CN102691333A

CN102691333A - Central waterworks monitoring and controlling device, waterworks monitoring and controlling system, and waterworks monitoring and controlling program

Info

Publication number: CN102691333A
Application number: CN2012100780235A
Authority: CN
Inventors: 足立进吾; 河原林雅; 高桥信补; 佐藤达广; 安富弘泰; 田所秀之
Original assignee: Hitachi Ltd
Current assignee: Hitachi Ltd
Priority date: 2011-03-22
Filing date: 2012-03-22
Publication date: 2012-09-26
Anticipated expiration: 2032-03-22
Also published as: WO2012127977A1; JP5416729B2; JP2012197629A; CN102691333B

Abstract

Provided is a central waterworks monitoring and controlling device which is capable of taking into account the nonlinearity and multi-valuedness of an amount of flow and a cost, and, by using cost calculation with a suppressed calculation load, makes a waterworks operation plan and performs facility control such that the operation cost is minimized. A central waterworks monitoring and controlling device for controlling a water conveying and distributing pump facility or the like comprises: an equipment characteristics storage unit for storing the equipment characteristics of each pump; a control rule storage unit for storing an operation method, etc. of the facility to be controlled; a cost model constructing unit for constructing a cost model on the basis of the stored equipment characteristics and the control rule; a cost calculation unit for estimating the operation cost of waterworks operation plan data by using the cost model; an operation plan optimization unit for creating waterworks operation plan data minimizing the operation cost estimated by the cost calculation unit; and a communication unit for transmitting the optimum operation plan data to the facility to be controlled.

Description

Water course central monitoring control device, water course monitoring control system, and water course monitoring control program

Technical Field

The present invention relates to a central waterworks monitoring and control device, a waterworks monitoring and control system, and a waterworks monitoring and control program, and more particularly, to a central waterworks monitoring and control device, a waterworks monitoring and control system, and a waterworks monitoring and control program for rescuing an optimal operation plan for cost evaluation and controlling a waterworks facility based on the operation plan.

Background

As background art in this field, there are patent document 1 and patent document 2. The technique described in patent document 1 is to propose a water supply facility operation evaluation device capable of evaluating the operation cost of the entire water supply facility by calculating the operation cost (chemical cost and electric power cost) of the entire water supply facility.

The technique described in patent document 2 is capable of accurately evaluating a difference in power consumption of a pump and a blower due to a change in equipment configuration and operation method.

Patent document 1: japanese laid-open patent publication No. 2002-

Patent document 2: japanese patent laid-open No. 2007 & 249374

Patent document 1 describes a structure of a water supply line operation evaluation device. However, the water supply line operation evaluation device of patent document 1 can only evaluate the cost in proportion to the daily amount of the water intake amount, the water delivery amount, and the water distribution amount.

In such a water supply line operation evaluation device, for example, as represented by the water distribution amount, there is a nonlinearity between the flow rate and the cost (power consumption), and in some cases, an evaluation error of the cost is large in an evaluation object in which the flow rate change in one day is large. In general, the number of pumps is controlled by a number control rule, and the number of pumps operated differs and the cost (power consumption) differs even for the same amount of water to be distributed when the amount of water to be distributed increases and decreases, and this phenomenon is called natural polarization. In the water supply line operation evaluation device of patent document 1, natural polarization cannot be taken into consideration, and an evaluation error of cost may be large. In other words, the multivalue of the cost with respect to the flow rate cannot be considered. Further, due to the above-described error, there is a case where a water supply line operation plan to be evaluated and control based on the plan leave room for further improvement.

Patent document 2 describes a configuration of an energy diagnosis device. However, the energy diagnosis device of patent document 2 requires a simulation device for estimating the energy in a facility in which a plurality of pumps are controlled in cooperation with each other, the simulation device being provided for the discharge amount of the individual pump or for calculating the discharge amount of the individual pump.

In such an energy diagnosis device, for example, when a facility operation method for minimizing the energy consumption of the entire water channel facility is determined by an optimization technique using the evaluation of the energy diagnosis device, the calculation time for the optimization calculation may increase due to the fact that a search space for determining the operation method until the discharge amount of the individual pump is determined becomes enormous, or the amount of calculation of a simulation device for calculating the discharge amount of the individual pump is large.

Disclosure of Invention

Accordingly, the present invention provides a central monitoring and control device that can perform planning and facility control of a waterway operation plan with the minimum operation cost by using cost calculation in which the calculation load is suppressed, while taking into consideration the nonlinearity and multivalue of the flow rate and the cost. For example, particularly, a central monitoring control device is provided which finds an optimal operation plan with respect to non-linearity corresponding to a significant flow rate and cost in a distribution pump facility and cost evaluation considering natural polarization of the number of pumps in operation, and controls a water channel facility based on the operation plan.

In order to solve the above problem, for example, the structure described in the claims is adopted.

The present application includes a plurality of solutions to the above-described problem, and if an example thereof is given, the present application is a waterway central monitoring control device 101 that controls a water intake pump facility, a water supply pump facility, a water distribution pump facility, and the like, and includes: an equipment characteristic storage unit 121 that stores equipment characteristics for each pump of the facility to be controlled; a control rule storage unit 122 for storing control rules for specifying the operation modes of the respective pump machines in the controlled facilities; a cost model constructing unit 111 that constructs a cost model for each control target facility based on the information of the device characteristic storage unit and the control rule storage unit, and stores the cost model in the cost model storage unit 123; a cost calculation unit 112 that evaluates the operation cost of the water course operation plan data using the cost model stored in the cost model storage unit 123; an operation plan optimization unit 113 for creating optimal water course operation plan data for minimizing the operation cost evaluated by the cost calculation unit 112; a communication unit 142 that transmits the optimal operation plan data to the controlled facility; and a human-machine interface section 141 that interfaces with an operator; the cost model is configured by a state transition relationship in which the number of pump operation units of the facility to be controlled is set as a state, and a function in which a cost is given by setting the discharge flow rate of the facility to be controlled in each state as an input, and the cost calculation unit 112 is configured by a state transition machine that executes a state transition expression of the cost model.

The invention has the following effects:

according to the present invention, it is possible to provide a central monitoring and control device and a waterway monitoring and control system that find an optimal operation plan for evaluating the nonlinearity of flow rate and cost that are significant in a distribution pump facility and the cost in consideration of natural polarization of operation of the number of pumps, and control a waterway facility based on the operation plan.

Problems, configurations, and effects other than those described above will become apparent from the following description of the embodiments.

Drawings

Fig. 1 is a block diagram of a water supply monitoring control system.

Fig. 2 is a block diagram illustrating a configuration of a control target device of a control target facility.

Fig. 3 is a hardware block diagram of the central monitoring and control device for water supply.

Fig. 4 is a diagram illustrating an apparatus characteristic table.

Fig. 5 is a graph of flow-head characteristics, which are elements of the equipment characteristic table.

