no code implementations • 29 Feb 2024 • Jinhao Li, Changlong Wang, Yanru Zhang, Hao Wang
To bridge this gap, we develop a novel BESS joint bidding strategy that utilizes deep reinforcement learning (DRL) to bid in the spot and contingency frequency control ancillary services (FCAS) markets.
no code implementations • 29 Jan 2024 • Jinhao Li, Changlong Wang, Hao Wang
This paper studies the synergy of solar-battery energy storage system (BESS) and develops a viable strategy for the BESS to unlock its economic potential by serving as a backup to reduce solar curtailments while also participating in the electricity market.
no code implementations • 29 Jan 2024 • Jinhao Li, Ruichang Zhang, Hao Wang, Zhi Liu, Hongyang Lai, Yanru Zhang
Renewable energy resources (RERs) have been increasingly integrated into distribution networks (DNs) for decarbonization.
no code implementations • 28 Nov 2023 • Jinhao Li, Shiyao Li, Jiaming Xu, Shan Huang, Yaoxiu Lian, Jun Liu, Yu Wang, Guohao Dai
Weights are quantized by groups, while the ranges of weights are large in some groups, resulting in large quantization errors and nonnegligible accuracy loss (e. g. >3% for Llama2-7b with 2-bit quantization in GPTQ and Greenbit).
no code implementations • 27 Aug 2023 • Jinhao Li, Yu Hui Yuan, Qiushi Cui, Hao Wang
Therefore, we are motivated to develop a comprehensive multi-objective framework for optimal CS placement in a traffic network overlaid by a distribution network, considering multiple stakeholders' interested factors, such as traffic flow, PEV charging time cost, PEV travel distance, and the reliability of the distribution network.
no code implementations • 5 Apr 2023 • Jinhao Li, Changlong Wang, Hao Wang
However, the variable nature of wind generation can undermine system reliability and lead to wind curtailment, causing substantial economic losses to wind power producers.
no code implementations • 27 Dec 2022 • Jinhao Li, Changlong Wang, Hao Wang
Simulations also show that using curtailed wind generation as a power source for charging the BESS can lead to additional financial gains.
no code implementations • 13 Dec 2022 • Zhuo Wei, Frits de Nijs, Jinhao Li, Hao Wang
This paper investigates reinforcement learning, which gradually optimizes a fair PV curtailment strategy by interacting with the system.
no code implementations • 22 Dec 2021 • Jinhao Li, Ruichang Zhang, Hao Wang, Zhi Liu, Hongyang Lai, Yanru Zhang
Considering uncertainties and voltage fluctuation issues introduced by RERs, in this paper, we propose a deep reinforcement learning (DRL)-based strategy leveraging spatial-temporal (ST) graphical information of power systems, to dynamically search for the optimal operation, i. e., optimal power flow (OPF), of power systems with a high uptake of RERs.