Water management planning system and water management planning method

Abstract

To draft a water operation plan which realizes a water level response desired by a user.SOLUTION: The present invention is directed to a water operation planning system for drafting a water operation plan in a water supply facility having a plurality of distribution reservoirs by using a computer having a processor and a memory. The computer has an interface for setting, by a user, a weight coefficient as a parameter for use in determining priority for recovering a water level. The processor calculates, under restriction on a water demand amount predicted based on the past water distribution amount, with respect to each of the distribution reservoirs, plan values of a flow amount and a water level which minimizes a predetermined object function including items calculated by using the weight coefficient and a value based on a relation between a predicted water level of a distribution reservoir and a target water level of the distribution reservoir, and outputs at least the plan value and the weight coefficient to the interface.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a water operation planning method and system for calculating future planned values of pipeline flow rate and water tank level in a water supply system, and particularly to a water operation planning system and method suitable for realizing a desired water level response during or before a disaster.

Background Art

[0002] In Patent Document 1, a water operation planning problem is solved to derive pipeline flow rate and pump operation planned values such that the water tank level falls within the upper and lower limits. In some cases, a constraint condition that the water level recovers in the morning is also included in the planning problem for solution.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In Patent Document 1, mainly the operation during steady state in which the same demand pattern is repeated daily is targeted. There is a problem that when a disaster such as an earthquake, a typhoon, or a pipeline accident occurs (non-steady state), it is impossible to realize an operation that maintains or increases the water level or quickly recovers the water level when the water level drops.

[0005] In addition, during non-steady state, an increase in the opportunity to design an operation method to meet the desires of the operator (desired water level response) is expected. For example, the following examples can be considered. Case 1: Before the typhoon arrives, it is desired to maintain a high water level in water tanks 1 to 3 and gradually raise the water level of water tanks 4 and 5 to the upper limit. Case 2: Due to burst leakage, the water levels of water tanks 1 to 3 and filter tanks 1 to z3 have dropped, but it is desired to prioritize the water tanks for water level recovery. Case 3: Unexpectedly high turbidity occurs, making water intake difficult after 2 hours. We want to quickly increase the storage capacity of reservoir A before that happens.

[0006] Conventional technologies are designed to plan operations under steady-state conditions, and therefore have the problem of not being able to achieve the desired water level response (water level recovery or water level increase) for the various operational conditions mentioned above.

[0007] The objective of the present invention is to provide a water management planning method and system that achieves a water level response desired by the user. [Means for solving the problem]

[0008] The water operation planning system according to the present invention is a water operation planning system that uses a computer having a processor and memory to plan water operation in a water supply facility having multiple water reservoirs, wherein the computer has an interface for setting weight coefficients, which are parameters for determining the priority of water level restoration, from the user, and the processor calculates planned values ​​for flow rate and water level that minimize a predetermined objective function for each of the water reservoirs, under constraints on the amount of water demand predicted based on past water distribution amounts, using a value based on the relationship between the predicted water level for the water reservoir and the target water level for the water reservoir and the weight coefficient, and outputs at least the planned values ​​and the weight coefficient to the interface. [Effects of the Invention]

[0009] According to the present invention, it is possible to achieve the water level response desired by the user. [Brief explanation of the drawing]

[0010] [Figure 1] Overall diagram of the water supply system [Figure 2] Diagram of the water supply facility [Figure 3] Configuration diagram of the water operation planning process in the first embodiment. [Figure 4]Output screen of the water operation plan system of the first embodiment [Figure 5] Flowchart of the water operation plan formulation process of the first embodiment [Figure 6] Configuration diagram of the water operation plan formulation process of the second embodiment [Figure 7] Explanation diagram of the storage capacity calculation process [Figure 8] Explanation diagram of the method of distributing the storage capacity to each water storage tank [Figure 9] Diagram showing an example of the calculated target water level response [Figure 10] Configuration diagram of the weighting coefficient calculation process [Figure 11] Output screen of the water operation plan formulation system of the second embodiment [Figure 12] Flowchart of the water operation plan formulation process of the second embodiment [Figure 13] Configuration diagram of the water operation plan formulation process of the third embodiment [Figure 14] Output screen of the water operation plan formulation system of the third embodiment [Figure 15] Flowchart of the water operation plan formulation process of the third embodiment [Figure 16] Examples of water demand during normal times and burst leakage times [Figure 17] Table for storing water demand measurement values and water demand prediction values

Modes for Carrying Out the Invention

[0011] Hereinafter, embodiments of the present invention will be described with reference to the drawings. The following description and drawings are examples for explaining the present invention, and for the sake of clarity of explanation, appropriate omissions and simplifications have been made. The present invention can be implemented in various other forms. Unless otherwise particularly limited, each component may be singular or plural.

