Hydroelectric power plant operation support device and hydroelectric power plant operation support method

Abstract

This makes it possible to reduce the computational load while preventing a decrease in the accuracy of hydroelectric power plant operation plans. [Solution] An operation support device for a hydroelectric power plant according to an embodiment of the present invention includes an evaluation function generator and an optimization calculation processor. The evaluation function generator generates an evaluation function based on the power generation output of a generator, which changes over time, in accordance with the time-series amount of water consumed for power generation taken from the water stored in a dam. The optimization calculation processor constrains the time-series amount of water consumed for power generation and the relationship between the time-series amount of water consumed for power generation and the time-series amount of power generation output relative to the time-series amount of water consumed for power generation to a predetermined operating point, which changes in accordance with the head based on the amount of water stored in the dam, and generates a planned value for the time-series amount of water consumed for power generation so as to maximize the evaluation function.

Description

[Technical Field]

[0001] An embodiment of the present invention relates to an operation support device for a hydroelectric power plant and an operation support method for a hydroelectric power plant. [Background technology]

[0002] The amount of water flowing into a dam water system generally varies depending on factors such as rainfall upstream, snowmelt, spring water, etc. In order to generate electricity in accordance with the amount of inflow, it is necessary to plan and operate the connected power plants in accordance with the amount of inflow into the dam water system.

[0003] In such a water system, at a dam-type power plant, the head of the power generation equipment changes depending on the dam water level, and while high water level operation can increase the amount of power generated, when the dam water level reaches its upper limit, the operation of releasing water from the dam that is not used for power generation can result in a decrease in power generation.

[0004] Regarding operation planning for hydroelectric power plants that takes into account the head caused by changes in dam water level, there are known methods for planning operations for hydroelectric power plants (see, for example, Patent Document 1) that create a power generation operation plan by repeatedly updating a simulation of changes in water storage volume using a power generation output model that takes into account changes in head, and an operation plan generation device (see, for example, Patent Document 2) that divides the possible ranges of water storage volume and discharge volume at the power plant, repeatedly generates optimization problems, and derives optimal solutions to create an operation plan for a hydroelectric power plant. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent No. 5425985 [Patent Document 2] Patent No. 7362793 Summary of the Invention [Problem to be solved by the invention]

[0006] However, in order to ensure the accuracy of hydroelectric power plant operation plans through repeated calculations, there is a trade-off between the computational load and the accuracy of the plan, and high computational loads are required. Furthermore, in operation plans for dam water systems where multiple power plants are connected, the computational load becomes even higher, which can make practical operation difficult.

[0007] The embodiments of the present invention have been made taking these circumstances into consideration, and provide a hydroelectric power plant operation support device and a hydroelectric power plant operation support method that can reduce the computational load while suppressing a decrease in the accuracy of the hydroelectric power plant operation plan. [Means for solving the problem]

[0008] An operation support device for a hydroelectric power plant according to an embodiment of the present invention includes an evaluation function generator and an optimization processing unit. The evaluation function generator generates an evaluation function based on the power generation output of a generator that changes over time in accordance with the time-series amount of water consumed for power generation taken from the water stored in the dam. The optimization processing unit constrains the time-series amount of water consumed for power generation and the relationship between the time-series amount of water consumed for power generation and the time-series amount of power generation output relative to the time-series amount of water consumed for power generation to a predetermined operating point that changes in accordance with the head based on the amount of water stored in the dam, and generates a planned value for the time-series amount of water consumed for power generation so as to maximize the evaluation function. [Effects of the Invention]

[0009] According to the present invention, it is possible to reduce the calculation load while suppressing a decrease in the accuracy of the operation plan of a hydroelectric power plant. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a block diagram showing an example of the configuration of a hydroelectric power plant operation support system according to an embodiment of the present invention. [Figure 2] FIG. 1 is a diagram showing an example of a model of a river system that is the subject of a river system operation plan. [Figure 3] FIG. 2 is a block diagram showing an example of the configuration of a processing unit according to the present embodiment. [Figure 4] FIG. 10 is a diagram showing pipeline loss characteristic data. [Figure 5]FIG. 1 is a diagram showing turbine efficiency as turbine characteristic data. [Figure 6] FIG. 10 is a diagram showing generator efficiency as generator characteristic data. [Figure 7] 10 is a flowchart showing an example of a process for generating hydroelectric power generation data. [Figure 8] FIG. 10 is a diagram showing water volume power generation data showing the relationship between power generation output and water volume used for power generation. [Figure 9] FIG. 10 is a diagram showing water volume power generation data showing the relationship between power generation output and water volume used for power generation in the case of two units. [Figure 10] FIG. 10 is a diagram showing an example of a calculation model generated by a luck evaluation model generation unit. [Figure 11] A diagram showing the relationship between various decision variables at each time step. [Figure 12] 1 is a table illustrating the selection of an operating point. [Figure 13] 10 is a flowchart showing an example of processing performed by an operation support device for a hydroelectric power plant. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, a power conversion device and a control method according to an embodiment of the present invention will be described in detail with reference to the drawings. Note that the embodiment described below is an example of an embodiment of the present invention, and the present invention should not be interpreted as being limited to these embodiments. Furthermore, in the drawings referred to in this embodiment, identical parts or parts having similar functions are given the same or similar reference numerals, and repeated explanations thereof may be omitted. Furthermore, part of the configuration may be omitted from the drawings.

