JP2013031283A - Demand controller - Google Patents

Abstract

PROBLEM TO BE SOLVED: To effectively avoid the inconvenience that power consumption per demand time limit exceeds a target value even when the power generation amount of a power generator is decreased abruptly in a demand time limit.SOLUTION: A prediction section 30 of a demand controller 1 corrects a prediction value Pp of power consumption at the end of a demand time limit based on the electric energy consumed actually by a power consumption apparatus in the progress of the demand time limit and corrects a prediction value Ps of power generation amount at the end of the demand time limit based on the electric energy generated actually by a power generator 7 according to the contribution rate which declines as the end of the demand time limit is nearing, and a power control section 31 reflects the prediction value Pp of power consumption and the prediction value Ps of power generation amount corrected by the prediction section 30 and performs control for suppressing output of the power consumption apparatus.

Description

  The present invention relates to a power generation means for generating power using commercial power and natural energy, and / or a demand control device for supplying power from a storage battery to a power consuming device.

  Conventionally, the amount of power consumed by power consuming devices installed in stores and facilities varies greatly depending on the environment such as temperature and humidity, and peaks at certain times. In general, the electricity charge is calculated from the basic charge and the electricity charge based on the contract with the power company. This basic fee is determined based on the maximum value (maximum demand) of the integrated value of the power consumption of the entire facility for each predetermined unit time (for example, 30 minutes, hereinafter referred to as “demand time limit”). Therefore, it is required to minimize the maximum demand.

  Therefore, in the conventional demand control system, the generation of the peak of the power consumption is avoided (peak cut) by performing the control for suppressing the power consumption of the power consuming device in the demand time period where the power peak appears.

  On the other hand, the said facility may be provided with the electric power system which has a solar power generation device and a storage battery. In this case, a charge / discharge plan for the storage battery is made based on the amount of power generated by the solar power generation device, the charge power amount of the storage battery, and the power consumption amount of the power consuming device, and charge / discharge control of the storage battery is performed. As a result, when the consumption of power supplied from the commercial system exceeds the peak cut level (target value), the storage battery is discharged, and the peak cut of power consumption is performed without controlling the operation of the equipment as much as possible. (For example, refer patent document 1).

JP 2009-284586 A

  However, in the above control, since the power generation amount generated by the photovoltaic power generation device was performed on the premise that there is no large fluctuation from the predicted value, the predicted power generation amount greatly decreased due to a sudden weather change within the demand period. As a result, there is a problem that the amount of power supplied from the commercial system exceeds the peak cut level.

  The present invention has been made to solve the conventional technical problem, and even when the power generation amount of the power generator suddenly decreases within the demand time period, the consumption amount of power supplied from the commercial system per demand time period. A demand control device capable of effectively avoiding the inconvenience of exceeding the target value is provided.

  The demand control device of the present invention controls power supply from a power generation means that generates power using commercial power and natural energy to a power consuming device, and at the start of a demand time period, the demand control device A prediction unit that predicts a predicted value Pp of power consumption by the power consuming device until the end of the time period, and predicts a predicted value Ps of power generation by the power generation means until the end of the demand period based on the power generation environment condition; The prediction value Pp-Ps of commercial power obtained by subtracting the predicted value Ps of power generation from the predicted value Pp of power consumption predicted by the prediction unit is the target value Pt of power consumption per demand time limit. A power control unit that performs control to suppress the output of the power consuming device, and the prediction unit is based on the amount of power actually consumed by the power consuming device during the demand period. The predicted value Pp of the power consumption until the end of the demand time period is corrected, and the predicted value Ps of the power generation amount until the end of the demand time period is calculated based on the amount of power actually generated by the power generation means. The power control unit corrects the predicted value Pp of the power consumption and the predicted value Ps of the power generation, which are corrected by the prediction unit, to suppress the output of the power consuming device. It is characterized by performing.

  The demand control device according to claim 2 controls power supply from commercial power, a storage battery, and a power generation means that generates power using natural energy to a power consuming device, and at the start of a demand time period, the device environmental condition Is used to predict the predicted value Pp of the power consumption by the power consuming device until the end of the demand period, and the predicted value Ps of the power generation by the power generation means until the end of the demand period based on the power generation environment condition The prediction unit for prediction, and the predicted power consumption predicted value Pp-Ps obtained by subtracting the predicted power generation amount Ps from the predicted power consumption predicted value Pp of the prediction unit are the power consumption per demand time limit. A power control unit that controls the output of the storage battery to start or increase the supply of power from the storage battery to the power consuming device. While the time period is in progress, the predicted value Pp of power consumption until the end of the demand time period is corrected based on the amount of power actually consumed by the power consuming device, and the amount of power actually generated by the power generation means is changed. Based on this, the predicted value Ps of the power generation amount until the end of the demand time period is corrected with a contribution rate that decreases as the demand time period ends, and the power control unit corrects the predicted value Pp of the power consumption corrected by the prediction unit and The power supply by the storage battery is controlled by reflecting the predicted value Ps of the power generation amount.

  According to a third aspect of the present invention, in each of the above-mentioned inventions, the power control unit predicts a commercial power consumption predicted value Pp− obtained by subtracting the power generation predicted value Ps from the power consumption predicted value Pp predicted by the prediction unit. If Ps exceeds the power consumption set value Pt × α obtained by multiplying the target value Pt by a predetermined safety coefficient α before the power consumption exceeds the target value Pt, the output of the power consuming device is Control to suppress or control the output of the storage battery to start or increase the supply of power from the storage battery to the power consuming device.

  The invention of claim 4 is characterized in that, in each of the above inventions, the contribution ratio is a value in the range of 0 to 1 and becomes smaller as the remaining time until the end of the demand time period decreases.

  The invention of claim 5 is characterized in that, in the invention of claim 3 or claim 4, the predicting unit decreases the safety coefficient α closer to the start time of the demand time limit.

  According to a sixth aspect of the present invention, in each of the second to fifth aspects of the present invention, the power control unit predicts a time at which the power charged in the storage battery is used up, and a time period during which the predicted time falls in unit price of commercial power In this case, the output of the storage battery is controlled to start or increase the supply of power to the power consuming device, and the commercial power is charged to the storage battery during a time period when the unit price of the commercial power decreases.

  According to a seventh aspect of the present invention, in each of the second to sixth aspects of the present invention, the power control unit is configured such that the predicted commercial power consumption value Pp-Ps predicted by the prediction unit is a target value Pt of power consumption or power consumption. When the amount exceeds the set value Pt × α, when the difference exceeds the amount of charge of the storage battery, control is performed to suppress the output of the power consuming device for the amount of power of the difference.

  The invention of claim 8 relates to each of the above inventions, and stores the amount of power actually consumed by the power consuming device, the device environmental conditions including the temperature and humidity data at that time, and the time zone in association with each other. The power generation result database constructed by associating and storing the power consumption result database constructed by, the amount of power actually generated by the power generation means, and the power generation environmental conditions and time zones including the weather data at that time And a prediction unit predicts a predicted value Pp of power consumption and a predicted value Ps of power generation by referring to the power consumption result database and the power generation result database based on the current device environment condition and power generation environment condition. It is characterized by doing.

  In the invention of claim 9, in the above invention, when the control for suppressing the output of the power consuming device is performed, the power consumption of the power consuming device when the output of the power consuming device is not suppressed is estimated and consumed. It is characterized by constructing a power performance database.

  The invention of claim 10 is characterized in that, in each of the above inventions, the power generation means is a solar power generation device or a wind power generation device.

