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Analyzing the consequences of power factor degradation in grid-connected solar photovoltaic systems
(2024)
This study examines the impact of integrating solar photovoltaic (PV) systems on power factor (PF) within low-voltage radial distribution networks, using empirical data from the Energy Self-Sufficiency for Health Facilities in Ghana (EnerSHelF) project sites in Ghana. The research included simulations focusing on optimal PV integration, with and without PF considerations, and the strategic placement of PV and shunt capacitors (SC). Three scenarios evaluated PV injection at high-load demand nodes, achieving penetration levels of 85.00 percent, 82.88 percent with high voltage drop, and 100.00 percent with high loss nodes. Additionally, three scenarios assessed SC allocation methods: proportional to the node's reactive power demand (Scenario I), even distribution (Scenario II), and proportional to installed PV capacity at PV nodes (Scenario III).
The analysis used a twin-objective index (TOI), combining voltage deviations and power factor degradation. Results showed significant PV curtailment was necessary to achieve standard PF. Optimal penetration levels, considering TOI, reduced PV penetration from 85.00 percent to 63.75 percent, 82.88 percent to 57.38 percent, and 100.00 percent to 72.50 percent for high load, high voltage drops, and high loss nodes, respectively. Notably, all scenarios showed a concerning PF of 0.00 at dead-end nodes (P20, P21, P22).
Scenario I achieved PF ranges of -0.26 to 1.00 with PV at high load, -0.69 to 1.00 with PV at high voltage drop, and 0.95 to 1.00 with PV at high loss nodes. Scenario II produced similar ranges, -0.48 to 1.00, -1.00 to 0.99, and 0.30 to 0.96, with PV placement at high load, voltage drops, and loss nodes, respectively. Scenario III yielded ranges of -0.19 to 0.97 (high load), -0.23 to 1.00 (high voltage drop), and 0.86 to 0.96 (high losses).
The study concluded that the most effective strategy involves installing PVs at high-loss nodes and distributing SCs proportionally to the node's reactive power demand (Scenario I). This approach achieved a more uniform PF pattern throughout the network, highlighting the practical implications of strategic PV placement and targeted reactive power compensation for maintaining a healthy and efficient distribution system with solar PV integration.
Intention: Within the research project EnerSHelF (Energy-Self-Sufficiency for Health Facilities in Ghana), i. a. energy-meteorological and load-related measurement data are collected, for which an overview of the availability is to be presented on a poster.
Context: In Ghana, the total electricity consumed has almost doubled between 2008 and 2018 according to the Energy Commission of Ghana. This goes along with an unstable power grid, resulting in power outages whenever electricity consumption peaks. The blackouts called "dumsor" in Ghana, pose a severe burden to the healthcare sector. Innovative solutions are needed to reduce greenhouse gas emissions and improve energy and health access.
Optimal placement and upgrade of solar PV integration in a grid-connected solar photovoltaic system
(2024)
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.