JP2000146257A - Method of and device for controlling building energy system and recording medium with control processing program recorded - Google Patents

Abstract

PROBLEM TO BE SOLVED: To realize a more optimum design of a building energy system than a prior art and control an application. SOLUTION: In a cogeneration system for supplying energy to a power load, a cooling load and a heating load by using a gas engine 31, a heat pump 30 and an exhaust heat using absorption type refrigerating machine 32 on the basis of energy from a power supply source EP and a city gas supply source UG, a prescribed performance function is employed to control an optimum construction to be obtained. In this case, Hamilton algorithm is used based on prescribed input parameters to calculate and output prescribed variables and output parameters go that the function value of the performance function is minimum. Then, the gas engine 31, the exhaust heat using absorption type refrigerating machine 32 and the heat pump 30 are controlled so as to obtaine the calculated output parameters. so that an application is achieved by maintaining the calculated optimum design conditions.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] The present invention relates to a method of converting the supplied energy into a predetermined value by using at least one energy conversion means based on energy supplied from at least one of a power supply source and a fuel supply source. A building energy system for converting the converted energy into another energy and supplying the converted energy to at least one of a power load, a cooling load, and a heating load so as to be optimally configured in the building energy system. The present invention relates to a control method and apparatus, and a recording medium that records a control processing program for a building energy system.

[0002]

2. Description of the Related Art Cogeneration systems (hereinafter referred to as cogeneration systems)
It is called CGS. Conventionally, two or more effective energies are obtained from a single energy. However, here, the target is a system that generates electricity using gas fuel and collects the exhaust heat to supply heat. And Therefore, C
GS is a system that is also effective for effective energy utilization and peak power load problems, and is also expected to take measures against global environmental problems (for example, Prior Art Document 1 “Air Conditioning and Sanitary Engineering Society,” Planning, Design and Evaluation of Cogeneration System Using City Gas ", Maruzen, 1994
See year. ).

An important issue in the design of a CGS is to determine a long-term economical system and device configuration based on the demand for electricity and heat. However,
Determining the configuration and capacity of a device in consideration of the operation policy of each device is very complicated, and is generally a matter of extreme difficulty. For this reason, it is a conventional general method (hereinafter, referred to as a conventional example) that rules for system operation such as power demand tracking and heat demand tracking are set, and economic evaluation and system operation are performed by a simulation method. ) (For example,
See Prior Art Document 1 and Prior Art Document 2, "Iwatani et al.," Analysis 1 of Effect of Design Factors of Building Facilities on Energy Saving Effect ", Proceedings of 1997 Annual Conference of Japan Society of Air Conditioning and Sanitary Engineers". )

[0004]

In the conventional example, conventionally,
The design conditions are evaluated depending on whether the operation of the gas engine is set according to the power demand (electric drive) or whether it is set according to the cooling and heating demand (heat drive). For this reason, although the evaluation can be performed when the operating conditions are set, there is a problem that the optimization calculation including the operating conditions cannot be performed.

[0005] The building energy system obtains energy from a power supply source and a fuel supply source, and also requires a power load, a cooling load or a cooling load (cooling load is also referred to as a cooling load), and heating required for the building. It is a system that satisfies the load and hot water supply load, and there is a similar problem in a building energy system including CGS.

SUMMARY OF THE INVENTION An object of the present invention is to solve the above-mentioned problems and to provide a control method and apparatus for a building energy system capable of performing optimal control and operation control as compared with the conventional example, and a recording recording a control processing program. To provide a medium.

[0007]

According to a first aspect of the present invention, there is provided a control method of a building energy system, wherein at least one energy conversion is performed based on energy supplied from at least one of a power supply source and a fuel supply source. In a building energy system for converting the supplied energy to another predetermined energy by using means and supplying the converted energy to at least one of a power load, a cold load, and a hot load, A control method of a building energy system for controlling to an optimal configuration using a predetermined evaluation function, wherein the power load of the power load, the cooling load of the cooling load, and the heating load of the heating load. At least one of them, the number of divided devices of the energy conversion means, the conversion efficiency of the energy conversion means, The relationship between the conversion efficiency and the maximum input capacity of the conversion means and the initial cost, the energy rate data of the energy conversion means, the maintenance cost of the building energy system, and the initial cost and running cost of the energy supply system to be compared. Inputting the input parameters including the following, storing the input parameters in the storage means, based on the input parameters stored in the storage means, using a predetermined Hamiltonian algorithm, the evaluation So that the function value of the function is minimum or maximum, the input energy amount to the energy conversion means,
Calculating and outputting variables and output parameters including a waste energy amount from the energy conversion means, an output capacity of the energy conversion means, and an initial cost and a running cost of the building energy system. I do.

Further, a control method of a building energy system according to a second invention uses a plurality of energy conversion means based on energy supplied from at least one of a power supply source and a fuel supply source. In a building energy system for converting the supplied energy to another predetermined energy and supplying the converted energy to at least one of a power load, a cold load, and a heat load, a predetermined evaluation function is defined as: A control method for a building energy system that controls to be an optimal configuration by using at least one of a power load of the power load, a cold load of the cold load, and a thermal load of the warm load. , The number of divided devices of each energy conversion means, the conversion efficiency of each energy conversion means, and the conversion of each energy conversion means. The relationship between the efficiency and the maximum input capacity and the initial cost, the relationship between the input energy amount and the maximum input capacity and the partial load factor in each of the energy conversion means, and the energy rate data of each of the energy conversion means, Inputting input parameters including a maintenance cost of the building energy system and an initial cost and a running cost of an energy supply system to be compared; storing the input parameter in a storage unit; and storing the storage unit. Based on the input parameters stored in the above, using a predetermined Hamiltonian algorithm, so that the function value of the evaluation function is minimum or maximum, the input energy amount to each of the energy conversion means, and the energy conversion The amount of waste energy from the means Calculating and outputting variables and output parameters including an output capacity of the energy conversion means, a partial load factor of each of the energy conversion means, and an initial cost and a running cost of the building energy system. .

Further, a control method of a building energy system according to a third aspect of the present invention uses a gas engine, a heat pump, and an exhaust-heat-absorption refrigerator based on energy from a power supply source and a city gas supply source. In a building energy system including a cogeneration system for supplying energy to an electric load, a cooling load, and a heating load, a building energy system control method for controlling to an optimal configuration using a predetermined evaluation function is used. Therefore, the input energy amount including the electric power load amount, the cooling load amount, and the heating load amount, the gas engine device price, the heat pump device price, the exhaust heat utilization absorption refrigerator device price, and the exhaust heat utilization The number of absorption chillers, the number of heat pumps, electricity rate data, gas rate data, and the above building energy system Inputting input parameters including a maintenance cost and an initial cost and a running cost of the energy supply system to be compared; storing the input parameter in the storage unit; and storing the input parameter in the storage unit. Based on the parameters, using a predetermined Hamilton algorithm, the purchased power amount, the maximum value of the purchased power amount, the purchased gas amount, and the maximum value of the purchased gas amount so that the function value of the evaluation function is minimized. And the amount of heat input to the exhaust heat absorption chiller for cooling, the amount of heat input to the exhaust heat absorption chiller for heating, the amount of input power to the heat pump for cooling, The amount of input power to the heat pump, the amount of waste power, the amount of waste heat waste, the device capacity of the waste heat utilization absorption refrigerator, and the device capacity of the heat pump, Serial and initial cost and running cost of the building energy system, and wherein the power running costs, in that it comprises the step of calculating and outputting variables and output parameters and a running cost of the gas.

In the control method for a building energy system, the thermal load preferably includes at least one of a heating load and a hot water supply load. Further, the energy conversion means is preferably a generator, an electric heat source, a heat source for ice making and a heat storage tank, a waste heat utilization machine, a fuel-type cold and hot water generator, a gas heat pump, a fuel-type boiler, At least one of the following.

In the control method for a building energy system, the evaluation function preferably calculates a difference between an initial cost of the building energy system and an initial cost of the energy supply system to be compared with a running cost of the building energy system. And the return on investment divided by the difference between the energy supply system and the running cost of the energy supply system to be compared. The evaluation function is preferably an energy consumption represented by a linear combination of the input energy amounts. Moreover, the evaluation function is preferably the emissions of CO _2, expressed as a linear combination of the respective input energy. Further, the evaluation function is preferably an evaluation function represented by a linear combination of the investment recovery years, the energy consumption, and the CO ₂ emission.

In the control method for a building energy system according to the first or second aspect of the present invention, preferably, each of the energy conversion means is controlled so as to have the calculated input energy amount. The method further includes the step of operating while maintaining the optimum design conditions. In the control method for a building energy system according to the third aspect of the present invention, preferably, the gas engine is controlled such that the calculated gas purchase amount is reached, and the calculated input heat amount for cooling and heating are calculated. By controlling the exhaust heat utilization type absorption refrigerator to have an input heat amount for the heat pump, and controlling the heat pump to be the input power for the cooling and the input power for the heating calculated above. The method further includes a step of operating while maintaining the optimum design conditions thus set.

[0013] A control device for a building energy system according to a fourth aspect of the present invention uses at least one energy conversion means based on energy supplied from at least one of a power supply source and a fuel supply source. In a building energy system for converting supplied energy into another predetermined energy and supplying the converted energy to at least one of a power load, a cold load, and a heat load, a predetermined evaluation function is used. A control device for a building energy system that controls to be an optimal configuration, wherein at least one of a power load of the power load, a cooling load of the cooling load, and a heating load of the heating load, The number of divided devices of the energy conversion means, the conversion efficiency of the energy conversion means, and the conversion of the energy conversion means The input including the relationship between the rate and the maximum input capacity and the initial cost, the energy rate data of the energy conversion means, the maintenance cost of the building energy system, and the initial cost and running cost of the energy supply system to be compared. Input means for inputting parameters, storage means for storing input parameters input by the input means,
Based on the input parameters stored in the storage means,
Using a predetermined Hamiltonian algorithm, the input energy amount to the energy conversion means, the waste energy amount from the energy conversion means, and the energy conversion means so that the function value of the evaluation function is minimum or maximum. And a calculating means for calculating and outputting variables and output parameters including the output capacity of the above and the initial cost and running cost of the building energy system.

The control device for a building energy system according to the fifth invention uses a plurality of energy conversion means based on energy supplied from at least one of a power supply source and a fuel supply source. In a building energy system for converting the supplied energy to another predetermined energy and supplying the converted energy to at least one of a power load, a cold load, and a heat load, a predetermined evaluation function is defined as: A control device for a building energy system that controls to be an optimal configuration by using at least one of a power load of the power load, a cold load of the cold load, and a thermal load of the warm load. , The number of divided devices of each energy conversion means, the conversion efficiency of each energy conversion means, and the conversion of each energy conversion means. The relationship between the efficiency and the maximum input capacity and the initial cost, the relationship between the input energy amount and the maximum input capacity and the partial load factor in each of the energy conversion means, and the energy rate data of each of the energy conversion means, An input unit for inputting input parameters including a maintenance cost of the building energy system and an initial cost and a running cost of an energy supply system to be compared; a storage unit for storing input parameters input by the input unit; Based on the input parameters stored in the storage means, using a predetermined Hamiltonian algorithm, the amount of input energy to each of the energy conversion means, so that the function value of the evaluation function is minimum or maximum, and The amount of waste energy from energy conversion means Calculating means for calculating and outputting variables and output parameters including an output capacity of each of the energy converting means, a partial load factor of each of the energy converting means, and an initial cost and a running cost of the building energy system. It is characterized by the following.

