Optimal and Coordinated DER Control for Resiliency Improvement Considering Generation and Load Uncertainties During Extreme Events
Article
Olowu, TO, Inaolaji, A, Behnamfar, M et al. (2025). Optimal and Coordinated DER Control for Resiliency Improvement Considering Generation and Load Uncertainties During Extreme Events
. IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 10.1109/TIA.2025.3620279
Olowu, TO, Inaolaji, A, Behnamfar, M et al. (2025). Optimal and Coordinated DER Control for Resiliency Improvement Considering Generation and Load Uncertainties During Extreme Events
. IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 10.1109/TIA.2025.3620279
This paper proposes a multiobjective distribution optimal power flow formulation to improve the resiliency of distribution feeders. The formulated base resiliency strategy prioritizes critical infrastructures (CIs) by ranking them and ensuring their continuous power supply during extreme events through the optimal sizing and placement of hybrid distributed energy resources (DERs). A DER hosting formulation with uncertainty quantification to maximize the capacity integration of the DER is proposed. To ensure effective voltage regulation during extreme events, the DER's smart inverter (SI)'s grid following and grid forming control capabilities are modeled. To capture the probability of subsystem failure during an extreme weather event, this paper proposes a fragility formulation that considers both the windspeed and the age of the components within the grid. Since the load profiles of the CIs will vary during extreme weather events, this paper proposes a weather-adjusted load profile formulation that uses a sigmoid function to model the CI's occupancy behavioral pattern. An extreme event caused by two hurricane categories is simulated on an IEEE 34 distribution feeder using the proposed probabilities of failures. A mixed integer nonlinear programming formulation that aims to maximize the penetration of the DERs, improve the network resiliency, and minimize the overall network losses while satisfying all network and power flow constraints is formulated. The effectiveness of the proposed resiliency enhancement approach is validated via numerical simulations.
