Reactive Power Planning Considering Voltage Stability

Responding to the growing number of voltage collapse events,researches on power system voltage stability has achieved a significantprogress since1970s. However, the theory of voltage stability is still far frommaturity. Consequently, industrial applications are quite limited so far,compared to some classical problems in power system such as rotor anglestability.Load margin index (LMI) is wildly used to evaluate static voltagestability (SVS). However, subject to the inaccurate model and the unilateralhypothetical scenario of load increase, using LMI solely neither can weprecisely predict the parameter changes which lead to static collapse, norcomprehensively capture the impacts of all parameters to the stability. As afavorable complement to LMI, the branch impedance margin index (BIMI),based on nearest collapse point in the branch impedance parameter space,was proposed and validated on12test systems with bus number range from3to3012in this work. By a contrastive analysis, this thesis argued that BIMI, showing a complementarity to LMI, not only remedy the defects of LMI tosome extent, but also has a promising application prospect in indicating SVScritical branches and estimating SVS after N-1contingency.Taking the advantage of BIMI on SVS evaluation after N-1contingency,a two-stage strategy of static reactive power compensation planningconsidering the constraints of voltage stability margin both under normalcondition and after N-1contingency is proposed in this work. The planningscheme produced or refined can not only support the optimal scenario withminimum network loss but also satisfies the SVS requirements under normalcondition and after N-1contingencies with minimum investment cost. Toreliably solve the bi-level optimization model and impove efficiency on thesecond stage, an equivalent model is proposed and demonstrated in this work.Taking advantage of this equivalent model, the primal bi-level problem canbe solved by a classical algorithm with clear convergence and lesscomputation burden. This strategy of reactive power planning is validatedthrough one small-scale system and one practical bulk system.