Analysis Of Electric Power Consumption Research Articles

The combined effect of carbon fiber and carbon nanotubes on the electrical and self-heating properties of cement composites

This work investigates the electrical and heating performance of conductive cement composites by using carbonaceous materials (carbon fibers (CF) and carbon nanotubes (CNT)) as conductive materials. Various volume fractions of carbonaceous materials were used to indicate the electrical heating performance of the cement composites. Experimental results showed that adding the carbonaceous materials in cement composites reduced the electrical resistance by more than 98% than that of the main cement paste. The percolation threshold of all carbonaceous cement composites was found to be between 0.1 and 0.75 vol%. By applying a potential voltage to the cement composites, different heating temperatures were investigated depending on the type of carbonaceous materials and their volume fractions. The conductive cement composites showed high heating performance exceeded 100°C within a record time when the input voltage is 60 V. At the end of the study, an analysis of electric power consumption was carried out to determine the feasibility of using carbonaceous materials as self-heating components in the suggested conductive cement composites.

Analysis of Electric Power Consumption and Proposals for Energy Sustainability for the University of Unicomfacauca (Colombia)

The negative effect caused by the degradation of nature and its ecosystems by the production of unbridled energy, drives in recent years the reduction of environmental impacts generated by high energy consumption through policies and proposals focused on the generation of rational energy. Although there are international laws and conventions in favor of energy sustainability, backed by international standards for energy management, such as ISO 50001, there is a lack of disclosure of cases of research studies focused on different entities that produce goods and services in countries developing. This paper presents the analysis of the electricity consumption of the University of Unicomfacauca in Popayí¡n-Colombia, which leads to the generation of proposals for savings, energy efficiency and generation of photovoltaic energy for self-consumption; the first phase of the study consists in carrying out the energy inventory of the equipment and facilities; the second phase consists of the diagnosis, load inventory, macro consumption analysis and definition of energy saving and efficiency measures; the third phase involves the implementation of the proposed measures taking into account the cost benefit; the fourth phase, monitoring and evaluation of the measures implemented is carried out. The results show the model for the total monthly and annual electricity consumption, the energy analysis of the electrical system of the specified substations in maximum active power and apparent power, the load index and the electric power consumption; Likewise, the energy analysis of the lighting system and the viability of generating photovoltaic energy for self-consumption.

Complex statistical data analysis of electric power consumption, consumption of energy resources and production volumes


 
 
 Aims of this research are development of a complex statistical analysis algorithm for active electric power consumption data, consumption of energy resources and manufacturing products, implementation of statistical analysis in practice. Proposed parameters and criteria, which can help to technical staff in factories, to provide optimal and economical operating of supply and distribution systems as electricity, water, gas, heat, compressed air, etc. for production facilities, based on the collected active electric power consumption data for previous periods, information about consumption dynamic. It is concluded that the statistical analysis of the data, obtained for each type of engineering equipments (water supply and sewage, supply systems of compressed air, gas, electricity and steam) and various consumables coefficients (in the proposed algorithm) make possible to identify "weak areas" and to determine the most rational ways to optimize energy usage.
 
 

The Increase of Power Efficiency of Underground Coal Mining by the Forecasting of Electric Power Consumption

In article the analysis of electric power consumption and problems of power saving on coal mines are considered. Nowadays the share of conditionally constant costs of electric power for providing safe working conditions underground on coal mines is big. Therefore, the power efficiency of underground coal mining depends on electric power expense of the main technological processes and size of conditionally constant costs. The important direction of increase of power efficiency of coal mining is forecasting of a power consumption and monitoring of electric power expense. One of the main approaches to reducing of electric power costs is increase in accuracy of the enterprise demand in the wholesale electric power market. It is offered to use artificial neural networks to forecasting of day-ahead power consumption with hourly breakdown. At the same time use of neural and indistinct (hybrid) systems on the principles of fuzzy logic, neural networks and genetic algorithms is more preferable. This model allows to do exact short-term forecasts at a small array of input data. A set of the input parameters characterizing mining-and-geological and technological features of the enterprise is offered.

Software including the functions of automated analysis of electric power consumption in pipeline oil transportation

Oil and petroleum products transportation is characterized by a significant cost of electric power. Correct oil and petroleum products accounting and forecasting requires knowledge of many factors. The software for norms of electric power consumption analysis for the planned period was developed at the Ufa Scientific Center of the Russian Academy of Sciences. Based on the principles of the relational data model, a schematic diagram/arrangement for the main oil transportation objects was developed, which allows to hold the initial data and calculated parameters in a structured manner.

Analysis of electric power consumption using Self-Organizing Maps.

AbstractSelf-organizing maps (SOM) are excellent tools to extract and visualize information from large scale systems. In this paper, these maps are used to analyze data from an electric power system in a group of buildings. An experiment has been proposed to study the electric power consumption in these buildings according to the electricity tariff in order to achieve energy and economic savings. The input space of the SOM is mainly composed of a set of electric, meteorological and time period variables. Component planes and hit maps have been used for visualization. It has been proven that hit maps produce a close approximation to the real energy consumption.

Benchmarking energy consumption in municipal wastewater treatment plants in Japan

Reduction of greenhouse gas (GHG) emissions is one of the most important tasks facing municipal WWTPs. Electric power consumption typically accounts for about 90% of the total energy consumption. This study presents a benchmarking analysis of electric power consumption. The specific power consumption (SPC) ranged from 0.44 to 2.07 kWh/m(3) for oxidation ditch plants and from 0.30 to 1.89 kWh/m(3) for conventional activated sludge plants without sludge incineration. Observed differences of the SPC can be attributed to the difference in the scale of plants rather than to different kinds of wastewater treatment processes. It was concluded that economical benefits by centralizing treatment had contributed significantly to the reduction of energy consumption. Further analysis was carried out on the plant that had shown an extremely small SPC value of 0.32 kWh/m(3). In this WWTP, a large amount of digestion gas was generated by anaerobic digestion. In particular, it was used to generate power using phosphoric acid fuel cells to generate approximately 50% of the energy consumed in the plant. It was calculated that this plant had reduced the overall SPC by 0.17 kWh/m(3). The effect of power generation using digestion gas demonstrated clearly the advantage of implementing energy recovery schemes.