JP2001273008A - Optimum operation control system for plant supplying both of heat and electricity - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an optimum operation control system controlling a plant operation according to a high precise operation plan and outputting a high reliable operation plan. SOLUTION: This system suppresses redundant steam of a plant and controls the inflow and outflow electrical energy of the plant within the fixed range, on the basis of the past electric power and thermal load data based on plant operation data from an energy plant 11, the plant electric power and thermal load estimated according to meteorological data, and the characterization factor of a constituent plant apparatus. It also outputs the plant control data calculated so that a fixed evaluation function value becomes a maximum or minimum, which control the number of an operating plant and the load of each constituent plant apparatus, to the energy plant 11.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an optimal operation control system for a cogeneration plant for supporting and controlling efficient operation in an energy plant for supplying cold and hot heat and electric power.

[0002]

2. Description of the Related Art In a conventional power supply plant, an operation whose primary purpose is to satisfy power demand and improve power generation efficiency is performed, and heat has been discarded or hardly considered. However, in recent years, it is conceivable that a power supply plant supplies heat at the same time as supplying power, and it is desired to improve not only power but also heat energy efficiency at the same time. A cogeneration plant is a facility that simultaneously supplies power and heat according to demand.

FIG. 13 is an explanatory diagram showing the configuration of a conventional cogeneration plant optimal operation control system. That is, the past heat load data of the energy plant 11 is stored in the heat load data storage unit 13 based on the plant operation data input from the energy plant 11 that supplies the cooling / heating heat and the electric power via the plant operation data input unit 12. Is done. The heat load predicting means 16 is based on the past heat load data stored in the heat load data storage means 13 and the weather data input from the human interface 14 via the weather data input unit 15, based on the current day or the next day. The plant heat load is predicted. A value representing the input / output performance of the plant component stored in the plant component characteristic coefficient storage means 17 (hereinafter referred to as a characteristic coefficient);
The predicted plant heat load value predicted by the heat load prediction means 16 is input to the optimal operation planning means 18. The optimal operation planning means 18 calculates plant control data for controlling the number of operating plants and load control of each plant component by an optimization method based on the input information, and outputs the plant control data to the plant control data output. The energy is sent to the energy plant 11 via the section 19. The energy plant 11 controls the number of operating plants and the load according to the plant control data sent from the optimal operation planning means 18. It should be noted that the characteristic coefficients of the plant components are input from the human interface 14.

[0004]

The conventional cogeneration plant optimal operation control system has the following problems and requirements.

[0005] That is, in a cogeneration plant, it is difficult to properly allocate the heat output side when generating power so as to meet the power demand and the heat demand on the customer side, so that it may be difficult to effectively use energy. There has been a demand for means for controlling the inflow commercial power (hereinafter referred to as power purchase) and the plant outflow power within a certain range.

[0006] In the load prediction function of the operation planning system, a highly accurate and inexpensive weather forecast information acquiring means has been desired. In addition, conventionally, when planning the operation of a cogeneration system (CGS), C
There is a problem that the fluctuation of the capacity of the GS is ignored, or the fluctuation of the capacity of the CGS due to the intake air temperature cannot be appropriately reflected in the operation plan because the performance of the CGS is corrected by using the outside air temperature. .

[0007] On the other hand, in the conventional cogeneration plant optimal operation control system, the amount of power flowing into and out of the plant is not constant due to load fluctuations and the like. By controlling, the electric power flowing into and out of the plant was controlled within a desired range. For this reason, the energy efficiency has fallen below the ideal state, and the economic efficiency has to be reduced. here,
An on-premise generator is a generator that is installed and operated for the purpose of supplementing the power consumption in the plant premises with in-house power generation and improving economic efficiency, or a main purpose of supplying power to consumers Point to.

As a means for avoiding such a reduction in the efficiency of the on-site generator, it is effective to provide a relatively small-capacity adjusting generator. In other words, only the adjusting generator increases or decreases the output with respect to the instantaneous load fluctuation, so that it is possible to perform plant outflow / input power control while preventing the efficiency of the on-premise generator from decreasing. However, no conventional cogeneration plant optimal operation control system has a means for controlling the generator for adjustment.

