Multi-water-tank peak-shaving and storage system and method

Abstract

This invention provides a multi-tank peak-shaving and water storage system and method, relating to the field of water tank storage technology. The system includes: collecting water tank data and real-time pipeline flow rate, and processing this data to obtain the peak water usage period, real-time water age, and predicted water consumption for future periods for each water tank; processing the real-time pipeline flow rate under each storage area, the predicted water consumption of each water tank, the peak water usage period, the real-time liquid level, and the real-time water age to obtain the storage high liquid level for each water tank during peak water usage periods, the off-peak high liquid level during off-peak water usage periods, and the valve-opening water intake period; controlling the corresponding water tank to fill to the storage high liquid level when the real-time liquid level reaches a preset minimum liquid level during the valve-opening water intake period or during peak water usage periods, and controlling the corresponding water tank to fill to the off-peak high liquid level when the real-time liquid level does not reach the preset minimum liquid level during the valve-opening water intake period or during off-peak water usage periods. The beneficial effect is to prevent artificially created peak periods caused by scheduling based solely on the data characteristics of a single water tank.

Description

Technical Field

[0001] This invention relates to the field of water tank regulation technology, and in particular to a multi-tank peak-shaving regulation system and method. Background Technology

[0002] In recent years, with the increase in population density and the proliferation of high-rise buildings in cities, the construction and renovation of secondary water supply equipment have also increased. During this process, the following problems with traditional secondary water supply systems can be easily identified: 1. Many water tanks are not fully utilized. Some city water tanks have large storage capacity, which could effectively improve the stability of water output from water plants, but due to unreasonable regulation, their regulatory role is not fully realized; 2. Excessive water age. Many large water tanks store too much water, resulting in excessive hydraulic retention time, leading to reduced residual chlorine and yellowing water; 3. A large number of water tanks filling during peak periods can easily lead to insufficient pressure in the direct supply area or surrounding areas; 4. To ensure sufficient pressure at the most unfavorable point, dispatchers often increase the outlet pressure of water plants or regional booster pump stations. However, such insufficiently targeted solutions not only cause a significant increase in energy consumption but may also increase the possibility of pipeline leaks and bursts.

[0003] To address the above issues, there are currently three main solutions for peak-shaving and water storage regulation:

[0004] The first method involves using manual means to estimate the approximate peak time based on the water usage patterns of individual water tanks, and directly setting the water tank's filling time so that the tank fills with water within a fixed period until it reaches the maximum liquid level. Although this can solve the problem of insufficient pressure in the direct supply area caused by water filling during peak periods, what truly affects the pressure of the municipal pipe network is the peak period of the municipal pipe network, not the peak period of the water tank, meaning that it does not solve the problem of municipal pipe network pressure.

[0005] The second approach is to directly modify the water tank structure to make the tank large enough. Based on the water usage patterns of individual tanks, the peak water usage time can be estimated, water can be introduced during peak periods, and the water outlet structure can be modified to correspond to different instantaneous flow rates at different water demands. This can alleviate the problems of insufficient water supply and easy pipe breakage during peak periods. However, this will lead to increased costs and significantly increase the duration of disruption to residents' normal water use during the renovation period.

[0006] The third method involves determining peak periods based on the water usage patterns of individual water tanks. Water is introduced during peak periods according to fixed high and low water levels in the tanks, and then introduced again when water usage is insufficient during or after peak periods to reduce the inflow during peak times and alleviate the problem of insufficient pressure on the municipal water supply network during peak periods. In addition, valve opening control is implemented, with the valves fully open during off-peak periods. If water is still needed during peak periods, the valve opening is adjusted according to the inflow volume to maintain a balance between inflow and outflow during peak periods, preventing excessive competition for municipal water supply. A water quality monitoring system is also added to disinfect the water tanks when water quality is poor. This scheme only analyzes the peak period of a single water tank, without calculating the peak water consumption, making it impossible to reasonably control the water storage. Furthermore, the water intake logic, which relies on fixed high and low water levels and only replenishes water when water demand is insufficient during or after peak periods, is limited to a single tank and does not consider the situation of multiple tanks. Adjusting water storage based solely on the water consumption patterns of a single tank may lead to too many tanks simultaneously replenishing water in a certain area, resulting in excessive instantaneous flow in the pipe network and causing peak periods to occur earlier, creating new artificial peak periods. Additionally, starting water storage at a fixed low level and stopping at a fixed high level may result in excessively long hydraulic retention times, causing water quality problems such as reduced residual chlorine and yellowing of the water. Adding a water quality monitoring system further increases the difficulty and cost of retrofitting old secondary water supply tanks.

[0007] Based on the above issues, a reasonable peak-shaving and water storage strategy needs to be adopted to ensure that the water tank draws water from the municipal pipeline network during off-peak periods. This strategy should take into account both the optimal pipeline pressure and the water age of the tank, so that the water intake of the tank is more reasonable and can better guarantee the normal and safe water use of residents. Summary of the Invention

[0008] To address the problems existing in the prior art, the present invention provides a multi-tank peak-shaving and storage system, comprising:

[0009] At least one peak-shaving and storage control cabinet, each of which is connected to at least one water tank, is used to collect water tank data and real-time pipeline flow of the municipal pipeline network where the water tank is located, and to process the water tank data to obtain the peak water period, real-time water age and predicted water consumption for future periods for each water tank.

[0010] The peak-shaving and storage platform is connected to each of the peak-shaving and storage control cabinets. It is used to process the pre-divided multiple storage zones, the real-time pipeline flow under each storage zone, the predicted water consumption of each water tank, the peak period of the water tank, the real-time liquid level, and the real-time water age to obtain the storage high liquid level of each water tank during the peak water consumption period, the non-peak period high liquid level during the non-peak water consumption period, and the valve opening water intake period.

