CN104919484A - Energy management device and energy management system - Google Patents

Abstract

An energy-management device (11) in this energy-management system (10) is provided with the following: an acquisition means (transmission/reception functionality) that acquires information on the load current being drawn by air-conditioning devices (41a through 41n) installed in a building and information on weather conditions in the region where said building is located; an external-heat-load calculation unit (11d) that uses the acquired weather-condition information to calculate the external heat load flowing into the building from outside; and an internal-heat-load estimation unit (11b) that uses the acquired load current to estimate an air-conditioning heat load, i.e. the heat load imposed by the air-conditioning devices (41a through 41n), and uses the difference between said air-conditioning heat load and the calculated external heat load to estimate an internal heat load excluding the air-conditioning heat load for the inside of the building (i.e., an indoor-unit heat load plus a human-body heat load).

Description

Energy management device and energy management system

technical field

The present invention relates to an energy management device and an energy management system for estimating energy consumption in a building to perform efficient energy management.

Background technique

In recent years, energy management systems (EMS: Energy Management System) have been introduced into buildings such as office buildings and commercial buildings. It is known that EMS targets building equipment such as air-conditioning equipment, lighting equipment, disaster prevention equipment, and anti-theft equipment in buildings (such as buildings), and monitors the indoor environment, energy consumption, and status of each device and equipment through various sensors and instruments. Optimum operation management and control of each device and equipment.

In addition, in recent years, the importance of saving energy (abbreviated as energy saving) and the importance of energy management using EMS have increased due to concerns about the global environment.

For example, Patent Document 1 proposes a method of effectively managing energy by collecting energy data and operating conditions of various devices in a building facility and monitoring them in real time, or analyzing and displaying energy consumption trends based on history. .

On the other hand, in Patent Document 2, it is proposed to calculate the thermal load of the indoor environment and the air-conditioning equipment based on the physical model, and adopt the indoor environment/air-conditioning simulation used in the estimation of the air-conditioning load, the design of the air-conditioning system, etc. (refer to non-patent Literature), a method for efficient air conditioning control.

Furthermore, Patent Document 2 describes that energy consumption, comfort, cost, etc. are evaluated by performing simulations for several hours to a day based on information on weather conditions, measured values of the indoor environment, and an operation plan of air-conditioning equipment. , a method of supporting the manager's operation plan formulation. According to this method, it is possible to achieve control that balances comfort, energy saving, and cost saving.

Patent Document 1: Japanese Patent Laid-Open No. 2011-248568

Patent Document 2: Japanese Patent Laid-Open No. 2011-141092

Non-Patent Document 1: Air Conditioning and Sanitary Engineering Society "Air Conditioning and Sanitary Engineering Handbook 14th Edition" p443-p469

Contents of the invention

However, in the case of controlling the air conditioner according to the method of Patent Document 2, in order to accurately simulate the indoor environment/air conditioning load, it is necessary to accurately set the internal thermal load in the computer performing the simulation. Indoor equipment such as lighting fixtures and OA (Office Automation) equipment generate a large heat load. In order to distinguish these heat loads with high precision, it is necessary to measure and grasp the operation status and power consumption of each indoor device by using an EMS such as that disclosed in Patent Document 1. However, in order to individually measure all the operating conditions and power consumption of each device in the room, a plurality of expensive power meters and the like are required, so there is a problem that the cost is greatly increased and it is difficult to implement.

Therefore, a configuration is generally employed in which only the power consumption of the entire building is measured with a power meter. Even in buildings with slightly higher added value, the structure is limited to measuring power consumption by installing a power meter on each floor.

In addition, in the case of a general office building, the human body heat load of indoor occupants has a large influence on the same level as the heat generated by indoor equipment, but there is a problem that there is no means to directly measure the human body heat load.

In recent years, there is a method of estimating the heat load of the human body in combination with an entry and exit management system introduced for safety reasons, but the cost is still high. In addition, the access control system is not something that can be introduced in any facility, so there is a problem that it is difficult to distinguish the heat load of the human body especially in small and medium-sized buildings where a large-scale building management system is not installed. Due to these problems, there is a problem that, when performing energy demand prediction in buildings, it cannot be performed appropriately at low cost.

The present invention has been made in view of such circumstances, and an object of the present invention is to provide a low-cost and high-accuracy estimate of the internal heat load of each device in the building, the human body, etc., and can perform low-cost and suitable internal heat transfer in the building. An energy management device for energy demand forecasting and an energy management system.

In order to solve the above-mentioned problems, the present invention includes: an acquisition unit that acquires information on the operation of air-conditioning equipment installed in a building and information on weather conditions in the construction area of the building; and an external heat load calculation unit that uses the acquired information. The information on the weather conditions is used to calculate the external heat load flowing from the outside to the inside of the building; and the internal heat load estimation unit estimates the heat load of the air conditioner based on the acquired operation information of the air conditioner. The air-conditioning heat load estimates an internal heat load in the building other than the air-conditioning heat load based on a difference between the air-conditioning heat load and the calculated external heat load.

According to the present invention, it is possible to provide an energy management device and an energy management system capable of estimating internal thermal loads of various devices and human bodies in a building at low cost and with high accuracy, and capable of predicting energy demand in a building at low cost and suitably.

