Source: https://patents.google.com/patent/JP5908302B2/en
Timestamp: 2019-12-09 22:03:30
Document Index: 173361584

Matched Legal Cases: ['art 14', 'art 14', 'art 10', 'art 10', 'art 11', 'art 11', 'art 11', 'art 11', 'art 122']

JP5908302B2 - Storage energy storage optimization device, optimization method and optimization program - Google Patents
Storage energy storage optimization device, optimization method and optimization program Download PDF
JP5908302B2
JP5908302B2 JP2012040650A JP2012040650A JP5908302B2 JP 5908302 B2 JP5908302 B2 JP 5908302B2 JP 2012040650 A JP2012040650 A JP 2012040650A JP 2012040650 A JP2012040650 A JP 2012040650A JP 5908302 B2 JP5908302 B2 JP 5908302B2
JP2012040650A
JP2013174412A (en
正明 齋藤
村山　大
憲史 三ッ本
2012-02-27 Priority to JP2012040650A priority Critical patent/JP5908302B2/en
2013-09-05 Publication of JP2013174412A publication Critical patent/JP2013174412A/en
2016-04-26 Publication of JP5908302B2 publication Critical patent/JP5908302B2/en
Embodiments of the present invention relate to a technique for optimizing an operation schedule of devices to be controlled such as energy supply devices, energy consuming devices, energy storage devices and the like in a building, for example.
Domestic energy consumption of buildings such as buildings is about 20% of the final energy consumption. For this reason, if the manager and user of the building can continue to save energy, the final energy consumption can be suppressed.
Furthermore, in response to the recent tightening of power demand, there is an increasing need for peak cuts that reduce energy consumption during peak hours. For example, an upper limit of electric power used is imposed on large consumers such as buildings. In addition, there is a high need for a peak shift that uses a heat storage device to shift the peak time of energy consumption.
Against this background, the introduction of energy supply equipment that uses renewable energy such as sunlight and solar heat is expected to accelerate further in the future. However, the output of energy supply equipment that uses renewable energy is greatly affected by weather conditions such as the weather. For this reason, the introduction of energy storage devices such as storage batteries and heat storage devices that can compensate for this will also increase in the future.
As described above, in the future, energy supply devices and energy storage devices introduced into facilities such as buildings are expected to diversify. In addition, an operation planning method for efficiently operating these devices in an entire building by linking them well with existing devices is required.
For example, there is a technique for minimizing energy consumption, cost, and CO 2 generation amount in a predetermined period for an energy supply facility having a heat storage tank. In addition, there are a method for performing peak cut based on air conditioning load prediction, a method for utilizing ice thermal storage air conditioning for peak cut, and the like.
Japanese Patent No. 3763767 Japanese Patent No. 3519321 Japanese Patent No. 3669755
By the way, all of the conventional planning methods for building operation plans are methods that focus only on heat storage. Photovoltaic power generation devices and storage batteries, solar water heaters, and heat storage in which the amount of energy supplied depends on the weather. The device is not considered.
Conventionally, energy consumption is predicted in advance, and an operation plan for energy consuming equipment and energy storage equipment is drawn up based on the predicted value. However, generally, energy consumption is predicted based on past data such as weather and electric power demand. For this reason, in the prediction, the characteristic depending on the operation state for a plurality of different types of devices is not considered, and high prediction accuracy is not necessarily obtained.
Embodiments of the present invention have been proposed to solve the above-described problems of the prior art, and the purpose thereof is to set the prediction and storage heat storage schedule considering the control setting value of each control target device. It is intended to provide a storage heat storage optimization technology that improves prediction accuracy and enables efficient operation.
In order to achieve the above object, an embodiment of the present invention performs control based on a prediction unit that sets a predicted value of energy consumption or supply energy of a plurality of control target devices, and a predicted value set by the prediction unit. A start / stop optimization unit that creates a start / stop schedule for the target device, the start / stop optimization unit based on the startup priority of the control target device determined based on a predetermined evaluation index, A start / stop condition setting unit that sets a start / stop condition for a control target device according to thermal energy consumption, and a start device that allocates a control target device to be started at each time based on the start / stop condition and the predicted value The allocation unit, the manufacturing unit price calculation unit that calculates the cooling unit price of the controlled device with the lowest startup priority among the controlled units that start at each time, and heat radiation from the time when the cooling unit price is high Sequentially assigned, and having a heat storage radiator assignment unit cold production cost sequentially assign heat storage or energy storage from a low time of discharge.
In addition, as another aspect, it can also be grasped as a method for realizing the functions of the above-described units by a computer or an electronic circuit and a program to be executed by the computer.
Connection configuration diagram showing an example of a storage heat storage optimization system Connection configuration diagram showing a configuration example of controlled devices in a building Block diagram showing a configuration example of a storage heat storage optimization device Block diagram showing the configuration of the optimization processor The flowchart which shows the processing procedure at the time of the next day schedule planning of the storage energy storage optimization device The figure which shows an example of the past weather data and operation data which were memorize | stored in the process data storage part Flow chart showing processing procedure of start / stop optimization unit The figure which shows the cold production cost of the control target equipment The figure which shows the thermal production unit price of the control object equipment The figure which shows starting order and start / stop condition of the control object equipment The figure which shows the allocation of the control object apparatus in each time A figure showing an example of the daily cold water production unit price The figure which shows the example which rearranged the daily cold water production unit price in ascending order The figure which shows the allocation of the control target equipment according to the cold production price Diagram showing optimization variables for state optimization Figure showing an example of an evaluation index selection screen Flow chart showing the processing procedure for rescheduling on the day The figure which shows the example of a burden level presentation in a setting value adjustment part The figure which shows the example of a burden level presentation in a setting value adjustment part The figure which shows the logic of PMV setting and illumination intensity setting according to the number of people in the room The figure which shows the example of presentation of the burden level classified by room according to the number of people in a room in a setting value adjustment part
[A. Outline of Embodiment]
[1. Storage heat storage optimization system]
As shown in FIG. 1, the power storage heat storage optimization system of the present embodiment includes various control target devices 2, a local control device 3, and a power storage heat storage optimization device 4 installed in a building 1.
The control target device 2 includes at least one of an energy consuming device, an energy supply device, and an energy storage device. The energy consuming equipment includes, for example, air conditioning (air conditioning) equipment, lighting equipment, and heat source equipment. An energy supply apparatus contains a solar power generation device (PV) and a solar water heater, for example. The energy storage device includes a storage battery and a heat storage device. The CGS, air-cooled HP, water-cooled refrigerator, absorption chiller / heater, etc., which will be described later, are energy consuming devices. The control target device 2 of the present embodiment includes a device that also serves as one of an energy consuming device, an energy supply device, and an energy storage device.
The local control device 3 is a device that is connected to each control target device 2 and controls starting and stopping of each control target device 2. Hereinafter, the start / stop may be referred to as start / stop. The local control device 3 may be provided for each control target device 2 or may be configured to control a plurality of control target devices 2 collectively. The control by each local control device 3 follows an instruction by the storage heat storage optimization device 4 connected to each local control device 3 via the network N.
The power storage heat storage optimization device 4 is a device that optimizes the power storage heat storage schedule of the control target device 2 based on process data, setting parameters, and the like. The power storage heat storage schedule is information that optimizes the schedule of starting and stopping of each control target device and the state quantity of each control target device in a predetermined future period.
The process data includes information from the outside that changes over time, such as weather data, operation data, target values, control set values, and the like. The weather data includes past weather data and weather forecast data. The operation data includes control setting values (to be described later) of the past control target devices 2 and state quantities of the control target devices 2 at the time of execution of the power storage heat storage schedule. The target value includes a power suppression command value, a peak shift request value, and a request value from the building manager. The power suppression command value is determined by a contract or a request from an electric power company.
