Stochastic and distributed scheduling of shipboard power systems using MθFOA-ADMM

Mohamed A. Mohamed, Hossein Chabok, Emad Mahrous Awwad, Ahmed M. El-Sherbeeny, Mohammed A. Elmeligy and Ziad M. Ali

Energy, 2020, vol. 206, issue C

Abstract: This article introduces an effective stochastic operation framework for optimal energy management of the shipboard power systems including large, nonlinear and dynamic loads. The proposed framework divides the ship power system into several agents, which coordinate with each other based on their demands/supplies until. The alternating direction method of multipliers (ADMM) is deployed as the multi-agent framework to solve the reformulated distributed energy management problem in the ship. Two types of turbo-generators are considered in the proposed system model, including single-shaft and twin-shaft models, to increase the part-load efficiency in certain times when facing variable speed operation. The proposed distributed framework is equipped with a recursive mechanism, which helps the ship system for running optimal load scheduling when facing insufficient power generation. In order to model the uncertainty effects associated with the forecast error in the interval-ahead load demand, a stochastic framework based on unscented transform is devised which can work in the nonlinear and correlated environments of shipboard power systems. Due to the nonlinear cost function in each agent, a powerful optimization algorithm based on modified θ-firefly algorithm (Mθ-FOA) is proposed. This is a phasor algorithm, which helps for escaping from premature convergence and getting trapped in local optima. The appropriate performance of the proposed stochastic model is examined on the real dataset of a ship power system. The simulation results show the high robustness, guarantied consensus, economic operation and feasible solution when power generation shortage based on load shedding in the system.

Keywords: Energy management; Shipping transport; Alternating direction method of multipliers; Load scheduling; Uncertainty; θ-firefly algorithm (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544220311488
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:206:y:2020:i:c:s0360544220311488

DOI: 10.1016/j.energy.2020.118041

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().