Energy plant control support device, energy plant control support method, and energy plant control system

Abstract

To reduce discrepancy between an operation plan and an operation result of an energy plant.SOLUTION: According to the present embodiment, a first processor sets planned energy supply quantities in time series of devices that supply an energy storage device with energy to a first setting on the basis of planned energy supply quantities in time series while complying with prescribed constraints. A second processor for executing a processing within a second period shorter than a first period sets planned energy supply quantities in time series of the devices to a second setting on the basis of a first difference between planned energy supply quantities in time series and measured energy supply quantities in time series actually supplied from the energy storage device, so as to reduce the first difference while complying with prescribed rules. An energy plant control assist device supplies a signal having information related to at least one of the first setting and the second setting to controllers of the devices.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] An embodiment of the present invention relates to an energy plant control support device, an energy plant control support method, and an energy plant control system. [Background technology]

[0002] An energy plant control support system is a system that provides an operating point that allows a target energy plant to operate more efficiently. It is known that such an energy plant control support system uses an optimization method to calculate the operating point. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 4050036 [Patent Document 2] Japanese Patent Application Laid-Open No. 2002-362512 Summary of the Invention [Problem to be solved by the invention]

[0004] However, when using optimization techniques for the operation planning of an energy plant, a time-series energy supply amount as a planned value to the supply destination is required as a condition. Therefore, in order to create an operation plan, it is necessary to set the time-series energy supply amount as a planned value in advance. However, there is a discrepancy between the planned value set in advance and the actual measured value of the energy actually supplied, which causes a discrepancy between the operation plan and the operation results of the energy plant.

[0005] The present embodiment provides an energy plant control support device, an energy plant control support method, and an energy plant control system that can suppress deviation between an operation plan and an operation result of an energy plant. [Means for solving the problem]

[0006] According to this embodiment, an energy plant control support device that supports control of equipment in an energy plant based on a time-series energy supply amount as a planned value from an energy storage device during a first period includes a first processing unit and a second processing unit. The first processing unit first sets a time-series energy supply amount as a planned value for an equipment that supplies energy to the energy storage device in accordance with a predetermined constraint based on the time-series energy supply amount as the planned value. The second processing unit executes processing during a second period shorter than the first period, and based on a first difference between the time-series energy supply amount as the planned value and the time-series energy supply amount as an actual measured value actually supplied from the energy storage device, second sets a time-series energy supply amount as a planned value for the equipment in accordance with a predetermined rule so as to reduce the first difference. The energy plant control support device supplies a signal containing information about at least one of the first setting and the second setting to a control device of the equipment. [Effects of the Invention]

[0007] According to this embodiment, it is possible to suppress the deviation between the operation plan and the operation results of the energy plant. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram showing a schematic configuration example of an energy plant control system. [Figure 2] FIG. 10 is a block diagram showing a detailed configuration example of an optimization engine. [Figure 3] FIG. 4 is a diagram showing an example of an operation plan generated by an optimization calculation unit. [Figure 4] FIG. 2 is a block diagram showing a detailed configuration example of a rule-based engine. [Figure 5] FIG. 10 is a diagram showing a processing result when a loose-base engine is not used. [Figure 6] FIG. 2 is a diagram showing an example of processing timing of the energy plant control assistance device. [Figure 7] FIG. 2 is a diagram showing a conceptual example of processing by a rule-based engine. [Figure 8] 10 is a diagram showing the set value of the total output of multiple devices and the total output of operating devices. [Figure 9] FIG. 10 is a diagram showing the relationship between the number of units in operation and the value obtained by subtracting the actual value from the planned value of the amount of heat storage and heat release. [Figure 10] 10 is a flowchart according to the rules of the rule calculation unit. [Figure 11] 11A and 11B are diagrams showing processing results according to the processing example of FIG. 10; [Figure 12] FIG. 10 is a diagram showing an example of the configuration of an energy plant control system according to a second embodiment. [Figure 13] FIG. 10 is a diagram showing an example of processing timing according to the second embodiment. [Figure 14] 13 shows an example of the configuration of a rule-based engine according to the third embodiment. [Figure 15] 11 is a flowchart showing an example of processing by a rule-based engine according to the third embodiment. [Figure 16] FIG. 2 is a diagram schematically illustrating the operating state of the device. [Figure 17] FIG. 10 is a diagram showing an example of a condition for changing the number of devices in operation according to the device operation status. [Figure 18] 13 is a flowchart showing an example of processing by a rule-based engine according to the fourth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] An energy plant control support device, an energy plant control support method, and an energy plant control system according to embodiments of the present invention will be described in detail below with reference to the drawings. Note that the embodiments described below are examples of embodiments of the present invention, and the present invention should not be interpreted as being limited to these embodiments. Furthermore, in the drawings referred to in this embodiment, identical parts or parts having similar functions are given the same or similar symbols, and repeated explanations thereof may be omitted. Furthermore, for convenience of explanation, the dimensional ratios of the drawings may differ from the actual ratios, and some components may be omitted from the drawings.

[0010] (First embodiment) FIG. 1 is a diagram showing a schematic configuration example of an energy plant control system according to this embodiment. The energy plant control system 1 includes an energy plant 10 and an energy plant control support device 20. The energy plant 10 is, for example, a plant that generates energy and stores energy. As a more specific example, the energy plant 10 is an energy plant that is capable of generating and storing heat. Note that, although this embodiment will be described taking heat generation and heat storage as an example, the present invention is not limited to this. For example, the energy plant 10 may be any plant that is capable of generating energy and storing energy, such as a hydrogen generation plant or a power generation plant.

[0011] The energy plant control assistance device 20 is a system that can generate energy to be supplied by the energy plant 10 under predetermined constraints. For example, the constraints may be such that the energy supplied to the energy storage device 104 during a predetermined first period matches the energy supplied from the energy storage device 104 to the load 106. Note that the constraints are merely examples and are not limited to these. For example, the first period is 24 hours.

[0012] 1, the energy plant 10 includes, for example, a plurality of devices 100, a plurality of control devices 102, an energy storage device 104, and a load 106. The devices 100 are heat source generating devices that generate cold or hot heat, and generate cold using, for example, electricity.