  According to the first aspect of the present invention, in the demand control device that controls the power supply from the power generation means that generates power using commercial power and natural energy to the power consuming device, at the start of the demand time period, the demand control device A prediction unit that predicts a predicted value Pp of power consumption by the power consuming device until the end of the demand time period, and predicts a predicted value Ps of power generation by the power generation means until the end of the demand time period based on the power generation environment condition And the predicted value Pp-Ps of commercial power obtained by subtracting the predicted value Ps of power generation from the predicted value Pp of power consumption predicted by the prediction unit is the target value Pt of power consumption per demand time limit. A power control unit that performs control to suppress the output of the power consuming device, and the prediction unit performs power consumption that is actually consumed by the power consuming device while the demand time period is in progress. Based on the amount, the predicted value Pp of the power consumption until the end of the demand time period is corrected, and the predicted value Ps of the power generation amount until the end of the demand time period is calculated based on the power actually generated by the power generation means. The power control unit corrects the predicted value Pp of the power consumption and the predicted value Ps of the power generation, which are corrected by the prediction unit, to suppress the output of the power consuming device as it approaches the end of the demand time period. Even if the power generation amount suddenly decreases due to sudden weather changes, the predicted value Ps of the power generation amount decreases with the contribution rate as it approaches the end of the demand period. Therefore, it is possible to perform control to suppress the output of the power consuming device with a margin, and the power consumption supplied from the commercial power at the end of the demand time limit is the target value Pt. It is possible to effectively suppress the occurrence of cause around peak power.

  According to the invention of claim 2, in the demand control device for controlling the power supply from the power generation means for generating power using the commercial power, the storage battery, and the natural energy to the power consuming device, at the start of the demand time period, the device environmental condition Is used to predict the predicted value Pp of the power consumption by the power consuming device until the end of the demand period, and the predicted value Ps of the power generation by the power generation means until the end of the demand period based on the power generation environment condition The prediction unit for prediction, and the predicted power consumption predicted value Pp-Ps obtained by subtracting the predicted power generation amount Ps from the predicted power consumption predicted value Pp of the prediction unit are the power consumption per demand time limit. A power control unit that controls the output of the storage battery to start or increase the supply of power from the storage battery to the power consuming device, and the prediction unit While the command period is in progress, the predicted power consumption Pp until the end of the demand period is corrected based on the amount of power actually consumed by the power consuming device, and the amount of power actually generated by the power generation means Based on the above, the power generation amount predicted value Ps until the end of the demand time period is corrected by a contribution rate that decreases as the demand time period ends, and the power control unit corrects the power consumption predicted value Pp corrected by the prediction unit. In addition, by controlling the power supply by the storage battery by reflecting the predicted value Ps of the power generation amount, even when the power generation amount suddenly decreases due to sudden weather changes, Since the predicted value Ps of the power generation amount is predicted to decrease depending on the contribution rate, it is possible to control power supply by the storage battery with a margin, and supply from commercial power at the end of the demand period. The power consumption can be effectively suppress the occurrence of peak power would exceed the target value Pt to be.

  According to the invention of claim 3, in each of the above-mentioned inventions, the power control unit predicts the commercial power consumption obtained by subtracting the power generation predicted value Ps from the power consumption predicted value Pp predicted by the prediction unit. When Pp−Ps exceeds a set value Pt × α of power consumption obtained by multiplying the target value Pt by a predetermined safety coefficient α before exceeding the target value Pt of power consumption, the output of the power consuming device is By performing suppression control or controlling the output of the storage battery to start or increase the supply of power from the storage battery to the power consuming device, generation of peak power can be avoided more reliably.

  According to the invention of claim 4, in each of the above-mentioned inventions, the contribution rate is in the range of 0 or more and 1 or less, and becomes a value that becomes smaller as the remaining time until the end of the demand time period decreases, so that the excess from the storage battery It is possible to achieve effective suppression of peak power in consideration of the weather while suppressing excessive power supply.

  According to the invention of claim 5, in each of the inventions of claim 3 or claim 4, the predicting unit reduces the safety factor α at a point closer to the start time of the demand time period, thereby making a more reliable peak power cut. This can be realized, and it is possible to suppress excessive power suppression control of the power consuming device or excessive power supply from the storage battery.

  According to the invention of claim 6, in each of the inventions of claims 2 to 5, the power control unit predicts a time when the electric power charged in the storage battery is used up, and the predicted time decreases the unit price of commercial power. In the time zone, the output of the storage battery is controlled to start or increase the supply of power to the power consuming equipment, and the commercial power is charged to the storage battery during the time zone when the unit price of commercial power decreases, so the prediction of power consumption Regardless of the magnitude relationship between the commercial power consumption predicted value Pp-Ps obtained by subtracting the power generation predicted value Ps from the value Pp, and the power consumption target value Pt or the set value Pt × α, the storage battery is charged. By using the generated power and charging the storage battery in a time zone in which the unit price of commercial power decreases, not only the peak power can be suppressed but also the power consumption can be suppressed.

  According to the invention of claim 7, in each of the inventions of claims 2 to 6, the power control unit is configured such that the predicted commercial power consumption value Pp−Ps predicted by the prediction unit is the target value Pt of power consumption or In the case where the power consumption amount exceeds the set value Pt × α, if the difference exceeds the storage battery charge amount, the control of suppressing the output of the power consumption device for the power amount of the difference amount is performed more reliably. Generation of peak power can be avoided.

  According to the invention of claim 8, in each of the above inventions, the amount of power actually consumed by the power consuming device, the device environmental condition including the temperature and humidity data at that time, and the time zone are stored in association with each other. Power generation constructed by associating and storing the power consumption record database constructed by doing, the amount of power actually generated by the power generation means, and the power generation environment condition and time zone including the weather data at that time And a prediction unit is configured to refer to the power consumption result database and the power generation result database based on the current device environment condition and the power generation environment condition, and to predict the power consumption amount Pp and the power generation amount prediction value Ps. It is possible to realize control based on highly accurate prediction.

  According to the invention of claim 9, in the above invention, when the control for suppressing the output of the power consuming device is performed, the power consumption amount of the power consuming device when the output of the power consuming device is not suppressed is estimated. By constructing a power consumption performance database, it is possible to improve the prediction accuracy over prediction based on the amount of power actually consumed by the power consuming device when control is performed to suppress the output of the power consuming device. .

  In particular, when the power generation means is a solar power generation device or a wind power generation device as in the invention of claim 10, the present invention is effective because the amount of power generation due to weather increases.

It is a schematic diagram of a control system to which the present invention is applied. It is a control block diagram of the demand control apparatus of FIG. It is a schematic diagram of the internal structure of a power consumption performance database. It is a figure which shows the internal structure of a power generation amount results database. It is a flowchart of basic control. It is a flowchart of the prediction / control process at the time of demand time limit start. It is a timing chart about the control in the demand time limit of each condition. It is a flowchart of the output suppression control determination process of discharge / apparatus. It is a flowchart of a prediction and control process in the middle of a demand time limit. It is a figure which shows transition of each electric energy estimated in a prediction control process (at the time of a start). It is a figure which shows transition of each electric energy estimated in a prediction control process (intermediate time. After 10-minute progress). In a prediction control process, it is a figure which shows transition of each electric energy when the electric power generation amount is less than prediction (intermediate time. After 20 minutes progress, without correction by a contribution rate). In a prediction control process, it is a figure which shows transition of each electric energy when the electric power generation amount is less than prediction (intermediate time. After 20 minutes progress, with correction by a contribution rate).

