Dynamic efficiency

14 January 2010

Dynamic performance measurement system has improved energy and electricity consumption at Saso.

Sasol is an integrated energy and chemicals company. It adds value to coal, oil and gas reserves, and uses these feedstocks to produce liquid fuels, fuel components and chemicals.

Until recently the profitability strategy of the Sasol steam plants in Sasolburg, South Africa, was to maximise output. Now, as the demand for steam has declined, the plant’s primary goal is to minimise costs.

Working with the consulting team at Invensys Operations Management, Sasol personnel developed real-time dynamic performance measurements (DPM) for the plants to determine the underlying real-time performance measures and calculate costs and profits. Management and operator dashboards were also created to provide management, operations and engineering with critical information in real time to enable better and more informed business decisions.

Modelled in the DCS, three station-level DPMs were developed: steam cost, steam quality and production rate. Each individual boiler is required to produce the lowest cost steam at the proper pressure and temperature specifications, maintain reliable production, while managing production rates. For each boiler, the variable steam generating cost, including labour, consists of five major components: coal, electricity, fuel, oil and water. Additionally, emissions levels were monitored and improved to enhance Sasol’s environmental footprint.

DPM algorithms, real-time financial models and unit levels were implemented in the two DCSs. Using existing plant-level assets for implementation, cost factors on the plant floor can be tracked in real time. The execution of these algorithms typically takes place in the microprocessors in the DCS. These algorithms are executed at a frequency that is in close proximity to the cycle time of the process, with the historical collection performed at a similar frequency. Unit-level metrics are then aggregated at the station and plant levels using the functionality of the historian. The totalisation can be performed at various periods, including the shift, day and month.

Real-time financial data with allocated costs are tracked using the ValuMax activity-based costing system and provide an immediate representation of product costs across the portfolio. The same real-time financial data is projected to eventually be integrated into SAP as the fidelity and applicability of the data is better understood.

Once the performance measurement models were installed, they were historicised to provide a performance profile of each unit and station. This baseline enabled an economic comparison of boilers under various conditions. Using better procedures and training, improvement initiatives and projects, operational developments can be financially tracked and validated. Creating this type of baseline enables the development of data for financial and accounting validation.

As Sasol’s division continues to improve its operation and drive business value for the company, it will acquire new products and process technologies to help achieve its goals. Sasol Infrachem’s management views development of its employees as one of the company’s most critical tasks. Government regulations and key personnel nearing retirement underscore the importance of skills and knowledge development.

The Invensys real-time energy usage monitoring solution was a key tool in helping Sasol achieve positive results on this project. Producing steam in the stations resulted in a six per cent saving in energy and a four per cent saving in electricity costs within the first month, amounting to savings of approximately US$230,000. Energy and electricity savings progressed and improved throughout the second and third months, saving US$400,000 in the first two months from two out of the five targeted plants. In collaboration with Invensys Operations Management, Sasol will incorporate future business information with process data and identify other areas of improvement through advanced multivariate statistical analysis, continuous improvement programmes such as Six Sigma, and other business value-adding activities.

This article first appeared in the Winter 2009 edition of Prime magazine.