Electrical load modeling and forecasting are critically important in the electrical network and smart grid. The sparse Bayesian Learning (SBL) algorithm can be utilized to model and forecast the electrical load behavior. The SBL algorithm can solve a sparse weight vector with respect to a kernel matrix for modeling electricity consumption. However, traditional SBL can only handle an electricity...

An integrated Artificial Neural NetworkParticle Swarm Optimization (PSO) is presented for analyzing global electricity consumption. To aim this purpose, following steps are done: STEP 1: in the first step, PSO is applied in order to determine world’s oil, natural gas, coal and primary energy demand equations based on socio-economic indicators. World’s population, Gross domestic product (GDP), o...

In recent years, energy predicament and environmental problems in the world caused by fossil fuels combustion make us to pay serious attention to optimizing energy consumption and using renewable energies. One of the potential renewable energies which can be helpful in electricity generation is harness wind and water energy or using these two kinds of energy simultaneously. In this study, to pr...

High electricity demand peaks and uncertain supply from renewable energy sources have a significant impact on the electricity price and the network capacity. One mechanism proposed to tackle this issue is the use of real-time pricing (RTP) at the end customer level. Here electricity retail prices are set in real-time in response to varying supply-demand conditions in a way that reduces peak dem...

Forecasting electricity consumption has often prefered to treat socioeconomic activity and wealth as exogenous. The motivation for this research is to endogenize electricity consumption with economic activity by introducing electricity demand, and the interactions between electricity use and economic activity, into macroeconomic demand equations. In this paper, I create an energy and macroecono...

This paperpresents empirical results regarding the determinants ofelectricity consumption in manufactured housing, commonly called mobile homes. The data consist of a random sample of over 400 Florida electricity customers--with information on socioeconomic characteristics, housing features, and monthly KWH consumption. The model explains over forty percent of the variation among customer usage...

Manufacturing enterprises nowadays face the challenge of increasing energy price and emission reduction requirements. An approach to reduce energy cost and become environmental friendly is to incorporate energy consumption into consideration while making the scheduling plans. The research presented by this paper is set in a classical job shop circumstance, the model for the triple objectives pr...

Under the background of smart grid’s real-time electricity prices theory, a real-time electricity prices and wireless communication smart meter was designed. The metering chip collects power consumption information. The real-time clock chip records current time. The communication between smart meter and system master station is achieved by the wireless communication module. The “freescale” micr...

In the household appliance industry, heat pump systems have been used for a long time in refrigerators and freezers to cool food, and the industry has driven the development of small, high-quality, low-price heat pump components. The low price of good quality heat pump components, along with an increased willingness by customers to pay extra for lower electricity consumption and environmental i...