JP6322588B2 - Community management system - Google Patents

Description

  The present invention relates to a technique for managing an operation of a community that operates a facility device by controlling parameters.

  There is a technique for managing the operation of equipment that operates by controlling parameters in a predetermined community. The parameter is, for example, resource consumption or operating time for operating the equipment.

  As an example, there is a technique for managing the organization operation of a factory so as to suppress the operation cost as much as possible in the operation of a factory that is a community that operates a manufacturing apparatus that is an equipment device with electric power. In factory operation, the higher the contract power, the higher the power charge, so an attempt is made to keep the contract power as low as possible.

  In recent years, the supply of electric power has been insufficient, and the electricity charges have gradually increased, and the penalty for excess contracted electric power has also increased in factories. For this reason, it is also required to suppress the excess of contract power as much as possible.

  For this reason, factory operation management systems have started to introduce a method (demand adjustment) that sets a target for power consumption (target power) during operation of the equipment and adjusts supply and demand so that the target power is not exceeded. Yes.

  As factory supply and demand adjustment, for example, there is a power peak shift that reduces the power of the power peak by implementing a shift in the execution time zone of the production process. In addition, there is a measure of charging the storage battery during a low demand period and discharging from the storage battery during a high demand period, thereby preventing the contract power from being exceeded while keeping the contract power low.

  However, even if such supply and demand adjustment measures are implemented to the maximum extent, it is possible to avoid a situation where power consumption exceeds the target power.

  Under such circumstances, it has been common practice to avoid exceeding the target power by giving up and paying the penalty for exceeding the contract power to the power company or by forcing the production site to stop a part of the production process. It was broken. As a penalty for exceeding the contract power, for example, not only the power usage fee exceeding the contract power is paid, but also the contract power charge for the next year is increased and the increase in the contract power fee is paid.

  However, when such an excess of target power occurs, it may be impossible to set operational restrictions in the first place. The operational restrictions are the operational restrictions of various parameters in the factory operation, and the factory is normally operated within the scope of the restrictions. Human resources, equipment, materials, power, etc. are resources that are parameters in the factory.

  If it is impossible to set resource constraints, it may be more reasonable to relax the constraints. However, it is not easy for a person who is responsible for setting such resource constraints, for example, a management layer, to become familiar with the operation of a plurality of resources such as human resources, facilities, materials, and electric power related to factory production. Therefore, it is usually difficult for management to choose the best solution.

  As described above, there may be no solution that can achieve the target even if the maximum supply and demand adjustment is performed within the limits of the resource of the current community operation. In that case, for the operation of the community, it is necessary to break the constraint of any resource, but it is difficult to determine how much it is reasonable to break which constraint.

  On the other hand, Patent Document 1 (Japanese Unexamined Patent Application Publication No. 2009-258863) discloses a technique for allowing a deviation from resource constraints and making a preferable production plan. Patent Document 1 states that “when the cumulative load at the end of the planning target period exceeds the cumulative process capability, in order to ensure the necessary process capability without reducing the load, the end of the planning target period of the calculation itself is determined. Set longer than the end of the planning period, expand the solution space to allow late delivery solutions, and add a late delivery penalty term to the objective function of the model in the basic solution when no late delivery occurs. For numerical calculations, a method using heuristics in combination with the Lagrange decomposition adjustment method is applied. "

JP 2009-258863 A

  The technology disclosed in Patent Document 1 allows the use of a Lagrangian relaxation, allowing the delivery of a reasonable schedule that cannot be executed unless a delay in delivery with respect to the order delivery date is allowed, and breaching the parameter constraint of the delivery date. It creates a possible schedule. That is, the technique of Patent Document 1 is a technique for relaxing the restriction of a single parameter called delivery date.

  However, in the operation of a community such as the factory described above, there are a plurality of resources, and there are a plurality of parameters in the operation of the factory including them. Which parameter is appropriate to be relaxed depends on the situation at that time. Therefore, the technique disclosed in Patent Document 1 cannot appropriately cope with an application for managing the operation of a complex community such as a factory.

  An object of the present invention is to provide a technique for appropriately managing the operation of a community that operates equipment by adjusting a plurality of parameters on which restrictions are imposed.

  In the community management system according to one aspect of the present invention, a plurality of communities that operate resources and use the resources to obtain the results of the operations of the facilities include a plurality of resources that include the usage amount of the resources and affect the cost of operation of the communities. Is a community management system for managing a parameter with a constraint, and a constraint setting unit for setting the constraint for each of the parameters, and for each parameter, it occurs per unit deviation when deviating from the constraint A constraint deviation cost calculation unit that calculates unit deviation amount cost for each factor that is a cost, and a future demand amount of the resource for operation of the facility equipment is predicted, and a state in which the deviation of the constraint cannot be avoided occurs. When the deviation from the constraint cannot be avoided, the supply and demand prediction unit for determining the Constraint that specifies a constraint departure pattern that is a pattern of how to relax the restriction of which parameter and how to operate the facility equipment based on the total cost of constraint departure that is the total cost of operation when the community deviates from the constraint A mitigation item determination unit.

  ADVANTAGE OF THE INVENTION According to this invention, the technique which adjusts the some parameter to which restrictions are imposed, and manages appropriately the operation | movement of the community which operates an equipment apparatus can be provided.

