An exponential increase in energy demand worldwide induces researchers to opt foralternative energy sources that are cleaner. The most effective solution to the global warming risk is to use sustainable sources. Researchers consider oceans can contribute towards environmentally friendly energy. The energy carried by the ocean through tides and waves creates a vast source of kinetic energy. Tidal, Photovoltaic (PV), Wind Energy, and Wave Energy are essential ocean energy resources identified by the researchers. The energy from these sources is termed as Marine Renewable Energy (MRE). When disconnected from the primary grid, energy sources work in isolation mode. The intermittent nature of MRE reckons using an energy management system in its isolation mode. Energy Storage Systems (ESS) act as the energy buffer considering the erratic nature of MRE. Using excessive power from generators, ESS stores energy and supplies when power from the MRE is scarce. Energy storage consultant considers ESS’s robustness and futuristic potential while selecting Energy Storage alternatives. Performance parameters of these alternatives help the consultants choose the appropriate ESS. Performance parameters (qualitative and quantitative) of the ESS alternatives are the criteria for deciding the best ESS alternative. ESS selection is a Multiple Criteria Decision Making (MCDM) problem with multiple criteria and alternatives. MCDM method is the complex decision-making process that can solve the selection of alternatives in this multicriteria /multi- alternative situation. This research attempts to select the best ESS among alternatives using MCDM methods. MCDM method develops a multi-objective formulation in which the performance parameters of each alternative are compared to other alternatives. Energy density, power rating, discharge time, cycle efficiency, lifetime, and specific cost are the criteria to choose the best ESS. The alternatives chosen are Pumped Hydro Storage, Flywheel battery, Lithium Battery, Sodium Sulphur Battery, Lead Acid Battery, Compressed Air Energy Storage, Redox Flow Battery, and Nickel Cadmium Battery. MCDM problem is solved using the Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) method, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Preference ranking organization method for enrichment evaluation(PROMETHEE) methods. Results obtained from these MCDM methods are investigated. The VIKOR method is found to be most promising in the overall performance. MATLAB-based models are developed for all the three methods, and the suitable method for accurate decision-making for selecting the most appropriate ESS is determined. The chapters of the thesis are organized as follows. Chapter 1 discusses working with different MRE systems and ESS alternatives that can be used for MRE. The motivation for the research is also discussed. Chapter 2 reviews the existing literature, highlighting different MCDM applications and the gaps in the previous implementations. Chapter 3 defines the problem statement of the research. Chapter 4 states the objectives of this research. Chapter 5 introduces the importance of MCDM systems and discusses the methodology involved in all three MCDM methods. Chapter 6 details the MCDM formulation used for the rest of the thesis. Chapter 7 discusses the results obtained by the TOPSIS and PROMETHEE methods. The results obtained by the VIKOR method are explained in-detail as this research found VIKOR more feasible for the Energy storage system selection. Chapter 8 concludes the thesis, followed by references.