[0012] (One embodiment)

[0013] 1 is a block diagram showing an example of the configuration of a hydroelectric power plant operation support system 1 according to this embodiment. The operation support system 1 according to this embodiment is a system capable of supporting the operation of, for example, generators P1 to Pn.

[0014] The operation support system 1 according to this embodiment includes a hydroelectric power plant operation support device 10, a display device 20, an input device 30, and a prediction device 40. The hydroelectric power plant operation support device 10 includes a calculation processing unit 12 and an operating characteristic data storage unit 14. FIG. 1 also shows each dam Di (1≦i≦n) in a schematic diagram. The subscript "i" is a subscript attached to the variable of each dam or each power plant. n is a natural number and can be set to any number.

[0015] The devices related to the operation support system 1 may not be located at one location but may be distributed across multiple locations, and may be configured as a system that links devices located in remote locations via a communication system. In the following explanation, when describing events that are common to each dam or each power plant, the symbol "i" may not be added.

[0016] Each dam Di (1≦i≦n) is equipped with a generator Pi, a water level gauge WLi, an inflow meter Iqi, an outflow meter Oqi, etc. The hydroelectric power plant operation support device 10, the prediction device 40, the generator Pi, the water level gauge WLi, the inflow meter Iqi, the outflow meter Oqi, etc. are configured to be able to exchange signals containing various information with each other via a network nw. As a result, information such as the rotation speed of each generator Pi (1≦i≦n), the amount of water supplied, the amount of power generated, the total head, and the amount of inflow to each dam Di (1≦i≦n) is supplied to the hydroelectric power plant operation support device 10 and the prediction device 40. Hereinafter, the hydroelectric power plant operation support device 10 may be simply referred to as the operation support device 10.

[0017] The generator Pi may be, for example, a water turbine generator, and may be composed of a plurality of generators. That is, the power plant Ppi has at least the generator Pi.

[0018] The operation support device 10 is configured to include, for example, a CPU (Central Processing Unit), an MPU (Micro Processor Unit), RAM, and ROM, and configures each processing unit by executing programs stored in the RAM and ROM. This operation support device 10 is a device that can provide information on a method for planning water system operation.

[0019] The calculation processing unit 12 of the operation support device 10 calculates an operation plan for the amount of water used for power generation at each power plant Ppi (1≦i≦n) and the amount of discharge at each dam Di (1≦i≦n) in chronological order, based on, for example, the operating characteristic data of each power plant Ppi (1≦i≦n), the inflow prediction data of each dam Di (1≦i≦n), and the constraints of each dam Di (1≦i≦n). In addition, the hydroelectric power plant operation support device 10 can graph the operation plan and display it on the display device 20. Details of the calculation processing unit 12 will be described later using FIG. 3.

[0020] The operating characteristics data storage unit 14 is configured with, for example, an HDD (hard disk drive) or an SSD (solid state drive). As described above, the operating characteristics data storage unit 14 stores information such as the rotation speed, supply water volume, power generation volume, water level, and inflow volume to each dam Di (1 ≦ i ≦ n) of each generator Pi (1 ≦ m ≦ n) in chronological order. It also stores operating characteristics data for each power plant Ppi (1 ≦ i ≦ n).

[0021] The operational characteristics data includes pipeline loss characteristic data, generator characteristic data, and turbine characteristic data for each power plant Ppi (1≦i≦n). Furthermore, water volume power generation data, which indicates the relationship between the amount of water used for power generation and the power output calculated using these data, is stored. Furthermore, high-efficiency route data, high-power route data, and other data generated using this water volume power generation data are stored. Details of these data will be described later.

[0022] The display device 20 is, for example, a monitor, and displays image information generated by the operation support device 10.