Further, a control device for a building energy system according to a sixth aspect of the present invention uses a gas engine, a heat pump, and a waste heat absorption refrigerator based on energy from a power supply source and a city gas supply source. In a building energy system including a cogeneration system for supplying energy to an electric load, a cooling load, and a heating load, a building energy system control device that controls to have an optimal configuration using a predetermined evaluation function. Therefore, the input energy amount including the electric power load amount, the cooling load amount, and the heating load amount, the gas engine device price, the heat pump device price, the exhaust heat utilization absorption refrigerator device price, and the exhaust heat utilization The number of absorption chillers, the number of heat pumps, electricity rate data, gas rate data, and the above building energy system Input means for inputting an input parameter including a maintenance cost and an initial cost and a running cost of the energy supply system to be compared; a storage means for storing the input parameter input by the input means; and a storage means for storing the input parameter. Based on the input parameters obtained, using a predetermined Hamilton algorithm, so that the function value of the evaluation function is minimized,
Purchased electric energy, maximum value of purchased electric energy, purchased gas amount,
Maximum value of purchased gas amount, input heat amount to exhaust heat absorption absorption refrigerator for cooling, input heat amount to exhaust heat absorption refrigerator for heating, and input to heat pump for cooling The amount of power, the amount of power input to the heat pump for heating, the amount of waste power, the amount of waste waste heat, the device capacity of the waste heat utilization absorption refrigerator, the device capacity of the heat pump, and the initials of the building energy system It is characterized by comprising a calculating means for calculating and outputting variables and output parameters including cost and running cost, power running cost and gas running cost.

In the control device for a building energy system, the thermal load preferably includes at least one of a heating load and a hot water supply load. Further, the energy conversion means is preferably a generator, an electric heat source, a heat source for ice making and a heat storage tank, a waste heat utilization machine, a fuel-type cold and hot water generator, a gas heat pump, a fuel-type boiler, At least one of the following.

In the control device for a building energy system, the evaluation function preferably calculates a difference between an initial cost of the building energy system and an initial cost of the energy supply system to be compared with a running cost of the building energy system. And the return on investment divided by the difference between the energy supply system and the running cost of the energy supply system to be compared. The evaluation function is preferably an energy consumption represented by a linear combination of the input energy amounts. Moreover, the evaluation function is preferably the emissions of CO _2, expressed as a linear combination of the respective input energy. Further, the evaluation function is preferably an evaluation function represented by a linear combination of the investment recovery years, the energy consumption, and the CO ₂ emission.

In the control device for a building energy system according to the first or second aspect of the present invention, preferably, each of the energy conversion means is controlled so as to have the calculated input energy amount, so that the calculated energy amount is calculated. Control means for maintaining the optimum design conditions for operation is further provided. In the control device for a building energy system according to the third aspect of the present invention, preferably, the gas engine is controlled such that the calculated gas purchase amount is attained, and the calculated input heat amount for cooling and heating are calculated. By controlling the exhaust heat utilization type absorption refrigerator to have an input heat amount for the heat pump, and controlling the heat pump to be the input power for the cooling and the input power for the heating calculated above. And a control unit for maintaining the optimum design conditions for operation.

According to a seventh aspect of the present invention, there is provided a recording medium on which a control program for a building energy system is recorded, wherein the control medium includes a control processing program including each step in the method for controlling a building energy system.

[0020]

Embodiments of the present invention will be described below with reference to the drawings.

<First Embodiment> FIG. 1 is a block diagram showing the configuration of a control device of a cogeneration system (CGS) according to a first embodiment of the present invention.
The control device of the CGS 100 according to the first embodiment uses a gas engine 31, a heat pump 30, and an exhaust heat utilization absorption refrigerator 32 based on the energy from the power supply source EP and the city gas supply source UG. In a cogeneration system for supplying energy to an electric load, a cooling load, and a heating load, control is performed using a predetermined evaluation function so as to obtain an optimal configuration, and a Hamilton algorithm is used based on predetermined input parameters. Is used to calculate and output predetermined variables and output parameters so that the function value of the evaluation function is minimized. Then, the gas engine 31 and the exhaust heat absorption refrigeration are used so that the calculated output parameters become the calculated output parameters. By controlling the heat pump 32 and the heat pump 30, the operation is performed while maintaining the calculated optimum design conditions. It is set to.

First, a model of the CGS 100 will be described. FIGS. 3 and 4 show a CGS model and a comparative model (referred to as a model of an energy supply system to be compared) to be subjected to design control. In the CGS model of FIG. 3, electric energy from a power supply source EP is supplied to a heat pump (hereinafter, referred to as HP) 30 and a power load L1, and gas energy from a city gas supply source UG is supplied to a gas engine (hereinafter, referred to as GE). .). GE
31 converts the supplied gas energy into electric energy and outputs it to the HP 30 and the power load L1, where
Discharges heat during energy conversion. The HP 30 converts electric energy from the power supply sources EP and GE 31 into heat energy, generates the heat energy, and outputs the heat energy to the cooling load L2 and the heating load L3. On the other hand, the exhaust heat utilization absorption refrigerator (hereinafter, referred to as AR) 32 is provided with a GE3 using a known exhaust heat utilization absorption method.
1, the cooling load L2 and the heating load L
3 absorbs heat energy to perform a refrigeration action. Here, the power load L1 includes a lighting device or an electric device, the cooling load L2 includes a cooling device, and the heating load L3 includes a heating device.

On the other hand, in the comparative model of FIG. 4, the electric energy from the electric power
The HP 30 converts the electric energy from only the power supply source EP into heat energy, generates the heat energy, and outputs the heat energy to the cooling load L2 and the heating load L3.

That is, the CGS 100 purchases city gas in addition to the electric power, and uses the electric power generated by the GE 31 and the exhaust heat for the electric power of the building and the cooling and heating load demand. CG
To evaluate the economics of S100, etc., purchase only electric power,
The demand for cooling and heating was compared with the model using HP30.
When the CGS 100 is introduced, the capacity of the HP 30 can be reduced, but the GE 31 and the AR 32 for power generation are required.

The cost of the CGS 100 is considered as the initial cost of the initial purchase equipment, and the running cost of the power and gas purchased for operating the system and the CGS maintenance cost. When the capacity of the GE 31 is increased for the purpose of reducing the running cost, the initial cost increases. Conversely, GE31
, The initial cost is reduced, but the effect of reducing the running cost is reduced. Further, in many cases, the power demand that fluctuates seasonally and temporally and the heat demand for cooling and heating do not change proportionally, which complicates the system design. It is necessary to design an economical system that can operate efficiently under such conditions. In the present embodiment, a system for minimizing the investment recovery period and its operating conditions are calculated by using the evaluation function of how many years the initial cost increase due to the introduction of the CGS 100 can be recovered by reducing the running cost (return on investment). And CGS1
A control device for controlling 00 is disclosed.

In FIG. 1, the CGS control device of the present embodiment is constituted by a digital computer, and (a) a CPU (central processing unit) 10 for calculating and controlling the operation and processing of the control device; A) a ROM (read only memory) 11 for storing a basic program such as an operation program and data necessary for executing the basic program;
(C) operates as a working memory of the CPU 10,
A RAM (random access memory) 12 for temporarily storing parameters and data necessary for GS control processing,
(D) An input parameter 1 for storing an input parameter, and a variable and output parameter memory 4 for storing a variable and an output parameter, which are constituted by, for example, a hard disk memory.
(E) a parameter memory 13 including an evaluation function data memory 43 for storing function data of the evaluation function;
A keyboard interface 21 that is connected to a keyboard 14 for inputting data of input parameters and instruction commands, receives data and instruction commands input from the keyboard 14, performs interface processing such as predetermined signal conversion, and transmits the processed signals to the CPU 10. And (f) CPU
The CRT display 15 is connected to a CRT display 15 that displays output parameters, control information, setting instruction screens, and the like calculated by the CRT 10.
A display interface 22 that converts the image signal into an image signal for 5 and outputs it to the CRT display 15 for display;
(G) A printer that is connected to a printer 16 that prints output parameters, control information, setting instruction screens, and the like calculated by the CPU 10, performs predetermined signal conversion of print data to be printed, and outputs to the printer 16 for printing. An interface 23, and (h) C controlled based on output parameters and control information calculated by the CPU 10.
The control interface 24 is connected to the GS 100, performs predetermined signal conversion of the data, and outputs the data to the CGS 100 for control. (I) The CD-ROM 18 in which the CGS control processing program is stored stores the control processing program from the CD-ROM 18. A drive that is connected to a CD-ROM drive device 17 that reads out program data, performs a predetermined signal conversion, and transfers the read out program data of the control processing program to the RAM 12 or another hard disk memory (not shown). An apparatus interface 25 is provided, and these circuits 10-13 and 21-25 are connected via a bus 20.

In the control device, a CG described later in detail
The control processing program for the control processing of S may be stored in the CD-ROM 18 as described above, or may be stored in the RAM 1.
You may make it memorize beforehand in 2 or another hard disk memory.

The following conditions are assumed for the CGS model according to the present embodiment. (1) Disposal of waste heat from the GE 31 and generation surplus power are permitted. (2) The AR 32 and the HP 30 operate for cooling or heating on a monthly basis. (3) Consider the number division of the AR 32 and the HP 30. (4) The GE31, AR32, and HP30 devices can have any capacity. (5) The partial load characteristics of each device 30-32 are not considered.

Next, various data used in the control processing of the CGS and its calculation formula will be described.

(A) Power, cooling and heating load data Monthly standard power load (kW) and cooling load (k
W) and heating load (kW) are d _d (m,
h), d _c (m, h) and d _w (m, h).

(B) Device Performance and Price Data The power generation efficiency of the GE 31 having the maximum input capacity x _gm is η _gd , the waste heat recovery rate is η _gt , and the initial cost (device price including construction cost) is G _g (η _gd x _gm ). The cooling efficiency of the AR 32 having the maximum input capacity x _am is η _ac , the heating efficiency is η _aw , and the initial cost is G _a (η _ac x _am ). The cooling efficiency of the HP 30 having the maximum input capacity x _hm is η _hc , the heating efficiency is η _hw , and the initial cost is G _h (η _hc x _hm ). Here, the device cost was approximated by the following equation based on the real price. Here, a _ij is a coefficient for approximation.

[0032]

G _g (η _gd x _gm ) = a ₁₁ η _gd x _gm −a ₁₂ (η _gd x _gm ) ^a13

G _a (η _ac x _am ) = a ₂₁ + a ₂₂ η _ac x _am

G _h (η _hc x _hm ) = a ₃₁ η _hc x _hm −a ₃₂ (η _hc x _hm ) ^a33

(C) Cost of Electricity, City Gas, and CGS Maintenance The peak value of purchased power per hour is x _dm , the integrated value for one year is x _ds , and the basic charge and the pay-per-use charge are c _dp. , C _ds , and the peak value per hour of the purchased gas is x _gm , the integrated value for one year is x _gs , the flat rate basic charge, and the basic rate and the specific rate per gas usage are c, respectively.
_gb , c _gp , c _gs, and the CGS maintenance cost per power generation is c _cm . The power running cost x _rcd for one year, the gas running cost x _rcg including CGS maintenance, and the total running cost x _rc are expressed by the following equations.

