Mission-Based Optimal Control for the Evaluation of Power and Energy System Capability

With the advent of high energy pulse mission loads and distributed power and energy on all-electric ship platforms, a new total ship control system capability is emerging that could significantly impact overall mission success. No longer are loads limited to an all-or-nothing power per use approach. Rather, energy applied to advanced mission loads can be scaled—even regulated—to achieve a desired outcome. Within this new framework, the effectiveness of unique missions can be quantified as a function of the amount and allocation of power to service each mission load. Power elasticity enables a new frontier of how decisions are made during intense operational scenarios where limited power and energy resources are applied to competing load demands. Herein, a power allocation strategy that addresses this challenge is proposed. The general approach is to use state-space models to represent the evolution of both the mission and the engineering system that is supporting the mission. An optimal control problem is performed to maximize some functional over the mission state and actions. By doing so, it indicates the capability of the engineering system to support such missions. The uniqueness of this approach is that solutions become far more mission specific. Results based on a simple two-function platform—each competing for the same limited power resources—show that this approach can be used to assess the probability of success given a certain initial allocation of power.

[1]  N H Doerry,et al.  Implementing Quality of Service in shipboard power system design , 2011, 2011 IEEE Electric Ship Technologies Symposium.

[2]  Amjad Anvari-Moghaddam,et al.  Optimal planning and operation management of a ship electrical power system with energy storage system , 2016, IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society.

[3]  S. Mashayekh,et al.  Optimum sizing of energy storage for an electric ferry ship , 2012, 2012 IEEE Power and Energy Society General Meeting.

[4]  Norbert Doerry,et al.  Designing Electrical Power Systems for Survivability and Quality of Service , 2007 .

[5]  M. E. Fitzgerald,et al.  Mitigating contextual uncertainties with valuable changeability analysis in the multi-epoch domain , 2012, 2012 IEEE International Systems Conference SysCon 2012.

[6]  Norbert Doerry,et al.  Naval Power Systems: Integrated power systems for the continuity of the electrical power supply. , 2015, IEEE Electrification Magazine.

[7]  Adam M. Ross,et al.  HANDLING TEMPORAL COMPLEXITY IN THE DESIGN OF NON-TRANSPORT SHIPS USING EPOCH-ERA ANALYSIS , 2012 .

[8]  D.H. Clayton,et al.  Shipboard electrical power quality of service , 2005, IEEE Electric Ship Technologies Symposium, 2005..

[9]  David C. Yu,et al.  Optimal sizing of hybrid PV/diesel/battery in ship power system ☆ , 2015 .

[10]  Ganesh K. Venayagamoorthy,et al.  Optimal location and sizing of energy storage modules for a smart electric ship power system , 2011, 2011 IEEE Symposium on Computational Intelligence Applications In Smart Grid (CIASG).

[11]  Adam M. Ross,et al.  11.1.1 Using Natural Value-Centric Time Scales for Conceptualizing System Timelines through Epoch-Era Analysis , 2008 .

[12]  Osama A. Mohammed,et al.  A comparative study on the optimal combination of hybrid energy storage system for ship power systems , 2015, 2015 IEEE Electric Ship Technologies Symposium (ESTS).