Operation support system and method

Abstract

An operation support system is arranged to effectively provide an operator of an energy supply facility for supplying a plurality of energies in different forms with guide information of an operating method in which energy safety supply and operation cost reduction are both realized. The operation support system takes the steps of deriving demand prediction upper limit value and lower value for each energy form based on recorded demand data; deriving target operation pattern upper and lower limit values of each energy supply device based on the demand prediction upper and lower values; and displaying the target operation pattern upper and lower limit values.

What is claimed is:  
     
         1 . An operation support method for an energy supply facility having a plurality of energy forms, comprising: 
 deriving demand prediction upper and lower limits for each energy form;    calculating target operation pattern upper and lower limits corresponding to each energy form based on the demand prediction upper and lower limits; and    displaying the target operation pattern upper and lower limits.    
     
     
         2 . An operation support method of an energy supply facility having a plurality of energy forms, comprising: 
 deriving a demand prediction probability density distribution for each energy form;    calculating target operation pattern probability distributions corresponding to each energy form based on the demand prediction probability density distribution; and    displaying the target operation pattern probability density distributions.    
     
     
         3 . An operation support method as claimed in  claim 2 , further comprising setting upper and lower limits of the target operation pattern so that an integrated value of the target operation pattern probability density distribution between the upper and the lower limits of the target operation pattern may become a specified value.  
     
     
         4 . An operation support method as claimed in  claim 2 , wherein the displaying shows a time, a point of the target operation pattern corresponding to a peak of the target operation pattern probability density distribution, and the target operation pattern probability density distribution in three-dimensional axes.  
     
     
         5 . An operation support method as claimed in  claim 1 , further comprising generating an alarm signal if the actual operation pattern departs from a range between the upper and the lower limits of the target operation pattern.  
     
     
         6 . An operation support method as claimed in  claim 2 , further comprising generating an alarm signal if the actual operation pattern departs from a range between the upper and the lower limits of the target operation pattern.  
     
     
         7 . An operation support method according to  claim 1 , wherein the deriving step includes retrieving past demand data having matched conditions for an object of the demand prediction, and deriving demand prediction upper and lower limits of each energy form based on retrieved past demand data.  
     
     
         8 . An operation support method according to  claim 2 , wherein the deriving step includes retrieving past demand data having matched conditions for an object of the demand prediction, and deriving demand prediction upper and lower limits of each energy form based on retrieved past demand data.  
     
     
         9 . An operation support method according to  claim 7 , wherein the calculating step includes extracting sample data from retrieved past demand data between the demand prediction upper and lower limits of each energy form, deriving optional operation pattern corresponding to the each sample data, and assigning maximum value and minimum value from the optional operation pattern to the target operation.  
     
     
         10 . An operation support method according to  claim 8 , wherein the calculating step includes extracting sample data from retrieved past demand data between the demand prediction upper and lower limits of each energy form, deriving optional operation pattern corresponding to the each sample data, and assigning maximum value and minimum value from the optional operation pattern to the target operation.  
     
     
         11 . An operation support method of an energy supply facility having a plurality of energy forms, comprising: 
 deriving demand prediction upper and lower limits of each energy form;    deriving a demand prediction probability density distribution of each energy form;    calculating target operation pattern probability distributions corresponding with each energy form based on the upper and lower limits and the demand prediction probability density distribution,    setting upper and lower limits of the target operation pattern based on the target operation pattern probability distributions and a specified probability value; and    displaying the target operation pattern probability density distributions including the upper and lower limits of the target operation pattern probability density distributions.    
     
     
         12 . An operation support method according to  claim 1 , wherein the plurality of energy forms includes a gas turbine generating electric power and steam, a steam turbine generating electric power by using steam, an absorption refrigerator supplying chilled water by using steam, and a gas boiler generating steam.  
     
     
         13 . An operation support method according to  claim 2 , wherein the plurality of energy forms includes a gas turbine generating electric power and steam, a steam turbine generating electric power by using steam, an absorption refrigerator supplying chilled water by using steam, and a gas boiler generating steam.  
     
     
         14 . An operation support method according to  claim 11 , wherein the plurality of energy forms includes a gas turbine generating electric power and steam, a steam turbine generating electric power by using steam, an absorption refrigerator supplying chilled water by using steam, and a gas boiler generating steam.  
     
     
         15 . An operation support method according to  claim 12 , wherein, 
 the deriving step includes retrieving past demand data having matched conditions for an object of the demand prediction, the past demand data including past demand of electric power, steam, and chilled water with at least one of day, weather, and temperature, and calculating each average demand value and standard deviation of electric power, steam, and chilled water based on retrieved past demand data, and deriving demand prediction of upper and lower limits of electric power, steam, and chilled water,    the calculating step includes calculating target operation pattern upper and lower limits of the gas turbine, steam turbine, absorption refrigerator, and gas boiler corresponding to the derived demand prediction of upper and lower limits of electric power, steam, and chilled water.    
     