[0023] The input device 30 includes, for example, a mouse and a keyboard. The input device 30 inputs operation signals according to instructions from an operator to the hydroelectric power plant operation support device 10.

[0024] The prediction device 40 predicts the time-series inflow of water into the water system using weather forecasts, rainfall information, and snow accumulation information supplied from the Japan Meteorological Agency's server 50 via the network nw. More specifically, the prediction device 40 associates time-series data of past weather forecasts, rainfall information, and snow accumulation information with actual data on past inflows to each dam Di (1≦i≦n) and stores them in a storage unit. For example, such actual data is stored for several years or more.

[0025] The prediction device 40 uses this performance data to train a prediction model that inputs weather forecasts, rainfall information, and snow accumulation information and outputs the inflow amount qin (1≦i≦n) to each dam Di (1≦i≦n). For this type of training, a general neural network learning model or a multivariate analysis model such as linear regression can be used.

[0026] The prediction device 40 is supplied with time-series forecast data of three days' worth of weather forecast, rainfall information, and snowfall information, for example, in 30-minute increments. This enables the prediction device 40 to use a prediction model to output to the operation support device 10, in 30-minute increments, a three-day forecast value of the inflow amount qini (1≦i≦n) of water flowing into each dam Di (1≦i≦n).

[0027] Alternatively, the prediction device 40 uses weather forecasts, rainfall information, and snowfall information supplied via the network nw to refer to past weather forecasts, past rainfall information, etc. stored in the memory unit, and also refers to the actual data on past inflow volumes of each dam stored in the memory unit, and outputs predicted values ​​of the inflow volume qini (1≦i≦n) of water flowing into each dam in chronological order.

[0028] Here, instead of the actual data on the inflow of each dam, it is also possible to input the actual data on the discharge amount, water intake amount for power generation, and water level change of each dam and use the calculated inflow of each dam. Alternatively, the inflow of each dam can be predicted by predicting the flow rate of the river flowing into each dam.

[0029] (Water system model) The river system model according to this embodiment will be described with reference to Fig. 2. Fig. 2 is a diagram showing an example of a model of a river system that is the subject of a river system operation plan.

[0030] The model shown in Figure 2 is an example of a model for a dam water system in which multiple dams D1, D2, and D3 are connected. Here, for simplicity, an example of a three-stage dam will be described, but this is not limited to this and an i-stage dam may also be used. As mentioned above, i is in the range of 1≦i≦n, and n is any natural number.

[0031] Dams D1, D2, and D3 are each equipped with a generator P1, P2, and P3 that generates electricity using water taken from the dam. Generators P2 and P3 are examples of two generators. The amounts of water used for power generation q1 to q3 after being used by the generators at each dam are sent to the next dam together with the amounts of water qd1 to qd3 released from the dam gates of each dam D1 to D3.

[0032] The inflows of water into dams D1, D2, and D3 are qin1, qin2, and qin3, respectively. The total heads of dams D1, D2, and D3 are h1, h2, and h3, respectively. The water storage volumes of dams D1, D2, and D3 are v1, v2, and v3, respectively. The power generation volumes of generators P1, P2, and P3 are p1, p2, and p3, respectively. The power generation volumes of generators P1, P2, and P3 are sometimes referred to as power generation output or turbine power generation output.

[0033] The calculation processing unit 12 according to this embodiment will be described with reference to Fig. 3. Fig. 3 is a block diagram showing an example of the configuration of the calculation processing unit 12 according to this embodiment, which is capable of generating an operation plan using a water system model such as Fig. 2 and Fig. 10 described later.

[0034] The calculation processing unit 12 executes various calculation processes and includes an acquisition unit 100, a characteristic data generation unit 102, a control unit 104, and an operation plan calculation unit 106.

[0035] The acquisition unit 100 is an input interface between the network nw and the input device 30. The acquisition unit 100 acquires information such as the rotation speed, supply water volume, power generation volume, water level, and inflow volume to each dam Di (1 ≦ i ≦ n) of each generator Pi (1 ≦ i ≦ n) in chronological order via the network nw, and stores the information in the operating characteristics data storage unit 14. In addition, the acquisition unit 100 acquires operating characteristics data of each power plant Ppi (1 ≦ i ≦ n) via the network nw and stores the data in the operating characteristics data storage unit 14.

