In the current era, electromagnetic radiation is everywhere. Every day electromagnetic radiation and static electricity caused by a variety of hazards. So, anti-electromagnetic radiation and anti-static awareness gradually enjoys popular support, more attention are gained by people on the anti-electromagnetic radiation and anti-static. This caused radiation protection and anti-static clothing industry’s rise by the day. Radiation protection and anti-static clothing will enter various households to provide a certain amount of protection to the people's health. We discuss two parts in this paper, specifically from the effects of the electromagnetic radiation and electrostatic effects which started on radiation clothing and anti-static clothing. The main contents of this paper are as follows: The first part of the definition of electromagnetic radiation and its brief introduction, while explaining the types of electromagnetic radiation and electromagnetic radiation sources in daily lives, followed by the emphasis of serious harms on electromagnetic radiation on human health It is precisely because of electromagnetic radiation on people's lives have serious threat, that makes the development of radiation protection. This follows the basic introduction of the radiation suit and the development of radiation protection clothings. The development of radiation protection suits is an established industry. Materials made of radiation protection are constantly changing, but their basic working principle has not changed. Followed by the introduction of the basic principles of radiation protection clothings, we theoretically present specific analysis and demonstration. However, the theoretical analysis and practice is often consists a certain gap, so we highlight a few actual situations on the impact of radiation protection clothings. Finally, we present a simple discussion on wide range of applications of radiation protection clothings. The thought process of second part is similar as the first part, respectively, we introduce the health hazards and the impact on people's lives of electrostatic effect and static electricity . Followed by that it is the basic principles, relevant analysis and discussion of anti-static clothing Finally, we provide the detailed explanation of the application of anti-static clothing.

The increasing epileptic electricity supply, mainly in the residential areas of Nigerian cities, has been linked to the incorrect knowledge of the numerous socio-economic and physical indices that influence household electricity usage. Most of the seemingly identified explanatory factors were done at macro level which does not give a clear estimate of this electricity demand. The thrust of the study is to analyse empirically the household electricity determinants in Nigerian cities with a view to evolving a more informed and sustainable energy policy decision. Multistage area cluster sampling method was adopted in the study where 769 copies of structured questionnaire were distributed to electricity users of prepaid meters in five major Nigerian cities. The research hypothesis was tested using the multiple linear regression statistical tool. The result revealed that nine variables which include age (r = 0.05, p-value: 0.05), household income (r = 0.00, p-value: 0.05), number of hours that people stay outside the house (r = 0.043, p-value: 0.05), number of teenagers at home, (r = 0.006, p-value: 0.01) number of electrical appliances (r = 0.016, p-value: 0.01), type of house (r = 0.012, p-value: 0.01), hours that the electrical appliances are used (r = 0.043, p-value: 0.05), weather condition, (r = 0.011, p-value: 0.05) and the location of the building (r = 0.045, p-value: 0.05) were significant in determining the household electricity consumption. Policies based on the findings will give energy and urban planners an empirical basis for accurate and robust forecasting of the determinants that influence household electricity consumption in Nigeria that is devoid of any speculation or unfounded predictions.

The economic viability of a photovoltaic (PV) installation depends on regulations regarding administrative, technical and economic conditions associated with self-consumption and the sale of surplus production. Royal Decree (RD) 244/2019 is the Spanish legislation of reference for this case study, in which we analyse and compare PV installation offers by key suppliers. The proposals are not optimal in RD 244/2019 terms and appear not to fully contemplate power generation losses and seem to shift a representative percentage of consumption to the production period. In our case study of a residential dwelling, the best option corresponds to a 5 kWp installation with surplus sale to the market, with a payback period of 18 years and CO₂ emission reductions of 1026 kg/year. Demand-side management offers a potential improvement of 6%–21.8%. Based on the increase in electricity prices since 2020, the best option offers savings of up to €1507.74 and amortization in 4.24 years. Considering costs and savings, sale to the market could be considered as the only feasible regulatory mechanism for managing surpluses, accompanied by measures to facilitate administrative procedures and guarantees for end users.

To gain a deep understanding of maintenance and repair planning, investigate the weak points of the distribution network, and discover unusual events, it is necessary to trace the shutdowns that occurred in the network. Many incidents happened due to the failure of thermal equipment in schools. On the other hand, the most important task of electricity distribution companies is to provide reliable and stable electricity, which minimal blackouts and standard voltage should accompany. This research uses seasonal time series and artificial neural network approaches to provide models to predict the failure rate of one of the equipment used in two areas covered by the greater Tehran electricity distribution company. These data were extracted weekly from April 2019 to March 2021 from the ENOX incident registration software. For this purpose, after pre-processing the data, the appropriate final model was presented with the help of Minitab and MATLAB software. Also, average air temperature, rainfall, and wind speed were selected as input variables for the neural network. The mean square error has been used to evaluate the proposed models’ error rate. The results show that the time series models performed better than the multi-layer perceptron neural network in predicting the failure rate of the target equipment and can be used to predict future periods.

Electricity consumption in Europe has risen significantly in recent years, with households being the largest consumers of final electricity. Managing and reducing residential power consumption is critical for achieving efficient and sustainable energy management, conserving financial resources, and mitigating environmental effects. Many studies have used statistical models such as linear, multinomial, ridge, polynomial, and LASSO regression to examine and understand the determinants of residential energy consumption. However, these models are limited to capturing only direct effects among the determinants of household energy consumption. This study addresses these limitations by applying a path analysis model that captures the direct and indirect effects. Numerical and theoretical comparisons that demonstrate its advantages and efficiency are also given. The results show that Sub-metering components associated with specific uses, like cooking or water heating, have significant indirect impacts on global intensity through active power and that the voltage affects negatively the global power (active and reactive) due to the physical and behavioral mechanisms. Our findings provide an in-depth understanding of household electricity power consumption. This will improve forecasting and enable real-time energy management tools, extending to the design of precise energy efficiency policies to achieve SDG 7’s objectives.

This study aims to explore the implications of imported electrical equipment in Indonesia, analysing both short-term and long-term impacts using a quantitative approach. The research focuses on understanding how various economic factors, such as domestic production, international pricing, national income, and exchange rates, influence the country’s import dynamics in the electrical equipment sector. Employing an Error Correction Model (ECM) for regression analysis, the study utilises time-series data from 2007 to 2021 to delve into the complex interplay of these variables. The methodology involves a comprehensive analysis using the Augmented Dickey-Fuller and Phillips-Perron tests to assess the stationarity of the data. This approach ensures the robustness of the ECM, which is employed to analyse the short-term and long-term effects of the identified variables on electrical equipment imports in Indonesia. The results reveal significant relationships between these economic factors and import levels. In the short term, imports are shown to be sensitive to changes in domestic economic conditions and international market prices, while in the long term, the country’s economic growth, reflected through GDP, emerges as a significant determinant. The findings suggest that Indonesia’s electrical equipment import policies must adapt highly to domestic and international economic changes. In the short term, a responsive approach is required to manage the immediate impacts of market fluctuations. The study highlights the importance of aligning import strategies with broader economic growth and environmental sustainability goals for long-term sustainability. Policymakers are advised to focus on enhancing domestic production capabilities, reducing import dependency, and ensuring that environmental considerations are integral to import policies. This study contributes to understanding import dynamics in a developing country context, offering valuable insights for policymakers and industry stakeholders in shaping strategies for economic growth and sustainability in the electrical equipment sector. The findings underscore the need for a balanced, data-driven approach to managing imports, aligning short-term responses with long-term strategic objectives for Indonesia’s ongoing development and industrial advancement.