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Full-Text Articles in Engineering
Multi-Layered Energy Management Framework For Extreme Fast Charging Stations Considering Demand Charges, Battery Degradation, And Forecast Uncertainties, Waqas Ur Rehman, Jonathan W. Kimball, Rui Bo
Multi-Layered Energy Management Framework For Extreme Fast Charging Stations Considering Demand Charges, Battery Degradation, And Forecast Uncertainties, Waqas Ur Rehman, Jonathan W. Kimball, Rui Bo
Electrical and Computer Engineering Faculty Research & Creative Works
To achieve a cost-effective and expeditious charging experience for extreme fast charging station (XFCS) owners and electric vehicle (EV) users, the optimal operation of XFCS is crucial. It is however challenging to simultaneously manage the profit from energy arbitrage, the cost of demand charges, and the degradation of a battery energy storage system (BESS) under uncertainties. This paper, therefore, proposes a multi-layered multi-time scale energy flow management framework for an XFCS by considering long- and short-term forecast uncertainties, monthly demand charges reduction, and BESS life degradation. In the proposed approach, an upper scheduling layer (USL) ensures the overall operation economy …
Cooperative Deep $Q$ -Learning Framework For Environments Providing Image Feedback, Krishnan Raghavan, Vignesh Narayanan, Sarangapani Jagannathan
Cooperative Deep $Q$ -Learning Framework For Environments Providing Image Feedback, Krishnan Raghavan, Vignesh Narayanan, Sarangapani Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
In This Article, We Address Two Key Challenges in Deep Reinforcement Learning (DRL) Setting, Sample Inefficiency and Slow Learning, with a Dual-Neural Network (NN)-Driven Learning Approach. in the Proposed Approach, We Use Two Deep NNs with Independent Initialization to Robustly Approximate the Action-Value Function in the Presence of Image Inputs. in Particular, We Develop a Temporal Difference (TD) Error-Driven Learning (EDL) Approach, Where We Introduce a Set of Linear Transformations of the TD Error to Directly Update the Parameters of Each Layer in the Deep NN. We Demonstrate Theoretically that the Cost Minimized by the EDL Regime is an Approximation …
Continual Reinforcement Learning Formulation For Zero-Sum Game-Based Constrained Optimal Tracking, Behzad Farzanegan, Sarangapani Jagannathan
Continual Reinforcement Learning Formulation For Zero-Sum Game-Based Constrained Optimal Tracking, Behzad Farzanegan, Sarangapani Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
This study provides a novel reinforcement learning-based optimal tracking control of partially uncertain nonlinear discrete-time (DT) systems with state constraints using zero-sum game (ZSG) formulation. To address optimal tracking, a novel augmented system consisting of tracking error and its integral value, along with an uncertain desired trajectory, is constructed. A barrier function (BF) with a tradeoff factor is incorporated into the cost function to keep the state trajectories to remain within a compact set and to balance safety with optimality. Next, by using the modified value functional, the ZSG formulation is introduced wherein an actor–critic neural network (NN) framework is …
Virtual Inertia Scheduling (Vis) For Real-Time Economic Dispatch Of Ibrs-Penetrated Power Systems, Buxin She, Fangxing Li, Hantao Cui, Jinning Wang, Qiwei Zhang, Rui Bo
Virtual Inertia Scheduling (Vis) For Real-Time Economic Dispatch Of Ibrs-Penetrated Power Systems, Buxin She, Fangxing Li, Hantao Cui, Jinning Wang, Qiwei Zhang, Rui Bo
Electrical and Computer Engineering Faculty Research & Creative Works
A New Concept Called Virtual Inertia Scheduling (VIS) is Proposed to Efficiently Handle the Increasing Penetration of Inverter-Based Resources (IBRs) in Power Systems. VIS is an Inertia Management Framework that Targets Security-Constrained and Economy-Oriented Inertia Scheduling and Generation Dispatch with a Large Scale of Renewable Generations. Specifically, It Determines the Appropriate Power Setting Points and Reserved Capacities of Synchronous Generators and IBRs, as Well as the Control Modes and Control Parameters of IBRs to Provide Secure and Cost-Effective Inertia Support. First, a Uniform System Model is Employed to Quantify the Frequency Dynamics of the IBRs-Penetrated Power Systems after Disturbances. Leveraging …