JP5955206B2 - Demand control apparatus and method - Google Patents

Description

  The present invention relates to a demand control apparatus and a method thereof capable of demand-controlling a plurality of cooling devices installed for the same space.

  Conventionally, for facilities where the power consumption of air-conditioning chiller equipment accounts for the majority of the total power consumption, the chiller equipment operating / stopped state is controlled so that the total power consumption does not exceed the power receiving contract amount. There is known a demand control device that controls electric power, that is, demand control. On the other hand, in recent years, inverter control equipment has been introduced into the heat source equipment of refrigeration equipment, and not only control of operation / stop state of refrigeration equipment (ie, conventional on / off control) but also operation that can be changed continuously. Capability control is also possible. Therefore, flexible demand control can be realized.

  For example, Patent Document 1 discloses a demand control device that performs demand control of a plurality of air conditioners. Specifically, in Patent Document 1, a demand control device receives information on power consumption from an outdoor unit of an air conditioner via a signal line for air conditioning control, performs arithmetic processing based on the information on power, Takes the total value of power information and converts it to a power demand value. When it is judged that the preset upper limit demand value is exceeded, a control signal that suppresses the operating capacity of the air conditioner is generated and sent to the outdoor unit Is disclosed. According to the demand control device that changes the operation capacity of the cooling / heating apparatus as described above, it is possible to perform demand control in which the power consumption and the upper limit value substantially coincide with each other.

  Further, as one of demand control methods, a control map reference method in which a relationship between a capability suppression level and a set temperature of an indoor unit is created in advance is known. In this method, an empirically obtained control rule is applied to calculate a demand control amount by a feedback control method, or a control rule is created in advance so that the demand control amount becomes excessive.

JP 2007-212038 A

  However, there are many possible combinations of operating / stopped states and operating capacities of multiple air conditioners (heat source units) for one demand control amount, and the power consumption can be lower than the upper limit. There are various combinations. Nevertheless, the prior art described in Patent Document 1 can only perform demand control in which the power consumption and the upper limit value substantially coincide. That is, demand control in which power consumption of a plurality of air conditioners is minimized cannot be performed.

  Further, in demand control using the above-described control map reference method or the like, since advanced calculation processing is required to obtain a control rule, control for minimizing the power consumption of a plurality of refrigeration devices in an apparatus with low calculation capability Can not be done with.

  Therefore, the present invention has been made in view of the above-described problems, and an object of the present invention is to provide a technique capable of reducing the overall power consumption of a plurality of refrigeration devices as much as possible by a simple calculation. And

  The demand control device according to the present invention is a demand control device capable of demand-controlling a plurality of refrigeration devices installed in the same space, and represents the relationship between the operation capacity and the power consumption for each of the refrigeration devices. Data storage means for storing model data relating to the model and power measurement data relating to power consumption of the plurality of cooling devices, and a demand for calculating a demand control amount to be reduced in the future based on the current and past power measurement data Based on the control amount calculation means, the current operating capacity of the desired cooling / heating device in operation and the model data, the power consumption change per unit change of the operating capacity of the cooling / heating device is calculated, and the calculated power consumption A capability suppression amount calculating means for calculating a required capability suppression amount based on the change and the demand control amount; The demand control device includes a corrected overall cooling load obtained by subtracting the required capacity suppression amount from a sum of cooling loads corresponding to operating capacities that the plurality of cooling devices should output in the future, and the plurality of cooling devices. Power consumption of the plurality of cooling devices and their state values under the constraint that the total value of the values obtained by multiplying each of the driving capacity and the state value indicating the operation / stop state is equal to each other Optimal operation calculation means for calculating the operating capacity and the state value of the plurality of cooling devices that minimize the total value obtained by multiplying each of the values, and the plurality of cooling devices calculated by the optimal operation calculation means Control signal sending means for sending control signals related to the operating capacity and the state value to each of the plurality of cooling devices.

  ADVANTAGE OF THE INVENTION According to this invention, even if it is an apparatus with low calculation capability, the demand control by which the total power consumption of the several cooling-heat apparatus was reduced as much as possible can be implemented.

1 is a block diagram showing a configuration of a demand control system according to Embodiment 1. FIG. 1 is a block diagram illustrating a configuration of a demand control device according to a first embodiment. It is a figure which shows an example of a performance model. It is a figure which shows an example of the data format of model data. It is a figure which shows an example of the data format of driving | operation information data. It is a figure which shows an example of the data format of cooling / heating load data. 5 is a flowchart of the operation of the demand control device according to the first embodiment. FIG. 4 is a diagram illustrating an operation of the demand control device according to the first embodiment. It is a block diagram which shows the structure of the demand control system which concerns on Embodiment 2. FIG. FIG. 10 is a block diagram illustrating a configuration of a demand control system according to a third embodiment. 10 is a flowchart of the operation of the demand control apparatus according to the third embodiment.

<Embodiment 1>
FIG. 1 is a block diagram showing a configuration of a demand control system including a demand control device 10 according to Embodiment 1 of the present invention. The demand control device 10 includes a plurality of cooling / heating devices (here, four cooling / heating devices 2-1 to 2, which are distinguished by No 1 to No 4) installed for the same indoor space (hereinafter referred to as “target space 1”). 2-4) can be demand-controlled.

  The cooling / heating devices 2-1 to 2-4 are respectively indoor units 21-1 to 21-4 disposed in the target space 1 and heat source devices 22-1 to 22-4 disposed outside the target space 1. And is configured. Indoor units 21-1 to 21-4 and heat source units 22-1 to 22-4 are connected to each other by refrigerant pipes 23-1 to 23-4 so that heat can be moved.

  In addition, in the following description, when not distinguishing the refrigeration equipment 2-1 to 2-4, it describes as the refrigeration equipment 2-k (k = 1, 2, 3, 4), and the indoor units 21-1 to 21-4. Similarly, the heat source units 22-1 to 22-4 and the refrigerant pipes 23-1 to 23-4 are referred to as an indoor unit 21-k, a heat source unit 22-k, and a refrigerant pipe 23-k. In addition, here, the number N of the cooling / heating devices 2-k is described as four (k = 1, 2,..., N), but the number N may be two or more. As a special case of the form, the number may be one.

  Each cooling device 2-k changes the pressure of the refrigerant flowing through the refrigerant pipe 23-k under the control of the demand control device 10, and adjusts the temperature of the target space 1 by absorbing and radiating heat with the refrigerant. . Note that the indoor unit 21-k and the heat source unit 22-k of each cooling / heating device 2-k have measuring elements (for example, measuring the operation information related to the operation of the cooling / heating device 2-k and the cooling load information related to the cooling load). Sensors and the like (not shown here) are installed. Here, it is assumed that the operation information related to the operation includes an operation state value that is a state value indicating the operation / stop state and an operation capability (cooling capability) in the operation state.

