METHOD AND SYSTEM FOR INTERMEDIATE TO LONG-TERM FORECASTING OF ELECTRIC PRICES AND ENERGY DEMAND FOR INTEGRATED SUPPLY-SIDE ENERGY PLANNING

• US 20130013376A1
• Filed: 09/14/2012
• Published: 01/10/2013
• Est. Priority Date: 09/22/2009
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Kalagnanam, Jayant R., Subramanian, Dharmashankar
• Application Number:
  US13/618,907
• Publication Number:
  US 20130013376A1
• Time in Patent Office: Days
• US Class Current: 705/7.35
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/067 Enterprise or organisation modelling
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis
• CPC Class Codes: G06Q 50/06 Energy or water supply

Abstract

A method of price forecasting in an electrical energy supply network and/or load (energy demand) forecasting of a given consumer of electrical energy, in the context of an electrical energy supply network that is adapted to supply electrical energy to a number consumers connected to the network. The method includes developing a multi-regime, regime switching stochastic model for determining day ahead/spot market energy prices using at least one historical profile and subjective opinion from at least one expert; and the multiple regimes correspond to a number of combinations of physical factors. A regime is identifiable by at least three factors. The method thus facilitates identifying the optimal mix of energy hedge and exposure to day ahead/spot market prices for deriving economic benefits in overall energy expenditure.

Claims

1. A method of price forecasting in an electrical energy supply network and/or load (energy demand) forecasting of a given consumer of electrical energy, in the context of an electrical energy supply network that is adapted to supply electrical energy to a number consumers connected to the network, for identifying the optimal mix of energy hedge and exposure to day ahead/spot market prices for deriving economic benefits in overall energy expenditure, the method comprising;

selecting a time frame of at least one month;

selecting a set of hedge contracts for the time frame of at least one month with purchase price and sell back logic for unused energy;

computing, using the time frame and hedge contract selections, the overall energy expenditure distribution and quantify risk of exceeding a user defined known threshold;

applying numerical and simulation techniques to obtain a solution; and

generating, using said the obtained solution, sample sets of various volatile quantities consistent with the physical understanding and intra-/inter-variable temporal correlation,

wherein a program using a processor unit runs one or more of said selecting a time frame, selecting a set of hedge contracts, computing, applying and generating steps.

2. A method of price forecasting in an electrical energy supply network and/or load (energy demand) forecasting of a given consumer of electrical energy, in the context of an electrical energy supply network that is adapted to supply electrical energy to a number consumers connected to the network, for identifying the optimal mix of energy hedge and exposure to day ahead/spot market prices for deriving economic benefits in overall energy expenditure, the method comprising;

selecting a time frame of at least one month;

selecting a set of hedge contracts for the time frame of at least one month with purchase price and sell back logic for unused energy;

computing, based on the selections, rate structure details, and candidate set of energy hedge blocks along with minimum block size and minimum duration of purchase;

computing a set of hedge blocks with size and duration of coverage and real time and day ahead exposure using the result of the above computing; and

using stochastic mathematical programming techniques for obtaining a result,

wherein a program using a processor unit runs one or more of said selecting a time frame, selecting a set of hedge contracts, using, computing, and using stochastic mathematical programming techniques steps.