[0034]

[Number 4] _{x rcd = c dp x dm +} c ds x ds

X _rcg = c _gb + c _gp x _gm + (c _gs + c _cm η _gd ) x _gs

X _rc = x _rcd + x _rcg

Next, variables of the CGS model will be described. In the calculation, purchased electricity x _d (m, h) and purchased gas x _g
(M, h), input heat energy x _ac (m, h), x _aw (m, h) of AR32 for cooling and heating, input power x _hc (m, h) of HP 30 for cooling and heating. , X
_hw (m, h), surplus power z _d (m, h), and surplus waste heat z _t (m, h) to be discarded are each non-negative variables.
The following relationship is established between the power energy, the exhaust heat output of the GE 31, the cooling load, and the heating load.

[0036]

X _d (m, h) + η _gd x _g (m, h) = d
_d (m, h) + x _hc (m, h) + x _hw (m, h) + z
_d (m, h)

Η _gt x _g (m, h) = x _ac (m, h) + x
_{aw (m, h) + z} t (m, h)

Η _ac x _ac (m, h) + η _hc x _hc (m, h) = d
_c (m, h)

Η _aw x _aw (m, h) + η _hw x _hw (m, h) =
d _w (m, h)

In calculating the initial cost of the division of the number of units
The HP30_hWhen divided evenly into
Input volume per unit after distribution to cooling and heating
Quantity x _hmCalculate (m). Heating load that HP30 covers
The month is as follows.

[0038]

[Equation 11]

Similarly, a month without a cooling load covered by the HP 30 is given by the following equation.

[0040]

(Equation 12)

For a month in which cooling and heating simultaneously exist, an integer n
introduced the _{x (0 <n x <n} h) becomes the following equation.

[0042]

(Equation 13)

Therefore, the required input capacity x _hm throughout the year is given by the following equation.

[0044]

[Equation 14]

The required input capacities x _am1 and x _am2 of the AR32 divided into two non-uniformly are as follows in a month in which there is no heating load _covered by the AR32.

[0046]

(Equation 15)

Similarly, the following equation is for a month in which the cooling load provided by the AR 32 is not provided.

[0048]

(Equation 16)

The month in which the cooling and heating loads are simultaneously present is given by the following equation.

[0050]

[Equation 17]

(Equation 18)

Here, the initial cost _{xic1 of} CGS
Is given by the following equation.

[0052]

X _ic1 = G _g (η _gd x _gm ) + G _h (η _hcn
h x _hm ) + G _a (η _ac x _am1 + η _ac x _am2 )

In the example of non-equal division of two HPs 30, the required input capacitance of the HP 30 at this time is x _hm1 , x _hm2
Then, the initial cost x _ic2 of the _CGS 100 can be calculated by the following equation.

[0054]

X _ic2 = G _g (η _gd x _gm ) + G _h (η _{hc xhm1} +
η _hc x _hm2 ) + G _a (η _ac x _am1 + η _ac x _am2 )

Next, each variable will be described. The control device according to the present embodiment, when given input data including device price, fee, and building load data, outputs output data such as purchased power, gas, device capacity, etc., which meet target conditions (evaluation function). Is performed. Therefore, according to the present embodiment, it is possible to calculate a system configuration that meets the conditions required by the user. Here, the input parameters are shown in Table 1. These parameters are input using the keyboard 14 and stored in the input parameter memory 41.
Table 2 shows variables and output parameters. These parameters are parameters calculated in the course of calculation in the CGS control process and are output as output parameters.

[0056]

[Table 1] Input parameters ――――――――――――――――――――――――――― Power load _dd (m, h) Cooling load _dc (M, h) Heating load d _w (m, h) ――――――――――――――――――――――――― Power generation efficiency of GE31 η _gd Heat recovery rate of GE31 η _gt Cooling efficiency of AR32 η _ac Heating efficiency of AR32 η _aw Cooling efficiency of HP30 η _hc Heating efficiency of HP30 η _hw ―――――――――――――――――― ―――――――――― GE equipment price approximation equation (Equation 1) G _g AR equipment price approximation equation (Equation 2) G _a HP equipment price approximation equation (Equation 3) G _h ――――――― ―――――――――――――――――――――― AR split number n _a HP split number n _h ―――――――――――――――――― ――――――――――― Basic electricity charges c _dp electricity metered rate c _ds gas flat rate basic rate c _gb gas metered basic rate c _gp gas metered rate c _gs ―――――――――――――――――――――――――― ――― CGS maintenance cost c Initial cost of the _cm comparative model y _ic Running cost of the comparative model y _rc ―――――――――――――――――――――――――――― ―

In Table 1, a coefficient is stored for the approximate expression of the device price. That is, the initial cost Gg (η _gd , which is the equipment price including the construction cost of GE31)
x _gm ), the relationship for calculating the initial cost of the GE 31 from the power generation efficiency η _gd and the maximum input capacity x _{gm as shown in} Expression 1 is stored in the parameter memory 13 in advance.
To memorize. Further, in order to calculate the initial cost Ga (η _ac , x _am ) which is the equipment price including the construction cost of the AR 32, as shown in Expression 2, the initial cost of the AR 32 is calculated from the cooling efficiency η _ac and the maximum input capacity x _am. The relationship for calculating the cost is stored in the parameter memory 13 in advance. Further, in order to calculate the initial cost Gh (η _hc , x _hm ) which is the equipment price including the construction cost of the HP 33, the HP efficiency is calculated from the cooling efficiency η _hc and the maximum input capacity x _hm as shown in Expression 3.
The relationship for calculating the initial cost of 33 is stored in the parameter memory 13 in advance.

[0058]

[Table 2] Variables and output parameters ―――――――――――――――――――――――――――― Purchased (input) electric energy x _d (m, h) ) Maximum value of purchased electric power x _dm Purchased (input) gas amount x _g (m, h) Maximum value of purchased gas amount x _gm ―――――――――――――――――――― AR input heat quantity for cooling x _ac (m, h) AR input heat quantity for heating x _aw (m, h) HP input electric energy x _hc (m , H) HP input electric energy for heating x _hw (m, h) ―――――――――――――――――――――――――――― Waste power Amount z _d (m, h) Waste heat amount z _t (m, h) AR device capacity (output capacity) x _am HP device capacity (output capacity) x _hm ―――――――――――――――― CGS Initial cost x running cost _ic power running cost x _rcd gas x _RCG CGS running costs x _rc ---------------------------- -

In this embodiment, a typical investment recovery period U in economic evaluation is used as an evaluation function for optimization calculation.
And the data is stored in the evaluation function data memory 43. From the initial cost y _ic and the running cost y _{rc of} the comparative model using only electric power without using city gas, the investment recovery period U as an evaluation function is expressed by the following equation.

[0060]

U = (x _ic −y _ic ) / (y _rc −x _rc )

Next, the known Hamiltonian algorithm used for the calculation of the optimization will be briefly described. X ₁ the position of the mass system with 2n dimensions, ..., x _n, momentum p _1, ..., p _n
The following equation holds when expressed by:

[0062]

## EQU22 ## dx _i / dt = iH / ｄp _i

[Number 23] _{dp i / dt = -∂H / ∂x} i

The motion state can be described by the Hamiltonian canonical equation. Here, conservative force (potential energy U)
At the mass point receiving mass (mass m = 1), the Hamiltonian characteristic function H is given by the following equation.

[0064]

H = (１ ／) Σp _i ² + U (x ₁ , x ₂ ,... X _n ) i

Here, the following equation is obtained by eliminating the Hamiltonian characteristic function and the momentum.

[0066]

## EQU25 ## d ² x _i / dt ² = −∂U / ∂x _i

This equation shows a motion in which the force received from potential energy is used as acceleration. Based on this, a calculation method in which the motion is calculated by the Verré method based on the force that each variable receives from the evaluation function and converges to the point of the minimum value of the evaluation function is called a Hamiltonian algorithm. As is apparent from Equation 25, the dimension of the degree of freedom is increased by introducing the momentum. We call it a “high-dimensional algorithm” and use it as a method for finding the optimal solution of a complex system.

In the actual calculation processing, the variable x
_d (m, h), x _g (m, h), x _ac (m, h), x
_{aw (m, h), x} hc (m, h), x hw (m, h), z d
From (m, h) and z _t (m, h),
Variables are reduced using the relationship between x _d (m, h) and z _d (m, h), and x _hc (m, h), x _hw (m, h), z _t (m, h)
h) The variables were selected. Thereby, 1728 (= 3 ×
The motion of a mass point in a (12 × 24 × 2) -dimensional phase space was assumed (assumed), and a change per minute time was tracked by using the force received from the evaluation function as acceleration, and optimization was performed. Details of the variable range of each variable and the acceleration calculated from the evaluation function are shown below.

X _hc (m, h), x _hw (m, h), z
_The range of motion for the variable _t (m, h) and the CGS
An expansion formula for calculating the acceleration when the initial cost of the model is represented by Expression 20 is shown below. True [] used here is a function that becomes 1 when the value inside [] is true and becomes 0 when the value is false.

(A) 0 ≦ x for variable x _hc (m, h)
_{When hc} ≦ d _c / η _hc

[0071]

２６U / ２６x _hc = c1 / (y _rc −x _rc ) (∂
_{x ic / ∂x hc) + {} (x ic -y ic) / (y rc -
x _rc ) ² ｝ (∂x _rc / ∂x _hc )

２７x _ic / ∂x _hc = (∂G _g / ∂x _g ) (∂x _g
/ ∂x _hc ) + (∂G _a / ∂x _ac ) (∂x _ac / ∂x _hc ) +
(∂G _h / ∂x _hc )

２８G _g / ∂x _g = (a ₁₁ η _gd −a ₁₂ a ₁₃ η _gd
^a13 x _gm ^a13-1 ) True [x _g = x _gm ]

２９x _g / ∂x _hc = −η _hc / (η _gt η _ac )

数 G _a / ∂x _ac = a ₂₂ η _ac (True [x _ac
= X _am1 ] + True [x _ac = x _am2 ])

３１x _ac / ∂x _hc = −η _hc / η _ac

３２G _h / ∂x _hc = (a ₃₁ η _hc −a ₃₂ a ₃₃ η _hc
^a33 x _hm ) × (True [x _hc = x _hm1 ] + True [x
_hc = _xhm2 ])

_{３３x rc} / ∂x _hc = (∂x _rcd / ∂x _d ) (∂x
_d / ∂x _hc ) + (∂x _rcg / ∂x _g ) (∂x _g / ∂x _hc )

_{３４x rcd} / ∂x _d = c _dp True [x _d =
x _dm ] + c _ds

_{３５x rcg} / ∂x _g = c _gp True [x _g =
x _gm ] + c _ds + c _cm η _gd

３６x _d / ∂x _hc = 1−η _gd (∂x _g / ∂x _hc )

