In a Smart Grid, both the utility and the consumer can benefit from analytics based on electricity consumption data. In this abstract, we report our on-going research work on performing analytics for the USC campus micro-grid using electricity consumption and curtailment data available for campus buildings. Our goal is to provide the facility managers an insight into the changing electricity de...

The increase in energy prices combined with the environmental impact of energy production has made energy efficiency a key component towards the development of smart homes. An efficient energy management strategy for smart homes results in minimized electricity consumption leading to cost savings. Towards this goal, we investigate the impact of environmental factors on home energy consumption. ...

Original scientific paper Recently, there has been made a great effort to include electricity generation from the renewable energy sources into the power system. Random renewable generation creates the imbalance between electricity production and consumption, which requires power plants with fast response or energy storage systems. Generally accepted solution for load balancing is the concept o...

Germany’s energy transition has been accompanied by a near doubling of power prices for private households since the outset of the new millennium. Millions of poor households and those that are close to the poverty threshold are likely to suff er from these increases in electricity cost. Focusing on low-income households, this paper illustrates the distributional implications of Germany’s energ...

This paper use linear regression and non-linear artificial neural network (ANN) model to analyze how the four economic factors: national income (NI), population (POP), gross of domestic production (GDP), and consumer price index (CPI), affect Taiwan’s electricity consumption, furthermore, develop an economic forecasting model. Both models agree with that POP and NI are of the most influence on ...

This paper uses linear and nonlinear statistical models, including artificial neural network (ANN) methods, to investigate the influence of the four economic factors, which are the national income (NI), population (POP), gross of domestic production (GDP), and consumer price index (CPI) on the electricity consumption in Taiwan and then to develop an economic forecasting model. Both methods agre...

This project describes the electricity demand and energy consumption management system and its application to Southern Peru smelter. It is composed of an hourly demand-forecasting module and of a simulation component for a plant electrical system. The first module was done using dynamic neural networks with backpropagation training algorithm; it is used to predict the electric power demanded ev...

Smart meters are increasingly being deployed to measure electricity consumption of residential as well as non-residential consumers. The readings reported by these meters form a time series, which is stored at electric utility servers for billing purposes. Invalid readings may be reported because of malicious compromise of the smart meters themselves, or of the network infrastructure that suppo...

In order to meet ambitious emission reduction goals in California, greenhouse gas emissions from direct combustion of fossil fuels for residential space and water heating will need to be largely eliminated. If those emission reductions come from fuel switching (natural gas to electricity) then the electricity grid needs to be prepared for the additional load. This paper presents a new method fo...