Source: https://patents.google.com/patent/JP5990117B2/en
Timestamp: 2020-01-17 20:28:59
Document Index: 31711046

Matched Legal Cases: ['art 131', 'art 131', 'art 133', 'art 230', 'art 233', 'art 233']

JP5990117B2 - Control method, control server, and control program - Google Patents
Control method, control server, and control program Download PDF
JP5990117B2
JP5990117B2 JP2013042074A JP2013042074A JP5990117B2 JP 5990117 B2 JP5990117 B2 JP 5990117B2 JP 2013042074 A JP2013042074 A JP 2013042074A JP 2013042074 A JP2013042074 A JP 2013042074A JP 5990117 B2 JP5990117 B2 JP 5990117B2
JP2013042074A
JP2014171330A (en
仁史 屋並
秀直 岩根
穴井　宏和
宏和 穴井
辰次 原
2013-03-04 Application filed by 富士通株式会社, 国立大学法人 東京大学, 国立大学法人 東京大学 filed Critical 富士通株式会社
2013-03-04 Priority to JP2013042074A priority Critical patent/JP5990117B2/en
2014-09-18 Publication of JP2014171330A publication Critical patent/JP2014171330A/en
2016-09-07 Publication of JP5990117B2 publication Critical patent/JP5990117B2/en
The present invention relates to a control method and the like.
In recent years, companies are required to suppress peak power, which is the maximum value of demand power, due to concerns about power supply caused by the Great East Japan Earthquake. For example, as a conventional technique for suppressing peak power, there is a technique that uses each battery of a plurality of notebook PCs (Personal Computers) in the company. This conventional technology predicts a power demand curve and notebook battery remaining data from information such as past power consumption transitions and weather forecasts, and creates a notebook PC battery charge / discharge plan based on the demand curve. To do. Then, the conventional technology performs control for switching the driving mode of the notebook PC to any one of battery driving, AC (Alternate Current) driving, and battery charging while AC driving based on the charging / discharging plan.
JP 2012-161202 A JP 2011-254617 A
However, the above-described conventional technique has a problem that a charge / discharge plan cannot be created in a short processing time.
For example, when the scale of the system is large, charging and discharging each laptop battery in the company is planned for each time period, and it takes a huge amount of processing to create an optimal charging / discharging plan by simulation. I need it.
In one aspect, the present invention has been made in view of the above, and an object thereof is to provide a control method, a control server, and a control program capable of creating a charge / discharge plan even with a short processing time.
In the first plan, the computer executes the following processing. The computer, based on the remaining amount of the storage battery of the plurality of devices, the distribution of the remaining amount of the storage battery of the plurality of devices included in the group and the distribution of the remaining amount of the storage battery of the plurality of devices included in the other group. Equally classify multiple devices into multiple groups. A computer produces | generates the virtual control plan which switched the state of some apparatuses with respect to the control plan which prescribed | regulated the state regarding charging / discharging for every time slot | zone of each apparatus provided with the storage battery for every group. For each group, the computer simulates power demand for each time zone using a virtual control plan. For each group, if the simulated result is better than the simulation result of the control plan, the control plan is updated to a virtual control plan. The computer outputs a control plan if the end condition indicating whether a predetermined time has passed or not, and if the end condition is not satisfied, the computer repeatedly executes a process for updating the control plan until the end condition is satisfied. Let
According to one embodiment of the present invention, there is an effect that a charge / discharge plan can be created in a short processing time.
FIG. 1 is a diagram illustrating the configuration of the system according to the first embodiment. FIG. 2 is a diagram for explaining a state relating to charging / discharging of the storage battery of the notebook PC. FIG. 3 is a diagram illustrating the configuration of the control server according to the first embodiment. FIG. 4 is a diagram illustrating an example of demand forecast data. FIG. 5 is a diagram illustrating an example of the PC information table. FIG. 6 is a diagram illustrating an example of charging data. FIG. 7 is a diagram illustrating an example of discharge data. FIG. 8 is a diagram illustrating an example of the control plan table. FIG. 9 is a diagram for explaining the processing of the classification unit according to the first embodiment. FIG. 10 is a diagram illustrating an example of the classification result according to the first embodiment. FIG. 11 is a diagram for explaining processing of the power calculation unit according to the first embodiment. FIG. 12 is a diagram (1) for explaining the process of the generation unit according to the first embodiment. FIG. 13 is a diagram (2) for explaining the process of the generation unit according to the first embodiment. FIG. 14 is a diagram (3) for explaining the process of the generation unit according to the first embodiment. FIG. 15 is a diagram for explaining the process of the simulation unit according to the first embodiment. FIG. 16 is a flowchart illustrating the processing procedure of the control server according to the first embodiment. FIG. 17 is a flowchart of the process procedure of the control plan generation process according to the first embodiment. FIG. 18 is a diagram illustrating the configuration of the system according to the second embodiment. FIG. 19 is a diagram illustrating the configuration of the control server according to the second embodiment. FIG. 20 is a diagram illustrating an example of the first control plan table. FIG. 21 is a diagram for explaining the processing of the classification unit according to the second embodiment. FIG. 22 is a diagram illustrating an example of the classification result according to the second embodiment. FIG. 23 is a diagram (1) for explaining the process of the generation unit according to the second embodiment. FIG. 24 is a diagram (2) for explaining the process of the generation unit according to the second embodiment. FIG. 25 is a diagram (3) illustrating the process of the generation unit according to the second embodiment. FIG. 26 is a flowchart illustrating the processing procedure of the control server according to the second embodiment. FIG. 27 is a diagram illustrating an example of a computer that executes a control program.
Hereinafter, embodiments of a control method, a control server, and a control program disclosed in the present application will be described in detail with reference to the drawings. Note that the present invention is not limited to the embodiments.
A configuration of the system according to the first embodiment will be described. FIG. 1 is a diagram illustrating the configuration of the system according to the first embodiment. As shown in FIG. 1, the system includes a distribution board 20, notebook PCs (Personal Computers) 30 a, 30 b, 30 c, an illumination 50 a, a multi-function device 50 b, and a control server 100. Distribution board 20, notebook PCs 30 a, 30 b, 30 c and control server 100 are connected to each other via network 10. In addition, the distribution board 20, the notebook PCs 30 a, 30 b, 30 c, the illumination 50 a, and the multifunction device 50 b are connected to the power line 40.
The network 10 corresponds to, for example, an in-house LAN (Local Area Network). As the in-house LAN, an arbitrary type of communication network such as a wired LAN or a wireless LAN may be adopted and connected to another network such as the Internet or a LAN.
In the example illustrated in FIG. 1, the case where the notebook PCs 30 a, 30 b, and 30 c are connected to the control server 100 is illustrated, but the configuration is not limited to the illustrated configuration. For example, an arbitrary number of notebook PCs may be connected to the control server 100.
In the example illustrated in FIG. 1, a case where the notebook PCs 30 a, 30 b, 30 c, the illumination 50 a, and the multifunction device 50 b are connected to the power line 40 is illustrated, but the configuration is not limited to the illustrated configuration. That is, any electrical product may be connected to the power line 40. For example, electrical products such as a television, a refrigerator, and a microwave oven are connected to the power line 40. Hereinafter, when the illumination 50a, the multi-function device 50b, and other electric products are collectively referred to without distinction, they are referred to as an electric product 50. The electrical product 50 includes, for example, any product that consumes electric power in the company.
The control server 100 is a server device installed in the company, and creates a control plan that defines charging / discharging of batteries of a plurality of notebook PCs.
The distribution board 20 supplies power to the notebook PCs 30a, 30b, 30c, the illumination 50a, and the multi-function device 50b through the power line 40.
The notebook PCs 30a, 30b, and 30c are notebook personal computers used by users in the company. In the following description, the notebook PCs 30a, 30b, and 30c are appropriately described as “notebook PC30” or simply “PC”.
The notebook PC 30 is installed with a client application that controls charging / discharging of a storage battery mounted on the notebook PC 30. For example, the notebook PC 30 receives a control plan that defines a state related to charging / discharging of the storage battery of the own device from the control server 100, and switches the state related to charging / discharging of the storage battery of the own device according to the received control policy. The notebook PC 30 is an example of a device. Further, the storage battery of the notebook PC is also referred to as “battery” as appropriate.