Description of drawings

FIG. 1 is a block diagram showing the configuration of an energy management system according to an embodiment of the present invention.

FIG. 2 is a block diagram showing a configuration example of an energy management device in the energy management system according to the present embodiment.

Fig. 3 is a cross-sectional view of a building office part showing typical thermal loads affecting indoor environments in one office room in a building.

FIG. 4 is a graph showing an example of an internal thermal load, an external thermal load, and an air-conditioning thermal load estimated by the energy management device.

5 is a graph showing an example of internal heat load (estimated value), indoor equipment power consumption (measured value), and human body heat load (estimated value) obtained by the energy management device.

Fig. 6 is a graph showing an example of a variation pattern of power consumption of indoor devices.

FIG. 7 is a graph showing an example of a variation pattern of indoor human body heat load.

FIG. 8 is a graph showing the energy demand prediction results obtained by the energy management device together with current fluctuations in various power consumptions.

Fig. 9 is a first flowchart for explaining the operation of predicting the energy demand of a building by the energy management system.

Fig. 10 is a second flowchart for explaining the operation of predicting the energy demand of a building by the energy management system.

Fig. 11 is a third flowchart for explaining the operation of predicting the energy demand of a building by the energy management system.

Fig. 12 is a fourth flowchart for explaining the operation of predicting the energy demand of a building by the energy management system.

(Symbol Description)

10: energy management system; 11: energy management device; 11a: energy demand forecasting unit (demand forecasting unit); 11b: internal heat load estimation unit; 11c: application database unit; 11d: external heat load calculation unit; 12: local area network; 13: Electric power measuring device; 14: Air-conditioning equipment controller (air-conditioning information acquisition unit); 15: Public network; 16: Weather information providing device; 31: Switchboard; 41a～41n: Air-conditioning equipment; 42, 43: Outdoor unit; , 42b...42m, 43a, 43b...43m: indoor unit; Q _EW : heat load of outer wall; Q _SR : heat load of sunlight; Q _G : heat load of window heat transfer; Q _INF : wind heat load of ventilation gap; Q _IW : Inner wall floor heat load; Q _E : indoor equipment heat load (equipment heat load); Q _H , 105: human body heat load; Q _AC , 101: air conditioning heat load; 102: external heat load; 103: internal heat load; 104: Indoor equipment power consumption (equipment power consumption); 104M: indoor equipment power consumption mode (indoor equipment power consumption variation mode); 105: human body heat load mode (human body heat load variation mode); 121: expected external air temperature; 122: Predict the power consumption of air-conditioning equipment; 123: predict the overall power consumption of the building; 124: power consumption of air-conditioning equipment; 125: the overall power consumption of the building (overall power consumption).

Detailed ways

Hereinafter, embodiments of the present invention will be described with reference to the drawings.

<Structure of Embodiment>

FIG. 1 is a block diagram showing the configuration of an energy management system 10 according to the embodiment of the present invention.

The energy management system 10 estimates heat loads of indoor equipment such as air conditioners, lighting fixtures, OA equipment, human bodies, etc. in a building (for example, a building) at low cost and with high accuracy, and appropriately predicts energy demand in the building. This energy management system 10 is configured to include an energy management device 11 , a power measurement device 13 and an air conditioner controller 14 connected to the energy management device 11 via a local area network 12 , and weather information connected to the energy management device 11 via a public network 15 . Means 16 are provided.

The power measuring device 13 is installed in a switchboard 31 in a building, and measures power consumption of at least electrical equipment in the entire building (whole building power consumption). The power measurement data 23 , which is the measured power consumption value of the entire building, is transmitted to the energy management device 11 via the local area network 12 .

The air conditioner controller 14 is connected to n (n is a natural number) air conditioners 41a to 41n, acquires the air conditioner operating data 24 as information on the operating conditions of each of the air conditioners 41a to 41n, and sends them to the energy management device 11 via the local area network 12. Here, the information on the operating status refers to information including measured values such as load current, suction and exhaust air temperatures during air conditioning, which are operating information of the air conditioners 41a to 41n. The operation information includes, in addition to the load current, information related to the operation, such as the rotational speed of the motor in each of the air conditioners 41a to 41n.

In addition, it is assumed that each of the air conditioners 41a to 41n is a packaged air conditioner in which an outdoor unit and an indoor unit are combined. Therefore, the first air conditioner 41 a is configured to include an outdoor unit 42 connected to the air conditioner controller 14 , and a plurality of indoor units 42 a , 42 b . . . 42 n connected to the outdoor unit 42 . The n-th air conditioner 41 n is also configured to include an outdoor unit 43 connected to the air conditioner controller 14 and a plurality of indoor units 43 a , 43 b . . . 43 n connected to the outdoor unit 43 .

In addition, in the packaged air conditioner, both the outdoor units 42 and 43 and the indoor units 42a to 42m and 43a to 43m constitute a refrigeration cycle for cooling and heating. The components obtained by timely incorporating the condenser, condenser, blower, etc. into both sides.

The weather information providing device 16 is installed in a weather company, etc., and the weather data 21 such as the temperature, humidity, wind speed, and sunshine amount of the outside air measured in the construction area of the above-mentioned building is predicted by a computer based on the operation of a weather forecaster, etc. The weather forecast data 22 is sent to the energy management device 11 via the public network 15 .

