In the first article in this series, we discussed the many factors that impact energy output from solar arrays and why it's important to improve the insight into array performance if lifetime energy yield is to match expectations.

We challenged the industry paradigm that a Performance Ratio of 0.80 is best-in-class and pointed to the emergence of advanced panel-level monitoring and optimization technologies that can help make arrays “intelligent,” enabling enhanced Operations and Maintenance (O&M) practices that can help drive heightened expectations.

The second article outlined how these new technologies can be used to diagnose array impairments with an unprecedented level of accuracy and specificity. We introduced the concept of cloud-based intelligence, removing the need for human vigilance in the monitoring process and enabling the concept of a Virtual Network Operations Center (VNOC). These advanced systems perform real-time diagnosis of faults, specify site maintenance requirements, dispatch resources when issues trigger predefined financial thresholds and confirm when faults have been corrected.

In this third and final article in this series, we will discuss the deployment options for these advanced performance optimization technologies and more specifically how they can scale to bring “intelligence” to the performance and financial management process of the world’s largest PV arrays.

As PV panel prices have fallen, balance of system (BoS) costs have been gaining more attention. Conventional thinking has been focused on a cost-per-watt-installed metric. Using this lens, any expenditure on BoS items is a capital budget evil that must be minimized. This is a short-sighted view that assumes site design and O&M practices remain static and that the general “rules-of-thumb” for asset overbuild and Performance Ratio (PR) expectation are somehow inviolable facts of life.

A far more useful lens for scrutinizing project viability is Levelized Cost of Energy (LCOE). This takes into account the lifetime energy harvest, ongoing operational costs and the cost of financing, in addition to the initial capital cost. To build a successful project and maximize its potential for return, all four of these terms should be worked, not just the initial capital cost. This alters the dynamics of  considering BoS costs, with more focus being brought onto how smart BoS decisions can increase the numerator in the LCOE equation (increase energy harvest, reduce O&M costs, reduce costs of financing and insurance), far more than they impact the denominator (increased initial capital cost).

In the previous article, we explained how improved insight enabled by the precision and granularity of panel-level monitoring, coupled with enhanced O&M practices enabled by machine-based diagnostics, can raise the expectations for Performance Ratio and hence lifetime energy harvest. It can also reduce O&M costs, by automatically diagnosing impairments, pin-pointing their location, calculating the economic impact of intervention and then recommending prioritized action. Furthermore, there is growing evidence of its acceptance by the finance and insurance industry as a key element in risk mitigation, which can be a gate to getting a project financed and may reduce the costs of borrowing and insurance coverage. In Europe, large projects are now hard to finance without string-level monitoring as a minimum. There is also increasing attention from the insurance industry on technologies that can monitor panel degradation rates against warranties, increase physical asset security and increase safety by reducing the risk of fire and electric shock. From 2014, the National Electrical Code in the United States is set to outlaw the installation of any rooftop system that isn’t able to be rendered safe, down to the panel level, within seconds.

Advanced panel-level monitoring and control, such as that provided by the Clarity system from Solar Power Technologies Inc., is designed to address all of these ‘numerator enhancing actions’ in the LCOE equation.

Dynamic Optimization Technology, Design Flexibility and Smart Deployment Options

Project ROI can be enhanced further by the deployment of dynamic optimization technology, such as DC-DC converters, otherwise known as optimizers. These distributed panel-level electronic devices increase energy harvest by dynamically addressing the mismatches that arise within an array due to panel mismatch, damage, degradation, differential soiling, shade, alignment differences, variable clouding or temperature variations. According to NREL, such mismatch terms have the biggest impact on the Performance Ratio of PV arrays, amounting to a 10 percent to 50 percent downside risk to expected energy output. By using DC optimizers, which maintain every panel at maximum power point irrespective of array mismatches, typical recovery can be as much as 50 percent of the energy that would otherwise have been lost to these mismatch impairments.

In a large, well built, well maintained array, that doesn’t suffer any effects of shade or misalignment, the typical energy harvest gain from using optimizers will be in the 6 to 8 percent range over the life of the array. This is on top of the benefits that are gained by leveraging the advanced monitoring capabilities that are provided with many optimizer solutions.

Despite these benefits, large array owners have been reluctant to specify the use of optimizer technology. The potential energy harvest gain has not been viewed as sufficiently large or certain enough to overcome concerns regarding the initial capital cost for the technology. In essence, concern that the LCOE equation isn’t improved enough. However, next generation optimizers provide additional benefits in two key areas, which make this technology a compelling option in large-scale arrays.

The first area is flexibility in deployment. Fully autonomous optimizers, which can work independent of central control, or proprietary inverter technology, can be selectively deployed in areas of a large array that are known or suspected to have mismatch vulnerability. For instance, the part of an array that is subject to daily or seasonal shade; an array edge that gets excessive soiling from adjacent agricultural activity, or roads; the array center that gets less convection cooling and so exhibits higher cell temperatures that cause string drop-outs or even inverter trips in hot weather. These areas can be determined at the time of array design, or they can be highlighted by advanced monitoring technology once the array is operational. Optimizer technology can then be specified or retrofitted into areas with the maximum identified payback. With this intelligent, selective deployment, a site can enjoy the majority of the benefits of optimization technology but at a reduced cost, since optimizers are only committed to areas of maximum impact.