Here, the state regarding charge / discharge of the storage battery of the notebook PC 30 will be described. FIG. 2 is a diagram for explaining a state relating to charging / discharging of the storage battery of the notebook PC. In FIG. 2, the horizontal axis indicates time, and the vertical axis indicates power value [W]. For example, in the time zones 2a and 2d, the storage battery is not charged / discharged, and the notebook PC 30 is operating with an AC (Alternating Current) power source. This state is also referred to as “AC”. Further, for example, in the time zone 2b, a state is shown in which the notebook PC 30 is operating by discharging the storage battery. This state is also referred to as “BA”. Further, for example, in the time zone 2c, a state in which the notebook PC 30 is operating with an AC power supply while the storage battery is being charged is shown. This state is also referred to as “CH”. As shown in FIG. 2, the notebook PC 30 operates in a state of “AC”, “BA”, or “CH”. For example, when the notebook PC 30 receives from the control server 100 a control plan indicating that it operates at “BA” during the time zone “9:00 to 9:30”, it operates at “BA” during the designated time zone.
Next, the configuration of the control server 100 shown in FIG. 1 will be described. FIG. 3 is a diagram illustrating the configuration of the control server according to the first embodiment. As illustrated in FIG. 3, the control server 100 includes a communication control unit 110, a storage unit 120, and a control unit 130.
The communication control unit 110 is a processing unit that transmits and receives data between the distribution board 20 and the notebook PC 30. The communication control unit 110 corresponds to, for example, a network interface card (NIC). The control unit 130 described later exchanges data with the distribution board 20 and the notebook PC 30 via the communication control unit 110.
The storage unit 120 includes demand prediction data 121, a PC information table 122, charge data 123, discharge data 124, and a control plan table 125. The storage unit 120 corresponds to a storage device such as a semiconductor memory element such as a random access memory (RAM), a read only memory (ROM), and a flash memory.
The demand forecast data 121 is time series data of demand power predicted in the system. For example, the demand prediction data 121 is data in which each time zone in a day is associated with a demand power value. This power demand value is calculated from statistical data of past power consumption values, for example.
FIG. 4 is a diagram illustrating an example of demand forecast data. The horizontal axis in FIG. 4 indicates time, and the vertical axis indicates power value [kW]. FIG. 4 illustrates daily demand forecast data 121 in the company. For example, the demand prediction data 121 is calculated from statistical data of past power consumption values consumed by any product that consumes power in the company. Although FIG. 4 shows the case where the demand forecast data 121 is one pattern, the present invention is not limited to this. For example, the demand forecast data 121 may have a plurality of patterns when there is a difference in day of the week and time, and a plurality of transition methods are predicted.
The PC information table 122 holds, for example, various types of information regarding the notebook PC 30. FIG. 5 is a diagram illustrating an example of the PC information table. As shown in FIG. 5, the PC information table 122 associates “ID”, “observability”, “control availability”, “state”, “battery capacity”, and “charge rate”. Remember.
In FIG. 5, ID indicates ID (Identification) that uniquely identifies the notebook PC 30 in the company. The observation availability indicates whether or not the control server 100 can observe the corresponding notebook PC 30. For example, the observation availability “o” indicates that the control server 100 can observe the corresponding notebook PC 30, that is, the corresponding notebook PC 30 is connected to the in-house LAN 10. Further, for example, the observation availability “x” indicates that the control server 100 has not observed the corresponding notebook PC 30, that is, the corresponding notebook PC 30 is not connected to the in-house LAN 10.
In FIG. 5, controllability indicates whether or not the corresponding notebook PC 30 is connected to the power line 40. For example, control availability “o” indicates that the corresponding notebook PC 30 is connected to the power line 40. Further, for example, the control availability “x” indicates that the corresponding notebook PC 30 is not connected to the power line 40.
The state indicates the current state of the corresponding notebook PC 30. For example, the state “AC” indicates a state in which the storage battery is not charged / discharged and the notebook PC is operating with an AC power source. Further, for example, the state “BA” indicates a state in which the notebook PC is operating due to the storage battery being discharged. Further, for example, the state “CH” indicates a state in which the storage battery is charged and the notebook PC is operating with an AC power source. The battery capacity indicates a power capacity [Wh] determined as a battery specification of the corresponding notebook PC 30. The charging rate indicates the current charging rate [%] of the corresponding notebook PC 30. In the PC information table 122, for example, a notebook PC 30 used in the company is registered in advance. In addition, “-” in the figure indicates that there is no corresponding data.
As shown in FIG. 5, for example, the PC information table 122 includes an ID “PC1”, an observation availability “o”, a control availability “o”, a state “AC”, a battery capacity “65”, and a charging rate. “80” is stored in association with each other. That is, it shows that the PC 1 is connected to the network 10 and the power line 40 and is operating with an AC power source, the battery capacity is 65 [Wh], and the current charging rate is 80%. Similarly, the PC information table 122 stores information for other notebook PCs 30.
Returning to the description of FIG. The charging data 123 is data indicating a change in charging rate when charging a battery, for example. For example, the charging data 123 is data in which a charging rate and time when charging the battery of the notebook PC 30 are associated with each other. The charging data 123 is determined as battery specifications. The charging data 123 may be calculated from the stored data by storing the charging rate for each time when the battery of the notebook PC 30 is charged.
FIG. 6 is a diagram illustrating an example of charging data. The horizontal axis of FIG. 6 shows time [second], and a vertical axis | shaft shows charging rate [%]. FIG. 6 illustrates the charging rate when charging the battery of the notebook PC 30. Here, for convenience of explanation, the charging data 123 of the battery mounted on a certain notebook PC 30 is shown, but the charging data 123 is stored for each notebook PC 30. For example, the charging data 123 is stored in association with each ID of the notebook PC 30.
Returning to the description of FIG. For example, the discharge data 124 is data indicating a change in the charging rate when the battery is discharged. For example, the discharge data 124 is data in which the charging rate and time when discharging the battery of the notebook PC 30 are associated with each other. The discharge data 124 is determined as battery specifications. The discharge data 124 may be calculated from the stored data by storing the charging rate for each time when the battery of the notebook PC 30 is discharged.
FIG. 7 is a diagram illustrating an example of discharge data. The horizontal axis of FIG. 7 shows time [second], and a vertical axis | shaft shows charging rate [%]. FIG. 7 illustrates the charging rate when discharging the battery of the notebook PC 30. Here, for convenience of explanation, the discharge data 124 of the battery mounted on a certain notebook PC 30 is shown, but the discharge data 124 is stored for each notebook PC 30. For example, the discharge data 124 is stored in association with each ID of the notebook PC 30.
Returning to the description of FIG. The control plan table 125 holds information on a control plan that defines charging / discharging of each storage battery for each time zone. FIG. 8 is a diagram illustrating an example of the control plan table. As shown in FIG. 8, the control plan table 125 stores IDs and time zones every 30 minutes in association with each other. For example, the time zone “9:00” corresponds to the time zone from 9 o'clock to 9:30. One record of the control plan table 125 corresponds to the control policy of the corresponding notebook PC 30.
As shown in FIG. 8, the control plan table 125 includes, for example, an ID “PC1”, 9 o'clock to 11:30 “AC”, 11:30 to 12:30 “CH”, and 12:30 to 13:00. The half “BA” is stored in association with each other. That is, in the control plan table 125, the PC 1 operates with an AC power source from 9:00 to 11:30, operates while charging the storage battery from 11:30 to 12:30, and stores the storage battery from 12:30 to 13:30. Memorize that it is discharged and operating. Similarly, the control plan table 125 stores the state for each time zone for the other notebook PCs 30. Although the case where the control plan table 125 defines the state of the notebook PC 30 every 30 minutes has been described here, the present invention is not limited to this. For example, the control plan table 125 may define the state of the notebook PC 30 every 10 minutes.
The control unit 130 includes an acquisition unit 131, a measurement unit 132, a creation unit 133, and an output unit 134. The control unit 130 corresponds to an integrated device such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The control unit 130 corresponds to an electronic circuit such as a CPU or MPU (Micro Processing Unit).