Fig. 6 is a graph of flow rate-efficiency characteristics, which are elements of the device characteristic table.

Fig. 7 is a diagram illustrating a control rule table.

Fig. 8A is a table of discharge pressure settings as elements of the control rule table.

Fig. 8B is a diagram of a pipeline model as an element of the control rule table.

Fig. 9 is an example of a pump number switching flow table as an element of the control rule table.

Fig. 10 is a diagram illustrating a cost model table stored in the cost model storage unit.

Fig. 11A is a state transition diagram showing a state transition relationship of a cost model, which is an element of the cost model table.

Fig. 11B is a graph of the traffic-cost relationship of the cost model, which is an element of the cost model table.

Fig. 12A is a state transition diagram showing a state transition relationship of a cost model, which is an element of the cost model table.

Fig. 12B is a graph of the traffic-cost relationship of the cost model, which is an element of the cost model table.

Fig. 13A is a state transition diagram showing a state transition relationship of the cost model, which is an element of the cost model table.

Fig. 13B is a graph of the traffic-cost relationship of the cost model, which is an element of the cost model table.

Fig. 14A is a state transition diagram showing a state transition relationship of a cost model, which is an element of the cost model table.

Fig. 14B is a graph of the traffic-cost relationship of the cost model, which is an element of the cost model table.

FIG. 15 is a flowchart of a cost model construction process.

Fig. 16 is operation plan data.

Fig. 17 is facility restriction data.

FIG. 18 is a flowchart for explaining the processing of the device characteristics/control rule update section

Detailed Description

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings using examples. In addition, substantially the same portions are assigned the same reference numerals, and the description thereof will not be repeated. In the present embodiment, a description will be given of a water supply pump operation optimization apparatus that constructs a cost model from plant characteristics and control rules. However, the waterway is not limited to the upper waterway, and includes a middle waterway such as an industrial waterway (working water) and rainwater reclaimed water, and an agricultural waterway.

In fig. 1, a sewer monitoring and control system 500 is composed of a sewer central monitoring and control device 101, a facility 151 to be controlled, and a facility 152 to be controlled.

The central sewer monitoring and control system 101 includes a cost model constructing unit 111, a cost calculating unit 112, an operation plan optimizing unit 113, a demand predicting unit 114, a facility characteristic storage unit 121, a control rule storage unit 122, a cost model storage unit 123, a facility restriction storage unit 124, an operation plan storage unit 125, an actual operation data storage unit 126, a human-machine interface unit 141, and a communication unit 142. The central sewer monitoring and control device 101 is connected to a controlled facility 151 and a controlled facility 152, which are objects to be monitored and controlled, via the communication unit 142.

The controlled facility 151 includes a remote facility control device 161 and a controlled device (pump) 171. Similarly, the control-target facility 152 has a remote facility control device 162 and a control-target apparatus (valve) 172.

In fig. 1, the central water supply monitoring and control system 101 is connected to only 2 facilities, i.e., the controlled facility 151 and the controlled facility 152, but is generally connected to a plurality of controlled facilities, i.e., a water distribution and delivery pump facility, a water purification plant, and a water distribution plant. Here, the facility to be controlled is a water channel facility connected to the central water channel monitoring and controlling apparatus 101 via a network. The facility to be controlled is a facility that performs either or both of collection of measurement information by the central sewer monitoring and control device 101 and transmission of information on a control method from the central sewer monitoring and control device 101.

The cost model constructing unit 111 reads the plant characteristics of the pumps of the facility to be controlled stored in the plant characteristic storage unit 121 and the control rules of the facility to be controlled stored in the control rule storage unit 122 for each facility to be controlled, such as the facility to be controlled 151, which is configured by one or more pumps, and constructs a cost model of the facility to be controlled based on the plant characteristics and the control rules. Further, the cost model building section 111 stores the built cost model in the cost model storage section 123.

The cost calculation unit 112 calculates the cost required for control with the operation plan data 340, which is given from the operation plan optimization unit 113, based on the cost model read from the cost model storage unit 123, and outputs the calculated cost as the cost data 131. However, since the operation plan data 340 is information indicating the operation methods of all the facilities to be controlled, the cost calculation unit 112 reads the cost model from the cost model storage unit 123 for each facility to be controlled, extracts the operation method of the facility from the operation plan data 340, and calculates the cost of the facility. The cost calculation unit 112 then adds all the facilities to be controlled to calculate cost data. The operating cost of all facilities of the control object is represented by formula 1.

[ number 1 ]

<math> <mrow> <mi>Ctotal</mi> <mo>=</mo> <munderover> <mi>Σ</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </munderover> <mi>C</mi> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> </mrow> </math>

… (formula 1)

In this case, the amount of the solvent to be used,

ctotal: operating costs of all facilities of a controlled object [ kWh ]

j: index of facilities representing controlled objects

M: total number of facilities of control object

C (j): the operating cost [ kWh ] of the facility j to be controlled.

The method of calculating the operation cost c (j) of each facility j will be described later in the description of fig. 11 together with the description of the cost model.

When there is a facility that is not a controlled facility but for which the operating cost is to be considered, the operating cost can be calculated and added in the same manner with the facility being regarded as a controlled facility. Although the facility is not connected to the central sewer monitoring and control device 101, there are cases where the operating cost of the facility is considered, and the like.

The cost data 131 is composed of cost information including the operating cost Ctotal of all the facilities to be controlled, and may include cost information of each facility to be controlled, in addition to the operating cost Ctotal of all the facilities to be controlled.

In the present embodiment, the cost refers to the amount of power consumption required for the operation of the pump (facility operation). However, the power consumption may be converted to obtain an index using a purchase cost (electricity rate) of the power consumption, a greenhouse effect gas conversion value of the power consumption, and the like, in consideration of a change in unit price per time slot.

The operation plan optimization unit 113 reads out the constraint conditions to be satisfied by the operation plan from the facility constraint storage unit 124, uses the predicted water supply course demand value for each region obtained from the demand prediction unit 114 as the constraint conditions, and outputs the operation plan candidates satisfying the constraint conditions as the operation plan data 340. Then, the operation plan optimization unit 113 refers to the cost data 131 calculated by the cost calculation unit 112 with respect to the operation plan data 340 that has been output before, searches for another operation plan candidate that further reduces the cost, and repeats the process of outputting the operation plan data 340. By repeating the above-described processing until a certain stop condition is satisfied, the operation plan optimization unit 113 can calculate an operation plan that minimizes the cost.

The operation plan optimization unit 113 stores the calculated optimal operation plan data in the operation plan storage unit 125. Although it depends on details of the cost model and facility constraint used, the function of the operation plan optimization unit 113 can be described as an optimization problem as a mathematical plan method. The function of the operation plan optimization unit 113 can be installed by using a modern heuristic technique using a mathematical optimization technique such as a simple method or a branch restriction method, a genetic algorithm, or the like.