(B) For variable x _hw (m, h), 0 ≦ x
_{When hw} ≦ d _w / η _hw

[0073]

３７U / ∂x _hw = {1 / (y _rc −x _rc )} (∂
_{x ic / ∂x hw) + {} (x ic -y ic) / (y rc -
x _rc ) ² ｝ (∂x _rc / ∂x _hw )

３８x _ic / ∂x _hw = (∂G _g / ∂x _g ) (∂x _g
/ ∂x _hw ) + (∂G _a / ∂x _aw ) (∂x _aw / ∂x _hw ) +
(∂G _h / ∂x _hw )

３９x _g / ∂x _hw = −η _hw / (η _gt η _aw )

４０G _a / ∂x _aw = a ₂₂ η _aw (True [x _aw
= X _am1 ] + True [x _aw = x _am2 ])

４１x _aw / ∂x _hw = −η _hw / η _aw

４２G _h / ∂x _hw = (a ₃₁ η _hw −a ₃₂ a ₃₃ η _hw
^a33 x _hm ) × (True [x _hw = x _hm1 ] + True [x
_hw = _xhm2 ])

_{４３x rc} / ∂x _hw = (∂x _rcd / ∂x _d ) (∂x _d /
∂x _hw ) + (∂x _rcg / ∂x _g ) (∂x _g / ∂x _hw ) ∂x _d / ∂
x _hw = 1−η _gd (∂x _g / ∂x _hw )

(C) For the variable z _t (m, h), z _t ≧ 0
When

[0075]

４４U / ∂z _t = {1 / (y _rc −x _rc )} (∂
_{x ic / ∂z t) + {} (x ic -y ic) / (y rc -x rc) 2}
(∂x _rc / ∂z _t )

[Number 45] _{∂x ic / ∂z t = (∂G} g / ∂x g) (∂x g / ∂z t)

４６x _g / ∂z _t = 1 / η _gt

４７x _rc / ∂z _t = (∂x _rcd / ∂x _d ) (∂x _d
/ ∂z _t ) + (∂x _rcg / ∂x _g ) (∂x _g / ∂z _t )

４８x _d / ∂z _t = −η _gd (∂x _g / ∂z _t )

FIG. 2 is a flowchart showing a CGS control process executed by the control device of the cogeneration system of FIG. 2, first, enter the input parameters at step S1 or not (interrupt process) or not is judged, when it becomes YES, and the Hamiltonian algorithm based on the evaluation function for minimizing the payback period U ₁ in step S2 The variables and output parameters are calculated using the parameters and stored in the variable and output parameters memory 42. In the present embodiment, variables and output parameters are calculated using a known Hamiltonian algorithm so that the function value of the evaluation function of Expression 21 is minimized. Next, in step S3, the calculated variables and output parameters are set to C
Display on the RT display 15 and the printer 1
6 is printed. In step S4, each device of the CGS 100 is controlled and operated so that the calculated output parameter value is obtained. In the operation control process of step S4, specifically, the calculated purchased gas amount x _g (m,
h) to control the GE 31 so that AR for cooling
The AR 32 is controlled so that the input heat quantity x _ac (m, h) and the AR input heat quantity x _aw (m, h) for heating, the HP input power x _hc (m, h) for cooling and the heating H for
By controlling the HP 30 so that the P input power becomes x _hw (m, h), the operation can be performed while maintaining the calculated optimal design conditions.

[0077]

DESCRIPTION OF THE PREFERRED EMBODIMENTS The present inventors simulated the CGS control device shown in FIG. The calculation conditions and results will be described below.

The data used in the optimization calculation of the system for minimizing the payback period in the CGS model is as follows. (A) Load data The load data assumes a standard hotel with a total floor area of 10,000 m ² where cooling and heating demands exist simultaneously. Power,
FIGS. 5 to 7 show load fluctuations of cooling and heating on a monthly time basis. (B) Equipment prices Figures 8 to 10 show the market prices of equipment of a plurality of manufacturers including construction costs and their approximate values. In this case, the number 1 to number 3 of the coefficients, output capacitance (kW), when the price (yen), respectively, a ₁₁ =
380, a ₁₂ = 3.1, a ₁₃ = 1.5, a ₂₁ = 10,0
00, a ₂₂ = 55, a ₃₁ = 95, a ₃₂ = 11, a ₃₃ =
1.2. In this embodiment, when the number is divided, the apparatus price is determined based on the total capacity, and the cost loss due to the division is not considered. (C) Charge coefficient data In calculating the charge of electricity, city gas, and the cost required for maintenance of the CGS 100, the amount of use (kW) and charge (thousand yen) are _cdp = 18.72 and c, respectively. _ds =
0.48, c _gb = 540, c _gp = 1.184, c _gs =
0.06678 and c _cm = 0.105. here,
The annual running cost is calculated with one month as 30 days. The initial cost and running cost of the comparative model when using the above data are respectively y _ic = 4
7717 and y _rc = 71203 (unit: 1,000 yen).

In the calculation of this embodiment, the following three CGS
Calculations were performed on the model to minimize the payback years U. (A) Model 1 HP30 with one AR32 and the required capacity divided equally
Is a CGS model in which a plurality of. Are used, and the use of AR32 is preferentially used for a large load with respect to the cooling and heating load of each month. (B) Model 2 CG using two AR32s with the required capacity unequally divided and multiple HP30s with the required capacity evenly divided
This is an S model. (C) Model 3 Both AR32 and HP30 are CGS models in which the required capacity is unequally divided into two.

Further, a calculation result in the simulation of this embodiment will be described below. FIG. 11 shows the calculation results of the minimum investment recovery years in each model, and FIGS. 12 to 14 show the calculation results of the initial cost, running cost, and total waste heat amount at that time. 15 and 16 show the breakdown of the initial cost and running cost when the payback period is minimized.
Shown in The results of these calculations will be described below.

(A) Model 1 and Model 2 When the investment recovery years are optimized as an evaluation function, HP30
When the number of divisions is small, a large amount of gas is purchased even if there is heat to be discarded, thereby reducing running costs. HP
As the number of divisions of the 30 is increased, gas is wasted (reduction of the amount of waste heat) and electric power is used to reduce the initial cost and the running-up cost, thereby reducing the investment recovery years. These changes are illustrated in FIG.
5 and FIG. In the load data used here, the effect was saturated when the number of HP divisions was about 4 or 5, and it was found that the effect was hardly obtained even if the number of divisions was increased further.

In the model 1 and the model 2, the payback years, initial costs, and running costs show almost the same tendency. In Model 2 in which the AR was divided unequally, a reduction in the payback period was expected compared to Model 1, but the calculation result did not. However, a slight reduction in the amount of waste heat can be expected from FIG. 14 as an effect of unequally dividing the required capacity. The ratio of the capacity division at this time is 1/2.
0 or less.

(B) Model 3 From the results of FIGS. 11 to 19, it was found that the model 3 can realize the investment recovery years when the number of HP divisions of the models 1 and 2 is increased. This result shows that AR32 and HP
Although the number of divisions in each of the 30s is small and the number of divisions is small, it has been found that by performing the non-equal division, it is possible to achieve quite ideal system optimization under the condition of minimizing the investment recovery period. At this time, the division ratio of the AR32 is about 14: 1,
Was about 4: 1.

In the present embodiment, optimization of the system for minimizing the payback period and the dependence of the device division were examined without defining rules such as power demand tracking and heat demand tracking for CGS operation. As a result, it was confirmed that the evaluation based on the payback period including the fee structure at the time of energy purchase was possible by using the Hamiltonian algorithm.
Such an evaluation method is an effective means for deriving a detailed calculation value regarding system optimization by ideal operation and its operation condition.

As described above, according to the present embodiment, the Hamiltonian algorithm, which is effective in the optimization calculation of a system having a large number of control variables and performing a complicated motion, is used.
The present invention provides a CGS control method and apparatus from the viewpoint of economy. We did not set system operation rules such as power demand follow-up and heat demand follow-up, and optimized the system in CGS with consideration for equipment split, using the payback period including the purchased electricity and purchased gas tariff as an evaluation function. As a result, it was confirmed that the present control method and apparatus are effective for designing in consideration of optimal operation of CGS.

<Modification> In the above embodiment, the evaluation function is assumed to be the investment recovery period U ₁ , and the CGS at which this value is minimized
Although 100 designs and controls are performed, the present invention is not limited to this, and the following evaluation functions may be used.

(A) The evaluation function is defined as the primary energy consumption U
_{As 2} , the design and control of the CGS 100 that minimizes this value may be performed.

U ₂ = c ₁ × _ds + c ₂ × _gs Here, c ₁ and c ₂ are coefficients for converting the purchased amount of electric power and city gas into primary energy, respectively.
x _ds and x _gs are the purchase amounts of electric power and gas, respectively.

(B) Assuming that the evaluation function is a CO ₂ emission amount U ₃
The design and control of the CGS 100 that minimizes this value may be performed.

U ₃ = c ₃ × _ds + c ₄ × _gs Here, c ₃ and c ₄ are coefficients for converting the purchase amount of the electric power and the city gas into the CO ₂ emission amount, respectively, and x _ds ,
x _gs is the purchase amount of power and gas, respectively.

(C) Further, the evaluation function U is represented by a linear combination of the evaluation functions U1, U2, and U3 as expressed by the following equation, and the weighting coefficients k ₁ , k ₂ , and k ₃ are freely selected. Thus, the design and control of the CGS 100 having the desired performance may be performed.

U = k ₁ U ₁ + k ₁ U ₂ + k ₁ U ₃

In the present embodiment, the program data of the CGS control process shown in FIG. 2 is stored in the CD-ROM 17a. However, the present invention is not limited to this, and the present invention is not limited to this.
It may be stored in various recording media such as an optical disk such as RW, DVD, and MO, or a recording medium of a magneto-optical disk, or a recording medium of a magnetic disk such as a floppy disk. These recording media are computer-readable recording media. Further, the CGS control process may be executed by storing the program data of the control process of FIG. 2 in the ROM 11 or another memory in advance.

<Effects of First Embodiment> As described above, the present embodiment has the following unique effects. (1) An optimum system design condition can be calculated under a desired evaluation function and under a predetermined operating condition. Here, as the evaluation function, not only economy but also evaluation functions such as energy efficiency and environmental friendliness can be used, so that an optimal design of the CGS 100 can be performed and operation control can be performed under optimal conditions. (2) The CGS 100 can be optimally designed and its operation can be controlled by using a plurality of devices by dividing the number of devices, load conditions where cooling / heating demands are simultaneously present, and initial costs as variables. (3) Therefore, under operating conditions irrelevant to electricity-driven and heat-driven,
In addition, the optimal design of the CGS 100 can be performed and the operation can be controlled under the efficient operation conditions by the equal division or the non-equal division of the cooling / heating device.