SUMMARY OF THE INVENTION The present invention has been made in view of the above circumstances, and suppresses excessive steam in a plant, controls the amount of electric power flowing into and out of the plant, and corrects the capabilities of plant components based on intake air temperature prediction. By using
An object of the present invention is to provide an optimal operation control system for a cogeneration plant that can perform plant operation control according to a highly accurate operation plan. In addition, by providing a means for monitoring the change rate of the characteristic coefficient of the plant component equipment and notifying the user when the change rate deviates from the allowable value and inquiring whether or not to update the characteristic coefficient, highly reliable operation is provided. An object of the present invention is to provide an optimal operation control system of a cogeneration plant that outputs a plan. In addition, by providing means for calculating the control output of the adjusting generator serving as a buffer (buffer) so that the plant operation control according to the operation plan can sufficiently cope with actual load fluctuations, An object is to provide an optimal operation control system of a cogeneration plant that enables efficient plant operation control.

[0010]

In order to achieve the above object, an optimum operation control system for a cogeneration plant according to the present invention is provided based on plant operation data input from an energy plant that supplies cooling / heating and electric power. Power / heat load data storage means for storing the power / heat load data of the plant, and the plant power / heat load based on the past power / heat load data and weather data read from the power / heat load data storage means. Power and heat load prediction means for predicting, plant component characteristic coefficient storage means for storing characteristic coefficients of plant components constituting the energy plant, and plant power and heat load predicted by the power and heat load prediction means. Based on the characteristic coefficient of the plant component read from the plant component characteristic coefficient storage means, Control of the number of operating plants and the load control of each plant component so that the predetermined evaluation function value is maximized or minimized, while controlling the steam amount and controlling the power flowing into and out of the plant within a certain range. Optimum operation planning means for calculating plant control data to be performed and sending the calculated data to the energy plant.

Further, the optimum operation control system for a combined heat and power plant according to the present invention comprises a power / heat storage device for storing past power / heat load data based on plant operation data input from an energy plant for supplying cooling / heating heat and electric power. Load data storage means; power / heat load prediction means for predicting plant power / heat load based on past power / heat load data and weather data read from the power / heat load data storage means; and A plant component characteristic coefficient storage means for storing characteristic coefficients of plant components constituting the plant, a plant operation data storage means for storing plant operation data inputted from the energy plant, and a plant operation data storage means for reading from the plant operation data storage means. Based on the issued plant operation data, Update necessity of characteristic coefficient of the stored plant constituent while processing at a predetermined cycle unit, the plant constituent characteristic coefficient updating means for updating the characteristic coefficient when the predetermined update condition is satisfied, the power-
Based on the plant power / heat load predicted by the heat load predicting means and the characteristic coefficient of the plant component read out from the plant component characteristic coefficient storage, the amount of excess steam in the plant is suppressed, and Controlling the input power within a certain range, and calculating plant control data for controlling the number of operating plants and controlling the load on each plant component so that the predetermined evaluation function value is maximum or minimum. And an optimal operation planning means for sending the operation plan to the energy plant.

Further, the present invention provides the optimum operation control system for a combined heat and power plant, wherein intake temperature predicting means for predicting the intake air temperature to the plant components based on weather data is provided, and the optimal operation planning means is provided for the plant components. It is characterized by comprising means for correcting the capacity of the plant component equipment based on the predicted intake air temperature value.

Further, the present invention is characterized in that in the optimal operation control system of the cogeneration plant, the weather data is obtained from a communication interface such as the Internet.

The present invention also provides an optimum operation control system for a combined heat and power plant, wherein a change rate of a characteristic is monitored using a characteristic coefficient of a plant component before and after updating by a characteristic coefficient updating unit for a plant component, and the change rate is set. A characteristic change informing means for notifying the user when the value is equal to or more than the value or equal to or less than the set value is provided.

Further, according to the present invention, in the optimum operation control system for a combined heat and power plant, the characteristic change informing means receives an update permission / prohibition of a plant component characteristic coefficient from a user, and determines whether the update is permitted or not. Output to the

The present invention also provides an optimum operation control system for a combined heat and power plant, wherein a generator for adjustment is provided based on active power and reactive power of plant outflow / inflow power input from an energy plant that supplies cooling / heating heat and power. Means for calculating the output of the above is provided.

[0017]

DESCRIPTION OF THE PREFERRED EMBODIMENTS Embodiments of the present invention will be described below in detail with reference to the drawings.

