In the quest to decarbonize the power sector, a groundbreaking study published in Zhejiang dianli, translated as “Zhejiang Electric Power,” is set to reshape how we think about carbon emissions and new energy integration. Led by SHENG Junjie from State Grid Hubei Electric Power Co., Ltd., the research tackles a critical yet often overlooked aspect of renewable energy transmission: network losses and their carbon implications.
As China and other nations strive to meet ambitious “dual carbon” goals—peaking carbon emissions before 2030 and achieving carbon neutrality by 2060—the integration of new energy sources into power grids is accelerating. However, the transmission of this clean power to end users isn’t as straightforward as it seems. “While new energy power generation itself is carbon-free, the process of transmitting this power causes changes in network losses,” explains SHENG. “This means that the current operational model, where transmitted new energy power doesn’t bear any carbon emission responsibility, is no longer tenable.”
The crux of the issue lies in the fact that transmitting power over long distances results in energy losses, typically in the form of heat. These losses, albeit small, contribute to the overall carbon footprint of the power system. Moreover, as more renewable energy sources come online, the complexity of managing these losses and their associated emissions increases.
To address this challenge, SHENG and his team propose a novel principle: all network losses associated with transmitted power should be accounted for in carbon emission responsibilities. They designed a network loss allocation method tailored for different power transactions and employed an energy transaction allocation (ETA) algorithm. This algorithm precisely allocates the network losses caused by each power transaction contract on each transmission line, enabling a fair and accurate determination of carbon emission responsibilities.
The implications of this research are far-reaching. For energy companies, it means a more accurate accounting of their carbon footprint, which is crucial for meeting regulatory requirements and investor expectations. “This method allows us to pinpoint exactly where and how much carbon is being emitted due to network losses,” says SHENG. “This level of precision is vital for optimizing grid operations and reducing overall emissions.”
Moreover, the proposed method could pave the way for new business models in the energy sector. As carbon pricing mechanisms become more prevalent, the ability to accurately allocate and trade carbon credits will be a significant competitive advantage. Energy companies that can demonstrate a lower carbon footprint due to efficient transmission and loss management will be better positioned to thrive in a low-carbon economy.
The study also highlights the importance of advanced algorithms and data analytics in managing complex energy systems. As grids become more decentralized and renewable energy sources more diverse, the need for sophisticated tools to optimize operations and minimize emissions will only grow. This research is a step in that direction, showcasing how innovative algorithms can drive sustainability in the energy sector.
As the world transitions to a low-carbon future, the integration of new energy sources and the management of network losses will be critical. SHENG’s work, published in Zhejiang Electric Power, offers a roadmap for achieving this, with significant commercial and environmental benefits. The energy sector would do well to take note and adapt, for the future of power is not just about generating clean energy but also about transmitting it efficiently and responsibly.