<Supplementary Explanation of Terms> First, the maintenance cost (maintenance cost) of the CGS will be described. The maintenance cost is also called the maintenance and repair cost difference, and as shown below, CGS maintenance goes around for several years,
It is defined as the difference between the average annual cost and the general method. (1) Standard inspection and maintenance costs: These are the periodic maintenance costs and parts replacement costs performed with the CGS manufacturing company. Since the cycle is several years, the total of these is taken as the annual average. (2) Denitration and consumables: Replacement of equipment necessary for denitration and production of pure water, water treatment, chemicals and lubricating oil are anticipated. (3) Maintenance costs: Estimate the necessary personnel costs when conducting daily inspections or by appointing a chief engineer of a boiler / turbine.

Next, an index for evaluating economic efficiency will be described. The economics of CGS are evaluated based on running costs and initial costs. Typical economic performance indicators include simple recovery years, annual ordinary costs, and life cycle costs. (A) Simple recovery years: Simple recovery years (simple depreciation years)
Is obtained by dividing the capital investment for the conventional system by the introduction of CGS by the annual operating merit as shown in the following equation, and does not take into account factors such as interest rates. It is the most frequently used index from the initial planning stage because it is simple and excellent in qualitative comparison. However, it is not a suitable indicator for long-term quantitative economic evaluation corresponding to the useful life of equipment and buildings. When assessing the economics of CGS based on simple recovery years, generally 3 to 5 simple recovery years are used for commercial buildings.
Within a year can be considered as a guideline for CGS introduction decision-making.

[0094]

52] Simple recovery years = {(initial cost of cogeneration system) − (initial cost of conventional system)} / {(running cost of conventional system) − (running cost of cogeneration system)}

(B) Annual ordinary expenses: Annual ordinary expenses are obtained by adding fixed costs to running costs. The fixed cost is obtained by converting the initial cost into an amount per year in consideration of a useful life, an interest rate, and the like, and is calculated by the following equation.

[0096]

[Expression 53] PT = C ｛(1 + Ar ′) × ｛i (1 + i)
^t / (1 + i) ^t-1 {+ {Ar (1-S / C)} / (1-
^t {(S / C)) × t}

Here, PT is a fixed cost (yen / year), C is an equipment cost (yen), A is a ratio (evaluation rate) obtained by dividing the evaluation value of the equipment for tax and insurance premium by the equipment cost (evaluation rate), and S is the remaining Price (yen),
i is the interest rate, t is the useful life, and r and r 'are the insurance rate and tax rate, respectively. Annual recurring expenses are the simplest indicator to assess the long-term economic benefits.

(C) Life cycle cost (LCC):
Life cycle cost is a long-term economic indicator that has recently attracted attention as an alternative to annual ordinary costs.It also takes into account the rise in planning, design, and construction costs, taking into account the rise in interest rates, prices, and energy unit prices. Evaluate in consideration of all management, repair, insurance and disposal costs. Without detailed cost data such as accurate cost and quantity, accuracy cannot be obtained, and there are many factors to consider, making calculation difficult to understand. Therefore, it has been regarded as an index that is difficult to estimate at the planning and early design stages. However, the life cycle cost is an index capable of more appropriately evaluating the merit of the operating cost due to energy saving, and is significant in that it presents a quantitative economic effect to the customer.
The concept of trial calculation is shown below.

[0099]

(Equation 54)

Here, LCC is life cycle cost,
C _e is the initial cost of planning, design and construction, F _p is the present value conversion rate = 1 / (1 + i) ⁿ , C _R is the cost of repairing and renewing parts during the life of the building, and C _oj is the year in the jth fiscal year Operating cost (base annualized), I _oj is the inflation rate (increase rate of interest) in fiscal j, C _mj
Is the annual maintenance cost for the jth year in base year conversion, S is the disposal cost or residual value, and i is the interest.

<Second Embodiment> In the second embodiment, in the CGS of the first embodiment, a gas engine 31, a heat pump 30, and a waste heat absorption chiller (A
R) 32 (used as an air conditioner) in a partial load state (a state in which the maximum rated output is not output and the output is partially output at a predetermined partial load ratio). The optimal design, control, and operation of the CGS are performed in consideration of the state of the performance change, that is, in consideration of the partial load characteristics. In the first embodiment, since the vehicle is operated in the normal partial load state designed based on the maximum load,
The better this property is, the more important in energy saving. For example, when the output capacity of the generator is divided into 100 kW and two units, if there is a demand of 150 kW at a certain time, 1
100kW for the second unit and 50kW for the second unit,
The energy consumption will differ depending on whether the two units share 75 kW. This is because the power generation efficiency varies depending on the partial load factor of the generator. In the second embodiment according to the present invention, an optimum design is performed in consideration of the partial load factor. Hereinafter, matters different from the first embodiment will be described in detail.

First, the calculation conditions will be described. When the building power and the cooling and heating loads are covered only by power (Fig. 4
Compared to (comparison model), when the gas engine generator is used and the electric power and its exhaust heat are used, economy can be expected. Here, the following conditions are assumed, and the payback period of the investment (increase in initial cost 減少 decrease in annual running cost)
A CGS design method that minimizes the following will be described.

(1) Disposal of exhaust heat and surplus power generation in the gas engine generator (GE) 31 are permitted. (2) Consider the partial load factor of each of the energy conversion devices 30, 31, and 32. (3) The device cost of the energy conversion device uses an approximate expression based on the real price. (4) Cooling / heating machine using electric power (heat pump (HP)) 3
0 and the exhaust heat utilization absorption air conditioner (AR) 32 are limited to use only for cooling or heating on a monthly basis. (5) Consider even number division of the exhaust heat utilization absorption air conditioner (AR) 32 and the heat pump 30.

Next, various data will be described.
Monthly average power load (k
W), cooling load (kW), and heating load (kW) are d _d (m, h), d _c (m, h), and d _w (m, h), respectively.

Gas engine (GE) having city gas input capacity x _g and maximum input capacity x _gm = Max [x _g ]
31, the power generation efficiency is η _gd , the power generation partial load factor is F _gd , the exhaust heat recovery capacity is η _gl , and the initial cost (device price and construction cost)
The when the G _g, power generation partial load factor F _gd and initial cost G _g is assumed to be given by the following equation.

[0106]

F _gd (x _g / x _gm ) = a _ge (x _g / x _gm ) + b _ge

G _g (η _gd x _gm ) = 380 η _gd x _gm −3.1
(Η _gd x _gm ) ^1.5

Also, the exhaust heat input capacity x _a , the maximum input capacity x
_In an exhaust heat absorption refrigerator (AR) 32 having an _am
It is assumed that the cooling efficiency η _ac , the heating efficiency η _aw , and the initial cost G _a . At this time, the initial cost G _a is given by the following equation.

[0108]

G _a (η _ac x _am ) = 14000 + 21.5η _ac x _am

The cooling efficiency of the heat pump (HP) 30 having the power input capacity x _h and the maximum input capacity x _hm is η _hc , the partial load factor during cooling is F _hc , the heating efficiency is η _hw , and the initial cost is G _h. Then, the partial load factor F _hc and the initial cost G _h during cooling are given by the following equations.

[0110]

F _hc (x _h / x _hm ) = a _hp (x _h / x _hm ) + b _hp

G _h (η _hc x _hm ) = 120 η _hc x _hm −20
(Η _hc x _hm ) ^1.1

The coefficients on the right side for calculating the left side of Equations 55 to 59 are stored in the parameter memory 13 in advance.

Next, the formulas for calculating the electricity and city gas rates will be described. X is the peak value of purchased power per hour
_dm , and if the integrated value for one year is x _ds , the electricity rate for one year is

The [number 60] _{c dp x dm + c ds x} ds. Here, _cdp and _cds are a basic electricity charge and an electricity-based charge, respectively. _Assuming that the peak value of the purchased gas amount per hour is x _gm and the integrated value for one year is x _gs , the annual electricity rate is

It can be expressed by c _gb + c _gp x _gm + c _gs x _gs . Here, c _gb , c _gp , and c _gs are a gas fixed-rate basic charge, a gas-based basic rate, and a gas-based rate, respectively. Total running cost x
_rc is given by the following equation.

[Number 62] _{x rc = c dp x dm +} c ds x ds + c gb + c gp x gm
+ C _gs x _gs

Next, the CGS model will be described. Here, the purchased power amount x _d (m, h), the purchased gas amount x _g (m, h), the input heat energy x _ac (m, h) to the AR 32 for cooling and heating, x _aw (m, h) h), the input power to the HP 30 for cooling and heating x _hc (m,
_{h), x hw (m,} h), the excess power z _d (m, h), the excess heat z _t (m, h), the maximum input capacity per one AR32 and HP30 x _am, x _hm, Zero or positive variable. Here, AR32 and HP30 of number division number of each n _a, and n _h. At this time, the following relationship is established between the inputs and outputs of the devices 32 and 30. In the following, (m, h),
(M) is omitted.

[0114]

[Equation 63] Energy of electric power: x _d −z _d = d _d + x _hc + x _hw −η _gd F _gd (x _g / x _gm ) x
_gm

[Number 64] GE31 waste heat output _{of: η gt x g = x ac} + x aw + z t

[ _Equation 65] Heating load: η _aw x _aw + η _hw x _hw = d _w

[Equation 66] Cooling load: η _ac x _ac + η _hc ｛Int [x _hc / x _hm ] + F _hc (Sur
[X _hc / x _hm ])｝ x _hm = d _c

Here, the function Int [•] is a function indicating only the integer part of the argument, and the function Sur [•] is a function indicating the fractional part by truncating the integer part of the argument. Less than,
The same is true.

Next, the calculation of the maximum input capacity of the HP 30 will be described. The required input capacity x _hm (m) after the distribution of the number of units for cooling and heating for m months is given by the following equation.

[0117]

When x _hw = 0: x _hm (m) = x _hc / n _h

When x _hc = 0: x _hm (m) = x _hw / n _h

[Equation 69] At other times:

Here, the function Min is a function indicating the minimum value when the variable shown below is changed, and the function Ma
x is a function indicating the maximum value when changing the variables shown below. Therefore, the required input capacity x _hm throughout the year
Is given by the following equation.

[0119]

[Equation 70]

The required capacity of the AR 32 is similarly obtained. The initial cost _{xic at} this time is as follows.

[0121]

X _ic = G _g (η _gd x _gm ) + G _a (η _ac x _am ) n
_a + G _h (η _hc x _hm ) n _h

From the initial cost y _ic and running cost y _{rc of} the comparative model using only electric power without using city gas, the investment recovery period U as an evaluation function is as follows.

[0123]

Equation 72] _{U = (x ic -y ic)} / (y rc -x rc)

Further, preparation for optimization calculation will be described. From the input powers x _hc and x _hw to the HP 30 for cooling and heating, the input heat energies x _ac and x _aw to the AR 32 for cooling and heating are obtained by the following equations.

[0125]

X _aw = (d _w / η _aw ) − (η _hw / η _aw ) x _hw

X _ac = (d _c / η _ac ) − (η _hc / η _ac ) {Int
[x _hc / x _hm ] + F _hc (Sur [x _hc / x _hm ])} x _hm

Further, the purchased gas amount x _g and (the purchased electric power amount x _d ) − (the surplus exhaust heat amount z _d ) are obtained from the following equations.

[0127]

X _g = (x _a + z _t ) / η _gt

X _d -z _d = d _d + x _h -η _gd F _gd (x _g / x _gm ) x _gm

Here, all variables are zero or a positive number. From economic (minimizing the power to be discarded) condition, z _d = 0 when the right side of Equation 76 is positive, and when the right side is negative, x _d
= 0. Here, the range in which the variables x _hc and x _hw can be changed is as follows.

