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[Display omitted] • Feasibility study of cold ironing implementation on the ferry ship. • Cooperative cold ironing with green energy to enhance emission neutrality. • Reducing system and operational costs with a strategic energy management approach. • Two-stage management strategy combining system sizing and operation optimization. The cold ironing system is gaining interest as a promising approach to reduce emissions from ship transportation at ports, enabling further reductions with clean energy sources coordination. While cold ironing has predominantly been applied to long-staying vessels like cruise ships and containers, feasibility studies for short-berthing ships such as ferries are limited. However, the growing demand for short-distance logistics and passenger transfers highlights the need to tackle emissions issues from ferry transportation. Incorporating electrification technology together with integrated energy management systems can significantly reduce emissions from ferry operations. Accordingly, this paper proposes a cooperative cold ironing system integrated with clean energy sources for ferry terminals. A two-stage energy management strategy combining sizing and scheduling optimization is employed to reduce the port's emissions while minimizing system and operational costs. The proposed system configuration, determined through the sizing method, yields the lowest net present cost of $9.04 M. The applied energy management strategy managed to reduce operational costs by up to 63.402 %, while significantly decreasing emissions from both shipside and shoreside operations. From the shipside, emissions reductions of 38.44 % for CO 2 , 97.7 % for NO X , 96.69 % for SO 2 , and 92.1 % for PM were achieved. From the shoreside, the approach led to a 28 % reduction across all emission types. Thus, implementing cold ironing powered by clean energy sources is a viable solution for reducing emissions generated by ferry operations. The proposed energy management approach enables emissions reduction and delivering cost-effectiveness at ferry terminals. [ABSTRACT FROM AUTHOR]

• Fast Tri-level optimization approach. • HRES includes PV panels, wind turbines and HESS. • Real weather and load data of the stand-alone HRES. • The optimal solution for sizing and EMS stages. • Minimize the capital cost and maximize the efficiency of the whole system. Renewable energy sources penetrate our recent life very deeply. They have more expansion chances in the nearest future, especially in stand-alone and micro grid fields. Due to the uncertainty of the weather and the non-matching between the generated energy and demand, a hybrid energy storage system (HESS) is required. The optimization computations are the best way to select the optimal values for the capacity, sizes and quantities of the stand-alone hybrid renewable energy system (HRES) to satisfy the load demands of the available climate conditions. In this paper, the HRES which includes PV panels, wind turbines, battery banks, hydrogen tanks with fuel cells and electrolyzers has been tested and optimized using a tri-level optimization problem. Using Matlab software, the simulation results validate that the proposed method converged quickly and accurately to the optimal solution. The total capital cost was between $127,400 to $231,750. The maximum average efficiency was 83.53% at a minimum total capital cost of $127,400 and a minimum operating cost of $67 which were achieved in the same summer month presented in July. [ABSTRACT FROM AUTHOR]

The growing demand for sustainable systems due to climate change has led to increased reliance on renewable energy sources. However, this transition has raised concerns about power quality in power systems due to climate variations and the intermittent nature of renewables, photovoltaic energy generation in particular. In this context, uninterruptible power supply systems play a crucial role in ensuring reliable and high-quality energy supply. As an added benefit, photovoltaic energy generation may be integrated into uninterruptible power supply systems by sharing the inverter already present and storing generated energy in the batteries. In this paper, it is presented the design and management of photovoltaic energy, integrated into double-conversion uninterruptible power supplies. A method for selecting the suitable number of panels to be used in series in a given application is developed, considering the panel model used, and the environmental mission profile. A management algorithm for tracking the maximum power point of the photovoltaic generation while ensuring the hold-up time is proposed, introducing the dynamic hold-up time concept. Using the point for maximum power instead of the dynamic hold-up time at two different locations leads to voltage sags of 12.6% in the first and 24.3% in the second. Using the method to select the number of panels in series, 13 panels are selected for the first location, resulting in an annual generation that is only 2.3% smaller than the maximum power point. The results are validated using a hardware-in-the-loop platform and the dSpace Microlabbox 1202. • Design and management of photovoltaic energy in uninterruptible power supplies. • Development of algorithms for selecting the appropriate number of panels in series. • Proposal of the dynamic hold-up time concept. [ABSTRACT FROM AUTHOR]

• HRES with PV-Wind and different types of energy storage systems. • Optimal size and efficient performance of HRES. • Bi-level mixed integer nonlinear programming optimization approach. • Real application of a stand-alone HRES in a real case study, Jordan. This paper aims to design and run a standalone hybrid renewable energy System (HRES) feeding residential building load. The suggested HRES encompasses photovoltaic panels and wind turbines as energy sources, combined with a hydrogen subsystem and a bank of batteries for energy storage. The meteorological input data includes irradiance, temperature, and wind speed for four seasonal weeks. These data sets are collected for a rural site situated in the town of Ras Munif, northern Jordan. The load profiles characterize a selected benchmark residential building. Consequently, a bi-level mixed integer nonlinear programming (BMINLP) problem is formulated to incorporate the designing problem with the energy management process. The upper level represents the sizing problem, while the lower level problem denotes the energy management strategy (EMS). Each problem has its independent objective function, constraints, and optimization variables. The EMS is an economic-based single objective optimization problem expressed as a mixed integer linear programming (MILP) problem. On the contrary, a mixed integer nonlinear programming (MINLP) approach frames the sizing problem to optimize a techno-economic-based multi-objective function. The interaction between the two problems is that the lower problem is an embedded constraint of the upper problem. Moreover, the candidate solutions from the upper problem are treated as fixed parameters in the lower problem. A multi-objective genetic algorithm is used to execute the overall problem by the MATLAB toolbox. The technical and economic performance parameters, including the investment cost, maintenance, operating costs, and others, are assessed based on the best findings. The key finding demonstrates that the summer week has the lowest total cost and energy loss factor, with around 132,000 $ and 0, respectively. Furthermore, the findings reveal that the entire system's energy loss factor for each sample period is less than 0.0009. This value is substantially less than the permitted limit of 0.01. [ABSTRACT FROM AUTHOR]