Optimal design and performance analysis of photovoltaic power systems for solar vehicles

Optimal design and operation of a low-temperature waste heat recovery system incorporating thermal storage and auxiliary boiler for agricultural greenhouse heating

Understanding the nuances of climate change on buildings in desert areas is a timely topic with several socioeconomic implications. This study quantifies the impacts of future climate variability and extreme events on the optimal design of renewable energy systems (RES) for buildings in Saudi Arabia. A comprehensive framework integrating multi-model climate projections, extreme event analysis, and stochastic optimization is developed to evaluate system reliability and economic performance under future climate uncertainty. Hourly downscaled climate data spanning 2025–2099 across multiple Shared Socioeconomic Pathways (SSP) are considered, and stochastic optimization is used to determine RES configurations that minimize life cycle cost (LCC) across all scenarios. Analyses are conducted at hourly resolution over three future 25-year periods: 2025–2049, 2050–2074, and 2075–2099. Results indicate that differences between climate scenarios become more pronounced in the late-century period (2075–2099), leading to increased sensitivity of optimal RES design to climate conditions. The stochastic design ensures higher operational reliability than systems optimized solely for a high-emission scenario, with a 3.1% increase in LCC. Relative to the sustainable scenario, the high-emission scenario requires larger RES capacities, particularly in battery storage, resulting in a 20% higher LCC. Accounting for extreme events from an additional 24 scenarios from multiple climate models increases the LCC by 31.7%, highlighting the cost of resilience in an uncertain future climate. • Climate change affects building energy demand and renewable supply in desert areas. • High-emission pathways increase life cycle costs by 20% compared to sustainable ones. • A stochastic-based design improves system reliability with only a 3.1% cost increase. • Extreme weather events across 24 scenarios increase system costs by 31.7% • The best renewable system design is highly sensitive to late-century climate shifts.

• Power profile synthesis via a probability-based downsampling method. • Energy system design and lifetime cost optimization, ensuring vessel stability. • Model includes combinatorial placement decisions for energy systems and ballast. • Use of advanced MINLP solver (SCIP). • Fuel costs: 74.2%, CAPEX: 24.5% of total lifetime energy system costs. Low total lifetime cost is essential for the adoption of zero-emission ship energy systems, which must meet operational power demands while complying with onboard safety regulations. However, many studies rely on a simplified, averaged or insufficiently representative load profile and treat system design, operation, and integration feasibility separately, which can distort lifetime cost assessments and result in practically infeasible retrofit concepts. This study investigates how a hydrogen-based ship energy system can be optimally sized, operated, and arranged onboard to minimize total lifetime cost while satisfying operational constraints and stability requirements for a general cargo vessel retrofit. A representative power profile is synthesized from one year of operational data using a probability-based downsampling method and then used in a mixed-integer nonlinear lifetime cost optimization with discrete placement and ballast decisions, solved using the SCIP solver. The optimal retrofit comprises 1.4 MW of fuel cells, 180 kWh of batteries, and a 146 m 3 liquefied hydrogen (LH 2 ) tank, requires 171 t of ballast to satisfy trim and vertical stability constraints, and is primarily driven by fuel costs, which account for 74% of the total lifetime cost. Overall, the results indicate that the viability of hydrogen-based ship retrofits primarily depends on LH 2 storage integration constraints and hydrogen price assumptions, and that the proposed framework provides a practical basis for lifetime cost assessment of feasible retrofit designs.

• A residential photovoltaic energy supply system is modelled and analysed. • Hydrogen and battery storages are used for energy balancing. • Fuel cell waste heat is integrated with a heat pump and thermal energy storage. • Optimal sizing of system components determined by modelling and simulation. • Simple yet effective energy management algorithm is provided. This paper analyses a self-sustained, green electricity supply system for residential buildings based on photovoltaic generation supported by battery and hydrogen energy storage. Photovoltaic power generation depends on season, time of day, and weather, and is inherently out of sync with residential electricity demand. This imbalance can be addressed through short-term storage using batteries and long-term storage using a hydrogen system composed of an electrolyser, hydrogen storage, and a fuel cell. However, the high cost of technological equipment results in high annual costs of electricity and heat supply, making optimal system design and operation essential. To address this challenge, a techno-economic simulation model of the entire system is developed to support optimal component sizing and process control. Compared to related studies, the proposed approach employs simple and transparent techno-economic models, enabling adaptability to specific use cases. A power management algorithm is introduced to prioritise battery-based daily balancing and hydrogen-based seasonal balancing. The simulation study provides full-year energy flow profiles, detailed annual energy balance results, and a breakdown of electricity supply costs. Thermal integration of the fuel cell and heat pump is also considered to improve overall system efficiency. Results indicate that, with appropriate sizing and control, the annual electricity supply cost is approximately 4300 EUR for a state-of-the-art single-family house, which may be competitive in regions with high electricity and transmission costs.