[0011] The peak-shaving and storage control cabinet is also used to control the corresponding water tank to fill with water until the real-time liquid level reaches the storage high level when the real-time liquid level reaches the preset minimum liquid level during the valve opening water inlet period or the peak water usage period, and to control the corresponding water tank to fill with water until the real-time liquid level reaches the off-peak period high level when the real-time liquid level reaches the preset minimum liquid level outside the valve opening water inlet period or the off-peak water usage period.

[0012] Preferably, each of the water tanks is equipped with a level gauge, and each of the water tanks is equipped with an inlet flow meter and an outlet flow meter respectively at its inlet and outlet. Each of the water tanks is connected to a municipal pipeline network with a municipal pipeline network flow meter for collecting the real-time pipeline network flow. An electric regulating valve is also provided between the inlet of each water tank and the corresponding inlet flow meter.

[0013] The water tank data includes the real-time liquid level, real-time inflow rate, and real-time outflow rate of the water tank.

[0014] The peak-shaving and water storage platform controls the opening of the electric regulating valve to control the water intake of the corresponding water tank.

[0015] Preferably, the peak-shaving and storage control cabinet includes:

[0016] The data acquisition and control module is used to periodically acquire the real-time liquid level, real-time inflow rate and real-time outflow rate of each water tank according to a preset time interval;

[0017] The first processing module, connected to the acquisition and control module, is used to calculate the difference between the real-time outflow rate corresponding to the end time and the start time of each preset time interval as the cumulative flow rate difference.

[0018] The second processing module, connected to the first processing module, is used to acquire data on factors affecting the cumulative flow difference, filter the data on factors affecting the cumulative flow difference, and then input the filtered data on factors affecting the cumulative flow difference into a pre-trained water consumption prediction model to obtain the predicted water consumption for each preset time interval in the next day.

[0019] The third processing module, connected to the first processing module, is used to process the cumulative flow difference to obtain the peak period of each day, and to take the intersection of the peak periods of each day to obtain the peak period of each water tank.

[0020] Preferably, the peak-shaving and storage control cabinet further includes:

[0021] The fourth processing module, connected to the acquisition and control module, is used to estimate the initial water age of each water tank before it is connected to the system based on the real-time liquid level, and to calculate the real-time water age based on the initial water age, the real-time liquid level, and the real-time inflow rate.

[0022] Preferably, the third processing module includes:

[0023] The sorting unit is used to sort the cumulative traffic differences of each day in chronological order to obtain a traffic difference queue, and to calculate the sum of all the cumulative traffic differences in the traffic difference queue to obtain the total daily traffic difference.

[0024] The extraction unit, connected to the sorting unit, is used to sequentially calculate the proportion of the cumulative traffic difference in the traffic difference queue to the total daily traffic difference, and add consecutive cumulative traffic differences with a proportion not less than a preset threshold to the same peak set. The earliest start time of the preset time interval associated with the cumulative traffic difference in each peak set is taken as the start time of the corresponding peak period, and the latest end time is taken as the end time of the peak period.

[0025] Preferably, the peak-shaving and water storage platform includes:

[0026] The area management module is used to perform network topology analysis on the municipal pipeline network to divide the water tanks belonging to the same main pipeline network into the same storage area.

[0027] The peak period processing module is connected to the area management module and is used to obtain the peak period of the municipal pipeline network corresponding to each of the storage areas based on the real-time pipeline network flow under each storage area.

[0028] The regulation and scheduling module is connected to the peak period processing module and the area management module, respectively. It is used to obtain the peak period water consumption of each water tank based on the peak period of the pipeline network under each regulation and storage area, the predicted water consumption of each water tank, and the peak period processing of the water tank. It also obtains the regulation and storage high liquid level of each water tank during the peak water consumption period, the non-peak period high liquid level during the non-peak water consumption period, and the valve opening water intake period based on the peak period water consumption, the predicted water consumption, the real-time liquid level, and the real-time water age.

[0029] Preferably, the storage and scheduling module includes:

[0030] A water consumption processing unit is used to compare the peak period of each water tank with the peak period of the corresponding water storage area to obtain a reasonable peak period for each water tank, and to use the predicted water consumption corresponding to the reasonable peak period as the peak period water consumption for each water tank.

[0031] Preferably, the storage and scheduling module further includes:

[0032] The water tank scheduling unit is used to compare the peak water consumption of each water tank with the effective volume of the water tank, and when the effective volume is not greater than the peak water consumption, it uses a genetic algorithm to process the predicted water consumption, the real-time liquid level, and the real-time water age to obtain the storage high liquid level of each water tank during the peak water consumption period and the valve opening and water inlet period of the electric regulating valve.

[0033] Preferably, the storage and scheduling module further includes:

[0034] The high liquid level determination unit is used to take the time period other than each of the reasonable peak periods as the non-peak water usage period of each water tank, and take the predicted water usage corresponding to the non-peak water usage period as the non-peak water usage of each water tank. Then, based on the non-peak water usage and the real-time water age, a genetic algorithm is used to process and obtain the non-peak high liquid level of the non-peak water usage period.

[0035] The present invention also provides a multi-tank peak-shaving and storage method, applied to the above-mentioned multi-tank peak-shaving and storage system, the multi-tank peak-shaving and storage method comprising:

[0036] Step S1: The multi-tank peak-shaving and storage system collects the water tank data of the water tanks and the real-time pipeline flow of the municipal pipeline network where the water tanks are located, and processes the water tank data to obtain the peak water period, real-time water age and predicted water consumption for future periods for each water tank.

[0037] Step S2: The multi-tank peak-shaving storage system processes the pre-divided storage zones, the real-time pipeline flow rate under each storage zone, the predicted water consumption of each tank, the peak period of the tank, the real-time liquid level, and the real-time water age to obtain the storage high liquid level of each tank during the peak water consumption period, the off-peak high liquid level during the off-peak water consumption period, and the valve opening water intake period.

