China’s coastal provinces may have a small land mass, but they are home to 76% of the population. These provinces are responsible for 72% of total national power consumption and 70% of total CO2 emissions. Decarbonizing these areas is a crucial step for China to achieve carbon neutrality by 2060, and offshore wind power could be the solution. A new study, published in Nature Communications, has developed a model to test the capabilities of the grid to accommodate renewable power variability and to design the optimal investment plans for offshore wind power.

The Study

The Harvard-China Project on Energy, Economy, and Environment, a U.S.-China collaborative research program based at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), and collaborators at Huazhong University of Science and Technology (HUST) in China, conducted the study. The researchers created a bottom-up model to analyze opportunities for province-by-province grid integration of renewables at elevated levels of offshore investment. The study is one of the first to do so.

Onshore wind investment accounts for over 80% of national and 30% of global wind commitments. However, it offers significantly less output in winter and limited grid flexibility. Other zero-carbon energy sources like solar and nuclear power also have financial, geographic, and safety constraints. On the other hand, offshore wind can provide a more optimal renewable energy resource.

According to Michael McElroy, Gilbert Butler Professor of Environmental Studies at SEAS and chair of the Harvard-China Project, “The results indicate that at least 1,000 GW of offshore wind capacity could already be available at a levelized cost below that for nuclear units in China.” He further explains that “We found that offshore wind investment levels could be more than double the current government target.”

To create the optimal deployment plan for offshore wind, the researchers led by Prof. Xinyu Chen of HUST, designed a high-resolution assessment model of China’s provinces. The model combines a refined analysis of offshore wind resources and economics, considers the micro siting of wind farms with optimization of the delivery system, and simulates hourly power system demands. It identifies optimal plans for provincial investments in offshore installations, transmissions, and storage.

The modeled system doubles current offshore wind investment by 2030 and improves current provincial deployment plans for offshore wind, shifting part of the investment from Guangdong to provinces such as Jiangsu and Zhejiang. As a result, the plan could boost national renewable penetration from 31.5% to 40%, at a cost lower than anticipated in the current plan. By 2050, offshore wind capacity in China could reach as high as 1500 GW.

Xinyang Guo, a visiting fellow with the Harvard-China Project, Ph.D. candidate at HUST, and first author of the paper, says, “China has abundant wind resources and favorable sea depth conditions to develop offshore wind power. Deployment of offshore wind farms in China could not only provide the largest market for the global wind industry in the upcoming decade, but it could offer also an important building block for China to transition away from fossil fuel-based energy systems.”

Offshore wind power offers a promising solution to decarbonize coastal China. The study shows that offshore wind investment levels could be more than double the current government target. By 2050, offshore wind capacity in China could reach as high as 1500 GW. This could provide the largest market for the global wind industry and an important building block for China to transition away from fossil fuel-based energy systems.

Technology

Articles You May Like

Unveiling New Frontiers: The Discovery of Topological Electron Crystals in Moiré Superlattices
The Intricate Story of Snot: What the Colors of Mucus Reveal About Your Health
The Hidden Impact of Recreational Activities on Waterways
Revolutionizing Sleep Apnea Treatment: The FDA Approves Zepbound

Leave a Reply

Your email address will not be published. Required fields are marked *