[0129]

0 ≦ x _hw ≦ (d _w / η _hw )

[ _Expression 78] 0 ≦ x _hc ≦ [(d _c / η _hc ) − ｛n _hc (1−
a _hp ) + b _hp ｝ x _hm ] / a _hp where

[ _Expression 79] n _hc = Int [x _hc / x _hm ]

Further, the fineness of the Hamiltonian algorithm
A method for calculating the coefficient will be described. Hamiltonian Al
In Gorism, you exercise virtually with the force received from the evaluation function.
You. This force is obtained by partially differentiating the evaluation function with a variable. This
Here, the variable to be changed is x _hc, X_hw, Z_tIt is.

First, the derivative of x _hc will be described below.

[0132]

８０U / ∂x _hc = c1 / (y _rc −x _rc )｝ (∂
_{x ic / ∂x hc) + {} (x ic -y ic) / (y rc -
x _rc ) ² ｝ (∂x _rc / ∂x _hc )

８１x _ic / ∂x _hc = (∂G _g / ∂x _g ) (∂x _g
/ ∂x _ac ) (∂x _ac / ∂x _hc ) + n _a (∂G _a / ∂x _ac )
(∂x _ac / ∂x _hc ) + n _h (∂G _h / ∂x _hc )

８２G _g / ∂x _g = (380η _gt -4.65η _gt)
^1.5 √ (x _gm ) True [x _g = x _gm ]

８３x _g / ∂x _ac = 1 / η _gt

８４G _a / ∂x _ac = 21.5η _ac True [x _ac → x _am ]

[Equation 85] ∂x _ac / ∂x _hc = −η _hc a _hp / η _ac

８６G _h / ∂x _hc = η _hc ｛120−22 (η _hc
x _hm ) ^0.1 ｝ True [x _hc → x _hm ]

８７x _rc / ∂x _hc = (∂ / ∂x _d ) (c _{dp xdm}
+ C _ds x _ds ) (∂x _d / ∂x _hc ) + (∂ / ∂x _g ) (c _gb +
c _gp x _gm + c _gs x _gs ) × (∂x _g / ∂x _ac ) (∂x _ac / ∂x
_hc )

In Expression 84, True [x _ac → x
_am ], among the number of convergence calculations performed in one operation, the value of a variable that can be taken in one convergence calculation is x _ac >
For x _am true (ie 1), and is false when the x _ac ≦ x _am (i.e. 0) function. In _Expression 86, True [x _hc → x _hm ] is a similar function.

[0134]

８８ (c _dp x _dm + c _ds x _ds ) / ∂x _d = c _dp T
rue [x _d = x _dm ] + c _ds

[Number 89] _{∂ (c gb + c gp x} gm + c gs x gs) / ∂x g =
_cgpTrue [ _xg = _xgm ] + _cgs

９０x _d / ∂x _hc = 1−η _gd ( _age + _bgeTr)
ue [x _g = x _gm ]) × (∂x _g / ∂x _ac ) (∂x _ac / ∂
x _hc ), when x _d > 0

９１x _d / ∂x _hc = 0, when x _d = 0

Next, the derivative of x _hw is shown below.

[0136]

９２U / ∂x _hw = ∂1 / (y _rc −x _rc )｝ (∂
_{x ic / ∂x hw) + {} (x ic -y ic) / (y rc -
x _rc ) ² ｝ (∂x _rc / ∂x _hw )

９３x _ic / ∂x _hw = (∂G _g / ∂x _g ) (∂x _g
/ ∂x _aw ) (∂x _aw / ∂x _hw ) + n _a (∂G _a / ∂x _aw )
(∂x _aw / ∂x _hw ) + n _h (∂G _h / ∂x _hw )

数 x _g / ∂x _aw = 1 / η _gt

９５x _aw / ∂x _hw = −η _hw / η _aw

９６G _a / ∂x _aw = 21.5 μ _ac True [x _aw → x _am ]

９７x _aw / ∂x _hw = −η _hw / η _aw

９８G _h / ∂x _hw = η _hc ｛120-22 (η _hc
x _hm ) ^0.1 ｝ True [x _hw → x _hm ]

９９x _rc / ∂x _hw = (∂ / ∂x _d ) (c _dp x _dm
+ C _ds x _ds ) (∂x _d / ∂x _hw ) + (∂ / ∂x _g ) (c _gb
+ C _gp x _gm + c _gs x _gs ) × (∂x _g / ∂x _aw ) (∂x _aw
/ ∂x _hw )

[Equation 100] (∂ / ｃx _d ) (c _dp x _dm + c _ds x _ds ) =
_cdpTrue [ _xd = _xdm ] + _cds

(∂ / ∂x _g ) (c _gb + c _gp x _gm + c _gs x
_gs ) = _cgpTrue [ _xg = _xgm ] + _cgs

１０２x _d / ∂x _hw = 1−η _gd ( _age + _bgeT)
rue [x _g = x _gm ]) × (∂x _g / ∂x _aw ) (∂x _aw /
∂x _hw ), when x _d > 0

１０３x _d / ∂x _hw = 0, x _d = 0

Further, the expression of the differential coefficient of z _t is shown below.

[0138]

{U / {z _t = {1 / (y _rc −x _rc )}}
_{(∂x ic / ∂z t) +} {(x ic -y ic) / (y rc -
x _rc ) ² ) (∂x _rc / ∂z _t )

[Number 105] _{∂x ic / ∂z t = (∂G} g / ∂x g) (∂x g / ∂z t)

数_{x g} / ∂z _t = 1 / η _gl

１０７x _rc / ∂z _t = (∂ / ∂x _d ) (c _dp x _dm
+ C _ds x _ds ) (∂x _d / ∂z _t ) + (∂ / ∂x _g ) (c <sub>gb
+ C gp x gm + c gs</sub> x gs) (∂x g / ∂z t)

[Number 108] _{∂x d / ∂z t = -η gd} (a ge + b ge Tru
e [x _g = x _gm ]) (∂x _g / ∂z _t ), when x _d > 0

１０９x _d / ∂z _t = 0, x _d = 0

Further, the coefficients of the approximate expression of the partial load factor are shown below.

(A) Coefficient for gas engine (GE) 31

When 0.00 ≦ x <0.25: a _ge = 0.65, b _ge = 0.00

When 0.25 ≦ x <0.50: a _ge = 1.01, b _ge = −0.09

When 0.50 ≦ x <0.75: a _ge = 1.19, b _ge = −0.18

When 0.75 ≦ x ≦ 1.00: a _ge = 1.15, b _ge −0.15

(B) Coefficient for heat pump (HP) 30

When 0.0 ≦ x <0.2: a _hp = 0.25, b _hp = 0.00

When 0.2 ≦ x <0.4: a _hp = 1.75, b _hp = −0.30

When 0.4 ≦ x <0.6: a _hp = 1.20, b _hp = −0.08

When 0.6 ≦ x <0.8: a _hp = 1.00, b _hp = 0.04

When 0.8 ≦ x ≦ 1.0: a _hp = 0.80, b _hp = 0.20

In the second embodiment, as compared with the first embodiment, the control device shown in FIG. The control process of CGS 2 is executed. That is, in FIG. 2, it is first determined in step S1 whether or not an input parameter has been input (interrupt processing). If YES, an evaluation is made in step S2 to minimize the investment recovery year U shown in Expression 72. Variables and output parameters are calculated using a Hamiltonian algorithm based on functions and stored in the variable and output parameter memory 42. In this embodiment,
Variables and output parameters are calculated by using a well-known Hamiltonian algorithm so that the function value of the evaluation function of Expression 72 is minimized. Next, in step S3, the calculated variables and output parameters are displayed on the CRT display 15.
And print it using the printer 16.
In step S4, each device of the CGS 100 is controlled and operated so that the calculated output parameter value is obtained. In the operation control processing of step S4, specifically,
The GE 31 is controlled so that the calculated purchased gas amount x _g (m, h) and the power generation partial load factor F _gd are obtained, and A for cooling is used.
The AR 32 is controlled so that the R input heat quantity x _ac (m, h) and the AR input heat quantity x _aw (m, h) for heating, the HP input power x _hc (m, h) for cooling and the heating Control by controlling the HP 30 so that the HP input power x _hw (m, h) and the partial load factor F _hc during cooling are maintained. It can be performed.

It should be noted that the evaluation function used in the second embodiment is not limited to the investment payback period of Equation 72, but may be another evaluation function shown in the first embodiment.

As described above, according to the present embodiment, in addition to the functions and effects of the first embodiment, each energy conversion device including the gas engine 31, the heat pump 30, and the exhaust heat absorption absorption refrigerator 32 is provided. The partial load factor of each energy conversion device is calculated and controlled in consideration of the partial load characteristics of the above, so that each energy conversion device can be operated more efficiently, and the economical efficiency of the entire CGS,
It can be optimally designed and operated in consideration of energy efficiency, environmental friendliness, etc.

<Third Embodiment> FIG. 20 shows a cogeneration system (CG) according to the first or second embodiment.
It is a block diagram showing composition of building energy system 200 concerning a 3rd embodiment including S), and shows composition of a building energy system which covered all the design control objects of the present invention. The control device of this system includes a control device similar to the control device of FIG. 1 according to the first or second embodiment, and is characterized in that the control device is applied to the system of FIG. In FIG. 20, L2 is a cooling load instead of the cooling load.

In FIG. 20, the power energy supplied from the power supply source EP is the power load L 1 and the electric heat source 5.
2, and the ice making heat source 53a. Fuel energy supplied from a fuel supply source UG such as city gas such as natural gas or oil is supplied from a generator 51 and a fuel-type cold / hot water generator 5
5. It is supplied to the gas heat pump 56 and the fuel boiler 57. The generator 51 includes, for example, a gas engine, a gas turbine, a fuel cell, a diesel engine, and the like, converts supplied fuel energy into electric energy, and converts the converted electric energy or waste heat energy into an electric power load L.
1. In addition to the electric heat source 52 and the ice making heat source 53a,
The heat is supplied to the exhaust heat utilization device 54, the heating load L3, and the hot water supply load L4. Here, the generator 51, the electric heat source 52, the ice making heat source 53a and the heat storage tank 53b, the exhaust heat utilization device 54, the fuel type cold / hot water generator 55, the gas heat pump 56, and the fuel type boiler 57 are all energy conversion devices. is there. The electric energy from the power supply source EP or the generator 51 may be supplied as auxiliary machine power energy to each of the devices 52 to 57 of the energy conversion device.

