# Developments, Trends, and Challenges in Optimization of Ship Energy Systems
## Appendix A Main Characteristics of Journal Articles on Optimization of Ship Energy Systems  
Main characteristics of articles on optimization of energy systems of ships published in journals are written in this Appendix. The articles are written in chronological order, as in Table 1. In order to save space, only the authors' names, the journal, and year of publication are given here for each article, while complete publication details are written in the References. Two numbers are written before the author(s) names: the first one is the number of the article in Table 1 and the second one, in bracket, is the number in the References. 1. [PERSON]; [PERSON] _International Journal of Thermodynamics_**2008**. System: superconfiguration of a COGES system of an LNG carrier with high-power gas turbines, moderate power gas turbines, HRSG units of single pressure, HRSG units of single pressure, HRSG units of double pressure, one steam turbine. SDO optimization. Five operating states. Objective: maximize NPV. Service speed among the independent variables. Solution with two levels: A synthesis and design and (B) operation with time decomposition. Algorithm: a hybrid of Particle Swarm Optimization (PSO) and Struggle Genetic Algorithm (StrGA). 2. [PERSON]; [PERSON]; [PERSON] _Energy_**2008**. System: superconfiguration of a COGES system of a cruise liner with high-power gas turbines, moderate power gas turbines, HRSG units of single pressure, HRSG units of double pressure, and one steam turbine. SDO optimization. Solution with two levels: A synthesis and design and B operation with time decomposition. Three operating states. Objective: minimize total annualized cost. Algorithm: a hybrid of Particle Swarm Optimization (PSO) and Struggle Genetic Algorithm (StrGA). 3. [PERSON]; [PERSON]; [PERSON]. _Energy_**2013**. System: steam methane prereformer for marine molten carbonate fuel cells (MCFC) fueled by liquefied natural gas (LNG). Design optimization at nominal operating conditions. Objective: minimization of the total irreversibility of the system subject to design, space, technical, and operational constraints. Algorithm: SQP implemented in gPROMS software. 4. [PERSON]; [PERSON]; [PERSON]; [PERSON] _Energy_**2013**. System: ORC with heat from exhaust gases of a diesel engine of MCR 72,240 kW. Synthesis and design (boiler pressure only) optimization: determine the optimum working fluid, boiler pressure, and Rankine process layout. Objective: maximize thermal efficiency. Algorithm: GA.
5. [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] _Energy_**2014**. System: Kalina cycle with heat from exhaust gases of a large diesel engine. Design optimization (at nominal conditions) of four variations of the cycle: Reference cycle, Split cycle, Reference cycle with reheat, Split cycle with reheat. Objective: maximize net power output (equivalent to maximum efficiency, because the inlet and outlet temperatures of the exhaust gases are considered fixed). Algorithm: GA.
6. [PERSON]; [PERSON]; [PERSON] _Ocean Engineering_**2015**. System: initial--two diesel main engines driving one propeller and one shaft generator and two DG sets of a Panamax product/chemical tanker. Retrofit: ORC operating on exhaust gas heat of the main engines. Design and operation optimization. Discretized annual load profile. Objective: minimization of fuel consumption. Economic evaluation is performed after optimization, for the optimal system. Algorithm: GA.
7. [PERSON]; [PERSON] _International Journal of Thermodynamics_**2015**. System: ORC with heat from the cooling circuit (charge air, cylinder cooling water, and lubricating oil). Evaluation criteria:technical, economic, environmental. Design and operation optimization at two levels. Four operating modes. Objectives: Operation--maximize the net savings in each one of the four modes of operation considered. Design--maximize NPV. Algorithm: at each level, GA determines a near optimal solution, while GRG2 determines the optimal solution. * [PERSON] et al.