  The operation information (operation state value and operation capability) measured by the measurement element and the cold load information (cool load) are periodically transmitted to the demand control device 10 via the communication line 3.

  The power meter 4 supplies the power supplied from the commercial power source to the plurality of cooling devices 2-k (the plurality of heat source devices 22-k) via the power supply line 5. In addition, the power meter 4 measures the total load power (total power consumption) of the plurality of cooling devices 2-k that are subject to demand control, and outputs a power pulse signal corresponding to the total to the communication line 6. To the demand control apparatus 10 periodically.

  The demand control device 10 communicates setting information related to the cooling / heating device 2-k set based on an input from the user, operation information and cooling / load information of the cooling / heating device 2-k transmitted via the communication line 3, and communication A predetermined calculation is performed based on the power pulse signal transmitted via the line 6. Then, the demand control device 10 sends a control signal for demand-controlling the plurality of cooling devices 2-k to the plurality of cooling devices 2-k via the communication line 6 based on the result obtained by the calculation. Send it out.

  The demand control device 10 may be provided integrally with a communication device (not shown here) such as a remote controller that incorporates a microcomputer with poor calculation capability, capable of communication via the communication lines 3 and 6, It may be provided individually. The communication via the communication lines 3 and 6 may be wired communication or wireless communication.

  FIG. 2 is a block diagram illustrating a configuration of the demand control apparatus 10. As shown in FIG. 2, the demand control apparatus 10 according to the first embodiment includes a data storage unit 101, a performance model data storage unit 102, a data setting unit 103, a demand control amount calculation unit 104, and a capability. The suppression amount calculation unit 105, the optimum operation calculation unit 106, and the control signal transmission unit 107 are configured.

  The data storage unit 101 and the performance model data storage unit 102 correspond to data storage means. The demand control amount calculation unit 104, the capability suppression amount calculation unit 105, the optimum operation calculation unit 106, and the control signal sending unit 107 are respectively a demand control amount calculation unit, a capability suppression amount calculation unit, an optimum operation calculation unit, And it corresponds to a control signal sending means. In addition, the data storage unit 101, the performance model data storage unit 102, and the data setting unit 103 can be configured by a storage device such as a flash memory, for example. On the other hand, part of the functions of the demand control amount calculation unit 104, the capability suppression amount calculation unit 105, the optimum operation calculation unit 106, and the control signal transmission unit 107 are realized by hardware such as a circuit device that realizes these functions. It can also be realized as a functional block of an arithmetic device by an arithmetic device (computer) such as a microcomputer or CPU executing software on the storage device.

  Next, each component of the demand control apparatus 10 will be described in detail.

The data storage unit 101 includes setting data including parameters (control cycle Δt (minutes), demand time limit end time t ^d _end (minutes), and upper limit demand value Vmax (kW), which will be described later) input from the system user, communication Operation information data including operation information (operation state value u _k and operation capability Q _k ) input via line 3, and cooling load including refrigeration load information (cool load L _k ) input via communication line 3 Store the data. Note that the subscript k means a value related to the cooling device 2-k. For example, the operating state value u _k , the operating capacity Q _k , and the cooling load L _k are the operating state value of the cooling device 2-k, It means operating capacity and cold load. Note that the subscript k appearing in the following description also means a value related to the cooling / heating device 2-k.

  Here, the demand control apparatus 10 counts the electric power pulse signal input via the communication line 6, and thereby the plurality of cooling devices 2-k (here, the cooling devices 2-1 to 2-) that are demand control targets. 4) The total power consumption (hereinafter referred to as “total power consumption (kWh)”) is periodically calculated. And the demand control apparatus 10 calculates the integrated value (power consumption integrated value D) of the total power consumption calculated regularly, and the demand value V corresponding to the said power consumption integrated value D with the measurement time is the data storage part 101. To store.

  Thereby, in addition to data, such as the above-mentioned setting data, the data storage unit 101 stores power measurement data related to the power consumption of the plurality of cooling / heating devices 2-k, that is, power measurement data including the demand value V.

  In addition, the data storage unit 101 is a control output to the plurality of refrigeration equipment 2-k, which is obtained by the demand control amount calculation unit 104, the capacity suppression amount calculation unit 105, and the optimum operation calculation unit 106. Data is also stored. Details of various data will be described later.

The performance model data storage unit 102 stores model data related to a performance model that represents the relationship between the driving capability Q _k and the power consumption W _k for each of the cooling / heating devices 2-k. Details will be described later, related that between the power consumption W _k and the operation capacity Q _k, may represent a power consumption W _k at the operating capacity Q _k polynomial (function). Therefore, the performance model data storage unit 102 according to the first embodiment, the coefficient a _k polynomial defining the performance _model, b _k, model data containing the c _k are, for each of a plurality of cold appliances 2-k It is remembered.

  The data setting unit 103 has a memory that can store various types of information, and stores various data necessary for the demand control amount calculation unit 104, the capability suppression amount calculation unit 105, and the optimum operation calculation unit 106 to calculate. The memory is appropriately set, or the data set in the memory is appropriately initialized.

  The demand control amount calculation unit 104 is based on the current and past power measurement data (here, the current and past demand value V) stored in the data storage unit 101, and the demand control corresponding to the power consumption to be reduced in the future. The amount ΔV is calculated.

Although the details will be described later, the demand control amount calculation unit 104 according to the first embodiment is based on the current and past demand values V stored in the data storage unit 101 in the future (demand time limit end time td ^). The demand value Ve of _end ) is predicted. Then, the demand control amount calculation unit 104 compares the predicted demand value Ve (hereinafter referred to as “predicted demand value Ve”) with the upper limit demand value Vmax stored in the data storage unit 101. When the predicted demand value Ve exceeds the upper limit demand value Vmax, the demand control amount calculation unit 104 determines the demand control amount ΔV to be reduced in the future based on the predicted demand value Ve and the upper limit demand value Vmax. The calculated demand control amount ΔV is written in the data storage unit 101.

Based on the current operating capacity Q _i of one desired cooling / heating device 2-i (i = 1 to 4) and the model data, the capability suppression amount calculation unit 105 2-i Change in power consumption W per unit change in driving ability Q (hereinafter referred to as “power consumption change μ”) is calculated. Then, the capability suppression amount calculation unit 105 calculates the required capability suppression amount based on the calculated power consumption change μ and the demand control amount ΔV to reduce the driving capability suppression amount necessary for realizing the demand control amount ΔV. Calculated as a quantity ΔQ.