[0013] The control device 102 is a device that controls the devices 100 in accordance with a setting signal that contains information about the settings of the energy plant control assistance device 20. The states of the multiple devices 100 and the load 106 are observed as measured values. These measured values ​​are supplied to the energy plant control assistance device 20.

[0014] The energy storage device 104 includes, for example, a cold heat storage tank, stores cold heat, and supplies it to the load 106. The load 106 is, for example, a cold heat plant such as an air conditioner. The energy storage device 104 according to this embodiment corresponds to an energy storage device.

[0015] The "device output" is the output of the device 100, and corresponds to the time-series amount of energy supplied from the device 100 to the energy storage device 104. The "amount of stored / discharged energy" is expressed as the difference between the input and output of the energy storage device (cold heat storage tank) 104. In other words, this "amount of stored / discharged energy" corresponds to the difference between the time-series amount of energy supplied from the device 100 to the energy storage device 104 and the time-series amount of energy supplied from the energy storage device 104 to the load 106.

[0016] The "integrated heat storage amount" is the amount of energy obtained by integrating the amount of energy stored and released during a target time period, for example, a first period. In the case of a cold heat storage tank, it can also be estimated from the temperature of the refrigerant (generally water) in the cold heat storage tank. In other words, this "integrated heat storage amount" corresponds to the integrated value of the difference between the time-series energy supply amount from the device 100 that supplies energy to the energy storage device 104 and the time-series energy supply amount supplied from the energy storage device 104 to the load 106. As described above, the time-series energy supply amount supplied to the load 106 and the time-series energy consumed by the load match.

[0017] The energy plant control support device 20 includes, for example, a CPU (Central Processing Unit). The energy plant control support device 20 can configure each processing unit of the optimization engine 202 and the rule-based engine 204 by, for example, executing a predetermined program stored in a storage unit 208 (see FIG. 2 ) described later.

[0018] The optimization engine 202 is a processing unit that provides an operating point for more efficiently operating the target energy plant 10, and outputs a set value to the energy plant 10. Here, more efficient operation means, for example, obtaining energy input to the energy storage device 106 at a lower cost under a constraint condition that matches the total amount of energy supplied from the energy storage device 104 and the total amount of energy consumed by the load 106 in a first period.

[0019] More specifically, the optimization engine 202 generates planned values ​​including setting values ​​for setting the operation states of the plurality of devices 100 under constraint conditions that match the total amount of time-series energy supply from the energy storage device 104 as a planned value for the first time period with the total amount of time-series energy supply to the energy storage device 104 as planned values ​​for the plurality of devices 100. Note that the constraint conditions according to the present embodiment are merely examples and are not intended to be limiting. In this way, the optimization engine 202 formulates a plan for storing and discharging energy in the energy storage device 104 according to the load 106, and provides the rule-based engine 204 with planned values ​​including information on operating points that determine the amount of energy to be input to the energy storage device 104 so as to meet the formulated conditions. Note that details of the optimization engine 202 will be described later.

[0020] The rule-based engine 204 outputs setting values ​​for the control device based on the planned values ​​output from the optimization engine 202 and the measured values ​​transmitted from the energy plant. In order to execute a plan of the optimization engine 202 to support the optimization operation in the first period, the rule-based engine 204 generates setting values ​​for a second period, which is shorter than the first period, in accordance with predetermined rules and outputs the setting values ​​to the energy plant 10. In other words, the rule-based engine 204 can adjust the setting values ​​for executing the overall optimization process of the optimization engine 202 in the first period for each second period. Details of the rule-based engine 204 will be described later.

[0021] 2 and 3, a detailed configuration example of the optimization engine 202 will be described. Fig. 2 is a block diagram showing a detailed configuration example of the optimization engine 202. As shown in Fig. 2, the optimization engine 202 includes a load management unit 250, a storage unit 208, an equipment parameter management unit 210, an equipment operation management unit 212, a calculation condition management unit 214, an optimization calculation unit 216, and a calculation result management unit 218. Furthermore, the storage unit 208 includes an equipment parameter database 208a, an equipment operation database 208b, and a calculation condition database 208c.

[0022] The load management unit 250 manages the time-series energy consumption of the load 106. For example, the load management unit 250 manages the energy consumption of the load 106 for each preset minimum interval within a first period. As described above, the time-series energy consumption of the load 106 corresponds to the time-series amount of energy supplied from the energy storage device 104.

[0023] The storage unit 208 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory), a flash memory, a hard disk, an optical disk, etc. The equipment parameter database 208a stores equipment parameters of the multiple equipment 100 that constitute the energy plant 10. Furthermore, parameters that indicate the performance indexes and ratings of the equipment 100 are referred to as equipment parameters.

[0024] The device operation database 208b stores data for managing the operation of multiple devices 100. Device operation refers to device downtime, operating conditions under partial load, etc. Parameters for setting the device 100 downtime, operating conditions under partial load, etc. are referred to as device operation parameters.

[0025] The calculation condition database 208c stores the calculation conditions in the optimization calculation unit 216. Parameters indicating the upper limit of the calculation time for the optimization calculation in the optimization calculation unit 216, the method of parallel calculation, etc. are referred to as calculation conditions.

[0026] The device parameter management unit 210 manages the data in the device parameter database 208a and supplies the device parameters required for the calculations in the optimization calculation unit 216 to the optimization calculation unit 216.

[0027] The device operations management unit 212 manages the data in the device operations database 208b. The device operations management unit 212 supplies the optimization calculation unit 216 with device operation parameters required for calculations in the optimization calculation unit 216.

[0028] The calculation condition management unit 214 manages the data in the calculation condition database 208c. The calculation condition management unit 214 supplies the optimization calculation unit 216 with the calculation conditions required for the calculations in the optimization calculation unit 216.

[0029] The optimization calculation unit 216 acquires data on equipment parameters, equipment operation parameters, and calculation conditions from the equipment parameter management unit 210, the equipment operation management unit 212, and the calculation condition management unit 214, respectively, and formulates an operation plan for the energy plant. The results of the formulation are transmitted to the calculation result management unit 218. For internal calculations of the optimization engine, a general calculation method or the like can be used (see, for example, Patent Document 2).

