Electric energy control device, electric energy control method, and program

Abstract

A power amount control device (10) comprises: a power supply scheduled amount acquisition unit (111) that acquires a power supply scheduled amount including a renewable energy supply amount in a prescribed time slot; and a surplus power amount computation unit (113) that calculates, by acquiring from intra-room control devices (20) the total intra-room power consumption amounts of respective rooms (100) and summing up the same, the DC total power consumption amount indicating the amount of power consumption for the whole data center, computes a surplus power amount which is the difference between the power supply scheduled amount and the DC total power consumption amount, and transmits, to the intra-room control devices (20), supercooling control notifications for executing supercooling control by an air conditioner using the surplus power amount.

Description

[Technical Field]

[0001] The present invention relates to a power amount control device, a power amount control method, and a program for optimizing the amount of power consumed in a data center (hereinafter, sometimes referred to as "DC"). [Background technology]

[0002] With the goal of reducing greenhouse gas emissions, the spread of facilities, equipment, and technologies to expand the use of renewable energy obtained from sources such as solar and wind power is being promoted. However, since the supply of renewable energy is affected by changes in the natural environment and it cannot be stored, it is necessary to maximize the efficiency of renewable energy utilization by increasing demand in line with peak power supply. For example, so-called "increased demand response (DR)" is being implemented, in which excess renewable energy output is consumed by operating demand equipment or absorbed by charging storage batteries. The amount of power supplied from renewable energy is increasing year by year, and it is expected that data centers (DCs) will also have more opportunities to receive power supply based on renewable energy.

[0003] On the other hand, the amount of data processed in data centers is increasing year by year, and it is necessary to improve the power consumption efficiency of the entire data center (the amount of power consumed by the entire data center for a certain amount of data processing).In a data center, in addition to the power consumed by servers, the power consumed by air conditioning also accounts for a large proportion of the power consumed, so there is a need to reduce the power consumption of the entire data center.

[0004] Non-Patent Document 1 discloses a technology that optimizes the power consumption of the entire DC by taking into consideration the power consumption of air conditioners and servers (IT devices). The air conditioning-linked IT load placement optimization method for data centers described in Non-Patent Document 1 collects operational and monitoring information from IT equipment in data centers to predict future changes in the load on the IT equipment and calculates the power increase for air conditioning equipment in response to the increase in power consumption of the IT equipment. Then, an optimization problem is solved to minimize the objective function, which is the amount of power consumed by the data center, so that the load concentration rate on the IT equipment increases over time, i.e., the number of operating IT devices is reduced. This calculates the placement of IT loads (virtual machines) on IT equipment that minimizes the amount of power consumed by the data center. [Prior art documents] [Non-patent literature]

[0005] [Non-Patent Document 1] Jun Okitsu and 4 others, "IT Load Placement Optimization Method Linked with Air Conditioning for Eco-Friendly Data Centers," FIT (Forum on Information Technology) 2010, 9th Information Science and Technology Forum, RC-009 Summary of the Invention [Problem to be solved by the invention]

[0006] However, the technology described in Non-Patent Document 1 uses a general-purpose rule-based standard in the air conditioning power model used to calculate the power consumption of air conditioning equipment, which is not dependent on the equipment conditions that vary from data center to data center. This makes it difficult to optimize the data center's power consumption, taking into account individual equipment conditions such as the location of the air conditioning equipment, airflow, server configuration within the data center, and thermal cooling efficiency. Furthermore, when a data center receives power supplied using renewable energy, maximizing the utilization efficiency of the renewable energy is not taken into consideration. In other words, when attempting to reduce the power consumption of the entire data center, the total power supply, including renewable energy, falls below the total power supply, which poses a problem of reduced utilization efficiency of the renewable energy.

[0007] The present invention was made in consideration of these points, and its objective is to improve the power utilization efficiency of air conditioning power consumption within a DC by utilizing surplus power, including renewable energy. [Means for solving the problem]

[0008] The power consumption control device of the present invention is a power consumption control device that is communicatively connected to room control devices for each room in a data center (DC) in which multiple rooms are installed, each of which controls the servers and air conditioners in the room, and controls the power consumption of each of the rooms.It is characterized by comprising: a planned power supply acquisition unit that acquires a planned power supply amount including the amount of renewable energy supply during a specified time period, and a surplus power calculation unit that acquires from each of the room control devices a total in-room power consumption that is the sum of the server power consumption and air conditioning power consumption in each room, calculates a DC total power consumption that indicates the power consumption of the entire data center by summing the total in-room power consumption of each room, calculates surplus power that is the difference between the planned power supply amount and the DC total power consumption, and sends a supercooling control notification to the room control device that causes supercooling control to be performed by the air conditioner in the room using the surplus power. [Effects of the Invention]

[0009] According to the present invention, it is possible to improve the efficiency of power utilization of air conditioning power consumption in a DC by utilizing surplus power including renewable energy. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a diagram showing the overall configuration of an electric energy control system including an electric energy control device according to an embodiment of the present invention; [Figure 2] FIG. 2 is a diagram showing the configuration within one room of a DC according to the present embodiment. [Figure 3] 2 is a functional block diagram showing an example of the configuration of an in-room control device according to the present embodiment. [Figure 4]FIG. 10 is a diagram for explaining situation classification according to the present embodiment. [Figure 5] 1 is a functional block diagram showing an example of the configuration of an electric energy control device according to an embodiment of the present invention; [Figure 6A] FIG. 10 is a diagram showing the case of room “A” in which a load pattern in which a high load continues in the first and second turns is executed. [Figure 6B] FIG. 10 is a diagram showing the case of room "B" in which a load pattern is executed in which a high load does not continue in the first and second turns. [Figure 6C] FIG. 10 is a diagram showing the case of room "C" in which a load pattern is executed in which the load is low in the first turn and the load is increased in the second turn. [Figure 6D] FIG. 10 is a diagram showing a room "D" case in which a load pattern is executed in which the first turn is a low load and the second turn is an increased load. [Figure 7A] FIG. 10 is a diagram showing evaluation results when control is performed with and without supercooling control in the first turn of room A. [Figure 7B] FIG. 10 is a diagram showing the evaluation results when control is performed with and without supercooling control in the first turn of Room B. [Figure 7C] FIG. 10 is a diagram showing evaluation results when control is performed with and without supercooling control in the first turn of Room C. [Figure 7D] FIG. 10 is a diagram showing evaluation results when control is performed with and without supercooling control in the first turn of room D. [Figure 8] FIG. 10 is a diagram showing the total amount of air conditioning power consumption for two turns in rooms A to D with and without supercooling control. [Figure 9] FIG. 10 is a diagram comparing the power gain of renewable energy for each load pattern. [Figure 10] 2 is a sequence diagram showing the flow of processing executed by an electric energy control system including the electric energy control device according to the present embodiment. FIG. [Figure 11]1 is a hardware configuration diagram illustrating an example of a computer that realizes the functions of the power amount control device and the in-room control device according to the present embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] Next, an embodiment of the present invention (hereinafter referred to as "the present embodiment") will be described. FIG. 1 is a diagram showing the overall configuration of an electric energy control system 1 including an electric energy control device 10 according to this embodiment.