The electric heat source 52 includes, for example, a heat pump, a centrifugal chiller, a screw chiller, etc., and converts supplied electric energy into cold energy or heating energy and supplies it to the cold load L2 and the heating load L3. Further, the ice making heat source 53a includes, for example, a brine (antifreeze) heat pump, a brine / centrifugal chiller, etc., and uses the supplied electric energy to make ice and make the cold energy of ice, for example, into an ice storage tank, a water storage tank, or the like. After the heat is stored in the heat storage tank 53b including the tank, the heat is supplied to the cooling load L2, and the cooling energy or heating energy of the ice is directly supplied to the cooling load L2 and the heating load L3. Further, the exhaust heat utilization machine 54 includes, for example, an exhaust heat utilization type refrigerator, converts the exhaust heat energy from the generator 51 into cold energy and supplies it to the cold load L2. The fuel-type cold / hot water generator 55 generates cold water or hot water using supplied fuel such as city gas or petroleum, and supplies the cold water or hot water to the cooling / heating load L2 and the heating load L3. Further, the gas heat pump 56 generates cold energy and heating energy by using the supplied city gas to generate a cold load L, respectively.
2 and the heating load L3. Further, the fuel-type boiler 57 boiles hot water using fuel such as city gas or oil, and supplies it to the heating load L3 and the hot water supply load L4.

In FIG. 20, a power load L1 includes various electric devices in a building, and a cooling load L2 includes a cooling load such as a refrigerator or an air conditioner that requires cooling energy in the building. Further, the heating load L3 and the hot water supply load L4 are also collectively called a thermal load. Here, the heating load is, for example, a heat source for air conditioning. The hot water supply load L4 has, for example, a hot water supply load for the following applications. (A) a heat source for air conditioning, (b) a heat source for hot water supply, (c) a heat source for snow melting, (d) a heat source for a hot water pool, (e) a heat source for cooking, (f) a heat source for washing, ( g) For example, a heat source for sterilization and disinfection in hospitals and the like, and (h) a heat source for factories.

Also in the building energy system of FIG. 20 according to the third embodiment, similarly to the control device of the cogeneration system (CGS) in the first or second embodiment, the power supply source EP and the fuel supply source UG are used. Based on the energy supplied from at least one of the above, the supplied energy is converted into another predetermined energy using at least one energy conversion device, and the converted energy is converted into the power load L1. Cooling load L
2 and the building energy system for supplying to at least one of the thermal loads L3 and L4 are controlled to have an optimum configuration using the above-described predetermined evaluation function. Here, the power load amount of the power load L1 and the cooling load L2
, And at least one of the thermal loads of the thermal loads L3 and L4, the number of divided energy converters, the conversion efficiency of the energy converter, the conversion efficiency and the maximum input capacity of the energy converter, and the initials. Input parameters including the relationship between the cost, the energy rate data of the energy conversion device, the maintenance cost of the building energy system, and the initial cost and running cost of the energy supply system to be compared are input using, for example, the keyboard 14. Then, it is stored in the parameter memory 13. Next, the CPU of the control device of FIG.
The CPU similar to 10 uses the above-described predetermined Hamiltonian algorithm based on the input parameters stored in the parameter memory 13 so that the function value of the evaluation function is minimized or maximized. The amount of input energy, the amount of waste energy from the energy conversion device, and the output capacity of the energy conversion device,
Variables and output parameters including the initial cost and the running cost of the building energy system are calculated and output. Further, by controlling the energy conversion device so as to be the calculated input energy amount,
The operation is performed while maintaining the calculated optimum design conditions.

As described above, according to the present embodiment,
It has the following unique effects. (1) An optimum system design condition can be calculated under a desired evaluation function and under a predetermined operating condition. Here, as the evaluation function, not only economic efficiency, but also evaluation functions such as energy efficiency and environmental friendliness can be used, so that an optimum design of a building energy system can be performed, and operation control can be performed under optimum conditions. it can. (2) It is possible to optimally design and control the operation of the building energy system by using a plurality of devices by dividing the number of devices, load conditions where cooling / heating demands are simultaneously present, and initial costs as variables. (3) Therefore, under operating conditions irrelevant to electricity-driven and heat-driven,
In addition, the optimum design of the building energy system can be performed and the operation can be controlled under the efficient operation condition by the equal division or the uneven division of the cooling and heating device. (4) Further, since the partial load factor of each energy conversion device is calculated and controlled in consideration of the partial load characteristics of the energy conversion device, each energy conversion device can be operated more efficiently. It can be optimally designed and operated in consideration of the economics, energy efficiency, environment, etc. of the whole building energy system.

[0151]

As described above in detail, according to the control method or apparatus for a building energy system according to the present invention, at least one of a power supply source and a fuel supply source can be used based on energy supplied from at least one of a power supply source and a fuel supply source. A building for converting the supplied energy into another predetermined energy by using one energy conversion means and supplying the converted energy to at least one of a power load, a cooling load, and a heating load. In the energy system, a control method of a building energy system for controlling to an optimum configuration using a predetermined evaluation function, wherein the power load of the power load, the cooling load of the cooling load, and the heating load of the heating load. At least one of the thermal loads, the number of divided devices of the energy conversion means, and the conversion efficiency of the energy conversion means. The relationship between conversion efficiency and maximum input capacity and initial cost of the energy conversion means,
Inputting input parameters including the energy rate data of the energy conversion means, the maintenance cost of the building energy system, and the initial cost and running cost of the energy supply system to be compared,
The input parameters stored in the storage means, based on the input parameters stored in the storage means, using a predetermined Hamiltonian algorithm, so that the function value of the evaluation function is minimum or maximum, Calculate variables and output parameters including the amount of input energy to the energy conversion means, the amount of waste energy from the energy conversion means, the output capacity of the energy conversion means, and the initial and running costs of the building energy system. And output. Then, by controlling each of the energy conversion means so as to have the calculated input energy amount, the operation is performed while maintaining the calculated optimum design condition.

Therefore, according to the present invention, the following specific effects are obtained. (1) An optimum system design condition can be calculated under a desired evaluation function and under a predetermined operating condition. Here, as the evaluation function, not only economic efficiency, but also evaluation functions such as energy efficiency and environmental friendliness can be used, so that an optimum design of a building energy system can be performed, and operation control can be performed under optimum conditions. it can. (2) It is possible to optimally design and control the operation of the building energy system by using a plurality of devices by dividing the number of devices, load conditions where cooling / heating demands are simultaneously present, and initial costs as variables. (3) Therefore, under operating conditions irrelevant to electricity-driven and heat-driven,
In addition, the optimum design of the building energy system can be performed and the operation can be controlled under the efficient operation condition by the equal division or the uneven division of the cooling and heating device. (4) Further, since the partial load factor of each energy conversion device is calculated and controlled in consideration of the partial load characteristics of the energy conversion device, each energy conversion device can be operated more efficiently. It is possible to design and operate the building energy system optimally in consideration of the economy, energy efficiency, environment, etc. of the whole building energy system.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a configuration of a control device of a cogeneration system (CGS) according to a first embodiment of the present invention.

FIG. 2 is a flowchart showing a CGS control process executed by the control device of the cogeneration system of FIG.

FIG. 3 is a block diagram illustrating a configuration of a CGS model according to the first embodiment.

FIG. 4 is a block diagram illustrating a configuration of a comparative model of a comparative example.

FIG. 5 is a graph showing power load data for each month and each time used in the simulation of the first embodiment.

FIG. 6 is a graph showing cooling load data for each month and for each time used in the simulation of the first embodiment.

FIG. 7 is a graph showing heating load data for each month and for each time used in the simulation of the first embodiment.

FIG. 8 is a graph showing a cost of a gas engine (GE) with respect to a power generation capacity used in the simulation of the first embodiment.

FIG. 9 shows an exhaust-heat-utilization absorption refrigerator (A) for cooling capacity, which is used in the simulation of the first embodiment.
It is a graph which shows the cost of R).

FIG. 10 is a graph showing the cost of the heat pump (HP) with respect to the cooling capacity used in the simulation of the first embodiment.

FIG. 11 is a graph showing a minimum investment recovery year with respect to the number of divided heat pumps (HP), which is a simulation result of the first embodiment.

FIG. 12 is a graph showing initial costs as a simulation result of the first embodiment, when the investment recovery years with respect to the number of divided heat pumps (HP) are minimum.

FIG. 13 is a graph showing the running cost when the payback period for the number of divided heat pumps (HP) is minimum, which is the simulation result of the first embodiment.

FIG. 14 is a graph showing the waste heat amount when the investment recovery years with respect to the number of divided heat pumps (HP) is the minimum, which is a simulation result of the first embodiment.

FIG. 15 is a graph showing the initial cost of the gas engine (GE) with respect to the number of divided heat pumps (HP), which is a simulation result of the first embodiment.

FIG. 16 is a graph showing the initial cost of the exhaust heat utilization type absorption refrigerator (AR) with respect to the number of divided heat pumps (HP), which is a simulation result of the first embodiment.

FIG. 17 is a graph showing the initial cost of the heat pump (HP) with respect to the number of divided heat pumps (HP), which is a simulation result of the first embodiment.

FIG. 18 is a graph showing a simulation result of the first embodiment, showing a running cost of electric power with respect to the number of divided heat pumps (HP).

FIG. 19 is a graph showing a simulation result of the first embodiment, showing the running cost of city gas including the maintenance cost of the cogeneration system (CGS) with respect to the number of divided heat pumps (HP).

FIG. 20 is a block diagram showing a configuration of a building energy system 200 according to a third embodiment including the cogeneration system (CGS) of the first or second embodiment.

[Explanation of symbols]

 10 CPU, 11 ROM, 12 RAM, 13 parameter memory, 14 keyboard, 15 CRT display, 16 printer, 17 CD-ROM drive, 18 CD-ROM, 20 bus, 21 Keyboard interface, 22 ... Display interface, 23 ... Printer interface, 24 ... Control interface, 25 ... Drive device interface, 30 ... Heat pump (HP), 31 ... Gas engine (GE), 32 ... Exhaust heat utilization absorption refrigerator (AR) ), 41: input parameter memory, 42: variable and output parameter memory, 43: evaluation function memory, 51: generator, 52: electric heat source, 53a: ice making heat source, 53b: heat storage tank, 54: exhaust heat utilization machine , 55 ... Fuel type cold / hot water generator, 5 ... gas heat pump, 57 ... fuel boiler, 100 ... cogeneration system (CGS), 200 ... building energy system, EP ... power supply source, UG ... city gas supply source, UG '... fuel supply source, L1 ... power load, L2: cooling load or cooling load; L3: heating load; L4: hot water supply load.

