An efficient and reliable scheduling algorithm for unit commitment scheme in microgrid systems using enhanced mixed integer particle swarm optimizer considering uncertainties

The use of an electrical energy storage system (EESS) in a microgrid (MG) is widely recognized as feasible method for mitigating the unpredictability and stochastic nature sustainable distributed generators other intermittent sources. battery (BES) most effective several power methods available today. unit commitment (UC) determines number dedicated dispatchable generators, respective power, amount transferred to absorbed from microgrid, well influence EESSs, among factors. BES deterioration considered UC conceptualization, enhanced mixed particle swarm optimizer (EMPSO) suggested solve MGs with EESS. Compared traditional PSO, acceleration constants EMPSO are exponentially adapted, inertial weight decreases linearly during each iteration. proposed integer optimization algorithm that can handle continuous, binary, variables. A part decision variables transformed into binary variable by introducing quadratic transfer function (TF). This paper also considers uncertainties renewable generation, load demand, electricity market prices. In addition, case study multiobjective MG operating cost defines additional problem discussed this paper. transformation single-objective model carried out using weighted sum approach, impacts different weights on lifespan analyzed. performance TF (EMPSO-Q) compared V-shaped (EMPSO-V), S-shaped (EMPSO-S), PSO (PSO-S). EMPSO-Q 15%, 35%, 45% better than EMPSO-V, EMPSO-S, PSO-S, respectively. when considered, falls $8729.87 $8986.98. Considering deterioration, improves 350 590, increases $8917.7. Therefore, obtained results prove could effectively efficiently problem.