Author: yuchenda

This week, I’m focusing on learning how to utilize Vis.js to manage our datasets and visualize the power flow and dynamic loads within the microgrid. Tackling the microgrid’s visualization is the most complex aspect of the web application, prompting me to prioritize it. Although I explored various open-source projects related to microgrid visualization, I found that integrating them poses significant challenges, and they lack the interactive capabilities we desire. Therefore I’ve switched my plan to building a new visualizer instead of integrating others.

For inspiration, I’ve explored several websites, including https://www.renewables.ninja/, which offers users the flexibility to adjust variables such as wind power, photovoltaics, weather conditions, and even select specific locations on a map. Currently, our minimum viable product (MVP) only accommodates location inputs. However, incorporating these additional customization options would be an excellent stretch goal for our project.

Unfortunately, my productivity dropped this week due to illness and the concurrent scheduling of my midterms. However, we had anticipated potential delays by incorporating some slack time into our schedule, allowing me to recover lost ground efficiently. For next week I’m aiming to finish the visualization of the microgrid before spring break.

This week, my focus was on exploring potential visualization methods for the gridlab-d file based on user input. While researching, I came across an open-source visualizer at https://github.com/jdechalendar/glm-plotter/tree/master/glm-plotter. However, integrating it into our project might prove challenging due to its reliance on a heavy web framework with Python 2 and outdated libraries. Additionally, it lacks functionalities essential for our needs, such as visualizing power flow and incorporating other features.

As a solution, I propose developing our visualization tool using node visualization tools. One promising option I’m considering is https://visjs.org/, a dynamic, browser-based library tailored for handling large datasets and facilitating data manipulation and interaction. My next step involves exploring its suitability for our project requirements and evaluating its potential integration.