Publications

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Traditionally electric grid planning strives to maintain safe, reliable, efficient, and affordable service for current and future customers. As policies, social preferences, and the threat landscape evolve, additional considerations for power system planners are emerging, including decarbonization, resilience, and energy equity and justice. The MOD-Plan framework leverages and extends prior work to provide a framework for integrating incorporating resilience, equity, and decarbonization into integrated distribution system planning.

Abstract not provided.

Abstract not provided.

Abstract not provided.

In the face of increasing natural disasters and an aging grid, utilities need to optimally choose investments to the existing infrastructure to promote resiliency. This paper presents a new investment decision optimization model to minimize unserved load over the recovery time and improve grid resilience to extreme weather event scenarios. Our optimization model includes a network power flow model which decides generator status and generator dispatch, optimal transmission switching (OTS) during the multi-time period recovery process, and an investment decision model subject to a given budget. Investment decisions include the hardening of transmission lines, generators, and substations. Our model uses a second order cone programming (SOCP) relaxation of the AC power flow model and is compared to the classic DC power flow approximation. A case study is provided on the 73-bus RTS-GMLC test system for various investment budgets and multiple hurricane scenarios to highlight the difference in optimal investment decisions between the SOCP model and the DC model, and demonstrate the advantages of OTS in resiliency settings. Results indicate that the network models yield different optimal investments, unit commitment, and OTS decisions, and an AC feasibility study indicates our SOCP resiliency model is more accurate than the DC model.

The goal of this work is to identify critical nodes in a bulk electric system for grid resilience to a specified threat. We present a cascading outage framework and an analytical framework for identifying electric grid failure trends and critical components. We create thousands of threat scenarios to be modeled in a dynamic electric grid cascading outage model. Each threat scenario determines which major grid components are removed from service due to the threat. The cascading outage model runs transient dynamic simulations which allow for secondary transients to affect the relays/protection leading to cascading outages. The results of the cascading model feed an analytics model to identify trends and critical components whose failure is more likely to cause serious systemic effects. Information on which system components are most critical to electric grid resilience can significantly assist grid planning and reduce grid consequences of large-scale disasters.

The Cramér-Rao Lower Bound (CRLB) is used as a classical benchmark to assess estimators. Online algorithms for estimating modal properties from ambient data, i.e., mode meters, can benefit from accurate estimates of forced oscillations. The CRLB provides insight into how well forced oscillation parameters, e.g., frequency and amplitude, can be estimated. Previous works have solved the lower bound under a single-channel PMU measurement; thus, this paper extends works further to study CRLB under two-channel PMU measurements. The goal is to study how correlated/uncorrelated noise can affect estimation accuracy. Interestingly, these studies shows that correlated noise can decrease the CRLB in some cases. This paper derives the CRLB for the two-channel case and discusses factors that affect the bound.

This paper studies a novel mixed-integer linear programming (MILP) formulation on the application of mobile energy storage (MES) to assist with black-start restoration following the full blackout of an electrical network. By synthesizing techniques in the literature to model generator black start and MES activity, the formulation is the first to integrate the two concepts. Furthermore, it recognizes that the manner in which MES facilitates black-start (BS) restoration may differ depending on what component damages occurred during the event that induced the blackout. Within the IEEE 14-Bus System, testing of the formulation has not only confirmed its efficacy but also underscored circumstances where BS restoration could especially benefit from MES intervention in practice. With an MES sized at 2.59% of total MW generation capacity, in certain damage configuration categories the median load energy unserved is reduced by as much as 45.52 MWh (8.26%), and the median final load supplied is raised by as much as 22.98 MW (10.39%).

We present a procedure for randomly generating realistic steady-state contingency scenarios based on the historical outage data from a particular event. First, we divide generation into classes and fit a probability distribution of outage magnitude for each class. Second, we provide a method for randomly synthesizing generator resilience levels in a way that preserves the data-driven probability distributions of outage magnitude. Finally, we devise a simple method of scaling the storm effects based on a single global parameter. We apply our methods using data from historical Winter Storm Uri to simulate contingency events for the ACTIVSg2000 synthetic grid on the footprint of Texas.

We propose a two-stage scenario-based stochastic optimization problem to determine investments that enhance power system resilience. The proposed optimization problem minimizes the Conditional Value at Risk (CVaR) of load loss to target low-probability high-impact events. We provide results in the context of generator winterization investments in Texas using winter storm scenarios generated from historical data collected from Winter Storm Uri. Results illustrate how the CVaR metric can be used to minimize the tail of the distribution of load loss and illustrate how risk-Aversity impacts investment decisions.

Abstract not provided.

Abstract not provided.

In the face of increasing natural disasters and an aging grid, utilities need to optimally choose investments to the existing infrastructure to promote resiliency. This paper presents a new investment decision optimization model to minimize unserved load over the recovery time and improve grid resilience to extreme weather event scenarios. Our optimization model includes a network power flow model which decides generator status and generator dispatch, optimal transmission switching (OTS) during the multi-time period recovery process, and an investment decision model subject to a given budget. Investment decisions include the hardening of transmission lines, generators, and substations. Our model uses a second order cone programming (SOCP) relaxation of the AC power flow model and is compared to the classic DC power flow approximation. A case study is provided on the 73-bus RTS-GMLC test system for various investment budgets and multiple hurricane scenarios to highlight the difference in optimal investment decisions between the SOCP model and the DC model, and demonstrate the advantages of OTS in resiliency settings. Results indicate that the network models yield different optimal investments, unit commitment, and OTS decisions, and an AC feasibility study indicates our SOCP resiliency model is more accurate than the DC model.

Abstract not provided.

This paper presents a preliminary investigation on controlling the existing high voltage dc (HVDC) links connecting the North American western interconnection (WI) to the other interconnections, to provide damping to inter-area oscillations. The control scheme is meant to damp inter-area modes of oscillation in the WI by using wide area synchrophasor feedback. A custom model is developed in General Electric's PSLF software for the wide area damping control scheme, and simulations are analyzed on a validated full 22,000 bus WI model. Results indicate that implementing the proposed control technique to the existing HVDC links in the WI can significantly improve the damping of the inter-area modes of the system.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.