The energy management device 11 is configured to include an energy demand prediction unit 11a, an internal heating load estimation unit 11b, an operation database unit 11c, and an external heating load calculation unit 11d.

The operation database unit 11c stores and accumulates the power measurement data 23 received from the power measurement device 13 and the air conditioner operation data received from the air conditioner controller 14 for each of the measurement date and a predetermined date. 24. Weather data 21 and weather forecast data 22 received from the weather information providing device 16 as information on weather conditions. Among them, each data is received by a not-shown data and signal transmission and reception function (acquisition means) of the energy management device 11 .

The external thermal load calculation unit 11d calculates the external thermal load flowing from the outdoor of the building into the room as described later. The internal thermal load estimating unit 11b estimates the indoor internal thermal load of the building as described later. There are several methods for calculating the external heating load. In this example, the calculation by the heating load simulation is performed, and at this time, the estimation of the internal heating load is also carried out.

The energy management device 11 of such a structure is provided with CPU (Central Processing Unit, central processing unit) 101a, ROM (Read Only Memory, read only memory) 101b, RAM (Random Access Memory, random access memory) 101c, as shown in Figure 2, A storage device (HDD: Hard DiskDrive, etc.) 101d that operates the database unit 11c is constructed, and these constituent elements 101a to 101d have a general configuration connected to the bus 102 . In such a structure, for example, CPU101a executes the program 101f written in ROM101b, and realizes each process control of the energy management apparatus 11 mentioned later.

FIG. 3 is a cross-sectional view of a building office portion showing typical thermal loads that affect the indoor environment in one office 110 in a building.

In the office 110, 111 is the glass window installed outside the building, 112 is the outer wall, 113 is the inner wall, 114 is the floor (or the ceiling of the lower floor), 115 is the indoor unit of the air conditioner, 116 is the lighting equipment, 117 is the Office equipment of various electrical equipment such as OA equipment, 118 is indoor personnel. However, it is assumed that the indoor unit 115 is any one of the indoor units 42a to 42m and 43a to 43m shown in FIG. 1 . In addition, the sun is represented by symbol 120 .

In addition, the arrow Q _EW is the heat load (heat load of the outer wall) entering the office room 110 from the outer wall 112, the arrow Q _SR is the heat load of sunlight entering the office room 110 from the glass window 111 (solar heat load), and the arrow Q _G is the heat load that enters the office room 110 through heat transfer from the glass window 111 (window heat transfer heat load), and the arrow Q _INF is the heat load that enters the office room 110 through ventilation and gap wind (ventilation gap wind heat load). load), the arrow Q _IW is the heat load entering the office room 110 from the inner wall 113 and the floor (or the ceiling of the lower floor) 114 (inner wall floor heat load). Arrow Q _E is the heat load (indoor equipment heat load) generated from lighting equipment 116 and office equipment 117 in the office 110, arrow Q _H is the human body heat load generated from indoor personnel 118 in the office 110, and arrow Q _AC is is the heat load of the air conditioner generated from the indoor unit 115 .

In addition, in FIG. 3 , the symbol θ _O shown next to the point (black circle) indicates the outside air temperature, θ _RS indicates the indoor temperature of the office room 110, and θ _A indicates the indoor temperature of the room adjacent to the office room 110, up, down, left, and right. Adjacent room temperature, SAT (Sol-air temperature) means the equivalent outside air temperature.

In the heat load simulation, according to the elements of each heat load Q _EW , Q _SR , Q _G , Q _INF , Q _IW , Q _E , Q _H , Q _AC indicated by the arrows, according to the predetermined time interval, according to the meteorological conditions ( external air temperature, humidity, wind speed, amount of sunlight, etc.), building specifications (walls, glass, etc.), and operating conditions of air-conditioning equipment (room temperature setting, air volume, etc.) Changes in the environment, air conditioning heat load, etc. The calculation methods of the heat loads Q _EW , Q _SR , Q _G , Q _INF , Q _IW , Q _E , Q _H , and Q _AC are well-known methods described in the above-mentioned non-patent literature, etc., so descriptions thereof are omitted here.

Among them, the data of building specifications in the building of this example are glass windows 111, internal and external walls 112, 113, gaps between doors, etc., insulation state, concrete thickness, window size, orientation (orientation), orientation of the building itself, etc. , These building specification data are stored in advance in the operational database unit 11c.

In addition, among the heat loads Q _EW , Q _SR , Q _G , Q _INF , Q _IW , Q _E , Q _H , and Q _AC , the indoor equipment heat load Q _E , the human body heat load Q _H , and the air conditioner heat load Q _AC is an internal heat load inside the office room 110 . The heat loads other than these, that is, the heat load of the outer wall Q _EW , the heat load of sunlight Q _SR , the heat load of heat transfer through the window Q _G , the heat load of the ventilation gap Q _INF , and the heat load of the inner wall and floor Q _IW are equivalent to those from the outside of the office 110. external heat load. In the following description, it is assumed that the internal heat load is both the indoor equipment heat load Q _E and the human body heat load Q _H other than the air conditioner heat load Q _AC . The air-conditioning thermal load Q _AC can be obtained as an actual measurement value by obtaining the power consumption based on the measured value of the load current and the like by the air-conditioning controller 14 , so it is used independently.

