JP7565894B2 - Plant Optimal Operation Planning System - Google Patents

Description

This disclosure relates to a plant optimal operation planning device.

In plant operation, reducing the total energy cost is an important issue. To address this issue, research is being conducted into plant operation planning problems, which involves planning the start/stop states and input/output of equipment with the aim of minimizing the total energy cost. In the past, from the perspective of simplifying calculations, operation patterns during start/stop transitions were rarely taken into account. However, with the introduction of the principle of competition in recent power system reforms, it has become an issue to create models that are closer to reality in order to produce energy efficiently. Therefore, several methods have been proposed for calculating plant operation schedule optimization that take into account operation patterns during start/stop transitions.

The plant operation schedule optimization method described in Patent Document 1 discloses a method in which the type of operation mode is included as an integer operation mode variable as one of the independent variables in the operation schedule optimization calculation, a predetermined operation pattern is assigned as an operation constraint condition according to the operation mode variable, and an operation schedule optimization calculation for the controlled plant is performed so that the operation cost for each operation mode or the operation cost during a mode change is minimized within a cost evaluation function. This method makes it possible to optimize the plant operation schedule by considering the operation pattern during the near future start-up transition or shutdown transition according to the current state of the plant, such as the duration of the previous shutdown.

In the operational planning method for a thermal power plant described in Non-Patent Document 1, a formulation method using mixed integer linear programming (MILP) is disclosed that takes into account the operation pattern during the start-up or stop transition by introducing a time-series binary variable for each type of operation mode or a constraint condition that distinguishes the time-series operation mode, and a constraint condition that expresses the operation pattern according to the operation mode.

JP 2005-284388 A

Applied Mechanics and Materials, Vols.672-674, pp.493-498, An MILP Formulation for the Thermal Unit Commitment Problem Considering Start-up and Shut-down Power Trajectories”, Jun Deng, Hua Wei

The plant operation schedule optimization method disclosed in Patent Document 1 has no constraints for distinguishing the operation mode in a time series during the planning period, such as hot start, warm start, or cold start, which is determined by the duration of a prior shutdown, and therefore it is difficult to consider the operation pattern during startup or shutdown transition according to the operation mode in a time series during the planning period. Here, hot start refers to an operation mode in which the startup transition period is relatively short, warm start refers to an operation mode in which the startup transition period is longer than that of a hot start, and cold start refers to an operation mode in which the startup transition period is longer than that of a warm start.

The thermal power plant operation planning method disclosed in Non-Patent Document 1 plans the power generation amount, which is the output of the thermal power plant, but does not plan the fuel consumption amount, which is the input of the thermal power plant. Therefore, it can only consider the output side operation pattern during startup transition or shutdown transition depending on the operation mode of the thermal power plant. A commonly known method for determining the input side operation pattern is to use a linear function that expresses the relationship between input and output. However, since it is difficult to express the input/output relationship during startup transition or shutdown transition of a thermal power plant with a linear function, it is difficult to consider the input side operation pattern during startup transition or shutdown transition depending on the operation mode of the thermal power plant.

Furthermore, the methods disclosed in Patent Document 1 and Non-Patent Document 1 are both intended for plants that consume fuel and supply one type of energy, but are difficult to apply when supplying multiple forms of energy, such as electricity and low-pressure steam, or when targeting plants with hierarchically configured equipment. Here, a plant with hierarchically configured equipment refers to, for example, a plant in which multiple devices consume fuel to output steam, and multiple other devices consume that steam to supply electricity.

The present disclosure has been made in consideration of the above circumstances, and aims to provide a plant optimal operation planning device that, in a plant having hierarchically configured constituent equipment, plans the start/stop states and input/output for each piece of plant constituent equipment while taking into account the input and output operating patterns during start-up and stop transitions according to the time-series operating mode over a planning period.

The plant optimal operation planning device disclosed herein is a plant optimal operation planning device for treating a target plant as a plant having hierarchically configured plant constituent equipment, and includes an operation mode discrimination constraint condition setting unit that sets operation mode discrimination constraint conditions which are constraint conditions for discriminating a time-series operation mode including any one of a hot start, a warm start, or a cold start startup pattern of the target plant, an output side operation pattern constraint condition setting unit that sets output side operation pattern constraint conditions which are constraint conditions expressing an output side operation pattern during startup transition and shutdown transition of the target plant, an input side operation pattern constraint condition setting unit that sets input side operation pattern constraint conditions which are constraint conditions expressing an input side operation pattern during startup transition and shutdown transition of the target plant, and an optimization calculation unit that develops an optimal operation plan including startup/shutdown states and input/output plans for each plant constituent equipment of the target plant based on the operation mode discrimination constraint conditions, the output side operation pattern constraint conditions, and the input side operation pattern constraint conditions.

