Optimization of Distributed Generation Based Hybrid Renewable Energy System for a DC Micro-Grid Using Particle Swarm Optimization
DOI:
https://doi.org/10.13052/dgaej2156-3306.3341Keywords:
Renewable energy, wind energy, biogas based IC engine and photovoltaic, multi-objective optimization, direct current micro-grid, particle swarm optimization.Abstract
This research work aims to design and optimize a multi-objective
function modeled on the variables concerning distributed generators
based on photovoltaic, wind and biogas based IC engine hybrid system
for community smart DC Micro-grid using particle swarm optimization
(PSO). The objectives of the research are to maximize the availability
of power and reduction of the cost, which in turn will reduce the size
of system with premier achievable availability. The output power of
photovoltaic, wind and biogas based IC engine generators would have
the highest priority for feeding the direct current bus as per the meth -
odology proposed. It was found that proposed method especially par -
ticle swarm optimization had shown the effective cost and availability
of photovoltaic, wind and biogas based IC engine generators in terms
of accuracy to the practical values and a faster rate of convergence.
When compared with other algorithms, particle swarm optimization
performs well in reducing the cost of the photovoltaic, wind and biogas
based IC engine generators. In addition, it was noted that availability
of photovoltaic, wind and biogas based IC engine generators would be
easily obtained using PSO algorithm. Future work would pertain to the
designing of a similar hybrid Renewable energy system considering Up-
time and Ramp rate constraints of biogas based IC engine generators for
community smart direct current micro-grid and optimize it using Multi
Objective Genetic Algorithm and compare its results with PSO.
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