2026-04-14T02:51:07Zhttps://recercat.cat/oai/request

oai:recercat.cat:2117/3615622026-02-08T02:57:32Zcom_2072_1033col_2072_452950

Renewables with energy storage: A time-series socioeconomic model for business and welfare analysis Costa, Vinicius Bonatto, Benedito Donizeti Zambroni de Souza, Antonio Carlos Ribeiro, Paulo Fernando Castilla Fernández, Miguel Arango, Lucas Àrees temàtiques de la UPC::Energies::Tecnologia energètica Energy storage Bass diffusion model Energy loss Energy storage systems Public policies Renewable distributed generation Socioeconomic electricity market model Energia -- Emmagatzematge This paper seeks to quantify the effects of the increasing penetration level of renewable distributed generation and energy storage systems on the regulated electricity market over time. More specifically, the emphasis is on the long-term implications of distributed energy resources on energy loss and how it affects the electricity market. The proposed methodology is based on a modified combination of the Bass diffusion model (time-series forecasting of the penetration level of distributed energy resources) and the optimized tariff model (socioeconomic regulated electricity market model). Such models have not previously been applied jointly, even though they exhibit great potential for long-term market assessment in the context of distributed energy resources integration. The methodology enables the analysis of multiple public policies regarding renewable distributed generation and energy storage systems, such as net billing schemes to accelerate their deployment. Furthermore, the methodology also enables the assessment of energy storage systems’ feasibility. By applying the methodology to a concession area in southern Brazil, results demonstrate that energy storage systems are feasible if combined with appropriate public policies, as a performance index (mean socioeconomic gain) of 329 (MR$) was obtained. The authors wholeheartedly recognize the seminal contributions of Prof. Hector Arango (In Memoriam) in creating the former optimized tariff model (absence of DG and ESS) and in proofreading this paper. The authors gratefully acknowledge the support of the Federal University of Itajuba and Universitat Politècnica de Catalunya. The authors also gratefully acknowledge the financial support in part of CAPES – Coor-denaç˜ao de Aperfeiçoamento de Pessoal de Nível Superior – Brazil – Finance Code 001, CNPq – National Council for Scientific and Techno-logical Development – Brazil, INERGE, and FAPEMIG. Finally, the au-thors value the support of Jéssica Polite in increasing the figures’ resolution. Peer Reviewed Postprint (author's final draft) 2022-03 Article https://www.sciencedirect.com/science/article/abs/pii/S2352152X21013347 Restricted access - publisher's policy Elsevier