The plant operation optimization planning device disclosed herein can plan the startup and shutdown states and input/output for each piece of plant equipment in a target plant having hierarchical plant equipment, while taking into account the input and output operation patterns during startup and shutdown transitions according to the time-series operation mode during the planning period.

1 is a diagram illustrating an example of a target plant targeted by a plant optimal operation planning apparatus according to a first embodiment. FIG. 2 is a diagram showing an example of the operation of a boiler. FIG. 2 is a diagram showing an example of a hot start of a boiler. FIG. 2 is a diagram showing an example of a warm start of a boiler. FIG. 2 is a diagram showing an example of a cold start of a boiler. FIG. 1 is a diagram illustrating an example of boiler shutdown. 1 is a diagram illustrating a functional configuration of a plant optimal operation planning device according to a first embodiment. FIG. 4 is a diagram showing an example of data on output side operation patterns for different boiler operation modes. FIG. 4 is a diagram showing an example of data on input side operation patterns for different boiler operation modes. FIG. 4 is a diagram showing an example of basic data for each operation mode of a boiler. FIG. 2 is a diagram illustrating an example of demand forecast data. FIG. 13 is a diagram showing an example of a power supply plan in which plans for power generation and purchased power are integrated for a first turbine and a second turbine. FIG. 13 is a diagram showing an example of a low-pressure steam supply plan in which plans for low-pressure steam amounts are integrated for a first turbine and a second turbine. 1 is a diagram illustrating a hardware configuration of a plant optimal operation planning device according to a first embodiment. 3 is a flowchart showing an operation of the plant optimal operation planning device according to the first embodiment; FIG. 11 is a diagram illustrating a functional configuration of a plant optimal operation planning device according to a second embodiment. 11 is a flowchart showing an operation of an optimal plant operation planning device according to a second embodiment.

The following describes the embodiments with reference to the attached drawings. In the following embodiments, detailed features are shown for the purpose of explaining the technology, but they are merely examples and not all of them are necessarily essential features for the embodiment to be feasible. The drawings are shown in a schematic manner, and for the convenience of explanation, configurations are omitted or simplified as appropriate in the drawings. Furthermore, the interrelationships between the sizes and positions of the configurations shown in different drawings are not necessarily described accurately and may be changed as appropriate. Furthermore, in the following description, similar components are illustrated with the same reference numerals, and their names and functions are also the same. Therefore, detailed descriptions of them may be omitted to avoid duplication. Furthermore, in the description of the present specification, when a certain component is described as "having," "including," or "having," these expressions are not exclusive expressions that exclude the existence of other components, unless otherwise specified.

<A. First embodiment>
<A-1. Configuration>
First, an example of a target plant 102 targeted by the plant optimal operation planning device 101A will be described. FIG. 1 shows an example of the target plant 102. The target plant 102 is configured to include two boilers 11 and 12 for supplying electric power and low-pressure steam, and two turbine generators 21 and 22 (hereinafter, turbines). Here, the boilers 11 and 12 and the turbines 21 and 22 are plant configuration equipment that constitute the target plant 102. The boilers 11 and 12 consume fuel such as city gas to generate high-pressure steam. The high-pressure steam generated by the boilers 11 and 12 is collected in a high-pressure steam header. The turbines 21 and 22 consume high-pressure steam in the high-pressure steam header to generate low-pressure steam and electric power. The amount of low-pressure steam generated can be adjusted by operating the extraction valves of the turbines 21 and 22. When the supply of electric power is insufficient for a reason such as the amount of electric power generated by the turbines 21 and 22 being less than the electric power demand, the target plant 102 can receive electric power based on a contract concluded with a retail electric power supplier. When the supply of low-pressure steam becomes excessive because the amount of low-pressure steam generated by the turbines 21, 22 is greater than the demand for low-pressure steam, the target plant 102 can release the low-pressure steam into the atmosphere. When the supply of high-pressure steam becomes excessive because the amount of high-pressure steam consumed by the turbines 21, 22 is less than the amount of high-pressure steam generated by the boilers 11, 12, the target plant 102 can release the high-pressure steam into the atmosphere. Note that the release of low-pressure steam and high-pressure steam into the atmosphere is not shown in FIG.

The operator of the target plant 102 is required to operate the target plant 102 in a way that reduces total energy costs in order to efficiently produce energy, and must operate the target plant 102 by planning the start/stop status and input/output of the plant's component equipment.

