Solar Power Forecasting in Smart Grids Using Distributed Information

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2014

Autores

Bessa, RJ (Autor) Outra; Trindade, A (Autor) Outra; Monteiro, A (Autor) Outra; Vladimiro Miranda (Autor) FEUP; Silva, CSP (Autor) Outra

Ata de Conferência Internacional

Título: Proceedings - 2014 Power Systems Computation Conference, PSCC 2014

Páginas: 1-7

2014 Power Systems Computation Conference, PSCC 2014

18 August 2014 through 22 August 2014

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 6 Citações

Outras Informações

ID Authenticus: P-00A-8MD

DOI: 10.1109/PSCC.2014.7038462

Abstract (EN): The growing penetration of solar power technology at low voltage (LV) level introduces new challenges in the distribution grid operation. Across the world, Distribution System Operators (DSO) are implementing the Smart Grid concept and one key function, in this new paradigm, is solar power forecasting. This paper presents a new forecasting framework, based on vector autoregression theory, that combines spatial-temporal data collected by smart meters and distribution transformer controllers to produce six-hour-ahead forecasts at the residential solar photovoltaic (PV) and secondary substation (i.e., MV/LV substation) levels. This framework has been tested for 44 micro-generation units and 10 secondary substations from the Smart Grid pilot in Evora, Portugal (one demonstration site of the EU Project SuSTAINABLE). A comparison was made with the well-known Autoregressive forecasting Model (AR - univariate model) leading to an improvement between 8% and 12% for the first 3 lead-times.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 7