Here, when the heat load simulation is performed, the air conditioning in the office 110 is properly performed, and if the indoor environment is maintained at a constant condition, the following equation (1) described in FIG. 3 holds.

Q _EW +Q _SR +Q _G +Q _INF +Q _IW +Q _E +Q _H +Q _AC ＝0...(1)

Here, the heat load Q _AC of the air conditioner is equal to the external heat load (Q _EW +Q _SR +Q _G +Q _INF +Q _IW ) + the internal load heat (Q _E +Q _H ), so by calculating Q _AC -(Q _EW + Q _SR +Q _G +Q _INF +Q _IW ), the following formula (2) is obtained to calculate (Q _E +Q _H )=internal heat load.

Q _E +Q _H ＝Q _AC -(Q _EW +Q _SR +Q _G +Q _INF +Q _IW )...(2)

The external heat load calculation part 11d shown in FIG. 1 is for all the rooms of the building, for each predetermined time, based on the weather data 21 and building specification data stored in the operation database part 11c, according to the above Known method, calculating the external heat load (Q _EW +Q _SR +Q _G +Q _INF +Q _IW ). However, when calculating the external heating load (Q _EW +Q _SR +Q _G +Q _INF +Q _IW ) in the future (future) date and time by the external heating load calculation unit 11d, as the weather condition, substitute the weather data21, and weather forecast data22.

The internal thermal load estimation unit 11b calculates the power consumption of the air conditioners by using the load current values of the air conditioners 41a to 41n in the air conditioner operation data 24 stored in the operation database unit 11c, and calculates the air conditioner thermal load as actual measured values. Q _AC . Furthermore, the internal thermal load estimating unit 11b applies the air-conditioning thermal load Q _AC and the external thermal load (Q _EW +Q _SR +Q _G +Q _INF +Q _IW ) calculated by the external thermal load calculation unit 11d to The above formula (2) is used to calculate the heat load Q _E of the indoor equipment + the heat load Q _H of the human body, that is, the estimation of the internal heat load.

An example of such estimated internal heating load, external heating load, and air-conditioning heating load Q _AC is shown in a graph in FIG. 4 . In FIG. 4 , the horizontal axis represents the time of day (0:00 to 24:00), and the vertical axis represents the thermal load (kw) equally divided by P0 to P9. On the horizontal and vertical axes, the air conditioner heat load (measured value) is shown by a curve 101 , the outer wall heat load (calculated value) by a curve 102 , and the internal heat load (estimated value) by a curve 103 .

The relationship of these heat loads 101-103 is shown by following formula (3).

Air conditioning heat load 101 - external heat load 102 = internal heat load 103...(3)

Therefore, the internal thermal load estimating unit 11b subtracts the total power consumption of the building based on the electric power measurement data 23 during a predetermined period stored in the operation database unit 11c, for example, from 0:00 to 24:00 a day, and subtracts the difference from the actual power consumption. Measure the power consumption of the corresponding air-conditioning equipment to obtain the power consumption of the indoor equipment (= heat load Q _E of the indoor equipment). This calculation is represented by the following formula (4).

Overall power consumption of the building - heat load of air conditioner 101 = power consumption of indoor equipment...(4)

The power consumption of the indoor equipment in the formula (4) is obtained from the power consumption of the entire building and the heat load 101 of the air conditioner which are actually measured values obtained by the power measuring device 13 shown in FIG. 1 , so it is also a measured value.

In addition, if there is no actual measured value of the power consumption of the air conditioner, it can also be obtained by dividing the air conditioner thermal load Q _AC by the coefficient of efficiency (COP) of the air conditioner.

Here, since indoor equipment power consumption = indoor equipment thermal load Q _E , if Q _E is known, the human body thermal load Q _H that is difficult to obtain directly can be obtained according to the above formula (2) as in the following formula (5) .

Q _H ＝Q _AC -(Q _EW +Q _SR +Q _G +Q _INF +Q _IW )-Q _E …(5)

In FIG. 5, as an example, the curve 105 of the human body heat load (estimated value) Q _H obtained by the above formula (5) and the internal heat load (estimated value) 103 based on the above formula (3) are combined by The indoor device power consumption (measured value) 104 represented by the above formula (4) is collectively represented. However, in FIG. 5 , the vertical axis represents heat load (kW), and the horizontal axis represents time.

The relationship between these thermal loads 103 and 105 and the power consumption 104 of the indoor equipment is represented by the following equation (5a) equivalent to the above equation (5).

Internal heat load 103 - indoor equipment power consumption 104 = human body heat load 105...(5a)

In the operation database unit 11c, the indoor equipment power consumption 104 (=indoor equipment thermal load Q _E ) and human body thermal load Q _H thus obtained are stored using date and time as common conditions (also referred to as parameters).

Next, the energy demand prediction part 11a shown in FIG. 1 performs the prediction process of energy demand as follows based on each data memorize|stored in the operation database part 11c.

As a precondition, the indoor equipment power consumption 104 and the indoor human heat load 105 shown in FIG. When sorting out the period of each section, for example, weekdays and holidays, the tendencies are substantially the same.