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. FIG. 1 is a schematic diagram of a control system to which the present invention is applied. The demand control device 1 according to the present embodiment is installed in a facility such as a store of a supermarket or a convenience store, for example. In the facility, the demand control device 1 and a showcase 2 constituting a control system, A refrigerator 3, an air conditioner 4, a power consuming device such as an illumination 5, a power generator 7 that generates power using natural energy such as a solar power generator or a wind power generator, and a storage battery 8 are provided. . In this embodiment, a solar power generation device will be described as an example of the power generation device.

  In each power consuming device, commercial power for supplying power from a commercial power source is connected via a cubicle 11 by an AC line (commercial power system) 10. The cubicle 11 is a power receiving / transforming facility that manages high voltage power supplied from an electric power company on the store side and converts it to low voltage.

  The solar power generation device 7 generates electric power in accordance with the amount of irradiated light (amount of solar radiation). The DC power generated by the solar power generation device 7 is converted into AC power by the connected power conditioner 12. The inverter 12 is connected to the AC line 10.

  In addition, an AC / DC converter 13 and a DC / AC converter 14 are connected in parallel to the AC line 10 and a storage battery 8 is connected thereto.

  As a result, each power consuming device such as the showcase 2 acquires the commercial power acquired via the cubicle 11, the power from the storage battery 8 acquired via the DC / AC converter 14, and the power conditioner 12. The electric power generated by the solar power generation device 7 is supplied and enabled. The storage battery 8 can be charged with commercial power acquired via the AC / DC converter 13 and power generated by the solar power generation device 7.

  The demand control device 1 is composed of a general-purpose microcomputer, and through a communication line 15, power consumption devices such as a showcase 2, a refrigerator 3, an air conditioner 4, and an illumination 5, a power conditioner 12, The AC / DC converter 13 and the DC / AC converter 14 are connected. The demand control device 1 also includes a power meter 20 that detects the amount of power consumed by each power consuming device in the store, an outside air temperature sensor 21 that detects the outside temperature of the store where the power consuming device is installed, A humidity sensor 22 for detecting the humidity is connected. Furthermore, the demand control apparatus 1 can be connected to a server 24 via a network 23 such as the Internet. The server 24 provides actual weather data indicating the weather actually observed as the weather data service and weather forecast data indicating the prediction of the weather. The weather data includes weather data such as sunny, cloudy, and rainy. Further, the server 24 may be installed outside the store and remotely control each device.

  FIG. 2 shows a control block diagram of the demand control apparatus 1 in the present embodiment. The demand control device 1 includes a prediction unit 30, a power control unit 31, a comparison unit 32, a power consumption result database 33, a power generation result database 34, a power usage amount acquisition unit 35, and a power generation amount acquisition unit 36. A storage battery discharge amount acquisition unit 44, a temperature acquisition unit 37, a humidity acquisition unit 38, a weather data acquisition unit 39, a timer 40, a storage battery remaining amount acquisition unit 41, a storage battery control unit 42, and a device control unit 43 Have.

  The power consumption record database 33 indicates the amount of power actually consumed by each power consuming device such as the showcase 2, the refrigerator 3, the air conditioner 4, and the lighting 5, and the outside air temperature of the store where the power consuming device is installed. It is constructed by storing in association with at least two conditions of the device environmental condition and the usage time zone of the power consuming device. The device environmental condition may associate the absolute humidity of the store where the power consuming device or the like is installed in addition to the outside air temperature with the power consumption.

  FIG. 3 schematically shows the internal configuration of the power consumption record database 33. The power consumption record database 33 includes three parameters of the outdoor temperature of the store where the power consuming device or the like is installed, its absolute humidity, and the usage time zone of the power consuming device, and a unit in each power consuming device such as the power consuming device. The actual value of power consumption at normal time per hour is stored in association with each other. As will be described in detail later, when control is performed to suppress the output of the power consuming device, the amount of power consumption of the power consuming device when the output of the power consuming device is not suppressed is estimated. It is stored in the database in association with temperature and humidity. FIG. 3 shows the amount of power consumed by each power consuming device when the outside air temperature is + 10 ° C. to + 15 ° C., the absolute humidity is 0.005 to 0.010 kg / kg, and the usage time zone is 0:00 to 0:10. Illustrated.

  The power generation result database 34 is constructed by storing the power actually generated by the solar power generation device 7 in association with the power generation environmental conditions such as weather data and the time zone at that time. .

  FIG. 4 shows the internal configuration of the power generation result database 34. The power generation amount result database 34 stores weather data (weather data) and the actual value of the power generation amount per unit time in the solar power generation device 7 in association with each other for each date and time.

  The prediction unit 30 ends the demand time period with reference to the power consumption performance database 33 based on the current device environment condition of the power consuming device at the start of the demand time period used as a unit time of control in the demand control device. The predicted value Pp of the power consumption amount by the power consuming device until the time is predicted. Further, at the start of the demand time period, based on the current power generation environment condition of the solar power generation device 7, the power generation amount database 34 is predicted with reference to the power generation result database 34 until the end of the demand time period. To do.

  Here, the “equipment environmental condition” refers to the environment in which each power consuming device is installed or the usage condition of the power consuming device. For example, the outside air temperature detected by each outside air temperature sensor 21 and the humidity sensor 22 The detected humidity and the usage time zone. The “power generation environmental condition” is the use date and time (including month and day and time zone) and weather data (weather data) acquired from the server 24 via the network 23. The outdoor air temperature of the store where the power consuming device detected by each temperature sensor 21 is installed is acquired by the temperature acquisition unit 37, and the absolute humidity of the store where the power consuming device detected by the humidity sensor 22 is installed Is acquired by the humidity acquisition unit 38. Weather data (weather data) transmitted from the server 24 via the network 23 is acquired by the weather data acquisition unit 39.

  Therefore, the prediction unit 30 acquires the device environmental conditions acquired by the temperature acquisition unit 37 and the humidity acquisition unit 38 and the device environmental conditions for the usage time period from the timer 40 and refers to the power consumption record database 33. . In addition, the prediction unit 30 refers to the power generation result database 34 for the power generation environment condition for the use date and the use time zone from the timer 40 and the power generation environment condition for the weather data acquired by the weather data acquisition unit 39. . When any environmental condition cannot be acquired for some reason, the prediction unit 30 calculates an average value of values stored in the databases 33 and 34 as the predicted value.

  The power consumption acquisition unit 35 acquires the amount of power actually consumed by each power consuming device from the wattmeter 20. The power generation amount acquisition unit 36 acquires the amount of power actually generated by the solar power generation device 7 from the power conditioner 12. The storage battery discharge amount acquisition unit 44 acquires the power actually discharged from the storage battery 8. As will be described in detail later, the comparison unit 32 uses a commercial power consumption predicted value Pp-Ps obtained by subtracting the power generation predicted value Ps from the power consumption predicted value Pp predicted by the prediction unit 30, and 1 The target value Pt of the power consumption per demand time limit, or the magnitude relation with the set value Pt × α of the power consumption obtained by multiplying the target value Pt by a safety factor α, which will be described later in detail, is compared. At this time, when it is predicted that the storage battery 8 is discharged, the predicted power consumption value of the commercial power is calculated from the predicted value Pp of the power consumption amount predicted by the prediction unit 30 and the predicted value Ps of the power generation amount. The Pp−Ps−Pd obtained by subtracting the discharge amount Pd of 8 is compared with the target value Pt of the power consumption per one demand period or the set value Pt × α of the power consumption. Note that the target value Pt or the set value Pt × α of the power consumption amount per demand time period is stored in the database 33 in advance, and the comparison unit 32 reads the value from the power consumption record database 33 and compares it.