Figure 2 shows an example of the operation of boilers 11 and 12, which are plant components. In Figure 2, boilers 11 and 12 go from operating to stopped and then back to operating. The horizontal axis of the graph in Figure 2 indicates time, and the vertical axis indicates physical quantities. In Figure 2, the solid line graph indicates the fuel consumption of boilers 11 and 12, and the dashed line graph indicates the amount of high-pressure steam generated by boilers 11 and 12.

The operating modes of the boilers 11 and 12 are broadly divided into four: operating, transitioning to shutdown, stopped, and transitioning to startup. Operating is an operating mode in which the boilers 11 and 12 are operated in the range from minimum input/output to maximum input/output. Transitioning to shutdown is an operating mode in which the input and output of the boilers 11 and 12 are reduced according to certain input and output patterns in order to transition the boilers 11 and 12 from operating to stopped. Stopped is an operating mode in which the boilers 11 and 12 are stopped with no input or output. Transitioning to startup is an operating mode in which the input and output of the boilers 11 and 12 are increased according to certain input and output patterns in order to transition the boilers 11 and 12 from stopped to operating.

The operating mode of turbines 21 and 22 is the same as the operating mode of boilers 11 and 12.

The startup transition period is divided into three operating modes depending on the duration of the prior shutdown: hot start, warm start, and cold start. A hot start is an operating mode in which the startup transition period is relatively short. A warm start is an operating mode in which the startup transition period is longer than a hot start. A cold start is an operating mode in which the startup transition period is longer than a warm start.

Figure 3 shows an example of a hot start of boilers 11 and 12. The horizontal axis of the graph in Figure 3 indicates time, and the vertical axis indicates physical quantities. The scale on the horizontal axis represents frames. A frame is a certain period of time. The solid line graph indicates the fuel consumption of boilers 11 and 12, and the dashed line graph indicates the amount of high-pressure steam generated by boilers 11 and 12. In the case of the hot start shown in Figure 3, the period during the startup transition is three frames.

Hot starting the turbines 21 and 22 is similar to hot starting the boilers 11 and 12.

Figure 4 shows an example of a warm start of boilers 11 and 12. The horizontal axis of the graph in Figure 4 indicates time, and the vertical axis indicates physical quantities. The scale on the horizontal axis indicates frames. The solid line graph indicates the fuel consumption of boilers 11 and 12, and the dashed line graph indicates the amount of high-pressure steam generated by boilers 11 and 12. In the case of the warm start shown in Figure 4, the period during the startup transition is four frames.

Warm starting of turbines 21 and 22 is similar to warm starting of boilers 11 and 12.

Figure 5 shows an example of a cold start of boilers 11 and 12. The horizontal axis of the graph in Figure 5 indicates time, and the vertical axis indicates physical quantities. The scale on the horizontal axis indicates frames. The solid line graph indicates the fuel consumption of boilers 11 and 12, and the dashed line graph indicates the amount of high-pressure steam generated by boilers 11 and 12. In the case of the cold start shown in Figure 5, the period during the startup transition is five frames.

Cold starting of turbines 21 and 22 is similar to cold starting of boilers 11 and 12.

Operating modes during the transition to shutdown may be divided according to the duration of the previous operation and the transition to startup. However, here, operating modes during the transition to shutdown are not divided according to the duration of the previous operation and the transition to startup. Shutdown is an operating mode during the transition to shutdown.

Figure 6 shows an example of the shutdown of boilers 11 and 12. The horizontal axis of the graph in Figure 6 indicates time, and the vertical axis indicates physical quantities. The scale on the horizontal axis indicates frames. The solid line graph indicates the fuel consumption of boilers 11 and 12, and the dashed line graph indicates the amount of high-pressure steam generated by boilers 11 and 12. In the case of the shutdown shown in Figure 6, the period during the transition to shutdown is three frames.

Shutdown of turbines 21 and 22 is similar to shutdown of boilers 11 and 12.

The above is an example of the target plant 102 targeted by the plant optimal operation planning device 101A.

Next, we will explain an example of the functional configuration of the plant optimal operation planning device 101A.

Figure 7 is a functional configuration diagram of the plant optimal operation planning device 101A. The plant optimal operation planning device 101A is configured to include an output side operation pattern database (hereinafter, database is referred to as DB) 201, an input side operation pattern DB 202, an equipment characteristic DB 203, a demand forecast DB 204, a contract information DB 205, a plan result DB 206, an actual value DB 207, a basic constraint condition setting unit 208, an operation mode discrimination constraint condition setting unit 209, an output side operation pattern constraint condition setting unit 210, an input side operation pattern constraint condition setting unit 211, an evaluation function setting unit 212, an optimization calculation unit 213, and a data input/output unit 214.

