Power BI Dashboard for Solar Energy Trading

Overview

Ingeniaprojects partnered with a client who needed a sophisticated system to optimize the buying, selling, and storing of solar energy. Given the fluctuating hourly energy prices across various regions in the United States and the seasonal demand changes, the client required an algorithm to recommend optimal trading decisions. Our solution involved integrating data from Excel files, developing a Python algorithm, and creating an interactive Power BI dashboard.

Technologies Used

In developing the Solar Energy Trading Dashboard, we leveraged a variety of advanced technologies to ensure robust functionality and seamless integration:

Python: Utilized for developing the algorithm that processes energy price data and generates trading scenarios.
Power BI: Used for creating interactive and user-friendly dashboard visualizations to help the client monitor energy prices and make informed trading decisions.
Excel: Served as the source of raw data for energy prices, integrated seamlessly with our system for real-time updates.

Challenge

The client needed a system to optimize solar energy trading in the face of fluctuating hourly energy prices and seasonal demand changes across various U.S. regions. The challenge was to create an algorithm that could provide optimal trading recommendations and integrate seamlessly with the client’s existing data.

Solution

Ingenia Projects developed a Python algorithm that processed energy price data from Excel files, generating scenarios based on solar panel characteristics. The algorithm provided recommendations on buying, selling, or storing energy. An interactive Power BI dashboard was created to visualize data and recommendations, ensuring the client could easily monitor and make informed decisions.

Results

Optimized Trading Decisions: Algorithmic recommendations improved trading efficiency.
Real-Time Data Integration: Ensured up-to-date information.
Enhanced Visualization: Provided clear insights into energy prices and trends.
Scalable Solution: Easily adaptable to handle additional data and regions.