Management device and management method

Abstract

To provide an energy plant management device that can perform optimization calculation in a shorter time and with higher accuracy.SOLUTION: A management device includes a processing device and a storage device. The storage device stores information on heat demand in an energy plant and equipment characteristic information indicating a correlation between a load on a heat source machine and energy consumption for each of a plurality of heat source machines included in the energy plant. The processing device creates, on the basis of the equipment characteristic information, the plurality of heat source machine groups, each of which includes one or more heat source machines included in the plurality of heat source machines. The processing device identifies, on the basis of the information of the heat demand and the information on the plurality of heat source machine groups, one or more heat source machine groups to be adopted as a control target corresponding to the heat demand, among the plurality of heat source machine groups, The processing device creates a heat source control plan, which is a plan for supplying heat to meet the heat demand using the heat source machines included in the identified heat source machine group.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present invention relates to a management device and a management method. [Background technology]

[0002] As background art of the present invention, for example, Japanese Patent Application Laid-Open No. 2011-002112 discloses a technique for simulating an optimal combination of a plurality of heat source machines and an optimal operation schedule for each heat source machine. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2011-002112 A Summary of the Invention [Problem to be solved by the invention]

[0004] In an energy plant control system including various heat source facilities, it is necessary to perform optimization calculations taking into account various parameters in order to formulate a heat source control plan. On the other hand, in optimization calculations for formulating a heat source control plan, the number and combinations of parameters to be considered also increase as the number of types of heat source facility configurations and the scale of the energy plant control system increase. If there are a huge number and combinations of parameters, a very long calculation time may be required, or all parameters may not be considered in the optimization calculation. Here, if all parameters cannot be considered in the optimization calculation, the plan created based on the result of the optimization calculation may not necessarily be better than other plan candidates that may be considered under the same conditions, and the accuracy of the optimization calculation may be reduced.

[0005] Here, the inventors have found a problem that by performing optimization calculations without considering the equipment characteristics of each heat source equipment, the optimization calculations are performed including heat source equipment that does not need to be considered in the heat source control plan, which results in an impact on the time and accuracy of the optimization calculations. Therefore, there is a demand for an energy plant management device that can perform optimization calculations in a shorter time and with higher accuracy, taking into account the equipment characteristics of each heat source equipment. Note that the technology described in Patent Document 1 does not consider the above problem. [Means for solving the problem]

[0006] According to a first aspect of the present invention, the following management device is provided. The management device includes a processing device and a storage device. The storage device stores information on heat demand in an energy plant and equipment characteristic information indicating a correlation between the load on the heat source machine and energy consumption for each of a plurality of heat source machines included in the energy plant. The processing device creates a plurality of heat source machine groups, each of which includes one or more heat source machines included in the plurality of heat source machines, based on the equipment characteristic information stored in the storage device. The processing device identifies one or more heat source machine groups to be adopted as control targets corresponding to the heat demand from among the plurality of heat source machine groups, based on the heat demand information stored in the storage device and information on the plurality of heat source machine groups. The processing device creates a heat source control plan, which is a plan to supply heat to meet the heat demand using the heat source machines included in the identified heat source machine group.

[0007] According to a second aspect of the present invention, the following management method is provided. This management method is a method performed using a processing device and a storage device. In this method, the storage device stores information on heat demand in an energy plant and equipment characteristic information indicating a correlation between the load on the heat source machine and energy consumption for each of a plurality of heat source machines included in the energy plant. This method includes the steps of: the processing device creating a plurality of heat source machine groups, each of which includes one or more heat source machines included in the plurality of heat source machines, based on the equipment characteristic information stored in the storage device; the processing device identifying one or more heat source machine groups to be adopted as control targets corresponding to the heat demand from among the plurality of heat source machine groups, based on the heat demand information stored in the storage device and information on the plurality of heat source machine groups; and the processing device creating a heat source control plan, which is a plan to supply heat to meet the heat demand using heat source machines included in the identified heat source machine group. Effect of the Invention

[0008] According to the present invention, it is possible to realize good optimization calculations even in an energy plant that is composed of various heat source equipment. Note that problems, configurations, and effects other than those described above will become apparent from the following description of the embodiment of the invention. [Brief description of the drawings]