[0038] Step S3: When the real-time liquid level of the multi-tank staggered peak storage system reaches the preset minimum liquid level during the valve opening water inlet period or the peak water usage period, the system controls the corresponding water tank to inlet water until the real-time liquid level reaches the storage high liquid level. When the real-time liquid level reaches the preset minimum liquid level outside the valve opening water inlet period or the non-peak water usage period, the system controls the corresponding water tank to inlet water until the real-time liquid level reaches the non-peak period high liquid level.

[0039] The above technical solution has the following advantages or beneficial effects:

[0040] 1) Divide the storage and regulation areas according to the pipeline network structure, and calculate the peak period of the pipeline network according to the water consumption pattern under the storage and regulation area. In this way, the peak period of the pipeline network and the peak period of the water tank can be comprehensively considered when staggering the peak storage and regulation, thereby solving the problem of insufficient pressure in the direct supply area during the peak period due to the water tank entering during the peak period.

[0041] 2) Instead of using a fixed high liquid level, the high liquid level for peak water use is determined based on the actual water usage of the water tank and the water demand during peak periods. This ensures that the water inflow into the water tank is within a reasonable range, preventing the water age from becoming too high and the water quality from deteriorating due to excessive water intake.

[0042] 3) By collecting water tank data for each storage area and combining it with the instantaneous flow rate of the pipeline network, the water tanks in each storage area are scheduled to prevent artificial peak periods caused by scheduling based solely on the data characteristics of a single water tank.

[0043] 4) In terms of hardware, it is only necessary to modify the existing structure of the water tank and professional instruments, such as adding flow meters or level gauges, and adding a peak-shaving and storage control cabinet instead of rebuilding the existing water tank, which saves costs and reduces modification time. Attached Figure Description

[0044] Figure 1 A schematic diagram of a multi-tank peak-shaving and storage system is shown in a preferred embodiment of the present invention.

[0045] Figure 2 A preferred embodiment of the present invention is shown in the overall architecture diagram of the multi-tank peak-shaving and storage system.

[0046] Figure 3 This is a schematic diagram of the water tank after hardware modification, which is a preferred embodiment of the present invention.

[0047] Figure 4 This is a flowchart illustrating a multi-tank peak-shaving and storage method, which is a preferred embodiment of the present invention. Detailed Implementation

[0048] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. The present invention is not limited to this embodiment; other embodiments that conform to the spirit of the present invention may also fall within the scope of the present invention.

[0049] In a preferred embodiment of the present invention, based on the above-mentioned problems existing in the prior art, a multi-tank peak-shaving and storage system is provided, such as... Figure 1 As shown, it includes:

[0050] At least one peak storage control cabinet 1, each peak storage control cabinet 1 is connected to at least one water tank 2, used to collect water tank data of water tank 2 and real-time pipeline flow of municipal pipeline where water tank 2 is located, and to process the water tank data to obtain the peak water period, real-time water age and predicted water consumption for future periods of each water tank.

[0051] The peak-shaving storage platform 3 is connected to each peak-shaving storage control cabinet 1. It is used to process the pre-divided multiple storage areas, the real-time pipeline flow under each storage area, the predicted water consumption of each water tank 2, the peak period of the water tank, the real-time liquid level, and the real-time water age to obtain the storage high liquid level of each water tank 2 during the peak water consumption period, the non-peak period high liquid level during the non-peak water consumption period, and the valve opening water intake period.

[0052] The staggered peak storage control cabinet 1 is also used to control the corresponding water tank 2 to fill with water until the real-time liquid level reaches the storage high level when the real-time liquid level reaches the preset minimum liquid level during the valve opening water inlet period or the peak water usage period, and to control the corresponding water tank 2 to fill with water until the real-time liquid level reaches the off-peak period high level when the real-time liquid level reaches the preset minimum liquid level outside the valve opening water inlet period or the off-peak water usage period.

[0053] Specifically, in this embodiment, as Figure 2 As shown, a peak storage control cabinet 1 can be connected to one or more water tanks 2. The data from each peak storage control cabinet 1 is finally collected into the peak storage platform 3 for peak storage scheduling. Preferably, each peak-shaving and water storage control cabinet 1 can be equipped with an edge gateway and a PLC connected to the edge gateway. The PLC is mainly responsible for communicating with each connected water tank 2 to collect water tank data and control the water inlet of the water tank 2. The water tank data collected by the PLC is sent to the edge gateway for processing to obtain the peak water period, real-time water age, and predicted water consumption for future periods for each water tank. Then, the edge gateway sends the peak water period, real-time water age, and predicted water consumption for future periods for each water tank to the peak-shaving and water storage platform 3 for peak-shaving and water storage scheduling, to obtain the high water level of each water tank 2 during peak water consumption periods, the high water level during off-peak periods during non-peak water consumption periods, and the valve opening water inlet period. Then, the edge gateway returns the high water level of each water tank 2 during peak water consumption periods, the high water level during off-peak periods during non-peak water consumption periods, and the valve opening water inlet period to the PLC for water inlet control.

[0054] By integrating an edge gateway into the peak-shaving and storage control cabinet 1, the processing of underlying water tank data can be performed at the edge gateway. The scheduling algorithm for multiple water tanks is then combined and performed on the peak-shaving and storage platform 3, making the calculation more efficient. At the same time, if the communication between the peak-shaving and storage control cabinet 1 and the peak-shaving and storage platform 3 is interrupted due to network instability or network interruption, the peak-shaving and storage control cabinet 1 can still guide the next storage based on the stored high liquid level of each water tank 2 during peak water use, high liquid level during off-peak periods during off-peak periods, and valve opening water inlet periods, ensuring the stability of system operation.

[0055] In a preferred embodiment of the present invention, such as Figure 3 As shown, each water tank 2 is equipped with a level gauge 4, and each water tank 2 is equipped with an inlet flow meter 5 and an outlet flow meter 6 at its inlet and outlet, respectively. Each water tank 2 is connected to a municipal pipeline network with a municipal pipeline network flow meter 7 for collecting real-time pipeline network flow. An electric regulating valve 8 is also provided between the inlet of each water tank and the corresponding inlet flow meter 5.

