Industrial electric power grid operation subject to an extreme event requires decision making by human operators under stressful conditions. Decision making using system data informatics under adverse dynamic events, especially if forecasted, should be supplemented by intelligent proactive control. Power transmission system operation during wildfires requires resiliency-driven proactive control for load shedding, line switching, and resource allocation considering the dynamics of the wildfire and failure propagation to minimize the impact on the system. However, the possible number of line and load switching in an extensive industrial system during an event make the traditional prediction-driven and stochastic approaches computationally intractable, leading operators to often use preplanned or greedy algorithms. In this article, we model and solve the proactive control problem as a Markov decision process (MDP) and introduce an integrated testbed for spatiotemporal wildfire propagation and proactive power-system operation. Our approach allows the controller to provide setpoints for all generation fleets in the power grid. We evaluate our approach utilizing the IEEE test system mapped onto a hypothetical terrain. Our results show that the proposed approach can help the operator to reduce load outage during an extreme event. It reduces power flow through lines that are to be de-energized and adjusts the load demand by increasing power flow through other lines.

Voltage sag mitigation utilizing dynamic voltage restorers (DVRs) can be classified as a common-pool resource (CPR) good. However, the ability of DVRs in improving voltage sag performance of only downstream customers provides the ability to exclude the non-contributors selectively. Therefore, unlike traditional CPR goods, the DVR allocation problem can give rise to partial excludability. Here, the non-collocated customers have been divided into feasible clusters through suitable positioning of DVRs using the proposed graph-partitioning principle. In the absence of trustworthiness, especially with the participation of electricity supply companies, the participants may ask an external agent and share their willingness-to-pay information to design the optimal set of clusters. Alternatively, the customers, including electricity supply companies, can also share internal information as an open system. Strategies for sharing internal information to avoid free-riding are also discussed. The utility distribution would ensure the viability of contribution group formation. Here, the results from three different utility-distributing solution concepts, such as an alternative definition of the core, the nucleous, and Shapley value, are compared. The simulation results are numerically verified for a small scale system and validated utilizing a large scale system. The proposed methodology can be used for any real-world system that follows similar properties.

With the increasing penetration of primarily inertia-less distributed energy resources, allowable delay in the fast frequency reserve provision to ensure marginal stability condition can become comparable with the requisite dead-time for fast-switching in a radial power distribution system (PDS) connected to the transmission system. Consequently, the prevailing short-duration load-generation imbalance might propagate as system-wide frequency excursion in the future power system, which traditionally has not been observed. Furthermore, during the fast-switching, some of the fast-acting reserve (FAR) providing local generators remain inaccessible to the bulk power system (BPS). This work has answered the questions of requisite reserve requirements to cater to such events through efficient energy and FAR provision joint-scheduling. Stochasticity of fast-switching, with temporary faults as a use-case, requires modeling of load-generation imbalance and local resource unavailability, vis-á-vis FAR requirement problem, as a chance-constraint. Due to the limited visibility at the BPS level, PDS operators must ensure sufficient FAR availability for a given confidence level of the chance-constraint. Individual chance-constraints are used to ensure mathematical simplicity. Here, the PDS is operated as a virtual power plant (VPP), where the operator can procure resources locally or from the wholesale market with the aim of profit maximization before the contingency occurs. Results show that FAR requirements can influence the local energy schedule and raise energy costs. Furthermore, the confidence level of the chance-constraint can impact overall profitability, and FAR should be scheduled carefully. Comparative analysis with a modified benchmark IEEE 33-node radial test system and a 98-node test system shows the superior performance of the proposed approach. The impact of the limited available FAR is also demonstrated.

With the increasing penetration of distributed energy resources (DERs) and extensive usage of information and communications technology (ICT) in decision-making, the mechanisms to control/optimize transmission and distribution grid voltage would experience a paradigm shift. Given the introduction of inverter-based DERs with vastly different dynamics, real-world performance characterization of the cyber-physical system (CPS) in terms of dynamical performance, scalability, robustness, and resiliency with the new control algorithms require precise classification and identification of suitable metrics. It has been identified that classical controller definitions, along with three inter-disciplinary domains, such as (i) power system, (ii) optimization, control, and decision-making, and (iii) networking and cyber-security, would provide a systematic basis for the development of an extended metric for performance evaluation of DER controllers; while providing the taxonomy. Majority of the control algorithms operate in multiple time scales, and therefore, algorithmic time-decomposition facilitates a new way of performance analysis. Extended discussion on communication requirements with the algorithmic architectural subtleties is expected to identify the real-world deployment challenges of voltage control/optimization algorithms in terms of presence of cyber vulnerabilities and associated mitigation mechanisms affecting the controller performance with DERs. Detailed discussion provided identifies the modeling requirements of the CPS for real-world deployment, specific to voltage control, facilitating the development of a unified test bed.