Kamyar Maleki

PhD student WP3 (2019–2022)

Supervisor: Prof. Eilif Pedersen (NTNU)




Research Gate

Optimization of Marine Power Plants

Research topic

Increasing strict regulations on emitted pollution of maritime operations directed the energy efficiency practical approaches toward hybrid solutions. Moreover, modeling and simulation have a significant role in the investigation of systems behavior for the aim of developing, enhancing and optimizations. Furthermore, numerical modeling and optimization methods enhance the approach of designers for obtaining the most efficient point of system configuration for specific goals and constraints. Since, for the aim of reaching the optimum state of the hybrid system configuration, the primary step is providing a high-fidelity model with flexibility in parameters and considering a control-oriented approach.
In previous PhD projects, the main components of hybrid power systems, such as generators, batteries and other mechanical and electrical devices have been accomplished.  However, there are two research gaps, the first is a model of fuel cells package by flexibility in design, size and operation. The second is optimum decision-making strategy of the energy management system. As a result, developing these two areas facilitates investigating operation state of each component in way of minimizing the consumed fuel and emission regarding the load requirements.  

In this PhD project, the main goal is reaching a package and methods of suggesting optimum hybrid power systems with flexibility in sizing, components configuration, system integration, and operations. Indeed, Multidisciplinary Design Optimization (MDO) is the fundamental optimization method that will be implemented in this project.  The main objective in the first stage is developing a package of high-fidelity model of Fuel Cells (FC) with the ability to suggest optimum size and construction. After defining the main parameters of FCs, the model will provide the specific FC operation in power system with an emphasis on dynamic response and control-oriented approach. The second stage, that will be developed in parallel, is implementing the optimum algorithm of energy management decision making. This algorithm will permit the system components such as generators, batteries and fuel cells to operate in an efficient way for reaching the goal of reducing fuel consumption and emission.

Expected results

  • High Fidelity Modeling of various Fuel Cells
  • Experimental Validation with Hybrid Power Systems Laboratory (HPS)
  • Optimization of PMS in Operation
  • Optimization in Sizing and Design by Multidisciplinary Design optimization