The control set value is a set value for operating each control target device 2. This control set value is a parameter that determines the start, operation state, and stop of each control target device 2. The control set value may be determined based on a power storage heat storage schedule when set by default, when selected from past operation data.
For example, the control set value includes a temperature set value, a PMV set value, an illumination illuminance set value of an air conditioner that is an energy consuming device, and the like. PMV is an abbreviation for Predicted Mean Vote, and is defined by the thermal index ISO7730 for air conditioning. PMV is a numerical value of how a person feels cold, where 0 is comfortable, − is cold, and + is warm. Parameters used for calculating PMV are temperature, humidity, average radiation temperature, amount of clothes, amount of activity, wind speed, and the like.
The control set value also includes CGS as an energy supply device, air-cooled HP, water-cooled refrigerator, output of absorption chiller / heater, load factor, and the like. Further, the control set value includes a storage battery that is an energy storage device, a storage amount of the heat storage device, a discharge amount, a heat storage amount, a discharge amount, and the like.
The setting parameters include, for example, various parameters used for the processing of the present embodiment, such as processing timing, weighting factor, evaluation index, device characteristic, threshold value, and the like. The processing timing includes timing when the optimization processing unit 40 starts processing, and timing when the rescheduling necessity determination unit 17 determines whether rescheduling is necessary.
The weighting coefficient is a coefficient used for similarity calculation described later. The evaluation index is an index that should be minimized for optimization, such as energy consumption, supply energy, and cost. The device characteristics include various parameters determined according to each device, such as the rating, lower limit output, and COP of each device 2 to be controlled.
COP (Coefficient of performance) is a coefficient of performance of a heat source device such as a heat pump, and is obtained by dividing cooling or heating capacity by power consumption. The threshold value is a threshold value for determining a difference between the operation data and the control setting value. The device priority is a priority of the control target device 2 that raises the burden level.
[2. Controlled device]
FIG. 2 shows a connection configuration example of various control target devices 2 and energy flows such as cold water, hot water, electricity, and gas. The energy transfer relationship of these devices to be controlled 2 is to supply electricity, cold heat, and hot heat to the room using the electric power received from the outside and the gas supplied from the outside as the energy source.
The control target device 2 shown here is an example, and it is free to use which control target device 2 is used or not. In addition, this embodiment does not exclude the control target device 2 that is not illustrated.
As the control target device 2, a storage battery 100, a PV 101, a CGS 103, an air-cooled HP 104, a water-cooled refrigerator 105, an absorption chiller / heater 106, a solar water heater 107, and a heat storage tank 108 are installed.
The storage battery 100 is a facility that uses a secondary battery that can perform both charging and discharging. The PV 101 is a power generation facility that includes a solar panel that converts sunlight energy into electrical energy. The PV 101 is one of devices in which the amount of energy supplied varies depending on weather conditions such as the weather.
A CGS (Co-Generation System) 103 is a system that can use exhaust heat along with power generation by an internal combustion engine or an external combustion engine. The CGS 103 in this example is a combined heat and power system that generates power using gas as an energy source and can use exhaust heat. A fuel cell may be used as a power generation and heat source.
An air-cooled HP (Heat pump) 104 is an apparatus that supplies cold water or hot water by using a phase change of a refrigerant using air as a heat source. The water-cooled refrigerator 105 is a device that supplies cold water by changing the phase of a refrigerant using water as a heat source.
The absorption chiller / heater 106 is a device that supplies cold water or hot water between a refrigerant condenser and an evaporator through a process of absorption of water vapor and regeneration by a heat source. As energy of the heat source, exhaust heat from gas, CGS 103, solar water heater 107, or the like can be used.
The solar water heater 107 is a water heater that supplies hot water using solar heat. The solar water heater 107 is one of devices in which the amount of energy supplied varies depending on weather conditions such as the weather. The heat storage tank 108 is a tank that stores heat using a stored heat medium. The air-cooled HP 104, the water-cooled refrigerator 105, the absorption chiller / heater 106, the solar water heater 107, and the heat storage tank 108 can supply hot water and cold water for the air conditioner 111.
Each room 110 in the building 1 is provided with, for example, an air conditioner 111, a temperature / humidity meter 112, an illuminance meter 116, an illumination 114, a camera 115, and the like. The air conditioner 111 and the illumination 114 are included in energy consuming equipment.
The flow of electricity, gas, cold water, and hot water in the control target device 2 as described above is as follows. That is, the power received from the power system is stored in the storage battery 100 or consumed by energy consuming devices such as the air conditioner 111 and the lighting 114.
The power generated by the PV 101 and the CGS 103 is also stored by the storage battery 100 or consumed by the energy consuming device. The received electric power and the generated electric power are consumed by the heat source devices of the air-cooled HP 104 and the water-cooled refrigerator 105 for heat production.
On the other hand, the gas from the gas supply system is consumed as fuel by the CGS 103 and the absorption chiller / heater 106. The absorption chiller / heater 106 can also produce cold heat using the heat generated by the solar water heater 107 or the CGS 103. The absorption chiller / heater 106 can be supplied with warmth only by supplying gas. Further, the absorption chiller / heater 106 can increase the amount of cold produced by adding gas, in addition to producing cold using hot heat.
The heat produced by the air-cooled HP 104, the water-cooled refrigerator 105, and the absorption chiller / heater 106 is stored in the heat storage tank 108 or used by the air conditioner 111 installed in the room 110 for air conditioning. The air conditioner 111 can also perform heating with hot water generated in any of the CGS 103, the air cooling HP 104, the absorption chiller / heater 106, and the solar water heater 107.
The thermohygrometer 112 includes a PMV calculation device 113 that calculates and outputs PMV based on the measured temperature and humidity. In this case, parameters other than temperature and humidity necessary for calculating PMV may be set by default, or those input from the outside may be used.
When the illumination 114 emits light by electric power, the illuminance of the room 110 changes. The camera 115 installed in the room 110 is connected to an analysis device that analyzes the illuminance of the room 110 and the number of people in the room from the captured image. Moreover, the illuminance meter 116 installed in the room 110 can measure and output the illuminance.
[B. Configuration of Embodiment]
[1. Storage heat storage optimization device]
A configuration of the storage heat storage optimization device 4 of the present embodiment will be described with reference to FIGS. 3 and 4. FIG. 3 is a block diagram showing the overall configuration of the storage heat storage optimization device 4, and FIG. 4 is a block diagram showing the optimization processing unit 40.
The storage energy storage optimization device 4 includes an optimization processing unit 40, a process data acquisition unit 20, a setting parameter input unit 21, a processing data storage unit 22, an optimization data storage unit 23, and a transmission / reception unit 24.
[2. Optimization processing unit]
The optimization processing unit 40 is a processing unit that optimizes the start / stop schedule of the device and the power storage heat storage schedule by calculation based on various processing data to be described later. The optimization processing unit 40 includes a set value adjustment unit 10, a prediction unit 11, a start / stop optimization unit 12, a state quantity optimization unit 13, a goal achievement determination unit 14, a control set value output unit 15, an inquiry unit 18, and a replay unit 18. A scheduling necessity determination unit 17 is included.
(Set value adjustment section)
The set value adjustment unit 10 is a processing unit that sets control set values such as temperature settings of an air conditioner and illumination intensity. As shown in FIG. 4, the set value adjusting unit 10 includes a setting unit 10a and an adjusting unit 10b. The setting unit 10a is a processing unit that sets a control set value. The adjustment unit 10b is a processing unit that adjusts the control set value in accordance with a purpose such as energy consumption suppression.