[0030] That is, the optimization calculation unit 216 uses the minimization of costs as an objective function, and finds the optimal operating point by calculating a predetermined calculation formula that incorporates the supply and demand balance for the load 106, the operating amounts of the multiple devices 100, and the integrated value of the heat storage amount of the energy storage device 104 as constraint conditions, and outputs the result as an operation plan.

[0031] 3A and 3B are diagrams showing examples of operation plans generated by the optimization calculation unit 216. FIG. 3A shows the supply amount L300 of the device output of the plurality of devices 100 and the supply amount L302 from the energy storage device 104 to the load 106. The horizontal axis represents time, and the vertical axis represents the amount of energy (MJ / h). That is, the supply amount L300 corresponds to the time-series energy supply amount as a planned value of the device 100 that supplies energy to the energy storage device 104. Furthermore, the supply amount L302 to the load 106 corresponds to the time-series energy supply amount as a planned value from the energy storage device 104.

[0032] FIG. B is a diagram showing the amount of stored and released energy of the energy storage device (cold heat storage tank) 104. The horizontal axis indicates time, and the vertical axis indicates the amount of energy (MJ / h). As described above, the amount of stored and released energy L304 is the difference between the input and output of the energy storage device 104. In other words, the amount of stored and released energy L304 is the difference between the amount of supply L300 of the equipment output and the amount of supply L302 to the load 106. The amount above 0 indicates the amount of accumulated energy of the amount of stored and released energy L304, and the amount below 0 indicates the amount of released energy of the amount of stored and released energy L304.

[0033] FIG. C is a diagram showing the accumulated heat storage amount L306. The horizontal axis represents time, and the vertical axis represents the amount of energy (MJ / h). The accumulated heat storage amount L306 is the amount of energy obtained by integrating the amount of stored and released energy L304 over time. In other words, the accumulated heat storage amount L306 is the accumulated value of the difference between the amount of energy supplied over time L300 as a planned value of the device 100 that supplies energy to the energy storage device 104, and the amount of energy supplied over time L302 as a planned value from the energy storage device 104.

[0034] 3C, the optimization calculation unit 216 minimizes the objective function under the constraint that the integrated heat storage amount L306 becomes 0 at the end of the first period. That is, the optimization calculation unit 216 minimizes the objective function under the constraint that the total amount of time-series energy supply L302 as a planned value from the energy storage device 104 in the first period and the total amount of time-series energy supply L300 as a planned value of the device 100 that supplies energy to the energy storage device 104 in the first period approach or match 0. Here, approaching means that the integrated heat storage amount L306 becomes closer to the objective value of 0 than the integrated heat storage amount L306 at the end of the first period when no constraint is set.

[0035] As a result, as shown in FIG. A, the optimization calculation unit 216 plans the supply amount L300 of the device output of the plurality of devices 100 in a time series. The supply amount L302 to the load 106 corresponds to the time series planned value of the load 106. As shown in FIG. B, by planning the supply amount L300 of the device output in a time series, the amount of stored energy and the amount of released energy of the stored / released energy amount L304 in the energy storage device 104 are planned in a time series.

[0036] The calculation result management unit 218 supplies the planned values ​​to the rule-based engine 204. As shown in FIG. 3 , the planned values ​​include a supply amount L300 of the multiple devices 100 as a planned value within the first period, a supply amount L302 as a planned value, an amount of stored energy and released energy L304 as a planned value, and an integrated value of stored heat L306 as a planned value. In this embodiment, the output value of the calculation result management unit 218 of the optimization engine 202 is referred to as a planned value, and a measured value or a value calculated from the measured value is referred to as an actual value. As described above, the amount of stored energy and released energy L304 as a planned value and the integrated value of stored heat L306 as a planned value can be calculated using the supply amount L300 as a planned value and the supply amount L302 as a planned value.

[0037] 4 to 8, the detailed configuration of the rule-based engine 204 will be described. Fig. 4 is a block diagram showing a detailed example configuration of the rule-based engine 204. As shown in Fig. 4, the rule-based engine 204 includes a measurement value acquisition unit 220, a storage unit 221, an equipment parameter management unit 222, an equipment operations management unit 224, a measurement value management unit 226, a plan management unit 228, a rule calculation unit 230, and a setting value management unit 232. Furthermore, the storage unit 221 includes an equipment parameter database 221a, an equipment operations database 221b, and a measurement value database 221c.

[0038] The measurement value acquisition unit 220 is a communication interface with the load 106 and the plurality of devices 100, and acquires each measurement value. The measurement value acquisition unit 220 also supplies each measurement value to a measurement value database 221c.

[0039] The storage unit 221 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory), a flash memory, a hard disk, an optical disk, etc. The equipment parameter database 221a stores equipment parameters for the rule-based engine 204 of the multiple equipment 100 that make up the energy plant 10. In addition, the equipment operation database 208b stores data for the rule-based engine 204 that manages the operation of the multiple equipment 100. The measurement value database 221c stores each measurement value supplied from the measurement value acquisition unit 220 in chronological order.

[0040] Device parameter management section 222 manages the data in device parameter database 221a. Device parameter management section 222 supplies rule calculation section 230 with device parameters required for calculations in rule calculation section 230.

[0041] The device operations management unit 224 manages the data in the device operations database 221b. The device operations management unit 224 supplies the rule calculation unit 230 with device operation parameters required for calculations in the rule calculation unit 230.

[0042] The measurement value management unit 226 manages the data in the measurement value database 221c and supplies the optimization calculation unit 216 with measurement value data required for calculations in the optimization calculation unit 216.

[0043] The plan management unit 228 manages the plan values ​​supplied from the calculation result management unit 218 (see FIG. 3). The rule calculation unit 230 uses the plan values ​​to set the total amount of device output, supply amount, etc. of the multiple devices 100 for each minimum interval, which is the second period. Details of the rule calculation unit 230 will be described later.