The plant characteristic control rule updating unit 115 updates the plant characteristic information of the pump of the facility to be controlled based on the actual operation data stored in the actual operation data storage unit 126, and updates the stored content in the plant characteristic storage unit 121. Information such as a water supply pipeline model of the facility to be controlled is updated, and the storage content of the control rule storage unit 122 is updated.

The human-machine interface section 141 displays the various information stored in the equipment characteristic storage section 121, the control rule storage section 122, and the cost model storage section 123 on the cost data 131 calculated by the cost calculation section 112 with respect to the optimal operation plan data by a display device or the like, and presents the information to the operator of the central sewer monitoring and control device 101. The human interface section 141 may include a display device not shown.

The communication unit 142 transmits the optimal operation plan data stored in the operation plan storage unit 125 to each of the controlled facilities such as the controlled facility 151 and the controlled facility 152. The communication unit 142 collects actual operation data from each control target facility and stores the collected actual operation data in the actual operation data storage unit 126. The operational data refers to the discharge flow rate, discharge pressure, and the like of the pump facility to be controlled.

In the controlled facility 151, the operation plan data received by the remote facility control device 161 is converted into a control signal for a controlled device such as a pump, and is reflected in the operating state of the controlled device (pump) 171. The remote facility control unit 161 collects measurement information such as a discharge flow rate and a discharge pressure from each measurement device, and transmits the measurement information to the central water passage monitoring control unit 101. The same processing is performed also in the facility 152 to be controlled, and the operation of the water course facility is optimized by reflecting the optimal operation plan created by the water course central monitoring control device 101 on the operating state of the facility.

With reference to fig. 2, a configuration of a control target device (pump) 171 of a control target facility will be described. In fig. 2, the pump No. 1 machine 201 and the pump No. 2 machine 202 are variable speed pumps, and the pump No. 3 machine 203 is a constant speed pump. The discharge valve 211 is a discharge valve of the machine 201 pump 1, the discharge valve 212 is a discharge valve of the machine 202 pump 2, and the discharge valve 213 is a discharge valve of the machine 203 pump 3. The suction well 221 supplies water to the

pump

201 and 203. The measuring device 231 is a device for measuring the discharge flow rate and the discharge pressure. The arrowed lines connecting the devices represent the piping within the facility.

The remote facility control device 161 in fig. 1 transmits, as control signals, an operation stop signal of the machine 201 No. 1 pump including the opening setting of the discharge valve 211, the rotation speed of the machine 201 No. 1 pump, an operation stop signal of the machine 202 No. 2 pump including the opening setting of the discharge valve 212, the rotation speed of the machine 202 No. 2 pump, and an operation stop signal of the machine 203 No. 3 pump including the opening setting of the discharge valve 213.

Further, the remote facility control device 161 collects the operation stop state of the machine 201 No. 1 pump, the rotation speed of the machine 201 No. 1 pump, the opening degree information of the discharge valve 211, the power consumption of the machine 201 No. 1 pump, the operation stop state of the machine 202 No. 2 pump, the rotation speed of the machine 202 No. 2 pump, the opening degree information of the discharge valve 212, the power consumption of the machine 202 No. 2 pump, the operation stop state of the machine 203 No. 3 pump, the opening degree information of the discharge valve 213 pump, the power consumption of the machine 203 No. 3 pump, the water level information of the suction well 221, the discharge flow rate from the meter 231, and the discharge flow rate information.

When the power consumption meter is not provided, the power consumption may be measured by combining the current measurement value of the current meter and the measurement value of the force rate to estimate the power.

The hardware configuration of the central water supply line monitoring and control device will be described with reference to fig. 3. In fig. 3, the central water supply monitoring and control device 101 includes a Central Processing Unit (CPU)110, a memory 120, a medium input/output unit 130, an input unit 140, a communication control unit 142, a display unit 145, a peripheral IF unit 180, and a bus 190.

CPU110 executes programs in memory 120. The memory 120 temporarily stores programs, tables, and the like. The media input/output unit 130 holds programs, tables, and the like. The input unit 140 is a keyboard, a mouse, or the like. The communication control unit 142 is the communication unit 142 of fig. 1. The communication control unit 142 is connected to the network 400. The display unit 145 is the display described with reference to fig. 1. The peripheral IF unit 180 is an interface for a printer and the like. The bus 190 interconnects the CPU110, the memory 120, the media input/output unit 130, the input unit 140, the communication control unit 142, the display unit 145, and the peripheral IF unit 180.

As is clear from a comparison between fig. 1 and fig. 3, the cost model constructing unit 111, the cost calculating unit 112, the operation plan optimizing unit 113, and the need predicting unit 114 of fig. 1 are realized by the CPU110 executing a program.

The device characteristic table stored in the device characteristic storage unit 121 will be described with reference to fig. 4. In fig. 4, the plant characteristic table 300 includes a facility 301, a pump number machine 302, a flow-head characteristic 303, a flow-efficiency characteristic 304, a variable speed 305, and a normalized control range 306 of the rotation speed.

The plant characteristic table 300 holds information on each of a flow rate-head characteristic, a flow rate-efficiency characteristic, a true/false value of whether or not the rotational speed control is possible (whether or not the speed is variable), and a control range of the normalized rotational speed in the case of variable speed, for each pump number of the facility to be controlled.

The flow rate-head characteristic (Q-H characteristic curve) of one pump determined from the device characteristic information stored in the device characteristic storage unit 121 will be described with reference to fig. 5.

As described earlier with reference to fig. 4, the equipment characteristic table 300 maintains the same flow-head characteristic 303 for each pump of the control target facility. In a vortex pump which is used more frequently facing an upward water channel, it is known that the flow-head characteristic is an approximation of either formula 2 or formula 3.

H is A.Q ^2+ B.Q + C … (formula 2)

H is A.Q ^ B + C … (formula 3)

In this case, the amount of the solvent to be used,

h: full lift of pump [ m ]

Q: discharge flow rate of pump [ m ^3/h ]

A. B, C: independent coefficients in each formula

B, ^ a: and a power of the square.

When the flow-head characteristics are approximated by the above expression, the type of the approximation expression and the coefficient A, B, C may be retained. Alternatively, a plurality of pairs of representative flow rates and lift may be held as data, and the flow-lift characteristics may be approximated by a polygonal line obtained by connecting these data by straight lines.

In the case of a pump for controlling the rotation speed, the flow-head characteristics are different curves according to the change in the rotation speed, as shown by the solid-line and dashed-line curves in fig. 5. Therefore, the flow-head characteristic must be maintained for each rotational speed as the device characteristic information. The effect of the rotational speed control is generally approximated by the following formula 4 or formula 5 (a similar law of the pump).

H/S ^2 ^ certain … (formula 4)

Q/S fixed … (formula 5)

In this case, the amount of the solvent to be used,

s: rotational speed [ rpm ].

