JP2001295700A - Control for energy supply system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To conduct the optimum operation of an energy supply system, constituted by plural energy apparatus of many types to eliminate the disadvantages of prior art, and achieve cost saving, energy saving or low environmental load, in energy supply for a dwelling house or multiple dwelling houses. SOLUTION: The optimization control for the whole system is conducted according to the arithmetic result of one system controller. In the system controller, a calendar and a timer are incorporated, and two energy demand data bases, corrected according to the history of past energy demand and three system operation map data previously obtained by test evaluation and simulation, are stored. The three system operation map data are the summary of data on energy saving, low cost and reduction in exhaust emission, and the energy demand amount estimated according to the energy demand data base and the actual energy demand amount are compared to select the scheduled operation control and the load follow-up control, thereby performing the optimized operation of the system.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an energy supply device in a facility having a high demand for heat energy or a house in a cold area, an energy supply device in a remote place where an energy supply infrastructure is not provided, or a disaster. The present invention relates to an energy supply device in an existing facility or an emergency energy supply device in an existing facility.

[0002]

2. Description of the Related Art Hitherto, as an autonomous energy supply system, a combination of a solar cell module, a fuel cell, and a composting device has been proposed (for example, Japanese Patent Application No. 10-225155, Japanese Patent Application No. 158228,
Japanese Patent Application No. 10-141465). As a method of controlling the system by calculating the optimal operation method of cogeneration, for example, Japanese Patent Application No. 08-086243 has been proposed.

[0003]

SUMMARY OF THE INVENTION Particularly in a cold region, heating,
Because of the large amount of heat utilization such as hot water supply and snow melting, additional heat supply equipment such as a boiler is often added. In this case, the power generated by the solar cell or fuel cell or the exhaust heat is satisfied on the heat demand side. After selecting the equipment,
The cost is higher and the equipment is larger than conventional boilers using fossil fuels. In addition, Japanese Patent Application Laid-Open No.
In the control method of the cogeneration system described in Japanese Patent No. 086243, means for estimating power load after a lapse of a predetermined time, data on past operation results and seasons, power load following operation based on the estimated power load, heat load following operation,
Means for performing energy simulation for each of the operation modes of multiple-unit rated operation, single-unit partial-load operation, and motor stop operation, means for calculating the energy consumption of each operation mode from the results of the energy simulation, and each calculated operation mode And a means for selecting an operation method that matches the objective function to be minimized, such as energy consumption and cost, and a means for operating the system based on the selected operation method are required. Controlling a complicated system requires complicated data preparation and input of a complicated algorithm on a control computer, and there is a problem that the equipment required for the control and the cost for preparation are high. Thus, in the present invention, a solar cell, a fuel cell, a cogeneration system using an internal combustion engine or an external combustion engine, and a heat supply device such as a boiler are combined to construct an energy supply system capable of sufficiently autonomous heat demand especially in cold regions. In addition, an optimization operation that minimizes energy costs, or an optimization operation that minimizes exhaust gas emissions, for example, or energy saving that is most achieved compared to conventional energy supply methods The optimized operation of the system is based on the energy demand prediction map data by storing the prediction map data of the heat demand and the operation map data in which the system operation for the power demand and the heat demand is calculated in advance in the control computer. Performs scheduled operation control, energy demand forecast map data and actual energy demand It is when the outside is large immediately by switching the load following control, making it possible to present at low cost optimization control of the system.