[0044] 5A and 5B are diagrams showing processing results according to an operation plan when the loose-base engine 204 is not used. Fig. 5A shows the supply amount L300 of the multiple devices 100 as a planned value, the supply amount L302 to the load 106 as a planned value, and the supply amount L302a to the load 106 as an actual value. The horizontal axis represents time, and the vertical axis represents the amount of energy (MJ / h).

[0045] FIG. B is a diagram showing the amount of stored energy L304a as an actual value. The horizontal axis indicates time, and the vertical axis indicates the amount of energy (MJ / h). As described above, the amount of stored energy L304a as an actual value is the difference between the input and output of the energy storage device 104. In other words, the amount of stored energy L304a as an actual value is the difference between the amount of supply L300 of the multiple devices 100 as a planned value and the amount of supply L302a to the load 106 as an actual value. FIG. C is a diagram showing the accumulated amount of stored heat L306a as an actual value. The horizontal axis indicates time, and the vertical axis indicates the amount of energy (MJ / h).

[0046] 5A, when the loose base engine 204 is not used, there is a discrepancy between the planned supply amount L302 and the actual supply amount L302a. This is because the planned supply amount L302 is a forecast set at, for example, 22:00 the previous day, as will be described later.

[0047] As shown in Figure B, when the actual supply amount L302a is less than the planned supply amount L302, if the equipment output is operated according to the planned supply amount L302, the actual stored / discharged energy amount L304a will fluctuate upward. On the other hand, when the actual supply amount L302a is greater than the planned supply amount L302, the actual stored / discharged energy amount L304a will fluctuate downward.

[0048] As shown in FIG. 1C, the actual value of the accumulated heat storage amount L306a differs due to the difference between the planned supply amount L302 and the actual supply amount L302a. In this example, the accumulated heat storage amount L306a is positive. If this continues, the accumulated heat storage amount L306a will not become zero and the accumulated heat amount will remain. Therefore, the loose base engine 204 resets each set value for each second period, which is shorter than the first period, so that the energy plant 10 operates in accordance with the operation plan of the optimization engine 202. In this case, the loose base engine 204 sets each set value according to a predetermined rule, for example, to reduce the costs of the multiple devices 100. As a result, the overall optimized operation of the energy plant 10 during the first period is performed, and even if a deviation occurs in the optimized operation, the energy plant 10 is operated so as to reduce the costs of the multiple devices 100.

[0049] Here, the processing timing of the rule-based engine 204 will be described, including the processing timing of the optimization engine 202. Fig. 6 is a diagram showing an example of the processing timing of the energy plant control support device 20. Diagram A of Fig. 6 is a diagram showing an example of the processing time of the optimization engine 202. The horizontal axis indicates time, and the vertical axis indicates the state in calculation or stopped. The processing state L400 indicates a state in which calculation is in progress when it is at a high level, and a state in which it is stopped when it is at a low level.

[0050] 6B is a diagram showing an example of processing time of the rule-based engine 204. The horizontal axis indicates time, and the vertical axis indicates the state of calculation or stoppage. The processing state L402 indicates a state of calculation in progress when it is at a high level, and indicates a state of stoppage when it is at a low level.

[0051] As shown in FIG. A, the optimization engine 202 creates a plan for the next day, for example, before 22:00, and outputs the operation plan values ​​for the next day to the rule-based engine 204. This output is performed every time the optimization calculation unit of the optimization engine 202 operates. The operation plan values ​​calculated in this manner are temporarily stored in the plan management unit 228 of the rule-based engine 204. The plan management unit 228 always transmits the latest created plan to the rule calculation unit 230.

[0052] The rule calculation unit 230 repeatedly performs recalculation using the operation plan value at each minimum interval T60, which is the second time. While FIG. B shows an example in which calculation is performed after the minimum interval T60, this is not limiting. For example, the interval does not have to be a fixed interval as long as it is equal to or longer than the minimum interval T60. In this way, the rule calculation unit 230 repeatedly performs calculation processing at intervals of the second time, which is shorter than the first time, which is the planning time of the optimization engine 202.

[0053] Here, a conceptual processing example of the rule-based engine 204 will be described. FIG. 7 is a diagram showing a conceptual processing example of the rule-based engine 204. Diagram A in FIG. 7 is a diagram showing the supply amount L302 to the load 106, which is a planned value of the optimization engine 202, and the supply amount L302a to the load 106, which is a performance value. The horizontal axis represents time, and the vertical axis represents the amount of energy (MJ / h). The optimization engine 202 plans the supply amount L302 to the load 106 for every 15 minutes, for example, by 22:00 the previous day. In other words, the planned value of the optimization engine 202 is in 15-minute increments, and the planned value for 24 hours of one day is made up of 96 time slots. In this case, the first period is 24 hours.

[0054] Figure B is a diagram conceptually illustrating that the rule-based engine 204 performs periodic processing for each second period. Figure C is a diagram illustrating the supply amount L300b of the multiple devices 100 corresponding to the device output setting values ​​output by the rule-based engine 204. The horizontal axis represents time, and the vertical axis represents the amount of energy (MJ / h).

[0055] As shown in FIG. A, for example, in the case of a planned value at 14:00, a supply amount L302 until 14:15 is planned. As shown in FIG. B, the rule-based engine 204 performs periodic processing. In this case, as shown in FIG. C, for example, the rule-based engine 204 outputs an equipment output set value as of 14:10. At this time, the rule-based engine 204 outputs an equipment output set value based on the difference between the planned value supply amount L302 and the actual value supply amount L302a as of 14:09. As a result, as shown in FIG. C, the actual value supply amount L300a of the equipment output approaches the equipment output set value output by the rule-based engine 204, and the difference between the planned value amount of stored / discharged energy L304 and the actual value amount of stored / discharged energy L304a decreases.

[0056] 8 to 10, a specific example of the rule of the rule calculation unit 230 will be described. The rule of this embodiment is an example of suppressing the output cost when a plurality of devices 100 are operated.

[0057] 8 is a diagram showing the set value of the total output of the plurality of devices 100 and the total output of the operating devices of the plurality of devices 100. The vertical axis indicates the amount of energy (MJ / h).

