The Solar Energy Data Portal
The solar energy production platform collects and stores solar production energy from various vendors. Its purpose is to offer a reliable and scalable solution for storing solar energy data internally and presenting it in different formats. Additionally, it provides analytics and data management capabilities for both internal and external requirements.
Industry:
Energy, Manufacturing
Services:
Back End Development, Cloud / DevOps, Front End Development
Location:
New York, US
Challenge
Creating a solar energy production platform involves numerous technical, logistical, and interoperability challenges. The platform must effectively handle the retrieval, storage, and representation of solar energy production data, which is inherently complex due to the variability of data formats, standards, and communication protocols used by different solar panel vendors. Here are the challenges we encountered while building a solar energy data portal:
Data heterogeneity
Solar panels and associated monitoring equipment from different vendors often produce data in varied formats and structures. Standardizing this data for consistent storage, processing, and analysis is a significant challenge. The platform needs a robust data ingestion pipeline that can normalize disparate data formats into a unified model.
Real-time data processing
Solar energy production data is typically generated in real-time. The platform must be capable of processing and updating data in real-time or near-real-time to provide timely insights to users. This requires efficient data processing pipelines and the ability to scale resources dynamically to handle fluctuating data volumes.
Data accuracy and integrity
Ensuring the accuracy and integrity of solar production data is critical, especially when dealing with data transmission over networks and the potential for data loss or corruption. Implementing error detection, correction algorithms, and robust validation mechanisms is necessary to maintain data quality.
Interoperability issues
Interfacing with systems and hardware from various vendors introduces interoperability challenges. The platform must be compatible with a wide range of APIs, communication protocols, and hardware specifications to ensure seamless data retrieval and integration.
Scalability
As the platform grows to accommodate more properties and solar panel systems, scalability becomes a paramount concern. The system architecture must support scaling both in terms of data volume and the number of end-users without compromising performance or user experience.
Solution
We built a solar energy production platform for collecting and storing solar production energy from different vendors. We developed a complex solution for collecting data on an hourly basis and historical data. We created data storage with fast and robust functionality for data aggregation on a weekly, monthly, and yearly basis. The monitoring and analytics are based on energy production data by region and inverter statuses.
Technologies Used
We used a comprehensive suite of technologies and hardware components to efficiently collect, store, and manage solar production data. At the network layer, it utilizes TCP/IP for general network communication, SNMP (Simple Network Management Protocol) for network management, and HTTP for web-based communication.
The hardware foundation of the platform includes solar panels, which capture solar energy, and inverters, which convert the solar energy from DC to AC, making it usable for data collection and analytics. This blend of advanced software and hardware technologies ensures the platform's capability to offer a reliable, scalable, and comprehensive solution for solar energy data management, catering to both internal analytics and external data presentation requirements.
The workflow
In developing our solar energy data portal, we meticulously crafted a workflow that began with the establishment of historical and real-time data collection pipelines, enabling comprehensive solar energy analysis.
Creating pipelines for historical data collection
We first established pipelines for the collection of historical data, ensuring we could gather, process, and store past data related to solar energy for analysis. This foundational step was critical for identifying trends, making predictions, and enhancing decision-making capabilities within the solar energy sector.
Creating a pipeline for hourly data collection
We developed an hourly data collection pipeline using an automated system to gather real-time or near-real-time solar energy data. This was essential for monitoring solar energy outputs, detecting anomalies, and providing up-to-date insights to our users.
Creating a platform for storing data from different vendors
To accommodate data from various solar energy vendors, we created a unified platform for data storage. This platform was designed to handle different data formats and sources seamlessly, prioritizing data integrity, security, and scalability to support a broad range of solar energy data analytics.
Creating cloud infrastructure
The creation of cloud infrastructure was a pivotal step, leveraging cloud computing to establish a scalable, flexible, and reliable infrastructure. This infrastructure supported the portal's demands, providing the necessary servers, storage, and networking resources in the cloud and ensuring the ability to scale as the portal grew.
Core logic development
The core logic development phase involved crafting the main functional code that underpins the portal, including developing algorithms for solar energy data analysis, implementing business rules, and ensuring efficient and effective portal operations.
Releasing the product in the development environment
Before going live, we released the portal in a development environment. This allowed our development and testing teams to closely examine its functionality, identify and fix bugs, and make necessary adjustments in a controlled setting.
Testing
The testing phase was comprehensive, encompassing unit tests, integration tests, system tests, and user acceptance tests to ensure the portal met all required standards and functioned correctly under various scenarios.
Releasing the product in the production environment
We released the portal in the production environment, making it accessible to end-users. This step involved deploying the portal in a live setting, where we monitored its performance and ensured smooth operations.
About the team
We built a product-oriented, startup-in-a-garage culture within a cross-functional development team.
Team composition
Team Lead/Architect
1
Full-Stack Engineers
4
Manual QA Engineer
1
Automation QA Engineer
1
Product Manager
1
Impact
The solution we built was carefully designed to offer a user-friendly interface that provides detailed insights into solar energy generation and usage. This is made possible through the use of powerful data analytics. By bringing the data in-house, we have greatly improved the reliability and availability of the system. This strategic decision not only preserves the integrity of the data, but also enables proactive monitoring of solar energy patterns and anomalies. These capabilities are essential for stakeholders who want to optimize solar energy usage, predict energy trends, and make informed decisions.
The core of our approach is the smooth integration and presentation of complex solar energy data in an accessible and intuitive format. Users can easily navigate through the portal to access real-time and historical data analyses, which are essential for understanding energy production and consumption patterns. This accessibility is vital for encouraging the adoption of solar energy by providing clear, actionable insights that can drive energy efficiency and sustainability efforts.
Moreover, this data portal lays a robust foundation for future business applications in the solar energy sector. Its scalable architecture and flexible design principles mean it can easily be adapted to accommodate new features, data sources, and user requirements. As the solar energy market evolves, the portal is poised to support an expanding range of applications, from predictive maintenance and performance optimization to integration with smart grid technologies.