An object of the present invention is to solve the above-mentioned disadvantages,
Cost saving for energy supply of houses and apartment houses,
With the objective function of energy saving or reduction of low environmental load, optimized operation of the whole system is performed at a low cost for multiple existing energy facilities, new energy facilities, or the addition of energy facilities to existing facilities. The purpose is to:

[0005]

In order to solve the above-mentioned problems, according to the present invention, a system controller for controlling the entire system is provided with an optimized operation data map for minimizing the energy cost, or for example, for the exhaust gas. Optimized operation data map that minimizes environmental load such as emission, or energy saving compared with existing energy supply method or existing energy equipment represented by combination of kerosene boiler and commercial power The optimized operation data map that is most frequently achieved is created in advance by using the results of tests and simulations of the components that constitute the system, and stored in the system controller. Each optimized operation map data is formed into a mathematical expression using an approximate expression for the fuel consumption, the power consumption, the operating range, and the like obtained in advance by a test, a simulation, and the like. Inside the system controller, energy demand map data for performing schedule control, a calendar, and a timer are set. In normal system operation, schedule operation is controlled from the energy demand map data and each optimized operation map data. On the other hand, when the energy demand map data and the actual energy demand greatly deviate, the load following control is immediately performed based on each optimized operation map data and the actual energy demand,
The amount of deviation at this time is stored in the storage device of the controller, and the energy demand map data is updated and used for future prediction of the load.

BEST MODE FOR CARRYING OUT THE INVENTION

Embodiment 1 FIG. 1 is a basic conceptual diagram of an energy supply device with control based on a driving operation map according to the present invention. The fuel supply device 4 includes a solar power generation device 5, a commercial power supply 6, and an engine generator 7. , 8, a solar heat collector, 10, a boiler, and 11 other energy devices, the system performs an optimized operation control based on a command given from a system controller operation result. A calendar and a timer are incorporated in the system controller 1. The energy demand map data 2 is corrected based on the history of the past energy demand, and the energy demand map data 3 is obtained in advance by test evaluation and simulation. System operation map data is also stored. The system operation map data of No. 3 is data that summarizes energy saving, low cost, reduction of exhaust gas, etc., and the values of power demand and heat demand required by 17 energy consumers,
The future demand is predicted while constantly comparing the demands obtained from the second energy demand database. At this time, the amount of heat stored in the 14 heat storage tanks, and the amount of heat produced and stored in the 18 electrolysis tanks when using the fuel cell 1
The difference between the optimized schedule operation control together with the system operation map data of 3 is constantly monitored by, for example, monitoring the remaining amounts of the hydrogen tank 9 and the oxygen tank 20 and the calculation of the optimization is performed again. Operation control. As for the power supply, a power supply system including a fuel cell 4, a solar power generator 5, and an engine generator 7 and a commercial power system 6 are individually connected to 13 switches. Since the power supply system is selected by the high-speed switch, no instantaneous interruption occurs. In addition, since a part of the electric power can be converted to heat by the 15 electric heaters installed in the 14 heat storage tanks, the operation is performed at the highest efficiency point in the internal combustion engine or the external combustion engine, and the surplus electric power is converted to heat. Heat can be stored. When the amount of heat supplied from the system is small relative to the demand, additional cooking can be performed with 16 auxiliary boilers.

FIG. 2 shows basic element data at the time of creating system operation map data when the relationship between the power generated by the engine generator and the amount of heat energy supplied is taken as an example. As for the various types of energy devices, the power output amount, the heat energy output amount, the energy loss amount, and the fuel consumption amount are previously tested or simulated as shown in the example of FIG. FIG. 1 shows basic element data for creating system operation map data when the engine speed, power output, and fuel consumption per power unit output of the engine generator are taken as examples. In this example, the power output with respect to the number of revolutions of the engine generator is described. However, for other energy devices, the relationship between the factor affecting the power output and the heat output and the amount thereof are obtained in advance.

Equation 1 shows a relational expression of the fuel consumption of the engine generator at the sampling time. A similar relational expression is introduced for all the components of the system such as the boiler.

(Equation 1) Equation 2 shows the relational expression of the jacket hot water heat output of the engine generator at the sampling time. A similar relational expression is introduced for all the components of the system such as the boiler.

(Equation 2) Equation 3 shows the relational expression of the exhaust gas heat output of the engine generator at the sampling time. A similar relational expression is introduced for all the components of the system such as the boiler.