It is a figure which shows the hardware constitutions of the community management system by Example 1. FIG. It is a block diagram which shows the function structure of the community management system by Example 1. FIG. It is a flowchart which shows the factor constraint deviation cost determination flow in the factory demand management apparatus 110. It is a graph which shows the example of the cost which generate | occur | produces when the working hours of the employee who is a factor deviate from the working time which is restrictions. It is a figure which shows the example of the information displayed on the screen in a factory demand management apparatus. It is a graph which shows the example of the cost which generate | occur | produces because the power consumption which is a factor deviates from contract electric power which is restrictions. It is a figure which shows the example of the cost which generate | occur | produces additionally with the chiller operating number. It is an example of a constraint deviation cost definition table. It is a flowchart which shows the restriction deviation total cost calculation flow in the factory demand management apparatus 110. It is a flowchart which shows the determinant sensitivity analysis flow in the factory demand management apparatus 110. It is a figure which shows an example of a sensitivity analysis table. It is a flowchart which shows the restriction relaxation pattern determination flow in the factory demand management apparatus 110. It is a table which shows the factor of control object. For example, when the influence threshold is 100 kWh, the candidate of the factor to be controlled is determined as shown in FIG. It is a table which shows an example of the calculation result of a constraint deviation pattern. It is a flowchart which shows the power consumption maximum value calculation flow in the factory demand management apparatus 110. FIG. It is a flowchart which shows the facility demand management apparatus control flow in the factory demand management apparatus 110. FIG. It is a table which shows an example of facility demand management apparatus control method information. It is a table which shows an example of facility demand management apparatus control method information. It is a table which shows an example of the control parameter setting of a facility demand management apparatus. 4 is a flowchart showing an equipment control flow in the equipment demand management apparatus 100. It is a graph which shows the example of the cost which generate | occur | produces additionally with the change of the temperature which can set the air conditioning in Example 2. FIG. It is a graph which shows the example of the cost which generate | occur | produces additionally with the change of the temperature which can set the air-conditioning in Example 2 when there are two or more consumers. 10 is an example of a constraint deviation cost definition table in the second embodiment. It is a figure which shows the example of the information displayed on the screen in BEMS in Example 2. FIG.

  Embodiments of the present invention will be described with reference to the drawings.

  In the present embodiment, a community management system that makes it possible to implement scheduling of an appropriate business plan for supply and demand adjustment in a factory community is illustrated.

  The community management system allows the working hours of the producers (employees) at each production facility, the operating hours of the equipment (equipment) when the power consumption of the entire factory for a certain period is expected to exceed the target power. The output of the air conditioning equipment or the like is set as a parameter with restrictions imposed on each of them, a restriction deviation pattern that minimizes the total cost at the time of deviation from the restriction is calculated, and the equipment is controlled based on the calculated new restriction. Note that the constraint is the controllable range of the parameter, when it is specified only by the upper limit value, when it is specified only by the lower limit value, when the range is specified by the upper limit value and the lower limit value, it is a discrete value that can be selected. There are cases where it is prescribed. According to the present embodiment, it is possible to schedule an appropriate business plan for supply and demand adjustment in a factory facility in a factory community.

  As energy management by information cooperation of multiple production facilities or production departments, not only cooperation within a single factory as shown in this example, but also a self-consignment system that distributes self-generated electricity between factories was used. Initiatives such as cooperation between factory bases and energy cooperation among multiple companies in the coastal complex are already underway. A present Example illustrates the community management system suitable for such energy management.

  FIG. 1 is a diagram illustrating a hardware configuration of the community management system according to the first embodiment. The community management system includes a facility demand management device 100 and a factory demand management device 110. The facility demand management apparatus 100 is a MES (Manufacturing Execution System), and the factory demand management apparatus 110 is a FEMS (Factor Energy Management. System). The facility demand management device 100 and the factory demand management device 110 perform power supply and demand adjustment in the customer facility and the factory, respectively. Here, the consumer means a main body divided for each production operation such as each department in the factory facility.

  The facility demand management device 100 and the equipment 106 are installed in a customer facility such as a production department in the factory, and the facility demand management device 100 of other customers and a plurality of customers are connected via the communication network 120. Are connected to a common factory demand management apparatus 110.

  The communication network 120 is a communication path for transmitting data between different terminals, and is, for example, the Internet or a dedicated line. However, as long as communication can be established between the facility demand management apparatuses 100 of different customers and between the facility demand management apparatus 100 and the factory demand management apparatus 110, the form is not limited.

  The facility demand management apparatus 100 includes a CPU 101, a communication unit 102, an input / output unit 103, a main storage device 104, and a secondary storage device 105, and is, for example, a PC terminal. The facility demand management apparatus 100 is installed in a customer's facility.

  The CPU 101 is a CPU (Central Processing Unit). The communication unit 102 is a communication interface for performing communication with the outside. The input / output unit 103 is an input / output interface for inputting / outputting information. The main storage device 104 is a main storage device that stores programs and data. The secondary storage device 105 is a secondary storage device that stores programs and data for a long period of time.

  In FIG. 1, the facility demand management apparatus 100 is installed in the customer's facility. However, the facility demand management device 100 may be installed outside the customer's facility as long as the ownership by the customer is protected. . In FIG. 1, the facility demand management apparatus 100 is configured with dedicated hardware. However, as another example, the facility demand management apparatus 100 is software installed on a PC owned by a consumer or provided on the cloud. It may be in the form of a service.