[0036] [Processing of characteristic data generation part] The characteristic data generating unit 102 generates pipeline loss characteristic data (see FIG. 4 described later), water turbine characteristic data (see FIG. 5 described later), and generator characteristic data (see FIG. 7 described later) when these data cannot be acquired via the network nw. The characteristic data generating unit 102 also generates water volume power generation data (see FIGS. 8 and 9 described later) that indicates the relationship between the amount of water used for power generation and the power output, using the pipeline loss characteristic data, water turbine characteristic data, and generator characteristic data. Furthermore, the characteristic data generating unit 102 generates high-efficiency route data (see FIGS. 8 and 9 described later) and high-power route data (see FIGS. 8 and 9 described later) using the water volume power generation data. Details of the characteristic data generating unit 102 will be described later using FIGS. 4 to 9.

[0037] The control unit 104 controls the entire operation support system 1. The control unit 104 also causes the display device 20 to display charts, numerical values, and the like generated by the operation plan calculation unit 106, which will be described later.

[0038] The operation plan calculation unit 106 calculates the inflow q of each dam Di (1≦i≦n) supplied via the network nw. ini (t) Using the forecast data (1≦i≦n), the amount of water used for power generation at each power plant Ppi (1≦i≦n) q i (t)(1≦i≦n), discharge amount q di (t)(1≦i≦n), power generation amount p i (t) (1≦i≦n) and other information, at least the amount of water used for power generation q i Calculate an operation plan including (t) (1≦i≦n), where t represents time.

[0039] Inflow amount q ini The prediction data (t) (1≦i≦n) may be data generated by the prediction device 40, or may be data supplied from another device via the network nw.

[0040] The management plan calculation unit 106 includes an evaluation model generation unit 108, an evaluation function generation unit 110, a constraint condition generation unit 112, an optimization calculation processing unit 114, and a plan generation unit 116. Details of the management plan calculation unit 106 will be described later.

[0041] Here, the characteristic data generating unit 102 will be described in detail. Fig. 4 is a diagram showing pipe loss characteristic data. The horizontal axis represents the amount of water used for power generation q [m 3 / s], and the vertical axis is the pipeline pressure loss (pipe loss head) l [m]. Pipe pressure loss l [m] indicates the pressure loss due to, for example, the gradient of the water conduit or friction in the penstock. Line L10 indicates the pipeline pressure loss l [m] when one unit is operating, and line L20 indicates the pipeline pressure loss l [m] when two units are operating. Water consumption for power generation q and turbine flow rate q t The relationship is q=N q t N indicates the number of operating vehicles. Note that in this embodiment, the units are used as examples, but are not limited to these. For example, any unit can be used as the unit according to this embodiment.

[0042] The pipeline pressure loss l [m] can be generated using, for example, the pipeline inflow loss coefficient, the pipeline pre-inflow flow velocity [m / s], and the pipeline post-inflow flow velocity [m / s], etc. In this way, the characteristic data generation unit 102 can generate pipeline loss data l [m] for cases where there is one generator and cases where there are two generators.

[0043] The characteristic data generator 102 generates the effective head (hl) [m] by subtracting the pipeline pressure loss l [m] from the total head h [m]. The total head h [m] indicates, for example, the difference in elevation between the intake level (the water surface elevation at the intake point) and the tailwater level (the water surface elevation at which water is discharged from the power plant).

[0044] Figure 5 shows the turbine efficiency η t The horizontal axis is the rotation speed per unit head n / Sqrt(hl), and the vertical axis is the flow rate per unit head q t / Sqrt(hl). The flow rate per unit head is the turbine flow rate q t [m 3 / s] divided by the square root of the effective head (hl) [m]. t [%] is the ratio of the turbine output to the theoretical power. Also, the amount of water used for power generation q [m 3 / s] is expressed by equation (1) using the number N of generators used for power generation.

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[0045] Figure 6 shows the generator efficiency η g The horizontal axis represents the load factor p t / p tR The vertical axis is the generator efficiency η g [%]. Load factor p t / p tR is the rated turbine output p tR and turbine power output p t The ratio of the turbine power output p t is expressed by equation (2), where g is the gravitational acceleration and ρ is the density of water.

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[0046] 7 is a flowchart showing an example of the process for generating water volume power generation data showing the relationship between the amount of water used for power generation and the power generation output by the characteristic data generation unit 102. The power generation output p [MW] of each generator Pi (1≦i≦n) is shown in equation (3), where N is the number of generators used for power generation.

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[0047] As shown in FIG. 7, the characteristic data generating unit 102 calculates the power generation output p [MW] and the amount of water used for power generation q [m 3 That is, the characteristic data generating unit 102 generates characteristic data (FIGS. 8 and 9 described later) showing the relationship between the power generation output pi(1≦i≦n) [MW] and the amount of water used for power generation qi(1≦i≦n) [m 3 / s] (see Figures 8 and 9).

