000007641 001__ 7641
000007641 005__ 20240531164504.0
000007641 02470 $$2doi$$a10.24868/issn.2515-818X.2018.071
000007641 035__ $$a2530515
000007641 037__ $$aGENERAL
000007641 245__ $$aNonlinear Power Flow Control Design Methodology for Navy Electric Ship Microgrid Energy Storage Requirements
000007641 269__ $$a2018-10-04
000007641 336__ $$aConference Proceedings
000007641 520__ $$aAs part of the U.S. Navy’s continued commitment to protecting U.S. interests at home and abroad, the Navy is investing in the development of new technologies that broaden U.S. warship capabilities and maintain U.S. naval superiority. NAVSEA is developing power systems technologies for the Navy to realize an all-electric warship. New nonlinear power system controls approaches are being developed to improve system performance in light of new electrically powered weaponry that behave as pulsed-loads. Advancements include the identification of pulsed-load profiles that identify Energy Storage System (ESS) requirements. A dynamic optimization engine has been developed and serves as the feedforward receding horizon control portion of the Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) feedback controls for ESS networked microgrid system. A Coalition Warfare Program (CWP) test scenario was selected. The CWP is defined with a Reduced Order Model (ROM) that includes; generation, ESS, and mission pulsed-loads. Several numerical simulation studies were conducted. The CWP scenario is bounded by a baseline mission load local ESS contrasted with no ESS full nonlinear metastable boundaries. The main goal is to minimize ESS size and weight while maintaining power system performance.  This paper focuses on the control and optimization of ESS as an integral part of supporting critical mission loads and real-time control algorithm development to improve future energy efficiency for multi-mission activities. 
000007641 542__ $$fCC-BY-NC-ND-4.0
000007641 6531_ $$aHierarchical control
000007641 6531_ $$aAdvanced Control
000007641 6531_ $$aEnergy Storage
000007641 6531_ $$aPulsed loads
000007641 6531_ $$aAgent-based Control
000007641 7001_ $$aWilson, D G$$uR&D Controls Engineer, PI, Sandia Electric Ship Program, Sandia National Labs, Albuquerque, NM, USA
000007641 7001_ $$aWeaver, W W$$uProfessor, Power Electronics/Controls/Power System, Michigan Technological University, Houghton, MI, USA
000007641 7001_ $$aRobinett III, R D$$uProfessor, Nonlinear Controls & Optimization, Michigan Technological University, Houghton, MI, USA
000007641 7001_ $$aYoung, J$$uChief Scientist, Nonlinear Optimization and Predictive Controls, OptimoJoe, LLC, Albuquerque, NM, USA
000007641 7001_ $$aGlover, S F$$uR&D Manager, PM, Sandia Electric Ship Program, Sandia National Labs, Albuquerque, NM, USA
000007641 7001_ $$aCook, M A$$uR&D Software Engineer, Lead Agents/Informatics Controls, Sandia National Labs, Albuquerque, NM, USA
000007641 7001_ $$aMarkle, S$$uDirector Electric Ships Office PMS320 Program, NAVSEA, PMS 320, Washington, D.C., USA
000007641 7001_ $$aMcCoy, T J$$uFormer Director of Navy Electric Ship and Power Systems Expert, McCoy Consulting, Box Elder, ND, USA
000007641 773__ $$tConference Proceedings of INEC
000007641 773__ $$jINEC 2018
000007641 789__ $$whttps://zenodo.org/record/2530515$$2URL$$eIsIdenticalTo
000007641 85641 $$uhttps://imarest.org/inec$$yConference website
000007641 8564_ $$9bda7d3ab-4478-4f8d-b900-8e8cc063f843$$s4178624$$uhttps://library.imarest.org/record/7641/files/INEC%202018%20Paper%20077%20Wilson%20FINAL.pdf