RENEWABLE ENERGY SYSTEMS MONITORING
Robust monitoring and targeting is vital as renewable energy technologies are still unfamiliar territory to maintenance teams, and they may not be experienced in the tell-tale signs of underperforming systems
emissions and reducing imported energy dependency. Where subsidies such as FiTs and RHI are eligible, renewables also come with a promise of real cost savings for building owners. However, they are expensive to purchase and install, and the savings they are expected to deliver are often very sensitive to the actual energy delivery. Many renewables (particularly PV)
come with simple monitoring systems and displays. But do these ever show comparative performance against expectation? What does that mean, and do system owners spend time looking at whether value for money is actually being achieved? This becomes an issue if there are numerous renewable energy assets across a dispersed estate. Renewable energy systems normally have
some form of backup – PV systems are grid connected, and renewable heat systems will normally have fossil fuel backup – so if the renewable system fails, there will not be a loss of service. However, there needs to be a trigger or alarm in place to ensure that the renewables are continuing to do their part. If renewables are not set up with an adequate M&T system (and many are not even set up with simple alarms),
it is possible that system failure will go unnoticed for months, as the backup system quietly kicks in. Robust M&T is vital, as renewable energy technologies are still unfamiliar territory to maintenance teams, and they may not be experienced in the telltale signs of underperforming systems.
What can go wrong? Different technologies have different potential problems to watch out for, and a few are discussed here. PV systems suffer disproportionately
from shading. A study at London South Bank University1
showed that an 11% loss
of direct annual sunlight led to a 28% reduction in electricity generation. Even seemingly trivial shading such as a handrail around a roof, or a tree branch, can change the resistance characteristics of a whole array, seriously reducing output. The causes of shading may have been overlooked during design and installation, or may be introduced at some point after installation – for example, a mobile phone mast might be erected on an adjacent building. There is little protection of renewable energy systems in the planning
Calculating PV performance
Modified Cumulative Sum Difference (CUSUM) techniques can be a powerful monitoring and reporting tool for renewable energy systems. For PV systems, we expect a linear (or near-linear) relationship between electricity output and solar irradiation (measured in kWh/m2
). Figure 1 shows just
such a relationship over six months for a PV array. The excellent relationship suggests the system is performing reasonably well. CUSUM analysis uses the equation of this line to predict output of the system for prevailing irradiation conditions, and compares this with the actual output. The differences between actual and predicted outputs each month are cumulatively summed to give a running total of over- or under-performance. Figure 2 shows the 12-month CUSUM for this array, the first six months of which are the period covered in Figure 1. It is apparent from this graph that after
February the performance of the system deteriorated rapidly, and that between
40 CIBSE Journal August 2012
Figure 1: Regression line for PV electricity output against solar irradiation over six months
December and January approximately 1,100 kWh of potential electricity generation was lost. This equates to more than 0.5 tonnes of unavoided CO2 emissions, and around £360 of lost FiTs payments. Contrast this with a CUSUM for a well-performing PV array over the same period (see Figure 3) where little deviation from predicted output is observed. This method of monitoring can be fully automated to provide current savings or waste and incorporate alarms to highlight changes in performance.
Figure 2: 12-month CUSUM for the PV array in Figure 1
Figure 3: 12-month CUSUM of a good-performing PV array
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