The output side operation pattern DB201 stores data on the output side operation patterns for each operation mode of each plant component equipment.

The input side operation pattern DB202 stores data on the input side operation patterns for each operation mode of each plant component equipment.

The equipment characteristic DB203 holds basic data for each plant component equipment operation mode, data on input/output characteristics during operation for each plant component equipment, data on the change rate limit for each plant component equipment, data on maximum input/output during operation for each plant component equipment, data on minimum input/output for each plant component equipment, data on upper and lower limits of the turbine low pressure steam extraction amount, data on the period during startup transition for each operation mode, and data on the period during shutdown transition for each operation mode.

Demand forecast DB204 holds data on electricity demand forecast values and data on low-pressure steam demand forecast values.

The contract information DB205 stores data on the contracted power, data on the unit price of electricity based on the contract concluded with the retail electricity supplier, and data on the unit price of city gas.

The planning result DB 206 holds data on the optimal operation plan results for the plant. Specifically, the planning result DB 206 holds data on the planned power generation amount for each turbine 21, 22, data on the planned low-pressure steam generation amount for each turbine 21, 22, data on the planned high-pressure steam consumption amount for each turbine 21, 22, data on the planned high-pressure steam generation amount for each boiler 11, 12, data on the planned fuel consumption amount for each boiler 11, 12, data on the planned start/stop status flag for each piece of plant equipment, data on the planned purchased power, and data on the planned fuel consumption.

The actual value DB 207 holds data on the past actual values of the high-pressure steam consumption for each turbine 21, 22, data on the past actual values of the fuel consumption for each boiler 11, 12, data on the past actual values of the start-up/shutdown state flag for each piece of plant equipment, data on the past actual values of the start-up flag for each piece of plant equipment, data on the past actual values of the start-up flag (hot start) for each piece of plant equipment, data on the past actual values of the start-up flag (warm start) for each piece of plant equipment, data on the past actual values of the start-up flag (cold start) for each piece of plant equipment, and data on the past actual values of the immediately after shutdown flag for each piece of plant equipment.

The basic constraint condition setting unit 208 sets input change rate constraints for each plant component equipment, upper and lower output limit constraints during operation, upper and lower input limit constraints during operation, power supply and demand balance constraints, high-pressure steam supply and demand balance constraints, low-pressure steam supply and demand balance constraints, and upper and lower limit constraints for variables.

The operation mode discrimination constraint condition setting unit 209 sets a constraint expressing the relationship between the start-up flag and the immediately after stopping flag, a constraint expressing the relationship between the start-up flag, the immediately after stopping flag, and the operating flag, and a constraint expressing the selection of the start-up pattern, i.e., which start-up pattern is to be selected from hot start, warm start, or cold start.

The output side operation pattern constraint condition setting unit 210 sets the output side operation pattern constraints during the start-up transition and the stop transition.

The input side operation pattern constraint condition setting unit 211 sets input side operation pattern constraints during start-up transition and stop transition.

The evaluation function setting unit 212 sets the evaluation function.

The optimization calculation unit 213 solves the optimal operation plan problem for the target plant 102 and obtains the optimal operation plan result for the target plant 102.

The data input/output unit 214 displays the data held in the output side operation pattern DB 201, the input side operation pattern DB 202, the equipment characteristics DB 203, the demand forecast DB 204, the contract information DB 205, the plan result DB 206, and the actual value DB 207, and sets the data held in the output side operation pattern DB 201, the input side operation pattern DB 202, the equipment characteristics DB 203, the demand forecast DB 204, and the contract information DB 205 that is necessary to create an optimal operation plan for the target plant 102.

One plant optimal operation planning device 101A is installed for each demand location. A demand location includes the electricity usage location and refers to the entire premises where electricity is used.

The above is an explanation of an example of the functional configuration of the plant optimal operation planning device 101A.

Next, we will explain an example of data stored in the various DBs of the plant optimal operation planning device 101A.

Figure 8 shows an example of data on output side operation patterns for each operation mode of a boiler, which is a plant component. The data shown in Figure 8 is held in the output side operation pattern DB 201. In Figure 8, outputs 1, 2, 3, 4, and 5 represent the first, second, third, fourth, and fifth frames during startup transition or shutdown transition, respectively. In the case of a hot start, the high-pressure steam volume, which is the output of the boiler in the first frame during startup transition, is 0.0%. 0.0% means that the high-pressure steam volume is 0.0% when the high-pressure steam volume when operated at rated speed is 100%. Similarly, in the case of a hot start, the high-pressure steam volumes in the second and third frames during startup transition are 25.0% and 50.0%, respectively. In the case of a warm start, the high-pressure steam volumes in the first, second, third, and fourth frames during startup transition are 0.0%, 16.7%, 33.3%, and 50.0%, respectively. In the case of a cold start, the amount of high-pressure steam in the first, second, third, fourth, and fifth frames during the start-up transition is 0.0%, 12.5%, 25.0%, 37.5%, and 50.0%, respectively. In the case of a shutdown, the amount of high-pressure steam in the first, second, and third frames during the stop transition is 50.0%, 25.0%, and 0.0%, respectively.