As a method of maintaining the flow-head characteristic per rotation speed, an approximation by the above-described similar law can be used. Alternatively, the flow-head characteristics of a plurality of representative rotational speeds may be maintained, and the flow-head characteristics may be approximated by interpolating other rotational speeds.

The flow rate-efficiency characteristic of one specified pump among the device characteristic information stored in the device characteristic storage unit 121 will be described with reference to fig. 6.

As with the flow-head characteristic, the equipment characteristic table 300 maintains the same flow-efficiency characteristic 304 for each pump number of the control-target facility, as previously described with reference to fig. 4. In a vortex pump that is used more frequently facing a water channel, it is known that the flow rate-efficiency characteristic is based on an approximation of either equation 6 or equation 7 below.

Eta is A.Q ^2+ B.Q … (formula 6)

Eta is A.Q ^3+ B.Q ^2+ C.Q … (formula 7)

In this case, the amount of the solvent to be used,

eta: efficiency of pump [ ]

Q: discharge flow rate of pump [ m ^3/h ]

A. B, C: coefficients independent for each formula.

When the flow rate-head characteristic is approximated by the above expression, the type of the approximation expression and the coefficient A, B, C may be retained. Alternatively, a plurality of pairs of representative flow rates and efficiencies may be held as data, and the flow rate-efficiency characteristics may be approximated by a polygonal line connecting these data with straight lines.

Here, the pump efficiency is a value obtained by dividing work performed by the pump on the discharged water by electric power supplied for driving the pump. That is, in general, the value is obtained by multiplying the pump mechanical efficiency described in the mechanical specification of the pump by the efficiency of the motor and, in the case of rotational speed control, by the efficiency of a control device such as an inverter. As a method of maintaining the efficiency characteristics, the pump mechanical efficiency, the motor efficiency, and the inverter efficiency can be maintained separately.

In the case of a pump that performs rotational speed control, the flow rate-efficiency characteristics are different curves due to a change in rotational speed, as shown by the solid-line and dashed-line curves in fig. 6. The effect of the speed control can be approximated by the similar law of the pump, as can the flow-head characteristic. Alternatively, the flow rate-efficiency characteristic may be approximated by maintaining the flow rate-efficiency characteristic at a representative rotation speed and interpolating other rotation speeds.

The power (cost) for determining the operation state of one pump can be evaluated based on the device characteristics stored in the device characteristic storage unit 121. Since the work of the pump on the discharge is expressed by the product of the discharge flow rate and the head, the electric power required for driving the pump can be expressed by equation 8.

E ═ k, Q, H/η … (formula 8)

In this case, the amount of the solvent to be used,

e: electric power required for pump driving [ kW ]

Q: discharge flow rate of pump [ m ^3/h ]

H: full lift of pump [ m ]

Eta: efficiency of pump [ ]

k: the proportionality coefficient [ kWh/m ^4 ].

However, the specification of the operating state means that Q (discharge flow rate), H (total head), η (efficiency) of the above equation are specified using the characteristics of fig. 5 and 6. The operating state changes according to the operating state of other pumps in the same facility and the characteristics of a piping water distribution area or the like where water is sent from the facility. In the case of variable speed pumps, the choice of rotational speed also affects the operating state.

The control rule table stored in the control rule storage unit 122 will be described with reference to fig. 7. In fig. 7, the control rule table 310 includes a facility 311, a number-of-operating-units switching flow rate table 312, a pump number operation order 313, the presence or absence of flow rate/pressure control 314, and a flow rate/pressure control method 315.

The control rule table 310 holds information on each of a switching flow rate table for controlling the number of pump operation units, an operation order determination method of the pump number machines, the presence or absence of control of the discharge flow rate and the discharge pressure, and a control method of the discharge flow rate and the discharge pressure, for each facility to be controlled. The operation order determination method of the pump machines is a control rule for determining the order in which a plurality of pump machines are started or stopped in a facility. Generally, the operation time of the pump is set for the purpose of equalizing the operation time. In addition, when a variable-speed pump is present in a facility, the variable-speed pump has an effect of reducing power consumption, and is generally used in preference to a fixed-speed pump. The information on the switching flow rate table for the number-of-pump-operated-units control and the manner of determining the operation order of the pump machines may be replaced with other information for specifying the transition condition of the state transition regarding the number of operated pump facilities described below with reference to fig. 11.

In a facility where discharge flow rate and discharge pressure control other than the number-of-pumps operation control is not performed, the operation state is determined by determining the pump number of the operating pump. However, when there is a variable-speed pump and when valve control is performed, there are 2 types of methods, that is, a method of setting a discharge pressure and a method of setting a discharge flow rate, among typical methods of controlling a discharge flow rate and a discharge pressure. For example, in a distribution pump facility including a variable-speed pump motor, the pump rotational speed is controlled with the discharge pressure set as a target, and the discharge flow rate is allowed to vary according to the required amount of the distribution area. Here, for example, when the controlled plant 151 is the water distribution pump plant, the setting method of the discharge pressure is stored in the remote plant control device 161, for example. The contents of the discharge pressure setting method may be held in the control rule storage unit 122. Details will be described later in the description of fig. 8A. On the other hand, in the water pump plant, the pump rotation speed and the valve opening degree are controlled with the discharge flow rate set as a target, and the discharge pressure is allowed to be arbitrarily changed within a range in which smooth water delivery is possible. However, in facilities for performing rotation speed control, in general, adjustment of the discharge flow rate and the discharge pressure by opening adjustment of the discharge valve is not performed in order to reduce energy loss of the valve (discharge valve). Here, when the controlled plant 151 is the above-described water pump plant including a variable speed pump, a model (flow rate-pressure characteristic) of a pipeline at a water delivery destination from the controlled plant 151 is necessary to estimate the rotational speed control in which the discharge flow rate is a set target. The water supply line model is also held by the control rule storage unit 122. Details will be described later in the description of fig. 8B.

A discharge pressure setting method in the control rule information stored in the control rule storage unit 122 will be described with reference to fig. 8A.

As described above in the control rule table of fig. 7, the same discharge pressure setting method is maintained for the facilities (water distribution pump facilities and the like) that perform the control based on the discharge pressure setting. Fig. 8A shows one of representative discharge pressure setting methods, namely, a method called estimated end pressure constant control.

P is P0+ C Q ^1.85 … (formula 9)

In this method, the discharge pressure is determined by equation 9 based on the discharge flow rate (or a value obtained by applying some averaging process to the discharge flow rate).

In this case, the amount of the solvent to be used,

p: discharge pressure [ kPa ]

Q: discharge flow rate [ m ^3/h ]

P0, C: and (4) the coefficient.

As in this embodiment, any method of determining the discharge pressure only from the discharge flow rate can be used. The discharge pressure setting for a constant discharge pressure can also be used for a constant control of an arbitrary discharge flow rate. On the other hand, in the system in which the discharge pressure is determined depending on the discharge flow rate of the facility or the like, the method described in detail in the description of fig. 11 can be used.

