Title Transmission and Distribution System Expansion Planning Considering Network and Generation Investments under Uncertainty
Authors Munoz-Delgado, Gregorio , Contreras, Javier , Arroyo, Jose M. , SÁNCHEZ DE LA NIETA LÓPEZ, AGUSTÍN ALEANDRO, Gibescu, Madeleine , IEEE
External publication Si
Means 2020 International Conference On Smart Energy Systems And Technologies (sest)
Scope Proceedings Paper
Nature Científica
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85093696714&doi=10.1109%2fSEST48500.2020.9203430&partnerID=40&md5=c25c610209bcbd192f5dad04805d7f77
Publication date 01/01/2020
ISI 000722591200068
Scopus Id 2-s2.0-85093696714
DOI 10.1109/SEST48500.2020.9203430
Abstract Due to the increased deployment of distributed generation, it becomes important to compute the ideal expansion plan for the overall system, even though, in practice, transmission and distribution network planners solve their problems independent of each other, leading to sub-optimal solutions. Therefore, this paper addresses the integrated expansion planning problem of transmission and distribution systems where investments in network and generation assets are jointly considered. Several alternatives are available for the installation of lines as well as conventional and wind-based generators at both system levels. Thus, the optimal expansion plan identifies the best alternative for the candidate assets under uncertain demand and wind power production. The proposed model is an instance of stochastic programming wherein uncertainty is characterized through a set of scenarios that explicitly capture the correlation between the sources of uncertainty. The resulting stochastic program is driven by the minimization of the total expected cost, which comprises investment and operating cost terms. The associated scenario-based deterministic equivalent is formulated as a mixed-integer linear program for which finite convergence to optimality is guaranteed. Numerical results show the effective performance of the proposed approach.
Keywords Distributed Generation; Integrated Transmission and Distribution Planning; Network and Generation Investment Decisions; Stochastic Programming; Uncertainty
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