Architectures for novel energy infrastructures: Multi-agent based coordination patterns

Abstract

Due to the increased proportion of small renewable energy sources in a distributed setting (DG-RES), active control of small distributed energy producing and consuming systems will play an important role in future electricity grids [1]. These distributed energy resources have production patterns, which are either partially stochastic (e.g. wind, solar cells) or are coupled to the primary user process (e.g. co-generation of heat and electricity). Furthermore, on the demand-side, and increasingly on the electricity storage side, opportunities exist for actively serving stability applications in the grid by real-time supply/demand coordination. In the future, an information and communication layer for grid coordination could serve a portfolio of ICT-applications on timescales running from seconds to hours. To get a grip on these (r)evolutionary developments, possibly toppling the electricity grid, in this paper, architecture requirements for future high proportion DG-RES electricity grids are collected from a Power Electronics System point of view as well as from an ICT point of view using an inventory of business models in the power grid that focus on coordination of multiple small-scale DG-RES resources. Modeled from an ICT point-of-view, these give rise to architectures for applications that can successively be implemented in hardware and software as active components in the distribution grid. A number of possible grid control strategy coordination patterns (GCPs), which are defined in a generic, reusable manner, can be seen to emerge. GCPs, connected and intertwined to one another on several layers (physical, commercial) of the grid, together, can provide the framework for coordination in the overall intelligent grid. Bottom-up approaches of implementing coordination in future active grids appear to be the method of choice to use in implementing the GCPs. Software agents [2], [3] coordinating primary processes using market algorithms, as implemented in the PowerMatcher approach [3]-[4], appear to be very suited for this.