The data for the output side operation pattern for each turbine operation mode is the same as the data for the output side operation pattern for each boiler operation mode.

Figure 9 is an example of data on input side operation patterns for each operation mode of a boiler, which is a plant component. The data shown in Figure 9 is held in the input side operation pattern DB 202. In Figure 9, inputs 1, 2, 3, 4, and 5 represent the first, second, third, fourth, and fifth frames during startup transition or shutdown transition, respectively. In the case of a hot start, the fuel consumption, which is the input of the boiler in the first frame during startup transition, is 16.7%. 16.7% means that the fuel consumption is 16.7% when the fuel consumption when operated at rated speed is 100%. Similarly, in the case of a hot start, the fuel consumption in the second and third frames during startup transition is 33.3% and 50.0%, respectively. In the case of a warm start, the fuel consumption in the first, second, third, and fourth frames during startup transition is 12.5%, 25.0%, 37.5%, and 50.0%, respectively. In the case of a cold start, the fuel consumption during the start-up transition in the first, second, third, fourth, and fifth frames is 10.0%, 20.0%, 30.0%, 40.0%, and 50.0%, respectively. In the case of a shutdown, the fuel consumption during the stop-down transition in the first, second, and third frames is 50.0%, 33.3%, and 16.7%, respectively.

For a certain plant component equipment, the period (number of frames) of the data of the input side operation pattern by operation mode, the period (number of frames) of the data of the output side operation pattern by operation mode, the period during startup transition by operation mode in equipment characteristics DB203, and the period during shutdown transition by operation mode in equipment characteristics DB203 are the same. For example, in the examples of Figures 8 and 9, the period of hot start is three frames, so the period during startup transition of hot start in equipment characteristics DB203 is also three frames.

The data for the input side operation pattern for each turbine operation mode is the same as the data for the input side operation pattern for each boiler operation mode.

Figure 10 is an example of basic data for each operation mode of a boiler, which is a plant component equipment. The basic data shown in Figure 10 is held in the equipment characteristics DB 203. A hot start means an operation mode selected at startup when the duration of a prior stop is 1 frame or more and less than 3 frames. A warm start means an operation mode selected at startup when the duration of a prior stop is 3 frames or more and less than 5 frames. A cold start means an operation mode selected at startup when the duration of a prior stop is 5 frames or more. A shutdown means an operation mode selected at shutdown when the duration of a prior operation and a transition to startup is 1 frame or more. The startup (shutdown) cost is the cost at startup or shutdown. The startup cost of a hot start is 10,000 yen. The startup cost of a warm start is 20,000 yen. The startup cost of a cold start is 30,000 yen. The shutdown cost of a shutdown is 20,000 yen.

The basic data for each turbine operating mode is the same as the basic data for each boiler operating mode.

Figure 11 is an example of demand forecast data. The demand forecast data is stored in the demand forecast DB 204. The demand forecast data in Figure 11 is data on the predicted values of the electricity demand and low-pressure steam demand of the target plant 102. The electricity demand forecast values are 100 kWh/h, 110 kWh/h, 120 kWh/h, 130 kWh/h, 125 kWh/h, and 120 kWh/h in the first, second, third, fourth, fifth, and sixth frames of the near future, respectively. The low-pressure steam demand forecast values are 60 MJ/h, 65 MJ/h, 70 MJ/h, 60 MJ/h, 50 MJ/h, and 40 MJ/h in the first, second, third, fourth, fifth, and sixth frames of the near future, respectively.

Figure 12 shows an example of a power supply plan that integrates plans for power generation and purchased power for turbines 21 and 22. The data in Figure 12 is stored in the plan result DB 206. The horizontal axis of the graph in Figure 12 indicates time, and the vertical axis indicates the amount of power. The matte hatching indicates the amount of purchased power, the cross hatching indicates the amount of power generated by turbine 21 (referred to as the first turbine), and the diagonal hatching indicates the amount of power generated by turbine 22 (referred to as the second turbine). For example, in the first frame in the near future, the amount of purchased power is 20 kWh/h, the amount of power generated by the first turbine is 40 kWh/h, and the amount of power generated by the second turbine is 40 kWh/h.