  The factory demand management device 110 includes a CPU 111, a communication unit 112, an input / output unit 113, a main storage device 114, and a secondary storage device 115. For example, the factory demand management device 110 is permitted to handle customer information such as a superordinate management department of a factory. Owned by the subject. The CPU 111 is a CPU. The communication unit 112 is a communication interface that performs communication with the outside. The input / output unit 113 is an input / output interface. The main storage device 114 is a main storage device. The secondary storage device 115 is a secondary storage device.

  FIG. 2 is a block diagram illustrating a functional configuration of the community management system according to the first embodiment.

  The facility demand management apparatus 100 includes a demand measurement unit 201 and an equipment device control unit 202.

  The demand measuring unit 201 measures the power demand of the equipment of the customer's facility, and transmits power demand information loaded with the measured power demand to the factory demand management device 110.

  The equipment control unit 202 controls the equipment of the customer based on the planned supply and demand plan. For example, a parameter (factor) that can be adjusted to control the equipment is adjusted within a range of constraints imposed on the factor to control the equipment.

  The factory demand management apparatus 110 includes a demand monitoring unit 210, a supply and demand prediction unit 211, a constraint deviation cost calculation unit 212, a determinant sensitivity analysis unit 213, a constraint relaxation item determination unit 214, a constraint relaxation cost presentation unit 215, and a constraint setting unit 216. Have

  The demand monitoring unit 210 receives power demand information transmitted from each facility demand management apparatus 100, aggregates them, and monitors the power demand of the entire factory.

  The supply and demand prediction unit 211 predicts a future demand that is a future power demand of the entire factory. For example, future demand can be predicted based on past power demand and information acquired from the outside.

  The constraint deviation cost calculation unit 212 generates a cost per unit deviation amount (also referred to as “unit deviation amount cost for each factor”) when the currently set constraints are deviated for each of a plurality of factors that determine power consumption. Calculated).

  The determinant sensitivity analysis unit 213 calculates, for each factor, the sensitivity to the final power consumption due to the factor.

  The constraint relaxation item determination unit 214 changes a factor of a constraint relaxation target (relaxation factor candidate) within a predetermined constraint departure range, and a constraint departure pattern that minimizes the cost (“constraint departure total cost”) generated by the departure. Is identified. The deviation range is a range of constraints from which the factor can deviate. For example, factors whose sensitivity calculated by the determinant sensitivity analysis unit 213 is equal to or higher than a predetermined threshold are set as mitigation factor candidates, and those mitigation factor candidates are adjusted to specify a constraint deviation pattern that minimizes the total constraint deviation cost.

  The constraint relaxation cost presentation unit 215 presents the calculated constraint deviation pattern to a manager who supervises the operation of the factory such as a manager. For example, the constraint relaxation cost presentation unit 215 displays constraint departure pattern information on the screen.

  The constraint setting unit 216 changes the setting of the constraint imposed on the facility demand management apparatus 100 in a direction to relax based on the constraint deviation pattern specified by the constraint relaxation item determination unit 214.

  Here, as an example, the demand monitoring unit 210, the supply and demand prediction unit 211, the constraint deviation cost calculation unit 212, the determinant sensitivity analysis unit 213, the constraint relaxation item determination unit 214, the constraint relaxation cost presentation unit 215, and the constraint setting unit 216 include The configuration is realized by installing software in the factory demand management apparatus 110. However, it is not limited to this configuration. As another example, each of the above units may be configured by installing software on a PC owned by a consumer, or may be provided as a cloud service on the Internet.

  FIG. 3 is a flowchart showing a factor constraint departure cost determination flow in the factory demand management apparatus 110. The factor constraint departure cost determination flow is a process for determining and recording how much a certain factor deviates when it deviates from the constraint, and recording it.

  In the power consumption determination factor definition (S300), the factory demand management device 110 defines a factor for determining the power consumption. Here, the factors that determine the power consumption are parameters that influence the power consumption in production, such as the number of products produced, the required quality of products, and the output of production equipment. For example, these factors may be extracted automatically from past demand history information using a multivariate analysis method such as multiple regression analysis, or a supervisor such as a manager or a site manager based on experience. It may be determined by trial and error. At this time, if the number of factors increases, the possibility of correlation between factors increases. In such cases, for example, the factor may be reduced to a smaller number of uncorrelated synthetic variables by principal component analysis, or when the influence on the operational cost due to correlation between factors is small, the administrator's judgment Such correlation may be ignored.

  Step S301 is a process executed by the constraint deviation cost calculation unit 212. Here, the cost (unit deviation cost per factor or constraint deviation cost) generated when the factor defined in the power consumption determination factor definition deviates from the currently set constraint range is determined. The unit deviation cost per factor is determined according to the characteristics of the factor.

  FIG. 4 is a graph showing an example of costs that occur when the working hours of employees as factors deviate from the available working hours as constraints. In this figure, the maximum workable time of the current employee is 8 hours, and when this restricted workable time is relaxed to 9 hours, 10 hours, and 11 hours, the costs incurred in each case are as follows. 200, 400, and 600.

  For example, when the factor is working hours, the cost generated due to deviation from the constraint may be estimated from wage and number of employees related to overtime work, or there may be cases where the restriction on working hours has been applied in the past. For example, the generated cost may be estimated by referring to the generated cost at that time.

  At this time, for example, the factory demand management apparatus 110 may display the information shown in FIG.

  FIG. 5 is a diagram illustrating an example of information displayed on the screen in the factory demand management apparatus. An input screen and an output screen to be presented to the manager or the site manager are shown. The manager or the site manager can specify the current constraint range for each factor, the constraint deviation cost per unit deviation amount, and the constraint deviation setting range on the input screen as shown in FIG.

