Energy consumption and heat dissipation have become key considerations for modern high performance computer systems. In this paper, we focus on non-clairvoyant speed scaling to minimize flow time plus energy for batched parallel jobs on multiprocessors. We consider a common scenario where the total power consumption cannot exceed a given budget and the power consumed on each processor is sα when running at speed s. Extending the Equi processor allocation policy, we propose two algorithms: U-Equi and N-Equi, which use respectively a uniform-speed and a non-uniform speed scaling function for the allocated processors. Using competitive analysis, we show that U-Equi is O(P(α−1)/α2 )-competitive for flow time plus energy, and N-Equi is O( α √ ln P)-competitive for the same metric when given sufficient power, where P is the total number of processors. Our simulation results confirm that U-Equi and N-Equi achieve better performance than a straightforward fixed-speed Equi strategy...