WO2002057968A1 - Method in connection with a power plant - Google Patents

Method in connection with a power plant Download PDF

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Publication number
WO2002057968A1
WO2002057968A1 PCT/FI2002/000034 FI0200034W WO02057968A1 WO 2002057968 A1 WO2002057968 A1 WO 2002057968A1 FI 0200034 W FI0200034 W FI 0200034W WO 02057968 A1 WO02057968 A1 WO 02057968A1
Authority
WO
WIPO (PCT)
Prior art keywords
central unit
power
measurement data
power plants
energy
Prior art date
Application number
PCT/FI2002/000034
Other languages
French (fr)
Other versions
WO2002057968A8 (en
Inventor
Juha Vanhanen
Original Assignee
Gaia Group Oy
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Gaia Group Oy filed Critical Gaia Group Oy
Priority to GB0311965A priority Critical patent/GB2387694B/en
Priority to DE20280327U priority patent/DE20280327U1/en
Publication of WO2002057968A1 publication Critical patent/WO2002057968A1/en
Publication of WO2002057968A8 publication Critical patent/WO2002057968A8/en

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S50/00—Market activities related to the operation of systems integrating technologies related to power network operation or related to communication or information technologies
    • Y04S50/14—Marketing, i.e. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards

Definitions

  • the present invention relates to a method in connection with power plants connected to form a network, the network comprising a central unit and the power plants comprising a measurement and control unit.
  • This object is achieved by a method according to the invention, the method being characterized in that the central unit comprises time series models of the power plants connected to form the network, the method comprising the steps of collecting measurement data to the central unit from the power plants connected thereto; storing the measurement data in a database of the central unit; updating the power-plant-specific time series models stored in the central unit; drawing up at the central unit power-plant- specific forecasts of the energy need for the next time period; retrieving price information relating to the next time period from energy exchanges, or the like, to the central unit; computing at the central unit optimum power levels for the generating units on the basis of load and price forecasts; and transmitting control commands to the generating units.
  • the underlying idea of the method of the invention is that the performance values of power plants, the price information regarding the electricity and fuels used at the power plants and other known costs together provide a simple basis for computing an operating power that optimises the costs of the power plants.
  • the method of the invention provides significant advantages with regard to the costs of power plants, because with the method optimisation becomes automated and it is carried out in real time, on the basis of the most recent price information.
  • the system updates the performance values of the power plants included in its database and thereby adapts to the situation prevailing at a current moment.
  • the method can be implemented using existing equipment.
  • FIG. 2 is a flow diagram of the operation of the method of the invention.
  • Figure 3 shows optimum powers computed for a power plant on the basis of different loads and electricity prices.
  • a simplest form of an arrangement implementing the control method comprises a central unit 1 connected to one or more generating units, i.e. power plants 2, over a known data transfer connection.
  • the central unit uses the data transfer connection to collect data on the variables of the power plants and on energy consumption at end use points, and transmits, in turn, control commands to the power plants to provide optimum control thereof.
  • the method according to the invention comprises a step of collecting 3 measurement data from the power plants to the central unit.
  • the central unit is located in the premises of a service supplier, for example, or, in the simplest case, at the generating unit.
  • the measurement data to be transferred to the central unit include the energy produced at the generating unit, the amount of fuel consumed during the last time step, and the proportions of electric energy and thermal energy in the energy produced.
  • the measurement data transferred to the central unit is processed 4 to suit the intended purpose, and a database 6 residing in the central unit is updated 5 on the basis of the amount of energy consumed, the energy proportions and production efficiency.
  • the database of the central unit contains time series models stored therein for each end use point of a generating unit connected to the central unit, whereby it is possible to accurately estimate the energy consumption of the next time step.
  • the time series models are updated 7, if necessary, on the basis of the actual consumption.
  • the central unit uses said time series model as a basis for computing 8 a forecast of the energy need of each end use point 2 connected to the central unit for the next time period.
  • a time series model containing data on the actual energy consumption during previous time steps this computation is simple.
  • Power-plant-specific time series models illustrate the energy need of the end use point in question. If the actual consumption during the previous time step deviates significantly from the actual consumption on corresponding, cyclically recurring time instants of the time series model, the energy need of the next time step can be modified, if desired.
  • the time series model gradually adapts itself, and the model allows a reliable estimate of the energy consumption of the next time step to be made.
  • price information for the next time period is retrieved 9 into the central unit from energy exchanges 10, or the like.
  • An energy exchange determines the market prices of fuels and electric energy for a specific time period onward. For example, an electricity exchange sets what is known as a spot price for electricity, and electricity suppliers commit themselves to selling electricity at this price for an hour onward.
  • the real-time prices of fuels can be also checked from other similar exchanges that react rapidly to changes in the markets and quote momentary fuel prices.
  • One example of other possible energy exchanges is a natural gas exchange.
  • the transmission costs and the purchase prices of electricity are updated into the central unit.
  • the central unit computes 11 the optimum powers of generating units connected thereto on the basis of the load and price forecasts and transmits 12 control commands to the measurement and control equipment at the production units.
  • the optimum power is computed for each generating unit by comparing the viability of the different alternatives with regard to costs.
  • the level of the optimum power depends for example on the purchase price of electric energy, its transmission price, the market price of the fuel used at the generating unit and the capacity of the generating unit.
  • optimisation involves comparing the costs of local production with a competing alternative, which is typically electric energy purchased at a market price from an electricity supplier, its transmission at current rates, and thermal energy purchased from a heat supplier.