  FIG. 6 is a graph showing an example of the cost generated when the power consumption, which is a factor, deviates from the contract power, which is a constraint. In this figure, when the current contract power is 700 kWh and the contract power is changed to 800 kWh, 900 kWh, and 1000 kWh, the generated costs are 100, 300, 500, and 800 in each case. The cost generated by exceeding the contract power can be calculated from, for example, information on the unit price of electric power presented by the power company.

  Further, when the constraint departure cost varies depending on the external environment, the generated cost is calculated in consideration of the influence of the external environment. For example, when the factor is the number of operating cooling chillers, the generated cost due to the change in the operating number varies depending on the outdoor temperature of the day. In other words, the higher the outside air temperature, the lower the cooling efficiency of the chiller, so that the amount of power used increases, resulting in an increase in cost.

  FIG. 7 is a diagram illustrating an example of additional costs that accompany the number of chiller operations. In this figure, the current maximum number of chillers that can be operated is 5, and when this maximum operable number is changed to 6, 7, 8, 9, 10, the cost that occurs in each case varies depending on the outside air temperature. It is shown that. For example, when the parameter is the number of operating chillers, refer to the past operation results of a factory that has introduced a similar chiller, for example, multiply the operation results by a factor based on the difference in factory scale. It may be estimated by referring to the cost that occurred at that time if there is a case where the restriction on the number of operating units has been applied in the past.

  Returning to FIG. 3, step S <b> 302 is processing for storing, in the main storage device 114 or the secondary storage device 115, the cost generated due to the constraint departure of each factor calculated by the constraint departure cost calculation unit 212 as a constraint departure cost definition table. .

  FIG. 8 is an example of a constraint departure cost definition table. For each factor, the external environmental condition, the unit deviation w, and the generated cost for each multiple of the unit deviation are shown.

  FIG. 9 is a flowchart showing a flow for calculating the total deviation from the constraint in the factory demand management apparatus 110.

  Step S400 is a process that is performed in the determinant sensitivity analysis unit 213 and calculates the degree of influence (sensitivity) of each factor on the power consumption. It is possible to reduce the calculation time for optimization by limiting the factors for performing constraint relaxation to those having a high influence degree and reducing the solution space. FIG. 10 shows a detailed flow of step S400.

  Step S401 is a process that is performed in the constraint relaxation item determination unit 214, changes the factor of the relaxation factor candidate within a predetermined constraint departure range, and identifies a constraint departure pattern that minimizes the cost caused by the departure. The detailed flow of step S401 will be described later using 6.

  Step S402 is processing that is performed in the constraint relaxation cost presentation unit 215 and presents the constraint departure pattern determined in step S401 and the total constraint departure cost at that time to the manager.

  Information presentation by the factory demand management apparatus 110 will be described. For example, as shown in the output screen of FIG. 5, the constraint deviation pattern and the total cost of deviation from the constraint are represented by the factors for changing the constraint, the deviation amount for each factor, the cost generated by the deviation, and the total cost generated by the constraint deviation. It is done in the form of presentation. As the total generated cost due to the deviation from the constraint, a value in the case of the currently set constraint and a value in the case where the constraint is relaxed may be indicated.

  Step S403 is processing performed in the constraint setting unit 216. The detailed flow of step S403 will be described later with reference to FIG.

  FIG. 10 is a flowchart showing a determinant sensitivity analysis flow in the factory demand management apparatus 110.

  Step S500 is a process of calculating the predicted resource demand of the entire factory, for example, every hour from the present to X hours later, and calculating the maximum value Dmax0. The detailed flow of step S500 will be described later with reference to FIG.

  Step S501 is a process of relaxing the upper limit of the control factor determinant by a predetermined ratio. For example, the upper limit value of the currently set constraint range is relaxed by 20% of the entire constraint range.

  In step S502, as in step S500, a predicted resource demand of the entire factory, for example, every hour from the present to X hours later, is calculated, and the maximum value Dmax. This is a process for calculating new. The detailed flow of step S502 will be described later with reference to FIG.

  In step S503, the demand forecast amount maximum value Dmax0 before the upper limit of the constraint is relaxed, and the demand forecast amount maximum value Dmax. new and the difference Dmax0-Dmax. new is calculated as the degree of influence (maximum fluctuation rate) on the power consumption of the entire factory by the factor to be controlled.

  Step S504 is processing for determining whether or not processing has been performed on data of all factors that determine power consumption. If it is confirmed that all the data has been processed, the process proceeds to step S505. If it cannot be confirmed, the process proceeds to step S503.

  FIG. 11 is a diagram illustrating an example of a sensitivity analysis table. Step S505 is a process of storing the calculation result of the degree of influence (maximum value fluctuation rate) as a sensitivity analysis table in the main storage device 114 or the secondary storage device 115 in the form as shown in FIG. 11, for example.

  FIG. 12 is a flowchart showing a constraint relaxation pattern determination flow in the factory demand management apparatus 110.

  Step S600 is processing for receiving the sensitivity analysis table (sensitivity analysis information) of FIG. 11 from the main storage device 114 or the secondary storage device 115. The acquired sensitivity analysis information data is stored in the secondary storage device 115.

  Step S601 is processing for receiving the constraint departure cost definition table (constraint departure cost information) of FIG. 8 from the main storage device 114 or the secondary storage device 115. The acquired constraint departure cost information data is stored in the secondary storage device 115.

