Evaluation of PV and QV based Voltage Stability Analyses in Converter Dominated Power Systems

PV and QV analyses have been widely used in industry. It has already been proven that these steady state methods can be used to assess power system's load ability from voltage stability perspective and that their use in terms of accuracy is justified when compared to time domain simulations. However, this prior validation was carried out for conventional synchronous generator dominated power systems. With increasing levels of power electronics interfaced generation (PEIG) being integrated in power systems, the accuracy of the PV and QV methods for these `green' power systems can be challenged. This paper investigates to what extend the use of these methods is justified when the power system faces a displacement of conventional generation with PEIG. To this end, assessments with the IEEE 9 bus system and full converter wind turbine generators have been performed in this study. It is shown that, when compared to time domain simulations, the traditional PV and QV analyses do not always accurately predict the saddle-node bifurcation point. Steady state PV analyses show inaccuracies between 1.8% and 16.8% (when compared to time domain simulations) in identification of the instability point. The mismatch between steady state and time domain QV analyses is between 6.1% and 22.9%. Based on the achieved results, QV analysis is shown to be typically less accurate than PV analysis for PEIG rich systems

Penempatan TCSC Untuk Memperbaiki Stabilitas Tegangan Akibat Perubahan Konfigurasi Sistem Transmisi JAMALI 500 KV Tahun 2019

Kebutuhan akan tenaga listrik yang terus berkembang setiap tahunnya menyebabkan sistem transmisi dipaksa untuk beroperasi pada batas stabilitasnya. Untuk mengatasi hal tersebut, diperlukan perubahan konfigurasi sistem dan penambahan unit generator. Namun hal tersebut membuat sistem menjadi semakin kompleks dan rentan terhadap gangguan, salah satunya adalah ketidakstabilan tegangan. Kestabilan tegangan dari sistem tenaga listrik dapat ditingkatkan dengan menggunakan Flexible AC transmission system (FACTS) seperti Thyristor Controlled Series Compensator (TCSC). Dikarenakan biaya yang mahal, maka diperlukan studi untuk menentukan lokasi pemasangan TCSC. Pada Tugas Akhir ini dibahas mengenai studi pemasangan Thyristor Controlled Series Compensator (TCSC) untuk memperbaiki stabilitas tegangan dari sistem transmisi Jawa-Bali 500 kV tahun 2019. Line Stability Factor (LQP) digunakan untuk menentukan lokasi yang optimal untuk pemasangan TCSC. Analisis stabilitas tegangan dilakukan dengan menggunakan LQP dan Kurva PV. Hasil menunjukan adanya peningkatan stabilitas tegangan dan power transfer capability setalah pemasangan TCSC. ================================================================= The growing need for electric power each year causes the transmission system to be forced to operate at its stability limit. To overcome this, it is required to change system configuration and add the generator unit. However, it makes the system more complex and susceptible to interference, one of which is the problem of voltage instability. Voltage stability of a power system can be improved using Flexible AC transmission system (FACTS) like Thyristor Controlled Series Compensator (TCSC). Due to the high cost, a study is needed to determine the location of the TCSC installation. This final project discussed the installation of Thyristor Controlled Series Compensator (TCSC) to improve the voltage stability of 500 kV Java-Bali transmission system in 2019. Line Stability Factor (LQP) is used to determine optimal location for TCSC installation. Voltage stability analysis is done by using LQP and PV curve. The results show an increase in voltage stability and power transfer capability after TCSC installation

Online monitoring and control of voltage stability margin via machine learning-based adaptive approaches

