summed up to obtain a second influence coefficient; According to the second influence coefficient and the second compensation load value 1, predicting the load loss value of each operating link in the simultaneous adjustment link to obtain the second compensation load value 2; The second compensation load value 1 and the second compensation load value 2 are integrated to obtain a second total load compensation value.

6. The method for dynamic balance adjustment of a heating pipe network system based on load forecasting according to claim 5 is characterized in that: The steps are as follows: Selecting a group with the smallest total load compensation value from the first total load compensation value and the second total load compensation value to obtain a preprocessing total compensation value; According to the preprocessing total compensation value, a group of regulating operation modes are selected from the first regulating operation mode and the second regulating operation mode as the regulating operation mode for best saving load loss, and the pre-use regulating operation mode is output; The demand load forecast result is preprocessed to compensate the difference of the total compensation value to obtain the actual required load forecast value; According to the actual load forecast value, a pre-adjustment operation mode is implemented to perform dynamic balance adjustment on the heating pipe network system, and a dynamic balance adjustment result is output.

7. A dynamic balance regulation system for a heating network system based on load forecasting, characterized in that: The system is used to implement the dynamic balance adjustment method of the heating pipe network system based on load forecasting according to any one of claims 1 to 6, comprising: The operation link classification unit is used to obtain the demand load prediction result of the user demand, and according to the demand load prediction result, count the simultaneous adjustment links and the non-simultaneous adjustment links, and when the operation sequence of the simultaneous adjustment links is before the operation sequence of the non-simultaneous adjustment links, output the first adjustment operation mode, and predict the total load loss value of the simultaneous adjustment links in the first adjustment operation mode to obtain a first compensation load value of one; The first load loss prediction unit is used to extract the load loss correlation influence degree between the non-simultaneous adjustment links and the simultaneous adjustment links in the first adjustment operation mode to obtain a first influence coefficient, and predict the total load loss value of the first adjustment operation mode according to the first influence coefficient and the first compensation load value to obtain a first total load compensation value; The operation mode distinction judgment unit is used to judge that when the operation sequence of the simultaneous adjustment link is after the operation sequence of the non-simultaneous adjustment link, output the second adjustment operation mode, and predict the total value of the load loss of the non-simultaneous adjustment link in the second adjustment operation mode to obtain a second compensation load value of one; A second load loss prediction unit is used to extract the load loss correlation influence degree between the simultaneous adjustment links and the non-simultaneous adjustment links in the second adjustment operation mode and then calculate the average value to obtain a second influence coefficient, and predict the total load loss value of the second adjustment operation mode according to the second influence coefficient and the second compensation load value to obtain a second total load compensation value; A dynamic balance adjustment unit is implemented to select a group of the smallest total load compensation values ​​from the first total load compensation value and the second total load compensation value to obtain a pre-processed total compensation value, and a pre-use adjustment operation mode is selected according to the pre-processed total compensation value. The pre-use adjustment operation mode is implemented to perform dynamic balance adjustment on the heating pipe network system, and the dynamic balance adjustment result is output.

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