Day-ahead Management of Energy Sources and Storage in Hybrid Microgrid to reduce Uncertainty

Year 2019, , 1167 - 1183, 01.12.2019

K Prakash Kumar B Saravanan

https://doi.org/10.35378/gujs.512736

Cited By: 5

Abstract

A day ahead management strategy is proposed
in this article to schedule energy generators and storage in presence of
Renewable Energy Sources under uncertainty conditions with an objective to
optimize the cost of energy generation. Artificial Fish Swarm algorithm is used
as optimization tool. The optimization problem is framed considering all the
practical constraints of energy generators and storage units. The uncertainty
of Renewable Energy Sources is treated with a proven uncertainty model and several
scenarios are drawn for energy availability and demand. The proposed energy
management algorithm is tested numerically on a grid connected microgrid
hosting a group of hybrid energy sources and storage battery for day ahead
scheduling under dynamic pricing and demand side management in one of the
generated uncertainty scenarios. The obtained results show that the performance
of Artificial Fish Swarm algorithm as an optimizing tool is validated and the
proposed Energy Management System is found to optimize the cost of energy
generation while matching the power generated with power required.

Keywords

Microgrid, Uncertainty, Storage, Energy Management, Day ahead scheduling

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