Research On Voltage Stability And Optimal Reactive Power Dispatch Under Uncertain Environments

Voltage stability and optimal reactive power dispatch (ORPD) are two important and hot topics in power engineering field, in which many researches have been done and abundant achievements have been achieved. Conventional investigations in these two topics, including mathematical models and solution methods, belong to the category of deterministic analysis, and their conclusions have significant instructive effect on voltage stability enhancement and reactive power resources optimal utilization. However, power system is in nature a large one with various uncertain factors. With the heavy integration of renewable energy sources, more and more random factors continue to emerge in current power system. Thorough consideration of these uncertain characteristics in these two topics is particularly significant. Investigations on modeling methods and solving strategy for uncertain characteristics can make contribution to the amendment of academic theory of voltage stability as well as ORPD research, and obtain more achievements with reference value and practical significance. To this reason, research on the two topics under uncertain environments is chosen to be the theme of this thesis, with the following four aspects included:impact of wind speed correlation (WSC) on voltage instability saddle-node bifurcation (SNB), voltage stability probabilistic evaluation considering uncertainty in power injection, comparison and improvement of multi-objective evolutionary algorithms (MOEAs) for multi-objective ORPD, and robust optimal strategy for multi-objective ORPD with consideration of load uncertainty. The investigations and achievements of this thesis are listed as follows.Impact of correlated wind speeds on voltage instability SNB is comprehensively investigated. Nataf transformation is adopted to establish WSC model for wind farms with close locations. Based on SNB transversality condition equations and Monte Carlo simulation technique, probability distribution of voltage stability margin under different WSC coefficients is obtained. Moreover, two risk indexes are presented and the voltage stability deterioration caused by WSC is evaluated from the viewpoint of risk analysis. Experimental results demonstrate that the probability of SNB under relative lower load growth level increases with the strengthening of WSC, implying strong correlated wind speeds bring negative effect in safe and stable operation of power system as far as voltage stability is concerned.A probabilistic evaluation method of voltage stability accounting for uncertainties in wind speeds and load levels is proposed. Based on Latin hypercube sampling (LHS) Monte Carlo simulation technique, this method can maintain a high degree of accuracy and reduce computational burden when compared with the simple random sampling Monte Carlo method. In addition, by combining LHS with Nataf transformation, the presented method can deal with correlated wind speeds of different wind farms and correlated load levels of different buses. Interior point method is used to solve nonlinear programming problems for voltage stability critical point on the sampling points, and the probability distribution of voltage stability margin is obtained. The effectiveness and accuracy of the proposed method is validated by case study on the IEEE118bus system.Five current typical MOEAs are selected and from an overall perspective the application of them in multi-objective ORPD is comparatively researched. Different from traditional approach that combines multiple objective functions into a single one by setting preference parameters, the multi-objective model, in which the system network loss and voltage deviation are taken into account, is directly utilized. Based on the test case of IEEE30bus system, the optimal performances of five MOEAs are compared and the superiorities and defects of them are analyzed in the viewpoints of quality and diversity of non-dominated solution set, extensity and uniformity of final Pareto front and convergence speed. On the basis of evaluating computing performances of five MOEAs the prospect of further research is put forward.A new optimal method based on multiple evolutionary algorithms with adaptive selection strategies (MEAASS) for multi-objective ORPD is proposed. Based on analysis of characteristics of state-of-the-art MOEAs, and considering the rules of consistency and complementation, candidate algorithm pool containing four different algorithms is presented. By means of adaptively favoring individual algorithms that exhibit higher reproductive success during the search, MEAASS simultaneously merges the strengths of multiple algorithms for population evolution. Based on the test case of IEEE30bus system, the computing performance of MEAASS is compared with existing popular algorithms. The numerical simulations demonstrate that MEAASS can obtain better performance of convergence during the entire optimization process.A robust optimal strategy for multi-objective ORPD with consideration of load randomness and correlation is proposed. Based on Monte Carlo integral form of objective functions, the expectations of system network loss and voltage deviation in presence of load fluctuations are approximately calculated, meanwhile the operational constraints under various load perturbations are taken into account, finally robust non-dominated solutions which are insensitive to load uncertainty are achieved. To reduce the error of Monte Carlo integration, LHS combinated with Nataf transformation is adopted to generate load level sample. MEAASS is utilized to solve the robust multi-objective ORPD on IEEE30bus system, and the results demonstrate that control schemes obtained by robust optimal strategy can maintain their performance and consistency with existence of load uncertainty.