We present in this paper the main applications of data mining techniques at Electricité de France, the French national electric power company. This includes electric load curve analysis and prediction of customer characteristics. Closely related with data mining techniques are data warehouse management problems: we show that statistical methods can be used to help to manage data consistency and...

with the aim of reducing cost of electricity consumption and peak load reduction, tools requirement for better managing electricity consumption have become inevitable in recent years. smart home has some equipment which are controllable and this ability is used for increasing comfort and minimizing electricity cost for residence. as a key component of smart home , electric vehicle(ev) ,increase...

Electric vehicles are anticipated to be essential components of future energy systems, as they possess the capability assimilate surplus generated by renewable sources. With increasing popularity plug-in hybrid electric (PHEVs), conventional internal combustion engine (ICE)-based expected gradually phased out, thereby decreasing greenhouse gases and reliance on foreign oil. Intensive research d...

In this paper we introduce a novel approach to exploring the benefits associated with Vehicle-to-Grid technology on an individual household level. We design an artifact that enables the implementation of different management strategies to utilize synergies between residential photovoltaic electricity generation and the energy storage provided by electric vehicles. The main advantage of this app...

A thrust allocation algorithm with capability to assist the power management system on a vessel with diesel-electric propulsion has recently been proposed. In the work presented here, the results show that the use of this thrust allocation algorithm produces a signi cant improvement in the stability of the electric bus frequency in the presence of large power load variations, as long as those l...

In this study, a fuzzy probability-based Markov chain model is developed for forecasting regional long-term electric power demand. The model can deal with the uncertainties in electric power system and reflect the vague and ambiguous during the process of power load forecasting through allowing uncertainties expressed as fuzzy parameters and discrete intervals. The developed model is applied to...

This paper presents a study to estimate the composition of an electric load, i.e. to determine the amount of each load class by the direct measurements of the total electric current waveform from instrument reading. Kalman filter algorithm is applied to estimate the electric load composition on a consumer side of a distributed power system. The electric load supplied from the different voltage ...

This paper presents a method for applying realtime scheduling techniques to balance the power usage of electric loads in cyber-physical energy systems. The aim of the proposed approach is to achieve predictability of the activation of electric loads to guarantee an upper bound on the peak electric power consumption. The contribution of this paper encompasses several aspects. The relevance of ba...

The load balancing algorithm used for the Future Renewable Electric Energy Delivery and Management (FREEDM) System power migration is analyzed for optimality. The discussion includes reduction from the bin packing problem, and limitations of this approach. Additionally, the discussion shows a reduction from the fractional knapsack problem, which allows for optimization based upon minimum cost o...

by developing the level of life in societies, the need for new resources of energy becomes more important. in almost all cases, the aim is to convert one form of energy to the electrical form. with advances of technology and use of new electric and electronic devices and gadgets, the need for electrical energy is increasing and providing stable and continuous electric power becomes very importa...