[0012] In the drawings, the positions, sizes, shapes, ranges, etc. of each component shown may not represent the actual positions, sizes, shapes, ranges, etc. in order to facilitate understanding of the invention. Therefore, the present invention is not necessarily limited to the positions, sizes, shapes, ranges, etc. disclosed in the drawings.

[0013] In the following description, various types of information may be described using expressions such as "database", "table", "list", etc. However, the various types of information may be represented by other data structures. In order to indicate that it does not depend on the data structure, "XX table", "XX list", etc. may be referred to as "XX information". When explaining identification information, when expressions such as "identification information", "identifier", "name", "ID", "number", etc. are used, these can be replaced with each other.

[0014] When there are a plurality of components having the same or similar functions, they may be described with the same reference numeral and different subscripts. However, when it is not necessary to distinguish these plurality of components, the subscripts may be omitted in the description.

[0015] Also, in the following description, there may be cases where the processing performed by executing a program is described. However, the program is executed by a processor (for example, a CPU, GPU (Graphics Processing Unit)) to perform the defined processing while appropriately using a storage resource (for example, a memory) and / or an interface device (for example, a communication port), etc. Therefore, the subject of the processing may be the processor. Similarly, the subject of the processing performed by executing the program may be a controller, device, system, computer, or node having a processor. The subject of the processing performed by executing the program may be an arithmetic unit and may include a dedicated circuit (for example, an FPGA (Field-Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit)) that performs a specific processing.

[0016] A program may be installed from its program source into a device such as a computer. The program source may be, for example, a program distribution server or a computer-readable storage medium. If the program source is a program distribution server, the program distribution server includes a processor and storage resources for storing the program to be distributed, and the processor of the program distribution server may distribute the program to other computers. Furthermore, in the following description, two or more programs may be implemented as a single program, or one program may be implemented as two or more programs.

[0017] (First embodiment) A first embodiment of the present invention will be described with reference to Figures 1 to 5, 16, and 17. Figure 1 is a diagram of the overall water supply system including the water operation planning system 1 of this embodiment. In addition to the water operation planning system 1, the monitoring and control device 2 and the water supply facilities 3 are connected to the network 4, and data can be exchanged between them through communication. A detailed example of the water supply facilities is shown in Figure 2. It consists of a water intake station 201, a water intake pump 202, a water conduit 203, a water treatment plant 204, a water treatment reservoir 205, a water transmission pipe 206, a flow rate adjustment valve 207, a distribution reservoir 1 (208), a distribution reservoir 2 (209), and a water distribution network 210, 211 for distributing water to consumers. Figure 2 shows the case where there are three distribution reservoirs (including water treatment reservoirs), but the present invention is also applicable when there are more or fewer of these.

[0018] Raw water taken from rivers is sent to a water treatment plant where it is purified. The purified water is temporarily stored in a water reservoir and then sent to a distribution reservoir via a water pipeline. From the distribution reservoir, the purified water is supplied to consumers through the water pipeline network.

[0019] Each pipeline is equipped with a flow meter to measure flow rate, the water treatment reservoir with a water level meter and a flow meter to measure filtration rate, and the distribution reservoir with a water level meter and a flow meter to measure water distribution rate. The measurement data is sent to the monitoring and control device 2 at predetermined intervals. Based on this data, the monitoring and control device 2 controls and manages the flow rate of each pipeline, pump operation, and the water level of the distribution reservoir.

[0020] The water management planning system 1 obtains measurement information such as water level and water distribution volume from the monitoring and control device 2, which is necessary for future planning of water volume and other factors. It then performs a future forecast of water distribution volume (water demand forecast) and calculates future planned values ​​for each pipeline flow rate and pump operation (ON / OFF information) based on these forecast values. The planned values ​​are sent to the monitoring and control device, and pipeline flow rates and pump operations are controlled based on these planned values.

[0021] As shown in Figure 1, the water operation planning system 1 is composed of a computer consisting of a storage device 13 comprising RAM, a hard disk, etc., a communication interface 14 for exchanging data via an external network, a processor 15 which is a control unit comprising a CPU, etc., and a data input / output interface 16 which consists of a human-machine interface such as a keyboard, mouse, and display. The processor 15 calls and executes the water operation planning processing program 11 stored in the storage device 13, and stores the calculation results in the database 12 or displays them on the data input / output interface 16. During the program execution process, data taken in from the data input / output interface 16 and various information stored in the database 12 in the storage device are referenced as needed and used for calculation processing.

[0022] Figure 3 shows the configuration of the water operation planning processing program 11 of the first embodiment, which realizes the target water level response that is a characteristic of this system. In the water demand forecasting process 30, the amount of water distributed (=water demand) from the two water reservoirs 208 and 209 is predicted. Here, statistical processing is applied to past water distribution data, weather data, temperature data, etc., to predict the amount of water distributed from the present time to 24 hours in advance. This method is a common and well-known method that is used in various water operation planning systems.

