Reaching an electricity system which is both economically efficient and environmentally friendly is motivating countries to design and execute different types of TOU demand response programs. But there are certain deficiencies which prevent these programs to effectively modify the load shape. Smart grid as a means could help the electricity system to reach the highest demand side management ...

We describe a method to generate statistical models of electricity demand from Commercial and Industrial (C&I) facilities including their response to dynamic pricing signals. Models are built with historical electricity demand data. A facility model is the sum of a baseline demand model and a residual demand model; the latter quantifies deviations from the baseline model due to dynamic pricing ...

This paper presents a summary of Demand Response (DR) in deregulated electricity markets. The definition and the classification of DR as well as potential benefits and associated cost components are presented. In addition, the most common indices used for DR measurement and evaluation are highccepted 8 April 2008 vailable online 21 May 2008

Demand Response (DR) programs encourage consumers to adjust their power consumption in response to DR events such as changes in electricity prices or sudden peaks in demand. While significant savings can be thus achieved, the real success of DR programs depends on the incentive compatible participation of consumers and their timely response to DR signals. In this work, we consider households th...

Demand Response (DR) programs encourage consumers to adjust their power consumption in response to DR events such as changes in electricity prices or sudden peaks in demand. While significant savings can be thus achieved, the real success of DR programs depends on the incentive compatible participation of consumers and their timely response to DR signals. In this work, we consider households th...

Demand-side load reduction is a key benefit of Smart Grids. However, existing demand response optimization (DR) programs fail to effectively leverage the near-realtime information available from smart meters and Building Area Networks to respond dynamically to changing energy use profiles. We investigate the use of semantic Complex Event Processing (CEP) patterns to model and detect dynamic sit...

Electricity markets are systems for affecting the purchase and sale of electricity using supply and demand to set energy prices. Electricity can be traded in organized markets or by negotiating forward bilateral contracts. Demand response (DR) refers to participation by customers in electricity markets, seeing and responding to prices as they change over time. Customers may adopt several basic ...

Power systems are in the midst of radical changes as a result of steadily rising demand, advanced technology integration and increasing penetration levels of renewable energy sources. Such developments have brought about increasing recognition of consumer behavior and the provision of DR (demand response). The aggregation of small loads as a DR flexibility resource allows end-users to participa...

Demand response (DR) enables customers to adjust their electricity usage to balance supply and demand. Although commercial and industrial DR have been in use for decades, residential DR is still emerging. The goal of this paper is to design a DR scheme for residential customers. We consider households operating various appliances and propose a distributed DR scheme to manage the appliances to k...

The widespread use of smart meters and other sensors in smart grid has resulted in unprecedented amounts of data being generated at high spatial and temporal resolutions. This high volume data is being generated at a high velocity and comes from a variety of sources, and is designated as “big data” by researchers and practitioners in various domains, including the smart grid domain. Predictive ...