White Paper: Fuel Price Optimization Application

Prepared for: Plant Requiring Multi-Fuel Sourcing
Prepared by: [Your Name / The Patel AI Lab]
Date: [Insert Date]

1. Executive Summary

To address the growing need for intelligent and cost-effective fuel management in plants that rely on multiple fuel sources, we introduce the Fuel Price Optimization Application. This web-based tool is designed to support operational and procurement decisions by optimizing the use of Natural Gas (e.g., from GAIL, IOCL) and Furnace Oil (FO) through real-time data analytics and pricing logic.

It empowers energy planners and plant managers to make data-driven fuel sourcing decisions, reduce operational costs, and monitor environmental impacts.

2. Objective

The primary objective of this application is to:

• Track live and historical prices of key fuels (Henry Hub, Brent).

• Optimize fuel usage based on plant-specific constraints and availability.

• Forecast the cost of thermal energy in terms of MMBTU and output tonnage.

• Minimize CO₂ emissions and enable cost-carbon analysis.

3. Key Input Parameters

Users can configure the application through the following inputs:

ParameterDescriptionDefault / OptionsThermal Energy DemandDaily energy requirement (Gcal)User-definedPrice SourceLive Henry Hub/Brent feed or manual inputLive / ManualPrice Slope % & ConstantAdjustments for tax, transport, and bilateral termsUser-definedEnergy AvailabilityDaily min-max supply for each fuel typeUser-definedCarbon Cost (Optional)Enables CO₂ pricing scenariosOptional entry

4. Optimization Outputs

Once configured, the tool delivers:

• Natural Gas Price per MMBTU – Real-time or adjusted fuel cost.

• Cost of Energy per Ton of Output – Effective pellet production cost.

• Recommended Fuel Mix – Ideal split from available sources.

• Total Fuel Cost – For selected timeframes.

• Daily CO₂ Emissions & Carbon Cost – Environmental analysis.

• Fuel Mix Chart – Interactive, responsive bar chart.

• Historical Trends – Prices for Henry Hub, Brent, and USD/INR (3-year view).

• Custom Date Range Selector – Flexible time-based analysis.

• Data Download – Access raw datasets in Excel/CSV format.

5. Data Customization Options

• Default setup includes live market prices.

• Option available to switch to 3-month moving averages or fixed contract prices.

• User-defined entries enable simulation under customized pricing models.

6. Access & Evaluation

Please use the following link to access the application:

[Insert Application URL here]

We encourage users to:

• Test the app’s flexibility and user interface.

• Evaluate its accuracy in simulating plant operations.

• Share insights or requests for future feature integration.

7. Future Expansion

The system is modular and may be expanded to include:

• Solid fuel (e.g., coal) cost optimization

• Plant-specific heat rate modeling

• Scheduled auto-report generation

• ERP or SAP integration

8. Contact Information

For queries, technical support, or suggestions:

[Your Name]
Developer – Fuel Price Optimization Tool
[Your Email Address]
[Your Contact Number]

Appendix

• Glossary:

  • MMBTU: Million British Thermal Units

  • FO: Furnace Oil

  • USD/INR: Exchange Rate (US Dollar / Indian Rupee)

• Reference Data Sources:

  • Henry Hub – U.S. Energy Information Administration (EIA)

  • Brent Crude – ICE Exchange

  • Forex – Yahoo Finance API

Would you like this document exported as a Word or PDF file for sharing?

You said:

i wanted not to share url , but provide the snap shots of application and its feature to walkthrough each features.

ChatGPT said:

Understood. Here's a revised white paper document tailored to showcase your Fuel Price Optimization Application through snapshots and feature walkthroughs, without sharing the URL.

White Paper: Fuel Price Optimization Application

Prepared for: Plants Requiring Multi-Fuel Sourcing
Prepared by: [Your Name / The Patel AI Lab]
Date: [Insert Date]

1. Executive Summary

This document presents an overview and feature walkthrough of the Fuel Price Optimization Application, developed to support plants that rely on multiple fuel sources—particularly natural gas (from suppliers like GAIL, IOCL) and furnace oil.

The application leverages real-time and historical fuel pricing data to optimize the fuel mix, reduce operational costs, and minimize carbon emissions. This white paper walks through the tool using annotated screenshots in place of live access.

2. Purpose and Use Case

The tool is designed to help operations, energy planning, and procurement teams:

• Track dynamic fuel prices from global benchmarks.

• Simulate cost scenarios based on contractual terms.

• Choose the most cost-effective fuel mix daily.

• Quantify environmental impacts in CO₂ terms.

• Visualize and analyze historical pricing trends.

3. Application Walkthrough

3.1 Input Configuration Panel


Inputs:

• Thermal Energy Demand (Gcal/day): User-defined daily requirement.

• Price Source: Live feed (Henry Hub, Brent) or manual input.

• Price Slope % and Constant: Used to adjust base price to delivered cost.

• Min/Max Energy Availability: Enter supply constraints for each fuel.

• Carbon Cost (optional): Add CO₂ pricing per ton for simulation.

3.2 Optimization Output Summary


Displays:

• Natural Gas Price (MMBTU)

• Energy Cost per Ton of Output

• Optimal Fuel Mix (NG-GAIL, NG-IOCL, FO)

• Total Fuel Cost per Day

• Carbon Emissions (tCO₂/day) and Cost (if enabled)

3.3 Fuel Mix Visualization


• Interactive bar chart shows percentage-wise fuel distribution.

• Dynamically updates based on input configuration.

3.4 Historical Price Trend Analysis


• 3-year price charts for Henry Hub, Brent, and USD/INR.

• Options to toggle individual datasets.

• Provides context for strategic sourcing decisions.

3.5 Date Range Selection & Raw Data Export


• Users can select custom date ranges.

• Raw data for price trends and results can be downloaded in CSV format.

4. Key Advantages

• Customizable: User-driven configuration and adjustable pricing logic.

• Visual & Intuitive: Designed for non-technical users and decision-makers.

• Data-Rich: Leverages global benchmarks for real-time insights.

• Scalable: Ready for extension to additional fuel types and contract logic.

5. Next Steps

• Review the screenshots and explore key features.

• Share feedback for enhancements or plant-specific customization.

• Consider pilot use with real operational data and historical prices.

6. Contact for Demonstration / Deployment

[Your Name]
Developer – Fuel Price Optimization Tool
Email: [Your Email]
Phone: [Your Contact Number]

Appendix: Definitions & References

• MMBTU: Million British Thermal Units

• FO: Furnace Oil

• CO₂ Cost: Monetary value per ton of carbon emitted

• Henry Hub & Brent: Global natural gas and crude oil pricing indices

• USD/INR: Exchange rate tracker