[0023] On the other hand, if a burst leak occurs due to a pipeline accident, the prediction accuracy of the conventional method described above deteriorates. This is because, despite the occurrence of a burst leak, the prediction is made using data from normal conditions, resulting in prediction results for normal conditions. Figure 16 shows an example of the normal water distribution response 1601 and the water distribution response 1602 during a burst leak. Figure 16 shows an example where a burst leak occurred at time t0 and continued. Generally, there is a certain difference (offset) α between the water distribution during normal conditions and the water distribution during a burst leak. This difference is calculated, and the predicted water distribution value is corrected; that is, α is added to the predicted water distribution value to calculate the predicted water distribution value during a burst leak and ensure prediction accuracy. In Figure 16, the value obtained by adding the above offset α to the predicted water distribution value 1601 during normal conditions is shown as the water distribution response 1602.

[0024] As shown in Figure 17, the calculation of α involves storing the measured and predicted water distribution values ​​prior to the current time (15:45). If the difference between these values ​​exceeds a predetermined value, it is determined that a burst leak has occurred, and the offset α can be calculated by taking the average of the water distribution deviations thereafter. Here, the predicted value at time T corresponds to the predicted demand value D(1) for the future time T closest to the current time, in a series of predictions in 15-minute increments up to 24 hours ahead, predicted 15 minutes before time T (predicted value D(1) at time T+15 minutes, predicted value D(2) at time T+30 minutes, predicted value D(3), ...). This value is stored in the table.

[0025] Figure 17 shows that a burst leak was determined to have occurred at 15:15 when the water distribution deviation reached 22. In Figure 17, the offset α is 22, which is the average of the deviations from 15:15 to 15:45 (the current time). Therefore, the normal water distribution response 1601 and the burst leak water distribution response 1602 in Figure 16 fluctuate approximately with the value of the above offset α. Specifically, as will be described later, this system includes a term in the objective function of the water operation planning problem that is obtained by multiplying the sum of the absolute values ​​of the deviations between the future predicted water level for the reservoir and the fixed target water level of that reservoir by a weighting coefficient. An interface is provided for the user to set this weighting coefficient, and the system calculates the planned values ​​of flow rate and water level that minimize the objective function under the set weights, and these planned values ​​can be displayed on the interface along with the weighting coefficient. This system also applies to situations where the water level drops when a burst leak occurs, and therefore uses the extended water demand forecast described above.

[0026] Next, we will describe the operational planning process 31 that realizes the target water level response, which is a characteristic of this system. Generally, operational planning is done by solving mathematical programming problems. A mathematical programming problem consists of an objective function (daily electricity cost, power consumption, pipeline fluctuation suppression, etc.), constraints (pipeline flow rate balance equation including flow rate, upper and lower water level limits, and predicted water demand), and decision variables (pipeline flow rate, water level, etc.). In this system, the following objective function 1 is used to realize the target water level response in situations such as recovery from a water level drop or when increasing storage capacity before a disaster.

[0027]

number

[0028] Here, t: time (one time unit corresponds to one hour), L0: water level of the clean water tank (205), L1: water level of the distribution tank 1 (208), L2: water level of the distribution tank 2 (209), L0_target: fixed target water level of the clean water tank, L1_target: fixed target water level of the distribution tank 1 (208), L2_target: fixed target water level of the distribution tank 2 (209), u1: flow rate of a certain pipeline, wi (i = 1, 2, 3): weight coefficient, k1: weight coefficient (set to 1).

[0029] The fixed target water level is set to a value close to the upper limit of water level operation. Also, wi is set by the user through the interface described later. The first to third terms are for formulating a plan to maintain the water level near the upper limit, and the fourth term works to suppress flow rate fluctuations as much as possible. Although only one term for suppressing flow rate fluctuations is shown, terms for suppressing fluctuations of all flow rate variables are added to the objective function. In this operation plan formulation process 31, under the constraint conditions, the planned values of future flow rates and water levels that minimize equation (1) are calculated by solving a mathematical programming problem using a solver.

[0030] The calculated planned values are displayed on the user interface screen shown in FIG. 4. In FIG. 4, the planned values 43 to 47 of future water levels and future pipeline flow rates (only a part is shown) for the scenario of recovering the decreased water level are displayed. The weight coefficients can be set at the upper part 42 of the screen. When the plan formulation button 40 is pressed, under the set weight coefficients, the previous demand prediction process and operation plan formulation process are executed, and the results (planned values) are displayed on this screen. The weight coefficient is a parameter for determining the priority of water level recovery. Thus, by adjusting the weight coefficient of the objective function through the interface, it becomes possible to achieve the water level response desired by the user.

