Advanced power generation systems for the 21st Century: Market survey and recommendations for a design philosophy

Abstract

Fuel saved by variable-speed control as function of fixed-speed for peacetime average use profile (5-to 60-kW gen-sets).

Phase I Report: DARPA Exoskeleton Program

“…For a 25 wt% NaBH 4 solution, there is a total of 6.3 molecules of water per molecule NaBH 4 . Two of those molecules are consumed in the hydrolysis reaction (Eq.…”

“…In general, turbine fuel consumption would be anticipated to be from 5 to 15% less efficient than that for reciprocating diesels (Andriulli, 1999;Heywood, 1988). Micro-turbine performance does not scale well below 25 kW and fuel consumption tends to increase more in comparison to piston engines at partial loads (Andriulli, 1999).…”

Prognostic Analysis of the Tactical Quiet Generator

“…These power systems must be portable, lightweight, quiet, electronically controlled, and continuously operable for long periods on a variety of fuels in extreme environmental conditions. Previous ORNL work 35 for the U.S. Department of Defense's Mobile Electric Power Program assessed the state of the art in key power technologies, including engines, alternators, power electronics, digital control, and diagnostics and prognostics. The goal was a set of design recommendations for future generators as a TQG replacement to take advantage of advanced technologies under the above usage constraints.…”

“…Subsequent ORNL work 36 developed a proof-of-concept 8-kW unit for the Mobile Electric Power Program on the basis of the earlier recommendations 35 . The requirements for this unit were: 50, 60, and 400 Hz from one unit; reduction of the generator-set weight by up to 55%; a similar reduction in volume; increase in fuel efficiency; maximal flexibility; low acoustic signature (65 dBA at 7m); low cost; high system reliability; and all on an aggressive proof-of-concept schedule.…”

“…The previous work 35 noted that reliable prognostics are very difficult for a variety of reasons, including different degradation rates for various machine components, depending on their initial condition, service environment, and maintenance history. Prediction of time-to-failure requires up-to-date trends in key parameters that are related to component condition and life span.…”