Combine enterprise simulation with powerful financial modelling tools
The energy generation, transmission and distribution sectors have long been at the forefront of the use of simulation and optimisation tools. However, the volume and rate of change driven by new technology, for example electric vehicles and renewables, and in some jurisdictions, the need to meet climate change obligations mean that the current generation of tools are inadequate. Many of the tools currently in use have been used at the plant level for engineering purposes or solely within narrow business functions such as asset maintenance. The lack of appreciation of financial or systemic issues by these lower level tools raises significant questions of their real value. How do you know if a locally optimised plan actually optimises the organisational objectives, is resilience to strategic risks and offers the greatest flexibility to leverage future opportunities?
Forward looking companies in this sector are realising that the spreadsheets and niche tools long used for making strategic decisions are inadequate in this rapidly changing national and global markets. Not only do they not fully represent the operational constraints that exist in their businesses, they lack the flexibility to rapidly develop practical financially productive decisions that cut across organisational silos. Therefore, the ability to make rapid, forward looking and holistic decisions is a key competency that energy companies must develop to succeed in an increasingly complex and uncertain sector.
BMA’s Next Generation Analytics provides an integrated modelling, optimisation and planning engine which can dramatically enhance the profitability of strategic and operational decision making within companies in this dynamic sector. Our tool can simultaneously consider multiple constraints, including operational, asset and financial constraints as well as sector specific constraints such as gas quality requirements. Critically, to what is an asset intensive sector our solution is industry leading in its ability to consider asset interdependencies in its optimisation.
In this case study we created a thirty year strategic, TOTEX model of a gas distribution network to carry out scenario analysis of alternative shale and hydrogen gas futures. The model analysed both operational outputs such as gas quality as well as infrastructure investment options. Enterprise Optimizer is uniquely suited to this challenge as it can model your asset base, processes and financials in equal detail. This combination of engineering and financial modelling capabilities allows it to offer a true TOTEX optimisation. Our mathematical optimisation engine will evaluate all decision trade-os, given the business constraints and financial objectives for both capital and operational investments and interventions.
In this case study we modelled an intermediate and low pressure gas distribution network down to asset level. The physical and functional connectivity of all asset (mains pipes and district governors) were modelled. This allowed us to quantify the impact of network redundancy and interdependencies on the consequence of asset failure.
In this case study we combined our statistical demand forecasting module with our prescriptive analytics optimisation module to optimise capacity planning. Our statistical forecasting technology can produce a sophisticated time series forecast of demand. For example, our forecasting technology automatically accounts for day of week, day of month and month of year eects. The demand forecast is then passed to our prescriptive analytics technology which includes full representation of resource availability down to a skills level. This solution provides a full resource management and capacity planning functionality including recruitment and training.