Case Study

How did a leading Independent Power Producer in Renewable Energy fast-track its Energy generation transformation?


A recent innovator in the clean energy space was eager to adopt a data analytic transformation that could help modernize and monitor their solar panel technology.  While the corporation had historically manufactured many clear energy parts, they had established a recent initiative dedicated to the production and maintenance of their solar panels and pumps. They were eager to implement an energy efficient solution that could optimize their solar panel energy efficiency and consolidate the constant flow and inundation of data from the solar panels that could later be repurposed by any power distribution company in the years to come. 

They needed to adopt a technological framework that could help them maintain a wide selection of independent panels, interconnected to one another through a series of string, as well as their designated inverters. The total capacity of the plant is at about 300MW, with over 40,000 strings and 3,000 inverters to account for.  


The enterprise’s Power & Generation Services (PGS) used an existing GRID data warehouse (DW) platform that consolidated servicing data of various component repairs, aggregated from multiple legacy systems. This data would be utilized by business users to conduct downstream analytics that measured quality & output of individual turbines. However, with the new digital imperatives, they would have to upgrade and expand their existing data warehouse capabilities. Upon an initial Technology Assessment, it was clear that their current GRID DW platform would not be up to par in handling the larger data loads and lacked the concurrent processing capabilities needed for its planned production. With over 20 years of experience in Data Management & Warehousing capabilities, the leader of clean energy and turbine energy chose to partner with Systech as they converted their GRID platform to a new technology stack. Additionally, the solution needed to also introduce a second replication layer for source data extraction and processing – so that data could be stored in both its raw and processed forms. Systech was the optimal partner when they were crunched with time and needed to ensure the effective conversion of their technology environment, without disrupting their operational workflows. Systech worked with key stakeholders to design and build a robust DW architecture. Systech also implemented Data processing & integration capabilities to streamline their analytics lifecycle. In order to enable easy analytics for all business users, Systech established and deployed a self-service analytics model, built upon Tableau – democratizing the analytics process so critical information can be delivered to the right person, by the right time.


Solar Panel Mechanics and Concerns 

Solar energy plants derive value from their ability to convert energy from the sun into other, more actionable types of energy. Panels are attached to smart, IoT devices that can capture information, such as how much voltage each panel provides independently, as well as other factors like decline of voltage production, efficiency of the panel, temperature, etc. This can be especially helpful when navigating periods of time when the sun shining at its peak, during the middle of the day compared to how it gradually goes down in the evening. Each engineer has a certain expectation of the operational performance of every panel. The objective of the smart device is that it can capture the real-time power data that each individual panel generates, and thereafter relay the data to the operator to indicate which panels are under performing and need to be inspected/cleaned. Systech Solution’s Doppler platform was a natural choice, as it could seamlessly offer insights surrounding areas like loss and leakage analysis, capacity utilization analysis, and asset analysis. The data collected from the panels could then be sent directly to Dopplr, which could then derive actionable insights from the influx of data. 

One of the main goals was to create an environment in which engineers could spend their time inspecting panels that need an intervention. With a steady flow of intelligence being relayed to the operators remotely it helps cut down on the manpower and operational demands of panel maintenance. Once the solution was implemented, instead of a full work force being required to perform inspections, one individual would be able to check on the panel in question; not only reducing the manpower required to maintain the machines but would be able to offer a more targeted “point of intelligence and action” for the engineers to reference. 

Impact of IoT Smart Devices

So how does the technology work? Each panel communicates with the IoT smart devices and based on the proximity coordinates – geo-positioning – of each coordinate, it can indicate its contour parameters. This means that each panel could identify the segregation and elevation affected by each panel. This is extremely important in identifying how full or flat panels are, variance in land consistency, and elevation patterns. For example, it can be extremely problematic to be unaware that panels are constrained at different elevations, since the higher panel will create a shadow over the lower ones later in the day, which make provide a false error reading and corrupt the model if left unaccounted for. 

The onsite smart devices also had other applications, such as IoT weather sensors that could offer findings on factors such as wind directions, humidity, and even air temperature. This Weather Measurement System (“WMS”) also factored into the performance of the panels. 

Real-time Updates, On and Off Duty

The Dopplr platform consolidates all these processes into an application that is continuously updated and available at any time and location. It can identify and keep track of each operator, maintain inverter functionality, and monitor cluster panel performance at an individual and collective scale (relative to what its historical output has been). 

Unlike other solutions on the market today, the Dopplr technology does not only alert you if the power generation has gone down, but also is able to suggest possible reasons why the error reading may have occurred. It may identify dust as the root issue surrounding an underperforming panel, for example, could be one factor in why it is underperforming. It also allows engineers to lighten their load when heading to a job site. Instead of bringing a tool for every possible reason the panel could be broken, for example, they now only need to carry equipment that is appropriate for the task at hand. 

This is only the beginning for the applications of the Dopplr solution for an innovator in the clean energy space. And the possibilities are endless. 

Renewable Energy

 Systech Solutions played a key role in implementing and optimizing the Dopplr solution for the leading Innovator in the Clean energy space. Start-to-finish, this infrastructure and solution were executed in less than one (1) month. The solar panel energy model created by Dopplr has already saved the customer countless hours of labor and development. 

Dopplr is a platform that foundationally has been designed to complement future technological adoption or changes and cut down on costs for customers by minimizing the price associated through a whole team of consultants. With Dopplr, customers are not only buying into a product but also benefit from all the services that come with being a member of the Systech family. 

All the BI, ML and Ingestion comes from the Dopplr platform. This customer was able to save on IT and infrastructure costs, without having to compromise on the skillset required to execute the tasks at hand. 

As showcased by this case study, Dopplr saves companies upfront costs of creating a fully packaged solution, when it could instead be leveraged to compensate for upfront performance cost pontification. The secret sauce lies in its AI modeling and processing capabilities. It offers action-oriented, prescriptive analysis, and smart mobile app combability that has totally revolutionized the data game.