[0012] As shown in Figure 1, the power consumption control system 1 is configured to include a DC (data center) 1000 having multiple rooms 100 each having multiple servers 3 and one or more air conditioners 4, a room control device 20 that is communicatively connected to the multiple servers 3 and one or more air conditioners 4 in the rooms 100 and is provided corresponding to each room 100, and a power consumption control device 10 that is communicatively connected to each room control device 20 and controls the amount of power consumed by the entire DC 1000. The power amount control device 10 and each room control device 20 may be provided inside the DC 1000 or may be provided in a location separate from the DC 1000.

[0013] FIG. 2 is a diagram showing the configuration within one room 100 of the DC 1000 according to this embodiment. DC1000 has a plurality of rooms 100, and as shown in Fig. 2, a plurality of servers 3 are installed in each room 100, and one or more air conditioners 4 are installed to control the air conditioning in the room 100. The amount of power consumed by the air conditioning of the entire room due to the operation of one or more air conditioners 4 is measured for each room 100 by an energy measuring device (not shown).

[0014] Each in-room control device 20 corresponding to each room 100 may acquire status information of the air conditioners 4 (air conditioners "1" and "2" in Figure 2) installed in the room 100 and transmit air conditioning control information via an air conditioning management device not shown, or may be directly connected to each air conditioner 4 for communication without going through the air conditioning management device. In addition, the room control device 20 may acquire status information and transmit control information from the server 3 installed in the room 100 via a server management device (not shown), or may be directly connected to the server 3 for communication.

[0015] In each room 100 of the DC 1000 in this embodiment, the servers 3 in the entire room are divided into areas where multiple servers 3 are arranged, as shown in Fig. 2, and controlled as "server areas." This server area 30 is an area that accommodates a group of servers on which virtual resources are arranged. Fig. 2 shows an example in which server areas "1" to "6" are provided.

[0016] In the DC1000, the explanation will be given assuming that a virtualization platform is built and operated. Known open source virtualization platforms include OpenStack (registered trademark), software for building cloud environments, and Kubernetes (registered trademark), software for operating and managing containerized workloads and services. OpenStack is primarily used to manage and operate physical machines and virtual machines (VMs). Kubernetes is primarily used to manage and operate containers. In this specification, an application virtualized on a virtualization platform (consisting of one or more containers, one or more VMs, etc.) is referred to as a virtual resource. In Kubernetes, the smallest execution unit of an application is a pod consisting of one or more containers.

[0017] In this embodiment, an "air conditioning area" is provided in correspondence with the server area 30 of the server group, as shown in Fig. 2. The air conditioning area 40 is a collective area in which the effect of air conditioning control is measured, and faces either the intake side or the exhaust side of the server 3. The air blown from the air conditioner 4 is blown out from the air-conditioning areas 40 on the intake side (air-conditioning areas "3," "4," "7," and "8" in FIG. 2) via piping installed, for example, under the floor of the room 100. Then, air whose temperature has risen due to the heat of each server 3 is taken in from the intakes of the piping installed in the air-conditioning areas 40 on the discharge side (air-conditioning areas "1," "2," "5," and "6" in FIG. 2), and an airflow is generated that returns to the air conditioner 4.

[0018] A plurality of sensors (temperature sensors, etc.) are installed in each of the air-conditioning areas 40. Temperature sensors are also installed at the air intakes of the servers 3 in each server area 30. Furthermore, sensors (temperature sensors, etc.) are also installed outside the DC 1000. Information obtained from these sensors (sensor information) can be acquired by the in-room control device 20 via a communication line, etc.

[0019] In the power amount control system 1 according to this embodiment, the power amount control device 10 acquires the planned power supply amount, including the renewable energy supply amount available in a predetermined time period, and the total load amount to be processed in the DC 1000 from an external device (for example, a system management device, etc.). The power amount control device 10 then calculates the total power consumption in each room 100 (the sum of the server power consumption and the air conditioning power consumption, referred to below as the "total room power consumption"), and calculates the total power consumption of the DC as a whole (referred to below as the "total DC power consumption"), which is the sum of the total room power consumption of each room. The power amount control device 10 calculates the surplus power from the difference between the calculated total DC power consumption and the planned power supply amount, including the renewable energy supply amount.

[0020] The power amount control system 1 then uses the calculated surplus power amount for the air conditioning supercooling of each room 100 in the DC 1000. The power amount control system 1 optimally controls allocation of how much renewable energy to allocate to each room 100 when using the planned power supply amount, including the renewable energy supply amount that must be used up in a certain time period, for the air conditioning supercooling of the rooms 100 in the DC 1000.

[0021] Next, the power amount control device 10 and the room control device 20 that constitute the power amount control system 1 according to this embodiment will be specifically described.

[0022] <Room control device> First, the in-room control device 20 will be described. FIG. 3 is a functional block diagram showing an example of the configuration of the in-room control device 20 according to this embodiment. The in-room control device 20 classifies each situation that causes a change in power consumption in the room 100 as a Situation, and calculates the total in-room power consumption, which is the sum of the server power consumption and the air conditioning power consumption when air conditioning control of the air conditioner 4 is performed for a predetermined load in each situation. The in-room control device 20 also generates supercooling-related information (details will be described later) for determining whether the room in question is a target for supercooling execution, and transmits this information to the power amount control device 10. The in-room control device 20 also receives a notification from the power amount control device 10 that the room is a target for supercooling control (supercooling control notification), and executes supercooling control. The in-room control device 20 is configured by a computer including a control unit 21, an input / output unit 22, and a storage unit .

[0023] The input / output unit 22 inputs and outputs information between the power amount control device 10 and each device (each server 3 and each air conditioner 4) in the DC 1000. The input / output unit 22 is made up of a communication interface that transmits and receives information via a communication line, and an input / output interface that inputs and outputs information between an input device such as a keyboard and an output device such as a monitor, both of which are not shown.

[0024] The storage unit 23 is configured by a hard disk, a flash memory, a RAM (Random Access Memory), or the like. The storage unit 23 temporarily stores programs for executing the functions of the control unit 21 and information necessary for the processing of the control unit 21. The storage unit 23 also stores a server power amount learning model 231, operation history information 232, control value power amount correspondence information 233, and supercooling power amount correspondence information 234 (details will be described later).