[0048] First, the characteristic data generating unit 102 acquires the total head h [m] within the possible range (step S100). 3 / s] (see equation (1)) are used as input values, and each is shifted (step S102), and the calculation of the power generation output p [MW] (see equation (3)) is repeated (step S103).

[0049] Fig. 8 is a diagram showing water volume power generation data showing the relationship between power generation output and water volume used for power generation. Fig. 8 is an example of characteristic data when the number of generators is one (N=1). The horizontal axis represents the water volume used for power generation q [m 3 / s] (see equation (1)), and the vertical axis represents the power generation output p [MW] (see equation (3)). As shown in FIG. 8, the characteristic data generating unit 102 calculates the minimum value h L [m] to maximum value h h Calculate the power generation output p for the amount of water used for power generation q within the range of [m].

[0050] Furthermore, the characteristic data generating unit 102 generates characteristic data showing the relationship between the power generation output p and the amount of water used for power generation q, and then generates a high-efficiency path Lq1 and a maximum output path Lq2 for each total head h. The high-efficiency path Lq1 is the most efficient operating point where the ratio between the power generation output p and the amount of water used for power generation q is maximized, and for example, (q 1L , p 1L ) and (q 1H , p H). In the case of maximizing the power-water ratio, which is the ratio between the power output (amount of generated power) p [MW] and the amount of water used for power generation q, the most efficient operating point is used as a constraint. The maximum output path Lq2 is the power plant maximum output operating point where the power output p is at its maximum value, for example, (q 2L , p 2L ) and (q 2H , p 2H ) is the line connecting

[0051] Fig. 9 is a diagram showing water volume power generation data showing the relationship between the power generation output and the amount of water used for power generation when there are two generators. The horizontal axis represents the amount of water used for power generation q [m 3 / s] (see equation (1)), and the vertical axis is the power generation output p [MW] (see equation (3)). The example up to the maximum output path Lq2 is a power generation example with one unit (N = 1), and the range using a power generation water consumption q greater than the maximum output path Lq2 is a power generation example with two units (N = 2).

[0052] The high-efficiency route Lq3 is the most efficient operating point when generating power with two units (N=2), where the ratio of power output p to water consumption q is maximized. For example, (q 3L , p 3L ) and (q 3H , p 3H The maximum output path Lq4 is the power plant maximum output operating point where the power output p is maximum when two units (N=2) are generating power. For example, (q 4L , p 4L ) and (q 4H , p 4H ) The characteristic data generation unit 102 stores characteristic data including the high-efficiency paths Lq1i, Lq3i (1≦i≦n) and maximum output paths Lq2i, Lq4i (1≦i≦n) of each generator Pi (1≦i≦n) in the operation characteristic data storage unit 14 (see FIG. 1).

[0053] [Operation plan calculation section processing] Referring again to FIG. 3, the detailed processing of the operation plan calculation unit 106 will be described.

[0054] FIG. 10 is a diagram showing an example of a calculation model generated by the evaluation model generation unit 108 of the operation plan calculation unit 106. Here, for ease of explanation, a two-stage dam is shown. In FIG. 10, as described above, i indicates the dam number and is in the range of 1≦i≦n. n is a natural number. In other words, for ease of explanation, FIG. 10 shows a two-stage dam as an example where 1≦i≦2, but is not limited to this. Note that the inflow q ini (t) is the predicted value of, for example, the prediction device 40 (see FIG. 1).

[0055] Figure 11 shows the relationship between various decision variables at each time step Δt. i (t), total head h i (t), water consumption for power generation q i (t), power output p i As described above, (t) satisfies the relationships of equations (1) to (5). As an example, the sampling Δt of the operation plan is set to 30 minutes. Therefore, when a two-day operation plan is targeted, nt = 96, that is, t = 1, 2, ..., 96. Note that the time step Δt according to this embodiment is, for example, 30 minutes, but is not limited to this.

[0056] The evaluation model generation unit 108 calculates the inflow q ini (t), dam water storage v i (t), total head h i (t), water consumption for power generation q i (t), discharge amount q di (t), power output p i The evaluation model generation unit 108 models the relationship between the dam water volume v i (t) is modeled as a dam water storage model using equation (4). For example, each unit example has an inflow q ini (t)[m 3 / s], dam water volume v i (t)[m 3 ], total head h i (t) [m], water consumption for power generation q i (t)[m 3 / s], discharge amount q di (t)[m 3 / s], power output pi (t) [MW].