Abstract In the development of offshore wind power in deep and far seas, the dynamic response characteristics of floating wind turbines and the tension safety of mooring systems are core indicators for structural design. Aiming at the problem that a single simulation tool is difficult to accurately couple the dynamic behaviors of the fluid-floating body-mooring system, this paper establishes a co-simulation platform of OpenFOAM and Moordyn. Taking the OC3-Hywind semi-submersible floating wind turbine as the research object, the RANS equations are used to solve the hydrodynamic forces, and the lumped mass method is adopted to discretize the composite mooring system, realizing the strong coupling simulation of the fluid-floating body-mooring system. The co-simulation method proposed in this paper can provide technical support for the optimal design of mooring systems for floating wind turbines.

CFD-guided thermodynamic evaluation of zeotropic mixtures in vertical channels for sustainable heat pump systems

Optimal design and operation of a solar-based multi-energy system for precast concrete plants

Optimal layout design of the propulsion shafting system of a ship with a shaft generator

Techno-economic feasibility and optimal design of grid-connected PV system with energy storage: A case study for Malaysia’s institutional

Hippopotamus algorithm for optimal sizing of hybrid renewable energy system

Multi-Timescale Scheduling Optimization of ALK/PEM Hybrid Electrolyzers System Considering Flexible Hydrogen Demand

Optimal design and energy management of a hybrid PV-Wind system with hydrogen and gravity energy storage: An off-grid sustainable alternative for coal power in Morocco

Integrating green hydrogen production and electrical energy storage in energy communities under uncertainty

The article has considered renewable energy sources with high energy potential, which in the near future will become the fastest growing source of electricity. Generation sources include solar, wind, and biomass resources, which contribute to economic growth and reduce pollution. Optimizing the renewable and sustainable energy project is a key factor as a reliable alternative to conventional hydrocarbons, as well as as an energy source. It can play a significant role in the future of renewable and sustainable energy in Iraq. In the work, Helioscope and HOMER Pro software are used to create a small model connected to a network and to estimate energy consumption for optimization purposes. The results have showed an internal rate of return of 12 %, as well as about 8.5 % return on investment, and the share of the renewable energy component is almost 99.7 %. The proposed method proved to be effective in terms of using renewable energy. The research can be applied in any country, especially in the neighboring countries of Iraq.

AC battery systems (ACBSs) based on multilevel converters (MLCs) have gained considerable attention in recent times for the provision of grid services due to high-power (HP) and high-energy (HE) capabilities. In a hybrid ACBS, multiple low-voltage ports provide DC interfaces for battery modules from the same or different chemistries, enabling flexible operation across a wide range of grid services. However, the design complexity increases substantially, due to (i) higher electrothermal coupling between heterogeneous battery modules and power electronic (PE) switches, (ii) grid compliance constraints and (iii) power quality requirements, which often leads to conservative oversizing and, consequently, increased total cost of ownership (TCO). To address these challenges, this paper proposes a co-design optimization framework for the sizing and selection of battery modules, PE components, and MLC architecture. A multi-fidelity modeling approach is presented to co-simulate the battery modules and MLC. The model captures electrochemical behavior, degradation dynamics, and power losses to enable accurate estimation of system-level energy efficiency. The framework then leverages a multi-objective nondominated sorting genetic algorithm (NSGA-II) to perform optimal cell-to-module sizing across different chemistries and MLC levels, while incorporating the inter-module balancing and AC power quality constraints. Comparative simulation studies show that the proposed co-design framework achieves life-cycle TCO reduction of 3.5%, 4.5% and 20% relative to non-hybrid (single chemistry) configurations based on LFP, NMC and LTO chemistries, respectively. The test results validate the effectiveness of the proposed co-design methodology for the optimal design of grid-tied AC battery systems.

