Multi-objective optimization of the renewable energy mix for a building. (25th May 2016) - Ascione, Fabrizio; Bianco, Nicola; De Masi, Rosa Francesca; De Stasio, Claudio; Mauro, Gerardo Maria; Vanoli, Giuseppe Peter
Highlights: Nearly zero-energy buildings require a drastic exploitation of renewables (RESs). A novel methodology is proposed to optimize the mix of RESs for a building. A multi-objective Genetic Algorithm is adopted by employing EnergyPlus and MATLAB®. Primary energy demand, investment cost and global cost are optimized. The methodology is applied to a new residential building located in Naples, Italy. Abstract: According to the increasing worldwide attention to energy and environmental performances of the building sector, the exploitation of renewable energy sources (RESs) represents a key strategy toward sustainable buildings. However, which is the 'best' mix of RES systems in new or existing buildings? This paper proposes a novel methodology, aimed to optimize the design of the mix of renewable energy systems for the integration of building energy demand in terms of energy uses for space heating/cooling, domestic hot water and electric devices. More in detail, a multi-objective optimization is performed by considering two contrasting objectives to be minimized: primary energy demand and investment cost. The global cost is investigated too, as further criterion, in order to detect the cost-optimal solution. Moreover, the fulfillment of the minimum levels of RES integration – as provided by Italian regulations – is taken into account as constraint. The optimization procedure is based on a genetic algorithm, which is performed by employing EnergyPlus and MATLAB®. As case study, the methodology is applied in order to optimize the renewable energy mix for a typical new Italian residential building, located in Naples (Mediterranean area). Thermal solar systems, photovoltaic panels and efficient heat pumps are investigated as RES systems.