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Modified Benders Decomposition for Solving Transmission Investment Game With Risk Measure
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.ORCID iD: 0000-0002-9998-9773
2018 (English)In: IEEE Transactions on Power Systems, ISSN 0885-8950, E-ISSN 1558-0679, Vol. 33, no 2, p. 1936-1947Article in journal (Refereed) Published
Abstract [en]

This paper proposes a mathematical model for transmission investment game where there are several transmission planners (TPs). The model is developed assuming a simultaneous-move game between TPs. Each TP maximizes the total surplus (producers', consumers', and transmission surplus) minus the investment cost of its region given the investment decisions of rival TPs. The transmission investment risk is also considered using the probability-of-shortfall measure. We assume one market operator who dispatches the generators in all TP's regions. The risk-constrained Nash equilibria model is formulated as amixed-integer linear program (MILP). To solve the proposed MILP, a solution algorithm is proposed that combines the standard branch-and bound algorithm (BB) with a proposed modified benders decomposition algorithm (MBD). The proposed BB-MBD algorithm is also parallelized to improve the computation performance. To improve the coordination between TPs, a supporting budget mechanism is also mathematically modeled in the MILP. The numerical results are carried out using the 9-bus 3-area and the IEEE Three Area RTS-96 networks. The computational performance of proposed BB-MBD is compared with standard BB algorithm.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2018. Vol. 33, no 2, p. 1936-1947
Keywords [en]
Benders decomposition, risk assessment, transmission investment game
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-224016DOI: 10.1109/TPWRS.2017.2743823ISI: 000425530300069Scopus ID: 2-s2.0-85028547583OAI: oai:DiVA.org:kth-224016DiVA, id: diva2:1192865
Note

QC 20180323

Available from: 2018-03-23 Created: 2018-03-23 Last updated: 2022-09-06Bibliographically approved

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Hesamzadeh, Mohammad Reza

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