Abstract As a core technology for autonomous navigation technology, inertial navigation offers high disturbance robustness as well as low observability. It plays a crucial role in various domains, including underwater vehicle operations. The accuracy of the inertial navigation calculation determines the precision of underwater navigation and positioning. However, owing to the non-uniformity of the gravitational field distribution of the Earth and the influence of component errors, the performance of inertial navigation degrades over long-term operation as it is influenced by the gravitational field of the Earth. Conventional inertial navigation replaces the actual gravitational field with an idealized normal gravitational field for computational simplicity. However, in complex underwater environments, such gravity-modeling approximations compromise overall solution accuracy. This study investigates the application of underwater gravity compensation in inertial navigation and examines its comprehensive influence on navigation performance, including compensation algorithms based on the spherical harmonic function model of the gravity field and gravity compensation methods for long-duration inertial navigation based on attitude damping. Simulation and experimental results demonstrated that the use of the gravity compensation method with attitude damping significantly improved the navigation solution accuracy of low-speed and long-endurance carriers. The final on-board measurement experiment results show that by adopting attitude damping for gravity compensation, the latitude accuracy of inertial navigation will increase by more than 10%, and the longitude accuracy will increase by over 60%. These findings provide theoretical support for the optimal design of inertial navigation systems and offer practical guidance for implementing gravity compensation techniques in engineering applications.

The technological devices and navigation equipment used on ships can be exposed to cyber-attacks. These attacks pose significant risks to life and property safety and can cause substantial economic damage to maritime enterprises. The aim of this study is, in light of academic research and past cyber incidents, to reveal potential cyber threats to ships and to suggest safer navigation support systems in terms of cybersecurity. The Bayesian Networks method was employed in the cybersecurity assessment of the systems. In the Bayesian network, nodes contributing to cybersecurity risks and the relationships between these nodes have been identified. Based on the possible scenarios constructed through conditional probability tables, this study aims to provide an answer to the question of how an optimal cybersecurity system should be designed for ships. In this context, alongside the theoretically ideal system design, a proposal for a practically applicable optimal design has also been developed. The theoretical optimal system design is structured under ideal conditions, incorporating maximum security measures in every component (e.g. no internet connection, use of devices from different brands, robust network infrastructure, etc.), whereas the practical system is designed with consideration of the current technological infrastructure and applicability on ships. The study has shown a significant difference between the theoretically most cyber-secure and the most cyber-insecure scenarios. This highlights significant potential improvements for corrective and preventive actions. The findings also show that satellite or radio-based navigation systems such as Positioning System and AIS pose significant cyber risks. However, it has been revealed that the real risk lies in computer technologies and computer-based systems. The study provides useful outputs for industry stakeholders and other relevant parties involved in efforts to create cyber-secure ship systems.

This study presents a comprehensive thermal analysis, design, and optimization framework for electrothermal heating systems integrated into composite wing structures. Thermal behavior is first investigated using finite volume simulations conducted with a commercial solver. An in-house thermal solver is then developed based on the governing heat transfer equations and a second-order finite difference discretization scheme. The in-house solver is validated against the commercial solver, showing a maximum deviation of less than 1%. The validated solver is subsequently coupled with a genetic algorithm to perform multi-objective optimization of the electrothermal heating system. A novel correlation for the convection heat transfer coefficient over airfoil surfaces is developed based on extensive turbulent flow simulations and a genetic algorithm. The developed correlation equation has significantly lower percent relative error (from 34% to 6%) compared to flat plate correlations. The developed convection coefficient is incorporated into the optimization process. Key design variables, including heat generation intensity, heater strip dimensions, and the thermal conductivity of composite and surface protection materials, are included in the optimization process. An original objective function is formulated to simultaneously minimize electrical power consumption, prevent ice formation on the external surface, and limit internal temperatures to safe operating ranges for composite materials. The optimized design is evaluated under both spatially varying and constant convection heat transfer coefficients to assess the impact of convection modeling assumptions. The proposed methodology provides a unified and extensible framework for the optimal design of electrothermal ice protection systems and can be readily extended to three-dimensional composite wing configurations.

ABSTRACT With growing demand for fast, reliable, and flexible communication, free‐space optical (FSO) systems have seen significant advancements. However, weather and altitude have a significant impact on their performance, which requires an optimum system design. Using OptiSystem simulations, this research compares four hybrid techniques using three different multiplexings: space division multiplexing (SDM), wavelength division multiplexing (WDM), and polarization division multiplexing (PDM). With a maximum quality factor (Q‐factor) of 149.47 and 0% bit error rate (BER) in clear circumstances, the WDM and SDM hybrid system performs the best among the evaluated setups. In ideal conditions, the more complicated WDM, SDM, and PDM configurations perform competitively, but interchannel interference causes them to suffer under high attenuation. WDM and SDM system maintain a Q‐factor of 20 and are the most robust in severe weather conditions like fog and torrential rain. All things considered, the WDM and SDM system provides the best balance between performance, complexity, and practical dependability for FSO communication. While the proposed system model 1 introduces a scalable, forward‐looking architecture, it also offers trade‐offs between capacity and robustness that can be fine‐tuned for future high‐performance FSO networks.