Although details will be described later, in the first embodiment, the capacity suppression amount calculation unit 105 is configured to operate the current operating capacity Q _i regarding one desired cooling / heating device 2-i (any one of i = 1 to 4). And the coefficients a _i and b _i of the polynomial are obtained from the data storage unit 101 and the performance model data storage unit 102, respectively. Then, capacity restriction amount computation unit 105, the current driving capacity and the acquired Q _i and the coefficient a _i, based on the b _i, when changing from the current driving behavior Q _i by weight units (e.g. 1 kW) the change of power consumption W _i, is calculated as the power consumption change μ. Then, the capacity suppression amount calculation unit 105 calculates the necessary capacity suppression amount ΔQ based on the calculated power consumption change μ and the demand control amount ΔV calculated by the demand control amount calculation unit 104, and the calculated necessary amount The capacity suppression amount ΔQ is written in the data storage unit 101.

The optimum operation calculating unit 106 corrects the corrected total cooling load (L) obtained by subtracting the required capacity suppression amount ΔQ from the sum L (here, L = L _{1 to} L ₄ ) of the cooling loads L _k of the plurality of cooling devices 2-k. and -ΔQ), generates a constraint that the sum of values obtained by a plurality of cold appliances 2-k runnability Q _k and their the operating state value u _k multiplied respectively are equal. Then, the optimum operation calculation unit 106 minimizes the total value of the values obtained by multiplying the power consumption W _k of the plurality of cooling devices 2- _k and their operation state values u _k under the constraint conditions. The operation capability Q _k and the operation state value uk of the plurality of cooling devices 2- _k to be calculated are calculated.

Although details will be described later, in the first embodiment, the optimum operation calculation unit 106 stores the operation state value u _k , the cooling load L _k , and the necessary capacity suppression amount ΔQ regarding the plurality of cooling devices 2-k as the data storage unit 101. acquires from, acquires coefficients for a plurality of cold appliances _{2-k a k, b k} , a _{c k} from the performance model data storage unit 102. The optimal operation arithmetic unit 106, cooling load L _k modified global obtained by subtracting the required capacity restriction amount Delta] Q a sum L cooling load of the (L-Delta] Q), the operating capacity Q _k of the plurality of cold appliances 2-k and the sum of values obtained by multiplying the their operating state values u _k, each of which generates a constraint that equal. Multiple Then, optimal operation arithmetic unit 106, in the constraint conditions, the sum of values obtained by a plurality of cold appliances 2 power consumption W _k and those of the operating state value u _k multiplied respectively in a minimum of calculating the operating capacity Q _k and the operating state value u _k of the cold appliance 2, writes the operating capacity Q _k and the operating state values u _k and the calculated data storage unit 101.

Control signal transmitting unit 107, stored the calculation result to the data storage unit 101, i.e., reads out the operating capacity Q _k and the operating state value u _k of the plurality of cold device 2 calculated by the optimum driving operation unit 106. Then, the control signal sending unit 107 sends a control signal instructing to control with the read driving capacity Q _k and the driving state value u _k to the plurality of cooling devices 2-k (here, a plurality of cooling devices 2-k). To the heat source unit 22-k).

  Next, various data stored in the data storage unit 101 and the performance model data storage unit 102 will be described.

[Setting data (parameter)]
The setting data stored in the data storage unit 101 includes a control cycle Δt (minutes), a demand time limit end time t ^d _end (minutes), and an upper limit demand value Vmax (kW) indicating the upper limit of the predicted demand value Ve. include.

[Model data]
Figure 3 is a diagram showing an example of a performance model indicating the relationship between the power consumption W _k and the operation capacity Q _k. Figure 4 is stored in the performance model data storage unit 102 according to the first embodiment, is a diagram illustrating an example of a data format of the model data containing the coefficients a _k, b _k, and c _k.

The power consumption W _k of the refrigeration equipment 2-k mainly includes compressor power consumption, electronic board input power, indoor / outdoor fan input power, and the like. The relationship between the driving capability and the power consumption in the refrigeration equipment 2 is as shown in FIG. 3 and can be sufficiently approximated by a quadratic equation such as the following equation (1).

In this equation (1), W _k (kW) and Q _k (kW) are the power consumption and operating capacity of the cooling device 2-k, and the coefficients a _k , b _k , and _ck are the cooling device 2-k. It is an intrinsic coefficient. As shown in FIG. 4, in the model data according to the first embodiment, not only the coefficients a _k , b _k , and _ck but also the maximum value (maximum capacity value Qmax _k ) that the driving capacity Q _k can take and The minimum value (minimum capacity value Qmin _k ) is also included for each cooling device 2-k.

[Operation information data]
FIG. 5 is a diagram illustrating an example of a data format of the driving information data stored in the data storage unit 101 according to the first embodiment. The operation information data of each cooling / heating device 2-k (each heat source device 22-k) has a value of “1” when the cooling / heating device 2-k is in operation, and “0” when it is stopped. The driving state value u _k to be taken and the driving capability Q _k which is the current driving capability value are included. The driving capability Q _k takes a value larger than “0” when the cooling / heating device 2-k is in operation, and takes a value “0” when the cooling device 2-k is stopped. In the example shown in FIG. 5, the operating state values u _{1 to} u ₃ of the operating refrigeration devices 2-1 to 2-3 take a value of “1”, and their operating capacities Q _{1 to} Q ₃ are “0”. Although the value is larger, the operation state value u ₄ of the stopped cooling / heating device 2-4 has a value of “0”, and the operation capability Q ₄ has a value of “0”.

[Cryogenic load data]
FIG. 6 is a diagram illustrating an example of a data format of the thermal load data stored in the data storage unit 101 according to the first embodiment. The cooling load L _k (kW) stored in the data storage unit 101 takes a value of “0” or more for the operating cooling device 2-k, and takes a value of “−1” when stopped. The example shown in FIG. 6 corresponds to the example shown in FIG. 5, and the cooling loads L _{1 to} L ₃ of the operating cooling devices 2-1 to 2-3 take values of “0” or more, but stop. The cooling load L ₄ of the inside cooling / heating device 2-4 takes a value of “−1”.

Here, the cooling load L _k is a value corresponding to the operating capability Q _k that the cooling device 2-k should output at the next control timing t + Δt (Δt is the control timing).

