By Topic

A Framework for Portfolio Management of Renewable Hybrid Energy Sources

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Tommer R. Ender ; Georgia Tech Research Institute, Atlanta, GA, USA ; Jonathan Murphy ; Comas Lamar Haynes

An energy systems modeling tool must address variability of ecological and socio-economic sensitivities in order to practically guide policy and budget related decisions. The aim of this effort is to produce an advisory and design tool geared toward aiding entities with robust planning of effective renewable energy solutions based on trusted models. A tool was developed that enables tradeoffs between various energy systems, based on neural network surrogate models of a publicly available power systems modeling tool. These surrogate models enable the higher-level decision-making tool to manipulate surrogate representations of actual engineering models, as opposed to relying on static data or static simulation results. This research will present a decision-maker with the ability to determine which various renewable and nonrenewable energy systems meet annual energy load requirements, acquisition and operation costs, and individual solution attributes.

Published in:

IEEE Systems Journal  (Volume:4 ,  Issue: 3 )