FIG. 1 is an explanatory diagram showing the configuration of an embodiment of the present invention. That is, from the energy plant 11 that supplies cooling / heating heat and electric power, the plant operation data input unit 1
2 based on the plant operation data input via
Past power and heat load data of the energy plant 11 is stored in the power and heat load data storage unit 21. Electric power
In the heat load prediction means 23, the past power / heat load data stored in the power / heat load data storage means 21,
Based on the weather data input via the weather data input unit 22 and the weather data, the plant power / heat load on the current day or the next day is predicted and output to the optimal operation planning means 26. The plant operation data input from the energy plant 11 via the plant operation data input unit 12 is stored in a plant operation data storage unit 24, and the plant operation data read from the plant operation data storage unit 24 is a plant component It is input to the characteristic coefficient updating means 25. The plant component equipment characteristic coefficient updating means 25 periodically analyzes the latest data on each plant component equipment in the plant operation data by applying a statistical regression method, and based on the result, the plant component equipment characteristic coefficient A calculation process of whether to create and update the plant component characteristic coefficients stored in the storage unit 17 is performed. In the arithmetic processing,
If the update is set to be performed automatically, the updated plant component characteristic coefficient is stored in the plant component characteristic coefficient storage unit 17 as it is, and if the update condition is specified in advance, the update condition is set. Only when satisfied, the updated plant component characteristic coefficient is stored in the plant component characteristic coefficient storage unit 17. The characteristic coefficients of the plant components may be input from the human interface 14. The plant component characteristic coefficient read from the plant component characteristic coefficient storage unit 17 is output to the optimal operation planning unit 26.
Further, the intake air temperature predicting means 27 predicts the intake air temperature to the plant component equipment based on the weather data input through the weather data input unit 22, and obtains the optimum operation planning means 2.
6 is output. The optimal operation planning means 26 includes a plant component characteristic coefficient inputted from the plant component characteristic coefficient storage 17, a plant power / thermal load predicted value predicted by the power / thermal load predicting means 23, and an intake air temperature prediction. Based on the intake air temperature to the plant components predicted by the means 27, the capability of the plant components is corrected and the following processing is performed. That is, the amount of surplus steam in the plant is suppressed, and the amount of power flowing into and out of the plant is controlled within a certain range. This optimal operation planning means 2
6. The plant control data for controlling the number of operating plants and controlling the load on each plant component is calculated by the optimization method such as mathematical programming implemented in 6 so that the plant operation cost is the lowest. The control data is sent to the energy plant 11 via the plant control data output unit 19. Energy plant 1
Numeral 1 controls the number of operating plants and the load according to the plant control data sent from the optimal operation planning means 26.

When controlling the adjusting generator, the active power value and the reactive power value in the plant operation data input from the energy plant 11 via the plant operation data input unit 12 are adjusted. Output calculation means 30
To calculate the control output of the adjusting generator,
The calculation result is sent to the energy plant 11 via the plant control data output unit 19. As the optimization evaluation criterion used by the optimal operation planning means 26, for example, the energy consumption and the carbon dioxide emission of the plant may be set in addition to the plant operation cost described above. Multi-objective optimization may be performed.

FIG. 2 is a structural explanatory view showing another embodiment of the present invention. In the drawings, the same portions are denoted by the same reference numerals and description thereof will be omitted. That is, the weather data input unit 22 is connected to a communication interface 28 such as the Internet,
The detailed and latest weather data is acquired from the communication interface 28 such as the Internet. Further, a characteristic change notifying unit 29 is provided between the plant component characteristic coefficient updating unit 25 and the human interface 14, and the rate of change of the performance characteristic is monitored using the plant component characteristic coefficient (slope / intercept) before and after the update. However, if the rate of change exceeds the set value or falls below the set value and deviates from the allowable value, the user is notified, and after the user permits the update, the updated plant component equipment characteristic coefficient is used for the operation plan. . If the user does not permit the update, the plant component equipment characteristic coefficient before the update is continuously used for the operation plan.

FIG. 3 is an explanatory diagram showing the relationship between the optimum operation control system, the energy plant, and the customer according to the present invention.
That is, plant operation data is input from the energy plant 11 to the optimum operation control system 31 as a measurement signal, and plant control data is input from the optimum operation control system 31 to the energy plant 11 as a control instruction. The energy plant 11 is energy that supplies electric power and heat required by consumers by consuming electric power, gas, heavy oil, water and sewage, and the like. The energy plant 11 has a cogeneration system (CGS) 32,
It consists of a boiler 33, a refrigerator 34, a heat exchanger 35, transfer equipment, auxiliary equipment, a piping system, etc., and generates electric power from a cogeneration system (CGS) 32 which is instructed by an optimal operation control system 31 to start / stop and generate electric power. Electricity is supplied to consumers as electric power, and the cogeneration system (C
The hot water and the steam generated from the GS (32) are supplied from the optimal operation control system 31 to the refrigerator 3 which has been instructed to start and stop and to produce heat.
4, and the refrigerator 34 supplies cold heat to the customer using the refrigerator as a drive source. In addition, steam or hot water generated from the boiler 33 which has been instructed by the optimal operation control system 31 for starting / stopping / manufacturing calorie is supplied to the customer as steam or hot water via the heat exchanger 35, and a part of the steam or hot water is supplied. It is used as a drive source of the refrigerator 34. Of the steam and hot water generated from the cogeneration system (CGS) 32 and the boiler 33, those not used as supply energy to consumers are discarded or stored as surplus steam and surplus hot water, respectively.