(Prediction unit)
The prediction unit 11 is a processing unit that predicts energy consumption or supply energy of the control target device 2. As shown in FIG. 4, the prediction unit 11 includes a similarity calculation unit 11a, a similar date extraction unit 11b, and a predicted value setting unit 11c.
The similarity calculation unit 11a is a processing unit that calculates the similarity with the execution date of the storage heat storage schedule to be optimized based on past weather data and control set values within a predetermined period. The similar date extraction unit 11b is a processing unit that extracts a date similar to the execution date of the power storage heat storage schedule based on the similarity calculated by the similarity calculation unit 11a. The predicted value setting unit 11c is a processing unit that sets the consumed energy or the supplied energy based on the operation data on the similar date extracted by the similar date extracting unit 11b as the predicted value.
(Start / Stop Optimization Department)
The start / stop optimization unit 12 is a processing unit that optimizes the start / stop schedule so that predetermined evaluation indexes such as energy consumption and energy cost of the control target device 2 are minimized. As shown in FIG. 4, the device start / stop optimization unit 12 includes a start priority determination unit 121, a start / stop condition setting unit 122, a start device allocation unit 123, a manufacturing unit price totaling unit 124, a heat storage / radiation allocation unit 125, a heat storage unit. A capacity determination unit 126 is included.
The activation priority determining unit 121 is a processing unit that determines the priority for activating the control target device 2 based on the evaluation index. The start / stop condition setting unit 122 is a processing unit that sets the start / stop condition of the control target device 2 based on the priority order, the characteristics of the control target device 2 and the energy consumption of cold or warm. This start / stop condition is composed of a start boundary condition and a stop boundary condition.
The activation boundary condition is a condition that becomes a boundary for activating the control target device 2. The stop boundary condition is a condition that becomes a boundary for stopping the activated control target device 2. For this reason, the start / stop condition setting unit 122 includes a start boundary condition setting unit 122a and a stop boundary condition setting unit 122b. The activation boundary condition setting unit 122a is a processing unit that sets the activation boundary condition based on the energy consumption of cold or warm heat. The stop boundary condition setting unit 122b is a processing unit that sets a stop boundary condition.
In the present embodiment, the stop boundary condition setting unit 122b sets the stop boundary condition so as to be a value smaller than the start boundary condition. This is because, for each control target device 2, even if the value of energy consumption is lower than the start boundary condition, there is a width until the value to be stopped is reached. This width is called a stop dead zone, which will be described in detail later.
The activation device allocation unit 123 is a processing unit that allocates the control target device 2 to be activated at each time of the day based on the activation boundary condition, the stop boundary condition, and the predicted energy consumption. The manufacturing unit price totaling unit 124 is a processing unit that calculates the manufacturing unit price at each assigned time, based on the manufacturing unit costs of cooling and heating of each control-compatible device 2.
The heat storage heat radiation allocation unit 125 is a processing unit that allocates heat storage or cold heat of a heat storage facility such as the heat storage tank 108 according to the calculated manufacturing unit price. The heat storage capacity determination unit 126 is a processing unit that determines whether or not the heat release amount of the assigned heat storage facility or the integrated value of the heat storage amount has reached the capacity of the heat storage facility.
(State quantity optimization section)
The state quantity optimizing unit 13 optimizes the continuous state quantity such as the amount of heat supplied to each control target device 2 whose start / stop is determined in the start / stop schedule based on the evaluation index, thereby This is a processing unit to be obtained.
(Goal achievement determination part)
The target achievement determination unit 14 is a processing unit that determines whether or not the optimized power storage heat storage schedule satisfies the target value. The target value includes a power suppression command value, a peak shift request value, and a request value from the building manager.
The target achievement determination unit 14 includes a comparison unit 14a, a determination unit 14b, an output instruction unit 14c, and an adjustment instruction unit 14d. The comparison unit 14a is a processing unit that compares the optimized power storage heat storage schedule with the target.
The determination unit 14b is a processing unit that determines whether the power storage heat storage schedule satisfies the target value based on the comparison result by the comparison unit 14a. The output instruction unit 14c is a processing unit that instructs the control set value output unit 15 to output the control set value for the power storage heat storage schedule determined by the determination unit 14b to satisfy the target value. The adjustment instruction unit 18d is a processing unit that instructs the set value adjustment unit 10 to readjust the set value when the determination unit 14b determines that the target value is not satisfied.
(Control set value output section)
The control set value output unit 15 is a processing unit that generates a control set value for each control target device 2 based on the power storage heat storage schedule and outputs the control set value to each local control device 3.
(Start instruction part)
The start instruction unit 16 is a processing unit that starts execution of optimization processing by the optimization processing unit 40 at a preset timing. For example, when setting a power storage heat storage schedule on the day before the execution date, it is conceivable that a predetermined time every day is set as the setting timing. It is possible to freely set how many days this is done and when.
(Rescheduling necessity determination unit)
The rescheduling necessity determination unit 17 is a processing unit that determines the necessity of rescheduling by comparing the control setting value based on the power storage heat storage schedule with the actual operation data at a preset timing.
For example, the rescheduling necessity determination unit 17 compares the control setting value with the operation data every 30 minutes on the execution date of the power storage heat storage schedule, and when a difference exceeding a predetermined threshold occurs. It is determined that rescheduling is necessary. It is possible to freely set the interval at which this timing is set.
(Inquiry Department)
The inquiry unit 18 is a processing unit that inquires of the local control device 3 whether or not to accept the power storage heat storage schedule when the target achievement determination unit 14 determines that the target cannot be achieved as a result of rescheduling.
The inquiry unit 18 includes a notification unit 18a, a reception unit 18b, an output instruction unit 18c, and an adjustment instruction unit 18d. The notification unit 18 a is a processing unit that notifies the local control device 3 of the target and the storage heat storage schedule to the local control device 3. The accepting unit 18 b is a processing unit that accepts a response indicating whether or not to accept from the local control device 3.
The output instruction unit 18c is a processing unit that instructs the control setting value output unit 15 to output the control setting value when the receiving unit 18b receives a response to be accepted. The adjustment instruction unit 18d is a processing unit that instructs the setting value adjustment unit 10 to readjust the setting value when the receiving unit 18b receives a response that is not accepted.
[3. Process data acquisition unit]
The process data acquisition unit 20 is a processing unit that acquires process data from the outside. As process data, operation data, weather data, target values, etc. are acquired as described above.
[4. Setting parameter input section]
The setting parameter input unit 21 is a processing unit that inputs setting parameters. As described above, the setting parameters include processing timing, weighting coefficient, evaluation index, device characteristics, threshold value, device priority order, and the like.
[5. Processing data storage unit]
The processing data storage unit 22 is a processing unit that stores data necessary for processing of the optimization processing unit 40 including process data and setting parameters. The processing data storage unit 22 includes information necessary for the processing of each unit in addition to those exemplified above. For example, arithmetic expressions and parameters for each part are included. Therefore, the processing data storage unit 22 also stores a power unit price, a gas unit price, etc. for obtaining the manufacturing unit price.
[6. Optimized data storage unit]
The optimization data storage unit 23 is a processing unit that stores data obtained by the optimization processing by the optimization processing unit 40. For example, the optimization data storage unit 23 stores a power storage heat storage schedule, a control set value, and the like. The data stored in the optimization data storage unit 23 can be stored as past operation data in the processing data storage unit 22 or used for the arithmetic processing of each unit in the optimization processing unit 40.
[7. Transmitter / receiver]
The transmission / reception unit 24 transmits / receives information to / from the storage heat storage optimization device 4 and the local control device 3, a building manager's terminal, a host supervisory control device, a server that provides weather information, and the like via the network N. It is a processing part to perform. The data stored in the processing data storage unit 22 and the optimization data storage unit 23 are transmitted by the transmission / reception unit 24, so that an external device as described above can be used.