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[0057] Also, the dam water volume v i (t) and total head h i The dam characteristics that show the relationship with (t) are coefficient a i、 b i The characteristic data generating unit 102 uses, for example, the coefficient a i、 b i is calculated in advance by linear regression analysis and stored in the driving characteristics data storage unit 14 (see FIG. 1).

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[0058] The evaluation function generating unit 110 generates an evaluation function H shown in equation (6). i (yen / kWh) can be obtained from the power company or power retailer that purchases the electricity via the network nw. When selling electricity to the wholesale electricity market, the electricity trading price is predicted and the electricity unit price c i (yen / kWh) may be set. That is, the evaluation function H shown in equation (6) is an evaluation function when the objective is to maximize the amount of electricity sold.

[0059] In addition, the electricity unit price c i If is set to a constant value, for example, 1, the evaluation function H indicates the total amount of power generated in the target water system during the operation plan period. In other words, the evaluation function H shown in equation (6) is i By setting H to a constant value, it becomes an evaluation function for the purpose of maximizing the amount of power generated. Note that the evaluation function H may be minimized by adding a negative value.

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[0060] The constraint generating unit 112 generates constraints for maximizing the evaluation function H. Referring again to FIGS. 8 and 9, in this embodiment, the amount of water used for power generation q i (t) and power output p i The relationship between (t) and the power plant is set to high-efficiency path Lq1, maximum output path Lq2, high-efficiency path Lq3, and maximum output path Lq4. This makes it possible to quickly calculate the evaluation function shown in equation (6) according to the objective. For example, if the objective is maximum efficiency, high-efficiency paths Lq1 and Lq3 are used as constraints. On the other hand, if the objective is maximum output, maximum output paths Lq2 and Lq4 are used as constraints. Operating points may be added and introduced into the constraints according to the circumstances of the target hydroelectric power plant. The following explains an example in which high-efficiency paths Lq1 and Lq3 and maximum output path Lq4 are used as constraints. This is a case in which the high-efficiency operating points for each number of operating units of the power plant and the operating point of the power plant's maximum output can be operated.

[0061] The constraint condition generator 112 generates the following constraint equations for each dam Di (1≦i≦n). Equations (7) and (8) are examples of constraint equations when selectively using the high-efficiency paths Lq1, Lq3, and the maximum output path Lq4. In other words, it is also possible to select the high-efficiency paths Lq1, Lq3, and the maximum output path Lq4 for each dam Di (1≦i≦n).

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[0062]

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[0063] FIG. 12 is a table illustrating the selection of the operating point. As shown in FIG. 0i (t), z 1i (t), z 2i (t), z 3i (t) indicates 0 or 1. 0i When (t) is 1, power generation is stopped. 1iWhen (t) is 1, the highly efficient route Lq1 is the constraint. 1i When (t) is 1, the most efficient operating point is the constraint when there is one operating vehicle.

[0064] Similarly, z 2i When (t) is 1, the highly efficient route Lq3 is set as a constraint. 2i When (t) is 1, the most efficient operating point is the constraint when there are two operating vehicles. 3i When (t) is 1, the maximum output route Lq4 is the constraint. 3i When (t) is 1, the maximum output operating point is the constraint when there are two operating vehicles.

[0065] Also, as shown in equation (10), z 1i When (t) is 1, by using equations (11) and (12) as linear constraints, the high-efficiency route Lq1 is i (t) and power output p i (t) moves.

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[0066] Similarly, as shown in equation (13), z 2i When (t) is 1, by using equations (14) and (15) as linear constraints, the high-efficiency route Lq3 is i (t) and power output p i (t) moves.

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[0067] Similarly, as shown in equation (13), z 2i When (t) is 1, by using equations (14) and (15) as linear constraints, the high-efficiency route Lq3 is i (t) and power output p i (t) moves.

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[0068] The optimization calculation processing unit 114 uses the relational expressions (1) to (5) as constraint conditions and executes a calculation to maximize the evaluation function H shown in equation (6). In this case, the constraint conditions are additionally the relations of equations (7) to (18). As described above, the optimization calculation processing unit 114 executes a calculation to maximize the evaluation function H using 30 minutes (see FIG. 11) as an example of the sampling Δt of the operation plan. Here, the optimization calculation processing unit 114 can use, for example, a general solver compatible with mixed integer programming to calculate a solution to the optimization problem to maximize H.