[0009] [Figure 1] FIG. 2 is a diagram illustrating an example of a relationship between an energy plant management device and a linked equipment system. [Diagram 2] 4 is a block diagram showing an example of a specific configuration of an operation plan processing unit. FIG. [Diagram 3] FIG. 2 is an example of a performance characteristic diagram of a heat source machine. [Figure 4] 11 is a flowchart showing an example of an overall flow from pre-processing to plan creation. [Diagram 5] 13 is a flowchart showing an example of a processing procedure performed by a heat source unit priority order determination unit. [Figure 6A]13 is a conceptual diagram showing an example of a heat source machine group creation processing procedure. FIG. [Figure 6B] 4 is a table showing an example of management information of a heat source machine. [Figure 7] 13 is a conceptual diagram showing a processing procedure performed by a heat source unit priority order determination unit. FIG. [Figure 8] 4 is an example of an operation plan created by a planning unit of the energy plant management device. [Figure 9] 4 is a block diagram showing an example of a specific configuration of an operation plan processing unit. FIG. [Figure 10] 13 is a flowchart of an example of a processing procedure in a CGS exhaust heat recovery planning unit. [Figure 11] 13 is a flowchart showing an example of a processing procedure performed by a heat source unit priority order determination unit. [Figure 12] 13 is a conceptual diagram showing a processing procedure performed by a heat source unit priority order determination unit. FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. The embodiment is an example for explaining the present invention, and appropriate omissions and simplifications are made for clarity of explanation. The present invention can be implemented in various other forms. Unless otherwise specified, each component may be singular or plural. In order to facilitate understanding of the invention, the position, size, shape, range, etc. of each component shown in the drawings may not represent the actual position, size, shape, range, etc. Therefore, the present invention is not necessarily limited to the position, size, shape, range, etc. disclosed in the drawings. As examples of various information, the various information may be described using expressions such as "table," "list," and "queue," but the various information may be expressed using data structures other than these. For example, various information such as "XX table," "XX list," and "XX queue" may be expressed as "XX information." When describing identification information, expressions such as "identification information," "identifier," "name," "ID," and "number" are used, but these are mutually interchangeable. When there are multiple components having the same or similar functions, they may be described by using the same reference numerals with different subscripts, or when there is no need to distinguish between these multiple components, the subscripts may be omitted. In the embodiment, a process performed by executing a program may be described. Here, a computer executes the program using a processor (e.g., CPU, GPU), and performs the process defined by the program while using a storage resource (e.g., memory) and an interface device (e.g., communication port), etc. Therefore, the subject of the process performed by executing the program may be the processor. Similarly, the subject of the process performed by executing the program may be a controller, device, system, computer, or node having a processor. The subject of the process performed by executing the program may be a calculation unit, and may include a dedicated circuit that performs a specific process. Here, the dedicated circuit is, for example, an FPGA (Field Programmable Gate Array), an ASIC (Application Specific Integrated Circuit), or a CPLD (Complex Programmable Logic Device), etc. The program may be installed in the computer from a program source. The program source may be, for example, a program distribution server or a computer-readable storage medium. When the program source is a program distribution server, the program distribution server may include a processor and a storage resource for storing the program to be distributed, and the processor of the program distribution server may distribute the program to be distributed to other computers. In addition, in an embodiment, two or more programs may be realized as one program, or one program may be realized as two or more programs.

[0011] In the embodiment, a technique is described that can realize accurate optimization calculations in a short time even in an energy plant including various heat source facilities. This technique can contribute from an environmental perspective by saving energy and from an economic perspective by reducing costs.

[0012] First Embodiment <Energy plant management device configuration> First, an example of the configuration of an energy plant management device and its surroundings will be described with reference to Figures 1 to 3. Figure 1 is a diagram showing an example of the configuration of an energy plant management system including an energy plant management device 10.

[0013] The energy plant management system may include an energy plant management device 10 (management device), a control output device 20, a power generation equipment management device 30, a heat source equipment management device 40, a weather provider 50, a unit price information site 60, the Internet 70, a user terminal 80, a generator 1, and a heat source unit 2. Note that the above-described form of the energy plant management system is one example, and functions described in one configuration may be divided into different configurations, or configurations described as different configurations may be integrated into one configuration.

[0014] The energy plant management device 10 performs data processing using various types of data. The control output device 20 outputs control information for the power generation equipment and the heat source equipment to the power generation equipment management device 30 and the heat source equipment management device 40 based on the information acquired from the energy plant management device 10. The power generation equipment management device 30 controls the power generation equipment including the generator 1. The heat source equipment management device 40 controls the heat source equipment including the heat source unit 2. The weather provider 50 provides information regarding the weather. The user terminal 80 may be, for example, a PC terminal of a manager at a remote management base, a PC terminal used by a system manager, a mobile terminal held by a worker, etc.

[0015] The energy plant management device 10 includes a prediction unit 100, a planning unit 200, an input unit 300, a display unit 400, a storage unit 500, and a communication interface 600. These can be configured using appropriate hardware.

[0016] The prediction unit 100 and the planning unit 200 can be configured using an appropriate processing device that performs data processing. The processing device may be configured using a processor, for example, as long as it can execute data processing. The energy plant management device 10 may include a RAM (Random Access Memory) from which the processing device reads data.

[0017] The input unit 300 is configured to input information for setting or changing the information recorded in the storage unit 500. The display unit 400 is configured to output the information recorded in the storage unit 500. The input unit 300 may be realized, for example, by including an operation device of a terminal used by a user. The display unit 400 may be realized, for example, by including a display screen of a terminal viewed by a user.

[0018] The storage unit 500 is configured using an appropriate storage device, for example, it can be configured using an HDD (Hard Disk Drive). The communication interface 600 is a component for communicating with other components of the energy plant management system.

[0019] The memory unit 500 stores equipment characteristic information 510, actual power and heat demand information 520, power and heat demand forecast information 530, weather information 540, unit price and emission coefficient information 550, constraint condition information 560, power generation and heat source control plan information 570, KPI information 580, and calendar information 590.

[0020] The equipment characteristic information 510 stores multidimensional approximated surface graph information indicating the relationship between the load factor, which is the ratio of output to the rated capacity of the generator 1 and heat source unit 2 constituting the energy plant, and the energy consumption. In addition, since the relationship between the load factor and the energy consumption changes depending on the environmental conditions under which the generator 1 and the heat source unit 2 are controlled, the equipment characteristic information 510 includes information on the relationship between the load factor and the energy consumption for each different environmental condition. Note that a specific example of the equipment characteristic information 510 will be described later in relation to FIG. 3.