[0058] 9 is a diagram showing the relationship between the value obtained by subtracting the actual value L304a from the planned value L304 of the amount of thermal storage and release heat and the number of operating units. The horizontal axis represents the value D304 obtained by subtracting the actual value L304a from the planned value L304, and the vertical axis represents the additional number of operating units. This example shows an example in which the rule calculation unit 230 adds one operating unit if the value D304 is smaller than delta minus (Δminus). On the other hand, this example shows an example in which the rule calculation unit 230 reduces the number of operating units by one if the value D304 is larger than delta plus (Δplus). In this way, the rule calculation unit 230 according to this embodiment sets delta minus (Δminus) and delta plus (Δplus) as dead bands.

[0059] Fig. 10 is a flowchart according to the rules of the rule calculation unit 230. As shown in Fig. 10, the rule calculation unit 230 determines the unit price per hour for each device 100 in the energy plant 10 using information in the device operation database 208b (step S100). Since the unit price per hour may fluctuate, the device operation database 208b is constantly updated with the latest data.

[0060] Next, the rule calculation unit 230 sorts the unit cost per hour for each device 100 of the energy plant 10 in ascending order of unit cost (step S102).

[0061] Next, the rule calculation unit 230 adds the device 100 with the lowest unit price (step S104). The first addition is made to 0.

[0062] Next, the rule calculation unit 230 determines whether the total output value of the devices 100 to be operated exceeds the supply amount L300 (see FIGS. 3 and 5) as a planned value (step S106). If the rule calculation unit 230 determines that the total output value does not exceed the planned value (No in step S106), the process repeats from step S104. Fig. 8 shows an example in which the total supply amount L300 is exceeded when the output values ​​of three devices 100 are added in order.

[0063] On the other hand, if the rule calculation unit 230 determines that the total output of each device 100 is exceeded (Yes in step S106), the rule calculation unit 230 sets the total output of each device 100 to be reduced until it matches the total supply amount L300 as the planned value. For example, the rule calculation unit 230 reduces the output of the device 100 with the highest unit price.

[0064] Subsequently, the rule calculation unit 230 determines whether the stored / discharged energy amount L304a (see FIG. 5) as the actual value exceeds the stored / discharged energy amount L304 (see FIG. 3) as the planned value (step S108).

[0065] When the rule calculation unit 230 determines that the stored / discharged energy amount L304a as the actual value exceeds the stored / discharged energy amount L304 as the planned value (Yes in step S108), as shown in FIG. 9, if the value obtained by subtracting the stored / discharged energy amount L304 from the stored / discharged energy amount L304a is greater than delta minus (Δminus), the rule calculation unit 230 stops operation of one of the devices 100 with the highest unit price (step S110), and ends the overall processing. On the other hand, when the rule calculation unit 230 determines that the amount of stored energy / discharge energy L304a as the actual value does not exceed the amount of stored energy / discharge energy L304 as the planned value (No in step S108), if the value obtained by subtracting the amount of stored energy / discharge energy L304a from the amount of stored energy / discharge energy L304 is greater than delta plus (Δplus), as shown in FIG. 9, the rule calculation unit 230 adds one device 100 with the lowest unit price among the devices that are not in operation to the operation (step S110), and ends the overall processing.

[0066] In this way, even if a difference occurs between the amount of stored / discharged energy L304a as the actual value and the amount of stored / discharged energy L304 as the planned value, the operation state of the device 100 is not changed unless it exceeds delta minus (Δminus) or delta plus (Δplus). As a result, if the difference between the actual value and the planned value is smaller than delta minus (Δminus) or delta plus (Δplus), energy consumption that occurs when the operation state of the device is changed is suppressed, and if the difference is larger than delta minus (Δminus) or delta plus (Δplus), the operation state of the device 100 is changed, making it possible to reduce the difference between the actual value and the planned value. In other words, delta minus (Δminus) and delta plus (Δplus) can be set taking into account energy consumption that occurs due to fluctuations in the operation of the device 100.

[0067] Fig. 11 is a diagram showing processing results according to the processing example of Fig. 10. Fig. A is a diagram showing the supply amount L300a of the multiple devices 100 as an actual value, the supply amount L302 to the load 106 as a planned value, and the supply amount L302a to the load 106 as an actual value. The horizontal axis represents time, and the vertical axis represents the amount of energy (MJ / h).

[0068] Figure B is a diagram showing the amount of stored energy and released energy L304a as an actual value. The horizontal axis indicates time, and the vertical axis indicates the amount of energy (MJ / h). As described above, the amount of stored energy and released energy L304a as an actual value is the difference between the actual values ​​of input and output in the energy storage device 104. Figure C is a diagram showing the integrated amount of stored heat L306a as an actual value. The horizontal axis indicates time, and the vertical axis indicates the amount of energy (MJ / h).

[0069] 11A, when the loose base engine 204 is used, the difference between the planned supply amount L302 and the actual supply amount L302a is reflected in the actual supply amount L300a of the device output of the plurality of devices 100. As a result, as shown in FIG. 11B, the loose base engine 204 can make the actual stored / discharge amount L304a and the planned stored / discharge amount L304 (see FIG. 3) approximately the same value. Therefore, the actual value of the accumulated heat amount L306a is approximately the same as the planned value of the accumulated heat amount L306 (see FIG. 3), and the accumulated energy of the energy storage device (cold heat storage tank) 104 can be consumed as planned, without excess or deficiency, as shown in FIG. 11C.

[0070] As described above, according to this embodiment, the optimization engine 202 of the energy plant control support device 20 generates an operation plan including the setting values ​​of each device 100 so as to minimize a target predetermined cost when supplying a supply amount L300 in the energy plant 10 for a first period, and the loose-base engine 204 resets the setting values ​​of each device 100 for each second period that is shorter than the first period so as to operate the energy plant 10 in accordance with the operation plan of the optimization engine 202. At this time, the loose-base engine 204 sets each setting value in accordance with a predetermined rule, for example, so as to reduce the costs of the multiple devices 100. As a result, the energy plant control support device 20 can perform an overall optimized operation of the energy plant 10 for the first period, and can operate the energy plant 10 in accordance with the predetermined rule so as to reduce the costs of the multiple devices 100 even if a deviation occurs in the optimized operation.

