Online optimization in power systems with high penetration of renewable generation: Advances and prospects

Z Wang, W Wei, JZF Pang, F Liu, B Yang… - IEEE/CAA Journal of …, 2023 - ieeexplore.ieee.org
Traditionally, offline optimization of power systems is acceptable due to the largely
predictable loads and reliable generation. The increasing penetration of fluctuating …

[HTML][HTML] Smart optimization in battery energy storage systems: An overview

H Song, C Liu, AM Amani, M Gu, M Jalili… - Energy and AI, 2024 - Elsevier
The increasing drive towards eco-friendly environment motivates the generation of energy
from renewable energy sources (RESs). The rising share of RESs in power generation …

Online distributed optimization for spatio-temporally constrained real-time peer-to-peer energy trading

J Liu, Q Long, RP Liu, W Liu, Y Hou - Applied Energy, 2023 - Elsevier
The proliferation of distributed renewable energy triggers the peer-to-peer (P2P) energy
market formations. To make profits, prosumers equipped with photovoltaic (PV) panels and …

A distributed online algorithm for promoting energy sharing between EV charging stations

D Yan, Y Chen - IEEE Transactions on Smart Grid, 2022 - ieeexplore.ieee.org
In recent years, electric vehicle (EV) charging stations have experienced an increasing
supply-demand mismatch due to their fluctuating renewable generation and unpredictable …

[HTML][HTML] Battery control with lookahead constraints in distribution grids using reinforcement learning

J da Silva André, E Stai, O Stanojev, G Hug - Electric Power Systems …, 2022 - Elsevier
In this paper, a computationally efficient real-time control of a battery with lookahead state-of-
energy constraints in active distribution grids with distributed energy sources is presented …

Event-triggered online energy flow control strategy for regional integrated energy system using Lyapunov optimization

G Wang, X Yang, W Cai, Y Zhang - … Journal of Electrical Power & Energy …, 2021 - Elsevier
Abstract Regional Integrated Energy System (RIES) provides an inspiring perspective for
constructing the future-oriented Energy Internet. However, the integration of heterogeneous …

Reinforcement Learning Based Dispatch of Batteries

P Benedicto, R Silva, C Gouveia - 2024 IEEE 22nd …, 2024 - ieeexplore.ieee.org
Microgrids are poised to become the building blocks of the future control architecture of
electric power systems. As the number of controllable points in the system grows …

An optimization framework for distributed energy resource planning and energy management strategy of storage devices and electric vehicles

B Ahmadi, O Ceylan, A Ozdemir - 2022 2nd International …, 2022 - ieeexplore.ieee.org
This paper proposes an optimal coordination strategy for electric vehicles and energy
storage devices in distribution grids besides the optimal allocation problem of renewable …

Distributed Reinforcement Learning for Real-Time Batteries Control Using Lagrangian Decomposition

E Stai, O Stanojev, RDN Di Prata… - … Conference on Smart …, 2022 - ieeexplore.ieee.org
This paper presents an efficient distributed real-time control scheme for a set of batteries in
power grids to follow a day-ahead dispatch plan. The problem of controlling the batteries is …

Economic MPC with an Online Reference Trajectory for Battery Scheduling Considering Demand Charge Management

C Cortes-Aguirre, YA Chen, A Ghosh, J Kleissl… - arxiv preprint arxiv …, 2024 - arxiv.org
Monthly demand charges form a significant portion of the electric bill for microgrids with
variable renewable energy generation. A battery energy storage system (BESS) is …