Case Study - Turning smart-meter data into local energy control
See how existing AMM infrastructure supported local load balancing, day-ahead tariff planning, and better use of distributed energy sources.
- Client
- AMM Data Processing & Analytics
- Year
- Service
- Software development, Security, audits & compliance, Team augmentation
We worked with smart meters, data concentrators, and MDM data to understand how secondary substation data could support more local energy decisions.
The project connected consumption data, PV production, controllable devices, and tariff planning into a practical model for smarter distribution management.
- Java
- Elasticsearch
- Apache Kafka
- Terraform
- Ansible
- RedHat Linux
- Project duration
- 2 yrs
- People involved
- 3
- MDs delivered
- 1,5k+
- Infrastructure support
- 24/7/365
Overview
The project asked a practical question: could existing Automated Metering Management infrastructure do more than collect readings? We looked at smart meters, data concentrators, and MDM data as building blocks for local energy control at the secondary substation level.
The work focused on local load balancing. That meant looking at consumption, photovoltaic production, and controllable devices such as hot water boilers as one system, not as separate operational silos.
We helped shape a model for optimized day-ahead Time-of-Use switching plans for individual smart meters. The output could then be compared against traditional ripple control to understand where data-driven local management is actually useful.
The value was not a flashy dashboard. It was a clearer operating model: use the data already present in the network, connect it to real control mechanisms, and make local distribution decisions less blind.