[0021] The power / heat demand actual information 520 is information on actual values ​​of power demand and heat demand in the energy supply system. The power / heat demand forecast information 530 is information on forecast values ​​of power demand and heat demand in the energy supply system. The power / heat demand forecast information 530 relates to information on the demand forecast result calculated by the demand forecast calculation unit 110 described later. The weather information 540 is information on weather actual information and weather forecast information acquired by the energy plant management device 10 through communication with the weather provider 50.

[0022] The unit price and emission coefficient information 550 is information on market electricity trading unit prices and non-fossil certificate unit prices acquired by the energy plant management device 10 through communication with the unit price information site 60. The information recorded in the unit price and emission coefficient information 550 can be viewed and changed by the user. The constraint condition information 560 is information on non-operation time information of power generation equipment and heat source equipment, the number of operations per day, the duration of continuous operation, the duration of continuous stoppage, the upper and lower limits of grid receiving power, etc., and can be viewed and changed by the user.

[0023] The KPI information 580 may include, for example, cost, CO 2 Among primary energy, the target items to be prioritized for minimization in the optimization calculation and annual CO 2 Information on emission target is stored. Calendar information section 590 stores day types such as weekdays, holidays, etc., and can be viewed and changed by the user.

[0024] The power generation and heat source control plan information 570 is information on the control plan of the power generation equipment and the heat source equipment calculated by the planner 200. The information stored in the memory 500 can be viewed via the display 400 or the user terminal 80, and can be changed via the input unit 300.

[0025] The forecast unit 100 is a demand forecast calculation unit 110 and a CO 2 The demand forecast calculation unit 110 is configured with an emission target calculation unit 120. The demand forecast calculation unit 110 predicts future energy demand using, for example, the correlation between the power and heat demand record information 520, the weather information 540, and the calendar information 590. 2The emission target calculation unit 120 calculates, for example, the annual CO 2 CO2 emissions target and calendar information for 590 days 2 Calculate the emission target.

[0026] The planner 200 is made up of an operation plan preprocessor 210 that performs preprocessing to shorten the optimization calculation time, an optimization calculation unit 220, and an operation plan postprocessor 230 that corrects the deviation range from the constraint conditions after the optimization calculation.

[0027] 2 is a block diagram showing an example of a functional configuration of the operation plan preprocessing unit 210. The operation plan preprocessing unit 210 includes a heat source unit priority determination unit 210a including an operable unit determination unit 211a, a heat amount unit calculation unit 212a, a group creation unit 213a, and a priority order / load allocation unit 214a. The functions of each component will be described later.

[0028] Here, the above-mentioned equipment characteristic information will be described in more detail with reference to Fig. 3. Fig. 3 shows an example of equipment characteristic information related to the heat source unit 2. The equipment characteristic information 510 stores information on heat demand and information indicating the correlation between the load on the heat source unit and the energy consumption for each of the multiple heat source units included in the energy plant.

[0029] The horizontal axis of FIG. 3 is the load factor, and the vertical axis is the energy consumption, and FIG. 3 shows the relationship between the load factor and the energy consumption. Here, the load factor is the ratio of the actual heat production amount to the rated heat production amount, which is a value specific to each heat source unit. Therefore, by multiplying the load factor on the horizontal axis of FIG. 3 by the rated heat production amount of the corresponding heat source unit, the heat production amount of the heat source unit can be calculated. Here, the horizontal axis of FIG. 3 shows the load factor, but it may be the value of the heat production amount of each heat source unit. Since the relationship between the load factor and the energy consumption also changes depending on the cooling water inlet temperature, which is an environmental condition, the equipment characteristic information 510 related to the heat source unit 2 stores multidimensional approximated curved surface graph information that takes into account the relationship with the environmental condition.

[0030] 3 shows a graph in which the cooling water inlet temperature is an example of an environmental condition, but a graph based on other environmental conditions may be stored in the equipment characteristic information 510. The equipment characteristic information 510 may express performance characteristics using a multi-surface approximation function in which the energy (electricity, gas, steam, waste hot water) consumed by the heat source unit varies depending on the cooling water temperature, the cold water temperature, and the capacity load factor, for example.

[0031] Next, data processing by the energy plant management apparatus 10 will be described with reference to Fig. 4 to Fig. 8. First, an example of the processing procedure of the optimization calculation will be described with reference to Fig. 4. Fig. 4 is a flow chart showing an example of the processing procedure of the optimization calculation. In particular, the processing device of the energy plant management apparatus 10 is the main body of the data processing.

[0032] In S101, the prediction unit 100 calculates predicted values ​​of power demand and heat demand from the current time into the future.

[0033] In S102, the operation plan preprocessing unit 210 limits the range in which an optimal solution is searched for in the optimization calculation unit 220 by assigning the startup priority of the heat source units and loads, excluding operating units to the extent that predetermined conditions are satisfied, and calculating the operating time and operating load factor of the generators, based on the equipment characteristic information 510, the power and heat demand forecast information 530, the weather information 540, the unit price and emission coefficient information 550, the constraint condition information 560, and the KPI information 570.

[0034] In S103, the optimization calculation unit 220 applies optimization calculation logic such as a brute force calculation method, a mathematical programming method, a particle swarm optimization method, etc., to calculate the cost, CO 2 , the primary energy targets to be prioritized and the CO 2 Calculate the optimal solution according to the emission target. CO 2 CO emissions 2 If the emission target is exceeded, CO 2 CO emissions 2 Purchase non-fossil fuel certificates to stay below the emissions target.