[0025] The control unit 21 is responsible for all the processing executed by the in-room control device 20, and as shown in Figure 3, is composed of a situation recognition unit 211, a placement pattern calculation unit 212, a server power consumption estimation unit 213, a control value power consumption correspondence information generation unit 214, a supercooling power consumption correspondence information generation unit 215, a total in-room power consumption calculation unit 216, a supercooling related information generation unit 217, a load placement control unit 218, and an air conditioning control unit 219.

[0026] The situation recognition unit 211 acquires information on each of the situation components, which are the "situation components" in the room 100 in the DC 1000 before control, including the "situation intake temperature of the server area," the "outside air temperature (outdoor temperature)," and the "server power consumption per server area" determined by the load arrangement. These situation components are external factors that affect the increase or decrease in the air conditioning power consumption.

[0027] The situation recognition unit 211 obtains temperature information from multiple temperature sensors installed around the air intakes of the servers 3 in each server area 30, calculates the average value, and calculates the average air intake temperature for each server area 30. The situation recognition unit 211 then averages the calculated average temperatures for each server area 30 across the entire room 100, and sets the obtained temperature as the "air intake temperature of the server area."

[0028] The situation recognition unit 211 regards information obtained from a temperature sensor set outside the DC 1000 as "outside air temperature (outside air temperature)." The "server power consumption amount for each server area" is information calculated by the server power consumption amount estimation unit 213 (details will be described later).

[0029] The situation recognition unit 211 determines to which situation category each piece of acquired information (external factor information) that is an external factor belongs. Each external factor is divided into multiple ranges between the minimum and maximum values ​​according to the characteristics of the external factor. A combination of the ranges into which each external factor is divided is defined as one Situation. This will be explained below with reference to Figure 4.

[0030] As shown in FIG. 4, each external factor is defined as a "factor" and a range to be divided is defined (hereinafter referred to as "division definition"). For example, the external factor for "factor1" shown in the Situation classification information 52 in FIG. 4 is "air intake temperature of the server area," and the division definition is "0-48 degrees divided into 6." The external factor for "factor2" is "outside air temperature (air temperature)," and the division definition is "0-48 degrees divided into 6." The external factor for "factor3" is "server power consumption in server area "1"," and the division definition is "0-200W divided into 20." Similarly, the external factor for "factor8" is "server power consumption in server area "6," and the division definition is "0-200W divided into 20."

[0031] Here, it is assumed that the information on the external factor acquired by the situation recognition unit 211 is the external factor information 51 shown in FIG. 4. In this case, the situation recognition unit 211 determines that the value of "factor1" (the air intake temperature of the server area) is "25," and therefore that this falls within the "24-32 range" (24 degrees or more and less than 32 degrees) as the "range," and sets the "factor range identifier" to "factor1-4." This "factor range identifier" is information that identifies the range to which the temperature belongs, for example, by dividing 0-48 degrees into six parts, such as "factor1-1" for 0 degrees or more and less than 8 degrees, "factor1-2" for 8 degrees or more and less than 16 degrees, and "factor1-3" for 16 degrees or more and less than 24 degrees. The same applies to the other "factors."

[0032] The situation recognition unit 211 combines information on the "factor range identifiers" of the external factors to create a "Situation classification" and determines that it is "factor1-4_factor2-4_factor3-4_factor4-4_factor5-5_factor6-5_factor7-4_factor8-4". In this way, the situation recognition unit 211 determines the "Situation classification" based on the acquired information on external factors.

[0033] 3, the allocation pattern calculation unit 212 obtains the load amount allocated to the room it is responsible for based on information on the load allocation ratio of each room 100 to the total DC load amount indicated in the inter-room load allocation pattern and information on the total load amount (total DC load amount), both of which are obtained from the power amount control device 10. Then, the allocation pattern calculation unit 212 obtains information on the amount of virtual resources to be newly allocated (e.g., the number of CPU cores), and calculates an allocation pattern in which new virtual resources (VMs, containers, etc.) are allocated to each server 3 based on the most recent resource usage status (e.g., CPU usage rate). After allocating the virtual resources to each server 3, the allocation pattern calculation unit 212 ensures that the resource occupation amount on each server 3 is equal to or less than the server capacity (upper limit value) x a predetermined threshold.

[0034] The server power consumption estimation unit 213 estimates the power consumption of each server 3 using a learning model (server power consumption learning model 231) in the placement pattern calculated by the placement pattern calculation unit 212. Then, based on the server placement configuration for each server area 30, the server power consumption estimation unit 213 calculates the total server power consumption for each server area 30 in the placement pattern.

[0035] Specifically, the server power consumption estimation unit 213 predicts the power consumption of each server 3 in the deployment pattern using a learning model (server power consumption learning model 231) that uses the air intake temperature of the server area and information on resource usage (e.g., CPU usage rate, memory usage rate, etc.) as input data and the server power consumption as output data. The server power consumption learning model 231 is generated in advance using the intake port temperature, the resource usage of the server 3, and the information on the server power consumption, which is the result information at that time, as learning data.

[0036] Furthermore, the server power consumption estimation unit 213 calculates the server power consumption for each server area 30 by adding up the server power consumption of each server 3 in the server area 30 based on the server layout configuration for each server area 30 .

[0037] The control value-power correspondence information generation unit 214 generates control value-power correspondence information 233 that indicates the control value (air conditioning control value) of each air conditioner 4 and the amount of air conditioning power consumed when each air conditioner 4 executes that air conditioning control value.

[0038] This control value-power correspondence information 233 is information stored for each situation classification, and stores the optimal control value (air conditioning control value) for each air conditioner 4 in each situation indicated by the situation classification determined by the situation recognition unit 211, and the amount of air conditioning power consumption when each air conditioner 4 executes that air conditioning control value. Here, the air conditioning control value is a parameter for controlling the air conditioner 4, and includes at least the temperature (target temperature), and may also include air volume, air direction, etc. In this embodiment, the parameters of the air conditioning control value will be described as the target temperature and air volume.

[0039] The information stored in this control value-power correspondence information 233, which relates the optimal air conditioning control values ​​(target temperature, air volume, etc.) for each situation classification and the amount of air conditioning power consumed when they are executed, can be obtained using a method that uses past performance data (stored in the memory unit 23 as operation history information 232) or a rule-based calculation method, but in this embodiment, an example of calculation by constructing a learning model (air conditioning control learning model) will be described below.

