Stochastic multi-stage model for co-planning of transmission system and merchant distributed energy resources
In recent years, while energy consumption is still increasing, system peak load is decreasing due to deregulation in power systems, application of demand response programmes, microgrids and smart grids implementation, and so on. Thus, transmission system operators (TSOs), which are usually a public...
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| Vydáno v: | IET generation, transmission & distribution Ročník 13; číslo 14; s. 3003 - 3010 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
The Institution of Engineering and Technology
23.07.2019
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| Témata: | |
| ISSN: | 1751-8687, 1751-8695 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | In recent years, while energy consumption is still increasing, system peak load is decreasing due to deregulation in power systems, application of demand response programmes, microgrids and smart grids implementation, and so on. Thus, transmission system operators (TSOs), which are usually a public entity, must reinforce the transmission systems to maintain power system reliability. They are not interested in investing transmission network because of high investment costs. In this regard, this study presents a new bi-level model for co-planning of transmission system and merchant distributed energy resources (DERs). The upper level takes the TSOs perspective and aims to minimise the line investment cost and cost of buying energy from conventional generators and DERs, while ensuring a given rate of return on DERs investments. The lower level simulates market clearing to find nodal prices for calculating DERs' profit and cost of buying energy. The proposed model is reformulated as a single-level mixed integer linear programming problem by strong duality technique, bigM method, and the complementary slackness conditions. The IEEE RTS 24 bus test system has been used to show the usefulness of the proposed model. |
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| ISSN: | 1751-8687 1751-8695 |
| DOI: | 10.1049/iet-gtd.2018.6324 |