In the vast landscape of rural China, the hum of electricity is more than just a convenience—it’s a lifeline for communities striving to revitalize and thrive. Huiru Zhao, a researcher at the College of Economics and Management, North China Electric Power University, Beijing, is at the forefront of a groundbreaking study that could revolutionize how we approach rural power grid investments. Published in ‘Zhongguo dianli’ (China Electric Power), Zhao’s research introduces a novel investment decision model that promises to optimize the contribution of rural grid projects to rural revitalization while maximizing financial benefits.
The study, which focuses on the development of modern rural power grids, addresses a critical need in China’s rural revitalization strategy. By constructing a comprehensive evaluation index system, Zhao and her team have quantified the contribution of rural grid projects in unprecedented ways. The system encompasses four key dimensions: safety and reliability, precise service, green and low-carbon initiatives, and digital intelligence. This holistic approach ensures that every aspect of rural grid development is considered, from the reliability of power supply to the environmental impact and technological advancements.
At the heart of this research is the application of the minimum cross-entropy model combined with the FUCOM-variance coefficient method to assign weights to these indexes. This sophisticated approach allows for a nuanced evaluation of rural grid projects, ensuring that each project’s contribution is accurately quantified. Zhao explains, “By using the weighted Marxian distance TOPSIS, we can scientifically evaluate the contribution of rural grid projects, providing a robust foundation for investment decisions.”
The model’s true power lies in its ability to optimize the contribution of rural grid units while maximizing financial benefits. This is achieved through a multi-objective optimization approach, which balances the need for rural revitalization with the financial constraints of power grid investments. The simulation results of a batch of 20 rural grid projects in a county demonstrate the model’s effectiveness, offering a clear path for precise and efficient investment in rural grids.
The implications of this research are far-reaching. For the energy sector, this model could transform how investments are made in rural power grids, ensuring that every project not only meets the immediate needs of rural communities but also contributes to long-term sustainability and economic growth. As Zhao notes, “The investment decision model can provide an effective reference for precise investment in rural grid projects, aligning with the broader goals of rural revitalization.”
This research is a significant step forward in the field of rural power grid development. By providing a scientific and quantitative approach to evaluating and investing in rural grid projects, Zhao’s work could shape future developments in the energy sector. It offers a blueprint for how to balance the complex needs of rural communities with the financial realities of power grid investments, paving the way for a more sustainable and prosperous future for rural China.
