Optimizing Decentralized Grid Markets through Group Selection

Automatic coordination mechanisms for the grid are required due to the increasing complexity exhibited in large scale distributed systems. Decentralized economic models are being considered as scalable coordination mechanisms for the management of service allocations to clients. However, decentralization incorporates further dynamicity and unpredictability into the system. Introducing higher levels of adaptation and learning in the coordination protocols helps cope with complexity. We provide a solution based on a self-organized, emergent mechanism evolving grid market participants through a group selection process. Dynamic congregations organize agents into optimized market segments, maximizing utility and thereby improving system-wide performance. We provide a system model and evaluation by simulation of the group selection mechanism. We further provide a prototype showing practical feasibility of the approach.