Research Information System
11th Virtual International Conference on Science, Technology and Management in Energy, Belgrade, Serbia, 24 - 25 November 2025, vol.1, pp.1-7, (Full Text)
Renewable energy resources are becoming more
prevalent in modern microgrids. This means that operators face a growing need
for optimization strategies. These strategies must balance technical, economic
and environmental objectives. This is especially true when battery degradation
is considered. Researchers are struggling to achieve this balance between
short-term cost savings and long-term system durability. The issue is addressed
in this study through the implementation of a two-stage approach. In the first
stage, photovoltaic (PV) capacity and battery size are determined using
particle swarm optimization (PSO) to ensure both economic feasibility and
realistic lifecycle performance. A mixed-integer linear programming (MILP)
model implemented in Python through Gurobi is employed in the second stage for
the management of daily energy operations. The analysis examines how different
objective-function priorities affect prosumers with varied consumption and
generation profiles in a multi-stage microgrid setting. A comparison is made
between three alternative formulations. (i) minimizing operating costs, (ii)
preserving battery health and (iii) maximizing renewable energy use, as well as
combined bi- and tri-objective versions. Simulation outcomes show that the ranking
of objectives strongly shapes system performance, which is important to
consider when designing and implementing systems. Indicators such as
self-consumption, self-sufficiency, curtailed power, CO2 emissions and storage
ageing show variations. Overall, practical guidance is offered by the findings
for engineers and planners aiming to design energy-management strategies that
link immediate operational goals with long-term sustainability and resilience
in prosumer-oriented microgrids.