Next, a description will be given of a means for making the most effective use of the recovered heat from the CGS 32 in consideration of not only the power demand but also the heat demand of the consumer.

In the present invention, the following objective function and constraint equation are described as an operation policy, and an operation plan that satisfies these conditions simultaneously is prepared. Thus, the plant components can be operated so as to simultaneously satisfy the power supply amount and the cold / hot heat supply amount, and the energy cost thereof can be minimized.

Objective function: minimization (Σ plant energy consumption (gas, heavy oil, power purchase, water supply, etc.) × each energy unit price) constraint equation 1): power purchase + CGS power generation = demand-side power supply + plant premises Power consumption (power of centrifugal chiller, power of other auxiliary equipment, etc.) Restriction formula 2): CGS production steam amount + boiler production steam amount = demand side supply steam amount + on-site consumption steam amount + surplus on-site steam amount Constraint expression 3): Surplus steam volume in the plant <upper limit of waste volume per unit time In actual operation, it is not possible to save power, but it is possible to spare some steam and hot water (dispose of it without using it). The term of the amount is set in the constraint equation, the upper limit value that can be discarded per hour is determined, and the gas consumption, power consumption, and water consumption ( Energy in boiler makeup water) By multiplying the over bids, while acknowledging the heat rejection, it is possible to minimize energy costs, including the thermal disposal costs. This enables a highly efficient operation plan that takes into account not only the power demand but also the heat demand.

FIG. 4 is an explanatory diagram for suppressing the amount of power purchase according to the present invention within a set value range. That is, from the optimal operation control system 31 of the present invention to each device of the energy plant 11 including the cogeneration system (CGS) 32, the boiler 33, the refrigerator 34, the heat exchanger 35, the transport equipment, the auxiliary equipment, and the piping system. The power supply, the cold heat supply, and the warm heat supply are performed from the energy plant 11 to the customer. In this case, the total energy cost of the commercial power, gas, oil, water, etc. consumed in the energy plant 11 is minimized, and the amount of purchased power is suppressed to a set value or less. Further, the amount of environmental load such as CO ₂ emitted from the energy plant 11 can be minimized as needed.

In general, upon contract with an electric power company, it is desired to control power consumption within a certain range during plant operation, such as constantly consuming more than a certain amount of power or not exceeding a certain upper limit. However, in the past, humans constantly monitored the excess or deficiency of the amount of electricity purchased, making automation difficult. This is largely attributable to the fact that changes in power demand cannot be predicted and that countermeasures have not been considered in advance.

The above-mentioned problem is that, for example, if it is expected that the amount of purchased electricity will be exceeded, the generator is started in advance just before the time, and the equipment that consumes a large amount of power is stopped to replace the low power consumption. This can be dealt with by starting the machine. For this purpose, it is necessary to control the plant components based on the prediction of the transition of the power load.

In the system of the present invention, the following constraint equations are described as operation policies, and an operation plan for observing these is formulated.

1) Power purchase> Contract minimum purchase 2) Power purchase <Contract demand maximum 3) Power supply to customer (predicted power load) = CGS
Total power generation + power purchase-plant power consumption By giving this power purchase and the state designation value to each device to realize the value as an indication value every time,
It is possible to systematically keep the amount of purchased electricity within a certain range. Although the description has been given of suppressing the amount of power purchase within the set value range, the same concept can be applied to not only the amount of power purchase but also the amount of power flowing out of the plant.

Next, means for minimizing the amount of environmental load such as CO ₂ will be described.

That is, by adding the following term to the above objective function, it is possible to make a plan for minimizing the emission of CO ₂ and the like.

