Forecasting and billing for the energy market

Our client is an IT company focused on developing IT solutions within the energy market. The various parties within the energy market (energy suppliers, network operators, energy producers and industrial bulk consumers) can contact our customer for the right software solution. They focus on sustainable modular software solutions as well as specific tailor-made applications. 

The Challenge

Various parties within the energy market exchange big data  to carry out the necessary forecasting and invoicing data within the energy market. In addition to basic metering information (location, address, meter type, …), this data also includes the actual consumption/production of the end customer. The ultimate purpose of this data is  to prepare a correct forecast for the energy suppliers on the one hand,  and validate and invoice this data on the other hand.

The scope of this project includes analysing the current (as is) situation of invoicing (fully supported by export CSV and further manual processing within Excel) and how this will be transformed into a semi-automatic and digital process (to be).

Project Approach

Forecasting and billing for the energy market

Based on the SCRUM framework, the different sprints are worked out with attention for the various components such as sprint planning, storyboarding, daily scrum, sprint review, etc. This agile methodology enables us to switch quickly and  monitor the right priorities.

The speed of processing goes hand in hand with the available computing power. To make optimal use of resources during this heavy billing process, Azure (Durable) functions were to handle and process the calculations completely serverless. Calculations are split up into separate calculation blocks that are processed independently and asynchronously. During this process, large amounts of unstructured data are collected by a solution that will manage data in an organized and structured way.

At the end of the process, the data is brought together from  different sources and processed into multiple invoices with corresponding client details. The billing process is triggered by different timer or application scenarios and monitored via a suitable platform for the full spectrum of users, from technical to business

Key Performances

Performance research in the context of big data processing within different database structures (SQL server / Cosmo DB )

Designing a business context analysis in which the current manual operation is transformed into a digital and automatic process

Technical development of a serverless billing processing using Azure (durable) Functions, Power Automate, Blob Storage and CosmoDB

Cost-benefit analysis in function of efficient use of Azure resources

Learn More about this Customer Story on the website of Ingenix.

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