The association of distributed generators, energy storage systems
and controllable loads close to the energy consumers gave place to a small-scale
electrical network called microgrid. The stochastic behavior of renewable energy
sources, as well as the demand variation, can lead in some cases to problems
related to the reliability of the microgrid system. On the other hand, the market
price of electricity from mainly non-renewable sources becomes a concern for a
simple consumer due to its high costs.
An innovative optimization method, combining linear programming,
based on the simplex method, with the particle swarm optimisation algorithm is
used to develop an energy management system. The management is performed
considering a smart city’s consumption profile, two management scenarios have
been proposed to characterize the relation price versus gas emissions for optimal
energy management.
The simulation results have demonstrated the reliability of the
optimisation approach on the energy management system in the optimal
scheduling of the microgrid generators power flows, having achieved a better
energy price compared to a previous study with the same data. The
computational results identified the optimal set-points of generators in a smart
city supplied by a microgrid while ensuring consumer comfort, minimising
greenhouse gas emissions and guarantee an appropriate operating price for all
consumers in the smart city.
The energy management system based on the proposed
optimisation approach gave an inverse correlation between economic and
environmental aspects, in fact, a multi-objective optimisation approach is
performed as a continuation of the work proposed in this paper.
