Reactive Power Management: Comparison of Expert-based and
Optimization-based Approaches for Dispatcher Training
Abstract
Reactive power management (RPM) in electric power systems is usually
based on a rule-based control derived from the transmission system
operator’s experience. This approach faces challenges as the number of
decisions and the complexity of the system operation is increasing. With
the increasing generation from renewables and the evolution of
electricity markets, the available resources must be optimally utilized.
In this paper, a comparison is made between the optimization-based
approach (OBA) and the experience-based expert approach (EBA) for RPM.
The OBA is based on security-constrained optimization with minimum
redispatch cost as the objective function for different contingencies.
In contrast, the EBA’s actions are based on the system operator’s
experience. Comparison is made in terms of the generator redispatch
cost, active and reactive power redispatch volume, nodal voltages, and
the number of actions to ensure secure operation. The analysis using a
reduced model of the target system shows that OBA is more beneficial
than EBA, with up to 22% and 42% reduction in redispatch cost and
volume, respectively. Moreover, the control decisions from both
approaches are seen to be similar. This study aims to show the
usefulness of the OBA and motivate TSOs to move towards
optimization-based reactive power management