Title Robust dynamic transmission and renewable generation expansion planning: Walking towards sustainable systems
Authors Roldan, C. , SÁNCHEZ DE LA NIETA LÓPEZ, AGUSTÍN ALEANDRO, Garcia-Bertrand, R. , Minguez, R.
External publication Si
Means Int J Electr Power Energy Syst
Scope Article
Nature Científica
JCR Quartile 1
SJR Quartile 1
JCR Impact 4.41800
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030317910&doi=10.1016%2fj.ijepes.2017.09.021&partnerID=40&md5=8701e064a66eb41867db09febf6b6aee
Publication date 01/03/2018
ISI 000418968000006
Scopus Id 2-s2.0-85030317910
DOI 10.1016/j.ijepes.2017.09.021
Abstract Recent breakthroughs in Dynamic Transmission Network Expansion Planning (DTNEP) have demonstrated that the use of robust optimization, while maintaining the full temporal dynamic complexity of the problem, renders the capacity expansion planning problem considering uncertainties computationally tractable for real systems. In this paper an adaptive robust formulation is proposed that considers, simultaneously: (i) a year-by-year integrated representation of uncertainties and investment decisions, (ii) the capacity expansion lines have and (iii) the construction and/or dismantling of renewable and conventional generation facilities as well. The Dynamic Transmission Network and Renewable Generation Expansion Planning (DTNRGEP) problem is formulated as a three-level adaptive robust optimization problem. The first level minimizes the investment costs for the transmission network and generation expansion planning, the second level maximizes the costs of operating the system with respect to uncertain parameters, while the third level minimizes those operational costs with respect to operational decisions. The method is tested on two cases: (i) an illustrative example based on the Garver IEEE system and (ii) a case study using the IEEE 118-bus system. Numerical results from these examples demonstrate that the proposed model enables optimal decisions to be made in order to reach a sustainable power system, while overcoming problem size limitations and computational intractability for realistic cases.
Keywords Power systems; Renewable generation expansion planning; Robust optimization; Transmission network expansion planning
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