COR-e brings AI to next generation power market analysis
The new platform is designed to simplify data collection and processing while offering forecasts modelled by artificial intelligence, with the intention to provide a more accessible approach to understanding energy markets and the electricity market in particular.
Features of the new platform include data aggregation of multiple sources, quality control and format alignment and artificial intelligence modelling of production, consumption and price forecasting.
New presentations includes simplified access to all data with streamlined interfaces and a customisable alert system to make it directly actionable.
“Artificial intelligence is a great opportunity to create modern, high performance solutions that can provide added value to all energy professionals, whether they are financial market experts or not,” says COR-e founder Emeric de Vigan.
The energy markets are now more than an obscure and speculative playground for a few specialised traders. Understanding and anticipating their development has become essential for players including producers and retailers as well as the often energy intensive industrials.
Most analytical software solutions used in the markets are based on classical methodologies and are robust and proven but are from a time when the sources of data to be analysed were limited.
Since then there has been an explosion in the volume of data to be analysed. The markets have been moving closer to a real-time basis. They also are seeing the entry of new players such as storage owners, electric vehicle charging providers and flexibility aggregators with new data streams.
Next generation solutions need to match the demands of today’s energy markets, which will continue to evolve with further electrification and growth of decentralised energy resources.
COR-e’s models are designed internally by its team of mathematical, financial and commercial experts.
The company manages 100M of data in over 20 countries, de Vigan says.
This story was originally published on Smart Energy International