The storage heat storage optimization device 4 includes an input unit for inputting information necessary for processing of each unit, an input unit for inputting processing selections and instructions, an interface for inputting information, an output unit for outputting processing results, and the like. Yes.
The input unit includes input devices that can be used now or in the future, such as a keyboard, a mouse, a touch panel, and a switch. The input unit can also perform the function of the setting parameter input unit 21 described above. The output unit includes any output device that can be used now or in the future, such as a display device and a printer. The operator can refer to the data stored in the processing data storage unit 22 and the optimization data storage unit 23 by displaying the data on the output unit.
[C. Operation of the embodiment]
The procedure of the optimization process according to the present embodiment as described above will be described with reference to FIGS.
[1. Processing to optimize the next day's operation schedule to the night before]
The process of the storage heat storage optimization device 4 will be described with reference to the flowchart of FIG. In addition, the process demonstrated below is a process which optimizes the electrical storage thermal storage schedule of the next day of the control object apparatus 2 in the building 1 on the night of the previous day, for example. Note that the power storage heat storage schedule to be optimized may be a predetermined period in the future, and is not limited to the next day or one day.
[1-1. Optimization execution start processing]
First, the start instruction unit 16 instructs the set value adjustment unit 10 to execute the optimization process at a preset time. For example, at 21:00 on the previous day, the optimization processing unit 40 starts executing the optimization process. The flowchart in FIG. 5 shows a processing flow after the execution of the optimization process is started in accordance with an instruction from the start instruction unit 40.
[1-2. Setting value adjustment process]
The setting unit 10a of the setting value adjusting unit 10 sets a control setting value in the building 1 on the next day (step 01). The control set value includes, for example, an air conditioning temperature set value, a PMV set value, an illuminance set value, and the like. The setting unit 10a sets, for example, the latest control setting value or the most frequently used control setting value among the operation data stored in the processing data storage unit 22 within a predetermined period as the control setting value. Note that the setting unit 10a can also set the setting value input via the input unit as the control setting value.
[1-3. Energy prediction process]
The prediction unit 11 predicts the energy consumption or supply energy of the control target device 2 based on the weather data and operation data of the past predetermined period stored in the processing data storage unit 22 (step 02).
Here, an example of the prediction process by the prediction unit 11 will be described. FIG. 6 is a table summarizing past days of the week, weather, temperature and humidity, and control set values stored in the processing data storage unit 22 as weather data and operation data. The reason for including the day of the week is that, depending on the building 1, there is a tendency of energy consumption depending on the day of the week, such as few people on Saturdays and Sundays. The control set value is, for example, a PMV set value or a PMV measured value, an illuminance set value or an illuminance measured value.
The similarity calculation unit 11a in the prediction unit 11 calculates the similarity between the weather data based on the weather forecast of the next day and the set control setting value based on the past data as described above. This calculation can be obtained by, for example, the following formula (1).
Here, the “weight by day of the week” uses a weight coefficient for each day of the week set in advance. Similarly, the “weight by weather” uses a preset weighting factor for each weather. For example, when the weather based on the forecast for the next day is “sunny”, the weight coefficient is small when the past data is “sunny”, but the weight coefficient is large when the past data is “rain”. The weighting factor of each factor such as “weight by day of the week” and “weight by weather”, a, b, c, d, and e is input from the setting parameter input unit 21 and stored in the processing data storage unit 22. Can be arbitrarily set according to the prediction accuracy.
The similar day extraction unit 11b extracts a day number that minimizes the similarity based on the similarity obtained by the similarity calculation unit 11a. The day number is a serial number obtained by allocating the operation data stored in the operation data storage unit 21 side by side.
The predicted value setting unit 11c sets the consumed energy or supplied energy of each control target device 2 on the date corresponding to the day number extracted by the similar date extracting unit 11b as the predicted value of the next day.
[1-4. Device start / stop optimization processing]
Next, the start / stop optimization unit 12 optimizes the start / stop schedule of the control target device 2 based on the predicted value set by the prediction unit 11. Here, the detailed processing of the start / stop optimization unit 12 will be described with reference to the flowchart of FIG. As a title index for optimization, it can be arbitrarily selected from several patterns as will be described later. However, here, as an example, a case where cost is selected as the minimization index will be described.
(Startup priority determination process)
That is, the activation priority determining unit 121 of the device start / stop optimizing unit 12 determines the priority for activating the control target device 2 (step 21). Here, an example of the cooling / heating unit price table used for determining the activation priority of the control target device 2 is shown in FIG.
The unit price table for cold heat production sets a plurality of cases as the supply mode of the control target device 2 that supplies cold heat, calculates the unit price when producing a unit amount of cold heat [kWh] for each case, and summarizes the table. Is. About each control object apparatus 2, the part applicable when supplying cold heat is made into a circle, and the unit price of the case is indicated in the bottom of the table.
The cold manufacturing unit price can be obtained by, for example, the following formulas (2) to (7).
Here, Case 3 is the unit price for manufacturing the cold when the power generated by the CGS 103 has no value. “No value” means a case where the power generated by the CGS 103 is not used effectively, for example, the demand for power is very small because the energy consuming equipment is hardly in operation.
On the other hand, Case 4 is a unit price for cold / heat production when the power generated by the CGS 103 is valuable. “Has value” means the case where the power generated by the CGS 103 is effectively consumed and the purchase of an equal amount of power can be reduced.
In addition, Case 5 is a unit price for cold / heat production using the hot water output of the solar water heater 107 for the absorption chiller / heater 106. For this reason, there is no consumption of fuel or the like, and the cost is nearly zero. Actually, a small amount of electric power is consumed by the operation of the auxiliary machinery. However, this value is so small that it is not considered here.
FIG. 9 shows an example of a thermal production unit price table used for determining the activation priority order of the control target device 2. The thermal production unit price table sets a plurality of cases as the supply mode of the control target device 2 that supplies the thermal energy, calculates the unit price for manufacturing the unit amount of thermal [kWh] for each case, and summarizes the table. It is a thing.
The thermal production unit price can be obtained by, for example, the following formulas (8) to (12).
The boot priority order determination unit 121 uses these tables to determine the boot priority order from the device with the smallest evaluation index. Here, the evaluation index is a cost. Taking the above-mentioned cooling and manufacturing unit price table as an example, the priority cases are in the order of Case 5 → Case 1 → Case 4 → Case 2 → Case 6 → Case 3.
Therefore, the priority of activation of the control target device 2 that supplies the cold energy is in the order of (1) to (5) below when the output of the solar water heater 107 is stable. This is a state in which sunlight is sufficiently obtained, for example, clear weather continues.
(1) Absorption chiller / heater 106 (using solar heat)
(2) Water-cooled refrigerator 105
(3) CGS 103 and absorption chiller / heater 106 (using CGS exhaust heat, but remaining power still remains using solar heat)
(4) Air-cooled HP104
(5) Absorption chiller / heater 106 (using gas)
Moreover, when there is no output of the solar water heater 107, it becomes the following (1)-(4) order.
(1) Water-cooled refrigerator 105
(2) Absorption chiller / heater 106 (using CGS exhaust heat)
(3) Air-cooled HP104
(4) Absorption chiller / heater 106 (using gas)
In this way, the activation priority order determination unit 121 can determine the activation priority order of the control target device 2 used for cooling or heating supply by calculating the unit cost of cooling and heating for each control target device 2. Even in the minimization problem where the evaluation index is other than the cost, the activation priority order of the control target devices 2 may be determined in the same order from the smallest evaluation index.
