FORM 2
THE PATENTS ACT  1970
(39 of 1970)
&
THE PATENT RULES  2003

PROVISIONAL SPECIFICATION

(See Section 10 and Rule 13)

Title of invention:
DEVICE  SYSTEM AND METHOD FOR POWER FORECASTING  OPTIMIZAION AND MANAGEMENT

APPLICANT:

Mzaya Private Limited
A company Incorporated in India under The Companies Act  1956
Having address:
B-26/27  Goodwill Assurance Building
Manmala Tank Road  Mahim  Mumbai 400016

The following specification describes the invention.

FIELD OF THE INVENTION:

The present invention generally relates to improving efficiencies of power utilities leveraging dynamic load forecasting  Scheduling and portfolio optimization in a stochastic environment. More particularly the invention relates to a device / system that enables energy utilities to make forward looking strategy which helps improve the overall system efficiency leveraging both exogenous and real time endogenous information leveraging state of the art quantitative techniques & decision information technologies.

BACKGROUND OF THE INVENTION:

The power industry value chain comprises Power Generators  Distributors and Transmitters  each having their own parameters that change dynamically to affect the available power to end consumer at the same time the cost at which this power is made available. The availability of sufficient power to consumers (whether industrial  agricultural or household) is important for economic growth and human development.

While on the demand side the drawl schedule is ever changing due to various observed and unobserved factors like weather condition  events and other macro factors on the supply side the available capacity and hence the power which can potentially be made available is fixed except for sources like wind or solar power where the available power is a function of weather parameter.

While the distributor face the challenge of being able to foresee the likely demand schedule and accordingly schedule power with generators. On the other hand the generators have to ensure that its its able to ramp up/down its units in order to be able to meet the desired load shape almost real time given that energy as a commodity is very expensive to store. Moreover  one also need to ensure that given the transmission capacity one do not want to get caught in a situation where though the power is available  could not be transmitted due to transmission capacity constrain. Hence  it becomes utmost important to distribute power procurement across units optimally.
An intelligent system of control is therefore required to ensure that the positions on the demand and supply side is appropriately mapped real time and to ensure that the sources of supply is distributed in such a way the available transmission does not become a constrain where every one starts drawing from a particular zone just because the tariffs were more lucrative but then could not deliver to the end consumer due to transmission congestions.

Several models and methods have been tried to address individual component but none has looked at it in an integrated manner where linkages are so strong. This invention looks at the complete energy market in an integrated fashion and hence being able to optimize the system as a whole to be able to increase available power at a reduced cost given the constraint.

OBJECTS OF THE INVENTION:

The primary objective of the present invention is to provide a system that acts as a platform for delivering customized solution to enable power utilities to make informed decisions regarding various activities of the power value chain.

Another object of the present invention is to provide a system that is capable of power load forecasting (short and medium term)  network planning and optimization  power procurement planning and analysis  invoice generation and billing reconciliation.

Another object of the present invention is to provide a method and system for managing a utility whereby the procurement and trading done by the utility can be effected in an economic and automatic fashion using the internet and intranet.

Another significant objective of the invention is to provide a forecasting engine that is adapted to new data and parameters and flexible to accommodate event database to capture special conditions.

Another significant objective of the invention is to provide a simulation engine that provides scenario analysis capability for better decision making.
Yet another objective of the invention is to optimize ramp up and ramp down across plants and units.

Yet another objective of the invention is to identify trading opportunities in the market.

Yet another objective of the invention is to reduce Unscheduled Interchange  Bilaterals and spot market power procurement charges.

Another object of the present invention is to reduce maintenance costs and use capacity optimally with minimal outage times.

Another object of the present invention is to maintain reasonable electric power consumption policy and forecasting and managing peak electric power  by forecasting total amount of electric power use and the amount of short-term electric power consumption at intervals of 15 minutes by class of industry and class of contract according to a customer baseline load (CBL).

BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWINGS

The foregoing objectives and the following description of the invention  is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the invention  there is shown in the drawings example constructions of the invention; however  the invention is not limited to the specific system and method disclosed in the drawings.

Figure 1 illustrates a system flow diagram of the process of delivering customized solution.

Figure 2 illustrates the various required inputs for portfolio optimization module.

Figure 3 illustrates the broad level system architecture of the present invention.

DESCRIPTION OF THE INVENTION

The invention will now be described with reference to the accompanying drawings which do not limit the scope and ambit of the invention. The description provided is purely by way of example and illustration.