  The power control unit 31 controls the output of the storage battery 8 via the storage battery control unit 42, starts or increases the supply of power from the storage battery 8 to each power consuming device, and uses each power consumption via the device control unit 43. Control the equipment. For example, the power consumption is suppressed by lowering the output of the air conditioner 4.

  Hereinafter, power supply control to each power consuming device by the prediction unit 30, the power control unit 31, and the comparison unit 32 will be described in detail with reference to FIGS. FIG. 5 is a flowchart for explaining the flow of basic processing of the demand control apparatus 1 in this embodiment. The processing in the flowchart starts when the demand control device 1 is activated.

(1) Basic Process of Demand Control Device First, the demand control device 1 acquires the current time from the timer 40 by the prediction unit 30 (step S1), and whether or not the acquired time is the timing for determining demand control. Is determined (step S2). In the present embodiment, the prediction unit 30 divides 30 minutes, which is one demand time period, at predetermined intervals, and performs demand control determination at the start of each interval. Here, the “predetermined interval” is a reference interval at which the power control unit 31 performs control determination, and is, for example, 10 minutes. In such a case, the prediction unit 30 makes a total of three determinations, once at the start of the demand time period and once every 10 minutes and 20 minutes after the start of the demand time period.

  In step S2, when the time acquired from the timer 40 is a timing for determining demand control, the process proceeds to step S3, and it is determined whether or not the determination timing is a start time of a demand time limit. When the determination timing is the start time of the demand time period, the process proceeds to step S4, and the “prediction / control process at the start of the demand time period” is performed. On the other hand, when the determination timing is not the start time of the demand time period, that is, after 10 minutes or 20 minutes after the start of the demand time period, the process proceeds to step S5, Prediction / control process ". Details of each “prediction / control process” will be described later.

  On the other hand, if the current time acquired from the timer 40 in step S2 is not the timing for determining the demand control, or if each “prediction / control process” is executed in step S4 or step S5, the process proceeds to step S6. The prediction unit 30 waits for a certain time. The waiting time is, for example, 1 minute, and after waiting, the process returns to step S1 and continues.

(2) Prediction / Control Process at Start of Demand Time Period Next, the prediction / control process at the start of the demand time period in step S4 will be described with reference to the flowchart of FIG. FIG. 7 shows a timing chart for the control in the demand time limit of each condition. The demand control device 1 initializes the demand control of the power consuming device in the previous demand time limit by the power control unit 31 (step S11, device reset). And the electric power control part 31 progresses to step S12, acquires the residual amount Pr of the present storage battery 8 from the storage battery residual amount acquisition part 41, and the electric power charged by the storage battery 8 based on the present battery residual amount Pr and a rated output. The time Td required to use up all the time is calculated and predicted.

  Next, in step S13, the power control unit 31 determines that the current time acquired from the timer 40 is the normal electricity bill time zone, and the time after the time Td predicted in step S12 is the unit price of commercial power. It is determined whether it is a night time zone that falls. If it is determined in step S13 that the current time is not a normal electricity bill time zone, or if the time after the predicted time Td has elapsed is not a night time zone in which the unit price of commercial power decreases, the process proceeds to step S14. The prediction unit 30 predicts a predicted value (predicted power consumption) Pp of the power consumption of each power consuming device until the end of the demand time limit. As described above, the prediction of the predicted power consumption Pp is performed with reference to the power consumption record database 33 based on the current device environmental conditions.

  Next, it progresses to step S15 and the prediction part 30 estimates the predicted value (predicted power generation amount) Ps of the electric power generation amount of the solar power generation device 7 until the end of the said demand time limit. As described above, the prediction of the predicted power generation amount Ps is based on the current power generation environment condition, that is, based on the weather forecast data (weather forecast data) acquired from the server 24 via the network 23. Do it by reference.

  In step S16, the prediction unit 30 calculates a commercial power consumption predicted value Pp-Ps obtained by subtracting the power generation predicted value Ps from the predicted power consumption predicted value Pp. The comparison unit 32 uses the acquired commercial power consumption predicted value Pp−Ps as the target value Pt of the power consumption per one demand time period, or the power consumption obtained by multiplying the target value Pt by a predetermined safety coefficient α. It is determined whether or not the quantity set value Pt × α is exceeded. In this embodiment, the case where the set value Pt × α of the power consumption is adopted is shown.

  Here, the safety factor α determines whether to use the power of the storage battery 8 in order to surely prevent the consumption of commercial power per demand period from exceeding the target value Pt of power consumption. This is a parameter for adjustment. The safety coefficient α is a value that becomes smaller as the time close to the start of the demand time limit in the range of 0 to 1. For example, by setting the demand time period elapsed time to t (minutes) and setting α = 0.7 + 0.01 t, the safety factor at the start of the demand time period is 0.7, the coefficient at the end is 1, and at the start of the demand time period Control that makes it easy to use power from the storage battery 8 can be performed so as to approach the target value Pt as it approaches the end. As a result, more reliable peak power cut can be realized and excessive power supply of the storage battery 8 can be suppressed. The change pattern of the safety factor α is stored in advance in the power consumption record database 33, and the comparison unit 32 refers to the power consumption record database 33 and acquires an appropriate safety factor α.

  In step S16, when the obtained commercial power consumption predicted value Pp−Ps exceeds the set value Pt × α (Pp−Ps> Pt × α), the demand time periods (i), (iii), (iv) in FIG. ), The power control unit 31 performs a “discharge / equipment demand control determination process”, and ends the prediction / control process at the start of the demand time limit. The details of the “discharge / equipment demand control determination process” will be described later. On the other hand, in step S16, when the obtained commercial power consumption predicted value Pp−Ps is equal to or less than the set value Pt × α (Pp−Ps ≦ Pt × α), the demand time periods (ii) and (v) in FIG. In this case, the process proceeds to step S18, and at most, (Pt × α) −Pp + Ps is charged with the commercial power to the storage battery 8 and the prediction / control process at the start of the demand time limit is terminated. In this case, the power control unit 31 determines whether or not the demand time period is a time zone in which the unit price of the commercial power falls, for example, a midnight power time zone, and only when it is the time zone, the power control unit 31 stores the commercial power in the storage battery 8. It is good also as making it charge. Thereby, reduction of an electricity bill can be aimed at.

  In the above step S13, when the current time is the normal electricity bill time zone and the time after the predicted time Td has passed is the night time zone when the unit price of the commercial power decreases, the process proceeds to step S19. The power control unit 31 controls the output of the storage battery 8 via the storage battery control unit 42 to supply power to the power consuming device and completely discharge the power of the storage battery 8. Then, the storage battery 8 is charged with the commercial power during the time period when the unit price of the commercial power decreases. As a result, the power consumption predicted value Pp−Ps obtained by subtracting the power generation predicted value Ps from the power consumption predicted value Pp and the power consumption target value Pt or the set value Pt × α are larger or smaller. Regardless of the relationship, by using the power charged in the storage battery 8 and charging the storage battery 8 in the time zone when the unit price of commercial power decreases, not only the peak power can be suppressed, but also the power consumption can be suppressed. . This completes the prediction / control process at the start of the demand time period.

