Journal ArticleOpen Access
Energy scheduling of community microgrid with battery cost using particle swarm optimisation
Authors
Author Affiliations
UNSW Sydney, Dhaka University of Engineering & Technology, Marche Polytechnic University, Aalborg University
Published InApplied Energy
Year2019
Citations177
Abstract
The integration of renewable energy sources together with an energy storage system into a distribution network has become essential not only to maintain continuous electricity supply but also to minimise electricity costs. The operational costs of this paradigm depend highly upon the optimal use of battery energy. This paper proposes day-ahead scheduling of the battery energy while considering its degradation costs due to charging-discharging cycles. The degradation costs with respect to the depth of charge are modelled and added to the objective function to determine the actual operational costs of the system. A framework to solve the function is developed in which particle swarm optimisation, the Rainflow algorithm and scenario techniques are integrated. Uncertainties of parameters, modelled by scenario generation…
View at Publisher
BORR does not host full-text PDFs. The button above takes you to the original publisher.