  In step S602, a factor to be controlled within a constraint range is determined when extracting a pattern for relaxing the constraint. As a method for determining a factor to be controlled, for example, the sensitivity analysis result of each factor shown in FIG. FIG. 13 is a table showing factors to be controlled. For example, when the influence threshold is 100 kWh, the candidate of the factor to be controlled is determined as shown in FIG.

  Step S <b> 603 is a process of calculating the constraint departure pattern that minimizes the overall constraint departure cost by performing the relaxation of the constraint of the factor determined as the control target.

  As a calculation method of the constraint departure pattern that minimizes the overall constraint departure cost, for example, the unit deviation amount of the controlled factor shown in FIG. 13 is used as a control variable, and the generated cost setting range for each constraint departure amount shown in FIG. As a condition, for example, there is a method of solving a combinatorial optimization problem by using an objective function for minimizing a constraint deviation cost.

  An example of the constraint departure cost minimization objective function can be shown as minimizeΣ (ai × Ri). Ri is the constraint deviation amount of factor i, and ai is the cost generated per unit deviation amount of factor i. The generated cost per unit deviation amount of the factor i is determined from the constraint deviation cost definition table of FIG. The solution to the optimization problem may be performed by the CPU 111 using an arbitrary optimization program, or may be performed by a person through trial and error.

  FIG. 14 is a table showing an example of the calculation result of the constraint departure pattern. The constraint departure pattern calculation result is registered in the secondary storage device 115 as shown in FIG. 14, for example.

  Returning to FIG. 12, step S604 is processing for confirming whether there is a solution that can be executed in step S603. If there is a feasible solution, the process proceeds to step S605, and if not, the process returns to step S602 to reduce the influence threshold by an arbitrary amount and select the control target factor again.

  Step S605 is processing to record the calculation result of the constraint deviation pattern in the main storage device 114 or the secondary storage device 115.

  FIG. 15 is a flowchart illustrating a flow of calculating the maximum power consumption value in the factory demand management apparatus 110.

  Step S700 is processing performed in the factory demand management apparatus 110 communication unit 112. The factory demand management apparatus 110 is connected to the facility demand management apparatus 100 of each customer in the factory via the communication network 120, and data can be transmitted / received by the communication unit 112.

  In step S <b> 700, the factory demand management apparatus 110 receives demand measurement information including a demand value measured by the demand measurement unit 201 from the controlled facility demand management apparatus 100 via the communication network 120. The acquired data is stored in the secondary storage device 115.

  Step S701 is processing for confirming whether demand measurement information has been received from all facility demand management apparatuses 100 in the factory. If it is confirmed that data has been received from all the facility demand management apparatuses 100, the process proceeds to step S702, and if it cannot be confirmed, the process returns to step S700.

  Step S702 is a process performed in the demand monitoring unit 210, and is a process of calculating the predicted power consumption Dt of the entire factory in the time zone t for each specified time from the present to X hours later. The predicted power consumption Dt at time t is calculated, for example, by the sum of the predicted fixed demand, that is, the demand that cannot be adjusted due to the production plan change (fixed demand) and the demand that can be adjusted (adjustable demand).

  The fixed demand may be calculated using a statistical method such as storage-based reasoning, or may be calculated using the previous day's actual value. The adjustable demand is determined by controlling the value of each factor within the constraint range so that the maximum demand from the present to X hours later is minimized. The value of each factor is determined by, for example, minimizing the maximum demand from the present function to X hours after the objective function, and using an arbitrary optimization program by the CPU 111 with the constraint condition as the current constraint range of each factor. It may be determined by trial and error. The calculated planned demand amount Dt of the entire factory at time t is stored in the secondary storage device 115.

  Step S703 is a process of extracting the maximum value from the calculated predicted power consumption Dt. The extracted maximum planned demand amount for the entire factory is stored in the secondary storage device 115.

  FIG. 16 is a flowchart showing a facility demand management apparatus control flow in the factory demand management apparatus 110.

  Step S800 is processing for receiving facility demand management device control method information from the main storage device 114 or the secondary storage device 115.

  17 and 18 are tables showing an example of facility demand management apparatus control method information. The facility demand management apparatus control method information is expressed, for example, in the form of a combination of the table shown in FIG. 17 and the table shown in FIG. FIG. 17 shows a control method ID representing a control method for the facility demand management apparatus. FIG. 18 shows the contents of the control method corresponding to the control method ID.

  The acquired facility demand management device control method information data is stored in the secondary storage device 115. The facility demand management apparatus control method of FIGS. 17 and 18 may be arbitrarily set by the administrator in accordance with the management form of each facility or the management system operation status.

  Step S801 is processing to execute an action for each facility demand management apparatus 100 in accordance with the facility demand management apparatus control method information. A plurality of forms are conceivable for the execution of the action, and any form may be adopted.

  In FIG. 17, when the facility demand management device has a control method ID of 1, the constraint deviation pattern calculation result shown in FIG. 14 is obtained from the main storage device 114 or the secondary storage device 115, and the facility manager is informed by e-mail. Notification of new constraints on equipment at the facility.

  In addition, in FIG. 17, the facility demand management apparatus having the control method ID 2 similarly obtains the constraint deviation pattern calculation result shown in FIG. 14 from the main storage device 114 or the secondary storage device 115, and The facility demand management apparatus 100 is notified of the change of the device control parameter.