The pipeline model in the control rule information stored in the control rule storage unit 122 will be described with reference to fig. 8B.

As described above in the control rule table of fig. 7, the same line model is maintained for the plant (water pump supply plant or the like) that performs the rotational speed control set based on the discharge flow rate in the controlled plant including the variable speed pump. The line model represents a relation of a discharge pressure P [ kPa ] required for a destination line to which water is supplied from the facility when a discharge flow rate Q [ m ^3/h ] is flowing. As a representative

P is P0+ C Q ^1.85 … (10)

The linear model uses equation 10 assuming a Haiche-Williams equation as the pressure loss of the line.

In this case, the amount of the solvent to be used,

p: discharge pressure [ kPa ]

Q: discharge flow rate [ m ^3/h ]

P0, C: and (4) the coefficient.

The coefficient P0 depends on the elevation of the facility, the elevation difference of the water delivery destination (outlet of the pipeline), and C depends on the length and diameter of the pipeline.

The pressure setting method of fig. 8A and the pipeline model of fig. 8B are examples of equations having the same form, but the setting meanings are different. The information on the pressure setting method is a control parameter determined arbitrarily, whereas the information on the line model is a model of an actual control target.

The number-of-pumps-operated switching flow rate table for specifying the flow rate for switching the number of pumps operated in the control rule information stored in the control rule storage unit 122 will be described with reference to fig. 9. In fig. 9, the number-of-pumps-operated switching flow rate table 320 includes the number 321 of pumps operated after stop, the number 322 of pumps operated after start, a pump stop flow rate 323, and a pump start flow rate 324.

The number-of-pumps-operated-unit switching flow rate table 320 holds information on a flow rate serving as a reference for increasing the number of pumps operated when the discharge flow rate increases, and holds information on a flow rate serving as a reference for decreasing the number of pumps operated when the discharge flow rate decreases. If the flow rate for increasing the number of pumps is the same as the flow rate for decreasing the number of pumps, if the discharge amount varies slightly before and after the flow rate, the start and stop of the pumps may frequently occur, and the deterioration of the pumps, electrical equipment, and the like may be accelerated. Therefore, control is performed to change the flow rate at which the number of stations is increased and the flow rate at which the number of stations is decreased. This phenomenon, in which the same discharge flow rate and the number of pumps operated are different, is called natural polarization. Although the example of fig. 9 shows that no pump number is designated, a table for designating a specific pump number may be used in a facility having a plurality of pumps with different characteristics.

The cost model table stored in the cost model storage unit 123 will be described with reference to fig. 10. In fig. 10, the cost model table 330 includes facilities 331, categories 332, and cost models 333.

The cost model table 330 stores at least one category 332 and cost model information 333 for each facility 331 to be controlled. Here, the category 332 is an item indicating the degree of precision or approximation of the cost model. Details of the category 332 and the cost model 333 will be described later in the description of fig. 11 to 14.

A cost model of a certain facility including 2 variable speed pumps and 1 fixed speed pump among the cost model information stored in the cost model storage unit 123 will be described with reference to fig. 11. The facility is the distribution pump yard B in fig. 4 and 7 among the controlled devices shown in fig. 2, and is referred to as a controlled facility 151 here. This facility 151 has a total of 3 pumps of 2 variable speed pumps (machine No. 1, machine No. 2) and 1 fixed speed pump (machine No. 3).

The control performed by the remote facility control apparatus 161 will be explained. When the discharge flow rate is changed over the flow rate threshold value described in the switching flow rate table of fig. 9, the number of pump operation units is changed. When the 1 pump is operated, the 2 nd pump is started when the discharge flow rate exceeds 11m ^ 3/min.

The machine number 1 or the machine number 2 as a variable speed pump is operated preferentially, and the machine number 3 is additionally operated only when 2 machines are already operated. However, 1 or more pumps must be operated. When the machine No. 1 and the machine No. 2 are operated and 1 of them is stopped, the machine No. having a long cumulative operation time is stopped in order to average the pump operation time. The rotation speeds of machine nos. 1 and 2 were controlled so as to be the pressure setting (estimated end pressure is constant) shown in fig. 8A.

The cost model of the present embodiment includes: a state transition relationship that abstracts changes in the operating state of the pump of the facility; and a function (hereinafter referred to as a power consumption function) for calculating power consumption from the discharge flow rate of the facility in each of the states. Fig. 11A is a state transition diagram showing a state transition relationship, and fig. 11B is a graph showing a power consumption function for each state in a superimposed manner.

In fig. 11A, the states AX, AY, B, and C are information indicating that the respective pump machines of the facility are operating or in operation. Specifically, the state AX indicates an operating state in which the machine No. 1 is operating and the machines No. 2 and 3 are stopped. Fig. 11A is a state transition diagram in which control related to the number of pumps of the remote facility control apparatus 161 is reproduced. When the discharge flow rate changes across the threshold value described in the operation number switching flow rate table 320 in fig. 9, the state transition is performed. Specifically, when the flow rate is reduced from the threshold value and the pump is stopped at 1 in the state B, the remote facility control device 161 shifts to the state AX or the state AY according to the magnitude of the cumulative operating time of the machine No. 1 and the machine No. 2.

Each graph in fig. 11B shows power consumption when the discharge flow rate is determined in each state. By setting the power consumption function for each state, the power consumption can reproduce different phenomena (natural polarization) even if the flow rate is the same for different states. The function of the power consumption is calculated from the discharge flow rate of the facility in each state, and does not necessarily need to be a function of only the discharge flow rate of the facility. The water level of the suction well on the suction side of the pump facility and the discharge flow rate of other facilities may be a function depending on parameters.

The cost model of fig. 11 can include nonlinearity of pump power consumption and multivalue property of natural polarization based on the number of pumps operating, and can perform accurate cost evaluation. On the other hand, when the cost model proportional to the water distribution amount (discharge flow rate) described in patent document 1 is used, the nonlinearity and the multivalue property shown in fig. 11B cannot be reproduced.

When viewed in the entire discharge flow rate range, the curve is convex downward, and therefore, when the discharge flow rate is small or large, the error becomes large. In the case of a small discharge flow rate or a discharge flow rate in which natural polarization affects the multivalue characteristic, the proportional cost model can be an evaluation value with a deviation of 20% or more, which is relatively too large or too small.

In the example of fig. 11B, the power consumption functions are different between the state AX in which only the engine pump No. 1 is operated and the state AY in which only the engine pump No. 2 is operated. This represents a difference in power consumption due to a difference in the device characteristics between the machine No. 1 and the machine No. 2. Even if the machine No. 1 and the machine No. 2 are, for example, pumps of the same type, a difference in the characteristics of the apparatus may occur due to aging. By using a cost model in which the operating state is taken into consideration as shown in fig. 11A, accurate cost evaluation can be performed even in this case.