In the first embodiment, the cooling load L _k is assumed to be the operating capacity Q _k that the cooling device 2-k should output at the next control timing t + Δt (Δt is the above-described control cycle), and this cooling load L _k. Is calculated based on the measurement information of the current control timing t by the above-described measurement elements (sensors, etc.) provided in each of the cooling / heating devices 2-k. Specifically, the measuring element determines the number of rotations (Hz) of the heat source unit 22-k according to the difference (ΔT) between the set temperature of the individual refrigeration equipment 2-k and the room temperature, and sets this number of rotations. Accordingly, the operation capability Q _k to be output at the next control timing t + Δt is obtained, and the operation capability Q _k is transmitted as the cooling load L _k to the demand control device 10 via the communication line 3. The cooling load L _k is not limited to that described above, and may be calculated by the demand control device 10 based on, for example, the operation information data shown in FIG.

[Power measurement data]
As described above, the demand control device 10 counts the power pulse signal input via the communication line 6 to obtain the power consumption of the plurality of refrigeration devices 2-k that are demand control targets, and sums them. The total power consumption is calculated periodically by taking And the demand control apparatus 10 which concerns on this Embodiment 1 calculates the integrated value of the said total power consumption as the power consumption integrated value D, applies the said power consumption integrated value D to following Formula (2), and is predetermined. A demand value V corresponding to the power consumption integrated value D per hour (here 1 hour) is obtained. The data storage unit 101 stores power measurement data regarding the power consumption of the plurality of cooling devices 2-k as described above, that is, power measurement data including the demand value V.

<Operation>
FIG. 7 is a flowchart showing an operation (demand control process) of the demand control apparatus 10 according to the first embodiment. Hereinafter, the operation of the demand control apparatus 10 will be described with reference to the flowchart of FIG. This operation is performed every control cycle Δt (minutes) (for example, 1 minute). In the following description, it is assumed that the current control timing is t, and the control timing is expressed in order of t−Δt, t, t + Δt, t + 2Δt,.

<Step S1 (data reading / initialization process)>
In step S <b> 1, the data setting unit 103 reads data and initializes data regarding the plurality of cooling devices 2-k.

Specifically, the data setting unit 103 receives from the data storage unit 101 setting data (control cycle Δt, demand time limit end time t ^d _end and upper limit demand value Vmax) and operation information data (operation at the current control timing t). State value u _k and operating capacity Q _k ) and cooling load data (cooling load L _k calculated based on measurement data at the current control timing t) are read. Further, the data setting unit 103 reads power measurement data (the demand values V of the current control timing t and the past control timing t−Δt) from the data storage unit 101 based on the setting data. Further, the data setting unit 103 reads model data (coefficients a _k , b _k , c _k , maximum capability value Qmax _k and minimum capability value Qmin _k ) from the performance model data storage unit 102.

  Then, the data setting unit 103 sets (initializes) the read data as initial data in its own memory. Specifically, the data setting unit 103 sets the number of the cooling / heating devices 2-k to be controlled indicated by the operation information data in a variable on its own memory, and the operation information data and cooling / heat for the number of the devices. Load data and model data are set for each cooling device 2-k.

In addition, the data setting unit 103 initializes variables and calculation results written in its own memory at the previous control timing t−Δt. Specifically, the data setting unit 103 writes the predicted demand value Ve, the demand control amount ΔV, the driving ability Q _i , the coefficients a _i , b _i , written in its own memory at the previous control timing t−Δt, Initialization to set power consumption change μ, required capacity suppression amount ΔQ, sum L of cooling load L _k , modified total cooling load (L−ΔQ), operation capability Q _k and operation state value u _k to “0” Run.

  In addition, although the structure which performs initialization with respect to various data etc. collectively in step S1 here is demonstrated, it is not restricted to this, For example, the said immediately before each step which performs a calculation Initialization may be appropriately performed on data related to the calculation. Further, the data setting unit 103 may perform the same initialization as described above not only on its own memory but also on the memory of the data storage unit 101.

<Step S2 (Demand Control Amount Calculation Processing)>
In step S2, the demand control amount calculation unit 104 calculates a demand control amount ΔV to be controlled at the next control timing elapsed time t ^d + Δt. Hereinafter, an example of calculation of the demand control amount ΔV by the demand control amount calculation unit 104 will be described with reference to FIG. First, the demand control amount calculation unit 104 performs an offset such that the demand time limit start time becomes 0 (minutes) and the demand value of the control timing corresponding to the demand time limit start time becomes V (0) (kW).

Specifically, the demand control amount calculation unit 104 acquires the elapsed time t ^d (minutes) from the demand time limit start time to the control timing t by offsetting the current control timing t with the demand time limit start time. Then, the demand value V (t ^d ) after the offset is obtained by offsetting the demand value V at the current control timing t by the demand value V (0). Similarly, the demand control amount calculation unit 104 acquires the elapsed time t ^d −Δt (minutes) from the demand time limit start time to the control timing t−Δt by offsetting the past control timing t−Δt. By offsetting the demand value V at the past control timing t−Δt, the offset demand value V (t ^d −Δt) is obtained.

Then, the demand control amount calculation unit 104 uses the elapsed time t ^d −Δt and the demand value V (t ^d −Δt) as coordinates, and the point using the elapsed time t ^d and demand value V (t ^d ) as coordinates. Linear prediction is performed from the change in demand value for the two closest points. Here, the demand control amount calculation unit 104 predicts the demand value Ve (kW) of the demand time limit end time t ^d _end (min) by applying the following equation (3) that allows the linear prediction. As described above, in the first embodiment, the demand control amount calculation unit 104 predicts the future demand value Ve substantially based on the current and past power measurement data.

The excess amount of the predicted demand value Ve with respect to the upper limit demand value Vmax at the demand time limit end time t ^d _end is (Ve−Vmax). That is, the excess amount that should have been suppressed during the time period from the demand time limit start time to the demand time limit end time t ^d _end is (Ve−Vmax). Demand control amount calculation unit 104, based on the excess amount (Ve-Vmax), the remaining demand time period within the elapsed time ^{t d} of the current control timing to the demand time end time _{^t d end} ^(t _{d end} -t for suppressing the excess amount (Ve-Vmax) in ^d), the calculated course of the next control timing time ^{t d} + Delta] t of the demand control amount [Delta] V (kW). Here, the demand control amount calculation unit 104 calculates the demand control amount ΔV by substituting the excess amount (Ve−Vmax) or the like into the following equation (4).

