Solar power generation promotion and withdrawal

Do PV subsidy policies affect the PV industry?

A review of the existing literature reveals there are already some studies focusing on PV subsidy policies. However, most of these studies focus on the impact of introducing subsidy policies on the PV industry instead of subsidy withdrawal policies.

Does China's feed-in-tariff subsidy policy improve photovoltaic power generation quality?

Over the past decade, the feed-in-tariff (FIT) subsidy policy of China has driven rapid growth in the photovoltaic power generation (PPG) industry. China now boasts the largest installed capacity of PPG around the world. However, the policy-driven expansion of the PPG industry has not brought about a simultaneous improvement in quality.

What if current power generation is less than the expected target?

If Q ∗ < Q t , then Q = Q L ∗ , and current power generation is less than the government's expected target. Under the constraints, the government will increase the subsidy level to reach the established total output level. In short, the government can only choose the strategy of - T ∗ Q L ∗ or - T H Q L ∗ to increase the amount of PPG.

Are solar photovoltaics ready to power a sustainable future?

Nat. Energy 3, 515–527 (2018). Victoria, M. et al. Solar photovoltaics is ready to power a sustainable future. Joule vol. 5 1041–1056 (Cell Press, 2021). Nemet, G. How solar energy became cheap: a model for low-carbon innovation. (Taylor & Francis, 2019). Rogers, E. Diffusion of Innovations. (Free Press, 2003). Farmer, J. D. & Lafond, F.

Is subsidy withdrawal effective in promoting technical progress?

By game analysis, it finds the current subsidy withdrawal is not effective in promoting technical progress and improving enterprises’ competitiveness. The government should announce the plan of subsidy reduction with clear adjustment as well as corresponding effective dates. The remainder of the paper is organized as follows.

Can enterprises predict the target PV production of government?

Furthermore, this study confines the analysis to certain special cases with complete information, where enterprises can predict the target PV production of government. As a result, the enterprises make decisions of R&D investment and power generation based on their anticipation.