(Start / stop condition setting process)
Next, the start / stop condition setting unit 122 calculates the start / stop condition of the control target device 2 according to the energy consumption of the cooling and heating based on the starting priority obtained by the starting priority determining unit 121 (step 22). ).
An example of the start / stop condition is shown in FIG. FIG. 10 shows an example of the start / stop condition of the cold energy supply device according to the cold energy consumption when the output of the solar water heater 107 can be stably expected.
First, the activation boundary condition setting unit 121a obtains an activation boundary condition for activating each control target device 2 in accordance with an increase in cold energy consumption. This starting boundary condition can be defined by the following equations (13) to (16), for example.
The start boundary condition [1] is a start condition for the water-cooled refrigerator 105. This starting condition is a case where the cold energy consumption is equal to or higher than the output of the absorption chiller / heater 106 using solar heat.
The start boundary condition [2] is a start condition of the CGS 103. This activation condition is when the cooling energy consumption is equal to or greater than the sum of the output of the absorption chiller / heater 106 using solar heat and the rated output of the water-cooled refrigerator 105.
The start boundary condition [3] is a start condition of the absorption chiller / heater 106. This starting condition is a case where the starting boundary condition [2] is equal to or greater than the sum of the difference between the rated cooling amount of the absorption chiller / heater 106 and the increase in the output of the absorption chiller / heater 106 by the CGS 103. is there.
The start boundary condition [4] is a case where the start boundary condition [3] and the rated cooling amount of the air-cooled HP 104 are equal to or greater than the sum. As described above, the activation boundary condition is defined by stacking the rated outputs of the devices to be controlled 2 in descending order of activation priority.
Next, the stop boundary condition setting unit 122b obtains a stop boundary condition for stopping each control target device 2. This stop boundary condition can be defined by the following equations (17) to (20), for example.
The stop boundary conditions [1] to [4] of each control target device 2 are set to values slightly smaller than the respective start boundary conditions [1] to [4]. Thereby, the stop dead zone is set for the stop boundary conditions [1] to [4] for each control target device 2. This is ΔH R , ΔH ABR-CH , ΔH HP-C , and ΔH ABR-CG in the equations (17) to (20).
The stop dead zone is a width or region provided between the start boundary condition and the stop boundary condition. The state in which the control target device 2 is in the stop dead zone is regarded as hysteresis in the sense that the start state is maintained without being influenced even after the start condition is once started by the start condition and is again below the start condition. You can also.
By setting the stop dead zone in this way, it is possible to exclude an operation plan in which the control target device 2 is excessively started and stopped even if the cold energy consumption fluctuates in the vicinity of the boundary.
The stop boundary condition is set in a range that does not become the lower limit output of each control target device 2. The reason will be described below. That is, each control target device 2 has a lower limit output. For this reason, depending on the set value of the stop dead zone, there may be a surplus in the amount of energy supply in the vicinity of the start boundary and the stop boundary region. Therefore, it is necessary to restrict the stop dead zone setting value of each control target device 2 so that the remainder of the energy supply amount does not occur. The following formulas (17) ′ to (20) ′ are formulas that define a stop dead zone in consideration of such constraints.
Here, this restriction will be described by taking, as an example, Expression (17) ′ relating to the stop dead zone set value of the water-cooled refrigerator. In FIG. 10, it is assumed that the water-cooled refrigerator 105 is operated at the lower limit output when the demand-side cold energy consumption gradually decreases and reaches the same amount as the start boundary condition [1].
Let us consider a case where the energy consumption on the demand side further decreases from this state. In this case, since the water-cooled refrigerator 105 is operating at the lower limit output, the output cannot be further reduced. For this reason, in order to maintain the energy supply and demand balance, the output of the control target device 2 having a higher startup priority is reduced. In the example of FIG. 10, the output of the absorption chiller / heater 106 on the lower stage side is reduced.
Then, it is assumed that the cold energy consumption on the demand side further decreases and approaches the stop boundary condition [1]. At this time, stop dead zone [Delta] H R is assumed to be the absorption power adjustment width of the water dispenser 106 (H ABR-CH × r ABR-SH -H ABR-CH-min) or more.
As a result, both the water-cooled refrigerator 105 and the absorption chiller / heater 106 become lower limit outputs according to the decrease in the energy consumption of the cooling heat, and the supply amount is unavoidable. In order to avoid this, in Expressions (17) ′ to (20) ′, a restriction on the stop dead zone setting is added.
Moreover, in the last term of each of these formulas (17) ′ to (20) ′, the lower limit output of each control target device 2 is subtracted. This is because, in the start boundary condition, the corresponding control target device 2 may be the lower limit output, or the corresponding control target device 2 may not be the lower limit output as in the above example.
The stop dead zone is set because it is necessary to avoid excessive start / stop of the control target device 2 as described above. Therefore, the stop dead zone may be set to a value that can achieve the purpose of avoiding this excessive start / stop.
On the other hand, if the stop dead zone is a large value, there is a high possibility that the output of the control target device 2 having a high activation priority will be narrowed down. Therefore, in order to make effective use of the control target device 2 having a high start priority as much as possible, it is desirable that the stop dead zone of each control target device 2 is a small value within a range in which excessive start / stop does not occur.
(Starting device allocation process)
Next, the activation device allocation unit 123 is activated at each time based on the start / stop conditions (start boundary condition and stop boundary condition) set by the start / stop condition setting unit 122 and the predicted value predicted by the prediction unit 11. The device 2 to be controlled is assigned (step 23).
An example of this allocation is shown in FIG. This is an example in which the control target device 2 to be activated is assigned to the cold energy consumption. In addition, in the intermediate period between summer (cooling period) and winter (heating period), cold energy consumption and thermal energy consumption may be mixed. In this case, what is necessary is just to allocate the control object apparatus 2 to start from the one with larger heat consumption energy.
Reference numeral 30 in FIG. 11 denotes the energy consumption for cooling and heating for the next day predicted by the prediction unit 11. The activation device allocating unit 123 sets the amount of heat to be borne by the control target device 2 that operates at each time and each control target device 2 based on the start / stop condition so as to satisfy the cooling energy consumption 30 at each time. Determine the allocation.
FIG. 11 is an example in which the allocation of the control target devices 2 to be activated is stacked in order from the device having the highest activation priority at an arbitrary time. In addition, even if all the control target devices 2 are allocated, there may be a time zone in which the supply amount does not reach the cold energy consumption 30. In that case, the activation device allocation unit 123 allocates the heat radiation 31 from the heat storage tank 108 during the time period when the supply amount is insufficient (step 24). It is also possible to assign discharge by the storage battery 100.
(Manufacturing unit price calculation process)
Next, the production unit price totaling unit 124 calculates the cold production unit price at each time (step 25). Here, the cold energy production unit price is a unit price required for producing cold energy. For example, the cost required to generate 1 kWh of cold water is the cold manufacturing unit price. This calculation is performed in order to determine the starting device in consideration of heat radiation and heat storage of the heat storage facility such as the heat storage tank 108.
The cold production cost at each time is the cold water production price of the control target device 2 having the lowest startup priority among the control target devices 2 operating at the time. This is because the device 2 to be controlled has the highest unit price, and the output should be reduced first as the energy consumption decreases. The control-target device 2, 11 is assigned to the most upper. Note that the unit price for manufacturing the cooling / heating device 2 is the same as that illustrated in FIGS. 8 and 9. FIG. 12 shows the chilled water production unit prices determined in this way arranged in a time series of one day.
