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.
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 paper represents a reaction to the alarm signal made by the physician of Oradea's Power Distribution Company (S.D. Oradea). The physician noticed above the average values tendency to illness, by the operating personnel from the electric stations. The first part contains some considerations on the risk concept. References are made to risk factors, evaluation of damage level, and risk management in power companies. The second part presents the results of the study made in S.D. Oradea, regarding the electromagnetic pollution in high and medium voltage stations. There are presented maximum values of electric field intensity distribution and the induction of magnetic field; references are made on the risk's influence on the electric station operators.
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.
The paper is structured in three parts. The first part explains the parametrical reliability of the power transformers (PT) in oil in context with its global reliability, taking into account the parameters that defines the state of PT. Is presenting the proposed model to parametrical reliability evaluate of PT. There are given mathematical expressions of the parametrical reliability, in relation with the three parametrical categories, defined for the state of PT viewing the general state of the insulation, the traditional parameters of PT oil, the content of gases in the oil of transformer and its weight. There explains the parametrical risk failure of PT and its global parametrical reliability. In the second part are presented the studies results, effected to a number of 29 PT, the nominal power being between [10 ÷ 25] MVA, located in electric stations of 110 kV/MV within the frame of analyzed power transmission and distribution system (PTDS), administrated by Electric Energy distribution and transmission Branch of Oradea -Romania Distribution Power and Supply (DSPO). There are determinate the paths successions stages by technical diagnosis of PT and there is exemplified the state parameters evolution in time. There gives the values of parametrical reliability function in relation with the three parametrical categories defined for the PT state. There is presented a assessment between the failure risk by derive of parameter and the unexpectedly failure risk by the analyzed PT. The conclusions as well as the recommendations to the analyzed PT exploitation activities are presented in the last part of the paper.
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