[0071] (Second embodiment) The energy plant control support device 20 according to the second embodiment differs from the energy plant control support device 20 according to the first embodiment in that the optimization engine 202 is capable of recalculating in accordance with the output of the load error calculation unit 206. The following describes the differences from the energy plant control support device 20 according to the first embodiment in terms of what is possible.

[0072] Fig. 12 is a diagram showing an example of the configuration of an energy plant control system 1 according to the second embodiment. As shown in Fig. 12, the energy plant control support device 20 differs from the energy plant control support device 20 according to the first embodiment in that it further includes a load error calculation unit 206.

[0073] The load error calculation unit 206 acquires the actual value of the supply amount L302a (see FIG. 11) as a value related to the load as a measurement value of the energy plant 10, and acquires the planned value of the supply amount L302 (see FIG. 11) from the optimization engine 202. Then, when the difference between the supply amount L302a and the supply amount L302 exceeds a predetermined value, the load error calculation unit 206 transmits an optimum calculation trigger signal to the optimization engine 202 to cause it to recalculate the operation plan.

[0074] Fig. 13 is a diagram showing an example of processing timing of the energy plant control support device 20 according to the second embodiment. Diagram A of Fig. 13 is a diagram showing an example of processing time of the optimization engine 202. The horizontal axis indicates time, and the vertical axis indicates the state of calculation in progress or stopped. The processing state L400a indicates a state of calculation in progress when it is at a high level, and indicates a state of stoppage when it is at a low level.

[0075] 13B is a diagram showing an example of processing time of the rule-based engine 204. The horizontal axis indicates time, and the vertical axis indicates the state of calculation or stoppage. Processing state L402a indicates a state of calculation in progress when it is at a high level, and indicates a state of stoppage when it is at a low level.

[0076] As shown in FIG. A, the optimization engine 202 creates a next day plan, which is the first period, before 22:00, and outputs the operation plan values ​​for the next day to the rule-based engine 204. When the operation of the energy plant 10 starts, the load error calculation unit 206 continues to calculate the difference value between the supply amount L302a and the supply amount L302. When the difference value exceeds a predetermined value, the load error calculation unit 206 transmits an optimum calculation trigger signal to the optimization engine 202 to cause it to recalculate the operation plan.

[0077] In FIG. A, the load error calculation unit 206 transmits an optimum operation calculation trigger signal to the optimization engine 202 at timings t10 and t14. As a result, the optimization engine 202 recalculates the operation plan and supplies the operation plan to the rule-based engine 204 at timings t12 and t16. As shown in FIG. B, the rule-based engine 204 recalculates each setting value based on predetermined rules in accordance with the operation plan supplied at timings t12 and t16.

[0078] As described above, according to this embodiment, the load error calculation unit 206 causes the optimization engine 202 to recalculate the operation plan when the difference between the planned supply amount L302a and the actual supply amount L302 exceeds a predetermined value. This enables re-optimization calculation when the deviation between the planned supply amount L302a and the actual supply amount L302 exceeds a predetermined value. Therefore, as the deviation between the supply amount L302a and the actual supply amount L302 increases, the deviation between the planned supply amount L302a and the actual supply amount L302, which is determined by the rule-based engine 204 controlling the operating state of the equipment 100, increases. However, by re-optimizing calculation, the deviation between the supply amount L302a and the actual supply amount L302 can be further reduced. In this way, the processing accuracy of the rule-based engine 204 is further improved, thereby reducing the overall cost increase for the first period.

[0079] (Third embodiment) The energy plant control support device 20 according to the third embodiment differs from the energy plant control support device 20 according to the first embodiment in that it further includes a stored energy amount estimation unit 234 that is capable of estimating stored energy in the energy storage device 104. The following describes the possible differences from the energy plant control support device 20 according to the first embodiment.

[0080] Fig. 14 is a block diagram showing an example of the configuration of the rule-based engine 204 according to the third embodiment. As shown in Fig. 14, the rule-based engine 204 further includes a stored energy amount estimation unit 234 and a stored energy estimated value management unit 236. Moreover, the storage unit 221 according to the third embodiment further includes a stored energy database 221d.

[0081] The stored energy amount estimation unit 234 estimates the stored energy of the energy storage device 104 based on the measurement values ​​of the energy storage device 104. For example, if the energy storage device 104 is a heat storage tank, the measurable quantity is temperature, and the stored energy amount estimation unit 234 estimates the stored heat amount based on the temperature. Furthermore, if the energy storage device 104 is a storage battery, the measurable quantity is voltage, and the stored energy amount estimation unit 234 estimates the stored energy amount based on the voltage. Furthermore, if the energy storage device 104 is a hydrogen tank, the measurable quantity is the internal pressure of the hydrogen tank, and the stored energy amount estimation unit 234 estimates the stored energy amount based on the pressure. Note that the stored energy amount estimation unit 234 according to this embodiment corresponds to an estimation unit.

[0082] The stored energy amount estimation unit 234 according to this embodiment estimates the amount of stored energy using the latest measurement data acquired by the measurement value acquisition unit 220 and past data stored in the measurement value database 221c. For example, the stored energy amount estimation unit 234 has a model of the energy storage device 104, and estimates the amount of stored energy using this model. A general model can be used as the model used for estimation.

[0083] The stored energy database 221d stores the estimated value of the stored energy amount estimating unit 234 in association with the measurement data used for the estimation. The stored energy estimated value managing unit 236 manages the stored energy database 221d and supplies the estimated value of the stored energy amount estimating unit 234 to the rule-based engine 202.

[0084] 15 is a flowchart showing an example of processing by the rule-based engine 204 according to the third embodiment, which differs from the flowchart in FIG. 10 in that steps S200 and S202 are added.

[0085] Measurement value acquisition unit 220 acquires the latest measurement data from energy storage device 104 (step S200). Stored energy amount estimation unit 234 estimates the amount of stored energy of energy storage device 104 using the latest measurement data acquired by measurement value acquisition unit 220 and past data stored in measurement value database 221c (step S202). Then, stored energy amount estimation unit 234 supplies the estimated value of the stored energy amount to rule calculation unit 230 via stored energy estimated value management unit 236 as an implementation value of the amount of stored and released energy in energy storage device 104. Rule calculation unit 230 executes the processes of steps S108 to S112 using the estimated value of the stored energy amount.