[0069] The plan generation unit 116 calculates the inflow q of each dam Di (1≦i≦n) for each time step Δt. ini (t), dam water storage v i (t), total head h i (t), water consumption for power generation q i (t), discharge amount q di (t), power output p i Therefore, when a two-day operation plan is targeted, the plan generation unit 116 generates an operation plan that includes at least information on nt=96, i.e., t=1, 2, ..., 96 (see FIG. 11).

[0070] The control unit 104 displays the operation plan table for each power plant Ppi (1≦i≦n) generated by the plan generation unit 116 on the display device 20. The control unit 104 can also send the plan to the power generation control device of each power plant Ppi (1≦i≦n) to enable automatic operation. In a water system operated by an operator, the power plant operator can refer to the operation plan on the display device 20 and operate the water system himself.

[0071] Fig. 13 is a flowchart showing an example of processing by the hydroelectric power plant operation support device 10. As shown in Fig. 13, first, the acquisition unit 100 stores the operating point, initial water level, and final water level of each power plant Ppi (1 ≦ i ≦ n) selected by the operator via the input device 30 in the operation characteristic data storage unit 14 (step S200). Here, the operating point is the most efficient operating point and the power plant maximum output operating point, and can be selected for each power plant Ppi (1 ≦ i ≦ n).

[0072] Next, the acquisition unit 100 acquires the inflow amount q in the prediction period via the network nw. ini (t) (1≦i≦n) and the current total head hi (1≦i≦n) are acquired and stored in the operation characteristics data storage unit 14 (step S202).

[0073] Next, the evaluation function generation unit 110 generates an evaluation function based on this initial information (step S204). Subsequently, the optimization calculation processing unit 114 executes a calculation to maximize the evaluation function H shown in equation (6) using the relational expressions (1) to (5) (step S206). The constraint conditions used in this calculation are the relations of equations (7) to (18).

[0074] Then, the plan generation unit 116 calculates the inflow q of each dam Di (1≦i≦n) for each time step Δt. ini (t), dam water storage v i (t), total head h i (t), water consumption for power generation q i (t), discharge amount q di (t), power output p i (t) is graphed and output to the display device 20 (step S208), and the process ends.

[0075] In this way, we can provide a method for planning water system operation that enables maximum operation of generated power by selecting high-efficiency operation that includes the time change in total head (static head) hi, which changes according to the change in the water storage volume of dam Di (1≦i≦n), the pipeline pressure loss l in the branch pipeline that varies for each number of operating units N (see Figure 4), and maximum output operation of the power plant. This makes it possible to generate operation plans with higher accuracy.

[0076] Additionally, for each dam Di (1≦i≦n), an operating point is selected from the high-efficiency operating point and the maximum output operating point, and these are added as constraints to maximize the evaluation function. This eliminates the need for repeated steps to derive the optimal solution by updating constraints to match the head caused by changes in dam water volume in the optimization process that maximizes the evaluation function, making it possible to reduce the computational load while preventing a decrease in the accuracy of the hydroelectric power plant operation plan. Therefore, it is possible to consider the total head (static head) hi caused by changes in dam water volume without a trade-off between computational load and planning accuracy, making it possible to provide a practical water system operation plan.

[0077] Furthermore, since the water system operation plan is calculated among the most efficient operating points for each number of operating units N for each power plant Ppi (1≦i≦n) and the operating point including the power plant's maximum output operating point, it is possible to reduce the number of operational changes to the water consumption for power generation at each power plant Ppi (1≦i≦n) for water systems operated by operators, such as private power generation systems. This supports efficient water system operation by operators. Furthermore, by selecting a combination of operating points to be output as an operation plan from the operating points included in the operating characteristic data for each power plant Ppi (1≦i≦n), it is possible to provide a water system operation plan tailored to the power plant's needs.

[0078] As described above, according to this embodiment, the evaluation function generating unit 110 calculates the time-series amount of water used for power generation q taken from the reservoir of the dam Di (1≦i≦n). i The power output p changes over time according to (t) i The sum of the power generation values ​​for (t) (1≦i≦n) is generated as the evaluation function H (equation (6)). Then, the optimization calculation processing unit 114 calculates the time-series power generation water consumption qi (t) (1≦i≦n) and the time series power output p i (t)(1≦i≦n) is expressed as the water storage volume v of dam Di(1≦i≦n). i (t) (1≦i≦n) based on the head h i (t) (Equation (5)) is constrained to a predetermined operating point (Equations (7) to (18)), and the time series of power generation water consumption q is calculated so that the evaluation function H is maximized. i We decided to generate a planned value for (t) (1≦i≦n).