The cost calculation unit 112 includes a state machine (state transition machine) for each facility to be controlled, simulates a state transition relationship of a cost model, calculates a cost (power consumption) from a power consumption function corresponding to a state, and calculates a cost (power consumption amount) of the facility by integrating the cost (power consumption) for each time.

The cost model is used to evaluate the instantaneous value of the power consumption from the instantaneous value of the discharge flow rate, but an average value of about 10 minutes to 1 hour, which is generally used for the operation planning data 340, can be used as it is. In general, the change in the discharge flow rate of the water supply facility is relatively moderate, and does not change greatly by about 10 minutes, and the discharge flow rate can be switched only 1 hour or less and 1 time or less in taking water from a water source, sending water to a distribution tank, and the like, so that the accuracy can be ensured in the above-described use method. In addition, since the transient phenomenon in which the pump is started and stopped has a large influence in a time shorter than 10 minutes, it is preferable to use an average flow rate of 10 minutes or more.

As described above, the evaluation target of the cost model of the present embodiment may be the electricity fee required to obtain the power consumption of the pump. Generally, the electricity rate is low at night when the power consumption is low. The unit price at night may be about 1/3 degrees during the day, and it is preferable to use the product. By setting up the water supply operation plan not on a daily basis but at an interval of 1 hour or less, it is possible to evaluate the electricity rate including a change in unit price, and it is possible to set up a water supply operation plan that utilizes nighttime electricity.

With reference to fig. 12, another cost model of the same facility as that of fig. 11 in the cost model information stored in the cost model storage unit 123 will be described. Fig. 12A is a state transition diagram showing a state transition relationship, and fig. 12B is a graph showing a power consumption function in each state in a superimposed manner, similarly to fig. 11.

The cost model of fig. 12 is an example of a cost model in which the cost model of fig. 11 is approximated. In fig. 12A, a state A, B, C indicates information on the number of pump operations of the facility. Specifically, the state a indicates an operation state in which the number of pumps operated is 1.

State a represents a state in which state AX and state AY in fig. 11A are unified, state B represents a state equivalent to state B in fig. 11A, and state C represents a state equivalent to state C in fig. 11A. By unifying the states, the power consumption function in the state a becomes a function of averaging the values of the power consumption functions in the state AX and the state AY. The cost evaluation considering the difference in the device characteristics between the pump No. 1 and the pump No. 2 cannot be performed by averaging, but since the model is formed, there is an advantage that the cost evaluation becomes unnecessary considering the cumulative operation time of the pump No. 1 and the like.

When the operation plan optimization unit 113 generates and evaluates a plurality of operation plan data 340, the cost evaluation is facilitated, and therefore, the calculation amount required for the cost evaluation is reduced, and the level of the optimization problem is changed, whereby a higher-speed optimization technique can be used. If there is no significant difference in the plant characteristics of the pump # 1 and the pump # 2, the cost evaluation does not generate a new error compared to the cost model of fig. 11, and the cost model of fig. 12 can be a more simple model.

With reference to fig. 13, another cost model of the same facility as that of fig. 11 among the cost model information stored in the cost model storage unit 123 will be described. In fig. 13, similarly to fig. 11, fig. 13A is a state transition diagram showing a state transition relationship, and fig. 13B is a graph showing a power consumption function in each state in a superimposed manner.

The cost model of fig. 13 is an example in which the cost model of fig. 12 is further approximated. In fig. 13A, only one state a is shown, and a model without state transition is shown. In fig. 13B, the power consumption function is a function in which the plurality of power consumption functions in fig. 12B are approximated by a single divided linear function (broken line) (divided linear approximation). In fig. 13B, the broken line indicates the power consumption function in fig. 12B before the approximation.

The model without the state transition cannot consider the multivalue of the cost due to the difference in the number of pump operation units. In addition, errors are generated that result from differentiating linear approximations to the nonlinear function. However, as described in the description of fig. 12, the advantage of cost modeling is improved. In the present embodiment, the cost model allows a certain evaluation error when considering evaluation for the operation plan data 340. This is because the required predicted value output from the required prediction unit 114 also has an error, and therefore the operation plan data 340 calculated from the required predicted value also inevitably has an error during control.

In the cost model of all the facilities to be controlled, when the power consumption function is linearly approximated in a differentiated manner as shown in fig. 13, the route optimization unit 113 and the cost calculation unit 112 can be installed by the optimized engine of the linear planning problem or the mixed integer linear planning problem. Therefore, a high-speed solution can be performed, and the calculation time required for the establishment of the optimal operation plan can be shortened.

A flow rate-energy cost model of a facility including 3 fixed speed pumps will be described with reference to fig. 14, among the cost model information stored in the cost model storage unit 123. In this facility, the discharge flow rate and the discharge pressure are controlled only by starting and stopping the pump without basically performing the rotation speed control and the valve opening degree control.

Fig. 14A is a state transition diagram showing a state transition relationship, and fig. 14B is a graph showing a power consumption function in each state in a superimposed manner. As in fig. 12A, the state A, B, C in fig. 14A is information indicating the number of pumps operating. As described above, when the rotation speed control or the valve control is not performed, the discharge flow rate is generally a discrete value corresponding to the pump operation state. The power consumption function in fig. 14B is also a function for acquiring the value of power consumption only for discrete discharge flow rates corresponding to the pump operating state.

On the other hand, in this facility, when the state transition is removed and the model based on the linear approximation is converted into the state transition state as shown in fig. 13, the power consumption function shown by the broken line in fig. 14B can be selected.

A process flow of constructing the cost model for one control target facility of the cost model constructing unit 111 will be described with reference to fig. 15. First, the process of constructing the cost model will be described with respect to the facility 151 described with reference to fig. 11 to 13.

In step 1401 of constructing the state transition relationship, the cost model constructing unit 111 creates the state transition relationship that reproduces the operation stop state of each pump in the facility, using the information stored in the control rule storage unit 122. In the control rule table 310 of fig. 7, the flow rate table 320 and the pump operation sequence 313 are switched by the number of operation stations. As described in the description of fig. 11A, the condition for the state transition between the respective states is determined, and the range of the discharge flow rate for each state is determined.

As shown in fig. 14, when the operation control is performed only for the number of fixed pumps, the discharge flow rate achieved by the passage state is obtained using the line model of fig. 8B and the device characteristics of the pump in operation in each state. The flow-head characteristics synthesized when a plurality of pumps were operated in parallel were obtained as follows. When the head is H1, the discharge flow rate of the machine pump No. 1 is Q11, and the discharge flow rate of the machine pump No. 2 is Q12, the discharge flow rate when the head is H1 is Q11+ Q12 when the machine pump No. 1 and the machine pump No. 2 are operated. The intersection of the flow-head characteristic synthesized as described above and the pipeline model of fig. 8B is the discharge flow rate achieved by the passing state.