[0086] As described above, according to this embodiment, the stored energy amount estimation unit 234 estimates the amount of energy stored in the energy storage device 104 based on measurement data acquired from the energy storage device 104. This makes it possible for the rule calculation unit 230 to calculate a setting value for each device 100 in accordance with a predetermined rule, even when it is difficult to directly measure the amount of energy stored in the energy storage device 104.

[0087] (Fourth embodiment) The energy plant control support device 20 according to the fourth embodiment differs from the energy plant control support device 20 according to the first embodiment in that the rule calculation unit 230 has an additional rule for changing the operating state of the equipment 100 according to the measurement data of the energy storage device 104.

[0088] The rule calculation unit 230 according to the fourth embodiment changes the number of operating devices 100 in accordance with the measured temperature of the energy storage device 104. In this case, the rule calculation unit 230 compares the amount of stored and released energy L304a (see FIG. 5) as an actual value with the amount of stored and released energy L304 (see FIG. 3) as a planned value, and changes the change condition for the number of operating devices 100.

[0089] FIG. 16 is a diagram schematically illustrating the operating state of the devices 100. The diagram shows the relationship between the set value of the total output of the multiple devices 100 and the total output of the multiple devices 100 in operation. The vertical axis represents the amount of energy (MJ / h). The rule calculation unit 230 compares the amount of stored and released energy L304a (see FIG. 5) as an actual value with the amount of stored and released energy L304 (see FIG. 3) as a planned value, and distinguishes between three states. For example, the rule calculation unit 230 determines that the number of operating units is excessive when the total output value of the multiple devices 100 in operation is greater than the set value of the total output of the multiple devices 100 by a predetermined amount. Furthermore, the rule calculation unit 230 determines that the number of operating units is appropriate when the absolute value of the difference between the total output value of the multiple devices 100 in operation and the set value of the total output of the multiple devices 100 is within a predetermined range. Furthermore, the rule calculation unit 230 determines that a state in which the total output value of the plurality of devices 100 in operation is less than the set value of the total output of the plurality of devices 100 by a predetermined amount is a state in which the number of operating devices is too small.

[0090] If the energy storage device 104 is a cold heat storage tank, it is necessary to operate additional equipment when the measured temperature value exceeds a reference value. This is because the temperature supplied to the load needs to be kept below a certain level. The rule calculation unit 230 according to this embodiment changes the conditions for adding or stopping the number of operating units, as shown in FIG. 17 .

[0091] 17 is a diagram showing an example of conditions for changing the operating number according to the operating state of the device 100. When the number of operating units is too small, the temperature at which the operating number is increased is T1u, and the temperature at which the operating number is decreased is T1d. When the number of operating units is appropriate, the temperature at which the operating number is increased is T2u, and the temperature at which the operating number is decreased is T2d. Furthermore, when the number of operating units is too large, the temperature at which the operating number is increased is T3u, and the temperature at which the operating number is decreased is T3d.

[0092] In this case, T3u > T2u > T1u. As a result, the measured temperature for increasing the number of operating units increases in the following order: excessive number of operating units, appropriate number of operating units, and under-operating number of units. In other words, the temperature range for increasing the number of operating units widens in the following order: under-operating number of units, appropriate number of operating units, and over-operating number of units. For example, when the number of operating units is excessive, the temperature tends to decrease over time. On the other hand, when the number of operating units is under-operating, the temperature tends to increase over time. In this way, by changing the temperature conditions, it is possible to bias the number of operating units to be increased when the number of operating units is under-operating compared to when the number of operating units is over-operating.

[0093] In this case, T3d > T2d > T1d. As a result, the measured temperature at which the number of operating units is reduced increases in the following order: excessive number of operating units, appropriate number of operating units, and under-operating number of units. In other words, the temperature range for reducing the number of operating units narrows in the following order: under-operating number of units, appropriate number of operating units, and excessive number of operating units. For example, when the number of operating units is excessive, the temperature tends to decrease over time. On the other hand, when the number of operating units is under-operating, the temperature tends to increase over time. In this way, by changing the temperature conditions, it is possible to bias the number of operating units to be reduced more in the excessive number of operating units than when the number of operating units is under-operating. As can be seen from these, by changing the heat storage tank temperature and the conditions for adding or stopping the number of operating units depending on each case, it is possible to more stably maintain the temperature of the energy storage device 104 within the standard range.

[0094] 18 is a flowchart showing an example of processing by the rule-based engine 204 according to the fourth embodiment, which differs from the flowchart in FIG. 10 in that steps S300 and S302 are added.

[0095] The measurement value acquisition unit 220 acquires a temperature as a measurement value from the energy storage device 104 (step S300). The rule calculation unit 230 determines the state of the plurality of devices 100 as being one of an excessive number of operating devices, an appropriate number of operating devices, or an insufficient number of operating devices, based on the processing information in steps S108 to S112, and changes the number of operating devices of the plurality of devices 100 in accordance with the example conditions shown in Fig. 17 (step S302), thereby completing the overall processing.

[0096] As described above, according to this embodiment, the rule calculation unit 230 classifies the state (case) of the energy storage device 104 based on the relationship between the set value of the total output of the plurality of devices 100 and the total output of the operating devices of the plurality of devices 100, and changes the temperature range for changing the operating state of the devices 100 according to the classification. This makes it possible to bias the increase or decrease in the number of operating devices 100 according to the state of the energy storage device 104, and makes it possible to more stably maintain the temperature of the energy storage device 104 within the reference range.

[0097] Although several embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be embodied in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, and are also included in the scope of the invention and its equivalents as defined in the claims. [Explanation of symbols]

[0098] 1: Energy plant control system, 10: Energy plant, 20: Energy plant control support device, 100: Equipment, 102: Control device, 104: Energy storage device, 106: Load, 202: Optimization engine, 204: Rule-based engine, 234: Stored energy amount estimation unit, 250: Load management unit.