Voltage instability or voltage collapse, observed in many blackout events, poses a significant threat to power system reliability. To prevent voltage collapse, the countermeasures suggested by the post analyses of the blackouts usually include the adoption of better online voltage stability monitoring and control tools. Recently, the variability and uncertainty imposed by the increasing penetration of renewable energy further magnifies this need. This work investigates the methodologies for online voltage stability margin (VSM) monitoring and control in the new era of smart grid and big data. It unleashes the value of online measurements and leverages the fruitful results in machine learning and demand response. An online VSM monitoring approach based on local regression and adaptive database is proposed. Considering the increasing variability and uncertainty of power system operation, this approach utilizes the locality of underlying pattern between VSM and reactive power reserve (RPR), and can adapt to the changing condition of system. LASSO (Least Absolute Shrinkage and Selection Operator) is tailored to solve the local regression problem so as to mitigate the curse of dimensionality for large-scale system. Along with the VSM prediction, its prediction interval is also estimated simultaneously in a simple but effective way, and utilized as an evidence to trigger the database updating. IEEE 30-bus system and a 60,000-bus large system are used to test and demonstrate the proposed approach. The results show that the proposed approach can be successfully employed in online voltage stability monitoring for real size systems, and the adaptivity of model and data endows the proposed approach with the advantage in the circumstances where large and unforeseen changes of system condition are inevitable. In case degenerative system conditions are identified, a control strategy is needed to steer the system back to security. A model predictive control (MPC) based framework is proposed to maintain VSM in near-real-time while minimizing the control cost. VSM is locally modeled as a linear function of RPRs based on the VSM monitoring tool, which convexifies the intricate VSM-constrained optimization problem. Thermostatically controlled loads (TCLs) are utilized through a demand response (DR) aggregator as the efficient measure to enhance voltage stability. For such an advanced application of the energy management system (EMS), plug-and-play is a necessary feature that makes the new controller really applicable in a cooperative operating environment. In this work, the cooperation is realized by a predictive interface strategy, which predicts the behaviors of relevant controllers using the simple models declared and updated by those controllers. In particular, the customer dissatisfaction, defined as the cumulative discomfort caused by DR, is explicitly constrained in respect of customers\u27 interests. This constraint maintains the applicability of the control. IEEE 30-bus system is used to demonstrate the proposed control strategy. Adaptivity and proactivity lie at the heart of the proposed approach. By making full use of real-time information, the proposed approach is competent at the task of VSM monitoring and control in a non-stationary and uncertain operating environment

Optimal power flow considering voltage stability with significant wind penetration

Voltage stability evaluation is one of the major issues in the power system operation and control. One reason is that there is an enormous number of voltage collapses which frequently occurs. The principal objective of this thesis is to choose appropriate criteria for voltage stability evaluation in optimal power flow (OPF) approach considering the worst contingency or the congested condition. Voltage stability can be affected by several elements and control ways which operate on different time scales. In particular, the role of wind power generation, demand response (DR), over excitation limiter (OXL), energy storage system (ESS) and on-load tap changer (OLTC) are significant. The proper modelling of these elements and control ways as well as using in an OPF approach should be analyzed in longterm voltage stability. First, an impedance-based (IB) index is presented in this thesis that can evaluate unstable behavior of the power system with doubly-fed induction generator (DFIG) wind farms integration. A model for DFIG capability curve limits is presented that can be integrated to the internal circuit of the generator. Furthermore, the OLTC model was added to this index. The index uses the concept of coupled single-port circuit. The OPF with new IB-index constraint is implemented to show the performance of the index. This study also introduces a multi-objective stochastic optimal power flow (SOPF) approach with the presence of uncertain wind power generations. The multi-objective SOPF investigates the operating cost, voltage stability and emission effects as the objective functions. The effect of the DR program is considered in this study. The fuzzification technique is used to normalize all objective functions in the multi-objective SOPF. A line voltage stability index (LVSI) is presented and compared with other LVSIs. The proposed multi-objective SOPF is also carried out with different existing LVSIs as the objective functions. Following the voltage stability assessment, the frequency control is also considered in the SOPF. In this case, the frequency restoration scheme cooperates with DR and spinning reserve to stop a frequency drop in contingency events. This scheme is defined in three levels. Furthermore, an extended-L (EL) index is used to evaluate voltage stability analysis. Several frequency and voltage constraints are added in the SOPF approach. The EL-index considers a generator equivalent model (GEM). In addition, energy storage systems (ESSs) are considered in this SOPF approach. Those approaches are analyzed in detail and they are tested and validated on several case studies. The results show that the proposed approaches operate successfully