(Equation 3) Equation 4 shows a constraint condition expression for the amount of fuel to be supplied to the engine generator. A similar constraint condition expression is given for all components constituting a system such as a boiler, using fuel consumption, flow rate, power consumption, and the like.

(Equation 4)

Equation 5 shows an operation cost calculation formula at the time of supply of commercial power and at the time of energy supply by the system at sampling time intervals. When additional energy equipment such as a separate boiler is added, each equation corresponding to this equation is added. In addition, equations for energy saving, environmental load, and the like are also given, and compared with conventional energy supply methods (such as power purchase, boilers, or existing facilities).

(Equation 5) Equation 6 shows the objective function of the control operation. In this case, the system is controlled to operate at a minimum cost for one day.
Other objective functions, such as energy saving and environmental load, are given and compared with conventional energy supply methods (such as power purchase, boilers or existing equipment).

(Equation 6) Equation 7 shows the objective function of the control operation. In this case, the system is controlled to operate at a minimum cost for one year.
Other objective functions, such as energy saving and environmental load, are given and compared with conventional energy supply methods (such as power purchase, boilers or existing equipment).

(Equation 7)

FIG. 2 is a flow chart of a calculation for determining the optimized operation of the system of the present invention. The system controller inputs an energy demand signal and compares this value with the energy demand prediction map data. If the difference is small, the flow proceeds to the schedule operation control flow. Proceed to flow. According to the flow of this figure, the system controller calculates the optimized operation at any time, and issues an operation control signal to the system. FIG. 3 shows the relationship between the operation of the system and the operating cost at each time on a representative day obtained by calculating the algorithm of FIG. In order to obtain an operating condition that minimizes the operating cost, it is determined by searching for the lowest valley in the vertical axis direction at each time. Similarly, a three-dimensional relationship similar to that in this figure is obtained for energy saving and environmental load.

FIG. 4 is map data showing the relationship between the system operation and the power and heat output created based on FIG. Since the calorific value of the fuel to be supplied for each operation is known, it can be used as a cost map by multiplying this by the fuel unit price. Similarly, such map data is provided for energy saving and environmental load. FIG. 5 is an example of the system operation when the schedule control and the load following control based on the optimized operation according to the first embodiment of the present invention are added.

[Brief description of the drawings]

FIG. 1 is a basic conceptual diagram of the present invention.

FIG. 2 is a diagram showing a relationship between fuel consumption of an engine generator and energy output.

FIG. 3 is a relationship between the number of revolutions of an engine generator, a power output, and a fuel consumption per unit power generation output.

FIG. 4 is a flowchart of a control algorithm according to the present invention.

FIG. 5 is a result graph of the operation of the system and the operating cost, as determined by the control algorithm.

FIG. 6 is an example of driving operation map data when the operation of the system is optimized.

FIG. 7 is an example of a control operation result of an energy supply system having a system controller equipped with a control algorithm according to the present invention.

Claims (1)

[Claims] 1. A power generating means using a solar cell module,
A means for supplying heat by sunlight, a means for generating power by a fuel cell, a means for supplying power generated by an internal combustion engine or an external combustion engine such as an engine or a gas turbine, and an energy supply means by exhaust heat thereof.
The operation of the system, energy costs, and energy supply facilities such as houses and condominiums that have multiple and / or multiple types of energy equipment equipped with boiler heat supply means and / or commercial power supply means The relationship between the operation of the system, and the relationship between the operation of the system and the environmental load such as exhaust gas emission, or the relationship between the operation of the system and energy saving is stored in the control computer as operation map data, and the power predicted in advance is stored. And the schedule data based on the demand data of heat are stored in the control computer, and the system is scheduled to be operated on the basis of the above operation map data according to the command of the control computer. At this time, the schedule data and the actual energy demand If the load deviates significantly, promptly follow the load following control. Controller of the energy supply system, characterized in that to perform the optimization operation of the stem.