While considerable emphasis has been placed herein on the particular features of this invention  it will be appreciated that various modifications can be made  and that many changes can be made in the aspects without departing from the principles of the invention. These and other modifications in the nature of the invention or the aspects will be apparent to those skilled in the art from the disclosure herein  whereby it is to be distinctly understood that the foregoing descriptive matter is to be interpreted merely as illustrative of the invention and not as a limitation.

Referring now to Figure 1 is a system flow diagram illustrating the process of delivering customized solution.

One of the aspects of the present invention relates to a system for providing a platform for delivering customized solution to enable power utilities to make informed decisions.

The said system comprises a device that is communicatively coupled to various data sources including but not limited to the Utility exchanges  servers that transmit information related to power generation  demand and agreements related to the power purchase.

In accordance with various embodiments of the present disclosure  the methods described herein are intended for operation as software programs modules running on a computer processor. The device as disclosed is configured to store executable program instructions in its memory as functional modules wherein each functional module consists of the sequence of instructions necessary for performance of a particular function. Each such module will now be discussed in detail.

1. Simulation Engine Module: The simulation engine module provides scenario analysis capability for better decision making using the data related to various paramters which potentially can affect load shape  Peak demand  power availability / supply and demand change scenarios and hence the price rule which is likely to prevail. The demand change scenarios further depends upon but not limited to weather change (rainfall whether scarce or in excess)  Micro and macroeconomic variable change (recession)  price sensitivity (tariff fluctuations or change in policies) and power usage elasticity (energy conservation)  innovation etc.

2. Industry Book module: An Industry Book module captures plant’s configuration and individual unit’s parameters. It also stores fuel / commodity price risk negotiation which are further depend upon but not limited to fuel formula / market pricing  hedge ratio  equivalent electricity in MW units and optimal fuel mix generation. Industrial book is treated as real option where one chooses to run the captive unit or buys from the market depending on prevailing price. Hence one exercise on capacity at which one is going to run. It also helps generators to estimate the hedge for the input fuel which may or may no be a traded commodity. For example  gas price might be a formula based and hence any hedge against changes in fuel cost is done in the form of position on the traded commodity which is energy in this case.

3. Trade Book module: A trade book module captures a power purchase agreements between two parties such as long term contracts  short term contracts along with associated data thereof e.g. Trading margin  open access and miscellaneous charges. It also maintains exchange contracts  conditions as well as energy and transmission charges. The trade book works like a bidding platform where the utilities are able to bid optimally. It helps the user to estimate the right bidding price leveraging game theoretic framework.

4. Transaction Book Module: A transaction book module captures and maintains the history of transactions in the trading book and also insures that all the back end activities related to trade book which are transactional in nature are captured and linked with the invoicing and billing system so as to ensure none of the fees/charges are missed out. This takes away the operational risk which many utilities are running today.

The said back office component of the system adopts common tariffs including following parameters but not limited to capacity charges  base energy charges  fuel price adjustments  reactive power charges  taxes  trading margin  transmission charges  operating charges. Further the price setup module comprises Invoice generation module that accepts the user defined pricing /cost formulas. Further the invoice generation module is flexible to accept the user defined invoice structure and capable of integrating the invoice data source with the financial decision making process. The said module is also adapted to create an Invoice and able to generate a flag based on one of the parameters in the invoice. Further  the said module provides reminder if the data payment is breached

5. Price Forecast module:
This particular module has two components
Short term: the Short term price forecasting engine has the ability to simulate frequency in the network and hence the price likely to prevail given the injection to and drawal from the system. This modules helps simulate day ahead  intra day and weekly price movements.
Medium and long term: The medium and long term price simulator operates like a long-term exchange where given the available declared and non-declared capacity including planned and commissioned and the demand curve  in a given regulatory environment simulates the price rule. This allows the user to simulate the forward price not just due the demand and supply side but also the structure of the market which is a function of no of players in the market  demand supply situation i.e. excess in demand or excess in supply and the regulatory environment.

6. Demand Forecast Module: One of the preferred aspects of the present invention provides a forecasting engine that is adapted to new data and parameters and flexible to accommodate event database to capture special conditions. Further  the forecasting engine is a hybrid engine that combines the power of various techniques like neural networks  Fuzzy systems  regression based linear and non linear models. It works seamlessly with ingest module for data feeding and data output. The forecasting engine considers various parameters like but not limited to short term  long term  medium term and price forecast. Further the forecasting engine consider the following parameters but not limited to weather conditions  temperature  calendar  historical demand  macro economic conditions  consumer segment.

