Giusti A.,DalleMolle Institute for Artificial Intelligence IDSIA |
Salani M.,DalleMolle Institute for Artificial Intelligence IDSIA |
Di Caro G.A.,DalleMolle Institute for Artificial Intelligence IDSIA |
Rizzoli A.E.,DalleMolle Institute for Artificial Intelligence IDSIA |
Gambardella L.M.,DalleMolle Institute for Artificial Intelligence IDSIA
IEEE Transactions on Smart Grid | Year: 2014
We address demand-side management of dispatchable loads in a residential microgrid by means of decentralized controllers deployed in each household. Controllers simultaneously optimize two possibly conflicting objectives: minimization of energy costs for the end user (considering a known, time-dependent tariff) and stabilization of the aggregate load profile (load flattening). The former objective can be optimized independently by each controller. On the other hand, the latter could benefit from a communication infrastructure that allows the controllers to explicitly exchange information and coordinate. To study how different levels of communication pervasiveness affect system performance, we developed a realistic micro-simulation environment accounting for the behavior of residents, dispatchable and non-dispatchable household loads, and the effects on the distribution network. We considered a generic model of communication among household controllers, not tied to any specific technology, and based on the partitioning of the households in a number of groups (neighborhoods). Controllers within the same neighborhood enjoy full connectivity, but cannot interact with controllers outside of their neighborhood. Through extensive simulation experiments, we observed that even communication neighborhoods constituted by as few as 3-4 households are sufficient to effectively stabilize the aggregate network load profile, with minimal bandwidth consumption. Increasing the neighborhood size leads to comparatively negligible performance improvements. We conclude that effective load flattening can be achieved with minimal requirements of communication infrastructure and transmitted information. © 2010-2012 IEEE.