(Heat storage / radiation allocation process)
Next, the heat storage and heat allocating unit 125 allocates heat and heat storage at each time according to the cold manufacturing unit price (step 26). That is, the chilled water production unit price at each time in FIG. 12 is sorted in ascending order as shown in FIG. 13, heat radiation is sequentially assigned from the time zone in which the chilled water production unit price is high, and heat storage is sequentially performed from the time zone in which the chilled water production unit price is low. Will be assigned.
Thus, the example of piled up the burden of the control object apparatus 2 to be started in consideration of heat radiation from the heat storage facility and heat storage is shown in FIG. In FIG. 14, a location 32 that exceeds the predicted cold energy consumption 30 indicates heat storage in the heat storage facility.
(Heat storage capacity judgment process)
Furthermore, the heat storage capacity determination unit 126 determines whether or not the heat radiation amount of the heat storage facility or the integrated value of the heat storage amount has reached the capacity of the heat storage facility (step 27). If the capacity of the heat storage facility has not been reached (NO in step 27), the process returns to step 25 again. That is, the manufacturing unit price totaling process and the heat storage and heat radiation allocation process are repeated.
When the heat storage capacity determination unit 126 determines that the integrated value of the heat storage amount and the heat dissipation amount has reached the capacity of the heat storage facility (YES in step 27), the device start / stop optimization process is terminated. With the above processing, it is possible to realize optimization of device start / stop in consideration of heat dissipation and heat storage of the heat storage facility, which minimizes the evaluation index.
[1-5. Storage heat storage schedule optimization process]
Further, the description will be returned to the flowchart of FIG. The state quantity optimizing unit 13 uses the information on the starting device at each time derived by the device start / stop optimizing unit 12 to create a schedule for storing and storing heat. (Step 04).
The state quantity optimization unit 13 optimizes the continuous state quantity such as the amount of heat supplied to the control target equipment 2 for which the start / stop is determined by the equipment start / stop optimization unit 12 so as to satisfy the constraints of the entire facility. To do. Here, the evaluation index to be optimized is the cost. Then, for example, the objective function for minimization can be defined as the following expression (21), and the constraint condition expression can be defined as the following expressions (22) to (27).
Optimization can be achieved by obtaining the variables X1 to X17 for minimizing the expression (21) using the expressions (22) to (27). FIG. 15 shows a summary of examples of variables X1 to X17 to be optimized. Here, the superscript t of a variable or the like represents time. Note that the power coefficient and the gas coefficient in Expression (21) vary depending on the evaluation index to be optimized. Value corresponding to this, for example, if the cost minimization, each electricity unit price and gas bid, if CO 2 minimization, the CO 2 emission factor respectively.
In Expressions (22) to (25), there are a large number of product terms mainly of the load factor variable and the start / stop variable of the control target device 2. For this reason, when solving the above problem as it is, a nonlinear solution algorithm must be applied.
However, in the present embodiment, as described above, the device start / stop optimization unit 12 optimizes the start / stop conditions of the control target device 2 in advance. For this reason, among the above variables, X11 to X17 are constants, and the problem is linearized. Therefore, it is not necessary to solve the above problem as it is, and an optimum value can be easily derived as a general linear algorithm.
Here, the case where the continuous state quantity of the control target device 2 is solved by using a mathematical programming method has been described. However, the optimal state quantity may be derived by repeatedly performing a simulation.
[1-6. Goal achievement judgment process]
Next, the target achievement determination unit 14 determines whether or not the power storage heat storage schedule obtained as described above satisfies the target value (step 05). Here, the target value stored in the processing data storage unit 22 includes the power suppression command value, the peak shift request value, the request value from the building manager, and the like as described above.
That is, the comparison unit 14a of the target achievement determination unit 14 compares the supply and demand balance at each time, the target value stored in the processing data storage unit 22, and the storage heat storage schedule. And the determination part 14b determines whether the electrical storage heat storage schedule is satisfying target value based on the comparison result by the comparison part 14a. Whether or not the target value is satisfied can be determined by whether or not the target value is less than or equal to the constraint value when the target value is the constraint value. The target value may be a daily restriction or a restriction for each time zone.
When the determination unit 14b determines that the target value is satisfied (YES in step 05), the output instruction unit 14c, the control set value output unit 15, the control target device 2 stores the storage heat storage schedule and the control set value. Direct output.
When the determination unit 14b determines that the target value is not satisfied (NO in step 05), the adjustment instruction unit 14d instructs the set value adjustment unit 10 to readjust the set value.
[1-7. Control set value output processing]
When the target achievement determination unit 14 determines that the target value has been achieved, the control set value output unit 15 outputs the control set value to the local control device 3 of each control target device 2 (step 06).
Various control set value output timings are conceivable. For example, the output timing is set to the day before the execution date of the storage heat storage schedule, and the control setting value received by each local control device 3 is held. Each local control device 3 executes control based on the control setting value on the execution date. The day of the execution date of the storage heat storage schedule may be set as the output timing.
In the optimization processing unit 40, the optimization data storage unit 23 stores values calculated in a series of processes including the power storage heat storage schedule.
On the other hand, when the target achievement determination unit 14 determines that the target value has not been achieved, the process returns to step 1 and a series of optimization processes are executed again from the set value adjustment process. In this way, the power storage heat storage optimization device 4 optimizes the power storage heat storage schedule until the target value is achieved.
The above is the process which the electrical storage heat storage optimization apparatus 4 optimizes the operation schedule of the next day to the night before. In the series of processes described above, the evaluation index to be minimized is the cost. However, the evaluation index may be other than cost. For example, CO 2 , peak power reception, energy consumption, etc. can also be used as evaluation indexes to be minimized. A composite index combining these evaluation indices can also be used.
Here, FIG. 16 shows an example of a GUI for selecting an evaluation index to be optimized by the setting parameter input unit 21. This can also be realized by an input unit and an output unit configured as a touch panel. Thus, the operator can select a desired evaluation index by selecting a button corresponding to each evaluation index displayed on the screen of the display device. Then, the power storage heat storage optimization device 4 can obtain a power storage heat storage schedule that minimizes each evaluation index by the same method as described above.
[2. When changing the schedule on the day]
As described above, the control target device 2 actually starts operation the next day based on the power storage heat storage schedule optimized the night before.
Here, the operation of the power storage and storage optimization device 4 when changing the power storage and heat storage schedule on the day when the control target device 2 is operated will be described with reference to the flowchart of FIG. Note that the basic process after the start of rescheduling is the same as the process optimized on the previous day and night, so the description will be simplified.
After starting the operation of the control target device 2, the rescheduling necessity determination unit 17 determines whether rescheduling is necessary at a predetermined timing (step 07). The determination is performed by collating data such as control setting values stored in the optimized data storage unit 20 with operation data stored in the processing data storage unit 22.
As the determination timing, for example, the following can be set.
(1) A predetermined interval (for example, 30 minutes)
(2) When a request from the operator is entered
(3) When sudden changes occur in the supply energy or consumption energy of PV101, etc., which is the subject of prediction
(4) When actual weather conditions (for example, temperature, humidity, weather, etc.) deviate from the weather forecast used for prediction or when sudden changes occur
(5) When the power storage heat storage schedule optimized by the state quantity optimization unit 13 deviates from the actual device operation state
As data to be compared for determination, for example, the following is used.
(a) Measured values and predicted values of supplied energy and consumed energy
(b) Optimized power storage heat storage schedule control settings and actual device operation status
The rescheduling necessity determination unit 17 determines that rescheduling is unnecessary when these differences do not exceed the predetermined threshold values (NO in step 07). When these differences deviate from a predetermined threshold value, it is determined that rescheduling is necessary (YES in step 07).