Figure 13 shows an example of a low-pressure steam supply plan in which plans for low-pressure steam volume are integrated for turbines 21 and 22. The data in Figure 13 is stored in the plan result DB 206. The horizontal axis of the graph in Figure 13 indicates time, and the vertical axis indicates low-pressure steam volume. The cross hatching indicates the low-pressure steam volume of turbine 21 (referred to as the first turbine), and the diagonal hatching indicates the low-pressure steam volume of turbine 22 (referred to as the second turbine). For example, for the first frame in the near future, the low-pressure steam volume of the first turbine is 30 MJ/h, and the low-pressure steam volume of the second turbine is 30 MJ/h.

The above is an example of data held in the output side operation pattern DB201, input side operation pattern DB202, equipment characteristics DB203, demand forecast DB204, and planning result DB206 of the plant optimal operation planning device 101A.

Next, we will explain an example of the hardware configuration of the plant optimal operation planning device 101A.

Figure 14 is a hardware configuration diagram of the plant optimal operation planning device 101A. The plant optimal operation planning device 101A includes an input device 301, an output device 302, a CPU (Central Processing Unit) 303, a main memory device 304, a secondary memory device 305, and a communication device 306. The communication device 306 is for connecting the plant optimal operation planning device 101A to a communication network 307. The data input/output unit 214 in Figure 7 is realized by the input device 301 and the output device 302. The output side operation pattern DB 201, the input side operation pattern DB 202, the equipment characteristic DB 203, the demand forecast DB 204, the contract information DB 205, the plan result DB 206, and the actual value DB 207 in Figure 7 are realized by the main memory device 304 or the secondary memory device 305. The basic constraint condition setting unit 208, the operation mode discrimination constraint condition setting unit 209, the output side operation pattern constraint condition setting unit 210, the input side operation pattern constraint condition setting unit 211, the evaluation function setting unit 212, and the optimization calculation unit 213 in FIG. 7 are realized by the CPU 303 executing software programs stored in the main storage device 304 or the secondary storage device 305. Acquisition of information from the target plant 102 in FIG. 7 is realized by the communication device 306.

<A-2. Operation>
Each value used in the optimal operation planning problem of the target plant 102 is defined as follows: Values with lowercase initial letters are variables, and values with uppercase initial letters are constants or functions.
(set)
[Common system]

[Boiler system]

[Turbine system]

(variable)
[Boiler system]

[Turbine system]

[others]

(Constants and Functions)
[Boiler system]

[Turbine system]

[others]

Note that if the time of each value, the past time, the set of times during the start-up transition period, or the set of times during the stop-down transition period is outside the range of the defined set, it means that the value does not exist. This concludes the definition of each value used in the optimal plant operation planning problem.

Figure 15 is a flowchart showing the operation of the plant optimal operation planning device 101A. First, the basic constraint condition setting unit 208 sets basic constraint conditions (step S101). The basic constraint condition setting unit 208 acquires data necessary for setting constraint conditions from the equipment characteristics DB 203 and the performance value DB 207, and sets the change rate constraints of the input for each piece of plant equipment shown in the following formulas (1) to (4).

The basic constraint condition setting unit 208 also acquires data necessary for setting constraint conditions from the equipment characteristics DB 203, and sets the upper and lower output limit constraints during operation shown in the following equations (5) and (6).

The basic constraint condition setting unit 208 also acquires data necessary for setting constraint conditions from the equipment characteristics DB 203, and sets the input upper and lower limit constraints during operation shown in the following equations (7) to (8).

The basic constraint condition setting unit 208 also sets the power supply and demand balance constraint shown in the following equation (9).

The basic constraint condition setting unit 208 also sets the high-pressure steam supply and demand balance constraint shown in the following equation (10).

The basic constraint condition setting unit 208 also sets the low-pressure steam supply and demand balance constraint shown in the following equation (11).

The basic constraint condition setting unit 208 also acquires data necessary for setting constraint conditions from the equipment characteristics DB 203 and the contract information DB 205, and sets upper and lower limit constraints for the variables shown in the following equations (12) and (13).

Next, the operation mode discrimination constraint condition setting unit 209 sets the operation mode discrimination constraint condition (step S102). Specifically, the operation mode discrimination constraint condition setting unit 209 acquires data necessary for setting the constraint condition from the performance value DB 207, and sets a constraint expressing the relationship between the start-up start flag and the immediately-after-stop flag shown in equations (14) to (19).

The operation mode discrimination constraint condition setting unit 209 also acquires data necessary for setting the constraint conditions from the equipment characteristics DB 203 and the performance value DB 207, and sets constraints expressing the relationship between the start-up start flag, the immediately after shutdown flag, and the operating flag shown in the following formula (20) to formula (23).