[0031] In the example of FIG. 4, the weight coefficients are set as w0 < w1 < w2. Therefore, it is a plan that prioritizes the recovery of the water level of the distribution tank 2 and then the recovery of the distribution tank 1. If this water level response is not satisfactory, the desired water level response can be achieved by resetting the weight coefficients. The weight coefficients corresponding to the satisfactory results can be stored in the system by pressing the weight coefficient save button 41.

[0032] Figure 5 shows a flowchart of the processing program that is executed when the planning button 40 is pressed.

[0033] In step 501, the water operation planning processing program 11 reads the input information necessary for planning the operation. Here, it reads weighting coefficients, target water levels, the latest reservoir water level measurements, past water distribution volume records, weather information, etc. For weighting coefficients, if a setting value exists on the interface screen shown in Figure 4, it is read and set. If there is no setting value on the screen, if there is a value stored in the system, that is used.

[0034] In step 502, the water operation planning processing program 11 performs water demand forecasting according to the processing of block 30 described above. Specifically, it forecasts water demand considering burst leakage based on the value of offset α.

[0035] In step 503, the water operation planning processing program 11 performs operation planning processing in accordance with the processing of block 31 described above.

[0036] Finally, in step 504, the water operation planning processing program 11 displays the calculation results on the interface screen shown in Figure 4 and terminates the process.

[0037] (Second example) Next, a second embodiment of the present invention will be described based on Figures 6 to 12. In the first embodiment, the user adjusted the weighting coefficients through trial and error to achieve the target water level response. While this method can be used to some extent when the number of reservoirs is small, it becomes difficult to use as the number of reservoirs increases. Therefore, the second embodiment includes a method for automatically calculating the weighting coefficients.

[0038] Figure 6 shows the processing configuration of the water operation planning processing program 111 of the second embodiment. The water operation planning processing program 111 has the same configuration as the water operation planning processing program 11 of the first embodiment shown in Figure 3, with the addition of a target water level response calculation process 61 and a weighting coefficient calculation process 62. The target water level response calculation process 61 is a process for calculating the target water level response, which is the water level response desired by the user. The weighting coefficient calculation process 62 is a process for automatically calculating weighting coefficients to achieve the target water level response.

[0039] As will be described in more detail later, in this embodiment, instead of an interface for setting weighting coefficients, an interface is provided for setting information regarding the priority and rate of raising the water level of each reservoir, and this information is used to calculate a target water level response, which is an achievable water level response. Then, a water operation planning method is used, which has a term obtained by multiplying the absolute sum of the deviations between the water level and its fixed target value by the weighting coefficient as its objective function. Weighting coefficients are calculated such that the water level response plan value, calculated by this method, approaches the target water level response, and the calculated weighting coefficients can be displayed on the interface along with the water level response plan value and target water level response corresponding to those weighting coefficients.

[0040] First, the details of the target water level response calculation process 61 will be explained based on Figures 7 to 9. This process consists of three steps: calculating the total amount that can be stored in the reservoirs, allocating the storage capacity to each reservoir, and calculating the target response for each reservoir. Each step corresponds to the explanation in Figures 7 to 9.

[0041] The calculation process for the storage capacity shown in Figure 7 is explained below. As shown in Block 71, the predicted value D(t) of the total demand (total water distribution) from the distribution reservoirs (excluding the water purification reservoirs) is predicted using the demand forecasting method described above. On the other hand, the time series S(t) of the amount that can be supplied to the distribution reservoirs (including the water purification reservoirs) is calculated from the upper limit of the filtration rate, etc. The above supply capacity is assumed to be predetermined. Here, it is not necessarily required to use the operational upper limit of the filtration rate, and the amount that is possible is set according to the situation. Also, the water system structure can be arbitrary, and the number of distribution reservoirs can be four or more.

[0042] As shown in the lower half of the graph in Figure 7, by integrating the difference between S(t) and D(t), the total amount of water that can be stored in all reservoirs (including water purification reservoirs) at a future time t, V(t), can be calculated as shown by the solid line 72. This line is generally a curve, but it can also be used as a linear approximation using the least squares method, as shown by the dotted line 73. Using a straight line has the effect of keeping the supply amount to each reservoir as constant as possible when formulating the operational plan problem (when solving the mathematical programming problem). In this way, an approximate straight line (dotted line) can also be used as a method for solving the mathematical programming problem in order to achieve a flat supply amount.