The acquisition unit 131 is a processing unit that acquires information on each part of the notebook PC 30 and registers the acquired information in the PC information table 122. In addition, the timing which the acquisition part 131 acquires information may set arbitrary timings by the person using the control server 100. For example, the acquisition unit 131 may acquire information immediately before the creation unit 133 described later creates a control plan.
The process of the acquisition part 131 is demonstrated using FIG. For example, the acquisition unit 131 acquires information indicating that the state of the PC 2 is “CH”, the charging rate is “50%”, and is connected to the power line 40 from the PC 2. The acquisition unit 131 records the acquired information in the PC information table 122 of FIG. For example, the acquisition unit 131 records control availability “o”, state “CH”, and charge rate “50” in the PC information table 122 in association with the PC 2. Further, since the acquisition unit 131 has acquired information from the PC 2, the acquisition unit 131 determines that the PC 2 is connected to the in-house LAN 10 and records the observation availability “◯” in the PC information table 122. Further, for example, the acquisition unit 131 determines that a PC from which information cannot be acquired is not connected to the in-house LAN 10, and records the observation availability “x” in the PC information table 122. For example, the acquisition unit 131 determines that the PC 3 is not connected to the in-house LAN 10 when the information of the PC 3 cannot be acquired at the timing of acquiring information about other PCs, and sets the observation availability “x” to the PC information table. 122.
The measuring unit 132 measures the power consumed in the system of FIG. For example, the measurement unit 132 measures the total amount of power consumed in the company by the electrical product connected to the power line 40. The measurement unit 132 records information on the measured power amount in the storage unit 120. Illustration of power information stored in the storage unit 120 is omitted. Any conventional technique can be applied to the method in which the measuring unit 132 measures the power consumed in the company. For example, the measuring unit 132 may measure the amount of power supplied by the distribution board 20 via the power line 40 and acquire the measured power amount from the distribution board 20. For example, the measurement unit 132 may measure the amount of power supplied from all the outlets in the company and calculate the sum.
The creation unit 133 is a processing unit that classifies each notebook PC 30 into a plurality of groups based on the remaining capacity of the storage battery, and then executes a local search method for each group to create a control plan. The creation unit 133 includes a classification unit 133a, a power calculation unit 133b, a generation unit 133c, a simulation unit 133d, an update unit 133e, and an execution unit 133f.
The classification unit 133a is a processing unit that classifies the notebook PCs 30 into a plurality of groups based on the remaining amount of the storage battery. In the classification unit 133a, the total value (or distribution) of the remaining amount of the storage battery of the notebook PC 30 included in a certain group is similar to the total value of the remaining amount of the storage battery of the plurality of notebook PCs 30 included in the other group. As described above, a plurality of devices are classified into a plurality of groups. In the first embodiment, as an example, the number of notebook PCs included in each group is the same. Note that the remaining amount of the storage battery corresponds to a value recorded in the PC information table 122 that is obtained by multiplying the battery capacity by the charging rate.
FIG. 9 is a diagram for explaining the processing of the classification unit according to the first embodiment. In FIG. 9, for convenience of explanation, only the storage battery built in each notebook PC is shown, and the illustration of the notebook PC 30 is omitted. For example, let the storage batteries 1a-1x be the storage batteries incorporated in the notebook PCs 30a-30x, respectively. It is assumed that the storage battery has more remaining capacity as the storage battery has more shaded portions. The classification unit 133a rearranges the storage batteries 1a to 1x in order from the one with the smallest remaining amount. For storage batteries having the same remaining amount, either may be arranged first.
For example, when the classification unit 133a rearranges the storage batteries 1a to 1x, the storage batteries are in the order of decreasing remaining capacity, 1h, 1l, 1e, 1q, 1s, 1m, 1u, 1p, 1w, 1j, 1o, 1x, 1g. , 1d, 1i, 1b, 1t, 1n, 1v, 1r, 1a, 1c, 1k, 1f.
Subsequently, the classification unit 133a classifies the storage batteries 1h, 1x, 1g, and 1f into the group 2A. That is, the group 2A includes notebook PCs 30h, 30x, 30g, and 30f. The classification unit 133a classifies the storage batteries 11, 1o, 1d, and 1k into the group 2B. That is, the group 2B includes notebook PCs 301, 30o, 30d, and 30k. The classification unit 133a classifies the storage batteries 1e, 1j, 1i, and 1c into the group 2C. That is, the group 2C includes notebook PCs 30e, 30j, 30i, and 30c.
The classification unit 133a classifies the storage batteries 1q, 1w, 1b, and 1a into the group 2D. That is, the group 2D includes notebook PCs 30q, 30w, 30b, and 30a. The classification unit 133a classifies the storage batteries 1s, 1p, 1t, and 1r into the group 2E. That is, the group 2E includes notebook PCs 30s, 30p, 30t, and 30r. The classification unit 133a classifies the storage batteries 1m, 1u, 1n, and 1v into the group 2F. That is, the group 2F includes notebook PCs 30m, 30u, 30n, and 30v.
As described above, the classification unit 133a classifies the notebook PCs 30a to 30x into the groups 2A to 2F, thereby obtaining a value similar to the total value of the remaining amount of the storage batteries of the notebook PC 30 included in each group. The classification unit 133a outputs the classification result information to the generation unit 133c, the simulation unit 133d, and the update unit 133e. FIG. 10 is a diagram illustrating an example of the classification result according to the first embodiment. As shown in FIG. 10, this classification result associates group identification information that uniquely identifies a group with an ID group. The ID group includes an ID that uniquely identifies each notebook PC 30 included in the group. For example, the IDs of the notebook PCs 30a to 30x are PC1 to PC24, respectively.
In FIG. 10, for example, the ID group corresponding to the group identification information “group 2A” is “PC8, PC24, PC7, PC6”. That is, the group 2A includes notebook PCs 30h, 30x, 30g, and 30f.
Returning to the description of FIG. The power calculation unit 133b is a processing unit that calculates the power allocated to each group classified by the classification unit 133a. For example, the power calculation unit 133b calculates the value of power allocated to each group based on the formula (1). The peak power predicted value shown in Expression (1) is the peak power predicted value of the entire system excluding the power consumption of the notebook PC 30. The current power consumption is the current power consumption of the entire system excluding the power consumption of the notebook PC 30. The power calculation unit 133b outputs information on the power allocated to each group to the simulation unit 133d.
Power allocated to each group = (peak power predicted value−current power consumption) / number of groups (1)
Next, the process of the power calculation unit 133b will be described in more detail. More specifically, the power calculation unit 133b calculates the power that can be used by the notebook PC 30 in each time period by solving the optimization problem shown in Expression (2). However, the conditions of formulas (3), (4), and (5) shall be satisfied. In Expressions (2) to (5), “k” is a variable indicating each time zone. FIG. 11 is a diagram for explaining processing of the power calculation unit according to the first embodiment. In FIG. 11, the horizontal axis indicates time, and the vertical axis indicates power value. The line segment 5a shows the predicted value of the demand power value in each time zone excluding the power of the notebook PC 30. The line segment 5b is the maximum predicted value of the demand power value excluding the power of the notebook PC 30, and corresponds to Dmax . u [k] is a total value of the power allocated to all the notebook PCs 30 in the time zone k. D [k] is a predicted value of the demand power value excluding the power of all the notebook PCs 30 in the time zone k. Note that a time zone in which the predicted value of the demand power value is the maximum value is k ′.
minΣu [k] (2)
u [k] ≦ D max −D [k] (3)
D [k-1] + u [k-1] (4)
Here, equation (2) is an optimization problem of minimizing the area of the shaded portion in FIG. Expression (3) is a conditional expression for preventing the power allocated to the notebook PC 30 in the time zone immediately before a certain time zone k from exceeding the maximum value of the demand power. Equation (4) is a condition that the sum of u [k] and D [k] gradually increases. Equation (5) indicates that the average remaining amount of the storage battery of the notebook PC 30 is equal to or greater than the predetermined value τ in the time zone immediately before the time zone k ′. Thereby, before it becomes the maximum value of the predicted value of the demand power value excluding the power of the notebook PC 30, the average remaining amount of the storage battery of the notebook PC 30 can be made equal to or greater than the predetermined value τ.