Abstract

A method in connection with power plants connected to form a network, the network comprising a central unit (1) and the power plants (2) comprising a measurement and control unit, wherein the central unit comprises time series models of the power plants connected to form the network, the method comprising the steps of collecting (3) measurement data to the central unit from the power plants connected thereto; storing (5) the measurement data in a database of the central unit; updating (7) the power-plant-specific time series models stored in the central unit; drawing up (8) at the central unit power-plant-specific forecasts of the energy need on the next time period; retrieving (9) price information relating to the next time period from energy exchanges, or the like, to the central unit; computing (11) at the central unit optimum power levels for the generating units on the basis of load and price forecasts; and transmitting (12) control commands to the generating units.

Description

METHOD IN CONNECTION WITH A POWER PLANT
BACKGROUND OF THE INVENTION
[0001] The present invention relates to a method in connection with power plants connected to form a network, the network comprising a central unit and the power plants comprising a measurement and control unit.
[0002] Current energy production is mostly centralized into large power plants from where energy is transmitted over long distances, the utilization of the plants being controlled by comparing the variable costs of the power plant with the current market price. Electricity and heat generation is, however, increasingly decentralized to take place at end user levels, or at their immediate proximity. These end users include hotels, spas, hospitals, greenhouses, or the like, where the amounts of energy consumed are fairly large and it is therefore economically viable to set up an independent power plant in connection with the site concerned. [0003] In recent years many countries have created separate electricity exchanges for electric energy trade to enable the price of electric energy to be monitored in real time. Through supply and demand the price of electricity sets at the exchange to a level corresponding to its real price, which serves as a reference level when comparisons between the output offered by electricity suppliers and the production costs are made.
[0004] Due to variations in market prices, production costs and transmission prices of electricity, a problem with end use points provided with power plants of their own is how to determine the cost level of the energy production in relation to energy purchased from outside in a reasonable and simple way. Moreover, it would be advantageous if an individual generating unit would not need to invest capital or personnel resources in such optimisation, but could purchase the optimisation from a service provider specialised in the field.
BRIEF DESCRIPTION OF THE INVENTION [0005] It is an object of the present invention to provide a method that avoids the above drawbacks and enables the amount of energy generated at a power plant to be optimised with a simple and reliable computation method. This object is achieved by a method according to the invention, the method being characterized in that the central unit comprises time series models of the power plants connected to form the network, the method comprising the steps of collecting measurement data to the central unit from the power plants connected thereto; storing the measurement data in a database of the central unit; updating the power-plant-specific time series models stored in the central unit; drawing up at the central unit power-plant- specific forecasts of the energy need for the next time period; retrieving price information relating to the next time period from energy exchanges, or the like, to the central unit; computing at the central unit optimum power levels for the generating units on the basis of load and price forecasts; and transmitting control commands to the generating units. [0006] The underlying idea of the method of the invention is that the performance values of power plants, the price information regarding the electricity and fuels used at the power plants and other known costs together provide a simple basis for computing an operating power that optimises the costs of the power plants. The method of the invention provides significant advantages with regard to the costs of power plants, because with the method optimisation becomes automated and it is carried out in real time, on the basis of the most recent price information. When carrying out the optimisation, the system updates the performance values of the power plants included in its database and thereby adapts to the situation prevailing at a current moment. In addition, the method can be implemented using existing equipment.
BRIEF DESCRIPTION OF THE DRAWINGS
[0007] In the following, the invention will be described in greater detail with reference to the preferred embodiments and the accompanying drawings, in which Figure 1 is a diagram of the method of the invention;
Figure 2 is a flow diagram of the operation of the method of the invention; and
Figure 3 shows optimum powers computed for a power plant on the basis of different loads and electricity prices.
DETAILED DESCRIPTION OF THE INVENTION
