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In this study, a technique for developing a distribution management system (DMS), which possesses the flexibility to take both preventive and corrective actions against thermal overloading of branches in active distribution networks (ADNs), has been demonstrated. An ADN comprises microgrids that consist of photovoltaic and battery energy storage systems (BESSs). The DMS primarily minimizes the hourly cumulative cost incurred by loads due to energy pricing of utility, by effectively dispatching the BESSs. Besides, the DMS regulates BESS state of charge and bus voltages within their limits. It also controls loading of branches by taking corrective measures during overloading or preventive measures during critical loading conditions. This DMS has been designed using a reinforcement learning based technique, namely, adaptive critic design (ACD). This study elaborates the formulation of ACD algorithm so that an effective performance of the controller can be achieved. As case study, a modified IEEE 5‐bus system along with a microgrid and its controllers have been modelled in detail and simulated in real‐time by developing a simulation‐in‐the‐loop testbed using OPAL‐RT and DSpace. This testbed facilitates simulation of the detailed model along with its power electronic components, such that both transient and steady‐state performance of the system can be observed.
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Bridging Transient and Steady-State Performance in Voltage Control: A Reinforcement Learning Approach With Safe Gradient Flow
Deep reinforcement learning approaches are becoming appealing for the design of nonlinear controllers for voltage control problems, but the lack of stability guarantees hinders their real-world deployment. This letter constructs a decentralized RL-based controller for inverter-based real-time voltage control in distribution systems. It features two components: a transient control policy and a steady-state performance optimizer. The transient policy is parameterized as a neural network, and the steady-state optimizer represents the gradient of the long-term operating cost function. The two parts are synthesized through a safe gradient flow framework, which prevents the violation of reactive power capacity constraints. We prove that if the output of the transient controller is bounded and monotonically decreasing with respect to its input, then the closed-loop system is asymptotically stable and converges to the optimal steady-state solution. We demonstrate the effectiveness of our method by conducting experiments with IEEE 13-bus and 123-bus distribution system test feeders.
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- Award ID(s):
- 2200692
- PAR ID:
- 10493715
- Publisher / Repository:
- IEEE
- Date Published:
- Journal Name:
- IEEE Control Systems Letters
- Volume:
- 7
- ISSN:
- 2475-1456
- Page Range / eLocation ID:
- 2845 to 2850
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1109/LCSYS.2023.3289435
