Related papers: Microgrid Optimal Energy Scheduling Considering Ne…
Health evaluation for lithium-ion batteries (LIBs) typically relies on constant charging/discharging protocols, often neglecting scenarios involving dynamic current profiles prevalent in electric vehicles. Conventional health indicators for…
Fast charging has attracted increasing attention from the battery community for electrical vehicles (EVs) to alleviate range anxiety and reduce charging time for EVs. However, inappropriate charging strategies would cause severe degradation…
In terms of the operation of microgrids, optimal scheduling is a vital issue that must be taken into account. In this regard, this paper proposes an effective framework for optimal scheduling of renewable microgrids considering energy…
This paper proposes a new convex model predictive control strategy for dynamic optimal power flow between battery energy storage systems distributed in an AC microgrid. The proposed control strategy uses a new problem formulation, based on…
The control of a battery thermal management system (BTMS) is essential for the thermal safety, energy efficiency, and durability of electric vehicles (EVs) in hot weather. To address the battery cooling optimization problem, this paper…
With the integration of renewable energy resources in power systems, managing operational flexibility and reliability while minimizing operational costs has become increasingly challenging. Battery energy storage system (BESS) offers a…
This work optimizes a lithium-ion battery charging schedule while considering a joint revenue and battery degradation model. The study extends the work of Meheswari et. al. to encourage battery usage/charging at optimal intervals depending…
Microgrids are self-sufficient small-scale power grid systems that can employ renewable generation sources and energy storage devices and can connect to the main grid or operate in a stand-alone mode. Most research on energy-storage…
This study addresses the challenges of energy deficiencies and high impact low probability (HILP) events in modern electrical grids by developing resilient microgrid energy management strategies. It introduces a sliding Model Predictive…
We consider energy-efficient wireless resource management in cellular networks where BSs are equipped with energy harvesting devices, using statistical information for traffic intensity and harvested energy. The problem is formulated as…
Hybrid power trains (HPT) run on multiple energy sources, often involving energy storage systems/batteries (ESS). As a result, the risk of battery degradation and the reliability of energy storage elements pose a major challenge in…
Utility-scale off-grid renewable power-to-hydrogen systems (OReP2HSs) typically include photovoltaic plants, wind turbines, electrolyzers (ELs), and energy storage systems. As an island system, OReP2HS requires at least one component,…
This paper proposes and experimentally validates a two-stage scheduling and control strategy for a behind-the-meter battery energy storage system (BESS) delivering both local and grid services. Considered services are the maximization of PV…
Equivalent Circuit Model(ECM)has been widelyused in battery modeling and state estimation because of itssimplicity, stability and interpretability.However, ECM maygenerate large estimation errors in extreme working conditionssuch as…
This paper addresses the challenges of charging infrastructure design (CID) for electrified public transport networks using Battery Electric Buses (BEBs) under conditions of sparse energy consumption data. Accurate energy consumption…
The rising integration of variable renewable energy sources (RES), like solar and wind power, introduces considerable uncertainty in grid operations and energy management. Effective forecasting models are essential for grid operators to…
By modeling the uncertainty of spinning reserves provided by energy storage with probabilistic constraints, a new optimal scheduling mode is proposed for minimizing the operating costs of an isolated microgrid (MG) by using…
This paper presents a unified framework for the optimal scheduling of battery dispatch and internal power allocation in Battery energy storage systems (BESS). This novel approach integrates both market-based (price-aware) signals and…
Advancing lithium-ion batteries (LIBs) in both design and usage is key to promoting electrification in the coming decades to mitigate human-caused climate change. Inadequate understanding of LIB degradation is an important bottleneck that…
This work presents an effective state of health indicator to indicate lithium-ion battery degradation based on a long short-term memory (LSTM) recurrent neural network (RNN) coupled with a sliding-window. The developed LSTM RNN is able to…