Modern computer systems offer some type of parallelism and use restricted resources. Parallel jobs require more than one processor at the same moment of time. Processors may operate at variable speeds. Running a job at a slower speed is more energy-efficient. However, it takes a longer time and affects the performance. We propose and experimentally evaluate heuristic methods based on greedy rules and list scheduling for the speed scaling scheduling problem with the total completion time criterion. Series of instances with various structure are constructed and tested. NP-hard and polynomially solvable cases are identified.