Course Outcome
| CO1 | Illustrate the need for mathematical models and various model examples. |
| CO2 | Apply various techniques for power flow modelling. |
| CO3 | Illustrate modelling methods for renewable energy systems, HVDC and STATCOM. |
| CO4 | Analyze the effect of uncertainty and to develop various energy probabilistic models. |
| CO5 | Develop solutions for differential modelling methods in standard test systems. |
Course Articulation Matrix: Correlation level [ 1: low, 2: medium, 3: High]
| PO | PO1 | PO2 | PO3 | PSO1 | PSO2 |
| CO | |||||
| CO1 | 1 | – | 1 | – | – |
| CO2 | 2 | – | 2 | – | – |
| CO3 | 2 | – | 2 | – | – |
| CO4 | 2 | – | 2 | – | – |
| CO5 | 2 | – | – | – | – |
Energy system modelling: background, motivations, modelling physical systems, time scales of power system dynamics, energy system architecture, energy system scripting, Synchronous machine modelling. Analysis of energy systems: power flow analysis, modelling and solution by Newton Raphson method, continuation power flow analysis, modelling, and solution by homotopy methods, optimal power flow analysis, modelling, and solution by gradient method. Modelling of Renewable Energy: operation of PV & Wind energy systems, frequency impact& voltage analysis, modelling of solid oxide fuel cell and battery energy storage. Modelling of HVDC transmission system and voltage source converter, modelling of STATCOM and analysis. Dealing with uncertainty and probabilistic techniques: uncertainty power flow analysis and probabilistic optimal power flow analysis. Case studies of various analyses on standard IEEE test system.