Optimal Allocation and Sizing of Battery Energy Storage System in Distribution Network Using Mountain Gazelle Optimization Algorithm
This paper addresses the problem of finding the optimal position and sizing of battery energy storage (BES) devices using a two-stage optimization technique. The primary stage uses mixed integer linear programming (MILP) to find the optimal positions along with their sizes. In the secondary stage, a...
Saved in:
Main Authors: | Umme Mumtahina, Sanath Alahakoon, Peter Wolfs |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
|
Series: | Energies |
Subjects: | |
Online Access: | https://www.mdpi.com/1996-1073/18/2/379 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Optimizing the Supply Chain for Recycling Electric Vehicle NMC Batteries
by: Fransisca Indraningsih Kasy, et al.
Published: (2025-01-01) -
Mathematical modelling-based blockchain with attention deep learning model for cybersecurity in IoT-consumer electronics
by: Hayam Alamro, et al.
Published: (2025-02-01) -
Multi-Timescale Battery-Charging Optimization for Electric Heavy-Duty Truck Battery-Swapping Stations, Considering Source–Load–Storage Uncertainty
by: Peijun Shi, et al.
Published: (2025-01-01) -
RL-ADN: A high-performance Deep Reinforcement Learning environment for optimal Energy Storage Systems dispatch in active distribution networks
by: Shengren Hou, et al.
Published: (2025-01-01) -
Optimizing model for agile product development in garment industry
by: Suhartini Suhartini, et al.
Published: (2025-01-01)