As described above, when the rescheduling necessity determining unit 17 determines that rescheduling is necessary, the set value adjusting unit 10 performs a set value adjusting process (step 08). In this setting value adjustment process, the setting value adjustment unit 10 acquires control setting values such as the temperature setting of the air conditioner and the illumination illuminance from the processing data storage unit 22 in the same manner as the previous day's processing.
The prediction unit 11 uses the latest process data stored in the processing data storage unit 22 to predict the supply energy and consumption energy of the control target device 2 in the same manner as the previous day's processing (step 09). .
The device start / stop optimizing unit 12 optimizes the device start / stop schedule by the same method as the process on the previous day (step 10). Next, the state quantity optimization unit 13 creates a power storage heat storage schedule using the current heat storage amount of the heat storage facility and the current power storage amount of the storage battery stored in the processing data storage unit 22 as initial values (step 11).
The target achievement determination unit 14 determines whether or not the power storage heat storage schedule has achieved the target (step 12). That is, when the determination unit 14b determines that the target has been achieved (YES in Step 12), the control set value output unit 15 outputs the power storage heat storage schedule and the control set value to the control target device 2 in accordance with an instruction from the output instruction unit 14c. (Step 15).
When the determination unit 14b determines that even one target cannot be achieved (NO in step 12), the notification unit 18a of the inquiry unit 18 notifies the local control device 3 of the target and the optimization result (step 13). . The notification target may be a building manager's terminal.
In the local control device 3, the operator confirms the power storage heat storage schedule displayed on the display device, and inputs a response indicating whether or not to accept using the input device.
The receiving unit 18b of the inquiry unit 18 receives a response from the local control device 3 (step 14). The output instruction unit 18c instructs the control setting value output unit 15 to output the control setting value when the receiving unit 18b receives a response to be accepted (YES in Step 14). The control set value output unit 15 outputs the control set value to the local control device 3 (step 15).
When the accepting unit 18b accepts a response that is not accepted (NO in step 14), the adjustment instructing unit 18d instructs the set value adjusting unit 10 to perform readjustment. The adjustment unit 10b of the set value adjustment unit 10 adjusts the load level for control setting values such as the temperature setting of the air conditioner and the illumination illuminance based on a predetermined device priority order.
Here, the burden level will be described. The burden level is a temperature setting for air conditioning, a PMV setting, and an illuminance setting for illumination. The state where the burden level is high is a state where the air conditioning setting or the illuminance setting decreases the comfort or workability of the person in the building 1.
The adjustment unit 10b of the set value adjustment unit 10 repeats the setting change in the direction of increasing the burden level until all the targets determined by the target achievement determination unit 14 are satisfied in the flowchart shown in FIG.
In addition, the goal achievement determination unit 14 does not need to ask the operator whether or not it is acceptable in each repetition of the above-described repetitive operation. For example, when all the goals determined by the goal achievement determination unit 14 are satisfied, the notification unit 18a can notify the local control device 3 of the burden level based on the adjusted set value. This notification is presented to the operator by the display device of the local control device 3 displaying it.
An example of this presentation is shown in FIG. In this example, the burden level for each time is presented in a graph, and a button that allows the burden and a storage / heat storage operation replan button that does not allow the burden are displayed. The operator responds to the inquiry by selecting any button using the input unit of the local control device 3.
Further, as shown in FIG. 19, the displayed burden level may be changed by the operator using the input unit. The reception unit 18 b of the inquiry unit 18 receives information related to the change of the burden level from the local control device 3. The adjusting unit 10b of the setting value adjusting unit 10 does not automatically change the setting value, but changes the setting value based on the burden level received by the receiving unit 18b. These processes are the same when an inquiry is notified to the building manager's terminal.
Furthermore, the set value adjustment unit 10 may adjust the PMV setting and the illuminance setting for each room according to the number of people in each room 110 in the building 1.
For example, assume that a camera 115 is installed in each room 110 as shown in FIG. The camera 115 is connected to an analysis device that analyzes the number of people in the room from the captured image.
The number of people in the room from the analysis unit is input by the setting parameter input unit 21 and stored in the processing data storage unit 22. The adjustment unit 10b of the set value adjustment unit 10 adjusts the PMV setting and the illuminance setting according to the number of people in each room.
FIG. 20 shows such a setting value adjustment logic according to the number of people in the room. In FIG. 20, the range of change between the PMV setting and the illuminance setting is derived according to the degree of deviation ΔkW [%] from the target value. Here, the target value is assumed to be a power reception amount limit value based on a power suppression command.
Furthermore, a weight is assigned to the change width of the PMV setting and the illuminance setting according to the number of people in each room and the number of persons, and a difference from the current set value is obtained. Thereby, a new PMV setting and illuminance setting are derived.
For example, as shown in FIG. 21, the burden level is set lower for a room with a large number of people. Conversely, for rooms with a small number of people, the burden level is set higher. For rooms with few people, stop all equipment in the room. As a result, the occupant can be prompted to move to another room.
[D. Effects of the embodiment]
According to the present embodiment as described above, the prediction accuracy can be improved by predicting the energy consumption or supply energy of the control target device 2 in consideration of the control setting value of the control target device 2. That is, by using the past control setting values of the same control target device 2 installed in the same room, it is possible to accurately predict the energy consumption or supply energy for a plurality of different control target devices 2. .
Further, even when the PV 101 and the solar water heater 107 whose outputs change according to the weather conditions are installed, the power storage and heat storage schedule can be obtained so as to maintain the energy supply / demand balance of the entire building 1.
In addition, it is possible to set in advance the storage heat storage schedule of various control target devices 2 related to the supply of power and heat, including hysteresis. Thereby, a practical and efficient operation plan in which the control target device 2 does not repeatedly start and stop can be stably established.
In addition, when there is a difference between the predicted value of consumed energy or supplied energy on the previous day, the actual value of the day, or the storage heat storage schedule of the control target device 2 and the actual operation state, Re-plan heat storage schedule. For this reason, additional energy procurement is minimized, and efficient operation is possible throughout the building 1.
Further, in order to determine the consistency with the target value, it is possible to satisfy an external request. In particular, by making an inquiry to a consumer, the burden level can be prevented from becoming excessively large, and the burden level can be set with an agreement. Furthermore, the burden level can be set in detail based on the number of people in each room. For this reason, the target can be satisfied without deteriorating comfort and workability.
[E. Other Embodiments]
The present embodiment is not limited to the above aspect.
(1) The device to be controlled is not limited to those exemplified above. For example, as the energy supply device, a facility whose output varies depending on weather conditions, such as a wind power generation facility, can be used instead of or in addition to the solar power generation apparatus and the solar water heater. Note that this embodiment is suitable for a BEMS (Building Energy Management System) that is a system for managing control target devices installed in a predetermined building such as a building. However, the installation position of the control target device is not limited to a single building or a plurality of buildings, and may include the outdoors. That is, it can be widely applied as an EMS (Energy Management System) for controlling a control target device installed in a predetermined area.
(2) The storage heat storage optimization device, local control device, terminal, and the like can be realized by controlling a computer including a CPU or the like with a predetermined program. The program in this case realizes the processing of each unit as described above by physically utilizing computer hardware.
A method, a program, and a recording medium that records the program for executing the processing of each unit described above are also one aspect of the embodiment. Moreover, how to set the range processed by hardware and the range processed by software including a program is not limited to a specific mode. For example, any one of the above-described units can be configured as a circuit that realizes each process.
(3) Each processing unit, storage unit, and the like described above may be realized by a common computer or may be realized by a plurality of computers connected by a network. For example, the processing data storage unit and the optimization data storage unit may be configured in a server connected to the optimization processing unit via a network.