In addition, in equation (21),

A set of times defined by

If it is outside the range, it means that the value does not exist. Also, in equation (21),

A set of past times defined by

Outside this range means the value does not exist. Similarly for each of the other values.

The operation mode discrimination constraint condition setting unit 209 also acquires data necessary for setting the constraint conditions from the equipment characteristics DB 203 and the actual value DB 207, and sets constraints expressing the selection of the startup pattern shown in equations (24) to (41). In this way, the operation mode discrimination constraint conditions express the constraint expressing the relationship between the startup start flag and the immediately after shutdown flag of the target plant 102, the constraint expressing the relationship between the startup start flag, the immediately after shutdown flag, and the operating flag of the target plant 102, and the constraint expressing the selection of the startup pattern of the target plant 102, as inequality constraints or equality constraints including time-series binary variables for each operation mode of the target plant 102.

Next, the output side operation pattern constraint condition setting unit 210 acquires data necessary for setting the constraint conditions from the output side operation pattern DB 201, the equipment characteristic DB 203, and the performance value DB 207, and sets the output side operation pattern constraint conditions shown in the following equations (42) to (45) (step S103). In this way, the output side operation pattern constraint conditions are expressed as equality constraints including time-series binary variables for each operation mode of the target plant and data on the output side operation pattern for each operation mode of the target plant.

Next, the input side operation pattern constraint condition setting unit 211 acquires data necessary for setting the constraint conditions from the input side operation pattern DB 202, the equipment characteristic DB 203, and the performance value DB 207, and sets the output side operation pattern constraints shown in equations (46) to (49). In this way, the input side operation pattern constraint conditions are expressed as equality constraints including time-series binary variables for each operation mode of the target plant and input side operation pattern data for each operation mode of the target plant.

Next, the evaluation function setting unit 212 acquires data necessary for setting the evaluation function from the equipment characteristics DB 203 and the contract information DB 205, and sets the evaluation function shown in the following formula (50).

Next, the optimization calculation unit 213 solves the optimal operation plan problem for the target plant 102 that minimizes the evaluation function set by the evaluation function setting unit 212 under the constraint conditions set by the basic constraint condition setting unit 208, the operation mode discrimination constraint condition setting unit 209, the output side operation pattern constraint condition setting unit 210, and the input side operation pattern constraint condition setting unit 211, using a solver that can solve mixed integer linear programming problems (MILP), and obtains an optimal operation plan result for the target plant 102 (step S106).

Finally, the optimization calculation unit 213 writes the data of the optimal operation plan result of the target plant 102, which are the planned data of the power generation amount for each turbine 21, 22, the planned data of the low pressure steam generation amount for each turbine 21, 22, the planned data of the high pressure steam consumption amount for each turbine 21, 22, the planned data of the high pressure steam generation amount for each boiler 11, 12, the planned data of the fuel consumption amount for each boiler 11, 12, the planned data of the start/stop status flag for each plant component equipment, the planned data of the purchased power, and the planned data of the fuel consumption, into the plan result DB 206.

<A-3. Effects>
In the plant optimal operation planning device 101A of the first embodiment, a plant having hierarchically configured plant constituent equipment is set as a target plant 102. The plant optimal operation planning device 101A includes an operation mode discrimination constraint condition setting unit 209 that sets operation mode discrimination constraint conditions that are constraint conditions for discriminating a time-series operation mode of the target plant, an output side operation pattern constraint condition setting unit 210 that sets output side operation pattern constraint conditions that are constraint conditions expressing an output side operation pattern during startup transition and shutdown transition of the target plant 102, an input side operation pattern constraint condition setting unit 211 that sets input side operation pattern constraint conditions that are constraint conditions expressing an input side operation pattern during startup transition and shutdown transition of the target plant 102, and an optimization calculation unit 213 that develops an optimal operation plan including a startup/shutdown state and an input/output plan for each plant constituent equipment of the target plant 102 based on the operation mode discrimination constraint conditions, the output side operation pattern constraint conditions, and the input side operation pattern constraint conditions. Therefore, according to the plant optimal operation planning device 101A, in a plant in which the plant constituent equipment is hierarchically structured, it is possible to create an optimal operation plan for the plant that creates a plan for the startup/shutdown state and input/output for each plant constituent equipment, while taking into account the operating patterns of the input and output sides during startup/shutdown transitions in accordance with the time-series operation mode over the planning period.

<B. Second embodiment>
In the second embodiment, a plant optimal operation planning system 101B will be described, in which the plant shown in Fig. 1 is used as a target plant 102. In the following description, components similar to those described in the above-described embodiments are illustrated with the same reference numerals, and detailed description thereof will be omitted as appropriate.