[0008] The method of the invention is illustrated with the diagrams shown in Figures 1 and 2. A simplest form of an arrangement implementing the control method comprises a central unit 1 connected to one or more generating units, i.e. power plants 2, over a known data transfer connection. The central unit uses the data transfer connection to collect data on the variables of the power plants and on energy consumption at end use points, and transmits, in turn, control commands to the power plants to provide optimum control thereof. [0009] The method according to the invention comprises a step of collecting 3 measurement data from the power plants to the central unit. The central unit is located in the premises of a service supplier, for example, or, in the simplest case, at the generating unit. Although a plural number of generating units is typically connected to a single central unit, the method of the invention is not restricted to be used in connection with a plural number of units but can also be applied in connection with a single generating unit. The measurement data to be transferred to the central unit include the energy produced at the generating unit, the amount of fuel consumed during the last time step, and the proportions of electric energy and thermal energy in the energy produced.
[0010] The measurement data transferred to the central unit is processed 4 to suit the intended purpose, and a database 6 residing in the central unit is updated 5 on the basis of the amount of energy consumed, the energy proportions and production efficiency. The database of the central unit contains time series models stored therein for each end use point of a generating unit connected to the central unit, whereby it is possible to accurately estimate the energy consumption of the next time step. At the same time with the storage of the above data into the database of the central unit, the time series models are updated 7, if necessary, on the basis of the actual consumption.
[0011] The central unit then uses said time series model as a basis for computing 8 a forecast of the energy need of each end use point 2 connected to the central unit for the next time period. With a time series model containing data on the actual energy consumption during previous time steps this computation is simple. Power-plant-specific time series models illustrate the energy need of the end use point in question. If the actual consumption during the previous time step deviates significantly from the actual consumption on corresponding, cyclically recurring time instants of the time series model, the energy need of the next time step can be modified, if desired. However, it is to be noted that the time series model gradually adapts itself, and the model allows a reliable estimate of the energy consumption of the next time step to be made. [0012] According to the invention, price information for the next time period is retrieved 9 into the central unit from energy exchanges 10, or the like. An energy exchange determines the market prices of fuels and electric energy for a specific time period onward. For example, an electricity exchange sets what is known as a spot price for electricity, and electricity suppliers commit themselves to selling electricity at this price for an hour onward. The real-time prices of fuels can be also checked from other similar exchanges that react rapidly to changes in the markets and quote momentary fuel prices. One example of other possible energy exchanges is a natural gas exchange. In addition, the transmission costs and the purchase prices of electricity are updated into the central unit.
[0013] When the price information needed for the next time period, such as the next hour, has been compiled, the central unit computes 11 the optimum powers of generating units connected thereto on the basis of the load and price forecasts and transmits 12 control commands to the measurement and control equipment at the production units. The optimum power is computed for each generating unit by comparing the viability of the different alternatives with regard to costs.
[0014] The level of the optimum power depends for example on the purchase price of electric energy, its transmission price, the market price of the fuel used at the generating unit and the capacity of the generating unit. In other words, optimisation involves comparing the costs of local production with a competing alternative, which is typically electric energy purchased at a market price from an electricity supplier, its transmission at current rates, and thermal energy purchased from a heat supplier.
[0015] In other words, economically optimum control is subject to frequent variations due to changes in consumption and prices. A distinct, individual factor that can be mentioned as having an impact on the control is for example the market price of the fuel, such as natural gas, used at a generating unit, when its price is affordable to such an extent that it is profitable to run the generating unit at the maximum power, or at a level close to it, whereby the end use point connected to the generating unit takes the electric energy it needs and the rest of the generated electricity is sold at the market price into the network for consumption by other end users. [0016] Another extreme in the optimisation is a situation where the price of electricity available for purchase is so low that independent electricity production is not economically viable. Even if there were no changes in the purchasing price of electricity, optimum control depends on the amount of energy needed and on the ratio of the electricity need to the need of thermal energy, for example. [0017] Most often the situation varies between the two extremes, and therefore optimisation carried out in time steps, at intervals of one hour, for example, provides clearly the best economic benefit for the generating unit. Figure 3 shows, by way of example, optimum values computed on different loads and electricity prices. The curves show the gain made by optimisation as FIM/hour as a function of the generating unit power. The peak values of the curves thus show the most economical operating power of the generating unit.
[0018] It is apparent to a person skilled in the art that as technology advances the basis idea of the invention can be implemented in various ways.
The invention and its embodiments are therefore not restricted to the above examples, but they may vary within the scope of the claims.