Objective function: minimization (weighting factor W1 * Σplant energy consumption + weighting factor W2 * Σenvironmental load emission) Environmental load emission = each energy consumption × each environmental load emission unit, where “energy cost” Attempts to simultaneously consider "minimization" and "minimization of environmental load emissions" often result in conflicting driving policies. Therefore, a “weighting coefficient” is provided in advance, and the “degree of importance” for the term is input between the two. The sum of the weighting factors is set to be 1.0.

FIG. 5 is a diagram for explaining a function of notifying a user of a change in a characteristic coefficient according to the present invention.

Updating of the characteristic coefficients of the plant components may cause a significant change in the tendency of the overall plan of the plant operation control, and should be performed particularly carefully. It is also necessary not to use non-stationary data such as at the time of equipment adjustment or at the time of failure to create characteristic coefficients that should represent the intrinsic characteristics of the equipment.

According to the present invention, 1) the device characteristic coefficient is recreated at regular intervals. After passing through the process of creating the characteristic coefficient, it is compared with the previous characteristic coefficient. The following discriminant is used as an example of the change rate judgment index (if this discriminant is satisfied, the effect on the overall plan is considered to be minimal, and the step of obtaining permission is skipped and the characteristics are automatically updated). .

Discriminant: Whichever is greater (first rate of change, second rate of change) <permission rate However, first rate of change: | (a1−a2) / a1 | second rate of change: | ( b1-b2) / b1 | Constraint formula before update: Y = a1X + b1 Constraint formula after update: Y = a2X + b2.

The permission rate is set in advance to a value such as 0.1 (= 10%) for each device. If the characteristic has changed, it is determined whether or not the value of the discriminant equation is equal to or higher than the set permission rate. If the value is equal to or lower than the set permission rate, the characteristic coefficient is automatically updated without notifying the user.

2) If there is a change exceeding the preset permission rate, the user is asked for permission / non-permission as to whether the corresponding characteristic coefficient may be updated. Examples of this means include: i) display of messages and marks on the human interface screen, ii) automatic printing of printed materials at night, iii) notification of changes for each device to the user through notification by pager, e-mail, etc. And so on.

3) When the user gives permission to update, the characteristic is reflected in the planning function and the characteristic coefficient of the corresponding device is updated. If update permission is not granted, the creation result is discarded.

FIG. 6 is a flowchart showing the processing for updating the device characteristic coefficient according to the present invention.

FIG. 7 is an explanatory view showing the execution of load prediction, planning and control of an operation plan, and acquisition of various information necessary for prediction according to the present invention. That is, as shown in FIG. 7A, the weather forecast / weather information provided from the weather forecast / weather information providing site on the Internet to the Internet 41 is automatically analyzed to extract information necessary for the prediction. The present invention provides the optimum operation control system 31. The optimum operation control system 31 executes load prediction based on weather forecast / weather information, drafts an operation plan, and instructs the energy plant 11 to control.

Generally, temperature information and weather information in a time range to be predicted are essential information for a highly accurate load prediction. In the conventional system, a temperature sensor value and other weather information sensor values are taken into the system, and necessary weather information is predicted by statistical processing in the system. In addition, they contracted with general information providers and set up dedicated equipment to acquire information.

However, weather information cannot be accurately predicted from only local sensor values, but becomes reliable only after analyzing information from a wide range at the Japan Meteorological Agency or the like.

The service of an information provider that satisfies the above has a disadvantage that the cost is generally high.

The system of the present invention utilizes the fact that such information has begun to be provided on the Internet at low cost or free of charge. In addition, it is possible to obtain more localized prediction information than before, and there is an advantage that further improvement and stability of prediction accuracy can be expected.

FIG. 7B shows an example of the provided information. In the provided site, the current status and the predicted information are obtained by rewriting portions such as a temperature / weather section in a predetermined format at regular intervals. It is realized by. (The underlined portion in the example) These provided information is character information called HTML, and lexical analysis can be performed.

Using this, the operator manually reads the relevant page only once beforehand, and specifies the lexical characters before and after the desired information. The system of the present invention makes it possible to access the providing site at regular intervals in order to perform load prediction, and to automatically extract necessary information at regular intervals by the lexical analysis function.

If the information providing format in the provided information site has changed and information cannot be obtained, this can be detected and the user can be prompted to reset.

FIG. 8 is a flowchart of the intake air temperature prediction process according to the present invention. That is, the intake air temperature data during the operation of each CGS is accumulated for each device, and a representative intake air temperature pattern is created at regular intervals by statistical processing. Then, temperature prediction information is obtained through the Internet or a user, and the representative intake temperature pattern is corrected based on the temperature prediction information, thereby obtaining an intake temperature prediction value at each time. The above processing is executed in the intake air temperature prediction means, and the processing result is used as input information in the subsequent CGS performance correction processing.