FIG. 6 shows an example of a variation pattern of the indoor device power consumption 104 showing the same tendency, and FIG. 7 shows an example of a variation pattern of the indoor body heat load 105 .

6 is a diagram showing estimated data 104 a , 104 b , and 104 c of indoor device power consumption 104 indoors for three days with the same operating conditions and a graph of an average indoor device power consumption pattern 104M for the three days. However, in FIG. 6 , the vertical axis represents heat load (kW), and the horizontal axis represents time.

That is, for each of the three weekdays, the internal heat load estimation unit 11b estimates the indoor equipment power consumption 104 in the room, and the estimated value on the first day is plotted as the first indoor equipment power consumption 104a, and the first indoor equipment power consumption 104a is plotted. The estimated value on the 2nd day is graphed as the second indoor device power consumption 104b, and the estimated value on the 3rd day is graphed as the third indoor device power consumption 104c. Furthermore, the average of the indoor equipment power consumption 104a, 104b, and 104c corresponding to 3 days is calculated by the internal thermal load estimation unit 11b to obtain an indoor equipment power consumption pattern (also simply referred to as a pattern) 104M.

7 is a diagram showing estimated data 105 a , 105 b , and 105 c of human body thermal load 105 indoors for three days on weekdays and a graph of an average human body thermal load pattern 105M corresponding to the three days with the same operating conditions. However, in FIG. 7 , the vertical axis represents thermal load (kW), and the horizontal axis represents time.

That is, in each of the 3 days of weekdays, the internal heat load estimation unit 11b estimates the indoor human body heat load 105, and the estimated value on the first day is plotted as the first human body heat load 105a, and the second day The estimated value on the third day is plotted as the second body thermal load 105b, and the estimated value on the third day is plotted as the third human thermal load 105c. Furthermore, the average of the body heat loads 105a, 105b, and 105c corresponding to 3 days is calculated by the internal heat load estimation unit 11b to obtain a body heat load model (also referred to as a model) 105M.

In order to obtain the respective patterns 104M and 105M in this way, the following settings are performed. That is, in the internal thermal load estimation unit 11b, it is set to automatically estimate the indoor equipment power consumption 104 and the human body thermal load 105 on a regular basis, for example, once a day, and further set to perform a three-day equivalent. Quantities are averaged to obtain the respective modes 104M, 105M. This setting is performed in a setting unit (not shown) of the energy management device 11 .

Furthermore, in the operation database part 11c, each pattern 104M, 105M obtained by this setting is stored in association with relevant data using date and time as a parameter.

Here, when the energy demand forecasting unit 11a of the energy management device 11 shown in FIG. 1 performs daily equivalent energy demand forecasting based on each data stored in the operation database unit 11c, the following arithmetic processing is performed. .

The energy management device 11 acquires the weather forecast data 22 of the day when the energy demand forecast is performed from the weather information providing device 16 via the public network 15, and performs the heat load simulation of the external heat load calculation unit 11d based on the acquired weather forecast data 22 and the building Material specification data to calculate external heat loads.

Next, when the energy demand forecast is performed by the energy demand forecasting unit 11a, the date (same as the usage status day) is searched from the operation database unit 11c for the same day (the same use status day) as the day on which the energy demand forecast is performed (the demand forecast date). The search patterns 104M and 105M are used as the indoor equipment heat load Q _E and the human body heat load Q _H .

Here, if the above formula (1) is modified to obtain the air-conditioning heat load Q _AC based on the relationship of the above formula (1) established by the thermal load simulation, the following formula (6) is obtained.

Q _AC ＝-(Q _EW +Q _SR +Q _G +Q _INF +Q _IW +Q _E +Q _H )…(6)

If conditions such as the preset indoor environment and air-conditioning implementation date and time are determined as in this equation (6), the necessary air-conditioning heat load Q _AC is estimated by the internal heat load estimation unit 11b.

Next, by dividing the obtained air-conditioning heat load Q _AC by the COP in the energy demand predicting unit 11a, a predicted value of the power consumption of the air-conditioning equipment is obtained. However, the COP can also be represented by a function corresponding to the air-conditioning heat load Q _AC . The accuracy is further improved by creating the COP function in advance from the air-conditioning equipment operation data 24 .

Here, since indoor equipment thermal load Q _E = indoor equipment power consumption, the energy demand prediction unit 11a can calculate the predicted value of power consumption of the whole building as in the following equation (7) to perform energy demand prediction.

Predicted value of overall power consumption of the building (forecast result of energy demand) = power consumption of air-conditioning equipment + Q _E ... (7)

Furthermore, the energy demand prediction part 11a displays this energy demand prediction result together with the current fluctuation|variation of various power consumptions on the display which is not shown like the graph shown in FIG. 8, for example. However, in FIG. 8 , the vertical axis represents power consumption (kW), and the horizontal axis represents time. In FIG. 8, the actual air-conditioning equipment up to the present (point 14 in the figure) is shown together with the predicted external air temperature 121, the predicted power consumption of the air-conditioning equipment 122, and the predicted power consumption of the entire building (forecast result of energy demand) 123. Power consumption 124 and overall building power consumption 125. The expected outside air temperature 121 is obtained from the weather forecast data 22 of the day when the energy demand forecast is performed from the weather information providing device 16 , and the external heating load calculation unit 11 d obtains it from the weather forecast data 22 .

