Queueing models with working vacations have been widely studied for their importance in optimizing both system efficiency and energy usage. This study extends the conventional M/M/1 queueing model with two distinct types of working vacations, each with a unique service rate, to a scenario where customers arrive in batches. Using the probability generating function method, we derive key performance indicators, including steady-state probabilities and the expected number of customers in the system. These indicators serve as the basis for evaluating the model’s power-saving performance, providing insights into energy efficiency under various batch size distributions. Additionally, numerical experiments are conducted to examine the average number of customers for batch arrivals following arbitrary distributions. The results confirm that the analytical findings align closely with simulation outcomes, thereby validating the model’s accuracy and effectiveness. This model provides a robust framework for evaluating and optimizing queue performance in systems requiring energy-saving measures, with practical applications in server management and energy-sensitive environments.