  FIG. 19 is a table showing an example of control parameter settings of the facility demand management apparatus. Here, the operating time is set as a control parameter for each equipment device of the facility. For example, assume that the restriction on the operating time of the device A is originally 9 (h). When the deviation amount 1 (h) is calculated as the constraint deviation pattern calculation result as shown in FIG. 14, the operating time restriction of the device A is changed to 10 (h), and the changed device restriction as shown in FIG. Information is transmitted to the facility demand management apparatus 100.

  In addition, in FIG. 17, the facility demand management apparatus having the control method ID 3 similarly obtains the constraint deviation pattern calculation result shown in FIG. 14 from the main storage device 114 or the secondary storage device 115. The employee's workable time in the time management system is automatically extended by one hour.

  FIG. 20 is a flowchart showing a facility device control flow in the facility demand management apparatus 100.

  Step S900 is processing performed in the communication unit 102 of the facility demand management apparatus 100. The facility demand management apparatus 100 is connected to the factory demand management apparatus 110 via the communication network 120, and data can be transmitted and received by the communication unit 102.

  In step S <b> 900, the facility demand management apparatus 100 receives facility equipment restriction information indicating restrictions on the operation of equipment equipment from the factory demand management apparatus 110 via the communication network 120. The acquired equipment device constraint information data is stored in the main storage device 104 or the secondary storage device 105. The equipment device restriction information is recorded, for example, in the same form as the control parameter setting of the equipment demand management apparatus shown in FIG.

  Step S901 is a process of changing the restriction of parameters for operating the equipment based on the equipment restriction information received in step S900. The restriction change may be automatically reflected in an internal setting parameter such as an operation time limit that is a restriction on an operation time that is a parameter of the facility device, or a manager of the facility demand management apparatus 100. The internal setting parameters of the equipment may be changed manually according to the operation restriction information displayed on the direct display screen.

  Step S902 is processing for operating the equipment according to the restrictions set in step S901. The equipment may be operated automatically according to the set restrictions, or may be manually operated according to the operation restriction information displayed on the display screen for the administrator of the facility demand management apparatus 100. Good.

  The present embodiment described above is organized as follows.

  The community management system according to the present embodiment restricts the community that uses the resource to operate the equipment and obtain the result of the operation of the equipment and restricts a plurality of parameters that include the resource usage and affect the cost of operating the community. It is a community management system that is established and managed.

  The community management system includes a constraint setting unit 216, a constraint deviation cost calculation unit 212, a supply and demand prediction unit 211, and a constraint relaxation item determination unit 214. The constraint setting unit 216 sets each constraint of parameters. The constraint departure cost calculation unit 212 calculates, for each parameter, a factor-by-factor unit departure amount cost that is a cost generated per unit departure amount when the constraint is deviated. The supply and demand prediction unit 211 predicts a future demand amount of resources for operating equipment and determines that a state in which a deviation from the constraint cannot be avoided occurs. When the constraint deviation cannot be avoided, the constraint relaxation item determination unit 214 determines which parameter constraint based on the total constraint departure cost, which is the total cost of operation at the time of community constraint departure, calculated from the factor-specific unit deviation cost. The constraint deviation pattern, which is a pattern of how much to relax and operate the equipment, is specified.

  As a result, the deviation of the constraint is allowed, and the constraint deviation pattern of how much the restriction of which parameter is relaxed is specified based on the total cost of the deviation of the deviation calculated from the unit deviation deviation cost for each factor. It is possible to appropriately manage the operation of the community operating the equipment by adjusting a plurality of parameters.

  In addition, the constraint setting unit 216 changes the constraint setting based on the constraint departure pattern identified by the constraint relaxation item determination unit 214. Since a new constraint is set based on the constraint departure pattern specified in the constraint departure total cost, it is possible to appropriately control the operation of the community.

  In addition, the constraint setting unit 216 sets constraints on parameters extracted in advance using a multivariate analysis method. Since the plurality of parameters extracted using the multivariate analysis method are appropriately adjusted, it is possible to appropriately manage the operation of the community operating the equipment.

  In addition, the constraint setting unit 216 subjects the parameters determined based on the degree of influence calculated as the degree to which the correlation between the parameters fluctuates the cost to the constraint relaxation. Since parameters determined in consideration of the degree to which the correlation between parameters affects the calculation accuracy of operating costs are subject to constraint relaxation, for example, changes in other parameters caused by changing certain parameters increase operating costs. In such a case, it is possible to keep the calculation accuracy of the operation cost at a certain level or more by excluding those parameters from the restriction relaxation target.

  In addition, the constraint setting unit 216 sets a composite parameter obtained by converting a parameter having an influence degree that the correlation between the parameters fluctuates as a cost to a predetermined value or more so as to be uncorrelated by component analysis, as a target of constraint relaxation. Since uncorrelated synthetic parameters can be used in place of a plurality of parameters having strong correlations, operational cost calculation errors are reduced, and community management is facilitated.

  Further, the constraint deviation cost calculation unit 212 calculates a unit deviation cost per factor corresponding to each of a plurality of values of the external environment, and the constraint relaxation item determination unit 214 calculates a factor corresponding to the measured value of the external environment. A constraint departure pattern is identified based on the total constraint departure cost calculated from each departure amount cost. Therefore, even when the cost generated for the unit deviation amount of the parameter changes due to a change in the external environment, it is possible to appropriately manage the operation of the community that operates the equipment.

