2016
DOI: 10.2172/1367390
|View full text |Cite
|
Sign up to set email alerts
|

2015 Distributed Wind Market Report

Abstract: Between 2003 and the end of 2015, over 75,000 wind turbines, totaling 934 MW in cumulative capacity, were deployed in distributed applications across all 50 states, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands. In 2015, 28 states added 28 MW of new distributed wind capacity, representing 1,713 turbine units and $102 million in investment. While the number of units installed increased slightly, capacity additions and investments decreased compared to 2014, when 63.6 MW of new distributed w… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

1
15
0
2

Year Published

2018
2018
2020
2020

Publication Types

Select...
3
2

Relationship

0
5

Authors

Journals

citations
Cited by 10 publications
(18 citation statements)
references
References 1 publication
1
15
0
2
Order By: Relevance
“…However, the LCOE values from Fig. 5 are comparable with ground-based references (0.13-0.31 EUR/kWh and 0.04-0.39 EUR/kWh) [46,47].…”
Section: Levelised Cost Of Energy: Pv Panelssupporting
confidence: 76%
See 2 more Smart Citations
“…However, the LCOE values from Fig. 5 are comparable with ground-based references (0.13-0.31 EUR/kWh and 0.04-0.39 EUR/kWh) [46,47].…”
Section: Levelised Cost Of Energy: Pv Panelssupporting
confidence: 76%
“…This analysis is performed to simulate the higher cost of a roof installation as well as a possible cost reduction caused by a growing market. It also expresses the current cost uncertainty of SWT [45, 46].…”
Section: Sensitivity Analysismentioning
confidence: 99%
See 1 more Smart Citation
“…Such complementary charge and discharge profiles can arise in practice due to the diverse load and renewable generation profiles of end users. Specifically, as the most promising sources of clean and sustainable energy, solar and wind energy have both been increasingly adopted by households, commercial buildings, and residential communities [5] [6]. Studies in [7]- [9] showed that solar and wind energy exhibit diverse and locational-dependent generation profiles.…”
Section: Introduction a Background And Motivationmentioning
confidence: 99%
“…The quadratic programming problem can be efficiently solved by the interior point method[39] 14. Though the installation of wind turbines faces geographical restrictions, technological innovations (such as vertical axis wind turbines) have promoted the adoption of wind energy for households, commercial building, and residential communities[6] [42][43]. Therefore, to capture a more complete picture of renewable energy deployment in practice, we consider both solar energy and wind energy in our simulation.…”
mentioning
confidence: 99%