Hybrid Forecast and Control Chain for Operation of Flexibility Assets in Micro-Grids

Hamidreza Mirtaheri, Piero Macaluso, Maurizio Fantino, Marily Efstratiadi, Sotiris Tsakanikas, Panagiotis Papadopoulos and Andrea Mazza
Additional contact information
Hamidreza Mirtaheri: Links Foundation, Via Pier Carlo Boggio 61, 10138 Turin, TO, Italy
Piero Macaluso: Links Foundation, Via Pier Carlo Boggio 61, 10138 Turin, TO, Italy
Maurizio Fantino: Links Foundation, Via Pier Carlo Boggio 61, 10138 Turin, TO, Italy
Marily Efstratiadi: Elin Verd, Pigon 33, Kifissia, 14564 Athina, Greece
Sotiris Tsakanikas: Elin Verd, Pigon 33, Kifissia, 14564 Athina, Greece
Panagiotis Papadopoulos: Elin Verd, Pigon 33, Kifissia, 14564 Athina, Greece
Andrea Mazza: Dipartimento Energia “Galileo Ferraris”, Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Torino, TO, Italy

Energies, 2021, vol. 14, issue 21, 1-22

Abstract: Studies on forecasting and optimal exploitation of renewable resources (especially within microgrids) were already introduced in the past. However, in several research papers, the constraints regarding integration within real applications were relaxed, i.e., this kind of research provides impractical solutions, although they are very complex. In this paper, the computational components (such as photovoltaic and load forecasting, and resource scheduling and optimization) are brought together into a practical implementation, introducing an automated system through a chain of independent services aiming to allow forecasting, optimization, and control. Encountered challenges may provide a valuable indication to make ground with this design, especially in cases for which the trade-off between sophistication and available resources should be rather considered. The research work was conducted to identify the requirements for controlling a set of flexibility assets—namely, electrochemical battery storage system and electric car charging station—for a semicommercial use-case by minimizing the operational energy costs for the microgrid considering static and dynamic parameters of the assets.

Keywords: microgrids; energy management system; forecast; artificial intelligence; neural networks; recurrent neural networks; convolutional neural network; ant colony optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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