Integrated battery model in cost-effective operation and load management of grid-connected smart nano-grid

This paper presents a comprehensive model of dynamic optimal operation management of the smart nano-grids (NGs) including the micro wind turbines (WTs) and micro photovoltaics (PVs) as renewable energy sources (RESs) while micro turbines (MTs) and fuel cell (FC) are considered as non-RESs. Furthermo...

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Bibliographic Details
Published in:IET renewable power generation 2019-05, Vol.13 (7), p.1123-1131
Main Authors: Heidari, Mehran, Niknam, Taher, Zare, Mohsen, Niknam, Solmaz
Format: Article
Language:English
Subjects:
comprehensive model
controllable curtailment
cost‐effective operation
distributed power generation
dynamic optimal operation management
environmental damage cost
exchanged power cost
fuel cell
grid‐connected smart nanogrid
integrated battery model
lead‐acid batteries
lithium‐ion batteries
load management
main grid
microphotovoltaics
microturbines
microwind turbines
modified teaching‐learning‐based optimisation algorithm
MTLBO algorithm
NG operation problem
nonRESs
objective functions
operating cost
optimisation
output powers
photovoltaic power systems
power generation economics
power losses
quadratic functions
renewable energy sources
Research Article
secondary cells
smart nanogrids
wind turbines
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Summary:This paper presents a comprehensive model of dynamic optimal operation management of the smart nano-grids (NGs) including the micro wind turbines (WTs) and micro photovoltaics (PVs) as renewable energy sources (RESs) while micro turbines (MTs) and fuel cell (FC) are considered as non-RESs. Furthermore, two types of lead-acid and lithium-ion batteries are considered besides the three types of controllable, curtailment-able and must run loads to increase the flexibility of the proposed formulation. The different objective functions of NG operation problem to be minimised include operating cost, environmental damage cost of pollution gases and exchanged power cost with the main grid. Also the power losses of batteries are modelled using the quadratic functions based on types and output powers of considered batteries, while these losses impose additional cost to operation cost functions of batteries. A modified teaching-learning-based optimisation (MTLBO) algorithm is used to cope with the multiobjective problem considering the constraints.
ISSN:1752-1416
1752-1424
1752-1424
DOI:10.1049/iet-rpg.2018.5842