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Found 16 papers, 1 papers with code
Network-Aware and Welfare-Maximizing Dynamic Pricing for Energy Sharing
The proliferation of behind-the-meter (BTM) distributed energy resources (DER) within the electrical distribution network presents significant supply and demand flexibilities, but also introduces operational challenges such as voltage spikes and reverse power flows.
Feedback Optimization of Incentives for Distribution Grid Services
Energy prices and net power injection limitations regulate the operations in distribution grids and typically ensure that operational constraints are met.
A Decentralized Market Mechanism for Energy Communities under Operating Envelopes
We propose an operating envelopes (OEs) aware energy community market mechanism that dynamically charges/rewards its members based on two-part pricing.
Equitable Networked Microgrid Topology Reconfiguration for Wildfire Risk Mitigation
Increasing amount of wildfires in recent years consistently challenges the safe and reliable operations of power systems.
Operating-Envelopes-Aware Decentralized Welfare Maximization for Energy Communities
We propose an operating-envelope-aware, prosumer-centric, and efficient energy community that aggregates individual and shared community distributed energy resources and transacts with a regulated distribution system operator (DSO) under a generalized net energy metering tariff design.
Enabling Grid-Aware Market Participation of Aggregate Flexible Resources
This paper proposes efficient optimization formulations and solution approaches for the characterization of hourly as well as multi-time-step generation cost curves for a distribution system with high penetration of DERs.
A Generalized LinDistFlow Model for Power Flow Analysis
This paper proposes a new linear power flow model for distribution system with accurate voltage magnitude estimates.
Ripple-Type Control for Enhancing Resilience of Networked Physical Systems
Distributed control agents have been advocated as an effective means for improving the resiliency of our physical infrastructures under unexpected events.
Accelerating Optimization and Reinforcement Learning with Quasi-Stochastic Approximation
(ii) With gain $a_t = g/(1+t)$ the results are not as sharp: the rate of convergence $1/t$ holds only if $I + g A^*$ is Hurwitz.
Online State Estimation for Time-Varying Systems
The paper investigates the problem of estimating the state of a time-varying system with a linear measurement model; in particular, the paper considers the case where the number of measurements available can be smaller than the number of states.
Model-Free State Estimation Using Low-Rank Canonical Polyadic Decomposition
As electric grids experience high penetration levels of renewable generation, fundamental changes are required to address real-time situational awareness.
Physics-Informed Deep Neural Network Method for Limited Observability State Estimation
We show that our method leads to a superior accuracy of the estimation when compared to the case when no physical information is provided.
Robust Matrix Completion State Estimation in Distribution Systems
It can estimate the system state in a low-observability system and has robust estimates without the bad data detection process in the face of multiple bad data.
Bi-Level Online Control without Regret
This paper considers a bi-level discrete-time control framework with real-time constraints, consisting of several local controllers and a central controller.
Response-Based Approachability and its Application to Generalized No-Regret Algorithms
The first (primary) condition is a geometric separation condition, while the second (dual) condition requires that the set be {\em non-excludable}, namely that for every mixed action of the opponent there exists a mixed action of the agent (a {\em response}) such that the resulting payoff vector belongs to $S$.
Online Classification with Specificity Constraints
To our best knowledge, this is the first algorithm that addresses the problem of the average tp-rate maximization under average fp-rate constraints in the online setting.