The specific processing in step S2 is as follows. The demand control amount calculation unit 104 sets the setting data (control cycle Δt) set in the data setting unit 103 in step S1 and the power measurement data (the demand value V of the current control timing t and the past control timing t−Δt). ) To calculate the current elapsed time t ^d −Δt, t ^d after the offset and demand values V (t ^d −Δt), V (t ^d ) after the offset, and the data storage unit 101 and the data Write to the variable of the setting unit 103.

Then, the demand control amount calculation unit 104 sets the set data (control cycle Δt and demand time limit end time t ^d _end ) set in the data setting unit 103 in step S1 and the current course after the offset calculated in step S2. The time t ^d and the demand values V (t ^d −Δt) and V (t ^d ) are substituted into variables on the memory prepared in the data setting unit 103 so as to execute the calculation based on the above equation (3). Then, the predicted demand value Ve is calculated. Then, the demand control amount calculation unit 104 writes the calculated predicted demand value Ve into the variables of the data storage unit 101 and the data setting unit 103.

Next, the demand control amount calculation unit 104 sets the set data (demand time limit end time t ^d _end and upper limit demand value Vmax) set in the data setting unit 103 in step S1 and the current value after the offset calculated in step S2. The demand control amount ΔV is calculated by substituting the elapsed time t ^d and the predicted demand value Ve into a variable on the memory prepared in the data setting unit 103 so as to execute the calculation based on the above equation (4). . Then, the demand control amount calculation unit 104 writes the calculated demand control amount ΔV in the variables of the data storage unit 101 and the data setting unit 103.

<Step S3 (Evaluation of demand control amount)>
In step S3, the capacity suppression amount calculation unit 105 determines whether or not the following expression (5) holds for the demand control amount ΔV set in the variable on the memory of the data setting unit 103 in step S2, that is, the demand control amount ΔV. Whether or not is larger than 0 is determined. When the demand control amount ΔV determines that the demand control amount ΔV is greater than 0, the capability suppression amount calculation unit 105 proceeds to step S4, and when the demand control amount ΔV is 0 or less, the demand control amount set in the data setting unit 103 The amount ΔV is set to 0 and the process proceeds to step S5.

<Step S4 (Power Consumption Change Calculation Process)>
In step S4, the capacity suppression amount calculation unit 105 performs a change in the power consumption W per unit change in the driving capacity Q when performing optimal operation control that can minimize the power consumption of the cooling / heating device 2-k, that is, Obtain the power consumption change μ. For example, the capacity suppression amount calculation unit 105 is configured such that the operating capacity Q _k is the maximum capacity value Qmax _k out of the currently operating refrigeration equipment 2-k (k = 1, 2, 3 in the examples of FIGS. 5 and 6). One cooling / heating device 2-i (one cooling / heating device 2-i serving as a partial load) which is smaller and larger than the minimum capacity value Qmin _k is selected.

Then, capacity restriction amount computation unit 105, the driving information of the cold appliance 2-i selected (current driving capability Q _i), on the basis of model data (coefficients a _i, b _i) and the current driving behavior The slope of the tangent line of the performance model curve at Q _i is calculated as the power consumption change μ. Here, the capacity suppression amount calculation unit 105 calculates the power consumption change μ by substituting the current operating capacity Q _i of the refrigeration equipment 2-i and the coefficients a _i and b _i into the following equation (6). . Note that, when the optimum operation control is performed so as to minimize the power consumption of the plurality of cooling devices, the power consumption changes μ of the cooling devices that are partial loads all have the same value.

The specific process in step S4 is as follows. The capability suppression amount calculation unit 105 compares the driving information data (current driving capability Q _k ) set in the data setting unit 103 in step S1 with the model data (maximum capability value Qmax _k and minimum capability value Qmin _k ). Then, one cooling / heating device 2-i having a partial load is selected from the plurality of cooling / heating devices 2-k. And the capacity | capacitance suppression amount calculating part 105 is selected from the driving | operation information data (present driving capacity _Qk ) and model data (coefficient _ak , _bk ) which were set to the data setting part 103 by step S1. -Obtain the current driving capability Q _i and coefficients a _i and b _i of _i . Then, the capacity suppression amount calculation unit 105 is a memory prepared in the data setting unit 103 so as to perform the calculation on the acquired current driving capability Q _i and the coefficients a _i and b _i based on the above equation (6). Substituting into the above variable, the power consumption change μ is calculated. Then, the capacity suppression amount calculation unit 105 writes the calculated power consumption change μ in the variables of the data storage unit 101 and the data setting unit 103.

  Here, the capability suppression amount calculation unit 105 analytically calculates the power consumption change μ using the above equation (6). However, the present invention is not limited to this, and the capacity suppression amount calculation unit 105 is configured to calculate (change in power consumption at a predetermined time) / (change in driving capacity at a predetermined time) based on actual driving performance Q and actual power consumption W data. Change) may be calculated as the power consumption change μ.

<Step S5 (Necessary ability suppression amount calculation process)>
In step S5, the capacity suppression amount calculation unit 105 is necessary to realize the demand control amount ΔV obtained in step S2 when performing the optimum operation control capable of minimizing the power consumption of the cooling / heating device 2-k. The amount of suppression of the necessary driving ability is calculated as the necessary capacity suppression amount ΔQ. Here, the capability suppression amount calculation unit 105 applies the demand control amount ΔV calculated in step S2 and the power consumption change μ calculated in step S4 to the following equation (7) to calculate the necessary capability suppression amount ΔQ. Is calculated.

  The specific process in step S5 is as follows. Based on the above (7), the capacity suppression amount calculation unit 105 calculates the demand control amount ΔV set in the data setting unit 103 in step S2 and the power consumption change μ set in the data setting unit 103 in step S4. The necessary capacity suppression amount ΔQ is calculated by substituting it into a memory variable prepared in the data setting unit 103 so as to execute the calculation. Then, the capability suppression amount calculation unit 105 writes the calculated required capability suppression amount ΔQ in the variables of the data storage unit 101 and the data setting unit 103.

<Step S6 (Driving ability / driving state value calculation process)>
In step S6, the optimum operation calculation unit 106 calculates the corrected overall cooling load (L-ΔQ) reflecting the required capacity suppression amount ΔQ and generates a constraint condition, and then the plurality of cooling devices 2-k. calculating the power consumption W _k and operating capacity Q _k and the operating state value u _k of the plurality of cold appliances 2-k that minimizes the sum of values obtained by multiplying their operating state values u _k and, respectively.

