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Mean-variance portfolio analysis data for optimizing community-based photovoltaic investment
Mahmoud Shakouri1, Hyun Woo Lee2
1School of Civil and Construction Engineering, Oregon State University, 220 Owen Hall, Corvallis, OR 97331, United States.
Creating a portfolio of photovoltaic (PV) systems across neighboring buildings can boost electricity generation and reduce output volatility. This approach leverages synergy for optimized community-based PV investment.
Area of Science:
- Renewable Energy Systems
- Building Integrated Photovoltaics
- Energy Economics
Background:
- Photovoltaic (PV) system electricity generation is influenced by shading, building orientation, and roof slope.
- Volatility in PV generation can be mitigated by diversifying system installations.
- Community-based PV investment offers potential for synergistic gains.
Purpose of the Study:
- To present data supporting the PACPIM model for optimized portfolio analysis in community-based photovoltaic investment.
- To provide a dataset of physical properties and simulated electricity generation for PV systems in 24 Oregon houses.
- To share Matlab code for constructing optimized PV portfolios.
Main Methods:
- Data collection on physical properties of 24 residential buildings in Oregon, USA.
- Simulation of hourly electricity generation data for installed PV systems.
- Development of Matlab code for optimized PV portfolio construction.
Main Results:
- A comprehensive dataset of building properties and simulated PV electricity generation is available.
- The provided Matlab code enables the creation of optimized PV portfolios.
- The methodology demonstrates the potential for synergistic benefits in community PV investments.
Conclusions:
- The presented data and code support the PACPIM model for community-based PV investment.
- Optimized PV portfolios can enhance electricity generation and reduce volatility.
- The approach is generalizable to diverse communities interested in PV system investment.
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