The power calculation unit 133b solves the optimization problem of Equation (2), calculates u [k] for each time slot, and divides u [k] by the number of groups, thereby assigning each group in each time slot. The power to be allocated is calculated, and the calculated power information is output to the simulation unit 133d.
The generation unit 133c is a processing unit that creates a control plan in units of groups classified by the classification unit 133a. First, an initial control plan is generated by setting a state for each notebook PC 30 in the control plan table 125 for each time period. FIG. 12 is a diagram (1) for explaining the process of the generation unit according to the first embodiment. In FIG. 12, as an example, only PCs 8, 24, 7, and 6 included in the group 2A among the records included in the control information table 125 are shown. As illustrated in FIG. 12, for example, the generation unit 133 c refers to the PC information table 122 and sets the state “AC” for all time zones of the controllable PC. Further, the generation unit 133c refers to the PC information table 122, and sets the state “UN1” for all time zones of the unobservable PC.
Further, the generation unit 133c refers to the PC information table 122, and sets the state “UN2” for all time zones of the PC that can be observed but cannot be controlled. Although the case where the state “AC” is set for all the time zones of the controllable PC has been described here, the present invention is not limited to this. For example, the state “BA” may be set for all time zones of the controllable PC. Further, for example, the state of each time zone of the notebook PC 30 of the control plan that has already been created may be set to each time zone of the corresponding notebook PC 30.
Here, “UN1” and “UN2” will be described. “UN1” indicates a state assumed for an unobservable PC. For example, “UN1” is set as an imaginary state in which the charging rate of the storage battery decreases in a discharged state and uses electric power in a charged state. This is because the storage battery of the notebook PC 30 that cannot be observed is discharged while it is not observed. In addition, it is considered that the notebook PC 30 that cannot be observed is connected to the in-house power supply line 40 and the demand power is increased. “UN2” indicates a state assumed for an uncontrollable PC. For example, “UN2” is set as an imaginary state in which the charge rate of the storage battery decreases in a discharged state and uses power in a state where the battery is operating with an AC power source. This is because the uncontrollable notebook PC 30 is connected to the in-house power line 40 to increase the power demand.
Further, the generation unit 133c selects an arbitrary time zone of the notebook PC 30 that can be controlled by the generated control plan, and switches the state to any one of “AC”, “BA”, and “CH”. This is referred to as a “switching instruction”. FIG. 13 is a diagram (2) for explaining the process of the generation unit according to the first embodiment. FIG. 13 (1) shows an example of the control plan table 125 before switching, and FIG. 13 (2) shows an example of the control plan table 125 after switching. As illustrated in FIG. 13, for example, the generation unit 133 c selects “9:30” of the PC 24. The generation unit 133c switches the state of the selected time zone and the subsequent time zones to “BA”. The shaded area in FIG. 13 indicates the time zone of the PC for which a switching instruction has been issued. In addition, the generation unit 133c records the time zone of the PC for which the switching instruction is issued in the control plan table 125.
In addition, when switching the state, the generation unit 133c switches the state until a switching instruction is issued after the next time period. FIG. 14 is a diagram (3) for explaining the process of the generation unit according to the first embodiment. FIG. 14A shows an example of the control plan table 125 before switching, and FIG. 14B shows an example of the control plan table 125 after switching. FIG. 14 illustrates a case where a switched state exists. In FIG. 14A, a case where there is an instruction to switch the state “BA” of “12:30” of the PC 8 will be described. As illustrated in FIG. 14, for example, the generation unit 133 c selects “11:30” of the PC 8 and issues a “switching instruction” for switching to “CH”. The generation unit 133c switches the state of the selected subsequent time zone to “CH”. In this case, since there is an instruction to switch the state “BA” of “12:30” of the PC 8, the generation unit 133a switches the state up to “12:00” to “CH”.
The generation unit 133c executes the above process for each group, and outputs control plan information for each group to the simulation unit 133d.
Returning to the description of FIG. The simulating unit 133d is a processing unit that simulates the demand power for each time zone using the control plan for each group generated by the generating unit 133c. For example, the simulation unit 133d simulates the demand power by subtracting the power usage amount by the notebook PC 30 from the demand prediction data 121 and adding the power usage amount when the notebook PC 30 operates according to the control plan. The simulation unit 133d simulates demand power for each group. The simulating unit 133d outputs the simulation result for each group to the updating unit 133e.
FIG. 15 is a diagram for explaining the process of the simulation unit according to the first embodiment. The horizontal axis in FIG. 15 indicates time, and the vertical axis indicates power value [kW]. FIG. 15 shows a simulation result when a control plan is created at intervals of 10 minutes from 8:00 to 20:00. As shown in FIG. 15, for example, the simulation unit 133d simulates demand power every 10 minutes based on the control plan, and calculates a post-control peak 11a every 10 minutes. For example, the simulating unit 133d calculates the post-control peak max j for each time period using the following equation (6). 11b corresponds to the demand forecast data 121 in FIG.
max j (demand forecast [j] −Σ i E Ai + Σ i E si [j] ) (6)
In equation (6), i represents the index of the notebook PC 30. j represents a time zone index. For example, j = 1 corresponds to the time zone from 9 o'clock to 9:30. The demand forecast [j] indicates a demand forecast value in the j-th time zone, and is a value given from the demand forecast data 121, for example. E si [j] indicates the power value of each state in the j-th time zone of the i-th notebook PC 30. For example, power usage E A state "AC" is, for example, 10 [W]. The power values E B state "BA" is, for example, 0 [W]. Further, the power value E C of the state “CH” is, for example, 60 [W]. Further, the power usage amount E U1 in the state “UN1” is E C [W] because the power used in the state “CH” is used. In addition, the power consumption E U2 state "UN2" is E A [W] because it uses power when the state "AC". E Ai indicates the amount of power used in the state “AC” of the i-th notebook PC 30. In addition, said Formula (6) is an example, and is not limited to this. For example, Σ i E Ai does not have to be subtracted when controlling with more margin.
Further, the simulation unit 133d simulates demand power for each time zone by adding a constraint condition to the control plan. For example, the simulation unit 133d calculates the charging rate of the storage battery in each time zone for each notebook PC 30. For example, the simulating unit 133b refers to the PC information table 122 and acquires the charging rate of the notebook PC 30. When the storage battery of the notebook PC 30 is charged for a certain time, the simulation unit 133b refers to the charging data 123 of FIG. 6 and estimates the charging rate after the lapse of time. When discharging from the storage battery of the notebook PC 30 for a certain time, the simulating unit 133d refers to the discharge data 124 in FIG. 7 and estimates the charge rate after the lapse of time.
And the simulation part 133b determines whether the estimated charge rate satisfy | fills the conditions of Formula (7), and satisfy | fills Formula (8). The constraint condition of Expression (7) is “the charge amount becomes maximum at the final time k ″”. C i in Expression (7) represents the electric capacity of the i-th notebook PC 30. N in Expression (8) is the number of groups classified by the classification unit 133a. Note that the constraint conditions and numerical values described here are merely examples, and the present invention is not limited to these. For example, a person using the control server 100 may arbitrarily set the constraint condition and the numerical value in consideration of the characteristics of the storage battery.
maxΣC i [k ″] (7)
Power consumption within group in time zone k ≦ u [k] / N (8)
When the simulating unit 133d determines that the expressions (7) and (8) are not satisfied, the simulating unit 133d continues the state of the notebook PC 30 in the immediately preceding time zone. The simulation unit 133b simulates again using the changed control plan until the constraint condition is satisfied.
The updating unit 133e is a processing unit that updates the control plan to the control plan after switching in the control plan table 125 when the simulated result is improved from the simulation result of the control plan before switching. It is. The updating unit 133e evaluates the simulation result for each group and determines whether or not to update the control plan for each group.