[0056] The water tank data includes the real-time liquid level, real-time inflow rate, and real-time outflow rate.

[0057] The peak-shaving and storage platform 3 controls the opening of the electric regulating valve 8 to control the water intake of the corresponding water tank 2.

[0058] In a preferred embodiment of the present invention, the peak-shaving and storage control cabinet 1 includes:

[0059] The data acquisition and control module 11 is used to periodically collect the real-time liquid level, real-time inflow rate and real-time outflow rate of each water tank according to a preset time interval.

[0060] The first processing module 12 is connected to the acquisition and control module 11 and is used to calculate the difference between the real-time outflow rate corresponding to the end time and the start time of each preset time interval as the cumulative flow rate difference.

[0061] The second processing module 13 is connected to the first processing module 12. It is used to obtain the data of factors affecting the cumulative flow difference, filter the data of factors, and then input the filtered data of factors and each cumulative flow difference into the pre-trained water consumption prediction model to obtain the predicted water consumption for each preset time interval in the next day.

[0062] The third processing module 14 is connected to the first processing module 12. It is used to process the daily peak period based on the cumulative flow difference and take the intersection of the peak periods of each day to obtain the peak period of each water tank.

[0063] Specifically, in this embodiment, the aforementioned preset time interval can be customized according to requirements. For example, if the preset time interval is 15 minutes, it means that the data acquisition control module 11 uses a 15-minute interval for collecting water tank data, thus collecting 96 data points per day. Preferably, the first data point of the day represents the water tank data from 23:45 of the previous day to 00:00 of today, the second data point represents the water tank data from 00:00 of today to 00:15 of today, and so on. The cumulative flow difference corresponding to the first data point is the difference between the real-time outflow rate collected at 00:00 of today and the real-time outflow rate collected at 23:45 of the previous day, and so on. Therefore, when the data acquisition interval is 15 minutes, there are also 96 data points for the cumulative flow difference in a day. Similarly, the predicted water consumption obtained by the water consumption prediction model is the predicted water consumption every 15 minutes of the future day, with 96 data points per day. The predicted water consumption corresponding to the first data point is the predicted water consumption from 23:45 of today to 00:00 of tomorrow, and so on.

[0064] Furthermore, before water consumption prediction, the process includes preprocessing the collected real-time liquid level, real-time inflow rate, and real-time outflow rate, including but not limited to supplementing missing data and eliminating extreme and noisy data. It also includes preprocessing abnormal data, including but not limited to extracting abnormal time points, determining whether historical prediction data exists for those abnormal time points, and if so, using those historical prediction data to fill the abnormal data; otherwise, using the average water consumption data from the two hours preceding those abnormal time points to fill the abnormal data.

[0065] Simultaneously, data on influencing factors are acquired, including but not limited to weather factor data, holiday factor data, and special event factor data. Weather factor data includes temperature, humidity, and precipitation data. Holiday factor data includes data on whether it is a workday, a rest day, or a major holiday. Special event factor data includes factors that increase water consumption, such as large-scale events requiring large amounts of water, and factors that decrease water consumption, such as a large number of people returning to their hometowns from a first-tier city during the Spring Festival, at which time the water consumption in that first-tier city will decrease rapidly.

[0066] After preprocessing the collected data, Pearson correlation analysis and Granger causality test were performed on the cumulative flow difference and influencing factor data. Based on the corresponding Granger causality test, it was determined whether the preprocessed influencing factor data and the cumulative flow difference were lagged. If so, the corresponding preprocessed influencing factor data was added to the relevant dataset as the filtered influencing factor data, and the preprocessed influencing factor data in the relevant dataset was used as exogenous variable data. If not, the process was terminated.

[0067] Specifically, the results of the Pearson correlation analysis mentioned above include the correlation coefficient r and the significance level p, wherein the formula for calculating the correlation coefficient r is as follows:

[0068]

[0069] Among them, X i Y is used to represent influencing factor data. i Used to represent the cumulative flow difference. Used to represent the mean of influencing factor data. The mean of the cumulative flow difference is used to represent the correlation coefficient r, which indicates that:

[0070] 0.8 < r ≤ 1.0: extremely strong correlation; 0.6 < r ≤ 0.8: strong correlation; 0.4 < r ≤ 0.6: moderate correlation; 0.2 < r ≤ 0.4: weak correlation; 0 ≤ r ≤ 0.2: extremely weak correlation or no correlation.

[0071] The null hypothesis H0 for the significance level p is R=0, which means there is no linear relationship between the two variables. The results represent: p<0.05: the two data are significantly related; p≥0.05: the two data are not related.

[0072] Furthermore, the Granger causality test described above incorporates all the information about the prediction of each variable, including the cumulative flow difference y and the influencing factor data x, into the time series of these variables, and tests the following regression estimate:

[0073]

[0074]

[0075] Among them, white noise u 1t and u 2t The above two equations assume that the values ​​are uncorrelated, and both assume that the current value is related to itself and other past values, thus obtaining the lagged correlation between the two.

[0076] Based on the calculation results of the above formula, data on strongly correlated influencing factors are included in the exogenous variables. The cumulative flow difference and the exogenous variable data are used together as input to the neural network for training to obtain a water consumption prediction model. In this embodiment, a single-layer Long Short-Term Memory (LSTM) artificial neural network is selected as the main structure of the neural network. Finally, the water consumption data for the next day is predicted based on the training results of the neural network, i.e., a total of 288 data points. Furthermore, since the constructed water consumption prediction model has a large time interval in the predicted data, the error will be amplified during prediction. Therefore, a cyclic prediction method is adopted, which integrates the results of each prediction with the previous data as the input data for the next prediction, thereby effectively reducing the prediction error.

