In early 2015, extreme snowfall in the Northeast United States and Southeast Canada led to unexpected challenges for operators of solar plants. The solar irradiance map for the region doesn’t suggest exceptional conditions. In fact, Q1 2015 was a fairly sunny period, and a few cloudy, snowy days are to be expected.
What the map doesn’t account for is the record-breaking low temperatures and the heavy February snowfall that refused to melt.
The U.S. Q1 2015 solar irradiance map doesn’t show abnormal conditions, but it doesn’t show the heavy snowfall and cold temperatures that blanketed the Northeast region.
PV panels can cope quite easily with light snowfall; snow will naturally melt throughout the day as panels warm; however, when snow cover is significantly thicker, panels do not warm up sufficiently to shed snow, and it sticks around much longer.
In this situation, operators usually send a maintenance team to resolve the problem manually. While this solution works well, operators are often too quick to implement it. There are several factors one should consider before assigning maintenance funds to solutions that may fail to address the issue. For example, underperformance that may seem snow-related could be related to faulty equipment.
To determine whether a problem is definitely snow-related and not a result of equipment failure, operators can can go outside and look at the snowfall level or use an on-site weather station pyranometer to check irradiance measurements. In extreme weather conditions, these devices are likely to show erroneous results but will at least indicate weather and power production problems and alert operators to the possibility of heavy snowfall.
For sites without weather stations, or if an operator is looking for a backup for the station, an ongoing weather data feed can be installed. Providers of modeled datasets, like Vaisala, supply these. The weather data feed is paired with existing monitoring solutions and provides critical information in underperformance assessments.
To determine the type and thickness of snowfall on panels, the most obvious solution is to send someone out with a ruler. If there is no maintenance team on-site, it’s recommended to use a road sensor: a piece of equipment commonly deployed in other sectors but designed specifically to measure snow and ice.
Road sensors can be used on solar projects to measure snow and ice levels on panels, so operations can make informed maintenance decisions.
Vaisala operates networks of sensors for road authorities in several areas known for extreme weather conditions, such as the Northeast. Knowing details of snow and ice conditions allows for mitigation efforts like salting or sanding roads. While it requires some creative thinking, these same sensors can be used to measure snow and ice levels on PV panels, which allows operators to make informed maintenance decisions.
Even if an issue is proven to be snow-related, immediately calling a maintenance team is not always the most cost-effective solution. If the weather looks to change dramatically over the next few days, an operator may choose to leave the snow on the panels, rather than pay the cost of sending out a maintenance team.
Costs depend on the system and its location. As an example, a 2.5-MW system in Massachusetts would make roughly $3,100 on a sunny day in Februrary. The cost for a team to remove the snow from the panels with a hot air blower would be $2,500. Project operators could argue that if the panels are covered in heavy snow again from a new storm the day after being cleared, the cost of sending in a maintenance team was not money well spent. On the other hand, there might be heavy rain on its way, which could clear the snow without the need for costly manual labor.
Specialized forecasters such as Vaisala can help operators make the most cost-effective decisions in these situations. Forecasts for a certain day and the next seven can be tailored to any given site. Meteograms for temperature and precipitation would give an operator warning of incoming rain storms or future snow cover.
A solar measurement station.
What’s more, these forecasters usually have historic datasets covering irradiance and weather variables from the last 10 to 20 years. This gives operators realistic expectations for future years on their solar park. Vaisala has snow data from 1997 onwards in the United States and can monitor trends to predict snowfall in any given part North America.
It is important that operators are fully aware of when underperformance comes as a result of snow cover and when it doesn’t. If all underperformance is written off as snow-related, other equipment problems can go unnoticed.
That’s why weather-adjusted performance analysis should be conducted regularly to ensure all problems can be properly categorized. Forecasting companies can provide weather resource data for operators to carry out this analysis themselves or can reforecast future performance, identifying areas for project improvement.
Extreme weather conditions do not need to undermine the performance of a functional park. As in the case of the road sensor, the onus is on solar plant operators to identify their biggest headaches and work with service providers to come up with innovative solutions. The first step always involves isolating the specific issue, since only when you know exactly what you’re dealing with can you find the solution that is going to work best for your team and your balance sheet.
This article is by Gwendalyn Bender, Product Manager for Energy Assessment at Vaisala.