  Further, the constraint departure cost calculation unit 212 calculates the unit-specific departure amount cost based on the operation results of other equipment similar to the equipment to be controlled. Since the factor deviation cost per factor is calculated based on the operation results of similar equipment, the community can be appropriately managed with the unit deviation cost per factor with high accuracy.

  In addition, the community management system further includes a determinant sensitivity analysis unit 213 that calculates the sensitivity to the cost for each parameter, and the constraint relaxation item determination unit 214 applies a parameter whose sensitivity is equal to or higher than a predetermined threshold to the constraint relaxation. set to target. By limiting only parameters that are highly sensitive to operating costs to be subject to constraint relaxation, the number of parameters can be reduced and calculation time can be shortened.

  Further, the community management system, for the constraint departure pattern identified by the constraint relaxation item determination unit 214, allows a parameter that allows the departure of the constraint, a departure amount that is an amount that deviates from the parameter constraint, and the parameter deviates from the constraint. There is further provided a constraint relaxation cost presentation unit 215 for presenting the constraint departure occurrence cost generated by the above and the constraint departure total cost at that time. Specifically, the constraint relaxation cost presenting unit 215 displays parameters that allow constraint departure, a deviation amount, a constraint departure occurrence cost, and a total constraint departure cost on the screen. Since the deviating parameter, the deviating amount, the generated cost, and the total amount of the entire operation cost are presented, it is possible to appropriately manage the parameter restrictions in the community operation based on them.

  A community is a factory that manufactures products as a result of the operation of equipment, and the parameters include the working hours of employees who operate the equipment. The costs incurred due to deviations in parameter constraints include additional allowances paid to employees. Thereby, the operation of the factory where the employee operates the equipment and manufactures the product can be appropriately managed.

  In addition, the community management system further includes a facility device control unit 202 that controls the facility device by setting parameters in the facility demand management apparatus 100 within the range of the constraints set by the constraint setting unit 216. Since the equipment is controlled by adjusting the parameter according to the constraint changed based on the specified constraint deviation pattern, the facility equipment in the community can be appropriately controlled when the parameter deviation is allowed.

  In addition, Example 1 demonstrated above is an example of embodiment of this invention, and this invention is not limited to this. In the practice of the present invention, deformation of the constituent elements and the like that do not depart from the scope of the invention are allowed. For example, in this embodiment, the setting range of the constraints by the community management system is within one factory, but it is also possible to integrate and manage the operation of the facilities of a plurality of factories and use them as a technique for setting the constraints at each factory. Is possible.

  In the present embodiment, the case where the present invention is applied to a building energy management system (BEMS) will be described. The basic configuration of the community management system of the present embodiment is the same as that of the community management system of the first embodiment described above, but there are some differences.

  The difference between the present embodiment and the first embodiment will be described with reference to FIGS.

  In this embodiment, the facility of the customer is not a production facility but a building contractor subject to energy management, for example, a tenant facility of a tenant manager in the building, and the equipment is equipment in each building and its related facilities. Specifically, air conditioning, lighting, etc.

  In this embodiment, the factory demand management apparatus shown in FIGS. 1 and 2 is changed to BEMS. The owner of the BEMS is an administrator who performs integrated management of building energy, for example, a BEMS aggregator. The BEMS is installed in the building or the related facility together with the equipment 106 and the like.

  In this embodiment, the BEMS aggregator and the customer have a demand response contract regarding the control of the customer equipment such as air conditioning. Control equipment directly or indirectly. Further, the constraint condition of the equipment (device) in the present embodiment indicates, for example, a settable temperature for air conditioning of the air conditioning equipment.

  The difference between the present embodiment and the first embodiment will be described with reference to FIG.

  In the present embodiment, when the constraint departure cost is calculated in step S301, the cost is calculated by including the increase in incentive provided to the customer, which is required when the constraint on the customer facility is changed.

  FIG. 21 is a graph illustrating an example of costs additionally generated in accordance with a change in temperature at which air conditioning can be set in the second embodiment. In this example, the current upper limit of the set temperature of each customer's air conditioning equipment that can be set by the BEMS aggregator is 26 ° C, and when the upper limit is changed to 27, 28 ° C, the additional generated cost in each case is 200. , 600. The generated cost due to the change in the upper limit temperature of the air conditioning is determined based on, for example, additional generated incentive information determined when a demand response contract with a customer is made.

  FIG. 22 is a graph illustrating an example of costs additionally generated in association with a change in temperature at which air conditioning can be set when there are a plurality of consumers in the second embodiment. When there are a plurality of customers participating in the demand response program, as shown in FIG. 22, a constraint deviation cost is defined for each customer according to the contract contents of the customer, and the data is retained. Also good.

  At this time, for example, the BEMS aggregator can specify the current constraint range for each factor, the constraint deviation cost per unit deviation amount, and the constraint deviation setting range on an input screen as shown in FIG.

  FIG. 23 is an example of a constraint departure cost definition table in the second embodiment. For each factor, the external environmental condition, the unit deviation w, and the generated cost for each multiple of the unit deviation are shown. In step S302, for example, a constraint deviation cost definition table as shown in FIG. 23 is registered.

  The difference between the present embodiment and the first embodiment will be described with reference to FIG.

