Sajeeb Saha

New online voltage stability margins and risk assessment for multi-bus smart power grids

This paper presents a quantitative framework for assessment of voltage stability in smart power networks. First, new stability indices similar to gain and phase margins in linear time invariant control systems are introduced. These indices can be computed online in conjunction with load-flow calculations. Then, a novel risk assessment framework incorporating the new stability indices is developed to methodologically quantify the voltage stability risks a power system faces at any given operating condition. In contrast to existing local stability indices and qualitative risk approaches, the indices and framework introduced provide analytical and quantitative evaluation of voltage stability and associated risks. The results are illustrated with a numerical example.

Dynamic Modeling of Power Systems Experiencing Faults in Transmission/Distribution Networks

In this paper we address some shortcomings in existing nonlinear dynamic models of power system experiencing symmetrical and unsymmetrical faults in their transmission/distribution networks. The shortcomings relate to: 1) approximations relating to stator dynamics, internal voltage of the positive sequence network and the dynamics of the negative and zero sequence networks, and 2) existing models are time -variant, which may not be suitable for system studies such as stability and fault detection studies that require time invariant model. The approximations outlined in 1) adversely affect the modeling accuracy, especially that of the system response during the period immediately after the occurrence of faults. We present in this paper a full fault-dependent time-invariant dynamical model of power systems experiencing symmetrical and unsymmetrical faults in their transmission/distribution networks and verify it through simulation studies mimicking real life scenarios. IEEE 30 bus power system is considered as the study case. The simulation results are compared to Matlabs “SimPower” and PSCAD/EMTDC software packages.

Faults detection and mitigation in excitation control of synchronous machines in large-scale power grids

This paper presents a new decentralised fault detection and mitigation system for excitation control systems used in synchronous generators in power grids. The system detects and diagnoses faults in the basic components of the excitation control systems with high accuracy and in almost real time using fuzzy set theory. Once a fault is diagnosed, a mitigation action follows, where the signal out of the faulty component is replaced by an alternative signal generated by the fault mitigation system. The mitigation action ensures that the field excitation voltage and thus the terminal voltage of the affected generator are controlled in a way that pre-fault stability of the grid is maintained. The accuracy and effectiveness of the proposed scheme are verified through case studies performed on the IEEE 30 bus test system.

Voltage Stability Margins and Risk Assessment in Smart Power Grids

Abstract This paper presents a quantitative framework for assessment of voltage stability in smart power networks. First, new stability indices similar to gain and phase margins in linear time invariant control systems are introduced. Then, a novel risk assessment framework incorporating the new stability indices is developed to methodologically quantify the voltage stability risks a power system faces at any given operating condition. In contrast to existing local stability indices and qualitative risk approaches, the indices and framework introduced provide analytical and quantitative evaluation of voltage stability and associated risks. The results are illustrated with a numerical example.

Excitation system fault diagnosis and mitigation in multi-machine power grids

An approach for fault diagnosis and restoration in the excitation systems of multi-machine power systems is presented in this paper. The approach is capable of detecting and locating faults in any exciter anywhere in the system with high accuracy using simple fuzzy logic. The use of logic only implies that faults can be detected in near real time. Once the fault is detected, the excitation is immediately adjusted to control the field current and thus the terminal voltage of the affected generator and also to ensure stability of the whole system. The high accuracy and real-time aspects of the proposed approach are verified through case studies performed on IEEE 30 bus power system.

An Enhanced Control Scheme for an IPM Synchronous Generator Based Wind Turbine With MTPA Trajectory and Maximum Power Extraction

This paper proposes an enhanced control scheme for a direct drive variable speed wind turbine with an interior permanent magnet (IPM) synchronous generator. The proposed control scheme incorporates maximum torque per ampere (MTPA) trajectory and maximum power extraction, which ensures the generation of required torque for maximum power extraction with minimum stator current. This in turn minimizes stator copper loss and excessive heat generated in the IPM synchronous generator. The performance of the proposed control scheme has been validated through rigours simulation and experimental studies under varying wind speed conditions. The simulation and experimental results demonstrate the efficacy of the proposed control method.

Diagnosis and Mitigation of Sensor Malfunctioning in a Permanent Magnet Synchronous Generator Based Wind Energy Conversion System

An approach for diagnosis and mitigation of sensor malfunctioning in a permanent magnet synchronous generator based direct-drive variable speed wind energy conversion system (WECS) is presented in this paper. Malfunctioning of current sensors causes erroneous grid- and machine-side current measurements, which significantly affect the operation of grid- and machine-side controllers, and in turn, performance of the WECS system degrades. In the proposed approach, the sliding-mode observer-based fault diagnosis theory is used to diagnose (i.e., to detect and estimate) the error induced in the grid- and machine-side current measurements due to sensor malfunctioning. The proposed mitigation action rectifies the measured grid- and machine-side currents using estimated measurement errors, as soon as malfunctioning of sensors is diagnosed, and ensures resilient operation of the WECS against sensor malfunctioning. The accuracy and effectiveness of the proposed approach are verified through rigorous simulation and experimental studies, which clearly demonstrate the effectiveness of the proposed approach.

A cyber attack resilient control for distributed energy resources

This paper presents a cyber-secure control method that enables an attack resilient operation of grid connected electronically coupled distributed energy resources (DERs). First, adverse impacts of attack templates such as denial of service, replay attack and bias injection on the DER system performance are demonstrated. It is shown that each attack scenario can drive the DER system to an unsafe state and jeopardize the system stability. To ensure the safe operation of DER in the presence of attacks, a sliding mode based observer is designed to detect and estimate the attacks. The estimated attacks are then used to compensate for corrupted data. The effectiveness of the proposed cyber attack mitigation method is demonstrated through simulation results applied to a detailed nonlinear (switch) model of a three-phase converter-base DER.

Control of islanded DC microgrids using nonlinear adaptive decentralized controllers

In this paper, an islanded DC microgrid is controlled using nonlinear adaptive decentralized controllers. The decentralized controllers are designed for the DC microgrid components which supply power (e.g., renewable energy sources and other standby generators) and store energy such as battery energy storage systems (BESSs). The power sources and BESSs in DC microgrids are decoupled using feedback linearization technique and adaptive controllers are then designed by considering the DC-link capacitor of these components as unknown. The adaptation law is used to estimate the value of the DC-link capacitor while ensuring the desired value of the common DC-bus voltage. The effectiveness of the proposed controller is evaluated on a DC microgrid with a fuel cell, solar photovoltaic (PV) unit, BESS, and DC loads. Simulation results are carried out under different operating conditions and compared with an existing proportional integral (PI) controller.

Sensor fault resilient operation of permanent magnet synchronous generator based wind energy conversion system

An approach to ensure sensor fault resilient operation of permanent magnet synchronous generator (PMSG) based wind energy conversion system (WECS) has been presented in this paper. Sensors measuring WECS quantities such as generator and grid side currents, generator speed and DC link voltage play essential role in reliable and efficient operation of PMSG based WECS. Malfunctioning of such sensors can significantly disrupt the efficient operation of WECS. The proposed approach complements WECS control systems with sliding mode observer (SMO) based fault diagnosis (detection and estimation) and mitigation components to ensure sensor fault resilient operation of the WECS. The efficacy of the proposed approach is validated through rigorous simulation studies carried out on a WECS connected to a practical test distribution system, which clearly demonstrates that the proposed approach is capable of nullifying the impact of sensor malfunctioning and ensuring efficient and optimal operation of WECS.