Multi-objective optimization of the renewable energy mix for a building. (25th May 2016)
- Record Type:
- Journal Article
- Title:
- Multi-objective optimization of the renewable energy mix for a building. (25th May 2016)
- Main Title:
- Multi-objective optimization of the renewable energy mix for a building
- Authors:
- Ascione, Fabrizio
Bianco, Nicola
De Masi, Rosa Francesca
De Stasio, Claudio
Mauro, Gerardo Maria
Vanoli, Giuseppe Peter - Abstract:
- 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 caseHighlights: 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. … (more)
- Is Part Of:
- Applied thermal engineering. Volume 101(2016:May)
- Journal:
- Applied thermal engineering
- Issue:
- Volume 101(2016:May)
- Issue Display:
- Volume 101 (2016)
- Year:
- 2016
- Volume:
- 101
- Issue Sort Value:
- 2016-0101-0000-0000
- Page Start:
- 612
- Page End:
- 621
- Publication Date:
- 2016-05-25
- Subjects:
- Renewable energy systems -- Building transient simulation -- Cost-optimal analysis -- Multi-objective optimization -- Genetic algorithm -- Building energy performance
Heat engineering -- Periodicals
Heating -- Equipment and supplies -- Periodicals
Periodicals
621.40205 - Journal URLs:
- http://www.sciencedirect.com/science/journal/13594311 ↗
http://www.elsevier.com/homepage/elecserv.htt ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.applthermaleng.2015.12.073 ↗
- Languages:
- English
- ISSNs:
- 1359-4311
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1580.101000
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British Library HMNTS - ELD Digital store - Ingest File:
- 2238.xml