Synergistic Integration of Renewable Energy and HVDC Technology for Enhanced Multi-objective Economic Emission Dispatch Using the Salp Swarm Algorithm

Peter Anuoluwapo Gbadega, Yanxia Sun

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper proposes a Salp Swarm Algorithm (SSA), a unique optimization technique for the synergistic integration of renewable energy and High Voltage Direct Current (HVDC) technology to enhance the performance of multi-objective economic emission dispatch (MODED). The primary aim is to optimize both the economic and environmental aspects of power systems. A mathematical model for MODED based on Wind-Solar-Thermal integrated energy has been carefully constructed, considering variables like the valve point effect, equality constraints, and inequality constraints. The study determines optimal generation levels and associated costs for six thermal generating units under various power demands, exploring diverse scenarios such as Economic Dispatch for High Voltage Alternating Current (HVAC) with Losses, Economic Dispatch for HVDC with Losses, Economic Dispatch for HVDC addressing challenges related to voltage instability, protection difficulties and losses in DC systems, Economic Dispatch HVAC & HVDC with Losses and Economic Dispatch for HVAC & HVDC with Renewable Energy (RE). To validate the model, tests have been conducted on the IEEE 30 Bus System with a substantial presence of renewable energy.

Original languageEnglish
Title of host publicationNeural Computing for Advanced Applications - 5th International Conference, NCAA 2024, Proceedings
EditorsHaijun Zhang, Xianxian Li, Tianyong Hao, Weizhi Meng, Zhou Wu, Qian He
PublisherSpringer Science and Business Media Deutschland GmbH
Pages232-249
Number of pages18
ISBN (Print)9789819770038
DOIs
Publication statusPublished - 2025
Event5th International Conference on Neural Computing for Advanced Applications, NCAA 2024 - Guilin, China
Duration: 5 Jul 20247 Jul 2024

Publication series

NameCommunications in Computer and Information Science
Volume2182 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference5th International Conference on Neural Computing for Advanced Applications, NCAA 2024
Country/TerritoryChina
CityGuilin
Period5/07/247/07/24

Keywords

  • HVAC
  • HVDC technology
  • Multi-objective dynamic economic dispatch
  • Renewable energy
  • Salp swarm algorithm

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics

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