[0077] Furthermore, it also includes processing the daily peak periods based on the cumulative flow differences using the third processing module 14, and taking the intersection of the peak periods of each day to obtain the peak periods of each water tank. Specifically, the third processing module 14 includes:

[0078] The sorting unit 141 is used to sort the cumulative traffic differences of each day in chronological order to obtain a traffic difference queue, and to calculate the sum of all cumulative traffic differences in the traffic difference queue to obtain the total daily traffic difference.

[0079] Extraction unit 142 is connected to sorting unit 141, which is used to calculate the proportion of the cumulative traffic difference in the traffic difference queue to the total traffic difference of the day in turn. The cumulative traffic differences with a proportion not less than a preset threshold are added to the same peak set. The earliest start time of the preset time interval associated with the corresponding cumulative traffic difference in each peak set is taken as the start time of the corresponding peak period, and the latest end time is taken as the end time of the peak period.

[0080] Specifically, in this embodiment, taking the traffic difference queue corresponding to a day as an example, which sequentially includes cumulative traffic difference 1, cumulative traffic difference 2, cumulative traffic difference 3 up to cumulative traffic difference 10, the proportion of cumulative traffic difference 1 to the sum of the 10 cumulative traffic differences is calculated. If the proportion is greater than a preset threshold, the proportion of cumulative traffic difference 2 to the sum of the 10 cumulative traffic differences is calculated. If the proportion is greater than the preset threshold, the proportion of cumulative traffic difference 3 to the sum of the 10 cumulative traffic differences is calculated. If the proportion is not greater than the preset threshold, cumulative traffic difference 1 and cumulative traffic difference 2 are added to a peak set, which corresponds to a peak period. The start time of the peak period is the start time of the preset time interval corresponding to cumulative traffic difference 1, and the end time of the peak period is the end time of the preset time interval corresponding to cumulative traffic difference 2. Continue calculating the percentage of cumulative traffic difference 4 relative to the sum of the 10 cumulative traffic differences. If this percentage is greater than a preset threshold, then continue calculating the percentages of cumulative traffic differences 5, 6, 7, and 8 relative to the sum of the 10 cumulative traffic differences. If the percentages corresponding to cumulative traffic differences 5, 6, and 7 are all greater than the preset threshold, but the percentage corresponding to cumulative traffic difference 8 is not greater than the preset threshold, then add cumulative traffic differences 4, 5, 6, and 7 to a peak set, which corresponds to another peak period. The start time of this peak period is the start time of the preset time interval corresponding to cumulative traffic difference 4, and the end time of this peak period is the end time of the preset time interval corresponding to cumulative traffic difference 7. Continue in this manner until all 10 cumulative traffic differences have been calculated and judged.

[0081] After obtaining the peak periods for each day, the peak periods of the water tank can be obtained by taking the intersection of the peak periods for multiple days.

[0082] In a preferred embodiment of the present invention, the peak-shaving and storage control cabinet 1 further includes:

[0083] The fourth processing module 15 is connected to the acquisition and control module 11. It is used to estimate the initial water age of each water tank before it is connected to the system based on the real-time liquid level, and to calculate the real-time water age based on the initial water age, real-time liquid level and real-time inflow rate.

[0084] Specifically, in this embodiment, regarding the initial water age, since the water tank is not connected to the peak-shaving and storage system, the water is generally filled from the lowest level to the highest level, and then continuously used until the lowest level is reached before starting to fill again. Therefore, the initial water age is estimated using the following formula.

[0085]

[0086] V=(L high -L low )*S bottom

[0087]

[0088] Among them, L low The initial minimum liquid level set in the water tank, measured in meters (m); L high The initial maximum liquid level set in the water tank, measured in meters (m); S bottom The water tank's bottom area is measured in square meters (m²); L is the current water level in the tank, measured in meters (m); and q is the average water consumption, measured in cubic meters (m³). 3 / h.

[0089] The real-time water age calculation method refers to collecting raw data and the previous water age data at fixed time intervals after connecting to the system to calculate the current water age, using the following formula:

[0090]

[0091] Among them, V 进 This refers to the current water inflow into the tank, measured in cubic meters (m³). 3 ;T 进 V' refers to the water age at which water enters the tank, measured in hours (h); V′ refers to the current water volume in the tank, measured in cubic meters (m³). 3 ;T n-1 The water age at the previous moment is measured in hours (h); Δt is the time difference between the current moment and the previous moment, also measured in hours (h).

[0092] After processing the peak water usage period, real-time water age, and predicted water consumption for future periods for each of the water tanks, each peak water storage control cabinet 1 sends the peak water usage period, real-time water age, and predicted water consumption for future periods for each of the water tanks to the peak water storage platform 3 for peak water storage scheduling. In a preferred embodiment of the present invention, the peak water storage platform 3 includes:

[0093] The area management module 31 is used to perform network topology analysis on the municipal pipeline network to divide water tanks belonging to the same main pipeline network into the same storage area.

[0094] The peak period processing module 32 is connected to the area management module 31 and is used to process the real-time pipeline flow under each storage area to obtain the peak period of the municipal pipeline network corresponding to each storage area.

[0095] The regulation and scheduling module 33 is connected to the peak period processing module 32 and the area management module 31 respectively. It is used to obtain the peak period water consumption of each water tank based on the peak period of the pipeline network under each regulation and storage area and the predicted water consumption of each water tank and the peak period processing of the water tank. It also obtains the regulation high liquid level of each water tank during the peak water consumption period, the non-peak period high liquid level during the non-peak water consumption period, and the valve opening water intake period based on the peak period water consumption, the predicted water consumption, the real-time liquid level, and the real-time water age.

[0096] Specifically, in this embodiment, the aforementioned pipeline topology analysis automatically determines water tanks under the same main pipeline and assigns them to the same storage area based on the municipal pipeline's water supply information and topology information. Preferably, the aforementioned storage area can also be customized by the user as needed. Then, for each storage area, the peak period of the municipal pipeline can be obtained based on the real-time pipeline flow. The processing procedure for the pipeline peak period is similar to the water tank peak period procedure. It first calculates the difference between the real-time pipeline flow collected at the end and start times of each preset time interval, then processes the difference to obtain the daily peak period, and finally takes the intersection of the peak periods of each day to obtain the pipeline peak period of each storage area. The specific processing procedure will not be elaborated here.

