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Resilient electrical distribution grid planning against seismic waves using distributed energy resources and sectionalizers: An Indian's urban grid case study
- Source :
- Renewable Energy. 178:241-259
- Publication Year :
- 2021
- Publisher :
- Elsevier BV, 2021.
-
Abstract
- The urban and suburban advancement has increased the consumption of energy per capita gradually. Electrical distribution companies have expanded their network to cater to the demand, making the system more vulnerable to low probability high impact events. The extreme events occurred in last five year had shown us complete to partial blackout, which calls for resiliency enhancement. The presented study concentrates on the Dehradun, India, which listed as the most earthquake-prone region by Union Nations Development Programme. Hence, this paper proposes three main strategies to make a resilient distribution grid against an earthquake; (i) Hardening approach at grid side and demand side against earthquake disaster (ii) Monte-Carlo methodology for earthquake hazard model (iii) K-means algorithm with clustering quality index to identify the multiple vulnerable zones. Grid side hardening is performed using the optimal unit placement of the Solar PV plant (SPP) with storage and parallel cables with sectionalizers. For demand-side hardening, electric vehicles are considered storage after an event, duly taking their future growth rate into account. Furthermore, a Mixed Integer non-linear problem is formulated to identify the optimal sizing and sitting of SPP with storage. The proposed methodology is developed and applied to the distribution system (156-bus) of Dehradun, India.
- Subjects :
- 060102 archaeology
Renewable Energy, Sustainability and the Environment
business.industry
Computer science
020209 energy
Photovoltaic system
Blackout
Distribution (economics)
06 humanities and the arts
02 engineering and technology
Grid
Civil engineering
Unit (housing)
Distributed generation
0202 electrical engineering, electronic engineering, information engineering
Per capita
medicine
0601 history and archaeology
medicine.symptom
business
Cluster analysis
Subjects
Details
- ISSN :
- 09601481
- Volume :
- 178
- Database :
- OpenAIRE
- Journal :
- Renewable Energy
- Accession number :
- edsair.doi...........e89c31333887b84b6f1cdb417aa661c8