Journal article
Slack Bus Modeling and Cost Analysis of Distributed Generator Installations
Journal of energy engineering, v 133(3), pp 111-120
01 Sep 2007
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The installation and operation of distributed generators (DGs) has great potential for local utilities to improve distribution system reliability and lower their operating and expansion planning costs. To evaluate this potential, distribution system analyses must reflect its new operating environment with significant DG. Resulting tools can be utilized by both utilities and DG owners to improve their decision making algorithms. As such, this work investigates two different slack bus models for unbalanced distribution power flow and their impacts on subsequent cost analysis. The models include the traditional single slack bus model which assigns the substation as the slack bus and a distributed slack bus model which assigns slack to the substation and DGs according to network-based participation factors. Detailed expressions for cost analysis which directly depend on the distributed slack bus model are presented and discussed. Simulations illustrate that the different slack bus models have significant impacts on cost analysis. The difference in estimated annual profit for local utilities reached up to 265% using the different slack models.
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Details
- Title
- Slack Bus Modeling and Cost Analysis of Distributed Generator Installations
- Creators
- Shiqiong Tong - Drexel UniversityKaren Miu - Drexel University
- Publication Details
- Journal of energy engineering, v 133(3), pp 111-120
- Publisher
- American Society of Civil Engineers
- Number of pages
- 10
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000248971000002
- Scopus ID
- 2-s2.0-34547922086
- Other Identifier
- 991021944601204721
UN Sustainable Development Goals (SDGs)
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Energy & Fuels
- Engineering, Civil