(3) Discharge / equipment demand control determination process Next, the discharge / apparatus demand control determination process in step S17 will be described with reference to the flowchart of FIG. In the control, first, in step S21, it is determined whether or not a peak time of power consumption by each power consuming device occurs during the same day. Specifically, the prediction unit 30 starts the demand time period acquired through the network 23 such as the Internet and the temperature of the space where the power consuming device is detected detected by the temperature sensor 21 at the start of the demand time period. Based on the predicted value of the temperature after the hour, the peak time of power consumption by each power consuming device is predicted with reference to the power consumption performance database 33. When the predicted peak time occurs on the same day, in the case of demand time periods (i) and (iii) in FIG. 7, the process proceeds to step S22.

  Here, the prediction unit 30 refers to the power consumption record database 33 for the predicted value of the amount of power consumed by the power consuming device in each demand time period, which exists between the start of the demand time period and the predicted peak time. Predict in advance. In addition, the prediction unit 30 refers to the power generation result database 34 for the predicted value of the power generation amount by the solar power generation device 7 in each demand time period that exists between the start of the demand time period and the predicted peak time. Predict in advance. At this time, it is desirable that the prediction unit 30 predicts the power consumption amount and the power generation amount for 24 hours in a time zone where the possibility of peak power is clearly not generated, such as a midnight time zone. At this point in time, the environmental condition is not accurately known, so the prediction unit 30 refers to the weather forecast data of the Japan Meteorological Agency acquired via the network 23 for the prediction of the temperature.

  Then, the prediction unit 30 calculates the predicted power consumption Pp (N) in each demand time period N and the predicted power generation amount Ps (N) in each demand time period N, and the commercial power in each demand time period N obtained from these is calculated. The difference between the predicted power consumption Pp (N) −Ps (N) and the target value Pt of the power consumption is set in the power consumption performance database 33 as a table for 48 demand time periods corresponding to one day. Thus, a demand time period in which the maximum peak power may occur and a demand time period that can be regarded as having a sufficient margin are predicted.

  And in the said step S22, the electric power control part 31 is the battery remaining time Pr of the present storage battery 8 charged beforehand via the storage battery control part 42, and the peak time (maximum peak electric power generation time zone) in the future day. Of the predicted charge / discharge amount up to Σ (Pt−Pp (N) + Ps (N)) and the predicted discharge amount Pp (Nmax) −Ps (Nmax) − at the peak time (maximum peak power generation time zone) Compare with Pt. That is, it is determined whether or not a sufficient amount of charge is secured in the storage battery 8 in the maximum peak power generation time zone. Here, Nmax represents a demand time period including the maximum peak power generation time zone.

  The term Pt−Pp (N) + Ps (N) is the commercial power consumption predicted value Pp () obtained by subtracting the power generation predicted value Ps (N) from the power consumption predicted value Pp (N). N) −Ps (N) is less than the target value Pt of the power consumption per one demand time period, and becomes a positive value for the demand time period with a margin in power. On the other hand, the demand time period in which the commercial power consumption predicted value Pp (N) −Ps (N) may exceed the target value Pt is a negative value. The prediction unit 30 can grasp the remaining charge amount of the storage battery 8 after a plurality of time periods by accumulating them by the number of demand time periods existing between the start of the demand time period and the peak time. .

  In step S22, when it is determined that the remaining battery level of the storage battery 8 is less than Pp-Ps-Pt × α, that is, when Pp-Ps-Pt × α exceeds the charge amount of the storage battery 8 (demand in FIG. 7). In the case of time limit (iii)), the power control unit 31 proceeds to step S25 and charges the storage battery 8 for the shortage Pp−Ps−Pt × α−Pr of the storage battery 8 (Pp−Ps−Pt × α and the storage battery 8). Control for suppressing the output of each power consuming device is performed so that the amount of power consumption is reduced by the difference amount of the amount). Specifically, by reducing the operation output by increasing the set temperature of the air conditioner 3 by 1 ° C. or turning off the lighting 5, the power consumption of each power consuming device is suppressed, and the peak power is more reliably determined. Avoid the occurrence of The power control unit 31 refers to the power consumption record database 33 to obtain the average power consumption during the past power consumption device operation for the reduced power amount in the control for suppressing the output of each power consumption device. Obtained by calculating using the rated power.

  On the other hand, if the peak time is not within the same day in step S21, the demand time limit (iv) in FIG. 7 or if the remaining charge of the storage battery 8 is sufficient at the peak time in step S22, the demand in FIG. In the case of the time limit (i), the process proceeds to step S23, and the power control unit 31 causes the storage battery 8 to discharge the amount of power corresponding to Pp-Ps-Pt × α so that it can be applied to each power consuming device by the end of the demand time limit. . At this time, the power control unit 31 controls the output of the storage battery 8 to discharge over 30 minutes when the demand time period ends. When the storage battery 8 is discharging, the power control unit 31 increases the discharge amount until the discharge amount of the storage battery 8 becomes Pp−Ps−Pt × α.

  When Pr ≧ Pp−Ps−Pt × α is not satisfied during the discharge of the storage battery 8, the process proceeds to step S <b> 25, and the power control unit 31 is Pp− which is the shortage of the charge amount of the storage battery 8 and the difference amount of power. Only Ps−Pt × α−Pr is controlled to suppress the output of each power consuming device such as an air conditioner. In addition, when the control which suppresses the output of the power consuming device is performed, the power consumption amount database of the power consuming device when the output of the power consuming device is not suppressed is estimated and the power consumption record database is constructed. Shall. For example, when the control of suppressing the output of the power consuming device is performed by increasing the set temperature of the cooling device by 1 ° C. or the like, it is based on the power consumption with respect to the set temperature of the device held in the power consumption record database. Then, the power consumption is corrected and registered in the power consumption record database when the control for suppressing the output of the power consuming device is not performed. Thereby, prediction accuracy can be improved rather than the prediction based on the electric energy actually consumed with the power consumption apparatus at the time of performing control which suppresses the output of a power consumption apparatus.

  On the other hand, if Pr ≧ Pp−Pt × α, the power control unit 31 ends the demand control determination process for the discharge / apparatus without performing any special process.

(4) Prediction / Control Process in the Middle of Demand Time Period Next, the prediction / control process in the middle of the demand time period in step S5 in FIG. 5 will be described with reference to the flowchart in FIG. The demand control device 1 starts the demand time period by the prediction unit 30 in step S31 during the demand time period, for example, when Δt has elapsed, in this embodiment, 10 minutes and 20 minutes after the demand time period starts. The predicted value (predicted power consumption) Pp of the power consumption until the end of the demand period is recalculated and corrected based on the actual value of the power actually consumed by the power consuming device from the time.

  Next, in step S <b> 32, the prediction unit 30 predicts the power generation amount from the start of the demand time period to the end of the demand time period based on the actual value of the power amount actually generated by the solar power generation device 7. (Predicted power generation) Ps is recalculated and corrected. At this time, the predicted value Ps of the power generation amount is corrected based on the contribution rate that decreases as it approaches the end of the demand time period.

Specifically, as shown in FIG. 9, the actual power generation amount P ₀ within the demand time period (T) is reflected in the power generation amount actual result database 34 (P ₀ · T / Δt). Then, the power generation amount prediction in which the contribution rate β (t) is changed according to the remaining time until the end of the demand time period is calculated. In this case, β (t) is a value (monotonically decreasing function) that becomes smaller as the remaining time until the end of the demand time period decreases in the range of 0 to 1.

  In step S <b> 33, the prediction unit 30 calculates a corrected consumption predicted value Pp−Ps of commercial power obtained by subtracting the corrected predicted value Ps of power generation from the corrected predicted value Pp of consumed power. The comparison unit 32 determines whether or not the obtained corrected consumption predicted value Pp−Ps of commercial power exceeds the set value Pt × α of power consumption obtained by multiplying the target value Pt per one demand period by a predetermined safety coefficient α. Judge whether or not.