For example, the update unit 133e obtains the peak power from the simulation result. The updating unit 133e acquires the power usage amount in each time zone up to the current time as an actual measurement value within one day. The updating unit 133e acquires the power usage amount in each time zone after the current time from the simulation result within the day. The update unit 133e calculates the maximum value of the acquired power consumption as peak power. The updating unit 133e compares the calculated peak power with the peak power calculated from the simulation result of the control plan before switching. The update unit 133e updates the control plan to the control plan after switching when the peak power is lower than the peak power calculated from the simulation result of the control plan before switching. The update unit 133e updates the control plan for each group.
Although the case where the updating unit 133e uses peak power as the evaluation value has been described here, the present invention is not limited to this. For example, the updating unit 133e combines one or more of the power usage after the current time, the storage battery charge (sum of the product of the charging rate and the battery capacity), the number of state switching, and the minimum power consumption. It may be used as an evaluation value. When combining a plurality, a single evaluation function can be processed as a single evaluation function by adding weights to the respective evaluation functions.
The execution unit 133f determines whether or not a predetermined end condition is satisfied. For example, the execution unit 133f determines whether five minutes have elapsed since the creation unit 133 started the process. The execution unit 133f repeatedly executes the processes of the generation unit 133c, the simulation unit 133d, and the update unit 133e when five minutes have not elapsed. In addition, although the case where the end condition is 5 minutes has been described here, the present invention is not limited to this. For example, the termination condition may be an arbitrary time or an arbitrary number of repetitions.
On the other hand, when 5 minutes have elapsed, the execution unit 133f outputs the updated control plan table 125 to the output unit 134. For example, the execution unit 133f outputs, to the output unit 134, the control plan table 125 that has been corrected by the simulation unit 133d to satisfy the constraint conditions.
The output unit 134 outputs the control plan. For example, the output unit 134 receives the control plan table 125 from the execution unit 133f. The output unit 134 outputs each record of the received control plan table 125 to the corresponding notebook PC 30.
Next, a processing procedure of the control server 100 according to the first embodiment will be described. FIG. 16 is a flowchart illustrating the processing procedure of the control server according to the first embodiment. For example, the process shown in FIG. 16 is executed at predetermined time intervals.
As shown in FIG. 16, the control server 100 acquires various data related to the PC information table 122 from the notebook PC 30 (step S101). The control server 100 classifies the plurality of notebook PCs 30 into a plurality of groups based on the PC information table 122 (step S102). In step 102, the control server 100 determines that the total value of the remaining amount of the storage batteries of the plurality of notebook PCs included in the group is similar to the total value of the remaining amount of the storage battery of the plurality of notebook PCs included in the other group. Classification is performed so that
The control server 100 solves the optimization problem and calculates the power u [k] that can be used by the entire notebook PC 30 in each time zone (step S103). The control server 100 distributes u [k] / N power to each group (step S104).
The control server 100 executes a control plan generation process (step S105), and controls the driving state of the notebook PC based on the control plan (step S106).
Next, the process procedure of the control plan generation process shown in step S105 of FIG. 16 will be described. FIG. 17 is a flowchart of the process procedure of the control plan generation process according to the first embodiment. As shown in FIG. 17, the control server 100 determines whether or not it is a processing timing (step S201). If it is not the processing timing (No at Step S201), the control server 100 proceeds to Step S201 again.
On the other hand, when it is a processing timing (step S201, Yes), the control server 100 generates a control plan (step S202). The control server 100 switches the state of the control plan (step S203) and simulates a demand curve (step S204).
The control server 100 determines whether or not the lower layer constraint condition is satisfied (step S205). The constraint conditions in step S205 correspond to, for example, the conditions shown in equations (7) and (8). If the control server 100 does not satisfy the constraint condition in the lower layer (step S205, No), the control server 100 proceeds to step S208. On the other hand, if the control server 100 satisfies the constraint conditions in the lower layer (step S205, Yes), the control server 100 proceeds to step S206.
The control server 100 determines whether the demand curve has improved (step S206). If the demand curve does not improve (No at Step S206), the control server 100 proceeds to Step S208.
On the other hand, when the demand curve is improved (step S206, Yes), the control server 100 updates the control plan after switching (step S207). The control server 100 determines whether it is the end timing (step S208). If it is not the end timing (step S208, No), the control server 100 proceeds to step S203.
On the other hand, in the case of the end timing (step S208, Yes), the control server 100 outputs a control plan (step S209).
Next, effects of the control server 100 according to the first embodiment will be described. The control server 100 classifies each notebook PC 30 into a plurality of groups based on the remaining amount of the storage battery of each notebook PC 30, and generates a control plan for each classified group. For this reason, the countermeasure for performing the local search method when generating the control plan can be divided and executed for each group, and a plan close to the optimum can be created even with a small amount of processing. Therefore, a control plan for reducing the peak power can be created in a short time even with a number of notebook PCs that cannot be calculated in time for the centralized control.
Further, since the control server 100 generates the control plan so as to satisfy the constraint conditions shown in the equations (7) and (8), at the final time without exceeding the power value assigned to each group. The remaining amount of the storage battery of the notebook PC 30 can be maximized.
Next, the configuration of the system according to the second embodiment will be described. FIG. 18 is a diagram illustrating the configuration of the system according to the second embodiment. As shown in FIG. 18, this system includes a distribution board 20, notebook PCs 30 a, 30 b, 30 c, an illumination 50 a, a multi-function device 50 b, and a control server 200. Distribution board 20, notebook PCs 30a, 30b, 30c, and control server 200 are connected to each other via network 10. In addition, the distribution board 20, the notebook PCs 30 a, 30 b, 30 c, the illumination 50 a, and the multifunction device 50 b are connected to the power line 40.
In FIG. 18, the distribution board 20, notebook PCs 30 a, 30 b, 30 c, illumination 50 a, multifunction device 50 b, and control server 200 are included. Since the description regarding the distribution board 20 and the notebook PCs 30a, 30b, and 30c is the same as that in the first embodiment, the same reference numerals are given here and the description is omitted.
The control server 200 is a server device installed in the company, and creates a control plan that defines charging / discharging of batteries of a plurality of notebook PCs. The control server 200 according to the second embodiment groups notebook PCs having similar remaining battery capacity based on the remaining battery capacity of the notebook PC 30 and regards each grouped notebook PC as a single notebook PC. To create a control plan.
FIG. 19 is a diagram illustrating the configuration of the control server according to the second embodiment. As illustrated in FIG. 19, the control server 200 includes a communication control unit 210, a storage unit 220, and a control unit 230.
The communication control unit 210 is a processing unit that transmits and receives data between the distribution board 20 and the notebook PC 30. The communication control unit 210 corresponds to, for example, a network interface card. The control unit 230 described later exchanges data with the distribution board 20 and the notebook PC 30 via the communication control unit 210.
The storage unit 220 includes demand prediction data 221, a PC information table 222, charge data 223, discharge data 224, a first control plan table 225, and a second control plan table 226. The storage unit 220 corresponds to a storage device such as a semiconductor memory element such as a RAM, a ROM, or a flash memory.
The demand prediction data 221 is time-series data of predicted power demand in the system. For example, the demand prediction data 221 is data in which each time zone in a day is associated with a demand power value. The demand forecast data 221 corresponds to the demand forecast data 121 shown in the first embodiment.
For example, the PC information table 222 holds various types of information related to the notebook PC 30. The PC information table 222 corresponds to the PC information table 122 shown in the first embodiment.
The charging data 223 is data indicating a change in the charging rate when charging the battery. The charging data 223 corresponds to the charging data 123 shown in the first embodiment.
The discharge data 224 is data indicating a change in the charging rate when the battery is discharged. The discharge data 224 corresponds to the discharge data 124 shown in the first embodiment.
The first control plan table 225 holds information on a control plan that defines charging / discharging of each storage battery for each time zone when a plurality of notebook PCs 30 included in the same group are regarded as a single notebook PC. FIG. 20 is a diagram illustrating an example of the first control plan table. As shown in FIG. 20, the second control plan table 225 stores a group ID and a time zone every 30 minutes in association with each other. For example, the time zone “9:00” corresponds to the time zone from 9 o'clock to 9:30. The group ID is information that uniquely identifies a group.
The second control plan table 226 holds information on a control plan that defines charge / discharge of each storage battery for each notebook PC 30 for each time zone. The second control plan table 226 corresponds to the control plan table 125 shown in the first embodiment.