     
         16 . An operation support method according to  claim 13 , wherein, 
 the deriving step includes retrieving past demand data having matched conditions for an object of the demand prediction, the past demand data including past demand of electric power, steam, and chilled water with at least one of day, weather, and temperature, and calculating each average demand value and standard deviation of electric power, steam, and chilled water based on retrieved past demand data, and deriving demand prediction of upper and lower limits of electric power, steam, and chilled water,    the calculating step includes calculating target operation pattern upper and lower limits of the gas turbine, steam turbine, absorption refrigerator, and gas boiler corresponding to the derived demand prediction of upper and lower limits of electric power, steam, and chilled water.    
     
     
         17 . An operation support method according to  claim 14 , wherein, 
 the deriving step includes retrieving past demand data having matched conditions for an object of the demand prediction, the past demand data including past demand of electric power, steam, and chilled water with at least one of day, weather, and temperature, and calculating each average demand value and standard deviation of electric power, steam, and chilled water based on retrieved past demand data, and deriving demand prediction of upper and lower limits of electric power, steam, and chilled water,    the calculating step includes calculating target operation pattern upper and lower limits of the gas turbine, steam turbine, absorption refrigerator, and gas boiler corresponding to the derived demand prediction of upper and lower limits of electric power, steam, and chilled water.    
     
     
         18 . An operation support system for supporting operation of an energy supply facility having a plurality of energy forms, comprising: 
 a data storage to store demand data of past demand for each energy forms;    a processor to perform demand prediction process and target operation pattern calculation process;    a display displaying target operation pattern calculated by the processor;    a program executed by the processor, wherein execution of the program by the processor causes the processor to implement a series of steps, comprising: 
 deriving demand prediction upper and lower limits for each energy form based on the demand data stored in the data storage; and  
 calculating target operation pattern upper and lower limits corresponding to each energy form based on the demand prediction upper and lower limits.  
   
     
     
         19 . An operation support system for supporting operation of an energy supply facility having a plurality of energy forms, comprising: 
 a data storage to store demand data of past demand for each energy forms;    a processor to perform demand prediction process and target operation pattern calculation process;    a display displaying target operation pattern probability density distributions target operation pattern probability density distributions calculated by the processor;    a program executed by the processor, wherein execution of the program by the processor causes the processor to implement a series of steps, comprising: 
 deriving a demand prediction probability density distribution for each energy form based on the demand data stored in the data storage; and  
 calculating target operation pattern probability distributions corresponding to each energy form based on the demand prediction probability density distribution.  
   
     
     
         20 . A software product for operation support system having a data storage, a processor, and a display, the product comprising: 
 at least one processor readable medium;    programming code, carried by the at least one medium, for execution by the processor, wherein execution of the programming code by the processor causes the system to implement a series of steps, comprising: 
 deriving demand prediction upper and lower limits for each energy form based on the data stored in data storage;  
 calculating target operation pattern upper and lower limits corresponding to each energy form based on the demand prediction upper and lower limits; and  
 displaying the target operation pattern upper and lower limits.  
   
     
     
         21 . A software product for operation support system having a data storage, a processor, and a display, the product comprising: 
 at least one processor readable medium;    programming code, carried by the at least one medium, for execution by the processor, wherein execution of the programming code by the processor causes the system to implement a series of steps, comprising: 
 deriving a demand prediction probability density distribution for each energy form based on the data stored in data storage;  
 calculating target operation pattern probability distributions corresponding to each energy form based on the demand prediction probability density distribution; and  
 displaying target operation pattern probability density distributions.  
   
     
     
         22 . A cogeneration energy supply system comprising: 
 two or more energy sources for generating energy; and,    an operation support system comprising: 
 data storage to store demand data of past demand for each energy sources;  
 a processor to perform demand prediction process and target operation pattern calculation process; and  
 a display displaying target operation pattern calculated by the processor;  
 wherein, the processor derives demand prediction upper and lower limits for each energy sources based on the demand data stored in the data storage and calculates target operation pattern upper and lower limits corresponding to each energy sources based on the demand prediction upper and lower limits.  
   
     
     
         23 . A cogeneration energy supply system comprising: 
 two or more energy sources for generating energy; and,    an operation support system, comprising: 
 data storage to store demand data of past demand for each energy sources;  
 a processor to perform demand prediction process and target operation pattern calculation process; and,  
 a display displaying target operation pattern probability density distributions target operation pattern probability density distributions calculated by the processor;  
 wherein the processor derives a demand prediction probability density distribution for each energy source based on the demand data stored in the data storage; and calculates target operation pattern probability distributions corresponding to each energy source based on the demand prediction probability density distribution.  
   
     
     
         24 . A cogeneration energy supply system according to  claim 22 , wherein 
 each energy sources are selected from the group the group consisting essentially of a gas turbine generating electric power and steam, a steam turbine generating electric power by using steam, an absorption refrigerator supplying chilled water by using steam, and a gas boiler generating steam.    
     
     
         25 . A cogeneration energy supply system according to  claim 23 , wherein 
 each energy sources are selected from the group the group consisting essentially of a gas turbine generating electric power and steam, a steam turbine generating electric power by using steam, an absorption refrigerator supplying chilled water by using steam, and a gas boiler generating steam.