[0043] Next, we will explain how the amount of water that can be stored is allocated to each reservoir (including the water purification reservoir) based on Figure 8. Here, the user has set the priority order for water level recovery in the order of reservoir 2, reservoir 1, and water purification reservoir, so reservoir 2 has the highest recovery priority. Furthermore, in the initial state (from the current time 0 to time T1), the allocation of the amount of water that can be stored to the water purification reservoir, reservoir 1, and reservoir 2 is set to 0.0, 0.1, and 0.9. This means that 90% of the amount of water that can be stored is allocated to reservoir 2, and the remaining 10% is allocated to reservoir 1. Furthermore, in the next state (from time T1 to time T2), the allocation of the amount of water that can be stored to the water purification reservoir, reservoir 1, and reservoir 2 is set to 0.1, 0.9, and 0.0. This means that since the water level of reservoir 2 recovers in the initial state, from time T1 to T2, 90% of the amount of water that can be stored is allocated to reservoir 1, and the remaining 10% is allocated to the water purification reservoir. From time T2 onward, all available storage capacity is supplied to the water purification reservoir. Given the recovery priority and allocation as described above, the feasible target water level response shown in Figure 9 can be calculated. The formulas for calculating the water level response at time T1, T2, and each reservoir, given the above priority and allocation, are as follows. Note that the target water level response can be calculated using the same method even if the priority and allocation are changed. • Calculation of T1 and T2 (Find T1 and T2 that satisfy the following equation)

[0044]

number

[0045]

number

[0046] Here, V(t): storage capacity at time t, L1, target: water level to be restored in reservoir 1, L2, target: water level to be restored in reservoir 2, L1(0): initial water level of reservoir 1, L2(0): initial water level of reservoir 2, L2(T1): water level of reservoir 2 at time T1. The calculation of the target water level response (with the current time set to 0, and calculating the future target water level response) can be performed as follows:

[0047] (a) In the case of 0 ≤ t ≤ T1

[0048]

number

[0049]

number

[0050] Also, (b) In the case of T1 ≤ t ≤ T2,

[0051]

number

[0052]

number

[0053] Also, (c) If T2 ≤ t,

[0054]

number

[0055] Here, t: time (current time is 0), L0: water level in the water purification reservoir (target water level), L1: water level in the distribution reservoir 1 (target water level), L2: water level in the distribution reservoir 2 (target water level), S0: cross-sectional area of ​​the water purification reservoir, S1: cross-sectional area of ​​the distribution reservoir 1, and S2: cross-sectional area of ​​the distribution reservoir 2.

[0056] In Figure 9, the target water level response 91 for reservoir 2 is calculated using equation (4), the target water level response 92 for reservoir 1 is calculated using equations (5) and (6), and the target water level response 93 for the water purification reservoir is calculated using equations (7) and (8). As shown in Figure 9, the target water level responses for reservoir 1, reservoir 2, and water purification reservoir are calculated based on the above allocation for each of the following periods: from the current time 0 to time T1, from time T1 to time T2, and from time T2 onward.

[0057] Next, we will explain the process of calculating the weight coefficient w that achieves the target response based on Figure 10 (details of the process in block 62 of Figure 6).

[0058] In block 102, the target water level response is calculated using the method described above (the method explained in Figures 7 to 9) under typical operating conditions where the water level decreases. Meanwhile, in block 101, the planned value of the water level response is calculated by performing the processes in blocks 30 and 31 in Figure 6 under certain weighting coefficients. In block 103, weighting coefficients that minimize errors are searched for and determined based on the sum of the squares of the errors between the target water level response and the planned water level response. A nonlinear optimization method is used to determine the weighting coefficients that bring the planned water level response closest to the target water level response.

[0059] Figure 11 shows an interface screen displaying the weighting coefficients, target water level response, planned water level response, and planned flow rate determined by the above process. When the planning button 1108 is pressed, the process is executed and the results such as the target response, planned values, and weighting coefficients are displayed. The target water level response is shown as a dotted line, and the planned values ​​are shown as solid lines. In this example, it can be seen that the planned values ​​are close to achieving the target values. At the top of the screen 1101, the user sets the recovery priority and recovery speed (corresponding to the allocation ratio of the storage capacity to the distribution reservoirs mentioned above), and the target water level response is calculated based on these settings. Furthermore, the planned flow rate values ​​1102-1106 that achieve the target water level response are calculated and output. In Figure 11, the water level recovery priority for the water purification reservoir, distribution reservoir 1, and distribution reservoir 2 are set to "3", "2", and "1", respectively, with lower numbers indicating higher priority. Furthermore, the initial recovery speed (water level recovery speed between 0 and T1) is set to "0.0", "0.1", and "0.9", respectively, and during this period, reservoir 2 is set to distribute water at the highest speed. Similarly, the next recovery speed (water level recovery speed between T1 and T2) is set to "0.1", "0.9", and "0.0", respectively, and during this period, reservoir 2 is set to distribute water at the highest speed. In addition, in the example shown in the figure, the weighting coefficients that achieve the target water level response are automatically calculated as "1.0", "1.4", and "1.8". The calculated weighting coefficients can be saved to the system using the weighting coefficient save button 1107 and reused. In this way, by automatically calculating the weighting coefficients of the objective function through the interface, it becomes easier for the user to achieve the water level response they desire compared to the first embodiment.

