Evaluating renewable energy applications in Libya

Modern power systems have been turning to distributed generation (DG) due to the increasing demand for electricity, fuel cost uncertainties, and environmental constraints. Particularly in developing countries, where DG technologies are being adopted for power system expansion planning, renewable energy sources, especially solar energy, have received significant attention. It may be possible to reconsider the traditional power grid paradigm by adopting small networks in islanded configurations in remote villages. This study presents a methodology for calculating and analysing the load demand of Al Marj City in Libya, utilizing a single calculation approach tool. To estimate the electricity load demand for future energy scenarios, it takes into account projected population growth and missing data for electricity distribution networks. Using renewable energy technologies, the study proposes solutions to Libya's random blackouts. Models and simulations are presented for two scenarios utilizing different renewable energy technologies (photovoltaic and wind) and considering standalone and grid-connected scenarios for Al-Marj city. For the photovoltaic and wind systems, the stand-alone cost of energy (COE) is 0.19 US$/kWh and 0.23 US$/kWh, respectively. In the grid-connected case, the COE is 0.15 US$/kWh for photovoltaics and 0.16 US$/kWh for wind systems. In addition, an LSTM neural network is developed and trained using historical data to forecast three crucial indicators, Consumption per capita, Primary energy consumption, and Population. The model's strong fitting accuracy indicates its potential for load demand forecasting in 2030. These forecasting outcomes significantly contribute to the modelling of a stand-alone system scenario through the utilization of Homer Pro software. This allows for the exploration and identification of the optimal system configuration required to meet the increasing load demand by the year 2030. The study employs MATLAB software, utilizing Sensitivity and Particle Swarm Optimization algorithms, to assess the placement and dimensions of distributed generation technologies. The primary objective is to minimize power losses. By comparing scenarios with and without distributed generators, a noteworthy decline in losses is observed, dropping from 0.74786 MW to 0.271021 MW. Furthermore, the investigation delves into the microgrid's behaviour during abrupt load fluctuations while operating in island mode. The simulation results affirm the adeptness of the controller in preserving voltage and frequency within acceptable thresholds, guaranteeing seamless system functioning. Moreover, the research employs HOMER Pro simulation to assess the financial viability of a Storage System aimed at achieving complete decarbonization. Notably, second-life electric vehicle (SL-EV) batteries emerge as the most fitting storage technology. The estimated cost of energy (COE) for systems utilizing SL-EV batteries is approximately 0.46 US$/kWh, notably lower than the calculated 0.67 US$/kWh for systems employing lead-acid batteries. Additionally, in terms of net present cost (NPC), the system integrated with SL-EV batteries necessitates an investment of 6.81 billion dollars, outperforming the lead-acid battery system, which requires an allocation of 7.5 billion dollars. This underlines the superior economic performance of SL-EV batteries in comparison to the conventionally utilized lead-acid batteries

Impact of Foliar Application of Chitosan Dissolved in Different Organic Acids on Isozymes, Protein Patterns and Physio-Biochemical Characteristics of Tomato Grown under Salinity Stress

In this study, the anti-stress capabilities of the foliar application of chitosan, dissolved in four different organic acids (acetic acid, ascorbic acid, citric acid and malic acid) have been investigated on tomato (Solanum lycopersicum L.) plants under salinity stress (100 mM NaCl). Morphological traits, photosynthetic pigments, osmolytes, secondary metabolites, oxidative stress, minerals, antioxidant enzymes activity, isozymes and protein patterns were tested for potential tolerance of tomato plants growing under salinity stress. Salinity stress was caused a reduction in growth parameters, photosynthetic pigments, soluble sugars, soluble proteins and potassium (K+) content. However, the contents of proline, ascorbic acid, total phenol, malondialdehyde (MDA), hydrogen peroxide (H2O2), sodium (Na+) and antioxidant enzyme activity were increased in tomato plants grown under saline conditions. Chitosan treatments in any of the non-stressed plants showed improvements in morphological traits, photosynthetic pigments, osmolytes, total phenol and antioxidant enzymes activity. Besides, the harmful impacts of salinity on tomato plants have also been reduced by lowering MDA, H2O2 and Na+ levels. Chitosan treatments in either non-stressed or stressed plants showed different responses in number and density of peroxidase (POD), polyphenol oxidase (PPO) and superoxide dismutase (SOD) isozymes. NaCl stress led to the diminishing of protein bands with different molecular weights, while they were produced again in response to chitosan foliar application. These responses were varied according to the type of solvent acid. It could be suggested that foliar application of chitosan, especially that dissolved in ascorbic or citric acid, could be commercially used for the stimulation of tomato plants grown under salinity stress