Value:

Currently reliability of must run units are treated in SC UC problem as an extra set of constraints and are quite often identified by expert knowledge resulting in inefficient solutions. The aim of the tool is to support planners to identify those reliability must-run units according to the real needs of the system applying the risk assessment for the voltage stability.

Features:

The global tendency in the energy sector is to reduce the number of fossil fuel-based generation to renewable energy sources which results in gradual switching from deterministic and fully controllable generation profiles to ones heavily affected by weather conditions and hence stochastic and uncertain. What follows is an increase of importance of risk assessment for power systems, along with the necessity to perform it for the purposes of short-term planning or even real-time operations.

Currently, the most accepted security procedure is based on the N-1 criterion which, when integrated with the security constrained unit commitment/economic dispatch or optimal power flow (SC UC/ED or SC OPF, respectively), allows to assure that the system parameters remain within safety limits after removing one of its elements. Moreover, due to computational issues the SC UC is DC instead of AC based what causes that voltage stability issues are not considered on optimization stage but mainly in pre-processing and some post-processing stage.

Voltage stability is ensured through the addition of the reliability must run units, which are included based on offline analysis and/or expert knowledge. It provides a conservative list of generators which ensures the voltage stability at the expense of the efficiency of the system. For critical situations, the voltage stability is checked again in post-processing: performing an adjustment of operating points, taps changes or extension of set of so called must-run units if it is required.

Innovation:

Substitution of offline analysis/expert knowledge by online analysis, probabilistic power flow analysis, efficient adaptive solution.