Research on the cost forecast of China's photovoltaic industry

Research on the cost forecast of China's photovoltaic industry

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Article ID: iaor201530503
Volume: 46
Issue: 1
Start Page Number: 3
End Page Number: 12
Publication Date: Jan 2016
Journal: R&D Management
Authors: , , , ,
Keywords: innovation, management, geography & environment, government, forecasting: applications
Abstract:

Global energy and environmental problems are increasing in severity. Countries worldwide are more concerned about and are paying greater attention to strengthening their energy‐saving and emissions‐reduction efforts, protecting the environment and promoting the development of new energy. Solar energy is becoming the mainstream of the global power industry because of its significant resources and low cost. This paper provides an overview of the current state‐of‐the‐art of photovoltaic electricity technology (‘photovoltaic’ or PV) in China and addresses its potential for future cost reductions. This paper analyses the relationship between current renewable energy costs and cumulative production, development and demonstration expenditures, and other institutional influences. The theoretical framework of a learning curve offers a complete methodology for examining the underlying capital cost trajectory when developing electricity cost estimates used in energy policy planning models. The cumulative production needed to achieve ‘break‐even’ (the point at which PV is competitive with conventional alternatives) is estimated for a range of learning curve parameter values. The social cost (pollution costs and value‐added tax considered) of PV is calculated, and the question of whether and how the ‘cost cap’ can be bridged is posed, the latter being the difference between what this cumulative production will cost and what it would cost if it could be produced at a currently competitive level. We also estimate how much PV could gain if the external costs (attributable to environmental and health damage) of energy were internalised, such as through an energy tax. We use the simulated results to provide suggestions for relevant PV industrial policymaking.

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