A smart grid electricity market with multiagents, smart appliances and combinatorial auctions

Consumption of electric energy in the world has been rapidly growing, but the current distribution and use of electricity is largely an outdated legacy infrastructure which results in gigantic inefficiencies. A recent trend to solve this situation is the gradual incorporation of more flexible and "smart" elements both in the distribution and consumption of electric energy, in which has been called the "Smart Grid" (SG). Though many proposals have been made for giving intelligence to the SG, most of them lack thorough validation to ensure that investments in them are cost effective and economical viable. Multi-Agent Systems (MAS) are becoming a SG enabling technology, as they provide a distributed coordination framework that can give its intelligence to the grid. In this work we propose a MAS based framework for a SG simulator that implements a combinatorial auction algorithm for a SG energy market with a Demand-Side Management (DSM) approach. With this method we aim to address energy cost reduction and reduced peak demand. The evaluation of our experimental results show an improvement in performance indicators related to both of those expected benefits.