Specifically, first, the optimum operation calculation unit 106 adds the sum L (here, L = L ₁ + L ₂ + L ₃ + L) for the cooling load L _k of the plurality of cooling devices 2-k measured at the current control timing t. ₄ ) is calculated, and the corrected total cooling load (L-ΔQ) is calculated by subtracting the necessary capacity suppression amount ΔQ from the sum. The optimal operation arithmetic unit 106 and the sum of values obtained by a plurality of cold appliances 2-k runnability Q _k and their the operating state value u _k multiplied respectively are equal, the following equation ( The constraint condition shown in 8) is acquired. In this equation (8), the driving capability Q _k and the driving state value u _k are unknown variables, and the right side of the second equation of the constraint condition, that is, the corrected total cooling load (L−ΔQ) is a constant.

Then, under this constraint condition, the optimum operation calculation unit 106 multiplies the power consumption W _k of the plurality of refrigeration devices 2- _k and their operation state values u _k , that is, the next value. The operation capability Q _k and the operation state value u _k of the plurality of cooling / heating devices 2-k that minimize the entire value of the equation (9) are calculated. In Equation (9), the driving ability Q _k and the driving state value u _k are unknown variables, and the coefficients a _k , b _k , and _kk are constants.

The optimal driving calculation unit 106 uses, for example, a Lagrange undetermined multiplier method, and the unknown variable (driving capability Q _k and The operating state value u _k ) is calculated. A specific example of using this Lagrange undetermined multiplier method is disclosed in a patent document (Japanese Patent Laid-Open No. 2011-89683).

In the first embodiment, the optimum operation calculation unit 106 minimizes the above equation (9) for each of combinations of values “0” and “1” that can be taken by the operation state value u _k for the plurality of cooling devices 2-k. the operating capacity Q _k to, is calculated by using the Lagrange multiplier method. Then, the optimum driving calculation unit 106 compares the values obtained by substituting the driving ability Q _k calculated for each of the above combinations into the above equation (9), and the driving state value u _{k of the} combination that minimizes the value. and the operating state value u _k calculated in step S6.

For example, for the above four cooling devices 2-1 to 2-4, the combination of the operating state values (u ₁ , u ₂ , u ₃ , u ₄ ) is (0, 0, 0, 0), (1, 0, 0, 0), (0, 1, 0, 0), (0, 0, 1, 0), (0, 0, 0, 1), ..., (1, 1, 1, 1 ) 15 types exist. In this case, the optimum operation calculation unit 106 sets one of the combinations, for example, (u ₁ , u ₂ , u ₃ , u ₄ ) = ( ₁ , ₁ , ₁ , ₁ ) to the above formula (8) and The function F is generated by substituting into the above formula (9) and subtracting the formula obtained by multiplying the formula (8) after substitution by the Lagrange multiplier λ from the formula (9) after substitution. Then, the optimum operation calculation unit 106 assumes that the partial differential values of the driving abilities Q _{1 to} Q ₄ and the Lagrange multiplier λ in the function F, that is, k + 1 (here, k = 4) variables are equal to 0. By generating k + 1 equations and solving the equations, the values of the driving abilities Q _{1 to} Q ₄ and the Lagrange multiplier λ are obtained. The optimum operation calculation unit 106 performs the calculation of the driving ability Q _k for the remaining 14 combinations.

Then, the optimum operation calculation unit 106 substitutes the driving ability Q _k calculated for each of the 15 combinations into the above equation (9), and sets the above equation (9) to the minimum among the 15 combinations. of the _{(u 1, u 2, u} 3, u 4), the operating state value _{u k} calculated in step S6. At the same time, the operating capacity Q _k to the above equation (9) to a minimum, and the driving behavior Q _k calculated in step S6.

The specific process in step S6 is as follows. The optimum operation calculation unit 106 calculates the total cooling load L by taking the sum of the cooling loads L _k of the plurality of operating cooling devices 2-k set in the data setting unit 103 in step S1. For example, as shown in FIG. 6, when the operation information data is L ₁ , L ₂ , L ₃ , −1, the optimum operation calculation unit 106 sets the overall cooling load L as L ₁ + L ₂ + L _3. calculate. The optimum operation calculation unit 106 writes the calculated overall cooling load L in the variables of the data storage unit 101 and the data setting unit 103.

Then, the optimum operation calculation unit 106, the overall cooling load L, the necessary capacity suppression amount ΔQ set in the data setting unit 103 in step S5, and the model data (coefficient a) set in the data setting unit 103 in step S1. _k , b _k , c _k , maximum capacity value Qmax _k and minimum capacity value Qmin _k ) are substituted into variables on the memory prepared in the data setting unit 103 so as to execute the calculation based on a predetermined formula. The driving ability Q _k and the driving state value u _k are calculated (here, k = 1 to 4). The optimum driving calculation unit 106 writes the calculated driving ability Q _k and the driving state value u _k into the variables of the data storage unit 101 and the data setting unit 103 (here, k = 1 to 4).

<Step S7 (control signal transmission process)>
Control signal transmitting unit 107 reads the operating capacity Q _k and the operating state values u _k is stored in the data storage unit 101 in step S6, a plurality of cold appliances by operating capacity Q _k and the operating state values u _k read the A control signal for controlling 2-k at the next control timing t + Δt is sent to the plurality of cooling devices 2-k (here, k = 1 to 4).

<Summary>
According to the demand control device 10 and the method as described above, the demand control amount to be reduced in the future is calculated for the plurality of cooling / heating devices 2-k installed in the target space 1. Of the combinations of operating capacity Q _k and the operating state value u _k of the plurality practicable a decrease in the demand control amount cold appliance 2-k (k = 1~N) , a plurality of cold appliances 2-k the sum of values obtained power consumption W _k with operating state value u _k and the multiplied respectively calculating the driving capacity Q _k and operating condition values u _k minimized. Therefore, it is possible to perform demand control in which the overall power consumption of the plurality of cooling / heating devices 2-k is reduced as much as possible. In addition, the demand control can be performed with a simple calculation (here, one calculation) without the need for advanced calculation processing such as the control map reference method and the feedback control method. The demand control as described above can be performed.

  In the above description, the demand control apparatus 10 performs the demand control method shown in the flowchart of FIG. However, the present invention is not limited to this. For example, it may be realized by a program that substantially executes the demand control method. For example, this program may be installed in a microcomputer or a computer of the demand control apparatus 10 or may be installed in a remote controller integrated with the demand control apparatus 10. In addition, when a program is mounted in the microcomputer and computer of the demand control apparatus 10, the structure by which the program is stored in the hard disk etc. which are recording media can be considered, for example. The computer-readable medium storing this program may be a CD-ROM or MO in addition to the hard disk. Furthermore, the program itself may be acquired via an electric communication line without using a recording medium.