In step 1402 of calculating the power consumption function, the cost model construction unit 111 specifies a function (power consumption function) for calculating power consumption from the discharge flow rate of the facility for each state obtained in step 1401 of constructing the state transition relationship. When a certain state is selected, the range of the discharge flow rate (the lower limit value and the upper limit value) and the number list of the operating pumps are determined. It is conceivable to fix the discharge flow rate within the above range. If there is pump speed control, valve control, control parameters to achieve a fixed discharge flow rate are determined according to the discharge pressure and discharge flow rate control scheme 315 shown in the control rules table 310 of fig. 7. As described in the explanation of fig. 6, the power consumption of each pump corresponding to the control parameter is calculated from the equipment characteristic information, and the sum of the power consumption of each pump is determined as the power consumption of the facility.

In the cost model of fig. 11, state C is considered. The discharge flow rate Q is fixed within the range of responsibility. Then, the discharge pressure P of the control target is determined based on the discharge pressure setting (estimated end pressure is constant) of fig. 8A. In general, the discharge pressure P can be approximated to the pump head H by unit conversion, and therefore the pump head H is determined. More strictly speaking, since a correction corresponding to the level of the pump suction well is applied, the effect of this correction can also be taken into account.

The discharge flow Q3 of the fixed speed No. 3 pump at the head H is determined from the equipment characteristic information (flow-head characteristic). As described in the row of the distribution pump farm B in fig. 7, the

variable speed pump

1 and 2 may be respectively configured to have the same flow rate for the remaining flow rate (Q-Q3). The rotational speeds S1 and S2 of the pump 1 and the pump 2, respectively, were determined to have a head H and a flow rate of (Q-Q3)/2 based on the device characteristic information (flow rate-head characteristic). From the head H, the flow rates Q1, Q2, and Q3 thus obtained, the efficiencies η 1, η 2, and η 3 of the respective pump machines can be also obtained, and the power consumptions E1, E2, and E3 of the respective pump machines can be calculated by the formulas described in the explanation of fig. 6. The power consumption of the facility at the discharge flow rate Q was determined as E1+ E2+ E3.

In the modeling step 1403, the cost model constructing unit 111 transforms the cost model from the cost model of fig. 11 to the cost model of fig. 12 as needed, and as described in the cost model of fig. 13. From the viewpoint of state transition, there are a change in the state transition relationship and a change in the power consumption function.

In the cost model of fig. 11, the state AX and the state AY are states in which the ranges of the discharge flow rates in charge are almost the same, and the difference in the power consumption function is small even at the same discharge flow rate, and they can be said to be similar to each other. This state is achieved when the pump No. 1 and the pump No. 2 are the same type of pump. The difference in the range of the discharge flow rate and the difference in the power consumption function are found in similar states to each other such that the difference is equal to or less than a predetermined threshold value, and by unifying these states, the model can be converted into the cost model of fig. 12.

On the other hand, the power consumption function is a nonlinear function, but can be approximated by a linear function in terms of distinction. Specifically, several discharge flow rates are arbitrarily selected, and a broken line connecting points of the selected discharge flow rates on a graph is a linear approximation. The accuracy of the approximation is evaluated as the sum of squares of the differences in the respective discharge flow rates, and an approximation is obtained such that the sum of squares is the smallest.

The cost model thus obtained is stored in the cost model storage unit 123 together with the degree of conversion, that is, the degree of precision or approximation of the cost model.

The optimal operation plan data 340 stored in the operation plan optimization unit 113 will be described with reference to fig. 16. In fig. 16, the operation plan data 340 includes a type 341, a time 342, and a plan flow rate 343.

The operation plan data 340 includes planned value information of the discharge flow rate for each period of 30 minutes in the future for each facility to be controlled. Further, even if the facility is not the controlled object, the planned value at each future time may be included in a deep item related to the pump operation, specifically, the water level of the distribution tank.

The facility restriction information stored in the facility restriction storage unit 124 will be described with reference to fig. 17. In fig. 17, the facility restriction information 350 is composed of a category 351, an item 352, and a content 353.

The facility restriction information 350 stores restriction information that satisfies the operation plan data 340 for each facility such as a facility to be controlled. As shown in fig. 17, examples of the restrictions include a discharge flow rate range (upper and lower limit values) of the pump facility, an upper limit of the number of times of switching of the discharge flow rate of the pump facility, a maximum value of a variation in the discharge flow rate of the pump facility, a water level range (upper and lower limit values) of the distribution tank, and a connection relationship between facilities to be controlled.

The flow of processing by the device characteristic control rule update unit 115 will be described with reference to fig. 18. Note that the description will be made by taking, as an example, a control target facility 151 having a control target device 171 shown in fig. 2. In the flow-head characteristic updating step 1701, the plant characteristic control rule updating unit 115 updates the flow-head characteristic shown in fig. 5. Here, the flow-head characteristic is modeled by equation 11.

H ═ f (Q, a, B, C) … (formula 11)

Wherein,

h: lift [ m ]

Q: discharge flow rate [ m ^3/h ]

When determining the coefficient A, B, C, the flow-head characteristic is determined. In addition, the speed control is modeled by a similar law for the pump. That is, using the rated rotation speed S0, the flow-lift characteristic at the rotation speed S is passed

H ═ f (Q × S/S0, A, B, C) × S ^2/S0^2 … (formula 12)

Equation 12 modeling

As specific examples of the function f,

expressions

2 and 3 listed in the description of fig. 5 can be used.

The discharge pressure P, the discharge flow rate Q, the water level of the intake well, the operation stop state of each pump, and the rotation speed of each variable-speed pump are extracted from the real-time data of operation for a fixed period such as the past 1 month period by the performance operation data storage unit 126. The pump head H is estimated from the discharge pressure P and the water level of the suction well. In each pump, assuming that the coefficient A, B, C is determined, the discharge flow rates Q1, Q2, and Q3 at the head H can be estimated using the real-time operation stop state and the rotation speed. The coefficient A, B, C of each pump is determined so that the square of the difference between the sum Q1+ Q2+ Q3 of the estimated discharge flow rate and the real-time discharge flow rate Q (Q-Q1-Q2-Q3) ^2 is the smallest value obtained by summing the real-time data (residual square sum).

The coefficient determination method for minimizing the sum of the squares of the residuals can be a general optimization method such as the toboggan simple method.

In the flow rate-efficiency characteristic updating step 1702, the device characteristic control rule updating unit 115 updates the flow rate-efficiency characteristic shown in fig. 6 as an example. Here, the flow-rate-efficiency characteristic is modeled by equation 13,

η ═ g (Q, a, B, C) … (formula 13)

Wherein,

eta: efficiency < - >)

Q: discharge flow rate [ m ^3/h ]

When the coefficient A, B, C is determined, the flow-efficiency characteristic is determined. In addition, the speed control is modeled by a similar law for the pump. That is, using the rated rotation speed S0, the flow-head characteristic at the rotation speed S is modeled by equation 14.