<B-1. Configuration>
16 is a functional configuration diagram of a plant optimal operation planning apparatus 101B. The plant optimal operation planning apparatus 101B has a similar configuration to the plant optimal operation planning apparatus 101A of the first embodiment.

The optimization calculation unit 213 solves the optimal operation plan problem for the target plant 102, obtains the optimal operation plan result for the target plant 102, and transmits the optimal operation plan result for the target plant 102 in the near future to the plant control device 103.

The plant control device 103 is a device that controls the target plant 102.

<B-2. Operation>
Fig. 17 is a flowchart showing the operation of the plant optimal operation planning apparatus 101B. Steps S101 to S107 in the flow of Fig. 17 are similar to steps S101 to S107 in the flow of Fig. 15, and therefore description thereof will be omitted.

After step S107, the optimization calculation unit 213 transmits the near future planning results (control target values) for the planned data of the power generation amount for each turbine, the planned data of the low-pressure steam generation amount for each turbine, the planned data of the high-pressure steam consumption amount for each turbine, the planned data of the high-pressure steam generation amount for each boiler, and the planned data of the fuel consumption amount for each boiler to the plant control device 103 (step S108).

<B-3. Effects>
The plant optimal operation planning device 101B of the second embodiment transmits the optimal operation plan for the target plant 102 formulated by the optimization calculation unit 213 to the plant control device 103 that controls the target plant 102. Therefore, according to the plant optimal operation planning device 101B, in addition to the effects of the first embodiment, it is possible to control the target plant 102 based on the optimal operation plan result for the target plant 102.

The embodiments can be freely combined, modified, or omitted as appropriate.

11, 12 Boiler, 21, 22 Turbine generator, 101A, 101B Plant optimal operation planning device, 102 Target plant, 103 Plant control device, 208 Basic constraint condition setting unit, 209 Operation mode discrimination constraint condition setting unit, 210 Output side operation pattern constraint condition setting unit, 211 Input side operation pattern constraint condition setting unit, 212 Evaluation function setting unit, 213 Optimization calculation unit, 214 Data input/output unit, 301 Input device, 302 Output device, 303 CPU, 304 Main storage device, 305 Secondary storage device, 306 Communication device, 307 Communication network, 201 Output side operation pattern DB, 202 Input side operation pattern DB, 203 Equipment characteristic DB, 204 Demand forecast DB, 205 Contract information DB, 206 Plan result DB, 207 Actual value DB.

Claims (5)

A plant operation optimum planning device for a plant having hierarchically configured plant configuration equipment,
an operation mode discrimination constraint condition setting unit that sets an operation mode discrimination constraint condition, which is a constraint condition for discriminating a time-series operation mode including any one of a hot start, a warm start, and a cold start start pattern of the target plant;
an output side operation pattern constraint condition setting unit that sets an output side operation pattern constraint condition which is a constraint condition expressing an output side operation pattern during a start-up transition and a stop transition of the target plant;
an input side operation pattern constraint condition setting unit that sets an input side operation pattern constraint condition which is a constraint condition expressing an input side operation pattern during a start-up transition and a stop transition of the target plant;
an optimization calculation unit that develops an optimal operation plan including a start/shutdown state and an input/output plan for each of the plant constituent facilities of the target plant based on the operation mode discrimination constraint condition, the output side operation pattern constraint condition, and the input side operation pattern constraint condition;
Optimal plant operation planning device. The driving mode discrimination constraint condition is:
A constraint expressing a relationship between a start-up start flag and an immediately-after-shutdown flag of the target plant;
A constraint expressing a relationship between a start-up start flag, a just-shutdown flag, and an operating flag of the target plant;
A constraint expressing a selection of a start-up pattern of the target plant.
The operation mode of the target plant is expressed by an inequality constraint or an equality constraint including a time-series binary variable for each operation mode of the target plant.
2. The plant optimum operation planning system according to claim 1. The output side operation pattern constraint condition is expressed by an equality constraint including a time series binary variable for each operation mode of the target plant and data of an output side operation pattern for each operation mode of the target plant.
3. The plant optimum operation planning device according to claim 1 or 2. the input side operation pattern constraint condition is expressed by an equality constraint including a time series binary variable for each operation mode of the target plant and data of an input side operation pattern for each operation mode of the target plant;
The plant optimum operation planning device according to any one of claims 1 to 3. Transmitting the optimal operation plan for the target plant formulated by the optimization calculation unit to a plant control device that controls the target plant.
The plant optimum operation planning device according to any one of claims 1 to 4.

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