<Embodiment 2>
FIG. 9 is a block diagram showing a configuration of a demand control system including the demand control apparatus 10 according to Embodiment 2 of the present invention. Note that in the demand control apparatus 10 according to the second embodiment, the same or similar components as those described in the first embodiment are denoted by the same reference numerals, and the following description will focus on differences. .

  As shown in FIG. 9, in the second embodiment, the power meter 4 not only supplies the power supplied from the commercial power source to the refrigeration equipment 2-k but also the power load via the power supply line 7. The apparatus 8 is also configured to be supplied. The power load device 8 collectively includes loads to be demand controlled in addition to the cooling / heating device 2-k such as lighting, office equipment, and office air conditioning equipment.

  This power meter 4 measures the total (total power consumption) of all the load power of the refrigeration equipment 2-k to be subject to demand control and the load power of the power load equipment 8, and the power corresponding to the total A pulse signal is periodically transmitted to the demand control device 10 via the communication line 6. On the other hand, the demand control device 10 counts the power pulse signal input via the communication line 6 to thereby determine the power consumption of the plurality of refrigeration devices 2-k to be demand controlled and the power load device to be demand-controlled. The total power consumption of 8 is periodically calculated as the total power consumption (kWh). In addition, the flowchart which shows operation | movement of the demand control apparatus 10 which concerns on this Embodiment 2 is the same as the flowchart shown in FIG.

  In the demand control apparatus 10 according to the present embodiment as described above, the power measurement data is data related to the power consumption of the plurality of cooling / heating devices 2-k and the power consumption of the other power load devices 8. . Therefore, it is possible to realize demand control having the same effect as in the first embodiment while taking into consideration the power consumption of the power load device 8 that is a demand management target.

<Embodiment 3>
FIG. 10 is a block diagram showing a configuration of a demand control system including the demand control apparatus 10 according to Embodiment 3 of the present invention. In the demand control system according to the third embodiment, components that are the same as or similar to the components described in the first embodiment are denoted by the corresponding reference numerals, and different points will be mainly described below. .

  The demand control system according to the third embodiment includes first and second demand control devices 10a and 10b, and an upper demand control device 10c that controls the first and second demand control devices 10a and 10b in an integrated manner. It is configured with. The first and second demand control devices 10a and 10b and the higher-order demand control device 10c are communicably connected via communication lines 9a and 9b, and all data to be handled by the demand control system is stored. , Sent and received between them.

  The first demand control device 10a is capable of demand-controlling the first plurality of cooling / heating devices 2a-k installed for the first target space 1a as in the above-described demand control device 10 ( Here, k = 1, 2, 3, 4). Similarly to the demand control device 10 described above, the second demand control device 10b is capable of demand-controlling the second plurality of cooling / heating devices 2b-k installed for the second target space 1b ( Here, k = 1, 2, 3, 4).

  The first cooling / heating device 2a-k includes an indoor unit 21a-k disposed in the first target space 1a and a heat source unit 22a-k disposed outside the first target space 1a. Has been. The indoor units 21a-k and the heat source units 22a-k are connected to each other by a refrigerant pipe 23a-k so that heat can be transferred. The second cooling / heating device 2b-k includes an indoor unit 21b-k disposed in the second target space 1b and a heat source unit 22b-k disposed outside the second target space 1b. Has been. The indoor unit 21b-k and the heat source unit 22b-k are connected to each other by a refrigerant pipe 23b-k so that heat can be moved.

  As shown in FIG. 10, in the third embodiment, the power meter 4 sends power supplied from a commercial power source to the first plurality of refrigeration devices 2a-k via the first power supply line 5a. While supplying, it supplies to 2nd several cold-heating apparatus 2b-k via the 2nd electric power supply line 5b. This power meter 4 is the sum of all load powers of the first plurality of cooling / heating devices 2a-k to be subject to demand control and all load powers of the second plurality of cooling / heating devices 2b-k (power consumption). And a power pulse signal corresponding to the sum is periodically transmitted to the host demand control apparatus 10c via the communication line 6c.

  The host demand control device 10c counts the power pulse signals input via the communication line 6c, thereby allowing the power consumption of the first and second plurality of refrigeration devices 2a-k and 2b-k that are demand control targets. Is periodically calculated as the total power consumption (kWh).

  Here, the host demand control apparatus 10c includes the data storage unit 101, the performance model data storage unit 102, the data setting unit 103, and the demand control amount calculation unit 104 described in the first embodiment. .

Based on the current and past power measurement data (current and past demand values V) stored in the data storage unit 101, the higher-order demand control device 10 c configured in this way is the first and second in the future. First and second demand control amounts ΔV _a and ΔV _b corresponding to power consumption to be reduced in the demand control devices 10a and 10b are calculated. Although the details will be described later, the first and second demand control amounts ΔV _a and ΔV _b are obtained by changing the demand control amount ΔV into the first plurality of cooling devices 2a-k and the second plurality of cooling heats. This is allocated to the devices 2b-k. The first demand control amount ΔV _a calculated by the host demand control device 10c is transmitted to the first demand control device 10a via the communication line 9a. Similarly, the second demand control amount ΔV _b calculated by the host demand control device 10c is transmitted to the second demand control device 10b via the communication line 9b.

  Each of the first and second demand control devices 10a and 10b includes the data storage unit 101, the performance model data storage unit 102, the data setting unit 103, the capacity suppression amount calculation unit 105, and the optimum operation calculation described in the first embodiment. A unit 106, a control signal transmission unit 107, and the like are provided.

The first and second demand control devices 10a and 10b configured as described above change the demand control amount ΔV used in the demand control device 10 to the first and second demand control amounts ΔV _a and ΔV _b . Use instead.

<Operation>
FIG. 11 is a flowchart showing the operation of the higher-order demand control apparatus 10c according to the third embodiment. This flowchart is the same as the flowchart (FIG. 7) described in the first embodiment except for step S11. However, steps S4, S5, and S6 are executed in each of the first and second demand control devices 10a and 10b. Hereinafter, the operation from step S4 to step S7 will be briefly described.

First, in step S4, the first demand control apparatus 10a, by performing the same process as in step S4 in the first embodiment, the first power changes mu _a calculated for the first target space 1a , transmits a first power change mu _a that the calculated upper demand control device 10c. Similarly, the second demand control apparatus 10b calculates the power consumption changes mu _b with respect to the second object space 1b, it sends a second power change mu _b that the calculated upper demand control device 10c.

