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Deterministic Hydropower Simulation Model for Ethiopia
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.ORCID iD: 0000-0001-6000-9363
2021 (English)In: 2021 IEEE Madrid PowerTech, PowerTech 2021 - Conference Proceedings, Institute of Electrical and Electronics Engineers (IEEE) , 2021, article id 9494862Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a long-term deterministic linear simulation model for the Ethiopian hydropower system, intending to utilize the water stored in the rainy season throughout the year with minimum load shedding. Two cases are simulated and compared to historical data. The base case represents current load levels, and the second case represents a load level increase. The results show that the Ethiopian hydropower system has a great deal of flexibility to be operated in a more efficient way to minimize load shedding. The results also show that the system can support a 50% load increase with minimum load shedding, mostly when the load demand exceeds the total generating capacity. The contribution of this paper is to apply a standard hydropower model for Ethiopia to estimate the potential of the Ethiopian hydropower system to avoid or minimize load shedding with improved generation and operation planning. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2021. article id 9494862
Keywords [en]
Hydroelectric power generation, optimization, power system planning, power system reliability, Electric power plant loads, Hydroelectric power, Hydroelectric power plants, Current loads, Generating capacity, Historical data, Hydropower system, Linear simulation, Load-shedding, Operation planning, Simulation model, Electric load shedding
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-311065DOI: 10.1109/PowerTech46648.2021.9494862ISI: 000848778000112Scopus ID: 2-s2.0-85112396386OAI: oai:DiVA.org:kth-311065DiVA, id: diva2:1652528
Conference
2021 IEEE Madrid PowerTech, PowerTech 2021, 28 June 2021 through 2 July 2021
Note

QC 20220419

Part of proceedings: ISBN 978-166543597-0

Available from: 2022-04-19 Created: 2022-04-19 Last updated: 2022-09-27Bibliographically approved

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Amelin, Mikael

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
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Output format
  • html
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  • asciidoc
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