[0035] In S104, the operation plan post-processing unit 230 compares the results calculated by the optimization calculation unit 220 with the non-operating time information of the power generation equipment and heat source equipment set in the constraint condition information 560, the number of operations per day, the duration of continuous operation, the duration of continuous stoppage, and the upper and lower limits of the grid receiving power, and if any of the results deviates from the constraint conditions, makes corrections so as not to deviate from the constraint conditions.

[0036] In S105, the result of the correction by the operation plan post-processing unit 230 is stored in the power generation / heat source control plan information 570.

[0037] Next, the details of the processing by the operation plan preprocessing unit 210 will be described with reference to Fig. 5 to Fig. 7. The processing by the operation plan preprocessing unit 210 described here corresponds to S102 in Fig. 4. Fig. 5 is a diagram showing a flowchart of an example of a processing procedure in the heat source unit priority order determination unit 210a included in the operation plan preprocessing unit 210. In detail, the processing device of the energy plant management device 10 is the main body of data processing.

[0038] In S201, the operable unit determination unit 211a receives the operation status of the heat source unit 2 managed by the heat source equipment management device 40, and if the operation status is broken or under inspection, excludes the relevant unit from subsequent processing targets as inoperable. Similarly, if the relevant unit is set to a non-operating time period in the planning target time of the constraint condition information 560, the relevant unit is also excluded from subsequent processing targets as inoperable.

[0039] In S202, a heat quantity unit is calculated, which indicates the amount of the first index required for each heat source device to produce a predetermined amount of heat. Here, the first index is the cost, CO 2 It may be either emissions or primary energy consumption. An example of how to calculate the heat intensity is shown below.

[0040] The heat quantity per unit calculation unit 212a refers to heat demand forecast information for the planning target time period from the power / heat demand forecast information 530, and calculates the minimum load rate and maximum load rate that the heat source machine can take from the equipment characteristic information 510. The heat quantity per unit calculation unit 212a also calculates the heat source unit width. The heat source unit width indicates the range that the value related to the energy consumption efficiency (here, the heat quantity per unit) can take when a predetermined range of load (for example, a load in the range between the maximum load rate and the minimum load rate) is applied to the heat source machine. Here, the value related to the energy consumption efficiency is, for example, a value in units of [￥ / GJ] as shown in FIG. 6A described later. Note that the value related to the energy consumption efficiency may be an index other than the heat quantity per unit.

[0041] If the heat demand forecast information for the planning time period is less than the minimum load of the heat source unit, the heat energy consumption unit calculation unit 212a determines that the unit cannot be operated during that time period and excludes the unit from subsequent processing. If the heat demand forecast information for the planning time period is equal to or greater than the minimum load and equal to or less than the maximum load of the heat source unit, the heat energy consumption unit calculation unit 212a determines that the range of load that the heat source unit can take is from the minimum load to the heat demand forecast information of the heat source unit. If the heat demand forecast information for the planning time period is equal to or greater than the maximum load of the heat source unit, the heat energy consumption unit calculation unit 212a determines that the range of load that the heat source unit can take is from the minimum load to the maximum load of the heat source unit. The heat energy consumption unit calculation unit 212a performs the above-mentioned process of determining the range of load that the heat source unit can take for all heat source units that make up the energy plant.

[0042] In S202, the heat source unit calculation unit 212a may also use weather forecast information for the planning time period from the weather information 540, and calculate the minimum and maximum load rates that the heat source unit can take from the equipment characteristic information 510. That is, the heat source unit calculation unit 212a may use the weather information 540 to refer to a graph in the equipment characteristic information 510 that corresponds to the environmental conditions, and calculate the load rate that the heat source unit can take.

[0043] Then, the heat source unit calculation unit 212a calculates the energy consumption for the load of the heat source unit for each prescribed interval defined by the internal setting value within the range of the load that each heat source unit can take obtained as a result of the determination process. The energy consumption of each heat source unit thus obtained is multiplied by the unit price and emission coefficient information 550 according to the target set in the KPI information (i.e., the unit price of the metered charge and the CO emission coefficient according to the KPI) to obtain the energy consumption. 2 The cost required per 1 GJ / h of produced heat is calculated by converting the amount of produced heat into CO2 emissions, etc., and dividing it by the amount of produced heat at the corresponding capacity load factor. 2 The heat unit consumption (consumption unit) is calculated as a value indicating the amount of emissions or primary energy consumption. Here, the higher the heat unit consumption, the greater the amount of energy required for the heat source device to generate a given amount of heat.

[0044] In S203, the group creation unit 213a compares the magnitude relationship between the heat quantity consumption units of the heat source machines calculated for each specified interval defined by an internal setting value in the heat quantity consumption unit calculation unit 212a.

[0045] 6A shows an example of processing related to the heat amount unit consumption calculation unit 212a and the group creation unit 213a. If the minimum or maximum value of the other heat source machines is included between the minimum and maximum values ​​of the heat amount unit consumption calculated by the heat amount unit consumption calculation unit 212a, the group creation unit 213a groups them as the same group. On the other hand, if neither the minimum nor the maximum value of the other heat source machines is included between the minimum and maximum values ​​of the heat amount unit consumption, the group creation unit 213a groups them as different groups. As a result, multiple heat source machine groups are created so that heat source machines with overlapping heat source unit widths are included in the same group. In addition, multiple heat source machine groups are created so that the heat source unit widths of the heat source machines do not overlap between different heat source machine groups.

[0046] Here, heat source machines with similar performance, i.e., heat source machines with similar heat unit consumption in heat production, are included in the same group, while heat source machines with different performance, i.e., heat source machines with dissimilar heat unit consumption in heat production, are included in another group.

[0047] When the heat source unit A and the heat source unit B are grouped into separate groups, a priority order is assigned, which will be described in detail later. In the example of Fig. 6A, the priority order for the heat source unit A is higher than the priority order for the heat source unit B, so that the priority order for the heat source unit A is first and the priority order for the heat source unit B is second.

[0048] FIG. 6B is a table showing an example of management information of heat source machines that can be referred to by the group creation unit 213a. This management information of heat source machines includes information on the minimum and maximum values ​​of the heat amount unit of each heat source machine calculated by the heat amount unit of each machine calculation unit 212a. That is, the management information of heat source machines includes a heat source unit width, which is information on the range of values ​​related to energy consumption efficiency. Furthermore, as shown in FIG. 6B, it may include information indicating the presence or absence of an exhaust heat recovery function. The exhaust heat recovery function relates to a function of supplying heat using exhaust heat from the power generation system of the facility. When the group creation unit 213a creates a group of heat source machines in S203, it may refer to management information of heat source machines such as the example shown in FIG. 6B. In addition, this management information of heat source machines may be stored in the equipment characteristics information 510.

[0049] Next, the process related to the step of priority order / load allocation in S204 will be described. FIG. 7 is a diagram showing the concept of an example of the processing procedure of the priority order / load allocation unit 214a. First, the priority order / load allocation unit 214a prioritizes the groups created by applying the logic (S201 to S203) of FIG. 5 to all heat source machines. That is, the priority order / load allocation unit 214a prioritizes the groups created by S214a-1 so that the group including the heat source machine with a low heat amount consumption rate has a higher priority. In the example of FIG. 7, three groups are created in S201 to S203, the value related to the energy consumption efficiency (heat amount consumption rate) of each heat source machine included in the multiple heat source machine groups is evaluated, and the priority order of group A including the heat source machine evaluated to have the lowest heat amount consumption rate is the first, the priority order of group B including the heat source machine evaluated to have the next lowest heat amount consumption rate is the second, and the priority order of group C including the heat source machine evaluated to have the next lowest heat amount consumption rate is the third.

[0050] Thereafter, the priority order / load allocation unit 214a allocates the maximum load of the heat source machines in the order of the groups with the highest priority order in S214a-3. The priority order / load allocation unit 214a performs the above process in S214a-2 until the total value of the allocated loads exceeds the heat demand. When the total value of the allocated loads exceeds the heat demand, the load of the last allocated group is not the maximum load but needs to be operated at partial load, so it is set as the optimum solution search element. In this example, group B is the optimum solution search element. That is, one or more first heat source machine groups that operate all heat source machines included in the group at maximum load like group A, and a second heat source machine group that allocates a part of the heat demand among the heat source machines included in the group like group B are identified. As a result, the first heat source machine group is not set as the optimum solution search element, and only the second heat source machine group is set as the optimum solution search element, which contributes to reducing the number of parameters to be considered.

[0051] In step S214a-4, the groups with the following priority levels have higher heat consumption rates than the group selected by the above process, and are therefore excluded from the operation plan creation targets. In this example, group C is excluded.

[0052] The range of loads that the heat source unit to which the load is finally assigned is "heat demand" minus "amount of heat produced by heat source units that have already been assigned rated loads." In S214a-5, for example, the load may be shared by all units in the group, or shared by the smallest possible number of units. In the latter case of sharing by the smallest possible number of units, the minimum and maximum values ​​of the load to be assigned are determined, and these minimum and maximum values ​​are set as the search range of the optimization calculation unit 220.

[0053] In the energy plant management device described in this embodiment, in the preprocessing of the optimization calculation, heat source machines are grouped based on the equipment characteristics of each heat source facility, and it is possible to determine on a group basis whether or not to use them as optimal solution search elements in the optimization calculation.As a result, there is no need to use all heat source machines included in the energy plant control system as optimal solution search elements in the optimization calculation, which reduces the number of parameters to be considered and enables the optimization calculation to be performed in a shorter time and with higher accuracy.

[0054] Next, an example of an operation plan will be described with reference to FIG. 8. FIG. 8 is an example of an operation plan created by the planner 200. That is, the planner 200 creates a heat source control plan, which is a plan for supplying heat to meet heat demand, using pre-processed data. In the example of the operation plan shown in FIG. 8, the amount of heat generated by each heat source unit adopted in the operation plan is determined in a period divided into 30 minutes. The horizontal axis indicates the start time of each period in 30 minutes, and the vertical axis indicates the amount of heat. In FIG. 8, the amount of heat generated by each heat source unit in each period is expressed as a stacked bar graph. Note that as long as an appropriate operation plan can be created, data in a form different from the form shown in FIG. 8 may be created.

[0055] <Second embodiment> Next, a second embodiment will be described. Note that the same description as in the first embodiment may be omitted. In the second embodiment, a cogeneration system (hereinafter, referred to as CGS) is included in the energy plant configuration. In the CGS, the exhaust heat generated from the generator, etc. can be recovered and utilized by the exhaust heat recovery mechanism of the heat source machine.

[0056] 9 is a block diagram showing an example of the functional configuration of the operation plan preprocessing unit 210 when the energy plant configuration includes a CGS. The operation plan preprocessing unit 210 is configured by adding a CGS exhaust heat recovery planning unit 210b, which is composed of an exhaust heat recovery merit calculation unit 211b, a peak cut presence / absence determination unit 212b, and a CGS operation plan formulation unit 213b, to the heat source unit priority order determination unit 210a described in the first embodiment. The functions of each component will be described later.