[0079] As a result, in the optimization process to maximize the evaluation function H, there is no need to repeatedly derive the optimal solution by updating the constraint conditions to match the head caused by changes in the dam water volume, making it possible to reduce the calculation load while suppressing a decrease in the accuracy of the operation plan for the power plant Ppi (1≦i≦n). [Explanation of symbols]

[0080] 1: Hydroelectric power plant operation support system, 10: Hydroelectric power plant operation support device, 20: Display device, 30: Input device, 40: Prediction device, 100: Acquisition unit, 102: Characteristic data generation unit, 110: Evaluation function generation unit, 114: Optimization calculation processing unit, 116: Plan generation unit, Di (1≦i≦n): Dam, h i (t)(1≦i≦n): Total head, l: Pipe loss length, Pi (1≦i≦n): Hydrogenerator, p i (t)(1≦i≦n): Power generation output (power generation amount), Ppi(1≦i≦n): Power plant, qi(1≦i≦n): Water consumption for power generation, qini(1≦i≦n): Inflow, v i (t): Dam water volume

Claims

1. an evaluation function generating unit that generates an evaluation function based on the power generation output of the generator that changes over time in accordance with the time-series amount of water used for power generation that is taken from the water storage in the dam; an optimization calculation processing unit that generates a planned value of the time-series amount of water used for power generation so as to maximize the evaluation function by constraining the time-series amount of water used for power generation and the relationship between the time-series amount of water used for power generation and the time-series amount of power generation output to a predetermined operating point that changes according to a head based on the amount of water stored in the dam; An operation support device for a hydroelectric power plant, comprising:

2. 2. The hydroelectric power plant operation support device of claim 1, wherein the time series water consumption for power generation is a planned value corresponding to the time series predicted value of the dam inflow into the dam, and the head changes over time based at least on the time series predicted value of the dam inflow and the time series planned value of the water consumption for power generation.

3. 2. The hydroelectric power plant operation support device according to claim 1, wherein the operating point is a maximum efficiency operating point at which the power generation efficiency of the power generation output relative to the amount of water used for power generation is maximized.

4. The hydroelectric power plant operation support device according to claim 3 , wherein the operating point is a maximum output operating point at which the power generation output relative to the amount of water used for power generation is maximized.

5. 5. The hydroelectric power plant operation support device according to claim 4, wherein the optimization calculation processing unit is capable of selecting, as the constraint, either an operating point with maximum efficiency or an operating point with maximum output.

6. 6. The hydroelectric power plant operation support device according to claim 1, wherein the optimization calculation processing unit, when the power generation output is output by a plurality of water turbine generators, restricts the operating point to an operating point according to the number of generators.

7. an operation plan generating unit that generates an operation plan including at least one of the head that changes over time, the planned value of the water consumption for power generation over time, and the planned power generation output over time; The hydroelectric power plant operation support device according to claim 6, further comprising:

8. The head is a total head, and becomes an effective head by subtracting the pipeline pressure loss in the pipeline used for power generation. an operating characteristics data storage unit that stores pipeline loss characteristics data that indicate the relationship between the amount of water used for power generation and the pipeline pressure loss, turbine characteristics data that indicate the turbine efficiency of the turbine generator that changes depending on the effective head, the rotational speed of the turbine generator, and the amount of water used for power generation, and generator characteristics data that indicate the generator efficiency of the turbine generator that changes depending on the power generation output of the turbine generator; a characteristic data generating unit that generates information on the operating points using the pipeline loss characteristic data, the water turbine characteristic data, and the generator characteristic data, and stores the information in the operating characteristic data storage unit; Further provided with 8. The hydroelectric power plant operation support device according to claim 7, wherein the optimization calculation processing unit generates the planned value of the time-series amount of water used for power generation using information on the operating points stored in the operating characteristics data storage unit.

9. 9. The hydroelectric power plant operation support device according to claim 8, wherein the optimization calculation processing unit is capable of defining the operating point as a linear expression using the amount of water used for power generation and the power generation output.

10. The hydroelectric power plant operation support device of claim 9, wherein the evaluation function is an added value in which a constant value is assigned as a coefficient of the power generation output when maximizing the amount of power generated, and is an added value in which the unit price of electricity is assigned as a coefficient of the power generation output when maximizing the amount of power sold.

11. 11. The hydroelectric power plant operation support device according to claim 10, wherein in the case of maximizing the electricity-to-water ratio, which is the ratio between the amount of generated electricity and the amount of water used for power generation, the most efficient operating point is used as a constraint condition.

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