<Operation of Embodiment>

Next, the operation|movement which performs the energy demand prediction of a building by the energy management system 10 of the said structure is demonstrated with reference to the flowchart shown in FIG.9-FIG.12. However, it is assumed that the building specification data of the building of this example shown in FIG. 3 is stored in advance in the operational database unit 11c shown in FIG. 1 .

In step S1 shown in FIG. 9 , the energy management device 11 shown in FIG. 1 receives the power consumption of the entire building measured every moment by the power measuring device 13 installed in the switchboard 31 in the building via the local area network 12 . The received power consumption of the entire building is stored as electric power measurement data 23 in association with date and time in the operation database unit 11c. However, it is assumed that the year and month are also associated with the date and time in this description of the operation.

In addition, in step S2, in the energy management device 11, the air conditioner operation data 24 of each air conditioner 41a-41n acquired by the air conditioner controller 14 is received via the local area network 12, and the received air conditioner operation data 24 is stored in the It is stored in association with date and time in the operation database unit 11c.

Furthermore, in step S3, in the energy management device 11, the weather data 21 is received from the weather information providing device 16 via the public network 15, and the received weather data 21 is stored in the operation database part 11c in association with the date and time. .

Next, in step S4, by the external heat load calculation unit 11d, for each room in the building, for each predetermined time, based on the weather data 21 and the building specification data stored in the operation database unit 11c, through the heat load calculation unit 11d. Load simulation to calculate the external heat load (Q _EW +Q _SR +Q _G +Q _INF +Q _IW ). That is, the outer wall heat load Q _EW , the solar heat load Q _SR , the window heat transfer heat load Q _G , the ventilation gap wind heat load Q _INF , and the inner wall floor heat load Q _IW indicated by arrows in FIG. 3 are calculated.

Furthermore, in step S5, the internal thermal load estimation unit 11b calculates the power consumption of the air conditioner based on the air conditioner operation data 24 stored in the operation database unit 11c, thereby estimating the air conditioner thermal load Q _AC as an actual value.

Furthermore, in step S6, the internal heat load estimation unit 11b calculates the air-conditioning heat load Q _AC estimated in the above step S5 and the external heat load (Q _EW + Q _SR + Q ) calculated in the above step S4. _G +Q _INF +Q _IW ) is applied to the above formula (2), so as to infer the internal heat load based on the heat load Q _E of the indoor equipment + the heat load of the human body Q _H .

Through these steps S4-S6, for example, as shown by the graph in FIG. Heat load (estimated value) 103. The relationship between these thermal loads 101 to 103 is shown in the above formula (3).

Next, in step S7 shown in FIG. 10 , the internal heating load estimating unit 11b subtracts from the daily equivalent building power consumption (electric power measurement data 23 ) accumulated in the operation database unit 11c. The power consumption of the air-conditioning equipment obtained in the above step S5 is used to obtain the power consumption of the indoor equipment (=heat load Q _E of the indoor equipment). The calculation formula is shown in the above formula (4).

Here, indoor equipment power consumption = indoor equipment thermal load Q _E , so in step S8, the internal thermal load estimation unit 11b applies this Q _E to the above formula (2), and then estimates the human body as in the above formula (5). Heat load Q _H .

Through these steps S7 and S8 , for example, as shown by the graph in FIG. 5 , daily indoor device power consumption (measured value) 104 and human body heat load (estimated value) 105 are obtained. When FIG. 5 shows the above-mentioned internal heat load (estimated value) 103 together with them, the relationship between the heat loads 103, 105 and the power consumption 104 of the indoor equipment is as the above formula equivalent to the above formula (5). (5a).

Next, in step S9, the indoor equipment power consumption 104 (=indoor equipment thermal load Q _E ), and the body heat load 105 obtained in the above step S8.

Next, in step S10, the internal heating load estimating unit 11b estimates the power consumption 104 of the indoor equipment for every predetermined time, and through this estimation, each estimated data 104a shown in FIG. 6 is obtained on a daily basis. , 104b, 104c, in the operation database part 11c, date and time are stored as parameters.

In addition, in step S11 shown in FIG. 11, the internal heat load estimating unit 11b estimates the human body heat load 105 in the room for each predetermined time, and through this estimation, each day shown in FIG. 7 is obtained. The estimation data 105a, 105b, 105c' are stored in the operation database part 11c with date and time as parameters.

Furthermore, in step S12, the internal heating load estimation unit 11b calculates the average of the estimation data 104a, 104b, 104c of the indoor equipment power consumption 104 stored in the operation database unit 11c, for example, for 3 days, to obtain the Indoor device power consumption mode 104M is shown. Furthermore, the average of estimated data 105a, 105b, and 105c of the same 3-day-equivalent human body thermal load 105 stored in the same manner is calculated to obtain a human body thermal load model 105M shown in FIG. 7 . In the operation database part 11c, each obtained pattern 104M, 105M is memorize|stored with date and time as a parameter.

Next, in step S13, the daily equivalent energy demand forecast is started by the energy demand forecasting part 11a shown in FIG.

In this case, in step S14 , in the energy management device 11 , the weather forecast data 22 of the day on which the energy demand forecast is performed is acquired from the weather information providing device 16 via the public network 15 .

