Time-of-day (peak-load) pricing of electricity is an indirect form of load management that prices electricity according to differences in the cost of supply by time of day and season of year. It reflects the costs in a more accurate manner than do the traditional block rate structures, as it logically stems from the marginal cost pricing theory, yet is compatible with the historical accounting ...

This article addresses the technical and economic challenges regarding the design of a “green” recharge area for electric vehicles at the University of Palermo in order to reduce costs and pollution connected to the charging process. Based on the behaviour of the student population, the electrical load is identified and two possible solutions are evaluated to manage the peak load: an orientatio...

This paper presents a short-term electric load forecasting method based on Autoregressive Tree Algorithm and Rough Set Theory. Firstly, Rough Set Theory was used to reduce the testing properties of Autoregressive Tree. It can optimize the Autoregressive Tree Algorithm. Then, Autoregressive Tree Model of Short-term electric load forecasting is set up. Using Rough Set Theory, the attributes will ...

Peak Shaving is one of the Energy Storage applications that has large potential to become important in the future’s smart grid. The goal of peak shaving is to avoid the installation of capacity to supply the peak load of highly variable loads. In cases where peak load coincide with electricity price peaks, peak shaving can also provide a reduction of energy cost. This paper addresses the challe...

Based on an extensive dataset containing aggregated hourly energy consumption readings of residents during March 2011 and October 2012 in South Ontario, Canada, this paper estimates the energy consumption of circulating pumps of residential swimming pools (CPRSP) non-intrusively, and quantifies the impact of CPRSP on the power system. The main challenges are that, first, widely used nonintrusiv...

Policymakers are encouraging the development of standardized and consistent methods to quantify the electric load impacts of demand response programs. For load impacts, an essential part of the analysis is the estimation of the baseline load profile. In this paper, we present a statistical evaluation of the performance of several different models used to calculate baselines for commercial build...

________________________________________________ AbstractPaper gives the compressed chronological work of scholars and comparison of classical and modern techniques to short term forecast the electrical load. This paper presents 10 approaches of load forecasting, their brief introduction and literature review. KeywordsLoad Forecasting, Classical Approach, Heuristic Approach, Fuzzy Logic, AI, AR...

Power management in micro grid is very important term to understand to stable the load curve. For stability of load curve we have to manage the demand. For manage the load (demand) we use demand response. The first objective of work is proposing customer participation model for electricity consumption cycle, for better transparency between supply and demand. Another objective is to develop the ...

The smart meter is an important part of the smart grid, and in order to take full advantage of smart meter data, this paper mines the electricity behaviors of smart meter users to improve the accuracy of load forecasting. First, the typical day loads of users are calculated separately according to different date types (ordinary workdays, day before holidays, holidays). Second, the similarity be...

Plug-in electric vehicles (PEVs) can serve in discharge mode as distributed energy and power resources operating as vehicle-to-grid (V2G) devices and in charge mode as loads or grid-to-vehicle (G2V) devices. It has been documented that PEVs serving as V2G systems can offer possible backup for renewable power sources, can provide reactive power support, active power regulation, load balancing, p...