[0040] <<Generation process of control value-power amount correspondence information>> The control value-power correspondence information generating unit 214 generates a learning model (air-conditioning control learning model) by executing a learning phase and an operation phase, which will be described below. First, in the learning phase, the control value-power correspondence information generator 214 randomly generates air conditioning control values ​​(target temperature, air volume, etc.) for each situation classification up to a predetermined number of times (N times). Then, the air conditioning controller 219 (air conditioning control execution unit 219a) operates each air conditioner 4 using the randomly generated air conditioning control values. The control value-power correspondence information generation unit 214 stores, for each situation classification, external factor information, air conditioning control value, the reward (area reward) calculated when that control is executed (details will be described later), and information on air conditioning power consumption as operation history information 232. Then, when the learning phase reaches a predetermined number of times (N times), the control value-power correspondence information generation unit 214 refers to the operation history information 232, and for each situation classification, takes in external factor information, air conditioning control values, and rewards (area rewards), generates air conditioning control learning data, and trains the learning model (air conditioning control learning model).

[0041] Furthermore, after a predetermined number of times (N times) in the learning phase, the control value-power-amount correspondence information generation unit 214 outputs air conditioning control values ​​(target temperature, air volume, etc.) by inputting external factor information into the air conditioning control learning model for each situation classification, and stores information on the reward (area reward) and air conditioning power consumption when control of the air conditioner 4 is executed using that air conditioning control value as operation history information 232. Then, when a condition based on a predetermined reward (described below) is met in the air conditioning control learning model for the corresponding situation classification, the control value-power-amount correspondence information generation unit 214 ends the learning phase and transitions to the operation phase.

[0042] Here, the reward is an index for evaluating the results of controlling the air conditioners 4 according to the calculated air-conditioning control values, and the reward (temperature reward) is calculated as an indication of how close the target temperature has been reached. In addition, the reward is set as an area reward as an index for evaluating each air-conditioning area 40, and an overall reward as an index for evaluating the room 100 as a whole. The area reward is calculated, for example, based on the difference between the target temperature and the temperature after control of the air conditioner 4 for a specified time. Specifically, assume that the temperature (area average temperature) of the air-conditioned area 40 at the start of control is 38 degrees, and the target temperature is 31 degrees. If the temperature after control is 32 degrees, this is 1 degree higher than the target temperature, so the reward is "90%." Note that here, if the temperature is 1 degree lower than the target temperature, the reward is calculated as "-10%."

[0043] The overall reward is an index for determining whether the air conditioning control of the entire room 100 is successful. This overall reward is used to determine whether the air conditioning control of the entire room 100 is successful or not, depending on whether the reward (overall reward) calculated according to a predetermined logic using the area rewards is equal to or greater than a predetermined threshold (pass threshold). The predetermined logic may be, for example, that the average value of each area reward is equal to or greater than a predetermined threshold (pass threshold), and may be set arbitrarily.

[0044] If the calculated overall reward in the air conditioning control learning model for the corresponding Situation classification exceeds a predetermined pass threshold and is determined to be pass, the control value power amount correspondence information generation unit 214 ends the learning phase and transitions to the operation phase. If the control value-power-amount correspondence information generation unit 214 determines that the overall remuneration is acceptable, it acquires the air conditioning control values ​​(target temperature, air volume, etc.) and the power consumption (air conditioning power consumption) of each air conditioner 4 during that air conditioning control for each situation classification, and generates control value-power-amount correspondence information 233. The control value-power correspondence information generating unit 214 generates the control value-power correspondence information 233 in advance of the operation stage and stores it in the storage unit 23 .

[0045] The supercooling power correspondence information generation unit 215 operates in a control mode (hereinafter referred to as the "supercooling control mode") in which each control parameter of the configurable control values ​​of the air conditioner (e.g., temperature, air volume, etc.) is set to a predetermined threshold value (predetermined control intensity) or higher to increase the cooling capacity. As the supercooling control mode, a predetermined threshold value is set for the capacity of the air conditioner 4, such as 80% of the maximum rotation speed of the fan of the air conditioner 4. As the configurable air conditioning parameters of the air conditioner 4, settings are made such as lowering the set temperature to a predetermined temperature or lower, raising the air volume intensity to a predetermined value or higher, etc. Then, the supercooling power correspondence information generation unit 215 generates, for each situation, information on the increase in air conditioning power consumption when the air conditioner 4 is controlled in the supercooling control mode (air conditioning power consumption increase information), as supercooling power correspondence information 234. The supercooling power amount correspondence information generating unit 215 generates the generated supercooling power amount correspondence information 234 in advance of the operation stage and stores it in the storage unit 23 .

[0046] The total in-room power consumption calculation unit 216 sums up the server power consumption for each server area 30 in the virtual resource placement pattern calculated by the placement pattern calculation unit 212, and calculates the sum (total in-room power consumption) of the total server power consumption, which is the sum of the total value, and the air conditioning power consumption obtained from the control value power consumption correspondence information 233 stored in the memory unit 23. The total room power consumption calculation unit 216 selects the smallest value of the air conditioning power consumption in the control value-power consumption correspondence information 233 within the range that satisfies the reward condition as the air conditioning power consumption for that Situation. The total in-room power consumption calculation unit 216 transmits the calculated total in-room power consumption amount in the room to the power amount control device 10.

[0047] The supercooling-related information generating unit 217 generates supercooling-related information indicating information required for the power amount control device 10 to select a room in which supercooling using surplus power is to be performed. The supercooling-related information is set according to the supercooling room selection method of the power amount control device 10. For example, if the supercooling room selection method is to select a room from those with high power efficiency (details will be described later), information on the total power consumption of the servers required for calculating the power efficiency (specifically, the total power consumption of the CPU server, the total power consumption of the GPU server, the total power consumption of the accelerator, etc.) is generated as the supercooling-related information. On the other hand, if the supercooling room selection method is one in which the server heat generation amount is above a predetermined value and the server heat generation amount continues to be above the predetermined value from the next turn onwards (details will be described later), the supercooling related information generation unit 217 generates supercooling related information if the room control device 20 has schedule information indicating that this condition is met or information indicating past trends.

[0048] The load placement control unit 218 places virtual resources (VMs, containers, etc.) on each server 3 based on the load placement pattern for each server 3.

[0049] The air conditioning control unit 219 controls the air conditioning (temperature, air volume, etc.) of each air conditioner 4, and includes an air conditioning control execution unit 219a and a supercooling air conditioning control unit 219b. The air conditioning control execution unit 219a controls each air conditioner 4 based on information about air conditioning control values ​​(target temperature, air volume, etc.) in a certain situation in the arrangement pattern calculated by the arrangement pattern calculation unit 212. When the air conditioner 4 in its own room 100 is selected as the air conditioner for supercooling air conditioning (when it receives a notification (supercooling control notification) that it is the target of supercooling control), the supercooling air conditioning control unit 219b performs air conditioning control in the supercooling control mode described above for that air conditioner 4. For each situation classification, the air conditioning control execution unit 219a stores external factor information, air conditioning control values ​​(target temperature, air volume, etc.), rewards obtained when the control is executed, and information on air conditioning power consumption as operation history information 232. The air conditioning control execution unit 219a may also store the date and time when the air conditioning control was executed as operation history information 232.

