Name
Abstract | ||
|---|---|---|
Recently an increase in electrical power installed on board ships has been revealed, especially for large Cruise ships and All Electric Ships (AES). In this context, the traditional approaches to Electrical Power Load Analysis (EPLA) and generation system size have become inadequate and inaccurate. Aim of this work is to propose an alternative method to perform an EPLA based on a stochastic modelling of loads, which are then combined together with a variant of the Monte Carlo Simulation (MCS) in order to calculate the total power demanded. The optimal selection of the generation system size is modelled as a Mixed-Integer Non Linear Problem (MINLP) and solved applying Genetic Algorithms (GA). The results here proposed shown that there is the real opportunity to apply stochastic approach in order to reduce the mission and installation costs of shipboard power systems with significant savings. |
Year | Venue | Keywords |
|---|---|---|
2017 | 2017 IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE EUROPE (ISGT-EUROPE) | Electric vehicle, Uncertainty management, electric power load analysis, optimal scheduling, power system optimal planning |
Field | DocType | ISSN |
Electric power,Mathematical optimization,Monte Carlo method,Computer science,Electric vehicle,Electric power system,Optimal design,Stochastic modelling,Genetic algorithm,Electricity generation | Conference | 2165-4816 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alessandro Boveri | 1 | 0 | 0.34 |
| Paola Gualeni | 2 | 0 | 0.34 |
| Diego Neroni | 3 | 0 | 0.34 |
| Federico Silvestro | 4 | 22 | 6.38 |