Claims

1. A method in connection with power plants connected to form a network, the network comprising a central unit (1) and the power plants (2) comprising a measurement and control unit, characterized in that the central unit comprises time series models of the power plants connected to form the network, the method comprising the steps of collecting (3) measurement data to the central unit from the power plants connected thereto; storing (5) the measurement data in a database of the central unit; updating (7) the power-plant-specific time series models stored in the central unit; drawing up (8) at the central unit power-plant-specific forecasts of the energy need for the next time period; retrieving (9) price information relating to the next time period from energy exchanges, or the like, to the central unit; computing (11) at the central unit optimum power levels for the generating units on the basis of load and price forecasts; and transmitting (12) control commands to the generating units.
2. A method according to claim ^ characterized in that the measurement data collected from the power plants comprise information about the amount of electric and thermal energy produced during the previous time period and the amount of fuel consumed to generate this energy amount.
3. A method according to claim 1 or 2, characterized in that the storing of the measurement data into the database comprises a step of processing the measurement data into a format suitable for the database, prior to the storage.
4. A method according to claim 3, characterized in that the processing of the measurement data comprises a step of forming values illustrating the efficiency of the power plant from the measurement data.
PCT/FI2002/000034 2001-01-18 2002-01-17 Method in connection with a power plant WO2002057968A1 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
GB0311965A GB2387694B (en) 2001-01-18 2002-01-17 Controlling power plants using time series models
DE20280327U DE20280327U1 (en) 2001-01-18 2002-01-17 Power plant renewal system

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
FI20010114A FI20010114A (en) 2001-01-18 2001-01-18 Procedure at power plants
FI20010114 2001-01-18

Publications (2)

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WO2002057968A1 true WO2002057968A1 (en) 2002-07-25
WO2002057968A8 WO2002057968A8 (en) 2003-10-30

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FI (1) FI20010114A (en)
GB (1) GB2387694B (en)
WO (1) WO2002057968A1 (en)

Cited By (4)

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Publication number Priority date Publication date Assignee Title
GB2405492A (en) * 2003-08-30 2005-03-02 Distant Control Ltd System for remote monitoring and control of power generating plant
GB2415809A (en) * 2004-06-25 2006-01-04 Emerson Process Management Method and apparatus for providing economic analysis of power generation and distribution
DE102007061604A1 (en) * 2007-12-20 2009-06-25 Alstom Technology Ltd. Optimization of the operation of a power plant
US9771834B2 (en) 2004-10-20 2017-09-26 Emerson Process Management Power & Water Solutions, Inc. Method and apparatus for providing load dispatch and pollution control optimization

Families Citing this family (1)

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Publication number Priority date Publication date Assignee Title
DE102017113926A1 (en) * 2017-06-23 2018-12-27 Rwe Power Aktiengesellschaft Method of operating a power plant

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US5621654A (en) * 1994-04-15 1997-04-15 Long Island Lighting Company System and method for economic dispatching of electrical power
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Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
GB2405492A (en) * 2003-08-30 2005-03-02 Distant Control Ltd System for remote monitoring and control of power generating plant
GB2405492B (en) * 2003-08-30 2008-01-02 Distant Control Ltd Method and apparatus for remote control of power plants
GB2415809A (en) * 2004-06-25 2006-01-04 Emerson Process Management Method and apparatus for providing economic analysis of power generation and distribution
US7190149B2 (en) 2004-06-25 2007-03-13 Emerson Process Management Power & Water Solutions, Inc. Method and apparatus for determining actual reactive capability curves
US7288921B2 (en) 2004-06-25 2007-10-30 Emerson Process Management Power & Water Solutions, Inc. Method and apparatus for providing economic analysis of power generation and distribution
US7385300B2 (en) 2004-06-25 2008-06-10 Emerson Process Management Power & Water Solutions, Inc. Method and apparatus for determining actual reactive capability curves
US7474080B2 (en) 2004-06-25 2009-01-06 Emerson Process Management Power & Water Solutions, Inc. Method and apparatus for providing economic analysis of power generation and distribution
GB2415809B (en) * 2004-06-25 2009-10-21 Emerson Process Management Method and apparatus for providing economic analysis of power generation and distribution
US9771834B2 (en) 2004-10-20 2017-09-26 Emerson Process Management Power & Water Solutions, Inc. Method and apparatus for providing load dispatch and pollution control optimization
DE102007061604A1 (en) * 2007-12-20 2009-06-25 Alstom Technology Ltd. Optimization of the operation of a power plant

Also Published As

Publication number Publication date
FI20010114A (en) 2002-07-19
GB2387694B (en) 2005-05-04
FI20010114A0 (en) 2001-01-18
WO2002057968A8 (en) 2003-10-30
GB0311965D0 (en) 2003-06-25
GB2387694A (en) 2003-10-22
DE20280327U1 (en) 2003-09-18

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