Next, in step S15, by the heat load simulation of the external heat load calculation unit 11d, based on the weather forecast data 22 acquired in the above step S14 and the building specification data stored in the operation database unit 11c, calculate External heat load (Q _EW +Q _SR +Q _G +Q _INF +Q _IW ). At this time, based on the weather forecast data 22, an estimated value of the outside air temperature (predicted outside air temperature) is also obtained.

Next, in step S16, the internal heat load estimation unit 11b searches the indoor device power consumption pattern 104M and the human body heat load pattern 105M on the same operation status day as the demand forecast day from the operation database unit 11c.

These search patterns 104M and 105M are used as the indoor equipment thermal load _QE and the human body thermal load _QH in the internal thermal load estimation unit 11b in step S17 shown in FIG. 12 . By applying these Q _E and Q _H and the external heat load (Q _EW + Q _SR + Q _G + Q _INF + Q _IW ) calculated in the above step S15 to the above formula (6), the air conditioner heat load is obtained Q _AC .

Next, in step S18, in the energy demand forecasting unit 11a, the air-conditioning heat load Q _AC obtained in the above-mentioned step S17 is divided by the COP to obtain the predicted value of the power consumption of the air conditioner (predicted power consumption of the air conditioner ).

Here, indoor equipment heat load Q _E = indoor equipment power consumption, so in step S19, in the energy demand prediction unit 11a, the predicted air conditioner power consumption and indoor equipment heat load Q _E are applied to the above formula (7), In this way, the predicted value of the overall power consumption of the building (predicted overall power consumption of the building) is calculated, and the energy demand forecast result is obtained.

Next, in step S20, the energy demand forecasting unit 11a displays the expected outside air temperature 121 obtained in the above-mentioned step S15 on a display not shown, as shown in FIG. The predicted air conditioner power consumption 122 and the predicted overall building power consumption (energy demand forecast result) 123 obtained in the above step S19 show the actual air conditioner power consumption 124 up to the present (point 14 in the figure). And the overall power consumption of the building is 125.

<Effect of Embodiment>

As described above, the energy management device 11 of the present embodiment is configured to include an acquisition unit (transmission and reception function) for acquiring the load current as the operation information of the air conditioners 41a to 41n installed in the building, and the construction area of the building. Information on weather conditions; the external heat load calculation unit 11d calculates the external heat load (Q _EW +Q _SR +Q _G +Q _INF +Q _IW ) flowing from the outside of the building to the inside of the building using the acquired information on the weather conditions and the internal thermal load estimation unit 11b estimates the air-conditioning thermal load Q _AC as the thermal load of the air-conditioning equipment 41a to 41n based on the obtained load current, and calculates the difference between the air-conditioning thermal load Q _AC and the calculated external thermal load , the internal heat load (= indoor equipment heat load (equipment heat load) Q _E + human body heat load Q _H ) of the building except for the air conditioner heat load Q _AC is estimated.

According to this configuration, the load currents of the air conditioners 41a to 41n, and The weather conditions in the area where the building is built can also predict the internal heat load of each device and human body in the building. Therefore, it is possible to estimate the internal heat load in the building at low cost and with high accuracy.

In addition, in the energy management device 11, the obtaining means obtains the power consumption of the whole building (total power consumption) which is the power consumption of the whole electrical equipment installed in the building, and the internal thermal load estimation unit 11b uses the obtained power consumption of the whole building . , and the difference between the air conditioner power consumption calculated from the load currents of the air conditioners 41a to 41n, the indoor equipment power consumption (equipment power consumption) 104 of the electrical equipment other than the air conditioners in the building is obtained. Then, the obtaining means subtracts the indoor equipment thermal load corresponding to the obtained indoor equipment power consumption 104 from the internal thermal load to estimate the human body thermal load Q _H , which is the thermal load of the human body inside the building.

According to this configuration, there is no measuring unit that directly measures the human body heat load Q _H in the building, but the energy management device 11 can further estimate the human body heat load Q that is difficult to distinguish by using the power consumption of the entire building and the load currents of the air conditioners 41a to 41n. _H. Therefore, the human body heat load Q _H in the building can be estimated with low cost and high accuracy.

In addition, in the energy management device 11, the internal heat load estimating unit 11b is configured to record the power consumption of the indoor equipment and the heat load of the human body as history information, take the average of the recorded power consumption of the indoor equipment and the heat load of the human body, and obtain The fluctuation patterns of the power consumption of the indoor equipment and the thermal load of the human body are determined in a predetermined period.

According to this configuration, for example, the variation patterns of the power consumption of the indoor equipment and the thermal load of the human body on a certain day can be easily obtained.

Moreover, in the energy management apparatus 11, the weather forecast data 22 of the forecast period in which energy demand forecast is performed is acquired as a weather condition in the acquisition means. The external heating load calculation unit 11d calculates the external heating load using the acquired weather forecast data 22 . The internal thermal load estimating unit 11b calculates the variation patterns of the power consumption of the indoor equipment and the thermal load of the human body based on the historical information of the same operating conditions as the forecast period, and calculates the air conditioner temperature based on these variation patterns and the calculated external thermal load. Handling of heat loads. In addition, it is configured to include an energy demand forecasting unit 11a as a demand forecasting unit that adds up the variation pattern of the air-conditioning equipment power consumption and the indoor equipment power consumption obtained from the air-conditioning heat load, and estimates the energy consumption during the forecast period. The predicted value of the overall power consumption.