A hybrid approach is used where first the series of models are trained once the estimates are available  the weights to individual models are assigned dynamically so as to ensure we are able to get the best possible forecast since it is possible that different models will give different level of accuracy for various part of energy demand distribution. Utilities across the globe have been struggling to get the accurate forecast for the energy load given the strong non-linerities and sometimes reversal of effects.

The present invention also provides a system for supporting reasonable electric power consumption policy and forecasting and managing peak electric power  by forecasting total amount of electric power use and the amount of short-term electric power consumption at intervals of 15 minutes by class of industry and class of contract according to a customer baseline load (CBL) and by selecting an optimal short-term forecasting value as a result of comparing forecast models.

7. Portfolio Optimization Module: A portfolio optimization module provides an optimized solution based on the following constraints but not limited to contracts  their obligations and rules  power surplus or short fall estimation  spot and day ahead market availability and rate. Further  the portfolio optimization module identifies optimal bidding strategy taking into account competitors’ strategy. Figure 2 illustrates the various required inputs for portfolio optimization module. The said module has further two types:
1. Short Term: It covers a span of 1 year. In this module the scenarios can be imported from simulation module.
2. Medium/Long Term: It covers a span of 1-5 years for medium term and on a yearly basis for 20 years horizon for long term. In this module also the scenarios can be imported from simulation module.

8. Power Flow Module: A power flow module minimizes operating cost of generation plants. Further it reduces system failure and improves customer satisfaction. It has various constraints include but not limited to load balance  spinning reserve  down time limits  CO2 emissions and ramp rate limits.

9. Network Flow Module: A network flow module captures the availability of supply from different source along with the risk associated to the expected supply of electricity from different sources. Further  it checks the availability of electricity from different sources. An output of the said module is given to portfolio optimization module and position mapping module for further processing.

10. Position Mapping Module: A position mapping module identifies a gap between demand and supply chain that is used in efficiency gain in Power procurement and sell. The position mapping module provides an enterprise wide snap shot of position gap at varying levels of granularity.

In one aspect  the system and method of the current invention enables the user to model near accurate future scenarios for making short  medium and long term contracts by considering forecasted data of demand and the demand and supply gap of the commodity.

In another aspect  the system and method of the current invention enables the generation units to generate optimal schedules for a certain time period (e.g. 24 hours) in order to minimize operating costs by considering constraints including load balance  spinning reserve  down time limits  Co2 emissions and ramp rate limits.

In another aspect  the system and method of the current invention enables automatic generation of work flows for power procurement  contract approval  Availability based tariff and allows open access booking and management.
In another aspect  the system and method of the current invention  on its own or in conjugation with existing ERP systems  is capable of setting up various scenario specific tariff information for billing and auditing that is configurable and user friendly.

In Fig. 3  in the system architecture of the present invention various components including the device have been shown enabling the effective implementation of a system that is integrated with the intelligent device. While various aspects have been shown and described  it will be understood that there is no intent to limit the application by such disclosure  but rather  it is intended to cover all modifications and alternate constructions falling within the spirit and scope of the application.

The methodology and techniques described with respect to various aspects can be performed using a device or other computing device within which a set of instructions  when executed  may cause the device to perform any one or more of the methodologies discussed above. In some embodiments  the device operates as a standalone device. In some embodiments  the device may be connected (e.g.  using a network) to other machines.

While considerable emphasis has been placed herein on the particular features of this invention  it will be appreciated that various modifications can be made  and that many changes can be made in the preferred aspects without departing from the principles of the invention. These and other modifications in the nature of the invention or the preferred aspects will be apparent to those skilled in the art from the disclosure herein  whereby it is to be distinctly understood that the foregoing descriptive matter is to be interpreted merely as illustrative of the invention and not as a limitation.

Dated this 24th day of December  2011

Priyank Gupta
Agent for Applicant
IN-PA-1454

ABSTRACT

The present invention provides a device and a system that enable power utilities to make informed decisions and a method thereof. The system provides a platform for load forecasting  network planning and optimization  power procurement planning and analysis  Generation schedule recommendation  Invoice generation and billing reconciliation and portfolio optimization.