[0060] Figure 12 shows a flowchart of the program that executes the planning process shown in Figure 11. This is the process that is executed when the planning button 1108 is pressed.

[0061] First, in step 1201, the water operation planning processing program 111 reads the input information necessary for this process. The input information includes the priority order for reservoir recovery, recovery speed information, latest water level measurements, actual water distribution volume data, and weather data, which are entered through the interface shown in Figure 11.

[0062] Next, in step 1202, the water operation planning processing program 111 calculates the storage capacity in the target water level response calculation processing 61 using the method described in Figure 7.

[0063] Next, in step 1203, the water operation planning processing program 111 calculates the target water level response for each water reservoir (including the water purification reservoir) in the target water level response calculation processing 61 described above, using the method explained in Figures 8 and 9.

[0064] Next, in step 1204, the water operation planning processing program 111 calculates weighting coefficients in the weighting coefficient calculation process 62 based on the process in Figure 10. The operation plan values ​​are also calculated through this calculation.

[0065] Finally, in step 1205, the water management planning processing program 111 displays the calculation results in the interface shown in Figure 11 and terminates the process.

[0066] (Third embodiment) Next, the water operation planning processing program 112 of the third embodiment will be described based on Figures 13 to 15. Figure 13 shows the processing configuration. The difference from the second embodiment is the water operation planning processing 131. In this embodiment, in addition to objective function 1 used in embodiments 1 and 2, objective function 2 is provided and used depending on the situation to improve the accuracy of achieving the target water level response. Specifically, as will be described later, objective function 2 is an objective function that includes a term obtained by summing the absolute values ​​of the deviation between the water level at a future time t and the target water level at time t calculated using the methods of embodiments 1 and 2 over a predetermined time range in the future. Then, by selecting these objective functions according to the situation and solving the water level planning problem, it is possible to calculate the future planned value.

[0067] The method using objective function 1 in Example 2 was an approximate method that achieved the target response by adjusting the weight coefficients, and therefore, in some situations, it may not satisfy the user. In Example 3, in the water operation planning process 131, the following objective function 2 is newly introduced to calculate the planned values ​​that achieve a more accurate target water level response.

[0068]

number

[0069] Here, L0, t(t): target water level of the water purification reservoir at time t, L1, t(t): target water level of distribution reservoir 1 at time t, and L2, t(t): target water level of distribution reservoir 2 at time t. These are set to target water level responses calculated in the process (target response calculation process 61) shown in Figures 7 to 9. In other words, in Examples 1 and 2, a pre-fixed target water level (for example, a value that is somewhat close to the upper limit of water level operation) was used as the target water level of the distribution reservoir in the objective function of the water operation planning problem. However, in this example, in order to achieve a more accurate target water level response, the water level calculated in the target response calculation process 61 shown in Example 2 is set as the target water level instead of a fixed target water level. The weight coefficients w0, w1, and w2 do not require adjustment and are all set to a fixed value of 1. The weight coefficient k is also set in advance by pre-calculation to suppress fluctuations.

[0070] In Example 3, the system is operated using objective function 1 in various situations such as maintaining, lowering, and restoring the water level. However, if a satisfactory water level response is not obtained during the restoration phase, the system is switched to objective function 2 at the user's instruction, and an operational plan is formulated. Using objective function 2 allows for a more precise water level response, but generating target values ​​in various situations is difficult, so it may be used only at a single point during the restoration phase.

[0071] Figure 14 shows the results of the operational plan formulation according to Example 3 when objective function 2 is selected during water level recovery. In Figure 14, the selection item for selecting the objective function is provided in the form of a pull-down menu 1409 at 1101 of the interface screen shown in Figure 11. In this example, objective function 2 is selected using the pull-down menu 1409, and flow rate plan values ​​1402 to 1606 that achieve the target water level response are calculated. The water level plan values ​​(solid line) accurately match the target water level (dotted line), and it can be seen that the pipeline flow rate fluctuates by only 1 degree to achieve this. Specifically, it can be seen that the flow rate in pipeline 1 displaced by 1407 at a certain time, and the flow rate in pipeline 2 displaced by 1408 at a certain time. This is because the selected objective function was changed from objective function 1 to objective function 2 in the pull-down menu 1409. As shown in the flow rate plan values ​​1402-1404, this change brings the water levels in the water purification reservoir, distribution reservoir 1, and distribution reservoir 2 closer to the target water level response compared to the respective water levels shown in Figure 11.