FIG. 9 is a flowchart of a CGS capacity correction process based on the intake air temperature prediction according to the present invention. That is, a table (hereinafter, referred to as a correlation table) showing the correlation between the intake air temperature and the CGS performance (power generation / steam production performance) fluctuation (hereinafter referred to as a correlation table) is created in advance for each CGS, and the corresponding time obtained by the intake air temperature prediction process is obtained. From the predicted intake air temperature and the correlation table, a CGS capability correction value at a corresponding time is obtained. An operation plan is executed using the CGS capacity correction value as a CGS planning capacity value, and a display / control output is extracted. Here, the correlation table is composed of numerical data in the form of a ratio to the rated capacity based on the power generation performance under typical temperature conditions specified in the device-specific data at the time of CGS delivery. Therefore, by multiplying this numerical value by the rated capacity, the CGS power generation output upper limit value for each intake air temperature can be calculated. The above processing is executed in the optimal operation planning means.

FIG. 10 is a processing flowchart of the operation planning function and the automatic operation control function of the present invention. That is, plant operation data and load data are measured and accumulated. An operation plan is executed by acquiring information necessary for load prediction / intake air temperature prediction to correct the CGS planning ability, or by acquiring an input from a user such as an operation planning policy, and executing and outputting the display. From the calculation result based on the operation plan execution, an instruction is output to the control output function to extract the control output. The above processing is periodically executed.

Next, calculation processing of the control output of the generator for adjustment will be described. As an example of plant outflow and inflow power control using a generator for adjustment, there are two applications, that is, an in-house power generation application and a specific electricity business application. Hereinafter, an example of the plant outflow / inflow power control when the adjusting generator is used for each application will be described.

FIG. 11 is a flow chart of the arithmetic processing for determining the output value of the adjusting generator for the private power generation according to the present invention.
That is, the value of the active power at the connection point between the plant and the power system is set to P (P takes a positive value when flowing into the plant premises and a negative value when flowing out of the plant premises). The value of the reactive power at the connection point between the plant and the power system is assumed to be Q (Q takes a positive value when the power system is delayed and takes a negative value when it is advanced).

Also, the upper limit of the power receiving contract of the plant with the power company is called "contract power", and the standard for setting the received power so as not to exceed the contract power is "margin". The margin is indicated by a ratio with respect to the contract power, and takes a value such as 10%. (Margin ≧ 0). Further, in a plant contracted to have no backflow to the power system, the minimum power that the plant must always receive from the power system is determined. This is referred to as “minimum received power”. The lower limit of the desirable power factor range at the power receiving point is referred to as a “power factor setting value”. Usually, a value such as 0.95 is taken.

First, the value of P at the power receiving point is monitored. If this value does not satisfy P ≦ contract power−the margin, it is determined that the contract power is exceeded or there is a risk of exceeding the contract power, and adjustment is performed. Increase the output of the generator (decrease P). It is assumed that the output increase instruction value to the adjustment generator = P- (contracted power-margin). Next, if P ≧ minimum received power is not satisfied, there is a possibility that a reverse tide to the power system will occur, so the output value of the adjusting generator is reduced (P is increased). It is assumed that the output decrease instruction value to the adjustment generator = minimum received power-P.

Next, the value of Q at the receiving point is monitored, and Q ≧
If 0 is not satisfied, it is considered that the reactive power is advanced,
Reduce the reactive power output from the regulating generator. It is assumed that the output decrease instruction value to the adjustment generator = | Q |. Next, P and Q
Is determined based on the value of. P / √ (P ² + Q
² ) If the power factor setting value is not satisfied, the current power factor value is
Judging that it is lower than the desired power factor value, the reactive power output of the adjusting generator is increased. Reactive power output increase instruction value to adjustment generator = Q-{(P / power factor set value) ² -P ² }
And

The above is constantly repeated, and P and Q are controlled to an appropriate range by the adjusting generator.

FIG. 12 is a flow chart of the arithmetic processing for determining the output value of the adjusting generator for the specific electric utility application of the present invention. That is, the value of the active power at the connection point between the plant and the power system is set to P (P takes a positive value when flowing into the plant premises and a negative value when flowing out of the plant premises).
The value of the reactive power at the connection point between the plant and the power system is defined as Q (Q takes a positive value when the power system is delayed and takes a negative value when advanced).

