Offshore wind power presents a promising solution to the pressing challenge of decarbonizing China’s coastal regions. These provinces, although small in size, are home to a staggering 76% of the country’s population. Furthermore, they account for a substantial 72% of the nation’s total power consumption and contribute to 70% of its overall CO2 emissions. Effectively transitioning these coastal areas away from fossil fuels is a critical task for China to achieve its goal of carbon neutrality by 2060, and offshore wind power appears to be a key solution.
A recent study published in Nature Communications introduces a novel bottom-up model that assesses the capacity of the grid to accommodate the variability of renewable power and devises optimal investment plans for offshore wind power. This research, conducted by the Harvard-China Project on Energy, Economy, and Environment in collaboration with Huazhong University of Science and Technology (HUST) in China, represents one of the pioneering efforts to analyze the potential for integrating renewables into the grid on a province-by-province basis, particularly focusing on substantial offshore investments.
Although China has made significant investments in onshore wind power, accounting for over 80% of national and 30% of global wind commitments, it faces challenges such as reduced output during winter and limited grid flexibility. Other zero-carbon energy sources like solar and nuclear power also encounter financial, geographic, and safety constraints. In contrast, offshore wind power holds the potential to offer a more optimal and reliable renewable energy resource.
By leveraging the vast offshore wind resources along its coast, China can tap into a sustainable and abundant energy supply. The implementation of offshore wind projects provides an opportunity to address the seasonal variability of onshore wind power and the constraints associated with other renewable sources. With careful planning and investment, China can harness the power of its coastal winds to drive its transition towards a greener and more sustainable energy future.
According to Michael McElroy, the Gilbert Butler Professor of Environmental Studies at SEAS and chair of the Harvard-China Project, the research findings reveal that China could already have access to at least 1,000 GW of offshore wind capacity at a cost lower than that of nuclear power. This indicates that offshore wind power has the potential to surpass the current government target, with investment levels potentially more than doubling.
To devise an optimal deployment plan for offshore wind, the team of researchers, led by Prof. Xinyu Chen from HUST, who is an alumnus of the Harvard-China Project, developed a high-resolution assessment model specific to China’s provinces. This model incorporates a comprehensive analysis of offshore wind resources and economics, considers the precise positioning of wind farms while optimizing the delivery system, and simulates hourly power demands in the system to identify the most advantageous provincial investment plans for offshore installations, transmission, and storage.
The proposed model suggests doubling the current offshore wind investment by 2030 and improving the existing provincial deployment plans, reallocating some of the investment from Guangdong to provinces like Jiangsu and Zhejiang. Consequently, this plan has the potential to increase national renewable penetration from 31.5% to 40% at a lower cost than what is anticipated in the current plan. By 2050, China’s offshore wind capacity could potentially reach an impressive 1,500 GW.
Xinyang Guo, a visiting fellow with the Harvard-China Project and a Ph.D. candidate at HUST, who is also the first author of the paper, emphasizes that China possesses abundant wind resources and favorable sea conditions for offshore wind power development. The deployment of offshore wind farms in China not only presents the largest market for the global wind industry in the coming decade but also serves as a crucial step for China to transition away from fossil fuel-based energy systems.