Shipboard microgrids (SBMGs) are becoming increasingly popular in the power industry due to their potential for reducing fossil-fuel usage and increasing power production. However, operating SBMGs poses significant challenges due to operational and environmental constraints. To address these challenges, intelligent control, management, and protection strategies are necessary to ensure safe operation under complex and uncertain conditions. This paper provides a comprehensive review of SBMGs, including their classifications, control, management, and protection, as well as the most recent research statistics in these areas. The state-of-the-art SBMG types, propulsion systems, and power system architectures are discussed, along with a comparison of recent research contributions and issues related to control, uncertainties, management, and protection in SBMGs. In addition, a bibliometric analysis is performed to examine recent trends in SBMG research. This paper concludes with a discussion of research gaps and recommendations for further investigation in the field of SBMGs, highlighting the need for more research on the optimization of SBMGs in terms of efficiency, reliability, and cost-effectiveness, as well as the development of advanced control and protection strategies to ensure safe and stable operation.

Different energy requirements of the residential sector are varied, such as electricity, heating, cooling, water, etc., and these necessities are met by multi-energy systems using various energy sources and converters. In this paper, an optimal day-ahead operation of a large residential demand sector is presented based on the energy hub (EH) model with combined heat and power (CHP) as a cogeneration system. The purpose of the optimization is to maximize social welfare (SW) and minimize environmental emissions subjected to numerous technical constraints. To explore the effectiveness of the proposed model, real cases were studied and results were analyzed. Moreover, to evaluate the efficiency of the proposed methodology, the Archimedes optimization algorithm (AOA) is implemented for optimizing the EH system. The performance of the AOA is compared with the genetic algorithm, and the results depict that the AOA is better in terms of convergence speed and global search ability. Implementation of the proposed framework shows that the total SW is increased by 27.44% and environmental emissions are reduced by 18.36% compared to the base case without the EH. Additionally, there is 512.26 MWh and 149.4 m³ as a surplus in the electricity and water that are sold to every network, respectively.

Grid connected electric vehicles (EVs) can provide energy quality services to ease intermittent renewable energy sources dependent, enhance grid stability performance, reliability and load balancing in the power system. Moreover, incorporating sufficient EVs into the power grid will assist reduce greenhouse gases. However, the unrestrained EVs charging impact the raise of peak request, frequency deflection, voltage instability, power quality from the acceptable limits. It can also cause overloading of the power system equipment and an increase in power losses. In this paper, the influences EV technologies on various energy systems, control scheme strategy, benefits, and motivational challenges are investigated. An overview of the impacts of uncontrolled EV loading on the electric power system and how controlled charging becomes benefit impacts is presented. Moreover, a review of the controlled charge and discharge benefits of EVs and the electrical serving involved in reduction of frequency deviation, voltage stability, power quality improvement is introduced. This review shows that integration of optimal control of EVs with a suitable optimization technique can improve and provide on time multi ancillary services of EV integrated with weak grid. In addition, this review provides research tracks which can be followed by researchers.

Energy consumption is growing in parallel with growth of economy. To meet needs of industrial, commercial and local users and to enable transfer of people and goods, a sufficient supply of energy must be provided. The energy infrastructure needs to be increased and diversified to provide energy needed by each region for future economic growth. The consideration of multiple energy carriers, not only electricity, represents an opportunity for system improvement. The couplings among different infrastructures must be taken into consideration in the light of the idea of "energy hub". This paper introduces a general modelling and optimization approach for power dispatch and conversion in energy systems including different energy carriers. Loads are supplied using different structures of energy hub to get the optimal structure of the hub. Finally, the approach is demonstrated in numerical case studies.

Seawater desalination is an attractive choice especially for remote areas where freshwater is rare. Egypt is moving toward the desalination of water as an alternative solution to the decrease in freshwater. The main objective of this study was to design an optimal, economic, and efficient hybrid system that feeds the electric needs of a small-scale brackish reverse osmosis desalination unit and a tourism motel located in Hurghada, Egypt. The optimization problem of sizing different components of hybrid system is a complicated one; it needs a special tool capable of solving it rapidly and effectively. Three different hybrid system scenarios are discussed to select the most optimum combination of them. These scenarios are the following: wind/PV/battery, wind/PV/diesel, and wind/PV/battery/diesel. In this study, a modified particle swarm optimization technique is applied for optimum sizing of the proposed hybrid system scenarios. The optimization problem is solved to minimize the annual total investment cost considering CO₂ emissions cost.