[0057] 10 is a flowchart showing an example of a processing procedure in the CGS exhaust heat recovery planning unit 210b. In particular, the processing device of the energy plant management device is responsible for data processing.

[0058] In S301a, the heat source unit priority order determination unit 210a performs heat source unit priority order determination for the case where a CGS is not used, using the same method as in the first embodiment, and determines the exhaust heat recovery unit to be planned. The exhaust heat recovery unit can be determined, for example, using management information as shown in FIG. 6B.

[0059] In S302a, the exhaust heat recovery merit calculation unit 211b calculates the effect (exhaust heat recovery merit) of operating the CGS. As an example, based on the information of the exhaust heat recovery unit determined in the S301a process, the unit calculates the difference between the value obtained by converting the energy consumption of the heat source unit when the exhaust heat recovery function is used into the target value determined by the KPI information and the value obtained by converting the energy consumption of the heat source unit when the exhaust heat recovery function is not used (for example, in the case of the first embodiment) into the target value determined by the KPI information, thereby calculating the target reduction amount determined by the KPI information as the exhaust heat recovery merit.

[0060] In S302b, the exhaust heat recovery merit calculation unit 211b calculates the power generation intensity of the CGS. The power generation intensity is calculated by subtracting the exhaust heat recovery merit from a value obtained by multiplying the gas consumption of the CGS by the unit price and emission coefficient information 550 according to the target set in the KPI information, and further dividing the result by a value obtained by subtracting the auxiliary loss from the power generated by the CGS.

[0061] If the KPI is cost, the maintenance cost defined in the equipment characteristics information 510 is added to the above calculation. In other words, the higher the power generation unit cost, the more target values ​​set in the KPIs are required for the generator to generate a specified amount of power, and therefore the smaller the power generation unit cost, the higher the priority.

[0062] In S303a, the peak cut presence / absence determining unit 212b calculates the difference between the maximum receiving power set in the power demand forecast information 530 and the constraint condition information 560 during the planning time period.

[0063] In S303b, it is determined whether the value calculated in S303a is greater than 0. If it is greater, the process proceeds to S303c. If it is not greater, the process proceeds to S304.

[0064] In S303c, the peak shaving presence / absence determination unit 212b creates a plan to operate the generators configured in the energy plant facility in the order of lowest power generation intensity. The power generation intensity of the CGS uses the value calculated in S302c. Here, for the generators other than the CGS configured in the energy plant facility, the peak shaving presence / absence determination unit 212b calculates the power generation intensity based on the information defined in the equipment characteristics information 510. For example, when a storage battery is present as a generator other than the CGS, the power generation intensity of the storage battery is calculated by multiplying the charge amount of each time period by the charging efficiency defined in the equipment characteristics information 510 and the unit price / emission coefficient information 550 according to the target set in the KPI information, and dividing the sum of the sum over all charging time periods by the charge amount of the storage battery, and multiplying the sum by the discharge efficiency.

[0065] In S304, the CGS operation plan creation unit 213b determines the operation time zone of each power generator determined in S303b. In addition, in S302a and S302b, a plan for operating the CGS is created in the time zone where the effect of operating the CGS exceeds 0.

[0066] Then, in S305, a heat source unit priority order determination is performed for the time period in which the CGS is in operation. An example of a method for determining the heat source unit priority order when the CGS is used in S305 will be described in FIG.

[0067] FIG. 11 shows an example of the processing flow of the heat source unit priority order determination unit 210a when there is CGS exhaust heat. In detail, the processing device of the energy plant management device is the main body of data processing. When CGS exhaust heat recovery is taken into consideration, the heat consumption rate of the exhaust heat recovery unit becomes lower, that is, the priority order becomes higher. Therefore, heat source units with exhaust heat recovery function are extracted from the operable units extracted in S201. The extraction of the exhaust heat recovery unit can be performed, for example, using management information as shown in FIG. 6B.

[0068] In S401, the heat source unit priority order determination unit 210a calculates the CGS maximum amount of exhaust heat. Power demand forecast information is obtained from the power / heat demand forecast information 530 in the storage unit 500, and the maximum amount of power that the CGS can generate is determined by subtracting therefrom the lower limit of the power reception set in the constraint condition information 560. From the maximum amount of power that the CGS can generate, the maximum amount of exhaust heat that the CGS can output is calculated using the CGS equipment characteristic information stored in the equipment characteristic information 510.

[0069] In S402, the heat source unit calculation unit 212a calculates the heat amount per unit of production taking into consideration the CGS exhaust heat amount. The heat amount per unit of production is calculated by using the equipment characteristic information of each heat source unit stored in the equipment characteristic information 510 to calculate a value in the case where the exhaust heat recovery unit consumes the CGS maximum exhaust heat amount calculated in S401. Here, as an example, in the case where an exhaust heat recovery unit capable of producing a second amount of heat when consuming the CGS maximum exhaust heat amount produces a first amount of heat including the second amount of heat produced by the exhaust heat recovery function, the amount of energy consumed by the exhaust heat recovery unit may be only the amount of energy consumed to produce the amount of heat obtained by subtracting the second amount of heat from the first amount of heat. In this case, the cost required per 1 GJ / h of produced heat amount, CO 2 The heat intensity is calculated as a value indicating the amount of emission or primary energy consumption. Then, the group creation process is performed in S203.

[0070] In S403, the heat source unit priority order determination unit 210a applies the logic of S201 to S203 in FIG. 11, prioritizes the created groups while taking into account exhaust heat recovery, and allocates CGS exhaust heat and load to groups with the highest priority.

