Nowadays, our life needs more and more electricity, and our lives cannot be without electricity, which requires our power to develop more quickly. Power plants are undoubtedly the place where electricity is produced. And now most of the power plant or chemical energy can be converted into heat, and then through the heat to do power production. The boiler is the main part of the power plant. Boiler unit consists of boiler body equipment and auxiliary equipment. The main body of the boiler consists of 'pot' (soft drinks system) and 'furnace' (combustion system). Baotou thermal power plant is mainly burning gas. The gas and air are at a certain rate into the furnace burning. This can greatly reduce the pollution of the environment, but also the full use of fuel. The soda system is mainly carried out in the drum. The heat generated by the combustion system heats the water in the drum, producing steam and then pushing the steam turbine into mechanical energy and finally into electrical energy. This has a high demand for water level, water composition, and the temperature of the steam produced in the drum. The water level should have upper and lower bounds, keeping it within a certain range. Water level is too high, will affect the steam drum soda separation effect, so that the steam drum exports of saturated steam with water increased, causing damage to the turbine, will cause serious explosion. And the water level is too low, it will affect the natural circulation of the normal, serious will make the individual water pipe to form a free water, resulting in flow stagnation, resulting in local metal wall overheating and burst pipe. Water in the heating at the same time will form a lot of scale, if not the chemical treatment of water will be in the formation of scale in the drum, cleaning more difficult, so the damage to the drum. The pressure of the drum is also an important control variable, and pressure control is highly correlated with liquid level control. It is necessary to ensure the integrity of the equipment, but also to ensure safety, followed by ensuring that the process of normal operation of the drum water. This time, the design is mainly for the unit steam temperature control system design. Steam temperature is one of the important indicators of boiler operation quality. It is too high and too low will significantly affect the power plant safety and economy. If the temperature of the steam is low, it will cause the power plant to increase the heat consumption and increase the axial thrust of the turbine to cause the thrust bearing to overload, but also cause the steam turbine to increase the final steam humidity, thus reducing the efficiency of the turbine, aggravating the erosion of the blade. On the contrary, the steam temperature is too high will make the super-heater wall metal strength decreased, and even burn the high temperature of the super-heater, the steam pipe and steam turbine high-pressure part will be damaged, seriously affecting safety. The boiler temperature control system mainly includes the adjustment of the superheated steam and the reheat steam temperature. The superheated steam temperature is the highest temperature in the boiler soda system. The stability of the steam temperature is very important for the safe and economical operation of the unit. Therefore, in the boiler operation, must ensure that the steam temperature in the vicinity of the specified value, and the temperature of the super-heater tube wall does not exceed the allowable working temperature.

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.

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 Ecuadorian electricity sector encompasses generation, transmission, distribution and sales. Since the change of the Constitution in Ecuador in 2008, the sector has opted to employ a centralized model. The present research aims to measure the efficiency level of the Ecuadorian electricity sector during the period 2012–2021, using a DEA-NETWORK methodology, which allows examining and integrating each of the phases defined above through intermediate inputs, which are inputs in subsequent phases and outputs of some other phases. These intermediate inputs are essential for analyzing efficiency from a global view of the system. For research purposes, the Ecuadorian electricity sector was divided into 9 planning zones. The results revealed that the efficiency of zones 6 and 8 had the greatest impact on the overall efficiency of the Ecuadorian electricity sector during the period 2012–2015. On the other hand, the distribution phase is the most efficient with an index of 0.9605, followed by sales with an index of 0.6251. It is also concluded that the most inefficient phases are generation and transmission, thus verifying the problems caused by the use of a centralized model.

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.

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.