[0050] <Power consumption control device> Next, the power amount control device 10 according to this embodiment will be described. FIG. 5 is a functional block diagram showing an example of the configuration of the power amount control device 10 according to this embodiment. The power amount control device 10 calculates the power consumption of the entire DC (total DC power consumption) by acquiring information on the total power consumption in each room 100 ("total room power consumption", which is the sum of server power consumption and air conditioning power consumption) from each room control device 20 and adding up the information.The power amount control device 10 then calculates the surplus power from the difference between the planned power supply amount, including the renewable energy supply amount, for the relevant time period and the total DC power consumption.The power amount control device 10 uses this surplus power for air conditioning supercooling control in each room. The power amount control device 10 is configured by a computer including a control unit 11, an input / output unit 12, and a storage unit 13.

[0051] The input / output unit 12 inputs and outputs information between each in-room control device 20, an external system management device (not shown), etc. This input / output unit 12 is composed of a communication interface that transmits and receives information via a communication line, and an input / output interface that inputs and outputs information between an input device such as a keyboard and an output device such as a monitor, neither of which is shown.

[0052] The storage unit 13 is configured by a hard disk, a flash memory, a RAM (Random Access Memory), or the like. The storage unit 13 temporarily stores programs for executing the functions of the control unit 11 and information required for the processing of the control unit 11.

[0053] The control unit 11 is responsible for all the processing executed by the power amount control device 10, and as shown in Figure 5, is composed of a planned power supply amount acquisition unit 111, a load distribution ratio setting unit 112, a surplus power amount calculation unit 113, and a supercooled room selection unit 114.

[0054] The planned power supply amount acquisition unit 111 acquires the planned power supply amount, including the amount of renewable energy supply, to be supplied to the entire DC 1000 in a relevant time period (predetermined time period) from an external system management device (not shown) or the like.

[0055] The load distribution ratio setting unit 112 acquires the total load amount (DC total load amount) to be processed within the DC 1000 from an external system management device (not shown) or the like. Then, the load distribution ratio setting unit 112 determines the load distribution ratio to each room 100 based on a predetermined load distribution logic. As a predetermined load distribution logic, for example, logic such as distributing the load equally to each room 100, distributing the load according to the processing capacity of each room, or distributing the load according to the operating rate or usage rate of the server 3 in each room 100 is set in advance. Then, the load distribution ratio setting unit 112 transmits the total DC load amount and the load distribution ratio of each room 100 to each of the in-room control devices 20.

[0056] The surplus power calculation unit 113 acquires information on the total in-room power consumption, which is the sum of the server power consumption and the air-conditioning power consumption, as the total power consumption in each room 100 from each in-room control device 20. Then, the surplus power calculation unit 113 calculates the total DC power consumption, which indicates the power consumption of the entire DC, by summing up the total in-room power consumption of each room 100. The surplus power calculation unit 113 calculates the amount of surplus power from the difference between the planned power supply amount including the renewable energy supply amount for the relevant time period, acquired by the planned power supply amount acquisition unit 111, and the total DC power consumption amount.

[0057] The surplus power calculation unit 113 transmits a supercooling control notification of the calculated surplus power amount to the room that is the target of the supercooling control, thereby causing the room control device 20 that received the notification to execute supercooling control of the air conditioner 4 for the room 100 that it is responsible for. When the supercooling room selection unit 114 performs the process of selecting a room for which supercooling control is to be executed, the surplus energy calculation unit 113 transmits a supercooling control notification to the selected room.

[0058] The supercooling room selection unit 114 determines the room in which supercooling control utilizing the amount of surplus power is to be performed based on a predetermined supercooling room selection logic. As the supercooled room selection logic, for example, the following "selection logic 1" and "selection logic 2" are used.

[0059] <Selection Logic 1> "Selection logic 1" is a logic that "prioritizes allocation to rooms with high power efficiency per load unit within the room." Here, "power efficiency" is defined by the following formula (1). Power efficiency = Server heat generation / (Server power consumption + Air conditioning power consumption) ...Equation (1)

[0060] The supercooling room selection unit 114 calculates this power efficiency for each room. In this formula (1), (server power consumption amount+air-conditioning power consumption amount) corresponds to the total power consumption amount in the room described above.

[0061] On the other hand, the server heat generation amount is the total heat generation amount in each room 100 (total room heat generation amount), and is defined by the following formula (2). Total heat generation in the room = CPU heat coefficient (kc) × total power consumption of the CPU server + GPU heat coefficient (kg) × total power consumption of the GPU server + accelerator heat coefficient (ka) × total power consumption of the accelerator ...Equation (2)

[0062] Here, the CPU heat coefficient (kc), GPU heat coefficient (kg), and accelerator heat coefficient (ka) are preset coefficients. Furthermore, if the server 3 in the room 100 is composed of, for example, a CPU server, a GPU server, an accelerator, etc., information on the total power consumption of the CPU server, the total power consumption of the GPU server, and the total power consumption of the accelerator in each room 100 (supercooling-related information including the power consumption of the server) is obtained from the in-room control device 20 in each room 100 as supercooling-related information. Then, the power efficiency of each room 100 (room power efficiency) is calculated using the following formula (3). Room power efficiency = total heat generated in the room / total power consumption in the room ...Equation (3)

[0063] The supercooling room selection unit 114 calculates the room power efficiency using the above formula (3) for each room 100. Then, the supercooling room selection unit 114 allocates the surplus power amount to the supercooling control of the air conditioning in order from the room 100 with the highest room power efficiency. Specifically, the supercooling room selection unit 114 selects the room 100 with the highest room power efficiency, and transmits a control instruction in the supercooling control mode (supercooling control notification) and information on the amount of surplus power to the selected room 100. The room control device 20 refers to the supercooling power amount correspondence information 234 and, if the acquired surplus power amount is equal to or greater than the increase in air conditioning power consumption due to supercooling, determines to execute the supercooling control mode and transmits information on the increase in air conditioning power consumption to the power amount control device 10. Next, the supercooling room selection unit 114 updates the amount of surplus power by subtracting the acquired increase in air-conditioning power consumption from the current amount of surplus power, and allocates the updated amount of surplus power to the room 100 with the next highest room power efficiency. The supercooling room selection unit 114 continues this process until no more surplus power can be allocated, thereby determining the room 100 to be supercooled.

