The role of battery energy storage in mitigating demand fluctuations of distribution networks caused by uncertain weather conditions using multi-objective Bonobo Optimizer.

Fluctuations in demand can have a significant impact on electrical distribution networks, causing variations in voltage and frequency, imbalances between power output and consumption, and putting strain on system components. This study suggests using optimized battery energy storage systems controlled by the Bonobo Optimizer (BO) algorithm, along with renewable photovoltaic sources, to mitigate the effects of system demand fluctuations (SDF). The utilization of the BO is intended to minimize the SDF and alleviate energy losses in the 69-bus system amidst uncertain demand situations from residential, commercial, and industrial sectors. The optimal compromise solution is obtained by implementing both single-objective and multi-objective optimizations utilizing two techniques: the fuzzy-based function approach and the technique for order of preference by similarity to the ideal solution. Diverse metrics are utilized to evaluate the excellence of the suggested approach, including power, voltage, and stability. The results demonstrate a significant increase in the load factor, with values of 98.86%, 99.64%, and 99.90% observed for the three forms of demand, compared to the load factors of 57.25%, 73.95%, and 73.22% seen in the base scenario. Moreover, there have been improvements in the voltage profile and system stability. Furthermore, a significant reduction in system energy loss has been seen in the multi-objective optimization case study. [ABSTRACT FROM AUTHOR]