[0097] More specifically, the regulation and scheduling includes two parts: one is to schedule the water tanks, and the other is to determine the high liquid level during off-peak periods.

[0098] When scheduling for each water tank, the peak water consumption of each tank must first be calculated in order to reasonably control the water storage. Based on this, the water storage and scheduling module 33 includes:

[0099] The water consumption processing unit 331 is used to compare the peak period of each water tank with the peak period of the corresponding storage area's pipeline network to obtain the reasonable peak period of each water tank, and to use the predicted water consumption corresponding to the reasonable peak period as the peak period water consumption of each water tank.

[0100] Specifically, in this embodiment, the comparison of the peak period of each water tank with the corresponding peak period of the pipeline network in the storage area includes firstly ensuring that the peak period of the pipeline network is met within a reasonable peak period. In other words, the peak period of the pipeline network must be a reasonable peak period. Secondly, taking into account the pressure and water consumption of the direct supply area corresponding to the water tank, the peak periods of the water tank with insufficient pressure and excessive water consumption in the direct supply area are extracted. Then, the extracted peak periods of the water tank and the peak periods of the pipeline network are combined to obtain the final reasonable peak period.

[0101] Considering that the reasonable peak period may not be a continuous period but rather multiple separate periods, the predicted water consumption for each water tank during peak hours can be calculated by adding the predicted water consumption for each period. For example, if there are two reasonable peak periods, 7:00 AM to 9:00 AM and 6:00 PM to 9:00 PM, and the predicted water consumption is calculated at 15-minute intervals, we can obtain 8 predicted water consumption intervals for 7:00 AM to 9:00 AM. The sum of these 8 predicted water consumption intervals is the peak water consumption for 7:00 AM to 9:00 AM. Similarly, the peak water consumption for 6:00 PM to 9:00 PM can be obtained by adding the two intervals together.

[0102] In a preferred embodiment of the present invention, the storage and scheduling module 33 further includes:

[0103] The water tank scheduling unit 332 is used to compare the peak water consumption of each water tank with the effective volume of the water tank, and when the effective volume is not greater than the peak water consumption, it uses a genetic algorithm to process the predicted water consumption, real-time liquid level and real-time water age to obtain the high liquid level of each water tank during the peak water consumption period and the opening valve of the electric regulating valve for water intake.

[0104] Specifically, in this embodiment, if the effective volume of the water tank is greater than the peak water consumption, then the water tank does not need to be filled during peak periods; otherwise, the water tank still needs to be filled during peak periods. If the water tank still needs to be filled during peak periods, then when considering the water tank's filling time, it is desirable to be as close as possible to the start time of the peak period. In addition, the algorithm uses predicted water consumption, the real-time liquid level of the water tank, and the real-time water age as the basis for predicting the future water age, where the prediction of the future water age is included in the calculation in the genetic algorithm. Based on the above calculation method, the water tank filling time, water age restrictions, and other constraints are comprehensively considered, such as obtaining different constraint results based on scenarios such as minimum cost, guaranteed pressure and flow at key points, guaranteed worst point, and optimal water age. Based on the above data, the genetic algorithm is used to obtain effective scheduling data, obtain the water tank's filling time and the liquid level at the end of the filling process, and guide the water tank's filling situation. The liquid level at the end of the filling process is called the high liquid level of the storage tank.

[0105] The effective volume mentioned above can be obtained by multiplying the difference between the high and low liquid levels in the water tank and the bottom area of ​​the water tank. The genetic algorithm's gene is the valve opening time for each water tank. During population initialization, the algorithm iteratively uses each valve opening time. The constraints are: if the effective volume of the water tank is greater than the peak water consumption, it should be used up after the peak period ends; if the effective volume is less than the peak water consumption, it should start filling water as close as possible to the start of the peak period. Other constraints include maintaining the water age within acceptable limits. Maintaining the water age within acceptable limits involves calculating the water tank level changes and water age data up to the end of the peak period based on the water volume prediction results and the valve opening time of each water tank in the genetic algorithm. The fitness of this genetic algorithm is calculated based on different scenarios including minimum cost, guaranteed pressure and flow at key points, guaranteed worst-case scenario, and optimal water age, along with the real-time water age and filling time of the water tank. For example, minimum cost is factored into the fitness calculation.

[0106] Furthermore, to address the issue that existing peak-shaving and water storage schemes do not provide corresponding scheduling strategies based on users' business needs, this embodiment uses a genetic algorithm to obtain different constraint results based on scenarios such as minimum cost, guaranteed pressure and flow at key points, guaranteed worst-case conditions, and optimal water age.

[0107] More specifically, if the user's business requirement is to minimize costs, the fitness of the genetic algorithm can be adjusted by calculating the degree of cost reduction in water intake under this scheduling method, such as the increase in overall municipal pressure compared to the current scheduling and the situation without scheduling. Therefore, the outlet pressure of the corresponding area's booster pump station or water plant can be reduced, thereby reducing costs. Based on this, the scheduling scheme with the greatest cost reduction is obtained, which is the scheduling scheme with the lowest cost.

[0108] If the user's business requirement is to ensure the pressure and flow of key points, then the constraints of one or more key points can be added to the genetic algorithm to ensure that the required flow and pressure are met during scheduling. At the same time, the fitness calculation should include the condition that the required flow and pressure of one or more key points are met during scheduling. For example, when a large event is held, the venue must meet its water supply requirements. Therefore, the fitness is highest only when the requirements are met during scheduling. Based on this, a scheduling scheme to ensure the pressure and flow of key points can be derived.