[0064] <Selection Logic 2> "Selection Logic 2" is a logic that "prioritizes allocation to rooms where the current server heat generation per air conditioner unit is above a predetermined value, and where the server heat generation per air conditioner unit will continue to be above the predetermined value from the next turn onwards." This is based on the fact that power efficiency can be improved by prioritizing supercooling control for rooms where the load (high load) that causes the server heat generation to be above a predetermined value continues. Below, it will be explained that the more continuously high the load in each turn, the higher the power efficiency due to the utilization of surplus power, including renewable energy.

[0065] [Verification results] For each of four rooms (Rooms A, B, C, and D) in the same environment, we created schedules with four different load fluctuation patterns (two turns: one turn is 30 minutes), and measured the amount of power consumed by the air conditioning when supercooling was performed and when normal control was performed without supercooling. Each room was equipped with two air conditioners 4. For each load fluctuation pattern, the power consumption of each air conditioner 4 was measured for a pattern in which supercooling control was performed in the first turn, and a pattern in which supercooling control was not performed in the first turn and normal control was performed. The average temperature in each room when supercooling started was around 19°C.

[0066] Room A (case where high load occurs continuously) 6A is a diagram showing the load fluctuation pattern of Room A. In the first turn (predetermined time period), a load (high load) of 60 kW (30 kW per unit) was applied to the entire room, and in the second turn (next predetermined time period), a load (high load) of 80 kW (40 kW per unit) was applied to the entire room. In other words, Room A is a case where high loads occur continuously.

[0067] Room B (case where high load does not occur continuously) Figure 6B shows the load fluctuation pattern for Room B. In the first turn, a load (high load) of 60 kW (30 kW per unit) was applied to the entire room, and in the second turn, a load (low load) of 30 kW (15 kW per unit) was applied to the entire room. In other words, Room B is a case where high loads do not occur continuously.

[0068] Room C (Low load on the first turn, increased load on the second turn (Part 1)) Figure 6C shows the load fluctuation pattern for Room C. In the first turn, a low load of 30 kW (15 kW per unit) was applied to the entire room, and in the second turn, a low load of 60 kW (30 kW per unit) was applied to the entire room. In other words, Room C was under low load in the first turn, and the load increased in the second turn.

[0069] Room D (Low load on the first turn, increased load on the second turn (part 2)) Figure 6D shows the load fluctuation pattern for Room D. In the first turn, a low load of 30 kW (15 kW per unit) was applied to the entire room, and in the second turn, a low load of 80 kW (40 kW per unit) was applied to the entire room. In other words, Room D was under a low load in the first turn, and the load was further increased in the second turn.

[0070] In the above four load fluctuation patterns, the power consumption of each air conditioner 4 was measured and analyzed for the cases where supercooling control was performed in the first turn and where supercooling control was not performed in the first turn. The results are shown in Figures 7A to 7D for Rooms A to D.

[0071] The evaluation results will be explained using FIG. 7A as an example. The "Server Load" column shows the overall load (server heat generation) placed on that room (Room A). "Phase" indicates whether it is the first or second turn, and the data surrounded by a thick solid line in the top two rows (symbol α) indicates data that was supercooled in the first turn. The data surrounded by a thick dotted line in the bottom two rows (symbol β) indicates data that was not supercooled in the first turn.

[0072] "Air conditioner '1'" and "Air conditioner '2'" indicate the power consumption of each air conditioner 4 in that turn. "Total power consumption (kW)" indicates the total power consumption (kW) of air conditioners "1" and "2" including the first and second turns. For example, in the case of air conditioners "1" and "2" (symbol α) that performed supercooling, the total power consumption is "16.57 = 5.03 + 5.38 + 3.04 + 3.12".

[0073] The "amount of renewable energy" ("Y" described below) indicates the amount of renewable energy (amount of electricity consumed) used in the first and second turns. In this case, it is "5.22" (kW). The "normal power reduction amount" ("X" described below) indicates the amount of normal power reduction achieved by performing supercooling control, including renewable energy. In this case, it is "5.52 = 16.87 - (16.57 - 5.22)" (kW). "Second turn power reduction rate [%]" indicates the power reduction rate for the second turn due to supercooling control. In this case, it is "47.26 (%) = ((4.99 + 6.69) - (3.04 + 3.12)) / (4.99 + 6.69) × 100".

[0074] "Power gain from renewable energy [%]" is calculated by dividing "normal power reduction amount (X)" by "amount of renewable energy (Y)" x 100. For the load pattern of Room A, the result is "105.75 (%) = 5.52 / 5.22". This power gain from renewable energy is an indicator that the higher the value, the higher the utilization efficiency of renewable energy (details will be provided later). "Total power consumption ratio [%]" indicates the ratio of total power consumption when supercooling is performed to the total power consumption without supercooling, which is 100%. For the load pattern of Room A, this is "98.22 (%) = 16.57 / 16.87".

[0075] 7A to 7D, the value of "second turn power reduction rate" indicates that the amount of power consumption in the second turn is reduced by supercooling in all load variation patterns.

[0076] On the other hand, in the "power gain of renewable energy" category, it was shown that the power gain of renewable energy was highest in Room A, which has a load pattern where high load continues continuously. As shown in Figure 8, in the case where high load continues (60kW → 80kW), the values ​​of "normal power reduction (X)" and "renewable energy amount (Y)" are almost the same, whereas in other cases (60kW → 30kW, 30kW → 60kW, 30kW → 80kW), "normal power reduction (X)" is lower than "renewable energy amount (Y)". Figure 9 compares the power gain of renewable energy for each load pattern. As shown in Figure 9, the load pattern where high load continues continuously has a higher power gain of renewable energy. In other words, by performing supercooling air conditioning control, renewable energy is converted into a cooling effect within DC1000, and air conditioning power consumption is reduced more efficiently.

[0077] From the above verification results, when "selection logic 2" is adopted, the supercooled room selection unit 114 performs a process of preferentially allocating rooms that are currently assigned a heat output from the assigned server per air conditioner unit (which may be "the heat output from all servers in the room") that is equal to or exceeds a predetermined value (i.e., a room with a high load) and that will continue to have a heat output from the assigned server per air conditioner unit (the heat output from all servers in the room) that is equal to or exceeds a predetermined value from the next turn onwards.

[0078] When "selection logic 2" is adopted, the supercooling room selection unit 114 collects supercooling-related information from the in-room control device 20 of each room 100, such as schedule information for rooms that will be continuously heavily loaded, and information indicating that the high load will continue based on past operational results stored in the operation history information 232 of the in-room control device 20, thereby extracting rooms that will be continuously heavily loaded and selecting the rooms 100 in which supercooling control should be preferentially executed.The supercooling room selection unit 114 then outputs information on the selected rooms 100 to the surplus energy calculation unit 113.

