In the early days of the solar industry, the focus was on getting solar photovoltaic (PV) systems up and running. Now that solar PV is entering the mainstream, the focus is on getting the best financial return. With the expansion in fleet sizes, many owners and operators are running fleets consisting of thousands of systems, even small increases in performance, cost-cutting measures, and improvements in operations and maintenance (O&M) functions can translate to a big effect on the bottom line. 

 

Until recently, owners and operators of fleets spread across wide geographical areas have relied on inefficient in-house asset management solutions due to the lack of other options. That is now changing with the introduction of sophisticated fleet management and data analytics software that provides them with clear, actionable data on which to base O&M decisions. By collecting and analyzing data from a wide range of sources, solar analytics software provides asset managers with insight into whether a system is performing up to expectations and the causes behind a system’s failure to perform. The access to such intelligence can boost energy output and save on O&M costs, thus increasing return on investment. 

 

Such cloud-based software applications allow asset managers to collect, organize, and analyze performance data from a diverse set of solar PV assets. Through filters accessed through customized dashboards, asset managers now have an unprecedented level of control over how performance data is aggregated and displayed. Fleets can be managed across multiple dimensions by installer, geographical region, system size, equipment type, install date, finance partner, and many other criteria. For example, a filter can be created that tracks all projects in New Jersey with inverters from a specific manufacturer, that have been installed in the last 60 days. Another strength of such software is its ability to handle data from a wide range of sources, including inverter direct data, legacy monitoring systems, and third-party performance data sets. 

 

But while sophisticated fleet management software lets asset managers know if a system isn’t performing up to expectations, it doesn’t tell them why a system isn’t performing up to expectations. This is where data analytics comes in. Data analytics software can be added to other fleet management software platforms, providing additional layers of system intelligence. Especially important is software that uses private and public historical and real-time data from weather stations, satellite imagery, federal agencies such as NASA and NOAA ,and other sources to provide highly accurate, ground-level, irradiance data across an install base or a geographic region. When used with other modeling data, i.e., the type of panel or inverter, such software provides asset managers with a truly accurate assessment of how much energy their systems should be producing based on the amount of sunlight that is hitting the ground at a specific location. This “big data” tool functions in a similar way to the gauge on a gas pump: Just as a driver needs to know how much fuel goes into the tank in order to calculate mileage, virtual irradiance measures the “fuel” that goes into a solar PV system, allowing stakeholders to determine if it is performing as it should. 

 

The use of virtual irradiance software also eliminates the need for on-site sensors, which are cost-prohibitive for small systems. In the case of systems where onsite sensors have already been installed, virtual irradiance software validates sensor data, which can become skewed due to factors such as soiling or miscalibration. 

 

The problem that remains, however, is the identification of causes behind a system’s failure to perform. Fortunately, new data analytics programs have been developed that can determine if underperformance is due to factors including weather uncertainty, snow downtime, shading, equipment downtime, equipment degradation, and inverter problems. The prescriptive analysis provided by such software enables a specific, detailed understanding of which factors are most affecting the performance of a solar PV system, and how the causes of the underperformance can best be addressed. For example, there’s no need to send out a truck if a dip in performance is due to passing cloud cover. 

 

An important feature of the new data analytics programs is their open software platform, which allow them to be integrated with any solar performance dataset, including a customers’ own. Such programs can also be integrated with other types of software, including O&M ticketing software. Users can use data analytics software to identify problems that lead to reduced performance, then create maintenance tickets through O&M software that define the most appropriate next steps, including activities such as ordering and stocking critical parts or tracking equipment repairs, materials, and labor costs. The integration of data analytics with O&M software enhances the ability of asset managers to identify systems that aren’t meeting performance expectations and to streamline O&M processes to improve workflow, minimize the time and expense of addressing problems, and reduce costly system downtime.   

 

Data analytics software also provides project developers with detailed information on the relative performance of systems that use different hardware types, that are installed under different climatic conditions, and that are installed by different businesses. This creates a powerful feedback loop that drives best practices in system design and installation, further decreasing the cost of solar PV by improving factors such as site selection, hardware vendor choice, warranty and insurance product structuring, and financing optimizing. These insights allow solar installers to price their services more competitively and increase their addressable markets. 

 

While solar PV is growing rapidly, it still comprises only a tiny percent of the U.S. energy supply. In order for solar PV to play a significant role in the generation of electricity, the industry will need increased access to real-time intelligence to optimize production at the point of use, save on costs, and improve O&M workflow. This can only come from sophisticated fleet management and data analytics software that draws on a wide range of available data to provide asset managers with the insight they need to get the most out of their solar PV assets. 

 

 

Michael Herzig is the founder and CEO of Locus Energy

 

Locus Energy | www.locusenergy.com