[0109] If the user's business requirement is to guarantee the worst-case scenario, then the constraint of the genetic algorithm can be increased to ensure that the worst-case scenario pressure is met under this scheduling method. At the same time, the result of calculating the worst-case scenario pressure under this scheduling method can be added to the fitness. The better the worst-case scenario pressure, the higher the fitness of this scheduling method. In this way, the scheduling scheme that guarantees the worst-case scenario can be obtained.

[0110] If the user's business requirement is optimal water age, the weight of the water age calculation result of each water tank can be increased in the fitness of the genetic algorithm, so that the fitness is higher when the water age is better, and thus a scheduling scheme that guarantees the worst point can be obtained.

[0111] In a preferred embodiment of the present invention, for the portion of the high liquid level determined during off-peak periods, the storage and scheduling module 33 further includes:

[0112] The high liquid level determination unit 333 is used to take the time period other than each reasonable peak period as the non-peak water use period of each water tank, and take the predicted water use corresponding to the non-peak water use period as the non-peak water use period of each water tank. Then, based on the non-peak water use period and the real-time water age, the non-peak high liquid level of the non-peak water use period is obtained by using a genetic algorithm.

[0113] Specifically, in this embodiment, determining the high liquid level during off-peak periods refers to lowering the high liquid level during non-discharge periods to ensure water age. However, since lowering the high liquid level too much can lead to frequent water intake, it is necessary to determine a suitable high liquid level during off-peak periods. Further, the high liquid level during off-peak periods is obtained using a genetic algorithm based on the predicted water consumption and predicted water age during off-peak periods. Specifically, based on the predicted water consumption and predicted water age during off-peak periods, the algorithm aims to minimize the number of water intakes during off-peak periods while satisfying the predicted water age and predicted water consumption. Here, the predicted water age is the water age data for each minute of the next day, predicted using the genetic algorithm based on the real-time water age. That is, under the aforementioned high liquid level during off-peak periods, the water age throughout the day can be kept within acceptable limits. For example, when this high liquid level during off-peak periods is selected, the liquid level is lowered when the water age is about to exceed the limit, allowing water intake while ensuring the water age does not exceed the limit.

[0114] In this genetic algorithm, the gene is the high liquid level of the water tank during off-peak hours, the initial population is the initial high liquid level during off-peak hours, the constraints are that the high liquid level during off-peak hours cannot be higher than the high liquid level of the water tank, cannot be lower than the low liquid level of the water tank, and must maintain the water age, and the fitness is that the younger the water age, the fewer the number of water inlets.

[0115] This invention also provides a multi-tank peak-shaving and storage method, applied to the aforementioned multi-tank peak-shaving and storage system, such as... Figure 4 As shown, the multi-tank peak-shaving and storage method includes:

[0116] Step S1: The multi-tank peak-shaving and storage system collects water tank data and real-time pipeline flow of the municipal pipeline network where the water tank is located, and processes the water tank data to obtain the peak water period, real-time water age and predicted water consumption for future periods for each water tank.

[0117] Step S2: The multi-tank peak-shaving storage system processes the pre-divided storage zones, the real-time pipeline flow under each storage zone, the predicted water consumption of each tank, the peak period of the tank, the real-time liquid level, and the real-time water age to obtain the storage high liquid level of each tank during the peak water consumption period, the off-peak high liquid level during the off-peak water consumption period, and the valve opening water intake period.

[0118] Step S3: When the real-time liquid level of the multi-tank staggered peak storage system reaches the preset minimum liquid level during the valve opening water inlet period or the peak water usage period, the corresponding water tank is controlled to inlet water until the real-time liquid level reaches the storage high liquid level. When the real-time liquid level does not reach the preset minimum liquid level during the valve opening water inlet period or the non-peak water usage period, the corresponding water tank is controlled to inlet water until the real-time liquid level reaches the non-peak period high liquid level.

[0119] The above description is merely a preferred embodiment of the present invention and does not limit the implementation and protection scope of the present invention. Those skilled in the art should realize that any equivalent substitutions and obvious changes made using the content of this specification and illustrations should be included within the protection scope of the present invention.

Claims

1. A multi-tank peak-shaving and storage system, characterized in that, include: At least one peak-shaving and storage control cabinet, each of which is connected to at least one water tank, is used to collect water tank data and real-time pipeline flow of the municipal pipeline network where the water tank is located, and to process the water tank data to obtain the peak water period, real-time water age and predicted water consumption for future periods for each water tank. The peak-shaving and storage platform is connected to each of the peak-shaving and storage control cabinets. It is used to process the pre-divided multiple storage zones, the real-time pipeline flow under each storage zone, the predicted water consumption of each water tank, the peak period of the water tank, the real-time liquid level, and the real-time water age to obtain the storage high liquid level of each water tank during the peak water consumption period, the off-peak high liquid level during the off-peak water consumption period, and the valve opening water intake period. The staggered peak storage control cabinet is also used to control the corresponding water tank to fill with water until the real-time liquid level reaches the storage high level when the real-time liquid level reaches the preset minimum liquid level during the valve opening water inlet period or the peak water usage period, and to control the corresponding water tank to fill with water until the real-time liquid level reaches the off-peak period high level when the real-time liquid level reaches the preset minimum liquid level outside the valve opening water inlet period or the off-peak water usage period. Each of the water tanks is equipped with a level gauge, and each of the water tanks is equipped with an inlet flow meter and an outlet flow meter respectively. The municipal pipeline network associated with each of the water tanks is equipped with a municipal pipeline network flow meter for collecting the real-time pipeline network flow. An electric regulating valve is also provided between the inlet of each water tank and the corresponding inlet flow meter. The water tank data includes the real-time liquid level, real-time inflow rate, and real-time outflow rate of the water tank. The peak-shaving and storage platform controls the opening of the electric regulating valve to control the water intake of the corresponding water tank; The peak-shaving and storage control cabinet includes: The data acquisition and control module is used to periodically acquire the real-time liquid level, real-time inflow rate and real-time outflow rate of each water tank according to a preset time interval; The fourth processing module, connected to the acquisition and control module, is used to estimate the initial water age of each water tank before it is connected to the system based on the real-time liquid level, and to calculate the real-time water age based on the initial water age, the real-time liquid level and the real-time inflow rate. The initial water age is estimated using the following formula: ； in, ; This refers to the initial minimum liquid level set in the water tank, measured in meters (m). This refers to the initial maximum liquid level set in the water tank, measured in meters (m). The area of ​​the water tank's bottom is measured in square meters (㎡); L represents the real-time water level in the tank, measured in meters (m). This refers to average water consumption, measured in m³ / h. The formula for calculating the real-time water age is as follows: ； in, This refers to the current water inflow rate into the water tank, also known as the real-time inflow rate, expressed in m³. The influent water age is indicated in hours (h). This refers to the current water volume in the tank, expressed in m³. The water age at the previous moment, measured in hours (h). This refers to the time difference between the current moment and the previous moment, measured in hours (h).

