This repository contains the source code relative to the college subject Electronic Business Technologies.
Electronic Business Technologies is a subject of the Informatics Engineering Doctoral Program from FEUP.
Retail electricity trading markets were designed long ago when power was produced almost exclusively using fossil fuels. Back then, balancing supply and demand of electricity and predicting market behavior was relatively easy. Then came the dawn of renewable energy. Renewable energy is great – it’s cheap and it’s clean. But the production output of renewables is hard to predict. Wind doesn’t always blow on cue and the sun doesn’t always shine according to forecast. That means the more renewable energy in the energy market mix, the bigger the 'intermittency' problem. And as more electricity consumers become producers as well – they call them 'prosumers' – the once straightforward supply and demand balancing act becomes breathtakingly complex. In 2009, they designed an open-source platform to support an artificial intelligence-driven Power Trading Agent Competition – PowerTAC – to explore how digital information systems could integrate sustainable energy into existing electricity markets in a profitable way. Power TAC models the high complexity of contemporary and future electricity markets, allowing for large scale experimentation. Autonomous machine-learning trading agents, or 'brokers', act as intermediary profit maximization parties between the market and 'customers', who represent consumers, producers and prosumers. Customer models represent households, small and large businesses, multi-residential buildings, wind parks, solar panel owners, electric vehicle owners, etc. Brokers aim at making profit through offering electricity tariffs to customers and trading electricity in the wholesale market, while carefully balancing supply and demand. With each annual tournament, the models become more sophisticated, the platform more flexible and the results more enlightening.