  In step S33, when the obtained commercial power consumption predicted value Pp−Ps exceeds the set value Pt × α (Pp−Ps> Pt × α), the process proceeds to step S34, and the same discharge / equipment as in (3) above Execute the demand control judgment process. That is, when peak power is generated on the same day after the next demand period, it is determined whether or not a sufficient amount of charge is secured in the storage battery 8 in the maximum peak power generation time period, and the battery of the storage battery 8 is determined. When it is determined that the remaining amount is less than Pp-Ps-Pt × α, the power control unit 31 reduces the amount of power consumption by the amount Pp-Ps-Pt × α-Pr that is insufficient for the charge amount of the storage battery 8. As described above, control is performed to suppress the output of each power consuming device.

  On the other hand, when the peak time is not within the same day, or when the remaining charge of the storage battery 8 is sufficient at the peak time, the power control unit 31 is able to apply to each power consuming device by the end of the demand time limit. Electric power for Ps−Pt × α is discharged to the storage battery 8.

  As a result of the prediction unit 30 correcting the power consumption prediction value Pp and the power generation prediction value Ps during the demand time period, the commercial power consumption prediction value Pp-Ps corrected by the prediction unit 30 is the power consumption setting value. When the difference exceeds Pt × α and the difference between them exceeds the charge amount Pr of the storage battery 8, that is, when Pr ≧ Pp−Ps−Pt × α is not satisfied, the power control unit 31 determines the charge amount of the storage battery 8. Control that suppresses the output of each power consuming device such as an air conditioner is performed only by Pp−Ps−Pt × α−Pr, which is a shortage and a difference amount of power. On the other hand, only the discharge process of the storage battery 8 is continued during Pr ≧ Pp−Ps−Pt × α.

  On the other hand, if the obtained commercial power consumption predicted value Pp−Ps is equal to or less than the set value Pt × α (Pp−Ps ≦ Pt × α) in step S33, the process proceeds to step S35, where the power control unit 31 performs the power consumption. When there is a device that is executing control for suppressing the output of the device, the operation of the device is returned to the normal operation. That is, the control for suppressing the output of the power consuming device is canceled.

  And it progresses to step S36, it is judged whether the storage battery 8 is discharging, and when it is discharging, the electric power control part 31 stops discharge of the storage battery 8. FIG. In step S37, commercial power is charged into the storage battery 8 by at most (Pt × α) −Pp + Ps, and the prediction / control process in the middle of the demand time period is terminated. Even in this case, the power control unit 31 determines whether or not the demand time period is a time zone in which the unit price of the commercial power falls, for example, a late-night power time zone. The storage battery 8 may be charged. Thereby, reduction of an electricity bill can be aimed at.

  Here, with reference to FIG. 10 to FIG. 13, the prediction control process in the demand time period according to the present embodiment will be described by taking the predicted transition of each power amount and the transition of the actual power amount as examples. In each figure, the vertical axis of the upper graph indicates the integrated amount of each power within the demand time period, and the vertical axis of the lower graph indicates the power generation amount of the solar power generation device 7. The horizontal axis indicates the passage of time for one demand time period.

  FIG. 10 shows the prediction of each power amount in the prediction / control process at the start of the demand time limit. The predicted power consumption amount Pp of the power consuming device in the one-demand time period is predicted with reference to the power consumption performance database 33 based on the device environmental conditions at the start of the demand time period in step S14 of FIG. It is estimated that the demand time period is consumed evenly from the start to the end. Note that the method of estimating the predicted power consumption Pp is not limited to this.

  The predicted power generation amount Ps of the solar power generation device 7 in the one-demand time period is the power generation environmental condition at the start of the demand time period, that is, weather forecast data (weather data) acquired from the server 24 via the network 23 in step S15 of FIG. Based on the forecast data), it is predicted with reference to the power generation result database 34. As shown in the lower graph, the predicted power generation amount Ps is estimated to be generated uniformly from the start point to the end point of the demand time period. The method for estimating the predicted power generation amount Ps is not limited to this.

  Therefore, the commercial power consumption predicted value Pp−Ps (dots in the figure) obtained by subtracting the power generation predicted value Ps (hatched part in the figure) from the power consumption predicted value Pp until the end of the demand time period. (Part) is lower than the power consumption set value Pt × α (the target value Pt at the end). Therefore, the commercial power is charged to the storage battery 8 by at most (Pt × α) −Pp + Ps ( S18 of FIG. 6). Then, such control is continued until the determination timing of the next demand control (in this embodiment, 10 minutes after the start of the demand time limit).

  Next, with reference to FIG. 11, the prediction / control process in the middle of the demand time period (after 10 minutes from the start) will be described. In FIG. 11, in the range from the start time of the demand time period (0 minutes) to the lapse of 10 minutes, each integrated value (upper Graph) and the actual power generation amount 7 (lower graph).

  In this case, in step S32 in FIG. 9, the predicted power generation amount Ps of the solar power generation device 7 from the current demand period (10 minutes after the start) to the end of the demand period is the start time of the demand period. From the actual value of the amount of power actually generated by the power generation device 7 up to the present time, the predicted value Ps of the power generation amount at the end of the demand time period is corrected. At this time, the prediction unit 30 corrects the predicted value Ps of the power generation amount by the contribution rate β (t) that decreases as it approaches the end of the demand period. At present, the demand time period, 30 minutes, is 10 minutes after the start of the demand time period, so the contribution rate β (t) is 2/3.

  In the lower graph of FIG. 11, the hatched portion from the start point to the end point indicates the transition of the predicted power generation amount Ps before correction by the contribution rate, and the dotted line indicates the contribution rate. The transition of the predicted power generation amount Ps when correction is performed is shown. In the upper graph of FIG. 11, the integrated value of the predicted power generation amount Ps based on the power generation actual value until the present time before the portion indicated by hatching from the start time to the end time is corrected by the contribution rate is shown. The portion above the dotted line in the hatching shows the integrated value of the predicted power generation amount Ps when the contribution rate is corrected.

  In this case, the commercial power obtained by subtracting the predicted value Ps of the power generation amount corrected by the contribution rate from the predicted value Pp of the power consumption amount until the end of the demand time period (the portion above the hatched dotted line in the figure) Consumption predicted value Pp-Ps (dot portion in the figure and portion below hatched dotted line) is lower than set value Pt × α (becomes target value Pt at the end). Therefore, the commercial power is charged to the storage battery 8 by at most (Pt × α) −Pp + Ps (S18 in FIG. 6). The control is continued until the next demand control determination timing (in this embodiment, 20 minutes after the start of the demand time limit).

  Next, as a control comparison in this embodiment, refer to FIG. 12 for prediction / control processing in the middle of the demand period (after 10 minutes from the start) when the predicted value Ps of the power generation amount is not corrected by the contribution rate β (t). To explain. In FIG. 12, from the start time to the end time of the demand time period, the actual power consumption amount of the power consumption device, the power generation amount of the power generation device 7, each integrated value of the commercial power amount (upper graph), and the actual power generation device 7 Shows the transition of the amount of power generation (lower graph).

  In this case, in the prediction / control processing in the middle of the demand time period (when 20 minutes have elapsed from the start), the predicted power generation amount Ps of the solar power generation device 7 until the end of the demand time period is 10 minutes from the start of the demand time period. The predicted value Ps of the power generation amount at the end of the demand period is corrected based on the actual value of the electric power actually generated by the power generation device 7 from the time to the present time (the correction by the contribution rate is not performed for comparison) ).

