Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Reservoir-Type Hydropower Equivalent Model Based on a Future Cost Piecewise Approximation
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.ORCID iD: 0000-0003-4443-7653
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.ORCID iD: 0000-0002-4004-0352
Department of Energy Conversion and Transport, Simón Bolívar University.
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
Show others and affiliations
2018 (English)In: Electric power systems research, ISSN 0378-7796, E-ISSN 1873-2046, Vol. 155, p. 184-195Article in journal (Refereed) Published
Abstract [en]

The long-term (LT) scheduling of reservoir-type hydropower plants is a multistage stochastic dynamic problem that has been traditionally solved using the stochastic dual dynamic programming (SDDP) approach. This LT schedule of releases should be met through short-term (ST) scheduling decisions obtained from a hydro-thermal scheduling that considers uncertainties. Both time scales can be linked if the ST problem considers as input the future cost function (FCF) obtained from LT studies. Known the piecewise-linear FCF, the hydro-scheduling can be solved as a one-stage problem. Under certain considerations a single segment of the FCF can be used to solve the schedule. From this formulation an equivalent model for the hydropower plant can be derived and used in ST studies. This model behaves accordingly to LT conditions to be met, and provides a marginal cost for dispatching the plant. A generation company (GENCO) owning a mix of hydro, wind, and thermal power will be the subject of study where the model will be implemented. The GENCO faces the problem of scheduling the hydraulic resource under uncertainties from e.g. wind and load while determining the market bids that maximize its profit under uncertainties from market prices. A two-stage stochastic unit commitment (SUC) for the ST scheduling implementing the equivalent hydro model will be solved.

Place, publisher, year, edition, pages
Elsevier, 2018. Vol. 155, p. 184-195
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electric Power Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-60771DOI: 10.1016/j.epsr.2017.09.028ISI: 000419410300018Scopus ID: 2-s2.0-85032274995OAI: oai:DiVA.org:ltu-60771DiVA, id: diva2:1050466
Note

Validerad;2017;Nivå 2;2017-11-06 (andbra)

Available from: 2016-11-29 Created: 2016-11-29 Last updated: 2018-01-25Bibliographically approved
In thesis
1. Stochastic Planning of Smart Electricity Distribution Networks
Open this publication in new window or tab >>Stochastic Planning of Smart Electricity Distribution Networks
2017 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The penetration of intermittent Distributed Generation (DG) brought additional uncertainty to the system operation and planning. To cope with uncertainties the Distribution System Operator (DSO) could implement several strategies. These strategies range from the inclusion of smart technologies which will increment system’s flexibility and resiliency, to improvements in forecasting, modeling, and regulatory pledge that will facilitate the planning activity. Regardless of the nature of the solutions, they could be collected in a sort of toolbox. The planner will access the toolbox to conform cost effective plans, better able to deal with any uncertainty. The present work will address the problem of distribution system planning under uncertainties, considering smart solutions along with traditional reinforcements, in the short-term lead time up to 3 years ahead. The work will be focused on three aspects that are the cornerstones of this work:

 • A planning facilitating strategy: Distribution Capacity Contracts (DCCs).

 • A flexibility enabler technology: Energy Storage.

 • A binding methodology: Multistage Stochastic Programming. Stochastic dual dynamic programming (SDDP). 

Under the present directive of the European Parliament concerning common rules for the internal market in electricity, distribution companies are not allowed to own DG but entitled to include it as a planning option to differ investment in traditional grid reinforcements. An evaluation of the regulatory context will lead this work to consider DCCs as a planning alternative available in the toolbox. The impact of this type of contract on the remuneration of the DG owner will be assessed in order to provide insight on its willingness to participate. The DCCs might aid the DSO to defer grid i ii investments during planning stages and to control the network flows during operation. 

Given that storage solutions help to match in time production from intermittent sources with load consumption, they will play a major role in dealing with uncertainties. A generic storage model (GSM) based on a future cost piecewise approximation will be developed. This model inspired by hydro-reservoirs will help assessing the impact of storage in planning decisions. This model will be tested by implementing it in short-term hydro scheduling and unit commitment studies. 

To trace a path towards the future of this research work, a discussion on the planning problem formulation, under consideration of the lead time, the expansion options, the smart strategies, and the regulatory framework will be presented. Special focus will be given to multistage stochastic programming methods and in particular to the SDDP approach.

Place, publisher, year, edition, pages
Luleå University of Technology, 2017
Series
Licentiate thesis / Luleå University of Technology, ISSN 1402-1757
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electric Power Engineering
Identifiers
urn:nbn:se:ltu:diva-60778 (URN)978-91-7583-775-8 (ISBN)978-91-7583-776-5 (ISBN)
Presentation
2017-02-10, Hörsal A, Campus Skellefteå, Skellefteå, 10:00
Supervisors
Available from: 2016-12-05 Created: 2016-11-29 Last updated: 2017-11-24Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Alvarez Perez, Manuel AlejandroRönnberg, SarahZhong, JinBollen, Math

Search in DiVA

By author/editor
Alvarez Perez, Manuel AlejandroRönnberg, SarahZhong, JinBollen, Math
By organisation
Energy Science
In the same journal
Electric power systems research
Other Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 272 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf