Project Title: ARTIFICIAL INTELLIGENCE IN ENERGY MANAGEMENT INNOVATIVE SERVICES
Acronym: ARTEMIS
PI: Dr Sanja Vraneš, principal research fellow, Institute Mihajlo Pupin
SRO’s: Institute Mihajlo Pupin
The global digitalization process has affected all sectors, and the electric power industry is currently experiencing the greatest transformation since its inception. The transition from a conventional system to the so-called smart grid, which involves a large number of distributed, often renewable, energy sources on the part of end consumers, is under way. The smart grid owes its name to the high level of digitalization, i.e. the establishment of advanced monitoring and management mechanisms. Within the smart grid, a new entity in the electric power system has been formed – a combined producer-consumer (prosumer), which has greater independence from the rest of the system, but also the ability to store locally produced energy or export it to the grid, thus providing additional flexibility for the entire system in terms of stability maintenance and optimal use of existing resources. ARTEMIS deals with the development of analytical tools, based on the use of artificial intelligence, for a more efficient prosumer management in the context of a smart grid. These tools will be integrated into a single application stack which will provide advanced analytical services in a variety of scenarios, ranging from a single household, through a block of buildings, to part of a distribution network. ARTEMIS services will predominantly rely on the application of the cutting-edge technologies and concepts in the field of artificial intelligence, in order to contribute to solving various problems.
PROJECT OBJECTIVE: ARTEMIS project goals include a reduction of total energy consumption and supply costs through advanced energy management techniques and greater use of renewable energy.
METHODOLOGY: The use of advanced machine learning techniques, including artificial neural networks and decision trees, as well as linear and integer programming techniques and semantic data processing tools is envisaged.
EXPECTED RESULTS: One of the expected results is the establishment of a generic stack of energy services based on the use of artificial intelligence, which can be easily integrated into existing energy management systems.
Illustration: Irena Gajic