  Therefore, the commercial power consumption predicted value Pp−Ps (indicated by a dotted line) obtained by subtracting the power generation predicted value Ps from the power consumption predicted value Pp at the end of the demand time period is the set value Pt × Since it is below α (the target value Pt at the end), the control for charging the storage battery 8 with the commercial power by the amount of (Pt × α) −Pp + Ps is continued until the end of the demand time limit. Yes.

  However, a rapid change in weather occurs between the lapse of 20 minutes from the start of the demand time period (end of the previous demand control determination timing) and the end of the demand time period, and the amount of power generated by the solar power generation device 7 is drastically increased. Even in the case of a decrease, the power control unit 31 continuously executes the control according to the prediction of the prediction unit 30 performed at the previous determination timing. Since the predicted value Pp cannot be decreased, or the amount of discharge from the storage battery 8 cannot be increased, as a result, the consumption value Pp-Ps of the commercial power exceeds the target value Pt at the end of the demand period.

  On the other hand, in the prediction / control process in the middle of the demand time period (in progress) in the present embodiment, as shown in FIG. 13, the prediction unit 30 reduces the contribution rate β (t) as it approaches the end of the demand time period. Thus, the predicted value Ps of the power generation amount is corrected. In FIG. 13, the integrated values of the actual power consumption of the power consuming device, the power generation amount of the power generation device 7, and the commercial power consumption are within the range from the start of the demand time period (0 minutes) to the lapse of 20 minutes. The upper graph) and the transition of the actual power generation amount of the power generator 7 (lower graph) are shown. Compared with FIG. 11, it is assumed that the actual power generation amount of the solar power generation device 7 from the time point 10 minutes to the time point 20 minutes from the start of the demand time limit is increased.

  That is, in step S32 of FIG. 9, the predicted power generation amount Ps of the solar power generation device 7 from the current demand period (20 minutes after the start) to the end of the demand period is 10 from the start of the demand period. The predicted value Ps of the power generation amount at the end of the demand time period is corrected based on the actual value of the power amount actually generated by the power generation device 7 from the minute point to the present time point. At this time, the prediction unit 30 corrects the predicted value Ps of the power generation amount by the contribution rate β (t) that decreases as it approaches the end of the demand time period. At present, the demand time period, 30 minutes, is 20 minutes after the start of the demand time period, so the contribution rate β (t) is 1/3.

  In the lower graph of FIG. 13, the hatched part from the start point to the end point indicates the transition of the predicted power generation amount Ps before correction by the contribution rate, and the dotted line indicates the contribution rate. The transition of the predicted power generation amount Ps when correction is performed is shown. From this figure, it can be seen that the contribution rate β (t) is smaller than the case of FIG. 11 because the demand time is approaching.

  In the upper graph of FIG. 13, the integrated value of the predicted power generation amount Ps based on the actual power generation value up to the present before the portion indicated by hatching from the start point to the end point is corrected by the contribution rate is shown. The portion above the dotted line in the hatching shows the integrated value of the predicted power generation amount Ps when the contribution rate is corrected.

  In this case, the commercial electric power obtained by subtracting the predicted value Ps of the power generation amount corrected by the contribution rate from the predicted value Pp of the power consumption amount at the end of the demand time period (the portion above the hatched dotted line in the figure). The predicted consumption value Pp−Ps (the dot portion in the figure and the portion below the hatched dotted line) exceeds the set value Pt × α (the target value Pt at the end) (Pp−Ps> Pt ×). α). For this reason, in step S34 in FIG.

  That is, in the discharge / equipment demand control determination process of FIG. 8, when peak power is generated during the same day after the next demand time period, a sufficient amount of charge is secured in the storage battery 8 in the maximum peak power generation time period. In the case where it is determined whether or not the battery remaining amount of the storage battery 8 is less than Pp−Ps−Pt × α, the power control unit 31 has an insufficient charge amount Pp−Ps− of the storage battery 8. Control is performed to suppress the output of each power consuming device so that the amount of power consumption is reduced by Pt × α−Pr.

  On the other hand, when the peak time is not within the same day, or when the remaining charge of the storage battery 8 is sufficient at the peak time, the power control unit 31 is able to apply to each power consuming device by the end of the demand time limit. The storage battery 8 is discharged with an amount of power corresponding to Ps−Pt × α.

  Thereby, the power control unit 31 controls the power supply by the storage battery 8 by reflecting the predicted value Pp of the power consumption corrected by the prediction unit 30 and the predicted value Ps of the power generation amount, thereby suddenly changing the weather. Even if the power generation amount Ps suddenly decreases due to the above, the predicted value Ps of the power generation amount is predicted to decrease depending on the contribution rate as it approaches the end of the demand time period. Supply control becomes possible, and it is possible to effectively suppress the generation of peak power in which the amount of power consumption supplied from commercial power at the end of the demand period exceeds the target value Pt.

  In particular, the contribution rate β (t) is set to a value that becomes smaller as the remaining time until the end of the demand time period is reduced in the range of 0 to 1, while suppressing excessive power supply from the storage battery 8, Effective suppression of peak power in consideration of the weather can be realized.

  In particular, when the solar power generation device or the wind power generation device is used as the power generation device as in the present embodiment, the change in the amount of power generation due to the weather increases, so the present invention is effective.

  In addition, in the said Example, since discharge by the storage battery 8 is not performed until the time of 20 minutes having passed since the start of the demand time limit, the consumption predicted value of commercial power is calculated as the predicted value Pp of the consumed power amount−the predicted value of the generated power amount. In the prediction / control process in the middle of the demand time limit, when the discharge by the storage battery 8 is performed before the prediction is made, the electric energy Pd already discharged by the storage battery 8 is also taken into consideration. The predicted power consumption value is assumed to be a power consumption prediction value Pp−a power generation prediction value Ps−a storage battery discharge amount Pd. Thereby, the accuracy of prediction / control in the middle of the demand time period can be further improved.

  Moreover, in the said Example, the consumption constructed | assembled by matching and storing the electric energy actually consumed with the power consumption apparatus, the apparatus environmental conditions including the temperature and humidity data at that time, and a time slot | zone A power generation result database 33, a power generation result database 34 constructed by associating and storing the amount of power actually generated by the power generation device 7 and the power generation environmental conditions and time zones including the weather data at that time; The prediction unit 30 refers to the power consumption result database 33 and the power generation result database 34 on the basis of the current device environment condition and power generation environment condition, and calculates the predicted value Pp of power consumption and the predicted value Ps of power generation. Although it is forecasted, it is not limited to this. Each equipment environmental condition, power generation environmental condition, and each time zone are converted into numerical values, and by using an arithmetic expression, The predicted value Ps of Hakachi Pp and the power generation amount may be predicted. This also makes it possible to realize control based on highly accurate prediction.

  In addition, the said Example is an Example corresponded to invention of Claim 2 of this application. On the other hand, an embodiment corresponding to the invention of claim 1 of the present application will be described below as another embodiment. In this case, the storage battery 8 in the above embodiment is not provided, or the storage battery 8 is not used. Therefore, in step S16 of FIG. 6 in “prediction / control process at start of demand time period” and in step S33 of FIG. 9 in “prediction / control process in the middle of demand time period”, from the predicted value Pp of the predicted power consumption amount. The predicted commercial power consumption value Pp-Ps obtained by subtracting the predicted power generation value Ps is obtained by multiplying the target value Pt of the power consumption per one demand time period or the target value Pt by a predetermined safety coefficient α. If it exceeds the set value Pt × α of the power consumption obtained in this way, the process proceeds to “discharge / equipment demand control determination process” in step S17 or step S34. In the “discharge / equipment demand control determination process”, when the discharge is started from the storage battery 8 in step S23 of FIG. 8, the storage battery 8 is not used or is not used. In step S24, it is determined that Pr ≧ Pp−Ps−Pt × α is not satisfied, and the process proceeds to step S25. And in the said step S25, since the charge amount Pr of the storage battery 8 is 0, the electric power control part 31 is each electric power consumption apparatus, such as an air conditioner, only Pp-Ps-Ptx (alpha) which is a difference amount electric power. The control which suppresses the output of is performed.