──────────────────────────────────────────────────続 き Continued on the front page (51) Int.Cl. ⁷ Identification symbol FI Theme coat ゛ (Reference) G05B 13/02 G05B 13/02 K (72) Inventor Masahide Yanagi 3-4-1 Shibaura, Minato-ku, Tokyo Inside NTT Facilities Co., Ltd. (72) Inventor Tsuneo Uekusa 3-4-1, Shibaura, Minato-ku, Tokyo Inside NTT Facilities Co., Ltd. (72) Inventor Kazumasa Shinkami Seika-cho, Soraku-gun, Kyoto Prefecture Daikan Inaya, 5 Sanhiradani, A.T.R. Co., Ltd. Environmentally Friendly Communication Research Laboratories (72) Inventor Junichi Yamada Kyoto, Soraku-gun, Seikacho Communication Research Laboratory

Claims (23)

[Claims] 1. An energy conversion unit that converts at least one energy supply into a predetermined energy based on energy supplied from at least one of a power supply source and a fuel supply source. Then, in a building energy system for supplying the converted energy to at least one of an electric load, a cooling load, and a heating load, a building energy that is controlled to have an optimal configuration using a predetermined evaluation function. A method of controlling a system, comprising: at least one of a power load amount of the power load, a cold load amount of the cold load, and a thermal load amount of the warm load; Relationship between the conversion efficiency of the conversion means, the conversion efficiency of the energy conversion means and the maximum input capacity and initial cost Inputting input parameters including energy charge data of the energy conversion means, maintenance cost of the building energy system, and initial cost and running cost of the energy supply system to be compared; and Storing in the storage means, based on the input parameters stored in the storage means,
Using a predetermined Hamiltonian algorithm, the input energy amount to the energy conversion means, the waste energy amount from the energy conversion means, and the energy conversion means so that the function value of the evaluation function is minimum or maximum. And calculating and outputting a variable and an output parameter including an output capacity of the building energy system and an initial cost and a running cost of the building energy system. 2. A method for converting the supplied energy into another predetermined energy using a plurality of energy converting means based on energy supplied from at least one of a power supply source and a fuel supply source. A building energy system for supplying converted energy to at least one of a power load, a cooling load, and a heating load, wherein the building energy system controls to have an optimum configuration using a predetermined evaluation function. The power load of the power load, the cooling load of the cooling load, and at least one of the heating loads of the heating load, the number of divided devices of the energy conversion means, The conversion efficiency of the energy conversion means, and the relationship between the conversion efficiency and the maximum input capacity of each energy conversion means and the initial cost, The relationship between the input energy amount and the maximum input capacity of each energy conversion means and the partial load factor, the energy rate data of each energy conversion means, the maintenance cost of the building energy system, and the energy supply system to be compared. Inputting an input parameter including an initial cost and a running cost of the input parameter, storing the input parameter in a storage unit, based on the input parameter stored in the storage unit,
Using a predetermined Hamiltonian algorithm, the amount of input energy to each of the energy conversion means, the amount of waste energy from each of the energy conversion means, and the Calculating and outputting variables and output parameters including an output capacity of the energy conversion means, a partial load factor of each of the energy conversion means, and an initial cost and a running cost of the building energy system. Control method of building energy system. 3. Supplying energy to a power load, a cooling load, and a heating load by using a gas engine, a heat pump, and an absorption refrigerator utilizing waste heat based on energy from a power supply source and a city gas supply source. In a building energy system including a co-generation system for controlling the building energy system, a control method for controlling the building energy system to have an optimal configuration using a predetermined evaluation function is provided. And the amount of input energy, including the gas engine equipment price, the heat pump equipment price, the exhaust heat absorption chiller equipment price, the number of exhaust heat absorption chillers, the number of heat pumps,
Inputting input parameters including power rate data, gas rate data, maintenance cost of the building energy system, and initial cost and running cost of the energy supply system to be compared; storing the input parameters input Storing in the means, based on the input parameters stored in the storage means,
Using a predetermined Hamilton algorithm, so that the function value of the evaluation function is minimized, the purchased power amount, the maximum value of the purchased power amount, the purchased gas amount, the maximum value of the purchased gas amount,
The amount of heat input to the waste heat absorption refrigerator for cooling, the amount of heat input to the waste heat absorption refrigerator for heating, the amount of input power to the heat pump for cooling, and the The amount of power input to the heat pump, the amount of waste power, the amount of waste heat waste, the device capacity of the waste heat absorption chiller, the device capacity of the heat pump, the initial cost and running cost of the building energy system, and A method for controlling a building energy system, comprising: calculating and outputting a variable and an output parameter including a running cost and a gas running cost. 4. The control method for a building energy system according to claim 1, wherein the thermal load includes at least one of a heating load and a hot water supply load. 5. The energy conversion means includes: a generator;
The apparatus according to claim 1, further comprising at least one of an electric heat source, an ice making heat source and a heat storage tank, a waste heat utilization machine, a fuel-type cold / hot water generator, a gas heat pump, and a fuel-type boiler. 5. The method for controlling a building energy system according to 1, 2, or 4. 6. The evaluation function calculates a difference between an initial cost of the building energy system and an initial cost of the energy supply system to be compared with the running cost of the building energy system and the running cost of the energy supply system to be compared. 6. The control method for a building energy system according to claim 1, wherein the investment recovery period is obtained by dividing by a difference from the cost. 7. The building energy system according to claim 1, wherein the evaluation function is an energy consumption represented by a linear combination of the input energy amounts. Control method. 8. The building energy system according to claim 1, wherein the evaluation function is a CO ₂ emission amount represented by a linear combination of the input energy amounts. Control method. 9. The evaluation function is an evaluation function represented by a linear combination of an investment recovery period according to claim 6, an energy consumption amount according to claim 7, and a CO ₂ emission amount according to claim 8. 6. A method according to claim 1, wherein the function is a function.
4. The method for controlling a building energy system according to any one of the above. 10. The method according to claim 1, further comprising the step of controlling each of said energy conversion means so as to obtain said calculated input energy amount, thereby maintaining said calculated optimum design conditions for operation. The method for controlling a building energy system according to claim 1. 11. The gas engine is controlled to have the calculated gas purchase amount, and the exhaust heat absorption refrigeration is to have the calculated input heat amount for cooling and the input heat amount for heating. Controlling the heat pump so that the calculated input power for cooling and the input power for heating become the calculated input power for heating, and thereby performing the operation while maintaining the calculated optimal design conditions. The method according to claim 3, further comprising: 12. The energy supplied from at least one of a power supply source and a fuel supply source is converted into another predetermined energy by using at least one energy conversion means. do it,
In a building energy system for supplying converted energy to at least one of a power load, a cooling load, and a heat load, control of a building energy system that controls to have an optimum configuration using a predetermined evaluation function. An apparatus, wherein at least one of the power load of the power load, the cooling load of the cooling load, and the heating load of the heating load, the number of divided devices of the energy conversion means, and The conversion efficiency, the conversion efficiency of the energy conversion means, the relationship between the maximum input capacity and the initial cost, the energy rate data of the energy conversion means, the maintenance cost of the building energy system, and the energy supply system to be compared. Input parameters including initial cost and running cost Input means for inputting, storage means for storing input parameters input by the input means, and, based on the input parameters stored in the storage means,
Using a predetermined Hamiltonian algorithm, the input energy amount to the energy conversion means, the waste energy amount from the energy conversion means, and the energy conversion means so that the function value of the evaluation function is minimum or maximum. And a calculating means for calculating and outputting variables and output parameters including an output capacity of the building energy system and an initial cost and a running cost of the building energy system. 13. Converting the supplied energy to another predetermined energy using a plurality of energy conversion means based on energy supplied from at least one of a power supply source and a fuel supply source. A building energy system for supplying converted energy to at least one of a power load, a cooling load, and a heating load, wherein the building energy system controls to have an optimum configuration using a predetermined evaluation function. The control device, wherein at least one of the power load amount of the power load, the cooling load amount of the cooling load, and the heating load amount of the heating load, the number of divided devices of each of the energy conversion means, The conversion efficiency of the energy conversion means, and the relationship between the conversion efficiency and the maximum input capacity of each energy conversion means and the initial cost. The relationship between the input energy amount and the maximum input capacity and the partial load factor in each of the energy conversion means, the energy rate data of each of the energy conversion means, the maintenance cost of the building energy system, and the energy supply system to be compared Input means for inputting input parameters including initial costs and running costs of the input means, storage means for storing the input parameters input by the input means, based on the input parameters stored in the storage means,
Using a predetermined Hamiltonian algorithm, the amount of input energy to each of the energy conversion means, the amount of waste energy from each of the energy conversion means, and the Calculation means for calculating and outputting variables and output parameters including an output capacity of the energy conversion means, a partial load factor of each of the energy conversion means, and an initial cost and a running cost of the building energy system. A control device for building energy systems. 14. Energy is supplied to an electric load, a cooling load, and a heating load by using a gas engine, a heat pump, and an exhaust heat absorption absorption refrigerator based on energy from a power supply source and a city gas supply source. A building energy system including a cogeneration system for controlling the building energy system using a predetermined evaluation function to achieve an optimal configuration, comprising: a power load, a cooling load, and a heating load. And the amount of input energy, including the gas engine equipment price, the heat pump equipment price, the exhaust heat absorption chiller equipment price, the number of exhaust heat absorption chillers, the number of heat pumps,
Input means for inputting input parameters including power rate data, gas rate data, maintenance cost of the building energy system, and initial cost and running cost of the energy supply system to be compared; Storage means for storing input parameters, based on the input parameters stored in the storage means,
Using a predetermined Hamilton algorithm, so that the function value of the evaluation function is minimized, the purchased power amount, the maximum value of the purchased power amount, the purchased gas amount, the maximum value of the purchased gas amount,
The amount of heat input to the waste heat absorption refrigerator for cooling, the amount of heat input to the waste heat absorption refrigerator for heating, the amount of input power to the heat pump for cooling, and the The amount of power input to the heat pump, the amount of waste power, the amount of waste heat waste, the device capacity of the waste heat absorption chiller, the device capacity of the heat pump, the initial cost and running cost of the building energy system, and A control device for a building energy system, comprising: calculation means for calculating and outputting a variable including a running cost and a gas running cost and an output parameter. 15. The control device for a building energy system according to claim 12, wherein the thermal load includes at least one of a heating load and a hot water supply load. 16. The energy conversion means includes a generator, an electric heat source, a heat source for ice making and a heat storage tank, a waste heat utilization machine, a fuel-type cold / hot water generator, a gas heat pump, a fuel-type boiler, The control device for a building energy system according to claim 12, 13 or 15, comprising at least one of the following. 17. The evaluation function calculates a difference between an initial cost of the building energy system and an initial cost of the energy supply system to be compared with the running cost of the building energy system and the running cost of the energy supply system to be compared. 17. The control device for a building energy system according to any one of claims 12 to 16, wherein the investment recovery years are obtained by dividing by a difference from the cost. 18. The building energy system according to claim 12, wherein the evaluation function is energy consumption represented by a linear combination of the input energy amounts. Control device. 19. The evaluation function, building energy system according to one of claims 12 to 16, characterized in that a CO ₂ emissions expressed as a linear combination of the respective input energy Control device. 20. The evaluation function, wherein the evaluation function is represented by a linear combination of the investment recovery years described in claim 17, the energy consumption described in claim 18, and the CO ₂ emission described in claim 19. 17. The control device for a building energy system according to claim 12, wherein the control device is a function. 21. Control means for controlling each of said energy conversion means so as to obtain said calculated input energy amount, thereby maintaining said calculated optimum design condition and operating. Claim 12
Or a control device for a building energy system according to claim 13. 22. The gas engine is controlled so that the calculated gas purchase amount is obtained, and the exhaust heat absorption refrigeration is used so as to obtain the calculated input heat amount for cooling and the input heat amount for heating. Control means for controlling the heat pump to control the heat pump so that the input power for cooling and the input power for heating are calculated, thereby maintaining the calculated optimum design conditions and operating the heat pump. The control device for a building energy system according to claim 14, further comprising: 23. A control program for a building energy system, wherein a control processing program including each step in the control method for a building energy system according to claim 1 is recorded. recoding media.