Stigmergy-Based Load Scheduling in a Demand Side Management Context
Type of Event:
The share of renewable energy sources (RES) generation is expected to grow dramatically in the following decades. This raises challenges for the power grid stability. Due to the intermittent and uncertain character-istics of these energy sources, it is desirable that they are utilized as they become available. In this con-text, new intelligent households can provide load flexibility to support demand and supply balancing and increase renewable energy utilization. However, it is vital to manage these flexible loads such that we can prevent herding events while respecting the privacy and autonomy of customers. In this context, it is inter-esting to observe that the power grid shows features observed in living systems. It is resilient to the failure of single components, as long as they are not essential. Moreover, it has the ability to moderately adapt its generation, to supply energy to large numbers of autonomous customers. Furthermore, it is in perma-nent evolution, incorporating new technologies, changing its features and limitations.
In this talk, we address the rescheduling of shiftable loads in a sub-section of the power grid (micro-grid) to maximize the utilization of RES. We propose an approach based on stigmergy for efficiently finding a close-to-optimal solution to the general problem. Customers are able to respond to a control signal broad-casted regularly and achieve a coherent behavior from a global perspective in a self-organized manner. The approach is reviewed in on-line and off-line optimization contexts. Furthermore, we present possibili-ties for adapting the algorithm to other combinatorial optimization problems and provide a comprehensive discussion on the requirements for developing artificial stigmergic systems.
Start: 2015-11-25 at 3:45 pm
End: 2015-11-25 at 4:45 pm
Building: 11.40, Room: 231
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Host: Research group Efficient Algorithms
Download: Media:Rios 25-11-2015.pdf