Claims

1. 1. An energy plant control support device that supports control of equipment in an energy plant based on a time-series energy supply amount as a first planned value from an energy storage device in a first period, a first processing unit that first sets a time-series energy supply amount as a second planned value of the device that supplies energy to the energy storage device in accordance with a predetermined constraint condition, based on the time-series energy supply amount as the first planned value; a second processing unit that executes processing for a second period shorter than the first period, and that secondly sets a time-series energy supply amount as a second planned value of the device in accordance with a predetermined rule based on a first difference between a time-series energy supply amount as the first planned value and a time-series energy supply amount as an actual measured value actually supplied from the energy storage device so as to reduce the first difference; Equipped with providing a signal containing information about at least one of the first setting and the second setting to a controller of the device; the energy plant has a plurality of devices that supply energy to the energy storage device, including the device; The second processing unit, as the predetermined rule, operates an equipment among the plurality of devices that is not operating and has the lowest cost per unit time when the time-series energy supply amount as the actual measured value is greater than the time-series energy supply amount as the first planned value at a predetermined point in time before the second setting.

2. 2. The energy plant control assistance device according to claim 1, wherein the predetermined constraint condition is that the total amount of time-series energy supply as a first planned value from the energy storage device during the first period and the total amount of time-series energy supply as a second planned value of the equipment that supplies energy to the energy storage device during the first period are close to or identical to each other.

3. 3. The energy plant control assistance device according to claim 2, wherein the second processing unit, as the predetermined rule, stops operation of an operating device among the plurality of devices that has the highest cost per unit time when the time-series energy supply amount as the actual measured value is less than the time-series energy supply amount as the first planned value at a predetermined point in time before the second setting.

4. The energy plant control assistance device according to claim 1 , wherein the second processing unit does not change the number of operating devices when the value of the first difference is within a predetermined range.

5. 5. The energy plant control assistance device according to claim 4, further comprising a load error calculation unit that causes the first processing unit to reset a time-series energy supply amount as a second planned value of the equipment in accordance with the value of the first difference.

6. the planned value of the stored energy of the energy storage device is an integrated value of a second difference between a time-series energy supply amount as a second planned value of the device that supplies energy to the energy storage device and a time-series energy supply amount as a first planned value from the energy storage device, an estimation unit that estimates an actual measured value of stored energy actually stored in the energy storage device based on a measurement value supplied from the energy storage device; 6. The energy plant control assistance device according to claim 5, wherein the second processing unit executes processing based on a third difference between the actual measured value of accumulated energy estimated by the estimation unit and the planned value of accumulated energy.

7. The energy plant control assistance device according to claim 6 , wherein the estimation unit estimates the actual measured value of the stored energy based on past measured values ​​of the energy plant.

8. The energy plant control assistance device according to claim 7 , wherein the second processing unit changes a condition for changing the operating states of the plurality of devices in accordance with the measured value supplied from the energy storage device.

9. the energy storage device is a cold heat storage tank; The energy plant control assistance device according to claim 8 , wherein the second processing unit changes a condition for changing the operating states of the plurality of devices in accordance with the measured temperature supplied from the energy storage device.

10. 10. The energy plant control assistance device according to claim 9, wherein the second processing unit changes a condition for changing the operating states of the plurality of devices further based on a planned value and an actual value of the stored energy of the energy storage device.

11. 11. The energy plant control assistance device according to claim 10, wherein the temperature range in which the number of operating devices among the plurality of devices is increased is narrowed as the actual value of the stored energy of the energy storage device becomes larger than the planned value.

12. 12. The energy plant control assistance device according to claim 11, wherein the temperature range in which the number of operating devices among the plurality of devices is reduced is narrowed as the actual value of the stored energy of the energy storage device becomes smaller than the planned value.

13. 1. An energy plant control support method for supporting control of equipment in an energy plant based on a time-series energy supply amount as a first planned value from an energy storage device in a first time period, the method comprising: a first processing step of first setting a time-series energy supply amount as a second planned value of the device that supplies energy to the energy storage device in accordance with a predetermined constraint condition, based on the time-series energy supply amount as the first planned value; a second processing step of executing processing for a second period shorter than the first period, wherein, based on a first difference between the time-series energy supply amount as the first planned value and the time-series energy supply amount as an actual measured value actually supplied from the energy storage device, secondly setting the time-series energy supply amount as a second planned value of the device in accordance with a predetermined rule so as to reduce the first difference; Equipped with providing a signal containing information about at least one of the first setting and the second setting to a controller of the device; the energy plant has a plurality of devices that supply energy to the energy storage device, including the device; In the second processing step, the predetermined rule is to operate an equipment having the lowest cost per unit time among the plurality of equipment that is not operating when the time-series energy supply amount as the actual measured value is greater than the time-series energy supply amount as the first planned value at a predetermined time point before the second setting.

14. An energy plant control system, comprising: Energy plants and an energy plant control support device; The energy plant comprises: an energy storage device; a device that generates cold and supplies it to the energy storage device; a control device for controlling the device, The energy plant control assistance device includes:

1. An energy plant control support device that supports control of equipment in an energy plant based on a time-series energy supply amount as a first planned value from an energy storage device in a first period, a first processing unit that first sets a time-series energy supply amount as a second planned value of the device that supplies energy to the energy storage device in accordance with a predetermined constraint condition, based on the time-series energy supply amount as the first planned value; a second processing unit that executes processing for a second period shorter than the first period, and that secondly sets a time-series energy supply amount as a second planned value of the device in accordance with a predetermined rule based on a first difference between a time-series energy supply amount as the first planned value and a time-series energy supply amount as an actual measured value actually supplied from the energy storage device so as to reduce the first difference; Equipped with providing a signal containing information about at least one of the first setting and the second setting to a controller of the device; the energy plant has a plurality of devices that supply energy to the energy storage device, including the device; The second processing unit, as the predetermined rule, operates an equipment among the plurality of devices that is not operating and has the lowest cost per unit time when the time-series energy supply amount as the actual measured value is greater than the time-series energy supply amount as the first planned value at a predetermined point in time before the second setting.

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