In the case of a specific utility business application, it is usually required to control the received power to ± 0. Here, the received power in the specific electricity business = ± 0 means that the integrated value (the amount of power) of the power at a certain time interval should be 0.
For this reason, it is possible to allow some margin for the target received power = ± 0. It is practically impossible to follow the control of the received power = ± 0 instantaneously, so there is no problem in allowing this margin. Therefore, the following two margins are set. The criterion provided to prevent the target received power = 0 from being significantly exceeded on the power receiving side (+ side) is “margin 1”. The margin 1 is represented by an electric power value and takes a value such as 100 kW (margin 1 ≧ 0). Similarly, the criterion provided to prevent the target received power from greatly exceeding the reverse flow side (− side) is “margin 2”. The margin 2 is represented by an electric power value,
Take a value such as -100 kW (margin 2 ≦ 0).

First, the value of P at the power receiving point is monitored, and if this does not satisfy P ≦ the margin 1, it is determined that the plant is in a greatly exceeded received power state, and the output of the adjusting generator is increased. Output increase instruction value to adjustment generator = | P-
The allowance is 1 |.

Next, when P ≧ the margin 2 is not satisfied, it is determined that a large backward flow is flowing from the plant, and the output of the adjusting generator is reduced. It is assumed that the output decrease instruction value to the adjustment generator = | P−the margin 2 |. Next, the value of Q at the power receiving point is monitored. If Q ≧ 0 is not satisfied, the reactive power is regarded as being delayed, and the reactive power output from the adjusting generator is reduced. Output decrease instruction value to adjustment generator =
| Q |. Next, the power factor is determined based on the values of P and Q. When | P | / √ (P ² + Q ² ) ≧ power factor setting value is not satisfied, it is determined that the current power factor value is lower than the desired power factor value, and the reactive power output of the adjusting generator is increased. . Reactive power output increase instruction value to adjustment generator = Q-√
{(P / power factor set value) ² −P ² }.

The above is constantly repeated, and P and Q are controlled to an appropriate range by the adjusting generator.

[0063]

As described above, according to the present invention, the residual steam of the plant is controlled, the power flowing into and out of the plant is controlled within a certain range, and the capacity of the component equipment of the plant is controlled based on the intake air temperature prediction. By correcting and using the above, it is possible to provide an optimal operation control system of a cogeneration plant capable of performing plant operation control according to a highly accurate operation plan. In addition, by providing a means for monitoring the change rate of the characteristic coefficient of the plant component equipment and notifying the user when the change rate deviates from the allowable value and inquiring whether or not to update the characteristic coefficient, highly reliable operation is provided. An optimal operation control system for a cogeneration plant that outputs a plan can be provided. Furthermore, to ensure that plant operation control according to the operation plan can sufficiently respond to actual load fluctuations,
By providing the means for calculating the control output of the adjusting generator serving as a buffer, it is possible to provide an optimal operation control system for a cogeneration plant that enables highly efficient plant operation control.

[Brief description of the drawings]

FIG. 1 is a configuration explanatory diagram showing an embodiment of the present invention.

FIG. 2 is a configuration explanatory view showing another embodiment of the present invention.

FIG. 3 is an explanatory diagram showing a relationship among an optimal operation control system, an energy plant, and a customer according to the present invention.

FIG. 4 is an explanatory diagram for suppressing a power purchase amount within a set value range according to the present invention.

FIG. 5 is a diagram illustrating a function of notifying a user of a change in a characteristic coefficient according to the present invention.

FIG. 6 is a flowchart showing a process of updating a device characteristic coefficient according to the present invention.

FIG. 7 is a diagram illustrating execution of load prediction and planning of operation according to the present invention;
It is explanatory drawing which shows acquisition of various information required for control and prediction.

FIG. 8 is a flowchart of an intake air temperature prediction process according to the present invention.

FIG. 9 is a flowchart of a CGS planned capacity correction process based on intake air temperature prediction according to the present invention.

FIG. 10 is a processing flowchart of an operation planning function and an automatic operation control function of the present invention.

FIG. 11 is a flowchart of a calculation process for determining an output value of an adjusting generator for a private power generation according to the present invention.

FIG. 12 is a flowchart of a calculation process for determining an output value of an adjusting generator for a specific electric utility application according to the present invention.

FIG. 13 is a configuration explanatory view showing a conventional cogeneration plant optimal operation control system.

