ECOOP: Applying Dynamic Coalition Formation to the Power Regulation Problem in Smart Grids

Abstract

In this work, we focus on one particular area of the smart grid, namely, the challenges faced by distribution network operators in securing the balance between supply and demand in the intraday market, as a growing number of load-controllable devices and small-scale, intermittent generators coming from renewables are expected to pervade the system. We introduce a multiagent design to facilitate coordinating the various actors in the grid. The underpinning of our approach consists of an online cooperation scheme, ECOOP, where agents learn a prediction model regarding potential coalition partners and so can respond in an agile manner to situations that are occurring in the grid, by means of negotiating and formulating speculative solutions, with respect to the estimated behavior of the system. We provide a computational characterization for our solution in terms of complexity, as well as an empirical analysis against real consumption data sets, based on the macro-model of the Australian energy market, showing a performance improvement of about 17%.

Taxi dispatching strategies with compensations

“…Fourthly, in this context, we also plan to look into coalition formation techniques from Cooperative Game Theory. In general, algorithms to compute solutions to coalitional games are known to suffer complexity problems, but we have applied an approximation scheme (the bilateral Shapely Value) in the context of a Smart Grid application (Mihailescu et al, 2017), and would like to explore as to how far a fair and efficient split of the savings implied by taxi reassignment can be implemented in this manner.…”