Data leads to information ….and information leads to insight………
Solar PV plants and wind turbines generate data at an alarming rate (about 1TB in a week). This data gets captured and logged in by the SCADA system as 10 minute or 15 minute average values with time stamps for chronological mapping. When this data is queried or pulled out from the server it is not in any easy readable format nor does it give any immediate value or insight.
Basic reporting tools today collate the average values to generate daily & monthly energy production reports. This is only a basic level of “information” currently derived from the vast amount of data logged by SCADA. It is with some effort that one realizes the vast potential this data has to generate insight & not just information.
Drawing from our expertise in the energy space, Algo Engines offers solar farm and wind farm managers performance assessment tools that leverage a range of visualizations. After all – A Picture is worth a thousand words or rather a terabyte of data…
1. Standard charts – Metrics like GHI, average wind speeds & frequency distribution (wind speed, GHI and so on) helps managers realize the potential renewable power available for conversion.
|Generation of Solar plants at different locations|
2. Two axis charts – Simple co-relation analysis of solar Irradiation Vs Energy units generated or Performance ratio Vs temperature for a PV plant gives immediate insight into the performance and possible reasons for loss of generation.
3. Wind rose – Visualizing the wind rose in a 2D plot helps understand the seasonality & strength of the wind potential at the farm site. One may realize the seasonality of wind if any in case there are few months where wind is stronger from particular range of direction on the wind rose.
4. Heat maps – Availability metrics give clear downtime figures and helps estimate loss of generation and revenue due to unavailability of the section and due to the grid. Algo Engines offers an Energy loss map which gives a quick overview of overall farm loss with drill down options to see inpidual loss due to PV sections or turbines. Red indicates loss while green indicates good performance.
|Energy loss heat map for different projects|
5. Stacked charts – Studying the frequency of critical alarms helps identify the various recurring faults in the inverter, combiner boxes or in the different subsystems of the wind turbine.
For example, alarms relating to string voltage in a PV string can give insight into under-voltage conditions. Temperature breach alarm in inverter casing could indicate possible defects in the power stage circuitry. Also in turbines, the temperature of gearbox oil is typically supposed to hover in the range of 90C. If gearbox oil temperature sensor shows breach of temperature tolerance more often then it may be a cause of concern worthy of quick investigation.
6. Scatter plots – Power curve analysis compares performance of each turbine on a farm with the rated performance as given by the manufacturer & helps understand the under-performing turbines which can be subjected to further investigation & root cause analysis.
For example, between two turbines A & B, it may so happen that A has a greater power generation but this may simply be due to higher average wind availability for that turbine. On studying the power curve plot it
may be realized that A is not generating as much as it should for that wind distribution and B is actually a better performing turbine.
How does all this help the owners & operators?
Based on the information via the different plots like Performance Ratio curve of a solar plant or the Power Curve of a wind turbine, operators are able to develop a more focused O&M strategy where the team’s activity is directed towards better care of the asset, quick identification & correction of critical faults that lead to downtime and revenue loss. Keeping track of alarms & leveraging the power of predictive maintenance helps them save components from failure and in the process save replacement costs and associated downtime. This also translates to better
component life. Knowing the health status of each critical component helps them plan inventory and optimize spares. Constant monitoring of generation & revenue will keep the asset teams informed of the current status and gaps.
At Algo Engines we understand the power of visualizations and have engineered our solution in a way to help owners and operators improve PV plant & turbine life, improve efficiency and get quicker returns on their renewable asset investment.