Optimizing Pricing for Natural Gas Distribution
BG Group (formerly part of British Gas) is a global energy company, specializing in production, transport, and supply of natural gas. Headquartered in London, with production and distribution operations in five continents from Kazakhstan to Bolivia, its 2004 revenues were £4,08 billion ($7.2 billion).
Setting energy prices for consumers in competitive markets is particularly challenging for regulated utilities. The company aims to maximize business value while meeting constraints of public regulatory agencies.
BG Group wanted an analytic decision tool to explore and optimize the effects of changing consumer tariffs, to be used by natural gas distribution companies in several parts of the world, including South America and India.
The tool had to model the price elasticity of demand, capital investments, and the effects on operating costs over time. This information feeds a financial model to evaluate the effect on financial returns and company value.
The model was originally developed as a spreadsheet in Microsoft Excel. It became so large — greater than 100 megabytes — so difficult to check, and so unstable that it was necessary to change the modeling platform.
According to the lead modeller on the project, BG Group decided to use Analytica because the model would be:
- Much clearer to understand
- Easier to develop and check
- Capable of working with large data sets
The Market Optimization Tool (MOT) was developed in Analytica to replace the spreadsheet model. The size of the MOT model in Analytica is only 4 Mbytes — under 4% of the size of the corresponding Microsoft Excel spreadsheet — even though it has substantially expanded capabilities.
MOT allows exploration of multiple scenarios at the same time, so that you can compare the effects of input changes across the model from the demand module through to the balance sheet. It uses a database to handle multiple scenarios with a flexible evaluation horizon.
MOT provides summary numbers for high level reports, or very detailed information, depending on how deep you want to drill down. It guarantees information consistency because all calculations are made in real time, so that there is no possibility of generating inconsistent scenarios. It is capable of handling a wide range of tariff structures and regulatory constraints.