A method of effective planning and control of industrial facility energy consumption is offered. The method allows optimally arranging the management and full control of complex production facilities in accordance with the criteria of minimal technical and economic losses at the forecasting control. The method is based on the optimal construction of the power efficiency characteristics with the...

Now-a-days, different sectors of the economy are being significantly affected by the electricity variable. In this research, we analyzed the monthly electricity consumption in Pakistan for the period of January 1990 through December 2011, using linear and non linear modeling techniques. They include ARIMA, Seasonal ARIMA (SARIMA) and ARCH/GARCH models. Electricity consumption model reveals a si...

Research on forecasting the seasonality and growth trend of natural gas (NG) production consumption will help organize an analysis base for NG inspection development, social issues, allow industrials elements to operate effectively reduce economic issues. In this situation, we handle a comparison structure application different models in monthly using cross-correlation function then analyze ass...

Nowadays, cities consume more energy to fuel their day-to-day activities. With the rise of electrical devices we face more challenges associated with energy control and distribution. Apart from this, we also spend a lot of energy trying to either heating or cooling our homes. This paper illustrates an architecture to extract, load, transform, mine and forecast Big Data. This technological archi...

Accurate forecasting of electric load has always been the most important issues in the electricity industry, particularly for developing countries. Due to the various influences, electric load forecasting reveals highly nonlinear characteristics. This paper creates a system for power load forecasting using support vector machine and ant colony optimization. The method of colony optimization is ...

The GasDay lab at Marquette University forecasts natural gas consumption for 26 Local Distributing Companies around the United States. We have a very large amount of data that has accumulated over the past 19 years, and the lab needs a way to select and process from all of this data to gain insight into our forecasting methods. MapReduce is a pair of functions originally proposed by Jeffrey Dea...

Based on the research of complexity and non-linearity of aero-engine exhaust gas temperature (EGT) system, a regularization adaptive chaotic prediction model applied in short time forecasting of EGT was proposed. In this research, we develop a new hybrid particle swarm optimization (HPSO) arithmetic in order to improve the accuracy of the forecasting model. This arithmetic enhanced the ability ...