Optimal sizing of off-line microgrid via hybrid multi-objective simulated annealing particle swarm optimizer. (September 2021) - Hafez, Ahmed.A.; Abdelaziz, Almoataz.Y.; Hendy, Mohamed.A.; Ali, Alaa.F.M.
Highlights: Advising a robust and straightforward sizing procedure for MG via hybrid SAPS algorithm. Identifying the optimal size of batteries to provide a reasonable reserve of active/instantaneous power for primary frequency regulation. Providing a quantitative and qualitative comparison between SA, PSO and SAPS algorithms. Improving the MG's recovery performance under concern following/post-disturbance while operating at an optimal energy cost. Abstract: In this paper, a simple and efficient hybrid Simulated Annealing Particle Swarm (SAPS) algorithm is proposed to determine the optimal size of a Microgrid (MG) that guarantees economically and reliable operation of the off-line mode and/or on-line mode of the MG. The proposed SAPS optimizer considers the intermittent nature of renewable energy sources (RESs) while boosting the power supply security/stability. Batteries are resized to enhance the power supply reliability and acting as virtual synchronous inertia. During disturbances/fault circumstances, the primary frequency control is provided by batteries and diesel generators. The constraints are set to achieve higher levels of power supply security and frequency stability. Qena AL-Gadida (QA) city is the MG under concern. The SAPS results are validated versus Simulated Annealing (SA) and Particle Swarm Optimization (PSO). The results revealed the reliability and applicability of the proposed sizing procedure. Moreover, adopting the primary frequency regulation of batteries resulted in a slight increase in the overall costs. Graphical abstract: Image, graphical abstract