[0079] <Processing flow> Next, the flow of processing executed by the power amount control system 1 will be described. FIG. 10 is a sequence diagram showing the flow of processing executed by the power amount control system 1 including the power amount control device 10 according to this embodiment. Here, it is assumed that the memory unit 23 of each room control device 20 has a server power consumption learning model 231, operation history information 232, control value power consumption correspondence information 233, and supercooling power consumption correspondence information 234 pre-stored therein.

[0080] First, the planned power supply amount acquisition unit 111 of the power amount control device 10 acquires the planned power supply amount including the planned renewable energy supply amount for the relevant time period from an external device (such as a system management device) (step S1). Furthermore, the load distribution ratio setting unit 112 acquires the total load amount (DC total load amount) to be processed in the DC 1000 from an external device (such as a system management device) (step S2).

[0081] Next, the load distribution ratio setting unit 112 determines the load distribution ratio to each room 100 based on a predetermined load distribution logic. The load distribution ratio setting unit 112 transmits the total DC load amount and the load distribution ratio set for each room 100 to each in-room control device 20 (step S3).

[0082] Next, the placement pattern calculation unit 212 of each in-room control device 20 obtains information on the load to be allocated to the room it is responsible for based on information on the load allocation ratio of each room 100 and information on the total load (total DC load) obtained from the power amount control device 10. Then, the allocation pattern calculation unit 212 calculates an allocation pattern for allocating the virtual resources to each server 3 in the user's own room 100 (step S4).

[0083] Next, the server power consumption estimation unit 213 of each in-room control device 20 estimates the power consumption of each server 3 in the arrangement pattern calculated by the arrangement pattern calculation unit 212 using the server power consumption learning model 231. Then, the server power consumption estimation unit 213 calculates the server power consumption for each server area 30 by adding up the server power consumption of each server 3 in the server area 30 based on the server layout configuration for each server area 30 (step S5).

[0084] Next, the situation recognition unit 211 of each in-room control device 20 acquires information (external factor information) on the outside air temperature, the air intake temperature of the server area, and the server power consumption amount for each server area 30, and determines the situation classification (step S6).

[0085] Next, the total in-room power consumption calculation unit 216 of each in-room control device 20 sums up the server power consumption for each server area 30, and calculates the sum (total in-room power consumption) of the total server power consumption, which is the sum of the total value, and the air conditioning power consumption obtained from the control value power consumption correspondence information 233 stored in the memory unit 23 (step S7). Then, the total in-room power consumption calculation unit 216 transmits the calculated total in-room power consumption amount in the room to the power amount control device 10.

[0086] Next, the surplus power calculation unit 113 of the power amount control device 10 calculates the total DC power consumption, which indicates the power consumption of the entire DC, by adding up the total in-room power consumption amounts acquired from each in-room control device 20. Next, the surplus power calculation unit 113 calculates the surplus power from the difference between the planned power supply amount including the renewable energy supply amount in the relevant time period and the total DC power consumption amount (step S8).

[0087] Meanwhile, the supercooling-related information generation unit 217 of each room control device 20 generates supercooling-related information indicating information required for selecting a room in which supercooling using surplus power will be performed (information indicating that high load will continue) based on information on the total power consumption for each type of server (e.g., CPU server, GPU server, accelerator), schedule information on the load on each room, past operation history, etc., in accordance with the supercooling selection method (selection logic) of the power amount control device 10, and transmits the information to the power amount control device 10 (step S9).

[0088] Next, the supercooling room selection unit 114 determines the room in which supercooling using the surplus power is to be performed based on a predetermined supercooling room selection logic (step S10). For example, when "selection logic 1" is set, the supercooled room selection unit 114 gives priority to rooms with high power efficiency per load unit within the room for allocation. On the other hand, when "selection logic 2" is set, the supercooled room selection unit 114 gives priority to rooms where the current server-in-charge heat generation per air conditioner unit is equal to or greater than a predetermined value, and where the server-in-charge heat generation per air conditioner unit will continue to be equal to or greater than a predetermined value from the next turn onwards.

[0089] Next, the surplus energy calculation unit 113 transmits a supercooling control notification to the in-room control device 20 of the room 100 that the supercooling room selection unit 114 has determined to be the target of the supercooling control. Then, the in-room control device 20 that has received the supercooling control notification executes supercooling control for the air conditioner 4 in addition to controlling the load amount allocated to its own room 100 in that turn (step S11).

[0090] In this way, the power consumption control system 1 utilizes surplus power, including renewable energy, to perform supercooling control of the air conditioner 4 to create a cooling effect, thereby reducing the amount of air conditioning power consumption required for cooling heat generated within DC1000.

[0091] <Hardware configuration> The power amount control device 10 and the room control device 20 according to this embodiment are realized by a computer 900 having a configuration as shown in FIG. 11, for example. 11 is a hardware configuration diagram showing an example of a computer 900 that realizes the functions of the power amount control device 10 and the room control device 20 according to this embodiment. The computer 900 has a CPU (Central Processing Unit) 901, a ROM (Read Only Memory) 902, a RAM 903, an HDD (Hard Disk Drive) 904, an input / output I / F (Interface) 905, a communication I / F 906, and a media I / F 907.

[0092] The CPU 901 operates based on a program stored in the ROM 902 or the HDD 904, and performs control by the control unit. The ROM 902 stores a boot program executed by the CPU 901 when the computer 900 starts up, programs related to the hardware of the computer 900, and the like.

[0093] The CPU 901 controls an input device 910 such as a mouse or keyboard, and an output device 911 such as a display or printer, via an input / output I / F 905. The CPU 901 acquires data from the input device 910 via the input / output I / F 905, and outputs generated data to the output device 911. Note that a GPU (Graphics Processing Unit) or the like may be used as a processor together with the CPU 901.

[0094] The HDD 904 stores programs executed by the CPU 901 and data used by the programs. The communication I / F 906 receives data from other devices via a communication network (e.g., NW (Network) 920) and outputs the data to the CPU 901, and also transmits data generated by the CPU 901 to other devices via the communication network.

[0095] The media I / F 907 reads a program or data stored in the recording medium 912 and outputs it to the CPU 901 via the RAM 903. The CPU 901 loads a program related to a target process from the recording medium 912 onto the RAM 903 via the media I / F 907, and executes the loaded program. The recording medium 912 is an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase Change Rewritable Disc), a magneto-optical recording medium such as an MO (Magneto Optical Disk), a magnetic recording medium, a semiconductor memory, or the like.

