Among the many potential future energy sources, hydrogen stands out as particularly promising. Because it is a green and renewable chemical process, water electrolysis has earned much interest among the different hydrogen production techniques. Seawater is the most abundant source of water and the ideal and cheapest electrolyte. The first part of this review includes the description of the general theoretical concepts: chemical, physical, and electrochemical, that stands on the basis of water electrolysis. Due to the rapid development of new electrode materials and cell technology, research has focused on specific seawater electrolysis parameters: the cathodic evolution of hydrogen; the concurrent anodic evolution of oxygen and chlorine; specific seawater catalyst electrodes; and analytical methods to describe their catalytic activity and seawater electrolyzer efficiency. Once the specific objectives of seawater electrolysis have been established through the design and energy performance of the electrolyzer, the study further describes the newest challenges that an accessible facility for the electrochemical production of hydrogen as fuel from seawater must respond to for sustainable development: capitalizing on known and emerging technologies; protecting the environment; utilizing green, renewable energies as sources of electricity; and above all, economic efficiency as a whole.

Hydrogen (H₂) is the most abundant element in the universe and it is also a neutral energy carrier, meaning the environmental effects of using it are strictly related to the effects of creating the means of producing of that amount of Hydrogen. So far, the H₂ generation by water electrolysis research field did not manage to break the efficiency barrier in order to consider H₂ production as a technology that sustains financially its self-development. However, given the complexity of this technology and the overall environmental impacts, an up-to-date research and development status review is critical. Thus, this study aims to identify the main trends, achievements and research directions of the H₂ generation using pure and alkaline water electrolysis, providing a review of the state of the art in the specific literature. Methods: In order to deliver this, a Systematic Literature Review was carried out, using PRISMA methodology, highlighting the research trends and results in peer review publish articles over more than two years (2020–2022). Findings: This review identifies niches and actual status of the H₂ generation by water and alkaline water electrolysis and points out, in numbers, the boundaries of the 2020–2022 timeline research.

Economic dispatch, emission dispatch, or their combination (EcD, EmD, EED) are essential issues in power systems optimization that focus on optimizing the efficient and sustainable use of energy resources to meet power demand. A new algorithm is proposed in this article to solve the dispatch problems with/without considering wind units. It is based on the Social Group Optimization (SGO) algorithm, but some features related to the selection and update of heuristics used to generate new solutions are changed. By applying the highly disruptive polynomial operator (HDP) and by generating sequences of random and chaotic numbers, the perturbation of the vectors composing the heuristics is achieved in our Modified Social Group Optimization (MSGO). Its effectiveness was investigated in 10-unit and 40-unit power systems, considering valve-point effects, transmission line losses, and inclusion of wind-based sources, implemented in four case studies. The results obtained for the 10-unit system indicate a very good MSGO performance, in terms of cost and emissions. The average cost reduction of MSGO compared to SGO is 368.1 $/h, 416.7 $/h, and 525.0 $/h for the 40-unit systems. The inclusion of wind units leads to 10% reduction in cost and 45% in emissions. Our modifications to MSGO lead to better convergence and higher-quality solutions than SGO or other competing algorithms.

Short-term load forecasting (STLF) is a fundamental tool for power networks’ proper functionality. As large consumers need to provide their own STLF, the residential consumers are the ones that need to be monitored and forecasted by the power network. There is a huge bibliography on all types of residential load forecast in which researchers have struggled to reach smaller forecasting errors. Regarding atypical consumption, we could see few titles before the coronavirus pandemic (COVID-19) restrictions, and afterwards all titles referred to the case of COVID-19. The purpose of this study was to identify, among the most used STLF methods—linear regression (LR), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN)—the one that had the best response in atypical consumption behavior and to state the best action to be taken during atypical consumption behavior on the residential side. The original contribution of this paper regards the forecasting of loads that do not have reference historic data. As the most recent available scenario, we evaluated our forecast with respect to the database of consumption behavior altered by different COVID-19 pandemic restrictions and the cause and effect of the factors influencing residential consumption, both in urban and rural areas. To estimate and validate the results of the forecasts, multiyear hourly residential consumption databases were used. The main findings were related to the huge forecasting errors that were generated, three times higher, if the forecasting algorithm was not set up for atypical consumption. Among the forecasting algorithms deployed, the best results were generated by ANN, followed by ARIMA and LR. We concluded that the forecasting methods deployed retained their hierarchy and accuracy in forecasting error during atypical consumer behavior, similar to forecasting in normal conditions, if a trigger/alarm mechanism was in place and there was sufficient time to adapt/deploy the forecasting algorithm. All results are meant to be used as best practices during power load uncertainty and atypical consumption behavior.

The transition to cleaner energy sources necessitates an in-depth understanding of the transport characteristics, losses, and opportunities associated with various gaseous fuels, including hydrogen, methane, and their mixtures, such as hythane. Hydrogen (H₂), the most abundant element in the universe, is increasingly recognized as a viable alternative to fossil fuels, primarily due to its potential to reduce carbon footprints as a cleaner energy source. Gradually gaining prominence in the energy market, it is displacing other fuels such as methane. In some transport systems, hydrogen is mixed with methane (CH₄) in order to reduce the carbon footprint while using the same existing production equipment. As more and more large methane consumers are implementing this mixture, we would like to see how the research has followed the market trend. An up-to-date research, development, and implementation status review is critical. This study aims to identify the main indicators of H₂ and CH₄ transport losses in pipes, providing a review of the state of the art in the specific literature. To deliver this, a systematic literature review (SLR) was carried out using preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology, pinpointing the research trends and results in peer review-published articles over a period of twelve years (2012–2024). Findings: this review identifies and points out, in numbers, the boundaries of the 2012–2024 timeline research.