Smart De-Centralized Self-Organization

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SDSO - Smart Decentralized Self-Optimization implements, validates and demonstrates embedded hardware and smart algorithms for the de-centralized control and optimization of flexible loads (i.e. the energy consumption of machines and other consumers) in an industrial environment. Within an energy micro grid (such as the energy grid of a industrial facility), SDSO enables a real-time optimization of energy demands (Demand Side Management) in response to real-time “price” signals inferred from physical properties of the AC electricity grid (e.g. frequency variations). This enables up-to-the-minute balancing of energy supply and demand which can be used to avoid consumption spikes and to fill demand troughs. Already in the current regulatory environment the end user can use more favorable basic tariffs with DSM. In the future it can be expected that flexible and load-dependent tariffs will allow a significant saving in energy costs. Overall, DSM contributes to grid stability and simplifies the use of renewable energy sources.

Duration: 01.01.2017 till 31.12.2017
Donee: German Research Center for Artificial Intelligence GmbH
Sponsor: European Union
Grant number: Funded by EIT DIGITAL, 2017.
Partner: DFKI GmbH
TU Berlin
Engineering S.A.
Easy Smart Grid
Application Field: Logistics, Production and Consumer
Data management
Related Projects: MMG-S
Modular Mobile Micro-Grid Services (01.2016- 12.2016)

Project details

SDSO smart algorithm on embedded HW (source: Hendrik Hanff, DFKI GmbH)

The future Digital Industry will be characterized by decentralized processes that involve many heterogeneous actors (robots, machines, autonomous transport vehicles etc.). Standard centralized process control is inadequate as it requires significant investments in communication infrastructure and is often not flexible enough to accommodate to dynamic and heterogeneous infrastructures.

Decentralized control and optimization promises to be cheaper, more stable, more flexible and scaleable.

The objective of SDSO is thus to implement and demonstrate a solution for de-centralized process control that is cheap, simple, and easy to install, both in new as well as legacy machinery.

SDSO is based on smart algorithms implemented on low-cost, off-the-shelf embedded hardware (e.g. powerful SoC microcontrollers or single-board computers), customized for energy management optimization in car manufacturing.

The new smart embedded hardware will be the core of an energy controller box
for new and legacy machinery. The optimization principle used is to reduce energy cost by avoiding consumption peaks through the self-optimization of
distributed energy consumers.

The outcome of this acitivity will be a functioning and tested product to be used in the car industry to save energy costs (which are considerable in this
sector). In the future, the product will be generalized for as a cheap and easy-to-install solution for the optimization of decentralized industrial processes.
As such processes will gain significant importance in the digital industry of tomorrow, the economic and societal impact of this product will be significant.

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