Even considering that the software already takes into account all possible measures to save energy, there are many aspects requiring some sort of configuration involving the power economy of the system:
installation: the choice between an optimal installation and one coping with physical obstacles
dimensioning of the battery
dimensioning of the solar panel
configuring the software
autonomy requirements and acceptable duration of power failure events
and many variables:
variable requirements (number and power requirements of sensors, frequency of measurement,...)
variable conditions (latitude, geographical obstacles, sunlight exposure, long periods of overcast sky)
Furthermore a tradeoff between cost and performance should be chosen during the configuration phase, and a system designed for a particular set of conditions may fail in case of software configuration changes.
There are many other considerations adding to the complexity of this particular design phase, and there are essentially two approaches to the problem:
empirical: the first requires the installation of a standard system fulfilling minimum requirements, then a validation of the system and, if needed, a possible software and hardware modification with subsequent resizing of the power supply, by trial and error, until a condition of self-sufficiency is reached
by design: the second involves an a priori calculation and sizing of the energy requirements of the custom system with validation of the design in the field.
The first step to implement the latter approach is to define an equation involving all the relevant variables. A further step will be implementing an online configuration page using this equation under the hood.
Even considering that the software already takes into account all possible measures to save energy, there are many aspects requiring some sort of configuration involving the power economy of the system:
and many variables:
Furthermore a tradeoff between cost and performance should be chosen during the configuration phase, and a system designed for a particular set of conditions may fail in case of software configuration changes. There are many other considerations adding to the complexity of this particular design phase, and there are essentially two approaches to the problem:
The first step to implement the latter approach is to define an equation involving all the relevant variables. A further step will be implementing an online configuration page using this equation under the hood.