Load Shedding for Voltage Regulation With Probabilistic Agent Compliance
With the increased observability and controllability of distribution systems, the share of behind-the-meter systems is trending upwards rapidly. As a consequence, the impact of human behaviors on system performance can no longer be ignored and should be reflected in the energy management system models. In this paper, we discuss the problem of distribution system voltage control by active power curtailment where the agent compliance of the load curtailment signal is probabilistic. We discuss the modeling of the optimal voltage control problem with probabilistic agent compliance as a chance-constrained optimization problem, its tractable safe approximation using convex restriction, and a scenario-based mixed-integer reformulation as well as the associated solution method based on augmented Lagrangian method. The numerical simulation on IEEE test system validates the effectiveness of the proposed approach in obtaining high-quality feasible load curtailment signal with low computational cost, which makes it a viable tool for real time decision making.
- Research Organization:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Sponsoring Organization:
- USDOE National Renewable Energy Laboratory (NREL), Laboratory Directed Research and Development (LDRD) Program
- DOE Contract Number:
- AC36-08GO28308
- OSTI ID:
- 2228319
- Report Number(s):
- NREL/CP-5D00-88170; MainId:88945; UUID:953fe1b8-a8cc-48ac-ae2b-b95d677ef155; MainAdminID:71170
- Resource Relation:
- Conference: Presented at the the 2023 IEEE Power & Energy Society General Meeting (PESGM), 16-20 July 2023, Orlando, Florida
- Country of Publication:
- United States
- Language:
- English
Similar Records
Distribution-Agnostic Stochastic Optimal Power Flow for Distribution Grids: Preprint
Chance-constrained Service Restoration for Distribution Networks with Renewables