[0072] Based on Figure 15, a flowchart of the program that performs the operational plan formulation process when objective function 2 is selected is shown. When objective function 1 is selected, the operational plan is formulated and the planned values ​​are displayed using the method described in Example 2 above.

[0073] In step 1501, the water operation plan formulation processing program 112 reads various information (input information) necessary for formulating the operation plan. The input information includes the priority order for reservoir recovery, recovery speed information, latest water level measurements, actual water distribution volume data, and weather data, which are entered through the interface shown in Figure 14.

[0074] In step 1502, the water operation planning processing program 112 calculates the target water level response for each water reservoir (including the water purification reservoir) according to the target water level response calculation processing 61 described above.

[0075] In step 1503, the water operation planning processing program 112 executes the aforementioned water demand forecasting process and the water operation planning processing 131, which formulates an operation plan using objective function 2 as the objective function, and calculates the planned values ​​for water level and flow rate.

[0076] Finally, in step 1504, the water operation planning processing program 112 displays the planned values ​​on the interface screen 1400 and terminates the process.

[0077] As described above, the third embodiment offers the advantage of being able to more precisely realize the water level response desired by the user.

[0078] As explained above, the water management planning system in each embodiment makes it possible to achieve the water level response desired by the user, even in non-routine situations such as during a disaster.

[0079] For example, as described in Example 1, Figures 3-5, Steps 503, 504, etc., in a water operation planning system (water operation planning system 1) that plans water operation in a water supply facility having multiple water reservoirs using a computer having a processor and memory, the computer has an interface (for example, the output screen shown in Figure 4) for the user to set weight coefficients w1-w3, which are parameters for determining the priority of water level restoration. The processor calculates planned values ​​for flow rate and water level that minimize a predetermined objective function (for example, Equation 1) for each of the water reservoirs, under constraints on the predicted water demand (predicted demand value obtained in the water demand forecasting process 30) based on past water distribution amounts, and a term calculated using a value based on the relationship between the predicted water level for the water reservoir and the target water level for the water reservoir (for example, the difference between the two) and the weight coefficients, and outputs at least the planned values ​​and the weight coefficients to the interface. Furthermore, the processor calculates the planned flow rate and water level that minimize the predetermined objective function, as shown in Equation 1, by using an objective function that includes a term calculated using the weight coefficient and the sum of the absolute values ​​of the deviations between the predicted water level for the reservoir and the fixed target water level of the reservoir, multiplied by a weight coefficient. Therefore, by adjusting the weight coefficient of the objective function through the interface, it becomes possible to achieve the water level response desired by the user with simple operations.

[0080] Furthermore, as explained using Example 2, Figure 6-12, etc., the interface accepts from the user the priority for restoring the water level and the water level restoration rate for each of the water reservoirs, instead of the weight coefficients. The processor calculates the amount of water that can be stored for each of the water reservoirs (e.g., Figure 8) based on a predetermined amount of water that can be supplied to the multiple water reservoirs and the predicted water demand. For each of the water reservoirs, using the set priority, the restoration rate, and the calculated storage capacity, the processor searches for a weight coefficient that minimizes the statistical value (e.g., the sum of squared errors between the target water level response and the planned water level response) based on the target water level (e.g., Figure 9) calculated according to a predetermined distribution of the storage capacity and the planned value (e.g., Figure 10). The processor then outputs the searched weight coefficient, the corresponding planned value, and the target water level to the interface. This allows the user to automatically achieve the desired water level response by calculating the weight coefficients through the interface.

[0081] Furthermore, as explained using Example 3, Figure 13-15, etc., the processor calculates planned flow rates and water levels for each of the reservoirs that minimize another predetermined objective function (e.g., Equation 2), which includes a term calculated using the sum of the absolute values ​​of the deviation between the predicted water level for the reservoir and the target water level calculated when the weight coefficients were searched, over a predetermined time range in the future, instead of the predetermined objective function. Thus, a more accurate target water level response can be achieved.

[0082] Furthermore, as explained using Figure 14, etc., the interface accepts a switching operation between the predetermined objective function and the other objective function (for example, Equation 1 and Equation 2), and the processor calculates the planned values ​​of flow rate and water level that minimize the objective function set by the switching operation. Therefore, the user can achieve a highly accurate target water level response with simple operation and at the desired timing.

[0083] Furthermore, as explained using Figures 16 and 17, the processor stores the measured past water distribution volume and the predicted water distribution volume in the memory. When the difference between the two exceeds a predetermined value, it determines that a burst leak has occurred. It then calculates a statistical value (e.g., an average value) of the difference between the two for the water distribution volume after that determination, and uses the calculated statistical value to predict the current water demand. This allows for an accurate understanding of water demand even when the water level drops during a burst leak.

