Photovoltaic Plant Optimization to Leverage Electric Self Consumption by Harnessing Building Thermal Mass

Carlos Fernández Bandera, Jose Pachano, Jaume Salom, Antonis Peppas and Germán Ramos Ruiz
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Carlos Fernández Bandera: School of Architecture, University of Navarra, 31009 Pamplona, Spain
Jose Pachano: School of Architecture, University of Navarra, 31009 Pamplona, Spain
Jaume Salom: IREC—Catalonia Institute for Energy Research, 08930 Barcelona, Spain
Antonis Peppas: School of Mining and Metallurgical Engineering, National Technical University of Athens (NTUA), 15780 Athens, Greece
Germán Ramos Ruiz: School of Architecture, University of Navarra, 31009 Pamplona, Spain

Sustainability, 2020, vol. 12, issue 2, 1-20

Abstract: The self-consumption without surplus to the grid is one of the aspects of the new Spanish law for prosumers. Increasing the share of renewable energy sources into the grid inherently leads to several constraints. The mismatch between the energy demand and the renewable energy production, which is intermittent in nature, is one of those challenges. Storage offers the possibility to decouple demand and supply, and therefore, it adds flexibility to the electric system. This research evaluates expanding electricity self-consumption without surplus to the grid by harnessing thermal mass storage in the residential sector. The methodology is investigated by using a variable refrigerant flow air conditioner system. Because there is no option to export the excess capacity to the grid, this research proposes an approach to profiting from this surplus energy by activating structural thermal mass, which is quantified from the information acquired using a building energy model. For this purpose, an EnergyPlus model of a flat in Pamplona (Spain) was used. The optimization analysis was based on a set-point modulation control strategy. Results show that under adequate climatological circumstances, the proposed methodology can reduce the total electric energy from the grid between by 60– 80 % .

Keywords: EnergyPlus; photovoltaic solar panel; model predictive control; thermal inertia; low/high thermal mass; genetic algorithm; power-to-heat (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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