  At this time, the prediction unit 30 determines whether the demand period is in progress, that is, in the “prediction / control process during the demand period”, based on the amount of power actually consumed by the power consuming device. While correcting the predicted value Pp of the power consumption amount, the predicted value Ps of the power generation amount until the end of the demand time period is decreased as it approaches the end of the demand time period based on the power amount actually generated by the power generation device 7. Commercial power obtained by correcting by the contribution rate and subtracting the predicted value Ps of the power generation amount corrected based on the contribution rate of the prediction unit 30 from the predicted value Pp of the power consumption amount corrected by the prediction unit 30 by the power control unit 31 When the predicted consumption value Pp−Ps of the power consumption exceeds the target value Pt of the power consumption amount per demand time limit or the set value Pt × α, control for suppressing the output of the power consuming device is performed. Thus, as in the case of the above embodiment, even when the storage battery 8 is not provided, similarly, even if the amount of power generation suddenly decreases due to sudden weather changes, Thus, it is possible to perform control for suppressing the output of the power consuming device, and to effectively suppress the generation of peak power.

1 Demand control device 2 Showcase (power consuming equipment)
3 Refrigerator (power consuming equipment)
4 Air conditioners (power consuming equipment)
5 Lighting (power consumption equipment)
7 Power generation equipment (solar power generation equipment)
8 Storage battery 10 AC line (commercial power system)
DESCRIPTION OF SYMBOLS 11 Cubicle 12 Power conditioner 13 AC / DC converter 14 DC / AC converter 15 Communication line 20 Power meter 21 Outside temperature sensor 22 Humidity sensor 23 Network 24 Server 30 Prediction part 31 Power control part 32 Comparison part 33 Power consumption performance database 34 Power generation Quantity result database 35 Electricity usage amount acquisition unit 36 Power generation amount acquisition unit 37 Outside air temperature acquisition unit 38 Absolute humidity acquisition unit 39 Weather data acquisition unit 40 Timer 41 Storage battery remaining amount acquisition unit 42 Storage battery control unit 43 Device control unit 44 Acquisition of battery discharge amount Part

Claims (10)

A demand control device that controls power supply from a power generation means that generates power using commercial power and natural energy to a power consuming device,
At the start of the demand time period, a predicted value Pp of the power consumption amount by the power consuming device until the end of the demand time period is predicted based on the device environment condition, and until the end of the demand time period based on the power generation environment condition A prediction unit that predicts a predicted value Ps of the amount of power generated by the power generation means,
The predicted value Pp-Ps of commercial power obtained by subtracting the predicted value Ps of power generation from the predicted value Pp of power consumption predicted by the prediction unit is the target value Pt of power consumption per demand period. A power control unit that performs control to suppress the output of the power consuming device,
The prediction unit corrects the predicted value Pp of the power consumption amount until the end of the demand time period based on the power amount actually consumed by the power consuming device during the progress of the demand time period, and the power generation means The predicted value Ps of the power generation amount until the end of the demand time period is corrected based on the amount of power actually generated in step 1 by a contribution rate that decreases as the demand time period approaches,
The power control unit performs control to suppress the output of the power consuming device by reflecting the predicted value Pp of the power consumption corrected by the prediction unit and the predicted value Ps of the power generation amount. Control device. A demand control device for controlling power supply from a power generation means for generating power using commercial power, a storage battery, and natural energy to a power consuming device,
At the start of the demand time period, a predicted value Pp of the power consumption amount by the power consuming device until the end of the demand time period is predicted based on the device environment condition, and until the end of the demand time period based on the power generation environment condition A prediction unit that predicts a predicted value Ps of the amount of power generated by the power generation means,
The predicted value Pp-Ps of commercial power obtained by subtracting the predicted value Ps of power generation from the predicted value Pp of power consumption predicted by the prediction unit is the target value Pt of power consumption per demand period. A power control unit that controls the output of the storage battery to start or increase the supply of power from the storage battery to the power consuming device,
The prediction unit corrects the predicted value Pp of the power consumption amount until the end of the demand time period based on the power amount actually consumed by the power consuming device during the progress of the demand time period, and the power generation means The predicted value Ps of the power generation amount until the end of the demand time period is corrected based on the amount of power actually generated in step 1 by a contribution rate that decreases as the demand time period approaches,
The power control unit controls power supply by the storage battery by reflecting the predicted value Pp of the power consumption and the predicted value Ps of the power generation amount corrected by the prediction unit.   The power control unit is configured to obtain a commercial power consumption predicted value Pp-Ps obtained by subtracting the power generation amount predicted value Ps from the power consumption predicted value Pp predicted by the prediction unit. Before exceeding the target value Pt, when exceeding the set value Pt × α of the power consumption obtained by multiplying the target value Pt by a predetermined safety coefficient α, control to suppress the output of the power consuming device, or The demand control device according to claim 1, wherein the output of the storage battery is controlled to start or increase the supply of power from the storage battery to the power consuming device.   4. The contribution rate according to claim 1, wherein the contribution rate is a value in a range of 0 to 1 and decreases as the remaining time until the end of the demand time period decreases. Demand control device.   5. The demand control apparatus according to claim 3, wherein the prediction unit decreases the safety coefficient α toward a time point closer to a start time of a demand time period.   The power control unit predicts a time when the power charged in the storage battery is used up, and when the predicted time is a time zone in which the unit price of commercial power falls, the output of the storage battery is controlled to the power consuming device. The demand control apparatus according to any one of claims 2 to 5, wherein supply of electric power is started or increased, and commercial power is charged into the storage battery in a time zone in which a unit price of commercial power decreases.   The power control unit, when the predicted power consumption value Pp-Ps predicted by the prediction unit exceeds the power consumption target value Pt or the power consumption set value Pt × α, the difference between them The demand according to any one of claims 2 to 6, wherein when the charge exceeds the charge amount of the storage battery, control is performed to suppress the output of the power consuming device for the difference amount of power. Control device. A power consumption result database constructed by associating and storing the amount of power actually consumed by the power consuming device, the device environmental conditions including temperature and humidity data at that time, and a time zone;
A power generation result database constructed by associating and storing the amount of power actually generated by the power generation means and the power generation environmental conditions and time zones including the weather data at that time,
The prediction unit predicts the predicted value Pp of the power consumption amount and the predicted value Ps of the power generation amount with reference to the actual power consumption database and the actual power generation result database based on the current device environment condition and power generation environment condition. The demand control apparatus according to any one of claims 1 to 7, wherein the demand control apparatus according to any one of claims 1 to 7 is provided.   When the control for suppressing the output of the power consuming device is performed, the amount of power consumption of the power consuming device when the output of the power consuming device is not suppressed is estimated to construct the power consumption record database. The demand control apparatus according to claim 8, wherein   The demand control device according to any one of claims 1 to 9, wherein the power generation means is a solar power generation device or a wind power generation device.

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