Probabilistic assessment of transient stability in reduced inertia systems

Abstract

A probabilistic approach to assess the transient stability of power systems with increased penetration of wind and Photo-Voltaic generation is presented in this paper. The impact on transient stability due to the intermittent behavior of Distributed Energy Resources (DERs) as well as due to their dynamic response when a disturbance happens is investigated. Moreover, the effect of conventional generation disconnection and consequently inertia reduction is studied. Apart from calculating transient stability related indices, a clustering technique is also applied to provide more information considering the impact of DERs and conventional generation disconnection on transient stability.

Contribution of Advanced Demand Side Management to Angular Stability of Interconnected Transmission Networks

“…It has been recognised in [6] that system angular stability is highly affected by system loading in such a way that high system loading can result in system angular instability. To be more specific, better angular stability performance is expected from system with higher spare capacity of synchronous machines while reduced spare capacity or disconnection of synchronous machines may result in detrimental effect on system angular stability [7].…”

“…However, reconnection of disconnected loads is expected to reduce the ability of synchronous machines to support system stability and therefore, resulting in decreased system angular stability. Moreover, system inertia is another essential factor that determines the system angular stability performance in such a way that systems with higher inertia present better angular stability performance [7].…”

Probabilistic Framework for Online Identification of Dynamic Behavior of Power Systems With Renewable Generation

“…All random variables are sampled according to appropriate probability distributions describing the behavior of corresponding uncertain parameter. Further details can be found in [6], [20]. The reason for performing probabilistic studies ensures that the representative (most probable) contingencies and operating conditions, from the set of all possible contingencies and operating conditions (determined by setting realistic ranges of uncertainties considered) will be considered and used for the training of the DTs (for the given system within the time frame of the study) which will consequently enable them to perform well in a realistic environment.…”