Models and simulations of future energy grids

We handle models and simulations using our own GridMind tool, developed for this purpose. GridMind is built up on algorithms from the field of artificial intelligence, which is able to process very large and complex simulations. We cooperate with CERIT-SC Supercomputing Cloud at Masaryk University for this purposes.

Models consist of individual components of the energy and communications infrastructure. Taking smart metering as an example, they include millions of components communicating with each another. They further include the processes of measurement, signalling and control as well as characteristics requested by individual users to meet their needs. All parameters can be set for the models – it is possible to simulate various different topologies, technologies and types of component behaviour. Models are created on the basis of the results of real pilot projects and tests. The resulting model can then be fleshed out over the longer term as the future development of modelled grid becomes clearer.

Company focus

Mycroft Mind is focused on issues connected with the modelling, simulation and development of systems for processing data from extensive sensor networks – especially in domain of energy distribution grids.

We are helping utility companies to analyse, test and design smart metering / smart grid technology implementation.

  • 1.

    Sensor data analyses and processing
    We are processing data collected in pilot smart metering / smart grid project and developing analytical methods to obtain value from the data. We have processed more than 100 million smart metering records.

    Analyses and data processing includes basic tasks like data validation, estimation as well as sophisticated methods for controllable consumption detection, behaviour based segmentation or prediction of photovoltaics production.

  • 2.

    Load Control System
    We have developed a software system which is used for optimization of energy flows under secondary substations. Main goal is to detect controllable consumption and shift the consumption to suitable time using tariff and relay switching. Typical example is to shift controllable consumption to time when production from local photovoltaic sources is predicted. Optimization algorithm is based on predictions of consumption, production and expected customer reaction on tariff switching.  


Pankaj Popat

phone: 0118-327-3770
mobile: 0780-109-4006

Edgefield, Western Avenue