Yunjing Guo

Why are you interested in sustainable energy solutions? Sustainable energy is the future trend. Humans seem to be unable to bypass Sustainable energy solutions.

How are your personal history and vision assets to development and research in energy and sustainability? During my undergraduate studies, I participated in several key research projects; each research experience was a springboard to gaining a deeper understanding of power systems and the potential for innovation, especially through the use of technology, like AI. One of my most significant experiences was the two years I spent in the National Key Laboratory of Tsinghua University. My work focused on an Artificial Intelligence application to address power system problems. I learned extensive machine learning algorithms and read a tremendous amount of literature in relative fields. I then summarized the usage of AI frameworks, such as TensorFlow, and put forward new ideas on how to combine AI technology with power systems. The AI manual I produced is still in use in the laboratory. 
In addition, I looked to apply AI to practical applications, using the TensorFlow framework and neural network to solve realistic power system problems. After I accumulated experience in programming and deepened my understanding of complex power flow calculations, I undertook more advanced jobs. I became responsible for building a hybrid AC/DC power flow calculation model and implemented the model in MATLAB and Python. Finally, I developed the power flow calculation model based on the Back/Forward Sweep method and this program has been packaged and used for future lab research. I also participated in another project: “Configuration Optimization for Hybrid AC/DC Urban Distribution Networks.” Using Python, I developed a hybrid AC/DC power flow calculation program that has been packaged and placed on a cloud server, where it runs as a cloud computing tool. Throughout the project, debugging the program trained me in valuable virtues, like learning to be meticulous and patient in my work. I learned to carefully check parameters and make sure every step could be carried out in accordance with the established steps, something that made me a better researcher. 
This led to my independent graduation project, using machine learning technology to solve the initial value problem of the power flow calculation. I analyzed the initial value of the power flow calculation of the hybrid AC-DC system using Deep Neural Network (DNN) to justify if the calculation is convergent and generated better initial values of power flow calculation using Generative Adversarial Network (GAN). I also learned to be persistent when I encountered difficulties and went to great lengths to find every possible solution. Ultimately, through intense work, I successfully accomplished my project, which was originally designed at a graduate level, and I won the outstanding graduation project prize. My work has been recognized as a new idea incorporating machine learning technology to power flow calculations. My work effectively enhances working efficiency and even solves complex problems that can’t be addressed by conventional methods, thus providing a unique value. Besides research experience, I also gained leadership skills as a team leader in a research project for the National Student’s Platform for Innovation and Entrepreneurship Training Program. My team project was the development of an automatic controller for the demand response of distributed electric heating based on a mobile terminal.
My interest in power systems has continued to motivate me during my graduate studies at Ohio State University. I joined Prof. Ramteen Sioshansi’s research group within the Department of Integrated System Engineering, and I constructed an economic dispatch and investment decision model of the power system, which took into consideration AC transmission lines, conventional power generation, and energy storage. The purpose of this research is to find a way to operate a complex power system at minimal cost and help the investment decision. Through my work, I have accumulated an incredible amount of knowledge within the sphere of engineering optimization. In collaboration with my instructor, we have been working throughout the fall semester to solve additional problems in our research, such as water desalination, while optimizing cost. In my research, I summarized the different methods of water system modeling basing the work on over a dozen literature sources. I then went on to determine the basic model of the water system, with the help of my instructor. Currently, I am using GAMS to implement a water system model, with water desalination technology included, integrating it with the rest of the power system. 

What is your dream job and how will it contribute to a more sustainable energy landscape? After the program, I may work in an energy company or as a faculty in a university. My work may help human use the cheaper sustainable energy. In the future, we may use more energy storages and integrate more systems. 

Who are potential key partners for your research? Energy companies, managers in government energy departments, and faculty will help me learn more about the latest information of this field.

Hobbies/Personal Interests: Drama, Music, Boxing, Photography