Decentralized Charging Control of Electric Vehicles in Residential Distribution Networks
arXiv:1710.05533 · doi:10.1109/TCST.2017.2771307
Abstract
Electric vehicle (EV) charging can negatively impact electric distribution networks by exceeding equipment thermal ratings and causing voltages to drop below standard ranges. In this paper, we develop a decentralized EV charging control scheme to achieve "valley-filling" (i.e., flattening demand profile during overnight charging), meanwhile meeting heterogeneous individual charging requirements and satisfying distribution network constraints. The formulated problem is an optimization problem with a non-separable objective function and strongly coupled inequality constraints. We propose a novel shrunken primal-dual subgradient (SPDS) algorithm to support the decentralized control scheme, derive conditions guaranteeing its convergence, and verify its efficacy and convergence with a representative distribution network model.
arXiv comment16 pages, 11 figures
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- Online Prediction-Assisted Safe Reinforcement Learning for Electric Vehicle Charging Station Recommendation in Dynamically Coupled Transportation-Power Systems
- Chance-Constrained Shrunken-Primal-Dual Subgradient (CC-SPDS) Approach for Decentralized Electric Vehicle Charging Control
- An ADMM-based MIQP platform for the EV aggregation management
- Joint Optimization for Coordinated Charging Control of Commercial Electric Vehicles Under Distributed Hydrogen Energy Supply
- Asynchrony-Resilient and Privacy-Preserving Charging Protocol for Plug-in Electric Vehicles
- Posture Adjustment for a Wheel-legged Robotic System via Leg Force Control with Prescribed Transient Performance
- Distributed Vehicle Grid Integration Over Communication and Physical Networks
- Privacy-Preserving Decentralized Multi-Agent Cooperative Optimization -- Paradigm Design and Privacy Analysis