[0096] For example, when the computer 900 functions as the power amount control device 10 and the room control device 20 of the present invention, the CPU 901 of the computer 900 executes a program loaded onto the RAM 903 to realize the functions of the power amount control device 10 and the room control device 20. The HDD 904 also stores data in the RAM 903. The CPU 901 reads and executes a program related to a target process from the recording medium 912. Alternatively, the CPU 901 may read a program related to a target process from another device via a communication network (NW 920).

[0097] <Effects> The effects of the power amount control device 10 and the like according to the present invention will be described below. The power consumption control device of the present invention is a power consumption control device 10 that is communicatively connected to room control devices 20 for each room 100 in a data center (DC1000) in which a plurality of rooms 100 are installed, each of which controls the servers 3 and air conditioners 4 in the room 100, and controls the power consumption of each room 100.It is characterized by having: a planned power supply amount acquisition unit 111 that acquires a planned power supply amount including the amount of renewable energy supply during a specified time period; and a surplus power amount calculation unit 113 that acquires from each room control device 20 a total in-room power consumption which is the sum of the server power consumption and air conditioning power consumption in each room 100, calculates a DC total power consumption which indicates the power consumption of the entire data center by summing the total in-room power consumption of each room 100, calculates surplus power which is the difference between the planned power supply amount and the DC total power consumption, and transmits a supercooling control notification to the room control device 20 to execute supercooling control by the air conditioner 4 of the room 100 using the surplus power amount.

[0098] In this way, the power amount control device 10 can improve the power utilization efficiency of the air conditioning power consumption within DC1000 by utilizing surplus power including renewable energy to perform supercooling control of the air conditioner 4.

[0099] The power control device 10 further includes a supercooling room selection unit 114 that selects a room 100 in which supercooling control using surplus power is to be performed. The supercooling room selection unit 114 acquires supercooling-related information, including the power consumption of the server 3, from each of the in-room control devices 20, calculates the total room heat generation amount indicating the overall heat generation amount in the room 100, calculates the power efficiency for each room 100 by dividing the total room heat generation amount by the total power consumption in the room, and allocates the surplus power in order of the calculated power efficiency.

[0100] In this way, the power amount control device 10 allocates surplus power in order of the rooms with the highest power efficiency and executes supercooling control, thereby improving the cooling effect and increasing the effect of reducing air conditioning power consumption.

[0101] The power amount control device 10 further includes a supercooling room selection unit 114 that selects a room 100 for which supercooling control using surplus power is to be performed, and the supercooling room selection unit 114 allocates surplus power by giving priority to a room 100 in which the server heat generation amount per air conditioner unit in a specified time period is equal to or greater than a specified value, and in which the server heat generation amount per air conditioner unit will continue to be equal to or greater than the specified value in the next turn, which indicates the next specified time period after the specified time period.

[0102] In this way, the power consumption control device 10 can preferentially select rooms in which the server heat generation amount is above a predetermined value and in which the server heat generation amount will continue to be above the predetermined value in the next turn as rooms in which to perform supercooling control, thereby increasing the effectiveness of reducing air conditioning power consumption.

[0103] The present invention is not limited to the above-described embodiments, and many modifications can be made by a person having ordinary skill in the art within the technical concept of the present invention. [Explanation of symbols]

[0104] 1. Power control system 3 Server 4 Air conditioner 10. Electricity amount control device 11,21 Control unit 12,22 Input / output section 13,23 Storage section 20 In-room control device 100 rooms 111 Power supply schedule acquisition unit 112 Load distribution ratio setting unit 113 Surplus power calculation unit 114 Supercooling room selection section 211 Situational Awareness Department 212 Placement pattern calculation unit 213 Server Power Consumption Estimation Unit 214 Control value power amount correspondence information generation unit 215 Supercooling power amount correspondence information generation unit 216 Total energy consumption calculation unit in room 217 Supercooling-related information generation unit 218 Load placement control unit 219 Air conditioning control unit 219a Air conditioning control execution unit 219b Supercooling air conditioning control unit 231 Server Power Consumption Learning Model 232 Operational History Information 233 Control value power amount correspondence information 234 Supercooling power consumption information 1000 Data Centers (DC)

Claims

1. A power amount control device is communicatively connected to a room control device for each room in a data center (DC) in which a plurality of rooms are installed, each room having a plurality of servers and one or more air conditioners arranged therein, and controls the amount of power consumption of each of the rooms, a planned power supply amount acquisition unit that acquires a planned power supply amount including a renewable energy supply amount for a predetermined time period; an excess power calculation unit that acquires from each of the in-room control devices a total in-room power consumption that is the sum of the server power consumption and the air conditioning power consumption in each room, calculates a total DC power consumption that indicates the power consumption of the entire data center by summing the total in-room power consumption of each room, calculates a surplus power amount that is the difference between the planned power supply amount and the total DC power consumption, and transmits a supercooling control notification to the in-room control device that causes the air conditioner in the room to perform supercooling control using the surplus power amount; An electric power amount control device comprising:

2. a supercooling room selection unit for selecting a room in which supercooling control based on the surplus power amount is to be performed, the supercooling room selection unit acquires supercooling-related information including the power consumption of the server from each of the in-room control devices, calculates a room total heat generation amount indicating the overall heat generation amount in the room, calculates power efficiency for each of the rooms by dividing the room total heat generation amount by the in-room total power consumption, and allocates the surplus power amount in order of the calculated power efficiency, starting from the room with the highest; The electric energy control device according to claim 1 ,

3. a supercooling room selection unit for selecting a room in which supercooling control based on the surplus power amount is to be performed, the supercooling room selection unit allocates the surplus power by giving priority to a room in which the server heat generation amount per air conditioner unit in the room during the specified time period is equal to or greater than a specified value, and in which the server heat generation amount per air conditioner unit will continue to be equal to or greater than the specified value in the next turn indicating the next specified time period after the specified time period; The electric energy control device according to claim 1 ,

4. A power control method for a power amount control device that is communicatively connected to a room control device for each room that controls the servers and air conditioners in a data center (DC) in which a plurality of rooms are installed, each room having a plurality of servers and one or more air conditioners, and that controls the amount of power consumed by each of the rooms, comprising: The power amount control device includes: acquiring a planned power supply amount including a renewable energy supply amount for a predetermined time period; acquiring from each of the in-room control devices a total in-room power consumption, which is the sum of the server power consumption and the air-conditioning power consumption in each room, calculating a total DC power consumption, which indicates the power consumption of the entire data center, by adding up the total in-room power consumption of each room, calculating a surplus power amount, which is the difference between the planned power supply amount and the total DC power consumption, and transmitting a supercooling control notification to the in-room control device to cause the air conditioner in the room to perform supercooling control using the surplus power amount; A power amount control method comprising:

5. A program for causing a computer to function as the power amount control device according to any one of claims 1 to 3.

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