The control unit 230 includes an acquisition unit 231, a measurement unit 232, a creation unit 233, a control plan specification unit 234, and an output unit 236. The control unit 230 corresponds to, for example, an integrated device such as an ASIC or FPGA. Moreover, the control part 230 respond | corresponds to electronic circuits, such as CPU and MPU, for example.
The acquisition unit 231 is a processing unit that acquires various pieces of information about the notebook PC 30 and registers the acquired information in the PC information table 222. Note that the timing at which the acquisition unit 131 acquires information may be set by the person using the control server 200 at an arbitrary timing. For example, the acquisition unit 231 may acquire information immediately before the creation unit 233 described later creates a control plan. The other description regarding the acquisition unit 231 corresponds to the acquisition unit 131 of the first embodiment.
The measurement unit 232 measures the power consumed in the system of FIG. For example, the measurement unit 232 measures the total amount of power consumed in-house by the electrical product connected to the power line 40. The measurement unit 232 records information on the measured power amount in the storage unit 220. Illustration of power information stored in the storage unit 220 is omitted.
The creation unit 233 classifies each notebook PC 30 into a plurality of groups based on the remaining amount of the storage battery, regards each group as a single notebook PC, executes a local search method, and creates a first control plan. Is a processing unit. The creation unit 233 includes a classification unit 233a, a generation unit 233b, a simulation unit 233c, an update unit 233d, and an execution unit 233e.
The classification unit 233a is a processing unit that classifies a plurality of groups based on the remaining amount of the storage battery of each notebook PC 30. The classification unit 233a classifies the plurality of notebook PCs 30 into a plurality of groups by grouping together notebook PCs having similar remaining battery levels.
FIG. 21 is a diagram for explaining the processing of the classification unit according to the second embodiment. In FIG. 21, for convenience of explanation, only the storage battery built in each notebook PC is shown, and the illustration of the notebook PC 30 is omitted. For example, let the storage batteries 1a-1x be the storage batteries incorporated in the notebook PCs 30a-30x, respectively. It is assumed that the storage battery has more remaining capacity as the storage battery has more shaded portions. The classification unit 133a rearranges the storage batteries 1a to 1x in order from the one with the smallest remaining amount. For storage batteries having the same remaining amount, either may be arranged first.
For example, when the classification unit 233a rearranges the storage batteries 1a to 1x, the storage batteries are arranged in ascending order of the remaining capacity 1h, 1l, 1e, 1q, 1s, 1m, 1u, 1p, 1w, 1j, 1o, 1x, 1g. , 1d, 1i, 1b, 1t, 1n, 1v, 1r, 1a, 1c, 1k, 1f. The classification unit 233a classifies the first to fourth storage batteries 1h, 1q, 1l, and 1e into the group 3A. That is, the group 3A includes notebook PCs 30h, 30q, 30l, and 30e.
The classification unit 233a classifies the fifth to eighth storage batteries 1s, 1m, 1u, and 1p into a group 3B. That is, the group 3B includes notebook PCs 30s, 30m, 30u, and 30p.
The classification unit 233a classifies the ninth to twelfth storage batteries 1w, 1j, 1o, 1x into the group 3C. That is, the group 3C includes notebook PCs 30w, 30j, 30o, and 30x.
The classification unit 233a classifies the thirteenth to sixteenth storage batteries 1g, 1d, 1i, and 1b into a group 3D. That is, the group 3D includes notebook PCs 30g, 30d, 30i, and 30b.
The classification unit 233a classifies the 17th to 20th storage batteries 1t, 1n, 1v, and 1r into a group 3E. That is, the group 3E includes notebook PCs 30t, 30n, 30v, and 30r.
The classification unit 233a classifies the 21st to 24th storage batteries 1a, 1c, 1k, and 1f into a group 3F. That is, the notebook PCs 30a, 30c, 30k, and 30f are included in the group 3F.
As described above, the classification unit 233a classifies the notebook PCs 30a to 30x into the groups 3A to 3F, thereby grouping notebook PCs having similar storage battery remaining amounts. The classification unit 133a outputs the information on the classification result to the generation unit 233b and the control plan specification unit 234. FIG. 22 is a diagram illustrating an example of the classification result according to the second embodiment. As shown in FIG. 22, this classification result associates group identification information that uniquely identifies a group with an ID group. The ID group includes an ID that uniquely identifies each notebook PC 30 included in the group. For example, the IDs of the notebook PCs 30a to 30x are PC1 to PC24, respectively.
In FIG. 22, for example, the ID group corresponding to the group identification information “group 3A” is “PC17, PC8, PC12, PC5”. That is, the group 3A includes notebook PCs 30h, 30q, 30l, and 30e.
Returning to the description of FIG. The generation unit 233b is a processing unit that creates a control plan by regarding a plurality of notebook PCs included in a group as a single notebook PC. For example, as shown in FIG. 22, when notebook PCs 30 are classified, PC 17, PC 8, PC 12, and PC 5 are regarded as a single notebook PC “group 3A”. Similarly, PC16, PC19, PC13, and PC21 are regarded as a single notebook PC “group 3B”. PC23, PC10, PC15, and PC24 are regarded as a single notebook PC “group 3C”. PC2, PC9, PC4, and PC7 are regarded as a single notebook PC “group 3D”. PC20, PC14, PC22, and PC18 are regarded as a single notebook PC “group 3E”. PC1, PC3, PC11, and PC6 are regarded as a single notebook PC “group 3F”.
Moreover, the production | generation part 233b shall collect each storage battery contained in the group for the storage battery of each group regarded as the single notebook PC. For example, the storage battery of group 3A is a storage battery in which the storage batteries of PC17, PC8, PC12, and PC5 are combined.
An initial control plan is generated by setting a state for each group in the control plan table 125 for each time period. FIG. 23 is a diagram (1) for explaining the process of the generation unit according to the second embodiment. In FIG. 23, as an example, description will be made using groups 3A and 3B regarded as a single notebook PC. As illustrated in FIG. 23, for example, the generation unit 233b refers to the PC information table 222 and sets the state “AC” for all time zones including controllable PCs. Although explanation is omitted here, when the group includes uncontrollable PCs, the state of each time zone corresponding to the group may be set to “UN1” or “UN2”.
The generation unit 233b selects an arbitrary time zone of the generated control plan and switches to any state of “AC”, “BA”, and “CH”. This is referred to as a “switching instruction”. FIG. 24 is a diagram (2) for explaining the process of the generation unit according to the second embodiment. FIG. 24A shows an example of the first control plan table 225 before switching, and FIG. 24B shows an example of the first control plan table 225 after switching. As illustrated in FIG. 24, for example, the generation unit 233b selects “9:30” of the group 3B. The generation unit 233b switches the state of the selected time zone and the subsequent time zones to “BA”. The shaded area in FIG. 24 indicates the time zone of the group for which a switching instruction has been issued. In addition, the generation unit 233b records the time zone of the group for which the switching instruction is issued in the first control plan table 225.
Further, when switching the state, the generation unit 233b switches the state until a switching instruction is issued after the next time period. FIG. 25 is a diagram (3) illustrating the process of the generation unit according to the second embodiment. FIG. 25 (1) shows an example of the first control plan table 225 before switching, and FIG. 25 (2) shows an example of the first control plan table 225 after switching. FIG. 25 illustrates a case where a switched state exists. FIG. 25A illustrates a case where there is an instruction to switch the state “BA” of “12:30” of the group 3A. As illustrated in FIG. 25, for example, the generation unit 233b selects “11:30” of the group 3B and issues a “switching instruction” for switching to “CH”. The generation unit 233b switches the state of the selected subsequent time zone to “CH”. In this case, since there is an instruction to switch the state “BA” of “12:30” of the group 3A, the generation unit 233b switches the state up to “12:00” to “CH”.
The generation unit 233b regards the plurality of notebook PCs included in the group as a single notebook PC, executes the above-described processing, and outputs the control plan information of each group to the simulation unit 233c.
