TY  - JOUR
U1  - Wissenschaftlicher Artikel
A1  - Amekah, Edward Dodzi
A1  - Ramde, Emmanuel Wendsongre
A1  - Quansah, David Ato
A1  - Twumasi, Elvis
A1  - Meilinger, Stefanie
A1  - Schneiders, Thorsten
T1  - Optimal placement and upgrade of solar PV integration in a grid-connected solar photovoltaic system
JF  - Solar Compass
N2  - The shift towards renewable energy sources has heightened the interest in solar photovoltaic (SPV) systems, particularly in grid-connected configurations, to enhance energy security and reduce carbon emissions. Grid-tied SPVs face power quality challenges when specific grid codes are compromised. This study investigates and upgrades an integrated 90 kWp solar plant within a distribution network, leveraging data from Ghana's Energy Self-Sufficiency for Health Facilities (EnerSHelF) project. The research explores four scenarios for SPV placement optimization using dynamic programming and the Conditional New Adaptive Foraging Tree Squirrel Search Algorithm (CNAFTSSA). A Python-based simulation identifies three scenarios, high load nodes, voltage drop nodes, and system loss nodes, as the points for placing PV for better performance. The analysis revealed 85 %, 82.88 %, and 100 % optimal SPV penetration levels for placing the SPV at high load, voltage drop, and loss nodes. System active power losses were reduced by 72.97 %, 71.52 %, and 70.15 %, and reactive power losses by 73.12 %, 71.86 %, and 68.11 %, respectively, by placing the SPV at the above three categories of nodes. The fourth scenario applies to CNAFTSSA, achieving 100 % SPV penetration and reducing active and reactive power losses by 72.33 % and 72.55 %, respectively. This approach optimizes the voltage regulation (VR) from 24.92 % to 4.16 %, outperforming the VR of PV placement at high load nodes, voltage drop nodes, and loss nodes, where the voltage regulations are 5.25 %, 9.36 %, and 9.64 %, respectively. The novel CNAFTSSA for optimal SPV placement demonstrates its effectiveness in achieving higher penetration levels and improving system losses and VR. The findings highlight the effectiveness of strategic SPV placement and offer a comprehensive methodology that can be adapted for similar power distribution systems.
KW  - Solar energy
KW  - Grid-connected hybrid energy systems
KW  - system losses
KW  - Fossil fuel power
KW  - photovoltaic systems
KW  - Voltage profile
Y1  - 2024
UN  - https://nbn-resolving.org/urn:nbn:de:hbz:1044-opus-87704
SN  - 2772-9400
SS  - 2772-9400
U6  - https://doi.org/10.1016/j.solcom.2024.100099
DO  - https://doi.org/10.1016/j.solcom.2024.100099
VL  - 12
IS  - 2
SP  - 18
S1  - 18
PB  - Elsevier
ER  -