Two strategies are employed to determine the position of the sun. The first employs sensors and iterative adjustment of the array to find the orientation that produces the maximum power. This strategy has the advantage of simplicity, but can be disrupted by the presence of clouds or other shadows. Once the position of the sun is lost, it may not be found again, and the array can remain poorly oriented.
A second strategy is based on the location (latitude and longitude) of the array and date/time data. Location data can be established within a microprocessor at the time of installation, and the microprocessor can include a clock. With these data, and a well-chosen solar position algorithm, the microprocessor can determine the position of the sun, even if it is obscured by clouds or other obstacles. The array can be positioned accurately regardless of weather, so when the sun comes out the array will already be correctly positioned.
Both methods are commonly employed, with the latter being generally considered more reliable.
An additional input to some controllers comes from an anemometer (wind speed sensor). When wind speed exceeds a set limit, the panels may be “stowed” – oriented so as to minimize drag against the wind and reduce risk of damage to the array. The stow position may be horizontal in regions with no snow, or tilted to the south in snowy regions to allow snow to slide off.
Tracking systems may include motors, actuators, and/or hydraulics. The control system must be configured accordingly, typically using encoders.
When panels are close together, they may partially shade each other early and late in the day. Simple algorithms provide for “back-tracking” – panels are kept at the “noon” position during those hours, so they continue to produce energy and do not shade each other (Figure 3). This feature reduces total energy produced, typically by 1% to 2%, but allows closer spacing of panels which increases the amount of energy produced per unit array area.
Tracking control systems typically gather little information; energy production is more commonly logged by the inverters that convert DC power to AC power. Data gathered by the tracking control system is primarily for evaluating its function and providing alerts when the system is not working properly.
On advanced networked solar tracking control systems, power and energy data can be logged by the solar tracker controller. In these systems, the data can be directly correlated with the tracker movements to verify correct and optimum operation.
Energy lost due to system down-time may be many times the energy consumed for operation of the tracking system, and of much more value than the cost of the control hardware. Thus, the primary considerations for control system selection are reliability and energy production.
Energy production can be accurately estimated by analysis of the control system algorithm together with insolation data from NREL or another proven source. Reliability can be evaluated using data for the hardware components and analysis of the control algorithm to understand potential failure modes during operation.
Tracking systems can increase energy production dramatically, reducing the number and cost of the panels and other system components needed to meet a given load. Control systems of high reliability and low relative cost are available to optimize the function of tracking systems and minimize the cost per unit of energy produced.
1. http://www.fsec.ucf.edu/en/publications/ pdf/fsec-gp-68-01.pdf
2. http://www.nrel.gov/rredc/pvwatts/ changing_parameters.html