(4) Each data storage area stored in the processing data storage unit and the optimized data storage unit can be configured as a storage unit for each data. Typically, these storage units can be configured by various built-in or externally connected memories, hard disks, and the like. However, any storage medium that can be used now or in the future can be used as the storage unit. A register or the like used for calculation can also be regarded as a storage unit. The storage mode includes not only a mode in which storage for a long time is held but also a mode in which data is temporarily stored for processing and deleted or updated in a short time.
(5) The specific contents and values of the information used in the embodiment are free and are not limited to specific contents and numerical values. In the embodiment, in the determination of the magnitude of the threshold value, the determination of coincidence mismatch, etc., it is determined that the value is included as follows, or the value is not included as larger, smaller, exceeding, not exceeding Judgment is also free. Therefore, for example, depending on the value setting, even if “more than” is read as “greater than” and “less than” is changed to “less than”, it is substantially the same.
(6) Although several embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are also included in the invention described in the claims and the equivalents thereof.
DESCRIPTION OF SYMBOLS 1 ... Building 2 ... Control coping apparatus 3 ... Local control apparatus 4 ... Power storage heat storage optimization apparatus 10 ... Adjustment value setting part 10a ... Setting part 10b ... Adjustment part 11 ... Prediction part 11a ... Similarity calculation part 11b ... Similarity date extraction part 11c ... Predicted value setting unit 12 ... Device start / stop optimization unit 13 ... State quantity optimization unit 14 ... Target achievement determination unit 14a ... Comparison unit 14b ... Determination unit 14c ... Output instruction unit 14d ... Adjustment instruction unit 15 ... Control set value Output unit 16 ... start instruction unit 17 ... rescheduling necessity determination unit 18 ... inquiry unit 18a ... notification unit 18b ... reception unit 18c ... output instruction unit 18d ... adjustment instruction unit 20 ... process data acquisition unit 21 ... setting parameter input unit 22 ... Processing data storage unit 23 ... Optimization data storage unit 24 ... Transmission / reception unit 100 ... Storage battery 101 ... PV
103 ... CGS
104 ... Air-cooled HP
105 ... Water-cooled refrigerator 106 ... Absorption-type water heater / heater 107 ... Solar water heater 108 ... Thermal storage tank 110 ... Room 111 ... Air conditioner 112 ... Temperature / humidity meter 114 ... Illumination 116 ... Illuminance meter 121 ... Start priority determination part 122 ... Departure Stop condition setting unit 122a ... Starting boundary condition setting unit 122b ... Stop boundary condition setting unit 123 ... Starting device allocation unit 124 ... Production unit price totaling unit 125 ... Heat storage heat radiation allocation unit 126 ... Heat storage capacity determination unit
A prediction unit for setting a predicted value of energy consumption or supply energy of a plurality of control target devices;
Based on the predicted value set by the prediction unit, a start / stop optimization unit that creates a start / stop schedule for the control target device;
The start / stop optimization unit
A start / stop condition setting unit that sets a start / stop condition of the control target device according to the energy consumption of the cooling and heating based on the start priority of the control target device determined based on a predetermined evaluation index;
Based on the start / stop condition and the predicted value, an activation device allocation unit that allocates a control target device to be activated at each time;
Among the control target devices that start at each time, a manufacturing unit price totaling unit that calculates the cooling unit price of the control target device with the lowest start priority,
A heat storage and heat radiation assigning unit that sequentially assigns heat radiation or discharge from the time when the cold production unit price is high, and sequentially assigns heat storage or power storage from the time when the cold production unit price is low,
An electricity storage heat storage optimization device characterized by comprising:
Based on the characteristics and the activation priority of the control target device, and starts boundary condition setting unit for setting a start boundary condition is a condition for activating the respective control target devices,
A stop boundary condition setting unit that sets a stop boundary condition that is a condition for stopping each control target device based on the characteristics of the control target device and the start priority,
The power storage and storage optimization device according to claim 1, wherein
3. The power storage heat storage according to claim 2, wherein the stop boundary condition setting unit sets the stop boundary condition to be smaller than the start boundary condition within a range in which a device having a high start priority is not a lower limit output. Optimization device.
For a control target device, a setting unit for setting a control setting value for determining start, operation state, and stop in a predetermined period in the future;
A target achievement determination unit for determining whether the power storage heat storage schedule has achieved a predetermined target value;
A control set value output unit that outputs a control set value based on the power storage heat storage schedule when the target achievement determination unit determines that the target value has been achieved;
An adjustment unit that adjusts the control set value set by the setting unit when the target achievement determination unit determines that the target value is not achieved;
The power storage heat storage optimization device according to claim 1, wherein the power storage heat storage optimization device is provided.
The goal decision unit, when it is determined not to have achieved the goal, whether or not to accept the control set value according to the electric storage heat storage schedule, according to claim 4, wherein it is assumed that the features with inquiry unit inquiring the outside Energy storage heat storage optimization device.
Whether the difference between the predicted value by the prediction unit and the actual consumed energy or supplied energy value or the difference between the control setting value and the actual state quantity of the control target device exceeds a predetermined threshold value A rescheduling necessity determination unit for determining
An adjustment unit that adjusts the control setting value when the rescheduling necessity determination unit determines that a predetermined threshold value is exceeded;
The power storage heat storage optimization device according to any one of claims 1 to 5, wherein
The power storage heat storage optimization device according to any one of claims 1 to 6, wherein the evaluation index is minimization of one or both of energy consumption and cost.
The control target equipment includes equipment for producing cold water and hot water,
The storage energy storage optimization device according to claim 7, wherein the evaluation index is a cold water production unit price and a hot water production unit price or a cold water production energy and a hot water production energy.
Energy consuming equipment includes lighting,
The power storage heat storage optimization apparatus according to any one of claims 1 to 8, wherein the control setting value used for comparison by the prediction unit is illuminance.
Energy consuming equipment includes air conditioners,
The power storage heat optimization apparatus according to claim 1, wherein the control setting value used for comparison by the prediction unit is a PMV value.
A prediction process for setting a predicted value of energy consumption or supply energy of a plurality of control target devices;
Based on the predicted value set by the prediction process, start / stop optimization processing for creating a start / stop schedule for the control target device;
The start / stop optimization process is:
A start / stop condition setting process for setting a start / stop condition of the control target device according to the energy consumption of the cold and heat based on the start priority of the control target device determined based on a predetermined evaluation index,
Based on the start / stop condition and the predicted value, an activation device allocation process for allocating control target devices to be activated at each time;
Manufacturing unit cost totalization processing for calculating the cooling unit manufacturing cost of the control target device having the lowest start priority among the control target devices that start at each time,
A heat storage and heat radiation allocation process for sequentially assigning heat dissipation or discharge from the time when the cold production unit price is high, and sequentially assigning heat storage or power storage from the time when the cold production unit price is low,
The electricity storage heat storage optimization method characterized by performing this.
Based on the characteristics and the activation priority before Symbol control target device, and starts boundary condition setting processing for setting the start boundary condition is a condition for activating the respective control target devices,
A stop boundary condition setting process for setting a stop boundary condition that is a condition for stopping each control target device based on the characteristics of the control target device and the start priority,
The method for optimizing the storage heat storage according to claim 11, comprising:
A storage heat storage optimization program characterized by causing
The storage energy storage optimization program according to claim 13, comprising:
JP2012040650A 2012-02-27 2012-02-27 Storage energy storage optimization device, optimization method and optimization program Active JP5908302B2 (en)
JP2012040650A JP5908302B2 (en) 2012-02-27 2012-02-27 Storage energy storage optimization device, optimization method and optimization program
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SG2013050018A SG192568A1 (en) 2012-02-27 2013-01-10 Electric/thermal energy storage schedule optimizing device, optimizing method and optimizing program
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