Transmission network expansion planning considering unit commitment problem simultaneously
Transmission Network Expansion Planning (TNEP) is an important part of power system planning in new structured power market. Its goal is to minimize the network construction and operational cost while satisfying the demand increase, considering technical and economic conditions. Since change in Unit...
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| Vydáno v: | 2010 IEEE PES Innovative Smart Grid Technologies Conference Europe s. 1 - 5 |
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| Hlavní autoři: | , , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
01.10.2010
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| Témata: | |
| ISBN: | 9781424485086, 1424485088, 142448510X, 9781424485109 |
| ISSN: | 2165-4816 |
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| Abstract | Transmission Network Expansion Planning (TNEP) is an important part of power system planning in new structured power market. Its goal is to minimize the network construction and operational cost while satisfying the demand increase, considering technical and economic conditions. Since change in Unit Commitment (UC), influences transmission lines, this paper presents an Integer Coded Genetic Algorithm (ICGA) to solve both problems together. Genetic algorithm can consider all generation and network constraints. Also random behavior of genetic algorithm can simulate real probabilities such as uncertainty in generation. Considering uncertainty for some units, in each iteration, it can find out the probability of congestion for each line. After all iterations it can highlight the transmission lines which need expansion, because of high congestion probability. Simulation results of the proposed idea are presented for IEEE30-bus network. |
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| AbstractList | Transmission Network Expansion Planning (TNEP) is an important part of power system planning in new structured power market. Its goal is to minimize the network construction and operational cost while satisfying the demand increase, considering technical and economic conditions. Since change in Unit Commitment (UC), influences transmission lines, this paper presents an Integer Coded Genetic Algorithm (ICGA) to solve both problems together. Genetic algorithm can consider all generation and network constraints. Also random behavior of genetic algorithm can simulate real probabilities such as uncertainty in generation. Considering uncertainty for some units, in each iteration, it can find out the probability of congestion for each line. After all iterations it can highlight the transmission lines which need expansion, because of high congestion probability. Simulation results of the proposed idea are presented for IEEE30-bus network. |
| Author | Tadayon, M Golestani, S Pirbazari, A M |
| Author_xml | – sequence: 1 givenname: S surname: Golestani fullname: Golestani, S email: golestani-s@eied.cm organization: Energy Ind. Eng. & Design (EIED), Tehran, Iran – sequence: 2 givenname: M surname: Tadayon fullname: Tadayon, M email: mahdi.tadayon@gmail.com organization: Behrad Consulting Eng., Isfehan, Iran – sequence: 3 givenname: A M surname: Pirbazari fullname: Pirbazari, A M email: alime@student.chalmers.se organization: Chalmers Univ. of Technol., Göteborg, Sweden |
| BackLink | https://research.chalmers.se/publication/216329$$DView record from Swedish Publication Index (Chalmers tekniska högskola) |
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| Snippet | Transmission Network Expansion Planning (TNEP) is an important part of power system planning in new structured power market. Its goal is to minimize the... |
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| SubjectTerms | Biological cells Biological system modeling Integer coded genetic algorithm Power system reliability Power transmission lines Schedules Transmission network expansion planning Unit commitment |
| Title | Transmission network expansion planning considering unit commitment problem simultaneously |
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