Improving microgrid reliability and performance by implementing novel optimizing strategies for renewable energy and storage devices

Résumé fourni par la source

The planning and operation of microgrids rely on efficient management of energy; especially where the generation of renewable sources is high and is intermittent and unpredictable. The intermittent characteristics of solar energy and wind velocity create a major problem of ensuring economic viability, voltage stability, and safe operation. In order to solve these problems, this paper suggests a Levy Flight Particle Swarm Optimization (LFPSO)-based techno-economic optimization model of optimal integration of wind, solar, micro-turbine distributed generators, and energy storage systems within a grid-connected micro-grid. The LFPSO is an extension of the traditional PSO that adds heavy-tailed Levy perturbations of flight, which greatly increases the possibility of world exploration as well as reduces premature convergence. The optimization model will reduce the levelized operating cost, system active power losses, and dependency of this substation at the same time, with nodal voltage magnitude and phase angle constraints to provide stable operation. The uncertainty of renewable generation is modeled explicitly by applying the scenario-based stochastic make-up of wind speed and solar irradiance. The validity of the methodology is demonstrated on an IEEE-13 bus microgrid under various conditions of renewable availability and load. Comparative convergence analysis has shown that LFPSO has a convergence time which is ten times less than standard PSO, and objective values are lower as well which is statistically validated with 100 independent runs showing robustness. The simulation results show that the operating cost is reduced to 0.142-0.145 USD/kWh, the active power loss is reduced by up to 80 percent under favorable conditions of renewable sources and the Substation Dependency Index (SBDI) is improved systematically, which is an indicator of better resilience of the microgrids. The findings affirm that LFPSO offers computationally efficient and robust optimization framework of microgrid energy management in the real world and has distinct benefits over its peer meta-heuristic approaches in addressing renewable uncertainty and multi-objective operational limitations.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.