An integrated approach for distributed energy resource short-term scheduling in smart grids considering realistic power system simulation

The large increase of distributed energy resources, including distributed generation, storage systems and demand response, especially in distribution networks, makes the management of the available resources a more complex and crucial process. With wind based generation gaining relevance, in terms of the generation mix, the fact that wind forecasting accuracy rapidly drops with the increase of the forecast anticipation time requires to undertake short-term and very short-term re-scheduling so the final implemented solution enables the lowest possible operation costs. This paper proposes a methodology for energy resource scheduling in smart grids, considering day ahead, hour ahead and five minutes ahead scheduling. The short-term scheduling, undertaken five minutes ahead, takes advantage of the high accuracy of the very-short term wind forecasting providing the user with more efficient scheduling solutions. The proposed method uses a Genetic Algorithm based approach for optimization that is able to cope with the hard execution time constraint of short-term scheduling. Realistic power system simulation, based on PSCAD®, is used to validate the obtained solutions. The paper includes a case study with a 33 bus distribution network with high penetration of distributed energy resources implemented in PSCAD®.

► Optimization of distributed energy resources scheduling.
► Genetic Algorithm optimization applied to the distributed energy resources scheduling.
► Optimization linked to a network simulation environment.
► Realistic network simulation using PSCAD.
► Distributed energy resources in a smart grid environment.