[0071] In S404, the heat source unit priority order determination unit 210a determines whether the total amount of exhaust heat recovery of the units allocated CGS exhaust heat exceeds the maximum amount of CGS exhaust heat. If it does not exceed the maximum amount of CGS exhaust heat, in S405, the amount of exhaust heat recovery in the group is maximized and the load factor at the maximum amount of exhaust heat recovery is set. After setting, the process returns to S403 and CGS exhaust heat allocation is performed for the next priority order.

[0072] In S404, if the total amount of waste heat recovered by the units allocated to the CGS exceeds the maximum amount of waste heat recovered by the CGS, the process proceeds to S406.

[0073] In S406, since the next priority unit cannot recover CGS exhaust heat, the heat source unit priority order determination unit 210a sets the exhaust heat recovery amount to 0 and reassesss the heat quantity consumption unit.

[0074] In S407, the heat source unit priority order determination unit 210a calculates the load factor when all the remaining CGS exhaust heat is used up. If there are multiple exhaust heat recovery units in the same group, it is not possible to determine the allocation of the remaining CGS exhaust heat, so the minimum load factor is determined from among the combinations that will use up the CGS exhaust heat.

[0075] Thereafter, the heat source unit priority order determination unit 210a allocates loads in the same manner as S214a-1 to S214a-5 in the first embodiment.

[0076] 12 is a diagram showing the concept of an example of the processing procedure of the priority order / load allocating unit 214a in the second embodiment. First, the priority order / load allocating unit 214a assigns priorities to the groups into which heat source units are grouped in S203. In process S403, CGS exhaust heat is allocated in descending order of priority, and since group A in this figure can recover the maximum amount of CGS exhaust heat, the load factor is set to 100% in S405.

[0077] Next, if group B is similarly allocated exhaust heat, and as a result group B recovers the maximum amount of CGS exhaust heat, there will be a shortage of CGS exhaust heat, so it will be necessary to adjust the amount of exhaust heat recovered in group B. Because there are multiple heat source units belonging to group B, the minimum and maximum values ​​that can be recovered by each unit are calculated from the combination of remaining CGS exhaust heat allocations. The load rate when the amount of exhaust heat recovered is at its minimum is calculated as the minimum load rate. Because RA5, a waste heat recovery unit belonging to group C, has no recoverable CGS exhaust heat remaining, S406 sets the amount of exhaust heat recovered to 0, revises the minimum and maximum basic units, and regroups and reviews the priorities.

[0078] The priority order / load allocation unit 214a sets the load factor search range for group B from the minimum load factor calculated in process S407 to 100%. In other words, since the combination of exhaust heat recovery amount and load factor in group B cannot be uniquely determined, it is calculated by the subsequent optimization logic and is not determined in preprocessing. However, the minimum load factor when the exhaust heat recovery amount is recovered so that the total is 1.0 is determined, and the load factor search range is determined.

[0079] Even when the heat source units belonging to group B have the maximum load factor, in group C, if Σ (the amount of heat produced by the load-allocated units)≦heat demand, the priority order / load allocating unit 214a sets the load factor to 100%.

[0080] In group D, depending on the range of the load rate of group B, the possible load rate range for the heat source units in group D is determined as the heat demand at the maximum load rate of the heat source units in group B - Σ (amount of heat produced by the load-assigned unit) - the heat demand at the minimum load rate of the heat source units in group B - Σ (amount of heat produced by the load-assigned unit) is determined. Because the amount of heat produced by group D makes Σ (amount of heat produced by the load-assigned unit) = heat demand, heat source units in groups after group D (groups different from groups A to D) are not included in the planning.

[0081] Thereafter, in the same manner as described above, the planning unit 200 uses the pre-processed data to create a heat source control plan, which is a plan for supplying heat to meet the heat demand.

[0082] In an energy plant control system equipped with a CGS, the types and number of parameters to be considered, such as the performance of the exhaust heat recovery function, the amount of exhaust heat recovered, etc. In the energy plant management device described in this embodiment, in the preprocessing of the optimization calculation, heat source equipment is grouped based on the equipment characteristics including the exhaust heat recovery function of each heat source equipment, and it is possible to determine whether or not to use each group as an optimal solution search element in the optimization calculation, thereby making it possible to reduce the number of parameters to be considered when planning an energy plant control system equipped with a CGS.

[0083] According to the above embodiment, as an example, an energy plant management device is provided that includes: a memory unit that stores information on heat demand in a heat source control system and equipment characteristic information, which is information indicating a correlation between the load on the heat source machines and energy consumption for each of the multiple heat source machines that constitute the heat source control system; a processing unit that creates multiple heat source machine groups, each of which includes one or more heat source machines included in the multiple heat source machines based on the equipment characteristic information; a data pre-processing unit that identifies one or more heat source machine groups among the multiple heat source machine groups to be adopted as control targets in creating a heat source control plan related to the heat demand based on information on heat demand and information on the multiple heat source machine groups; and a plan creation unit that creates a heat source control plan in which heat is supplied to meet the heat demand by heat source machines included in the heat source machine groups identified by the data pre-processing unit.

[0084] Although the embodiments have been described above, the present invention is not limited to the above-described embodiments, and includes various modifications and equivalent configurations within the spirit of the appended claims. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those having all of the configurations described. In addition, for example, other configurations may be added, deleted, or replaced with respect to part of the configuration of the embodiment.

