Year: 2014
Type: article
Abstract: This study combines principles of energy systems engineering and statistics to develop integrated models of residential energy use in the United States, to include residential recharging of electric vehicles.These models can be used by government, policymakers, and the utility industry to provide answers and guidance regarding the future of the U.S. energy system.Currently, electric power generation must match the total demand at each instant, following seasonal patterns and instantaneous fluctuations.Thus, one of the biggest drivers of costs and capacity requirement is the electricity demand that occurs during peak periods.These peak periods require utility companies to maintain operational capacity that often is underutilized, outdated, expensive, and inefficient.In light of this, flattening the demand curve has long been recognized as an effective way of cutting the cost of producing electricity and increasing overall efficiency.The problem is exacerbated by expected widespread adoption of non-dispatchable renewable power generation.The intermittent nature of renewable resources and their nondispatchability substantially limit the ability of electric power generation of adapting to the fluctuating demand.Smart grid technologies and demand response programs are proposed as a technical solution to make the electric power demand more flexible and able to adapt to power generation.Residential demand response programs offer different incentives
Author: Matteo Muratori
Institution: The Ohio State University
Language: English
Topic: Smart Grid Energy Management
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2519644322