Next, in step S11, the host demand control apparatus 10c uses the demand control amount ΔV calculated in step S2 as the first and second power consumption changes μ _a and μ _b as shown in the following equation (10). Is distributed to the first and second demand control amounts ΔV _a and ΔV _{b based} on the above. Then, the host demand control device 10c transmits the first and second demand control amounts ΔV _a and ΔV _b to the first and second demand control devices 10a and 10b, respectively.

Then, at step S5, the first demand control apparatus 10a, by performing the same processing as step S5 in the first embodiment, a first power change mu _a of which is calculated in step S4, step Based on the first demand control amount ΔV _a calculated in S11, the first necessary capacity suppression amount ΔQ _a related to the first target space 1a is calculated. Similarly, the second demand control apparatus 10b, on the basis of the second power change mu _b calculated in step S4, and a second demand control amount [Delta] V _b calculated in step S11, the The second necessary capacity suppression amount ΔQ _b for the second target space 1b is calculated.

Next, at step S6, the first demand control apparatus 10a, by performing the same processing as step S6 in the first embodiment, using a first required capacity restriction amount Delta] Q _a calculated in step S5 Thus, the calculation of the optimum operation control for the target space 1a is performed. Thereby, the 1st demand control apparatus 10a makes the 1st which minimizes the total value of the value obtained by multiplying the power consumption of 1st some cold-heating apparatus 2a-k, and those driving | running state values, respectively. The operation capability and the operation state value of the plurality of cooling / heating devices 2a-k are calculated. Similarly, the second demand control apparatus 10b, such as by using the second required capacity restriction amount Delta] Q _b calculated in step S5, executing calculation of the optimum operation control related to the target space 1b. Thereby, the second demand control device 10b minimizes the total value of the values obtained by multiplying the power consumption of the second plurality of refrigeration devices 2b-k and their operating state values, respectively. The operation capability and operation state value of the plurality of cooling / heating devices 2b-k are calculated.

  In step S7, the host demand control device 10c determines the first and second plurality of refrigeration devices 2a-k, 2b- according to the operation capacity and the operation state value calculated by the first and second demand control devices 10a, 10b. A control signal for controlling k is sent to the first and second demand control devices 10a and 10b, respectively.

  According to the demand control apparatus 10 according to the present embodiment as described above, the same effects as those in the first embodiment are obtained for each of the plurality of target spaces (first and second target spaces 1a and 1b). Demand control can be performed. In addition, the required demand control amount can be secured, and the operation of the cooling / heating device with reduced power consumption as a whole can be realized so that the operation capacity is not biased in each target space.

  It should be noted that the present invention can be freely combined with each other within the scope of the invention, and each embodiment can be appropriately modified or omitted.

  DESCRIPTION OF SYMBOLS 1 Object space, 2,2-1,2-2,2-3,2-4 Refrigeration equipment, 8 Electric power load equipment, 10 Demand control apparatus, 101 Data storage part, 102 Performance model data storage part, 104 Demand control amount Calculation unit, 105 ability suppression amount calculation unit, 106 optimum operation calculation unit, 107 control signal sending unit.

Claims (6)

A demand control device capable of demand-controlling a plurality of refrigeration equipment installed in the same space,
Data storage means for storing model data relating to a performance model representing the relationship between operating capacity and power consumption for each of the plurality of cooling devices, and power measurement data relating to power consumption of the plurality of cooling devices;
Demand control amount calculation means for calculating a demand control amount to be reduced in the future based on the current and past power measurement data;
Based on the current operating capacity of the desired cooling equipment in operation and the model data, a change in power consumption per unit change in the operating capacity of the cooling equipment is calculated, and the calculated power consumption change and the demand control amount A capability suppression amount calculation means for calculating a required capability suppression amount based on
The corrected overall cooling load obtained by subtracting the necessary capacity suppression amount from the sum of cooling loads corresponding to the operating capacities to be output in the future by the plurality of cooling devices, the operating capacities of the plurality of cooling devices, and their operation / A value obtained by multiplying the power consumption of the plurality of cooling devices and their state values, respectively, under the constraint that the total value of the values obtained by multiplying the state values indicating the stopped state is equal. Optimal operation calculation means for calculating the operation capacity and the state value of the plurality of cooling devices that minimize the total value of
A demand control device, comprising: control signal sending means for sending control signals related to the operation capability and the state value of the plurality of cooling devices calculated by the optimum operation calculating means to the plurality of cooling devices. The demand control device according to claim 1,
The model data includes polynomial coefficients that define the performance model;
The capability suppression amount calculation means includes:
A demand control device that calculates the power consumption change based on a current operating capability of a desired cooling / heating device in operation and the coefficient included in the model data. The demand control device according to claim 1 or 2,
The demand control amount calculation means includes:
A demand control device that predicts a future demand value based on the current and past power measurement data, and calculates the demand control amount based on an excess of the predicted demand value with respect to a preset upper limit demand value. The demand control device according to any one of claims 1 to 3,
The power measurement data is
A demand control device, which is data relating to power consumption of the plurality of cooling devices and power consumption of other power load devices. The demand control device according to claim 1,
The first plurality of cooling / heating devices are arranged for the first same space, and the second plurality of cooling / heating devices are arranged for the second same space,
Instead of the demand control amount, a demand control device that uses first and second distributed demand control amounts obtained by distributing the demand control amounts to the first and second plurality of cooling devices. A demand control method capable of demand-controlling a plurality of refrigeration devices installed in the same space,
(A) storing in the data storage means model data relating to a performance model that represents the relationship between the operation capacity and power consumption for each of the plurality of cooling devices, and power measurement data including power consumption of the plurality of cooling devices;
(B) calculating a demand control amount to be reduced in the future based on the current and past power measurement data;
(C) Based on the model data and the current operating capacity of the desired cooling / heating device in operation, a power consumption change per unit change in the operating capacity of the cooling / heating device is calculated, and the calculated power consumption change and the Calculating a required capacity suppression amount based on the demand control amount;
(D) the corrected overall cooling load obtained by subtracting the necessary capacity suppression amount from the sum of the cooling loads corresponding to the operating capacities that the plurality of cooling devices should output in the future, the operating capacities of the plurality of cooling devices, and Under the constraint that the total value of the values obtained by multiplying each of the state values indicating the operation / stop state of each is equal to each other, the power consumption of the plurality of cooling devices is multiplied by the state values, respectively. Calculating the operating capacity and the state value of the plurality of cooling devices to minimize the total value of the obtained values;
(E) a control signal sending means comprising a step of sending a control signal related to the operation capacity and the state value of the plurality of cooling / heating devices calculated in the step (d) to the plurality of cooling / heating devices, respectively. Control method.

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