According to this configuration, it is possible to predict energy demand in a building on a certain day at low cost, suitably, and easily. Therefore, for example, today, the heat load seems to be increasing, so energy-saving measures such as tightening somewhere can be easily performed so that it does not increase. As a specific example, today, at 2 o'clock in the afternoon, it seems that the upper limit load of the overall power consumption of the building will be exceeded, so observe the curve of the energy demand forecast in Fig. Such countermeasures are to stop the electrical equipment with low priority.

In addition, the energy management system 10 is configured to include: the above-mentioned energy management device 11; a power measurement device 13 that measures the power consumption of the entire electrical equipment installed in the building; The load current at the time of operation of the air conditioners 41a-41n installed in the building; and the weather information providing device 16, which measures and predicts the weather conditions of the construction area of the building and provides them.

Also in this energy management system 10 , the same effects as those of the energy management device 11 described above can be obtained.

In addition, the weather information providing device 16 may be installed in the building as accessory equipment. In addition, as operating conditions that the power consumption 104 of indoor equipment and indoor human body heat load 105 fluctuate in the same pattern, in addition to intervals such as weekdays and holidays, if the building is a commercial facility, it will also be during idle periods, busy periods, etc. Model it.

In addition, this invention is not limited to the said embodiment, Various modification examples are included. For example, the above-mentioned embodiment is an embodiment described in detail in order to explain this invention clearly, and is not necessarily limited to having all the structures demonstrated. In addition, a part of the structure of a certain embodiment can be replaced with the structure of another embodiment, and the structure of another embodiment can also be added to the structure of a certain embodiment. In addition, addition/deletion/replacement of other configurations can be performed for a part of the configurations of each embodiment.

In addition, with regard to the above-mentioned respective configurations, functions, processing units, processing units, etc., a part or all of them may be realized by hardware by, for example, designing an integrated circuit. In addition, the above-mentioned structures, functions, and the like may be realized by software by interpreting and executing a program for realizing each function by a processor. It is possible to store information such as programs, forms, and files that realize various functions in memory, hard disk, SSD (Solid State Drive, solid state drive machine) and other recording devices, or IC (Integrated Circuit, integrated circuit) card, SD (SecureDigital memory) , Secure Digital Memory) card, DVD (Digital Versatile Disc, digital universal disk) and other recording media.

In addition, as for the control lines and the information lines, the control lines and the information lines considered to be necessary for the explanation are shown, and it is not necessarily necessary to show all the control lines and the information lines in terms of products. It can also be considered that virtually all structures are interconnected.

Claims (5)

1. An energy management device, characterized in that it has: an acquisition unit that acquires information on the operation of air-conditioning equipment installed in the building and information on weather conditions in the area where the building is constructed; an external heat load calculation unit that calculates an external heat load flowing from the outside of the building to the inside using the acquired information on the weather conditions; and The internal thermal load estimation unit estimates an air-conditioning thermal load as a thermal load of the air-conditioning equipment based on the acquired operation information of the air-conditioning equipment, and estimates the air-conditioning thermal load based on a difference between the air-conditioning thermal load and the calculated external thermal load. In addition to the internal heat load of the air-conditioning heat load inside the building mentioned above. 2. The energy management device according to claim 1, characterized in that, the acquiring unit acquires overall power consumption that is the overall power consumption of electrical equipment installed in the building, The internal heat load estimating unit obtains the equipment of electrical equipment other than the air conditioner in the building based on the difference between the acquired overall power consumption and the power consumption of the air conditioner calculated from the operation information. For the power consumption, the heat load of the equipment corresponding to the power consumption of the equipment is subtracted from the internal heat load to estimate the heat load of the human body which is the heat load of the human body inside the building. 3. The energy management device according to claim 2, characterized in that, The internal thermal load estimating unit records the device power consumption and the human body thermal load as historical information, averages the recorded device power consumption and human thermal load, and calculates the respective values of the device power consumption and the human thermal load. pattern of change over a predetermined period. 4. The energy management device according to claim 3, characterized in that, The acquisition unit acquires weather forecast data during a forecast period in which the energy demand forecast is performed as information on the weather conditions, the external heating load calculation unit calculates the external heating load using the acquired weather forecast data, The internal thermal load estimating unit performs a process of obtaining a variation pattern of each of the equipment power consumption and the human body thermal load based on the history information of the same operation status as the prediction period, and calculating the variation pattern based on the variation pattern and the human body thermal load. Calculate the external heat load, find the air conditioner heat load, The energy management device includes a demand forecasting unit that adds the power consumption of the air-conditioning equipment obtained from the thermal load of the air-conditioning unit to a variation pattern of the power consumption of the equipment, and estimates the overall power consumption during the forecast period. predicted value of . 5. An energy management system, characterized in that it has: The energy management device according to any one of claims 2-4; A power measuring device to measure the overall power consumption of electrical equipment installed in a building; an air-conditioning information obtaining unit that obtains operation information of air-conditioning equipment installed in the building; and The weather information providing device measures, predicts and provides weather conditions in the construction area of the building.