Journal of Solar Energy Research
Volume:8 Issue: 4, Autumn 2023

Allocating renewable energy systems (RESs) in an electrical distribution system (EDS) is crucial to achieving various objectives. However, their intermittency presents several challenges. In this connection, an efficient meta-heuristic pathfinder algorithm (PFA) is employed to determine the optimal location and size of photovoltaic (PV) and wind turbine (WT) systems, along with energy storage systems (ESS) and capacitor banks (CB) for both grid and islanding modes of operations. An objective function was formulated for loss reduction, greenhouse gas (GHG) emissions, and voltage profile improvement. The simulation results for the IEEE 33-bus EDS system are shown for two cases: grid-connected and islanding. The computational effectiveness of the PFA was compared with that reported in the literature. The PFA results showed an outstanding ability to resolve difficult optimisation problems. In addition, the optimal size of the RES when the network operates in the grid-connected mode can significantly improve the performance. The real power losses and GHG emissions were reduced by 48.49 % and 67.75% with PV systems and the other, respectively, whereas WT systems they are reduced to 69.68 % and 67.85 %, respectively. However, a combination of ESS, CB, and PV/WT can render the EDN sustainable for the islanding mode of operations.

This research had the overarching goal of optimizing maintenance intervals and reducing the maintenance workload by enhancing accessibility for individuals lacking technical expertise in the upkeep of photovoltaic systems, with a particular focus on rooftop applications. The study achieved this objective by employing a linear regression algorithm to analyse climatic parameters such as wind speed, humidity, ambient temperature, and light intensity, collected from the installation site of a photovoltaic solar energy system. Simultaneously, the current and voltage values obtained from the system were also examined. This analysis not only facilitated the determination of power generation within the system but also enabled real-time detection of potential issues such as pollution, shadowing, bypass, and panel faults on the solar panels. Additionally, an artificial intelligence-supported interface was developed within the study, attributing any decline in power generation to specific causes and facilitating prompt intervention to rectify malfunctions, thereby ensuring more efficient system operation.

Most low-voltage (LV) feeders have significant losses, poor voltage profiles, and inadequate stability margins owing to their radial construction and high R/X ratio branches, thus, they may not be able to handle substantial solar photovoltaics (SPVs) and EV penetration. Thus, optimal integration of SPVs and rapid charging stations (RCSs) can solve this problem. This paper offers an enhanced pathfinder algorithm (EPFA) with guiding elements and three followers' life lifestyle procedures based on animal foraging, exploitation, and killing. First, the EV load penetration was used to evaluate the feeder performance. Subsequently, the required RCSs and SPVs were appropriately integrated to match the EV load penetration and optimise feeder performance. An Indian 85-bus real-time system was used for simulations. The losses and GHG emissions increased by 150% and 80%, respectively, without the SPVs and RCS for zero-to-full EV load penetration. RCSs allocation alone reduced the losses by 40.1%, whereas simultaneous SPVs and RCSs allocation reduced the losses by 66%. However, the GHG emissions decreased by 13.7% and 54.33%, respectively. This study shows that SPVs and RCS can enhance the feeder performance both technically and environmentally. In contrast, EPFA outperformed the other algorithms in terms of the global solution and convergence time.

This paper aims to study providing electricity and domestic hot water demand for a single-family house in Basra city, south of Iraq. Three systems have been simulated by TRNSYS16 software to determine their thermal and electrical performance: traditional house (without PVT), with the PVT/water-based and with the PVT/0.4%Al2O3 systems. The annual energy consumption, collected energy, auxiliary energy, thermal solar fraction and domestic hot water have been analyzed in long-term simulation. The results show that the use of the PVT/water and the PVT/0.4%Al2O3 systems combined with the house decreased the annual energy consumption by about 43.54% and 52. 33% compared with the traditional house. The results also established that when using the PVT/0.4%Al2O3 system, the collected energy increased by 17.12%, while the auxiliary energy decreased by 31.51% compared with the PVT/water system. It is also concluded that using both the PVT/Al2O3 and the PVT/water systems with the traditional building covered the domestic hot water demand at about 42% to 100%, and 46% to 100% in various months, respectively. Finally, the results highlighted that there is an improvement in the thermal solar fraction of about 14.5% in the case of using the PVT/Al2O3 system compared with the PVT/water) system

Accurate Global Horizontal Irradiance (GHI) data is key to designing optimal solar PV systems. Limited by the availability and high cost of traditional pyranometers in developing countries like Nigeria, this study proposes a cost-effective alternative using the Ångström-Prescott model and readily available sunshine data from the Nigerian Meteorological Agency. Empirical models for GHI estimation were developed for 37 selected locations across Nigeria. The country was divided into three regions, and estimates were then compared with NASA data using statistical metrics like R2, MBE, and RMSE to evaluate model performance. The results indicate that Sokoto, Ibi, and Abakaliki have the highest GHI values of 5.86 kWh/m2/day, 4.90 kWh/m2/day, and 4.76 kWh/m2/day, respectively. Conversely, the lowest GHI values were observed in Jos, Ilorin, and Benin City, with values of 4.84 kWh/m2/day, 4.71 kWh/m2/day, and 4.37 kWh/m2/day for regions 1, 2, and 3, respectively. Statistical tests revealed underestimation in the Gusau and Abuja models, slight overestimation in Sokoto, and the lowest accuracy in Jos. R² values ranged from 0.706 to 0.985, indicating strong correlations and high accuracy in most regions. By leveraging readily available sunshine data, this cost-effective method allows accurate GHI estimation, driving improved solar PV systems in Nigeria and similar contexts.

Although hydrogen is in its early stages in Iran, its development capacity is high. Considering the importance of these issues, this paper examines for the first time the production of hydrogen from solar energy in the hot and humid climate of Iran. For this purpose, five stations have been selected in Khuzestan province, and using HOMER V2.81 software, the annual solar electricity production of a 20 kW power plant connected to the grid has been calculated considering five types of solar panels (Mono-Crystalline, Poly-Crystalline, CIGS, CdTe, Amorphous). Then, using analytical equations and a solid oxide electrolyzer, the annual hydrogen production has been calculated. The results showed that Amorphous technology is the most suitable in terms of cost, and CdTe technology is the most suitable in terms of energy production and pollutant reduction. In total, among the studied stations, Masjed-e Soleyman city had the highest electricity production, highest hydrogen production, highest CO2 emission reduction prevention, and lowest cost per kWh produced with values of 37,492 kWh/year, 1,254.4 kg/year, 1,768 kg/year and $0.072/year respectively. Among the studied stations, Ahwaz was found to be the least suitable station.