A decomposition approach for integrated planning of primary and secondary distribution networks considering distributed generation

• Autor(a) principal: Hincapie, Ricardo A.
• Data de Publicação: 2019
• Outros Autores: Gallego R, Ramon A., Mantovani, Jose R. S. [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1016/j.ijepes.2018.09.040; http://hdl.handle.net/11449/185251
• topic: Bilevel model; Distributed generation; Distribution system planning; Primary and secondary networks; Tabu search algorithm

This paper presents a new model for optimal integrated planning of medium and low voltage distribution systems with penetration of distributed generation (DG) in the low voltage network. The proposed bilevel model takes into account in the upper and the lower levels, the medium and low voltage network planning respectively. This approach considers as conflict between these two agents (upper and lower levels), the size and location of the distribution transformers (DT), ie. the incidence in both networks of the power flow circulating from the primary to the secondary system. The main objective of this approach is to find a joint global solution that establishes a balance to benefit the planning of both networks, by decomposing the problem in two subproblems (or levels). The upper and lower levels involve the costs of installing and upgrading the new and existing elements (branches, DT, substations and DG) and the cost of the energy technical losses. This problem is formulated as a mixed integer non-linear model, and is solved using a tabu search algorithm (TSA). To verify the efficiency of the proposed methodology, three cases of study are compared: (i) traditional integrated planning, (ii) bilevel integrated planning and (iii) bilevel integrated planning with DG in the LV network. The obtained results show the importance of considering both networks in a simultaneous way in the electric distribution system planning, which allows finding answers of lower global costs.