η ═ g (Q × S/S0, a, B, C) … (formula 14)

The power consumption can now be modeled as,

e ═ k, Q, H/η … (formula 15)

Wherein

E: electric power consumption [ kW ]

K: proportionality coefficient [ kWh/m ^4]

H: lift [ m ]

As specific examples of the function g,

expressions

2 and 3 listed in the description of fig. 5 can be used.

The discharge pressure P, the discharge flow rate Q, the operation stop state of each pump, the rotation speed of each variable speed pump, and the power consumption of each pump are extracted from the operation real-time data of a fixed period such as the past 1 month period by the performance operation data storage unit 126. The pump head H is inferred from the discharge pressure P and the water level of the suction well. In each pump, assuming that the coefficient A, B, C is determined, the discharge flow rates Q1, Q2, and Q3 and the power consumptions E1, E2, and E3 at the head H can be estimated using the real-time operation stop state and the rotation speed and the flow rate-head characteristics updated before. The coefficient A, B, C of each pump may be determined so that the square of the difference between the estimated power consumption E1, E2, E3 and the corresponding real-time power consumption is minimized with respect to the value of the sum of the operation real-time data (residual square sum).

A determination method of a coefficient for minimizing the sum of squares of the residuals can be a general optimization method such as a toboggan simple method.

The cost evaluation corresponding to the characteristic change accompanying the equipment deterioration can be performed by the updating process of the equipment characteristic information by the equipment characteristic control rule updating unit 115. In addition, when a new or modified pump facility is to be created, the characteristic values described in the pump pattern are first set and evaluated, and the characteristic values are accumulated in real time with the operation, so that the device characteristic information more conforming to the operation state can be updated.

In the present embodiment, only the update of the plant characteristic information stored in the plant characteristic storage unit 121 is processed, but information stored in the control rule storage unit 122 such as a pipeline model shown as an example in fig. 8B may be updated based on the actual result operation data.

The present invention is not limited to the above-described embodiments, and includes various modifications. The present invention is not limited to the embodiments having all the configurations described above, but the present invention is not limited to the embodiments having all the configurations described above. In addition, a part of the configuration of each embodiment can be added, deleted, or replaced with another configuration.

Further, a part or all of the above-described configurations, functions, processing units, processing methods, and the like may be realized by hardware by designing an integrated circuit or the like. The respective configurations, functions, and the like described above may be realized by software by a processor interpreting and executing a program for realizing the respective functions. Information such as programs, tables, and files for realizing the respective functions can be stored in a memory, a hard disk, a recording device such as ssd (solid State drive), or a recording medium such as an IC card, an SD card, or a DVD.

The control lines and information lines are lines necessary for the description, and not all the control lines and information lines need to be shown in the product. In practice, virtually all of the components can be connected to one another.

Description of the symbols

101 … central water course monitoring and controlling device, 110 … Central Processing Unit (CPU), 111 … cost model constructing unit, 112 … cost calculating unit, 113 … operation plan optimizing unit, 114 … demand predicting unit, 120 … memory, 121 … equipment characteristic storing unit, 122 … control rule storing unit, 123 … cost model storing unit, 124 … facility restriction storing unit, 125 … operation plan storing unit, 126 … actual performance operation data storing unit, 130 … medium input/output unit, 140 … input unit, 141 … human-machine interface unit, 142 … communication unit, 145 … display unit, 180 … peripheral equipment IF unit, 190 … bus, 400 … network, 500 … water course monitoring and controlling system

Claims

1. A central monitoring control device for a waterway, which controls a water intake pump facility, a water supply pump facility, and a water distribution pump facility,

comprising:

an equipment characteristic storage unit that stores equipment characteristics of each pump in the controlled facility;

a control rule storage unit that stores control rules for specifying an operation mode and the like of each pump in the controlled facility;

a cost model constructing unit that constructs a cost model for each of the controlled facilities based on the information of the device characteristic storage unit and the control rule storage unit, and stores the cost model in a cost model storage unit;

a cost calculation unit that evaluates the operation cost of the water course operation plan data using the cost model stored in the cost model storage unit;

an operation plan optimizing unit that creates optimal waterway operation plan data that minimizes the operation cost evaluated by the cost calculating unit;

a communication unit that transmits the optimal operation plan data to the controlled facility; and

a human-machine interface section for interfacing with an operator,

the cost model is composed of a state transition relation in which the number of pump operation units of the facility to be controlled is set as a state and a function in which the cost is given by setting the discharge flow rate of the facility to be controlled in each state as an input,

the cost calculation unit is configured by a state transition machine that executes a state transition expression of the cost model.

2. The central waterway monitor control apparatus according to claim 1,

further comprises a performance operation data storage unit and a device characteristic control rule updating unit,

the communication unit collects information on operation performance from a facility to be controlled and stores the information in the performance operation data storage unit, and the equipment characteristic control rule updating unit updates the equipment characteristic information stored in the equipment characteristic storage unit and the control rule information stored in the control rule storage unit, based on the information on the operation performance.

3. The central waterway monitor control device according to claim 1 or claim 2,

the cost model constructing unit has the following functions: a function of converting a cost model having a state transition expression having an independent state for each operation stop state of a pump machine of a controlled facility into a cost model simplifying the state transition expression by unifying similar states; and a function of separately approximating the discharge flow rate of the controlled facility in each state by a linear function, the function being a function of giving a cost by using the discharge flow rate as an input.

4. The central waterway monitor control device according to any one of claims 1 to 3,

the function of applying the cost is obtained by calculating, as input, the discharge flow rate of the facility to be controlled of the cost model using the characteristic indicating the relationship between the discharge flow rate and the head of the pump and the characteristic indicating the relationship between the discharge flow rate and the efficiency of the pump, which are stored in the device characteristic storage unit, and using the rotation speed of the variable speed pump and the decompression width of the valve, which are determined by the control method in which the discharge flow rate or the discharge pressure is set, which are stored in the control rule storage unit.

5. The central waterway monitor control device according to any one of claims 1 to 4,

as a control method for setting the discharge pressure of the water distribution pump facility stored in the control rule storage unit, either estimated end pressure constant control or discharge pressure constant control is used.

6. The central waterway monitor control device according to any one of claims 1 to 5,

the operation cost evaluated by the cost calculation unit and minimized by the operation plan optimization unit is one of power consumption required for operation of the waterway facility, electricity fee for obtaining the power consumption, and greenhouse gas conversion value of the power consumption.

7. A water course monitoring control system for realizing a water course central monitoring control apparatus according to any one of claims 1 to 6 by a computer server,

by connecting with the control-object facility via the communication network,

the water course central monitoring control device transmits the operation plan data to the controlled target facility and collects the actual performance operation data from the controlled target facility.

8. A water course monitoring control program for controlling a water intake pump facility, a water supply pump facility, and a water distribution pump facility,

causing the computer to function as:

a human-machine interface section for interfacing with an operator,