Consumer demand for electricity varies greatly throughout the day, and utilities respond by price gouging during peak hours to disincentivize use. When price gouging is unsuccessful at lowering demand, utilities contribute extra capacity with “peaker” plants- small and inefficient natural gas plants that generate among the nation’s worst pollution. Most consumers aren’t aware of the hours when they should reduce consumption and end up paying over 10x as much per kWh to run everyday appliances during peak hours. With our application, users will be notified when surge pricing is likely to occur in order to save money and save the environment.

What it does

SurgeSaver tracks live and predictive Locational Marginal Pricing (LMP) across over 20 energy/power utilities in the Midwest and Mid Atlantic. We alert users when price gouging is likely to occur within the next 24 hours, giving them the necessary information to make informed decisions regarding their power usage. In addition, the application compiles and displays informative visualizations of demand trends.

SurgeSaver ultimately saves the consumer money while contributing to a cleaner environment.

How we built it

The application was built on javascript with data from the PJM Interconnection electrical grid, and Twilio text management. We also made heavy use of HTML and CSS for formatting and styling.

Challenges we ran into

We ran into a few challenges, primarily related to finding the data to use for predictive analytics, as it was very difficult to find a clean set of public time-series data on energy pricing. We also ran into difficulty when scaling the app, to ensure the appearance remained consistent across mobile devices. Moreover, this application was built virtually, and it was rather challenging to be communicating primarily via Zoom conferences.

Accomplishments that we're proud of

We are proud to have created an application that has a practical use for the average consumer and creates social impact. In the process, we learned a lot about different development techniques. This was also Lukas' first-ever hackathon and we are proud to have built a useful product together.

What we learned

We learned how to create a data visualization model using real-time data from API calls. Some specific libraries that we learned to use for the first time were chartjs for creating interactive graphs, node servers, and Sass for advanced CSS.

What's next for SurgeSaver

Over the coming months, we plan to add increased functionality through the addition of more data sources as well as email notifications. We hope to begin signing up customers so that the app can realize its full impact.

Try It out



api, chart.js, css3, html5, javascript, json, node.js, saas, vue, vuejs, yarn

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