Returning to the description of FIG. The simulation unit 233c is a processing unit that simulates demand power for each time period using the control plan for each group generated by the generation unit 233b. For example, the simulation unit 233c simulates the demand power by subtracting the power usage amount by the group from the demand prediction data 221 and adding the power usage amount when the group operates according to the control plan. The simulation unit 233c outputs the simulation result to the update unit 233d.
The simulation unit 233c simulates demand power every 10 minutes based on the control plan, and calculates a post-control peak 11a every 10 minutes. For example, the simulating unit 233c calculates the post-control peak max j for each time zone using the equation (6) described in the first embodiment.
Here, when the simulation unit 233c calculates the post-control peak max j using Equation (6), the power usage amount in each state is multiplied by the number of notebook PCs included in the group. In the second embodiment, the number of notebook PCs included in each group is four. In this case, the power usage E A state "AC", for example, a 10 × 4 [W]. The power values E B state "BA" is, for example, 0 × 4 [W]. Further, the power value E C of the state “CH” is, for example, 60 × 4 [W].
Further, the simulation unit 233c simulates demand power for each time zone by adding a constraint condition to the control plan. For example, the simulation unit 233c calculates the charging rate of the storage battery in each time zone of the group. The charge rate of the rechargeable battery in each time zone of the group is a charge rate when the rechargeable battery of each notebook PC included in the group is regarded as single. Moreover, the simulation part 233c makes the residual amount of the storage battery of a group the average value of the residual amount of each notebook PC contained in a group.
The simulating unit 233c refers to the charging rate of the storage batteries of the group and the charging data 223, and estimates the charging rate after the elapse of time. When discharging for a certain time from the storage batteries of the group, the simulation unit 233c refers to the discharge data 224 and estimates the charge rate after the elapse of the time.
The simulation unit 233c determines whether or not the estimated charging rate meets the constraint condition. For example, the simulating unit 233c determines whether or not the estimated charging rate satisfies the constraint condition “of the control plan generated so far, the sum of the remaining battery levels becomes the maximum at the end of the calculation section”. judge. When the simulation unit 233c determines that the condition is not satisfied, the simulation unit 233c continues the state of the group in the immediately preceding time zone. The simulation unit 233c uses the changed control plan to simulate again until a constraint condition is satisfied. Note that the constraint conditions and numerical values described here are merely examples, and the present invention is not limited to these. For example, a person using the control server 200 may arbitrarily set the constraint condition and the numerical value in consideration of the characteristics of the storage battery.
The update unit 233d updates the control plan to the control plan after switching when the simulated result is improved from the simulation result of the control plan before switching. For example, when the simulated result is improved from the simulation result of the control plan before switching, the updating unit 233d converts the control plan to the control plan after switching for the first control plan table 225. A processing unit to be updated.
For example, the update unit 233d obtains peak power from the simulation result. The updating unit 233d acquires, as an actual measurement value, the amount of power used in each time period up to the current time in the day. The updating unit 233d acquires the power usage amount in each time zone after the current time in the day from the simulation result. The update unit 233d calculates the maximum value of the acquired power consumption as peak power. The updating unit 233d compares the calculated peak power with the peak power calculated from the simulation result of the control plan before switching. The update unit 233d updates the control plan to the control plan after switching when the peak power is lower than the peak power calculated from the simulation result of the control plan before switching.
The execution unit 233e determines whether or not a predetermined end condition is satisfied. For example, the execution unit 233e determines whether five minutes have elapsed since the creation unit 233 started processing. The execution unit 233e repeatedly executes the processes of the generation unit 233b, the simulation unit 233c, and the update unit 233d when five minutes have not elapsed. In addition, although the case where the end condition is 5 minutes has been described here, the present invention is not limited to this. For example, the termination condition may be an arbitrary time or an arbitrary number of repetitions.
On the other hand, when 5 minutes have elapsed, the execution unit 233e outputs the updated information of the first control plan table 225 to the control plan specifying unit 234.
The control plan specifying unit 234 generates a control plan for each notebook PC 30 based on the first control plan table 225, and registers the generated control plan information for each notebook PC 30 in the second control plan table 226. Part. The control plan specifying unit 234 outputs the information in the second control plan table 226 to the output unit 236.
The control plan specifying unit 234 sets the state of each time zone set for the group as the maximum value that can be consumed by each notebook PC in the group. For example, the number of notebook PCs included in each group is four. In this case, the amount of power used in the state “AC” is, for example, 10 × 4 [W]. Further, the power value of the state “BA” is, for example, 0 × 4 [W]. Further, the power value of the state “CH” is, for example, 60 × 4 [W]. The control plan specifying unit 234 adds the maximum power that can be consumed in each time zone to the constraint condition, and solves the optimization problem in the same manner as the creating unit 233, thereby controlling each notebook PC included in the group. Generate a plan.
For example, when the first control plan table 225 is as shown in FIG. 20, the constraint conditions applied to each notebook PC 30 included in the group 3A are as follows. That is, the maximum value of power that can be consumed between “9:00:00 to 11:29” is “40 W”, and the maximum value of power that can be consumed between “11:30 to 11:29” is “240 W”. In addition, the maximum value of the power that can be consumed during “12:30 to 13:29” is “0 W”.
The output unit 236 outputs the data of the second control plan table to the corresponding notebook PC 30. The output unit 236 receives data of the second control plan table from the control plan specifying unit 234.
Next, processing of the control server 200 according to the second embodiment will be described. FIG. 26 is a flowchart illustrating the processing procedure of the control server according to the second embodiment. For example, the process shown in FIG. 26 is executed at predetermined time intervals.
As shown in FIG. 26, the control server 200 acquires various data related to the PC information table 222 from the notebook PC 30 (step S301). Based on the PC information table 222, the control server 200 groups notebook PCs having similar storage battery levels (step S302).
The control server 200 regards the plurality of notebook PCs 30 included in the group as a single notebook PC, and executes a control plan generation process (step S303). The first control plan table 225 is generated by the process of step S303.
Based on the first control plan table 225, the control server 200 identifies the maximum value of power that can be allocated within the group (step S304). The control server 200 adds the maximum power that can be allocated in the group to the constraint condition, and executes the control plan generation process (step S305). The second control plan table 226 is generated by the process of step S305.
Then, the control server 200 controls the driving state of the notebook PC based on the control plan (step S306).
Next, effects of the control server 200 according to the second embodiment will be described. The control server 200 groups notebook PCs having similar remaining battery levels based on the remaining battery level of each notebook PC 30, regards each grouped notebook PC as a single notebook PC, and creates a control plan. create. For this reason, it is possible to execute a countermeasure for performing a local search method when generating a control plan, regarding a group as a single device, and to create a plan that is close to optimal even with a small amount of processing.
Further, the control server 200 identifies the power of each time zone that can be used in the group based on the state assigned to each time zone of the group control plan, and determines the control plan of each notebook PC 30 in the group. Identify. For this reason, since the control plan can be generated for a small number of notebook PCs included in the group after the group control plan is created, the processing load can be reduced.
Next, an example of a computer that executes a control program that realizes the same function as the control servers 100 and 200 shown in the above embodiment will be described. FIG. 27 is a diagram illustrating an example of a computer that executes a control program.
As illustrated in FIG. 27, the computer 300 includes a CPU 301 that executes various arithmetic processes, an input device 302 that receives input of data from a user, and a display 303. The computer 300 also includes a reading device 304 that reads a program or the like from a storage medium, and an interface device 305 that exchanges data with other computers via a network. The computer 300 also includes a RAM 306 that temporarily stores various types of information and a hard disk device 307. The devices 301 to 307 are connected to the bus 308.
The hard disk device 307 includes, for example, a classification program 307a, a power calculation program 307b, a generation program 307c, a simulation program 307d, an update program 307e, and an execution program 307f. The CPU 301 reads each program 307 a to 307 f and develops it in the RAM 306.
The classification program 307a functions as a classification process 306a. The power calculation program 307b functions as a power calculation process 306b. The generation program 307c functions as a generation process 306c. The simulation program 307d functions as a simulation process 306d. The update program 307e functions as an update process 306e. The execution program 307f functions as an execution process 306f.
For example, the classification process 306a corresponds to the classification unit 133a. The power calculation process 306b corresponds to the power calculation unit 133b. The generation process 306c corresponds to the generation unit 133c. The simulation process 306d corresponds to the simulation unit 133d. The update program 306e corresponds to the update unit 133e. The execution process 306f corresponds to the execution unit 133f.