2. The multi-tank peak-shaving and storage system according to claim 1, characterized in that, The peak-shaving and storage control cabinet includes: The first processing module, connected to the acquisition and control module, is used to calculate the difference between the real-time outflow rate corresponding to the end time and the start time of each preset time interval as the cumulative flow rate difference. The second processing module, connected to the first processing module, is used to acquire data on factors affecting the cumulative flow difference, filter the data on factors affecting the cumulative flow difference, and then input the filtered data on factors affecting the cumulative flow difference into a pre-trained water consumption prediction model to obtain the predicted water consumption for each preset time interval in the next day. The third processing module, connected to the first processing module, is used to process the cumulative flow difference to obtain the peak period of each day, and to take the intersection of the peak periods of each day to obtain the peak period of each water tank.

3. The multi-tank peak-shaving and storage system according to claim 2, characterized in that, The third processing module includes: The sorting unit is used to sort the cumulative traffic differences of each day in chronological order to obtain a traffic difference queue, and to calculate the sum of all the cumulative traffic differences in the traffic difference queue to obtain the total daily traffic difference. The extraction unit, connected to the sorting unit, is used to sequentially calculate the proportion of the cumulative traffic difference in the traffic difference queue to the total daily traffic difference, and add consecutive cumulative traffic differences with a proportion not less than a preset threshold to the same peak set. The earliest start time of the preset time interval associated with the cumulative traffic difference in each peak set is taken as the start time of the corresponding peak period, and the latest end time is taken as the end time of the peak period.

4. The multi-tank peak-shaving and storage system according to claim 1, characterized in that, The peak-shaving and storage platform includes: The area management module is used to perform network topology analysis on the municipal pipeline network to divide the water tanks belonging to the same main pipeline network into the same storage area. The peak period processing module is connected to the area management module and is used to obtain the peak period of the municipal pipeline network corresponding to each of the storage areas based on the real-time pipeline network flow under each storage area. The regulation and scheduling module is connected to the peak period processing module and the area management module, respectively. It is used to obtain the peak period water consumption of each water tank based on the peak period of the pipeline network under each regulation and storage area, the predicted water consumption of each water tank, and the peak period processing of the water tank. It also obtains the regulation and storage high liquid level of each water tank during the peak water consumption period, the non-peak period high liquid level during the non-peak water consumption period, and the valve opening water intake period based on the peak period water consumption, the predicted water consumption, the real-time liquid level, and the real-time water age.

5. The multi-tank peak-shaving and storage system according to claim 4, characterized in that, The storage and scheduling module includes: A water consumption processing unit is used to compare the peak period of each water tank with the peak period of the corresponding water storage area to obtain a reasonable peak period for each water tank, and to use the predicted water consumption corresponding to the reasonable peak period as the peak period water consumption for each water tank.

6. The multi-tank peak-shaving and storage system according to claim 4, characterized in that, The storage and scheduling module also includes: The water tank scheduling unit is used to compare the peak water consumption of each water tank with the effective volume of the water tank, and when the effective volume is not greater than the peak water consumption, it uses a genetic algorithm to process the predicted water consumption, the real-time liquid level, and the real-time water age to obtain the storage high liquid level of each water tank during the peak water consumption period and the valve opening and water inlet period of the electric regulating valve.

7. The multi-tank peak-shaving and storage system according to claim 5, characterized in that, The storage and scheduling module also includes: The high liquid level determination unit is used to take the time period other than each of the reasonable peak periods as the non-peak water usage period of each water tank, and take the predicted water usage corresponding to the non-peak water usage period as the non-peak water usage of each water tank. Then, based on the non-peak water usage and the real-time water age, a genetic algorithm is used to process and obtain the non-peak high liquid level of the non-peak water usage period.

8. A multi-tank peak-shaving and water storage method, characterized in that, Applied to the multi-tank peak-shaving and storage system as described in any one of claims 1-7, the multi-tank peak-shaving and storage method includes: Step S1: The multi-tank peak-shaving and storage system collects the water tank data of the water tanks and the real-time pipeline flow of the municipal pipeline network where the water tanks are located, and processes the water tank data to obtain the peak water period, real-time water age and predicted water consumption for future periods for each water tank. Step S2: The multi-tank peak-shaving storage system processes the pre-divided storage zones, the real-time pipeline flow rate under each storage zone, the predicted water consumption of each tank, the peak period of the tank, the real-time liquid level, and the real-time water age to obtain the storage high liquid level of each tank during the peak water consumption period, the off-peak high liquid level during the off-peak water consumption period, and the valve opening water intake period. Step S3: When the real-time liquid level of the multi-tank staggered peak storage system reaches the preset minimum liquid level during the valve opening water inlet period or the peak water usage period, the system controls the corresponding water tank to inlet water until the real-time liquid level reaches the storage high liquid level. When the real-time liquid level reaches the preset minimum liquid level outside the valve opening water inlet period or the non-peak water usage period, the system controls the corresponding water tank to inlet water until the real-time liquid level reaches the non-peak period high liquid level.

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