NAP is a comprehensive software package for planning and analysis of electric power networks.
A single graphical user interface allows to access several calculation models:
- Initial Load Flow (ILF)
- Constrained Power Flow (CPF)
- Optimum Power Flow (OPF)
- Short Circuit (SCC)
- Contingency Analysis (OUTSIM)
- Stability (STABIL)
A state-of-the-art software
NAP is the result of more than 30 years of Systems Europe experience in load flow models, new research on mathematical and physical systems and modern Object Oriented Programming techniques. Our primary objectives were always to develop a software that is:
- easy to use: no specific skill is required to handle NAP interface because it is based on Windows standards.
- Planning oriented, i.e. several scenarios can be defined, commissioning and decommissioning years are taken into account, as well as load growth.
- Based on reliable, flexible and powerful algorithms.
Graphical Network Display
Networks are displayed in a one-line diagram schematic representation. The user may edit data and results to display on this network drawing. Moreover, any data or result may determine the colour and thickness of the network elements. Several windows can also be simultaneously opened, allowing to analyse at a glance different network alternatives. Standard drawing functions, such as zoom facilities, are of course available.
Network elements, i.e. nodes, lines, DC lines and transformers are created by simply drawing them on the network display. Click and drag is also available in order to move them.
By simply clicking on any network element, the user can edit any of its data and visualise its results. All data are in physical units (MW, km, ...), forget prerequisite per unit conversion.
Scenarios are organised into a hierarchical structure based on inheritance. It means that, if a particular data is not defined in a scenario, its value equals the value defined in its parent scenario. This parent value can inherit from its own parent, and so on. This method is the best for defining variants and avoiding data redundancy. As for planning, scenarios can differ in technical data or investments strategies..