  FIG. 24 is a diagram illustrating an example of information displayed on the screen in the BEMS according to the second embodiment. In step S <b> 402, as the constraint departure pattern and the constraint departure total cost, the factor for performing the constraint change, the deviation amount for each factor, the generation cost due to the deviation, and the total generation cost due to the constraint departure are presented. For example, as shown in FIG. 24, the air conditioning settable temperature of each consumer, which is a factor for changing the constraint, is presented, the deviation amount for each factor and the cost generated by the deviation are presented, and the total due to the constraint deviation is further presented. Present the incurred cost.

  The configuration of the community management system other than that described above is the same as that of the first embodiment. According to the community management system according to the present embodiment, it is possible to perform scheduling of an appropriate business plan for supply and demand adjustment in a building or a related facility with the same configuration as in the first embodiment.

  Further, in the present embodiment, the constraint relaxation item determination unit 214 of the BEMS includes an incentive to be provided to a customer who cooperates in resource supply and demand adjustment in the constraint deviation total cost. Since total costs including incentives can be optimized, it is possible to appropriately manage the operation of a community that operates equipment that can adjust the supply and demand of resources.

  The above-described embodiments of the present invention are examples for explaining the present invention, and are not intended to limit the scope of the present invention only to those embodiments. Those skilled in the art can implement the present invention in various other modes without departing from the gist of the present invention.

DESCRIPTION OF SYMBOLS 100 ... Facility demand management apparatus, 101 ... CPU, 102 ... Communication part, 103 ... Input / output part, 104 ... Main storage apparatus, 105 ... Secondary storage apparatus, 106 ... Equipment apparatus, 110 ... Factory demand management apparatus, 111 ... CPU , 112 ... Communication unit, 113 ... Input / output unit, 114 ... Main storage device, 115 ... Secondary storage device, 120 ... Communication network, 201 ... Demand measurement unit, 202 ... Equipment device control unit, 210 ... Demand monitoring unit, 211 Demand supply / demand prediction unit 212 Constraint restriction deviation calculation unit 213 Determinant sensitivity analysis unit 214 Constraint relaxation item determination unit 215 Constraint relaxation cost presentation unit 216 Constraint setting unit

Claims (13)

Community management for managing a facility that operates a facility device by using a resource and obtains a result of the operation of the facility device by restricting a plurality of parameters that include the resource usage amount and affect the cost of operation of the community A system,
A constraint setting unit for setting the constraint for each of the parameters;
For each parameter, a constraint deviation cost calculation unit that calculates a unit deviation amount cost per factor that is a cost generated per unit deviation amount when deviating from the constraint;
A demand-and-supply prediction unit that predicts a future demand amount of the resource for the operation of the facility equipment, and determines that a state in which a deviation from the constraint cannot be avoided occurs;
When the deviation of the constraint cannot be avoided, the restriction of which parameter is relaxed and how much based on the total cost of deviation of the constraint, which is the total cost of operation at the time of deviation of the community restriction calculated from the unit deviation amount cost for each factor. A constraint relaxation item determination unit that identifies a constraint deviation pattern that is a pattern of whether to operate the facility equipment;
Having community management system.   The community management system according to claim 1, wherein the constraint setting unit changes the setting of the constraint based on the constraint departure pattern specified by the constraint relaxation item determination unit.   The community management system according to claim 1, wherein the constraint setting unit sets the constraint on the parameter extracted in advance using a multivariate analysis method.   The community management system according to claim 1, wherein the constraint setting unit targets a parameter that is determined based on an influence degree calculated as a degree that the correlation between parameters varies the cost.   The constraint setting unit is subject to constraint relaxation for a composite parameter obtained by converting a parameter having an influence degree that causes a correlation between the parameters to fluctuate the operation cost to be uncorrelated by component analysis. The community management system according to claim 4. The constraint deviation cost calculating unit calculates a unit-specific deviation amount cost according to each of a plurality of values of the external environment,
The constraint relaxation item determination unit identifies the constraint departure pattern based on the total constraint departure cost calculated from the factor deviation cost according to the measured value of the external environment.
The community management system according to claim 1.   2. The community management system according to claim 1, wherein the constraint departure cost calculation unit calculates the unit-specific departure cost for each factor based on operation results of other equipment similar to the equipment. A determinant sensitivity analysis unit for calculating a sensitivity to the cost by the parameter for each parameter;
The community management system according to claim 1, wherein the constraint relaxation item determination unit sets a parameter whose sensitivity is equal to or higher than a predetermined threshold as a target of constraint relaxation. With respect to the constraint departure pattern identified by the constraint relaxation item determination unit, a parameter that allows the departure of the constraint, a departure amount that is an amount that deviates from the constraint of the parameter, and the parameter deviates from the constraint A constraint relaxation cost presentation unit that presents the constraint departure occurrence cost to be generated and the constraint departure total cost at that time;
The community management system according to claim 1.   10. The community management according to claim 9, wherein the constraint relaxation cost presentation unit displays a parameter allowing the constraint departure, the departure amount, the constraint departure occurrence cost, and the constraint departure total cost on a screen. system. The community is a factory that manufactures products as a result of the operation of the equipment.
The parameter includes working hours of an employee who operates the equipment, the constraint on the working time is workable time, and the cost caused by the deviation from the constraint on the parameter is for the employee Including additional benefits to pay,
The community management system according to claim 1. A facility device control unit configured to control the facility device by setting the parameter within the range of the constraint set by the constraint setting unit;
The community management system according to claim 2. The constraint relaxation item determination unit includes an incentive to be provided to a customer who cooperated in supply and demand adjustment of the resource in the total cost of deviation from the constraint.
The community management system according to claim 1.

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