[0084] The three examples described above illustrate the application of this system to scenarios where water levels in reservoirs have dropped during a disaster. However, it can also be effectively applied to scenarios where the storage capacity of reservoirs is increased before a disaster. Furthermore, even during a disaster, the system can be operated automatically by simply providing parameters to achieve the desired water level response, or by automatically calculating those parameters, thereby reducing the number of personnel required to operate the system. For example, even in the event of a burst leak, the system can automatically manage the desired water level while reducing the number of personnel required. Therefore, even if a burst leak occurs during a disaster caused by recent climate change, it is possible to propose a water management plan that responds quickly to the changes, and by using this system, social issues related to the water treatment environment can be solved. [Explanation of Symbols]

[0085] 1…Water operation planning system, 2…Monitoring and control device, 3…Water supply facilities, 4…Network, 11, 111, 112…Water operation planning processing program, 13…Storage device, 14…Communication I / F (interface), 15…Processor, 16…Data input / output I / F

Claims

1. A water operation planning system that uses a computer having a processor and memory to formulate a water operation plan for a water supply facility having multiple water reservoirs, The aforementioned computer, It has an interface for users to set weighting coefficients, which are parameters for determining the priority of water level restoration. The aforementioned processor, For each of the aforementioned reservoirs, under constraints on the predicted water demand based on past water distribution volumes, the planned flow rate and water level values ​​that minimize a predetermined objective function, which includes a term calculated using a value based on the relationship between the predicted water level for the reservoir and the target water level for the reservoir, and the weighting coefficient, are calculated. At least the planned value and the weighting coefficient are output to the interface. A water management planning system characterized by the following features.

2. A water management planning system according to claim 1, The aforementioned interface is For each of the aforementioned water reservoirs, instead of the weighting coefficient, the user can set the priority for restoring the water level and the speed at which the water level is restored. The aforementioned processor, Based on the predetermined amount of water that can be supplied to the plurality of water reservoirs and the predicted water demand, the amount of water that can be stored in each of the water reservoirs is calculated. For each of the aforementioned reservoirs, using the set priority, the recovery rate, and the calculated storage capacity, the weighting coefficient is searched for which the statistical value based on the target water level and the planned value, calculated according to a predetermined distribution of the storage capacity, becomes smaller. The interface outputs the searched weight coefficients, the corresponding planned values, and the target water level to the weight coefficients. A water management planning system characterized by the following features.

3. A water management planning system according to claim 2, The aforementioned processor, The predetermined objective function is used to calculate the planned values ​​of flow rate and water level that minimize the objective function, which includes a term calculated using the weight coefficient and the sum of the absolute values ​​of the deviations between the predicted water level for the reservoir and the fixed target water level of the reservoir, multiplied by a weight coefficient. A water management planning system characterized by the following features.

4. A water management planning system according to claim 3, The aforementioned processor, For each of the aforementioned reservoirs, under constraints on the predicted water demand based on past water distribution amounts, instead of the predetermined objective function, the planned flow rate and water level are calculated to minimize another predetermined objective function that includes a term calculated using the sum of the absolute values ​​of the deviations between the predicted water level for the reservoir and the target water level calculated when the weighting coefficients were searched, over a predetermined time range in the future. A water management planning system characterized by the following features.

5. A water management planning system according to claim 4, The aforementioned interface is The system accepts a switching operation between the predetermined objective function and the other objective function. The aforementioned processor, The system calculates the planned values ​​for flow rate and water level that minimize the objective function set by the aforementioned switching operation. A water management planning system characterized by the following features.

6. A water management planning system according to claim 1, The aforementioned processor, The measured values ​​of past water distribution and the predicted values ​​of the predicted water distribution are stored in the memory, and if the difference between the two exceeds a predetermined value, it is determined that a burst leak has occurred. A statistical value of the difference between the two is calculated for the water distribution after the determination, and the current water demand is predicted using the calculated statistical value. A water management planning system characterized by the following features.

7. A water operation planning method for formulating a water operation plan for a water supply facility having multiple water reservoirs, using a computer having a processor and memory, The aforementioned processor, For each of the aforementioned reservoirs, under constraints on the predicted water demand based on past water distribution volumes, the planned flow rate and water level are calculated to minimize a predetermined objective function that includes terms calculated using a value based on the relationship between the predicted water level for the reservoir and the target water level for the reservoir, and a weighting coefficient which is a parameter for determining the priority of water level restoration from the user. At least the planned value and the weighting coefficient are output to the interface for setting the weighting coefficient. A method for formulating a water management plan, characterized by the features described above.

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