Event Title
Poster: Optimize Solar Photovoltaic Supply Chain with Continuous Price Reduction
Location
Moakley Atrium
Start Time
10-5-2017 4:00 PM
End Time
10-5-2017 5:00 PM
Description
Over the past decades, global electricity generation has been dominated by fossil fuel, particularly coal. With concerns about large pollution emissions from coal-fired power plants increasing, and a general increased commitment to green energy, solar power has begun to surge worldwide. However, while the production of solar PV panels has risen greatly, there has been a sharp reduction in the price of solar PV panels, which has created a challenging issue for PV manufacturers and installers due to the quick change in the market. To have a deeper understanding of the PV supply chain, this research models the strategies for one manufacturer, one installer and one customer in one supply chain setting. Using dynamic programming and MATLAB coding, this research aims to (1) characterize the manufacturer's and assembler's optimal ordering and production decisions in decentralized and centralized situations; (2) conduct sensitivity analysis by simulating the supply chain with different parameters.
Poster: Optimize Solar Photovoltaic Supply Chain with Continuous Price Reduction
Moakley Atrium
Over the past decades, global electricity generation has been dominated by fossil fuel, particularly coal. With concerns about large pollution emissions from coal-fired power plants increasing, and a general increased commitment to green energy, solar power has begun to surge worldwide. However, while the production of solar PV panels has risen greatly, there has been a sharp reduction in the price of solar PV panels, which has created a challenging issue for PV manufacturers and installers due to the quick change in the market. To have a deeper understanding of the PV supply chain, this research models the strategies for one manufacturer, one installer and one customer in one supply chain setting. Using dynamic programming and MATLAB coding, this research aims to (1) characterize the manufacturer's and assembler's optimal ordering and production decisions in decentralized and centralized situations; (2) conduct sensitivity analysis by simulating the supply chain with different parameters.