Managing data for solar electric power production requires a new paradigm. Solar power plants are highly distributed, with each site generating renewable energy. Plants are spread over large geographic areas and are typically managed by off-site staff. Every software development project, including solar power inverter software, has unique requirements: specific performance objectives, reliability expectations, and time-to-market constraints. The increasing requirement for data storage on these devices poses a great challenge to developers of software for these systems. When it comes to data management, inverters require a reliable and flexible embedded relational data management technology.
Databases can be implemented in many different ways, and the choice of algorithms in a particular database product has a profound impact on performance. Areas most impacted by the implementation of the database include:
- Support for concurrent data access,
- Ability to manage large amounts of data,
- Performance impact of sharing data between tasks and other applications,
- Support for row-level locking granularity,
- Relative performance of read and write operations,
- Ability to query and analyze data with SQL queries.
Solar inverter software must share data between multiple tasks, continuously collecting data while adjusting settings based on historical trends. Voltage and power are measured and displayed in graphs an a built-in display or over a web-based management interface. Effectively managing this interaction over time is critical to the operation of the inverter and requires special attention during development. An important characteristic required for data management by these inverters from a relational embedded database is performance. Speed is an important consideration for most embedded systems and inverters are no exception.