[Explanation of symbols]

 REFERENCE SIGNS LIST 11 energy plant 12 plant operation data input unit 14 human interface 17 plant constituent device characteristic coefficient storage unit 19 plant control data output unit 21 power / heat load data storage unit 22 weather data input unit 23 power / heat load prediction unit 24 plant operation Data storage means 25 Plant constituent device characteristic coefficient updating means 26 Optimal operation planning means 27 Intake air temperature prediction means 28 Communication interface 29 Characteristic change notification means 30 Adjustment generator output calculation means

 ──────────────────────────────────────────────────続 き Continuing on the front page (72) Inventor, Yoshiaki Yamazaki 4-1-2, Hirano-cho, Chuo-ku, Osaka-shi, Osaka Inside Osaka Gas Co., Ltd. (72) Inventor Hisashi Saito 390 Kita-Nagai, Miyoshi-cho, Iruma-gun, Saitama Daidan Corporation F-term (reference) 3L060 AA03 CC01 DD02 EE21 5H004 GA14 GA15 GB06 HA14 KA16 KC03 KC12 KC23 KC25 LA15 MA04 9A001 HH34 JJ61 LL09

Claims (7)

[Claims] 1. Based on plant operation data input from an energy plant that supplies cooling / heating and electric power,
Power / heat load data storage means for storing past power / heat load data; and plant power / heat load based on past power / heat load data and weather data read from the power / heat load data storage means. Power / heat load prediction means for predicting the power factor, plant component characteristic coefficient storage means for storing characteristic coefficients of plant components constituting the energy plant, and plant power / heat load predicted by the power / heat load prediction means Based on the characteristic coefficients of the plant component equipment read from the plant component equipment characteristic coefficient storage means, while controlling the amount of excess steam in the plant, and controlling the amount of power flowing into and out of the plant within a predetermined range, The control of the number of operating plants and the load control of each plant component are performed so that the evaluation function value of Optimal operation control system of cogeneration plants, characterized in that to calculate the plant control data and a optimal operation planning means for sending to said energy plant. 2. Based on plant operation data input from an energy plant that supplies cooling / heating and electric power,
Power / heat load data storage means for storing past power / heat load data; and plant power / heat load based on past power / heat load data and weather data read from the power / heat load data storage means. Power / heat load prediction means for predicting the power consumption, plant component characteristic coefficient storage means for storing characteristic coefficients of plant components constituting the energy plant, and plant operation for storing plant operation data inputted from the energy plant. A data storage unit, and calculates, at a predetermined cycle, whether or not to update the characteristic coefficient of the plant component stored in the plant component characteristic coefficient storage based on the plant operation data read from the plant operation data storage. A plant component machine that processes and updates characteristic coefficients when a predetermined update condition is satisfied Device characteristic coefficient updating means, the plant power / heat load predicted by the power / heat load prediction means, and the remainder of the plant based on the characteristic coefficient of the plant component read out from the plant component characteristic coefficient storage means. In addition to controlling the amount of steam and controlling the amount of power flowing into and out of the plant within a certain range, the number of operating plants and the load of each component of the plant are controlled so that a predetermined evaluation function value is maximized or minimized. Optimal operation control system for a combined heat and power plant, comprising: optimal operation planning means for calculating plant control data for the plant and sending the calculated data to the energy plant. 3. An intake air temperature predicting means for predicting an intake air temperature to a plant component based on weather data, and an optimal operation planning means determines an ability of the plant component based on a predicted intake temperature of the plant component. The optimal operation control system for a cogeneration plant according to claim 1 or 2, further comprising a correction unit. 4. The optimal operation control system for a cogeneration plant according to claim 1, wherein the weather data is obtained from a communication interface such as the Internet. 5. A change rate of the characteristic is monitored using the characteristic coefficient of the plant component before and after the updating by the characteristic coefficient of the component component of the plant, and the user is notified when the change rate is equal to or more than the set value or equal to or less than the set value. 5. The optimum operation control system for a cogeneration plant according to claim 1, further comprising a characteristic change notifying unit. 6. The thermoelectric device according to claim 5, wherein the characteristic change notifying unit receives a permission / prohibition of updating of the plant component characteristic coefficient from the user and outputs the update permission / prohibition to the plant component characteristic coefficient updating unit. Optimal operation control system for co-feeding plant. 7. A means for calculating an output of the adjusting generator based on active power and reactive power of plant inflow / outflow power input from an energy plant that supplies cooling / heating heat and power. Claims 1, 2, 3,
7. The optimal operation control system of the cogeneration plant according to 4, 5, or 6.