[0085] Here, even if an energy plant control system is equipped with a CGS mechanism, depending on the type of KPI that is emphasized, there are cases where not using the CGS will result in a better result for the entire system. For this reason, a system capable of supporting a user in determining whether or not to use a CGS is desired. Thus, as one example, the energy plant management device separately creates a first heat source control plan related to a heat source control plan when the exhaust heat recovery function and the information on the exhaust heat amount are not used, and a second heat source control plan related to a heat source control plan when the exhaust heat recovery function and the information on the exhaust heat amount are used, and calculates values ​​related to the indicators of each heat source control plan (e.g., operating costs, CO 2Each heat source control plan may be output together with the heat source control plan, the heat source control plan, and the heat source control plan (e.g., amount of heat generated by the heat source control and the like). Here, each heat source control plan may be output so as to be comparable to a display screen of a terminal viewed by a user. Furthermore, a method for creating the first heat source control plan and the second heat source control plan may be the method described in the first or second embodiment described above.

[0086] The energy plant management device may output control information for responding to heat demand based on a heat source control plan selected by a user. The energy plant management device may automatically adopt a heat source control plan having a better index value from among the heat source control plans, and output control information for responding to heat demand. [Explanation of symbols]

[0087] 10. Energy plant management device 100 Prediction Department 200 Planning Department 500 storage section

Claims

1. A processing device and a storage device, The storage device includes: storing information on heat demand in the energy plant and equipment characteristic information indicating a correlation between a load on each of a plurality of heat source machines included in the energy plant and energy consumption; The processing device includes: Based on the equipment characteristic information stored in the storage device, a plurality of heat source machine groups are created, each of which includes one or more heat source machines included in the plurality of heat source machines; Identifying one or more heat source machine groups to be adopted as control targets corresponding to the heat demand among the plurality of heat source machine groups based on the heat demand information stored in the storage device and the plurality of heat source machine groups; A heat source control plan is created, which is a plan for supplying heat to meet the heat demand using the heat source machines included in the identified heat source machine group. A management device comprising:

2. The management device according to claim 1 , The storage device includes: A heat source unit width is stored, which is information on the range of values ​​related to energy consumption efficiency that can be obtained when a load within a specified range is applied to the heat source device; The processing device includes: The plurality of heat source machine groups are created so that the heat source machines having the same heat source unit width are included in the same group. A management device comprising:

3. The management device according to claim 1 , The storage device includes: Store a heat source unit width, which is information regarding the range of values ​​that can be taken on regarding energy consumption efficiency when a load within a specified range is applied to the heat source device; The processing device includes: The plurality of heat source machine groups are created so that the heat source unit widths of the heat source machines included in different heat source machine groups do not overlap. A management device comprising:

4. The management device according to claim 1 , The processing device includes: Evaluating a value relating to the energy consumption efficiency of each heat source machine included in the plurality of heat source machine groups, and assigning a priority to the plurality of heat source machine groups based on the evaluation when identifying a heat source machine group to be adopted as a control target in creating the heat source control plan. A management device comprising:

5. The management device according to claim 1 , The device characteristic information is storing a graph of said correlations associated with environmental conditions; The processing device includes: A process of creating the plurality of heat source machine groups using the graph according to the usage environment of the heat source machine is performed. A management device comprising:

6. The management device according to claim 1 , The processing device includes: Identifying one or more first heat source machine groups in which all heat source machines included in the group are operated at maximum load, and a second heat source machine group in which a part of the heat demand is apportioned among the heat source machines included in the group. A management device comprising:

7. The management device according to claim 1 , The storage device includes: Stores information on the exhaust heat recovery function, which is a function that supplies heat by utilizing the exhaust heat from the facility's power generation system, The processing device includes: Based on the information on the exhaust heat recovery function, one or more exhaust heat recovery heat source machines that are heat source machines to be adopted as control targets in creating the heat source control plan can be identified. A management device comprising:

8. The management device according to claim 1 , The storage device includes: Stores information on the exhaust heat recovery function, which is a function that supplies heat by utilizing the exhaust heat from the facility's power generation system, The processing device includes: Furthermore, based on the information on the exhaust heat recovery function, a plurality of heat source machine groups are created, each of which includes one or more heat source machines included in the plurality of heat source machines; Furthermore, one or more heat source machine groups to be adopted as control targets corresponding to the heat demand are identified from among the plurality of heat source machine groups based on the information on the amount of exhaust heat. A management device comprising:

9. The management device according to claim 8, The processing device includes: A first heat source control plan regarding the heat source control plan when the exhaust heat recovery function and the information on the exhaust heat amount are not used, and a second heat source control plan regarding the heat source control plan when the information on the exhaust heat recovery function and the exhaust heat amount are used can be created separately, The information on the first heat source control plan and the information on the second heat source control plan are output in a comparable manner. A management device comprising:

10. A management method using a processing device and a storage device, comprising: The storage device includes: Information on heat demand in the energy plant and equipment characteristic information indicating a correlation between a load on the heat source equipment and energy consumption for each of a plurality of heat source equipment included in the energy plant are stored, The processing device creates a plurality of heat source machine groups, each of which includes one or more heat source machines included in the plurality of heat source machines, based on the equipment characteristic information stored in the storage device; The processing device identifies one or more heat source machine groups to be adopted as a control target corresponding to the heat demand among the plurality of heat source machine groups based on the heat demand information stored in the storage device and the plurality of heat source machine group information; A step in which the processing device creates a heat source control plan that is a plan for supplying heat to meet the heat demand using the heat source machines included in the identified heat source machine group; A management method comprising:

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