SUSTAINABLE MICROGRID OPERATION: SNS ALGORITHM FOR COST-EFFICIENT ENERGY MANAGEMENT

This paper proposes a social network search (SNS) algorithm for optimizing energy management systems (EMS) in microgrids. The EMS focuses on economic aspects, specifically addressing economic load dispatch (ELD) in both grid-connected and isolated operational modes, with a specific emphasis on integrating renewable energy resources (RES). The effectiveness and efficiency of the proposed SNS algorithm are evidenced through simulations using a microgrid model with five distinct cases, each featuring varying combinations of distributed energy resources (DERs). To ensure a comprehensive evaluation, the particle swarm optimization (PSO) algorithm is also utilized. The results show that the proposed SNS algorithm is effective in determining optimal dispatch strategies for DERs in all operational modes, as well as optimizing power transactions with the main grid to reduce operational costs in grid-connected configurations. Moreover, the proposed SNS algorithm outperforms the PSO algorithm in all cases studied. Furthermore, the findings highlight the positive impact of RES on total generation costs, demonstrating how increasing RES integration, particularly solar and wind power, contributes to lower microgrid costs and reduced dependence on external grid power procurement, thereby enhancing overall microgrid performance efficiency.

Authors

Institutions

Publication Details

Journal
ERJ Engineering Research Journal
Published
2024-09-05
DOI
https://doi.org/10.21608/erjm.2024.276713.1324
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

SUSTAINABLE MICROGRID OPERATION: SNS ALGORITHM FOR COST-EFFICIENT ENERGY MANAGEMENT

S.R. Spea, Adel A. Abou El‐Ela, Nahla Zanaty
ERJ Engineering Research Journal
Smart Grid Energy Management
article

SUSTAINABLE MICROGRID OPERATION: SNS ALGORITHM FOR COST-EFFICIENT ENERGY MANAGEMENT

S.R. Spea, Adel A. Abou El‐Ela, Nahla Zanaty
article en

Abstract

This paper proposes a social network search (SNS) algorithm for optimizing energy management systems (EMS) in microgrids. The EMS focuses on economic aspects, specifically addressing economic load dispatch (ELD) in both grid-connected and isolated operational modes, with a specific emphasis on integrating renewable energy resources (RES). The effectiveness and efficiency of the proposed SNS algorithm are evidenced through simulations using a microgrid model with five distinct cases, each featuring varying combinations of distributed energy resources (DERs). To ensure a comprehensive evaluation, the particle swarm optimization (PSO) algorithm is also utilized. The results show that the proposed SNS algorithm is effective in determining optimal dispatch strategies for DERs in all operational modes, as well as optimizing power transactions with the main grid to reduce operational costs in grid-connected configurations. Moreover, the proposed SNS algorithm outperforms the PSO algorithm in all cases studied. Furthermore, the findings highlight the positive impact of RES on total generation costs, demonstrating how increasing RES integration, particularly solar and wind power, contributes to lower microgrid costs and reduced dependence on external grid power procurement, thereby enhancing overall microgrid performance efficiency.

ERJ Engineering Research JournalVol. 0(0)
Menoufia University (EG)
Affordable and clean energy
Openalex Percentile: Top 87%
Smart Grid Energy Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.