The electric power grid is operated with exceptionally high levels of reliability, yet recent large-scale outages have highlighted areas for improvement in operation, control, and planning of power systems.  Synchrophasor technology may be able to address these concerns, and Phasor Measurement Units (PMUs) are actively being deployed across the Western Interconnection and North America.  Initiatives such as the Western Interconnection Synchrophasor Program (WISP) are making significant investments PMUs with the expectation that wide-area, synchronized, high-resolution measurements will improve operator situational awareness, enable advanced control strategies, and aid in planning the grid. This research is multifaceted in that it focuses on improved operator awareness and alarming as well as innovative remedial controls utilizing synchrophasors.  It integrates existing tools, controls, and infrastructure with new technology to propose applications and schemes that can be implemented for any utility.  This work presents solutions to problems relevant to the industry today, emphasizing utility design and implementation.  The Bonneville Power Administration (BPA) and Western Electricity Coordinating Council (WECC) transmission systems are used as the testing environment, and the work performed here is being explored for implementation at BPA.  However, this work is general in nature such that it can be implemented in myriad networks and control centers. A Phase Angle Alarming methodology is proposed for improving operator situational awareness.  The methodology is used for setting phase angle limits for a two-tiered angle alarming application.  PMUs are clustered using an adapted disturbance-based probabilistic rms-coherency analysis.  While the lower tier angle limits are determined using static security assessment between the PMU clusters, the higher tier limits are based on pre-contingency operating conditions that signify poorly damped post-contingency oscillation ringdown.  Data mining tools, specifically decision trees, are employed to determine critical indicators and their respective thresholds.  An application is presented as a prototype; however, the methodology may be implemented in online tools as well as offline studies. System response to disturbances is not only dependent on pre-contingency conditions but also highly dependent on post-contingency controls.  Pre-defined controls such as Special Protection Schemes (SPSs) or Remedial Action Schemes (RAS) have a substantial impact on the stability of the system.  However, existing RAS controls are generally event-driven, meaning they respond to predetermined events on the system.  This research expands an existing event-driven voltage stability RAS to a response-based scheme using synchrophasor measurements.  A rate-of-change algorithm is used to detect substantial events that may put the WECC system at risk of instability.  Pickup of this algorithm triggers a RAS that provides high-speed wide-area reactive support in the BPA area.  The controls have proved effective for varying system conditions and topologies, and maintain stability for low probability, high consequence contingencies generally dismissed in today's deterministic planning studies. With investments being made in synchrophasor technology, the path of innovation has been laid; it's a matter of where it goes.  The goal of this research is to present simple, yet highly effective solutions to problems.  Doing so, the momentum behind synchrophasors can continue to build upon itself as it matures industry-wide. / Ph. D.

Information and communication technologies are being implemented more than ever in the power industry in order to make smarter power grids, termed as cyber-physical power systems (CPPSs). Along with the privileges of such modern power networks like reducing the total operation cost for end-use customers, they may be negatively affected by cyberattacks, above all false data injection (FDI) attacks as they are easier to be performed. As a case in point, an adversary can detour security systems, penetrate into the cyber layer of a typical CPPS, and manipulate the information, finally leading to security threats. Although prevention and detection mechanisms are significant tools to be utilized by power system operators to improve the reliability of such systems against cyberattacks, they cannot ensure the security of power grids since some FDI attacks might be designed to bypass the detection stage. Hence, a more powerful tool will be required, which is called remedial action scheme (RAS), to be implemented by power system operators to recover the targeted power grid in a timely manner. Toward this end, different RAS frameworks are presented in this dissertation in transmission, distribution, and microgrid levels to highlight the effectiveness of such reaction mechanisms in case of cyber threats targeting modern power systems. In the transmission level, optimal power flow (OPF) integrated with thyristor controlled series capacitor (TCSC) have been utilized to design a RAS to mitigate the negative impacts of FDI attacks, resulting in system congestion or power outages. In the distribution level, system operators take advantage of static VAR compensator (SVC) through solving a customized version of distribution feeder reconfiguration (DFR) problem to mitigate voltage violations in the form of overvoltages and undervolatges, caused by FDI cyberattacks. In light of the fact that some FDI attacks bypass the employed detection methods, it is crucial to prepare in advance for such scenarios. Hence, in this dissertation, a real-world framework is also proposed for mitigating false data injection (FDI) attacks targeting a lab-scale wind/PV microgrid and resulting in power shortage. The proposed RAS is developed as a hardware-in-the-loop (HIL) testbed within the cyber-physical structure of the smart microgrid. Finally, as a prerequisite of the proposed intelligent RAS, which is able to be used on different levels of a CPPS, power system operator is being in attacker’s shoe to scrutinize different scenarios of cyberattacks to make an initial archive set. The design of such mechanisms incorporates long-short-term memory (LSTM) cells into a deep recurrent neural network (DRNN) for the processing of archived data, termed intelligent archive framework (IAF), identifying the proper reaction mechanisms for different FDI cyberattacks. To react to cyberattacks for which similar pre-investigated remedial measures were not saved in the IAF, a power flow analysis is considered to a) examine the interdependency between transmission and distribution sectors and b) generate appropriate RASs in real time.