Most of the power demand at Container Terminals (CT) is related to Ship to Shore (STS) cranes. These cranes work simultaneously together for loading and unloading container. This issue causes the peak demand increase significantly. Considering the STS group crane's activity to move containers (from ship to shore and vice versa), finding the best delay time between STS cranes can play an important role to reduce the total power demand. The peak shaving strategy which has been used in this paper is Demand Side Management (DSM). DSM method increases e\square cient energy utilization and power quality of the system as well as the peak power and energy costs reduction. Simulations have been made for a preliminary evaluation of prospected efficiency goals. Results in MATLAB related to reference data shows the proposed method can reduce the peak power demand in STS group cranes around 60-70%. The simulations confirm also that the evaluation of the peak shaving assuming an equal time delay in the cranes duty offers acceptable preliminary estimates and reassures a simpler management.

Optimization of peak load shaving in STS group cranes based on PSO algorithm / Kermani, M.; Parise, G.; Martirano, L.; Parise, L.; Chavdarian, B.. - (2018), pp. 1-5. (Intervento presentato al convegno 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018 tenutosi a Campus of the University of Palermo, Complesso Didattico, Building 19, ita) [10.1109/EEEIC.2018.8494467].

Optimization of peak load shaving in STS group cranes based on PSO algorithm

Kermani, M.
;
Parise, G.;Martirano, L.;Parise, L.;
2018

Abstract

Most of the power demand at Container Terminals (CT) is related to Ship to Shore (STS) cranes. These cranes work simultaneously together for loading and unloading container. This issue causes the peak demand increase significantly. Considering the STS group crane's activity to move containers (from ship to shore and vice versa), finding the best delay time between STS cranes can play an important role to reduce the total power demand. The peak shaving strategy which has been used in this paper is Demand Side Management (DSM). DSM method increases e\square cient energy utilization and power quality of the system as well as the peak power and energy costs reduction. Simulations have been made for a preliminary evaluation of prospected efficiency goals. Results in MATLAB related to reference data shows the proposed method can reduce the peak power demand in STS group cranes around 60-70%. The simulations confirm also that the evaluation of the peak shaving assuming an equal time delay in the cranes duty offers acceptable preliminary estimates and reassures a simpler management.
2018
2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018
Demand Side Management; Microgrid; Particle Swarm Optimization; Peak Load Shaving; Ship to Sore Crane; Energy Engineering and Power Technology; Renewable Energy, Sustainability and the Environment; Electrical and Electronic Engineering; Industrial and Manufacturing Engineering; Environmental Engineering; Hardware and Architecture
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Optimization of peak load shaving in STS group cranes based on PSO algorithm / Kermani, M.; Parise, G.; Martirano, L.; Parise, L.; Chavdarian, B.. - (2018), pp. 1-5. (Intervento presentato al convegno 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2018 tenutosi a Campus of the University of Palermo, Complesso Didattico, Building 19, ita) [10.1109/EEEIC.2018.8494467].
File allegati a questo prodotto
File Dimensione Formato  
Kermami_optimization_2018.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 537.26 kB
Formato Adobe PDF
537.26 kB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1204660
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 11
  • ???jsp.display-item.citation.isi??? 6
social impact