Note that the programs 307a to 307f are not necessarily stored in the hard disk device 307 from the beginning. For example, each program is stored in a “portable physical medium” such as a flexible disk (FD), a CD-ROM, a DVD disk, a magneto-optical disk, and an IC card inserted into the computer 300. Then, the computer 300 may read the programs 307a to 307f from these and execute them.
(Supplementary note 1) A control method executed by a computer,
Based on the remaining amount of the storage battery of the plurality of devices, the distribution of the remaining amount of the storage battery of the plurality of devices included in the group and the distribution of the remaining amount of the storage battery of the plurality of devices included in the other group are equalized , Classifying the plurality of devices into a plurality of groups,
For each group, generate a virtual control plan in which the state of some devices is switched with respect to the control plan that defines the state relating to charging / discharging for each time zone of each device equipped with the storage battery,
For each group, the power demand for each time period is simulated using the virtual control plan,
For each group, if the simulated result is better than the simulated result of the control plan, update the control plan to the virtual control plan;
If the end condition of whether or not a predetermined time has passed is satisfied, the control plan is output. If the end condition is not satisfied, the process of updating the control plan is repeated until the end condition is satisfied. A control method characterized by executing each process.
(Additional remark 2) The process which calculates the electric power allocated to each group is further performed by dividing the total electric power allocated to these devices by the number of the groups,
The updating process is performed when the simulated result is improved from the simulated result of the control plan and the power of the temporary control plan does not exceed the power allocated to the group. The control method according to appendix 1, wherein a control plan is updated to the virtual control plan.
(Supplementary Note 3) A control method executed by a computer,
A plurality of devices having storage batteries are classified into a plurality of groups by grouping devices having similar storage battery remaining amounts based on the remaining amount of the storage battery of the device,
By considering the sum of the capacity of the storage batteries of the plurality of devices included in the group as the capacity of the storage battery of a single device, the plurality of devices included in each group is regarded as a single device, and each of the devices Generate a virtual control plan that switches the state of some devices against the control plan that defines the state related to charging and discharging for each time zone,
Simulating the power demand for each time period using the virtual control plan,
(Additional remark 4) Based on the state allocated to each time slot | zone of the control plan at the time of considering the several apparatus contained in the said group as a single apparatus, the electric power of each time slot | zone which can be used in the said group The control method according to supplementary note 3, further comprising executing a process of specifying and specifying a control plan of each device in the group.
(Supplementary Note 5) Based on the remaining amount of the storage battery of the plurality of devices, the distribution of the remaining amount of the storage battery of the plurality of devices included in the group is the distribution of the remaining amount of the storage battery of the plurality of devices included in the other group. A classification unit that classifies a plurality of devices into a plurality of groups so as to have similar values;
For each group, a generation unit that generates a virtual control plan in which the state of some devices is switched with respect to a control plan that defines a state relating to charging and discharging for each time zone of each device including a storage battery;
For each group, a simulation unit that simulates the power demand for each time period using the virtual control plan;
For each group, when the simulated result is improved from the simulated result of the control plan, an update unit that updates the control plan to the virtual control plan;
If the end condition of whether or not a predetermined time has passed is satisfied, the control plan is output. If the end condition is not satisfied, the process of updating the control plan is repeated until the end condition is satisfied. And a control server.
(Additional remark 6) It further has the electric power calculation part which calculates the electric power allocated to each group by dividing the total electric power allocated to a some apparatus by the number of groups,
The update unit performs the control when the simulated result is improved from the simulated result of the control plan and the power of the temporary control plan does not exceed the power allocated to the group. The control server according to appendix 5, wherein the plan is updated to the virtual control plan.
(Additional remark 7) Based on the remaining amount of the storage battery of the said apparatus, the several apparatus provided with the storage battery is grouped into the groups by grouping together the apparatuses with which the remaining amount of a storage battery is similar. A classification unit to
By considering the sum of the capacity of the storage batteries of the plurality of devices included in the group as the capacity of the storage battery of a single device, the plurality of devices included in each group is regarded as a single device, and each of the devices A generation unit that generates a virtual control plan in which the state of some devices is switched with respect to a control plan that defines a state relating to charging and discharging for each time period of
A simulation unit for simulating the power demand for each time period using the virtual control plan;
(Appendix 8) Based on the status assigned to each time zone of the control plan when a plurality of devices included in the group are regarded as a single device, the power in each time zone that can be used in the group is specified. The control server according to appendix 7, further comprising a control plan specifying unit that specifies a control plan for each device in the group.
Based on the remaining amount of the storage battery of the plurality of devices, the distribution of the remaining amount of the storage battery of the plurality of devices included in the group is similar to the distribution of the remaining amount of the storage battery of the plurality of devices included in the other group. To classify multiple devices into multiple groups,
For each group, generate a virtual control plan that switches the state of some devices against the control plan that defines the state related to charging and discharging for each time zone of each device equipped with a storage battery,
For each group, the power demand for each time zone is simulated using the virtual control plan,
If the end condition of whether or not a predetermined time has passed is satisfied, the control plan is output. If the end condition is not satisfied, the process of updating the control plan is repeated until the end condition is satisfied. A control program that causes each process to be executed.
(Additional remark 10) The process which calculates the electric power allocated to each group is further performed by dividing the total electric power allocated to a some apparatus by the number of groups,
The updating process is performed when the simulated result is improved from the simulated result of the control plan and the power of the temporary control plan does not exceed the power allocated to the group. The control program according to appendix 9, wherein a control plan is updated to the virtual control plan.
A plurality of devices having storage batteries are classified into a plurality of groups by grouping devices having similar storage battery amounts based on the remaining amount of storage batteries of the devices,
(Additional remark 12) Based on the state assigned to each time zone of the control plan when a plurality of devices included in the group are regarded as a single device, the power of each time zone that can be used in the group is specified. The control program according to appendix 11, wherein a process for specifying a control plan for each device in the group is further executed.
10 network 20 distribution board 30a, 30b, 30c notebook PC
50a Illumination 50b MFP 100, 200 Control server
Further dividing the total power allocated to the plurality of devices by the number of groups to calculate the power allocated to each group;
The updating process is performed when the simulated result is improved from the simulated result of the control plan and the power of the temporary control plan does not exceed the power allocated to the group. The control method according to claim 1, wherein a control plan is updated to the virtual control plan.
Based on the remaining amount of the storage battery of the plurality of devices, the distribution of the remaining amount of the storage battery of the plurality of devices included in the group is similar to the distribution of the remaining amount of the storage battery of the plurality of devices included in the other group. A classification unit for classifying a plurality of devices into a plurality of groups,
JP2013042074A 2013-03-04 2013-03-04 Control method, control server, and control program Active JP5990117B2 (en)
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JP6414743B2 (en) 2014-11-28 2018-10-31 富士通株式会社 Power supply control device, power supply control program, power supply control method, and power supply control system
JP6531384B2 (en) * 2014-12-17 2019-06-19 富士通株式会社 Calculation method, calculation program and calculation device
KR100763174B1 (en) * 2004-11-13 2007-10-04 삼성전자주식회사 Apparatus and method for displaying power-saving level
JP5369885B2 (en) * 2009-05-15 2013-12-18 トヨタ自動車株式会社 Power supply system and control method thereof
CN102986057B (en) * 2010-05-13 2016-11-23 飞机医疗有限公司 Battery bag and the electrical equipment with detachable battery bag
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Moeini-Aghtaie et al. 2012 Incorporating large-scale distant wind farms in probabilistic transmission expansion planning—Part I: Theory and algorithm
Kirovski et al. 1997 System-level synthesis of low-power hard real-time systems
Lin et al. 2014 Task scheduling with dynamic voltage and frequency scaling for energy minimization in the mobile cloud computing environment
Luo et al. 2001 Battery-aware static scheduling for distributed real-time embedded systems
Rakhmatov et al. 2003 Energy management for battery-powered embedded systems
Ahmadi et al. 2014 Security-constrained unit commitment with linearized system frequency limit constraints
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