Stochastic multiobjective optimization for hybrid power generation systems
| Type of publication: | Inproceedings |
| Citation: | |
| Booktitle: | Proceedings of the 11th European Workshop on Multi-Agent Systems (EUMAS 2012) |
| Year: | 2012 |
| Abstract: | A wide variety of renewable distributed energy technologies are now commercially available. However, due to their small-scale ca- pacity and intermittent nature, integrating such devices to the grid may degrade the security and reliability of the distribution systems. Virtual power plants (VPPs) representing clusters of distributed generators may alleviate these drawbacks by aggregating a reliable energy supply. In this paper, a methodology has been proposed for efficient demand-response in the context of hybrid power generation systems that combine different sources of energy. Specifically, the planning problem is formulated as a stochastic DCOP for determining the optimal dispatch. We then go on to propose a new distributed algorithm for solving the scheduling prob- lem and provide an empirical analysis of our approach for a Smart Grid scenario. |
| Keywords: | distributed constraint optimization, Multi-Agent Systems, Smart Grid, virtual power plants |
| Authors | |
| Added by: | [] |
| Total mark: | 0 |
|
Attachments
|
|
|
Notes
|
|
|
|
|
|
Topics
|
|
|
|
|