The main aim of this work is to establish a sensor MESH network using an ESP-MESH networking protocol with the ESP32 MCU (a Wi-Fi-enabled microcontroller) for indoor and outdoor air quality monitoring in real time. Each sensor node is deployed at a different location on the college campus and includes sensor arrays (CO₂, CO, and air quality) interfaced with the ESP32. The ESP-MESH networking protocol is a low-cost, easy-to-implement, medium-range, and low-power option. ESP32 microcontrollers are inexpensive and are used to establish the ESP-MESH network that allows numerous sensor nodes spread over a large physical area to be interconnected under the same wireless network to monitor air quality parameters accurately. The data of different air quality parameters (temperature, humidity, PM2.5, gas concentrations, etc.) is taken (every 2 min) from the indoor and outdoor nodes and continuously monitored for 72 min. A custom time-division multiple-access (TDMA) scheduling scheme for energy efficiency is applied to construct an appropriate transmission schedule that reduces the end-to-end transmission time from the sensor nodes to the router. The performance of the MESH network is estimated in terms of the package loss rate (PLR), package fault rate (PFR), and rate of packet delivery (RPD). The value of the RPD is more than 97%, and the value of the PMR and PER for each active node is less than 1.8%, which is under the limit. The results show that the ESP-MESH network protocol offers a considerably good quality of service, mainly for medium-area networks.

A novel algorithm is proposed for power angle control (PAC) to improve power quality (PQ) in distribution system. This algorithm reduces mathematical complication and its response time. It has aimed to make the designs of controller. The new concept is incorporates on triangle rules of vector addition/subtraction. The mathematical approach makes the algorithm efficient and comprehensive. The shunt voltage source converter (VSC) of unified power quality conditioner (UPQC) is controlled using instantaneous symmetrical component theory (ISCT). The ISCT enables UPQC to handle unbalanced and non‐linear loads. The complete phaser diagram has been shown for various voltage conditions. A vector addition and subtraction‐based mathematical calculation has been derived for estimation of different parameters of the proposed system. Proposed PAC can improve PQ in four wire distribution system with maximum utilisation of series VSC of UPQC. A simulation study for voltage sag/swell with the new algorithm for PAC verifies the improved performance of the system. Results have been discussed in detail.

The world is currently facing energy-related challenges due to the cost and pollution of non-renewable energy sources and the increasing power demand from renewable energy sources. Green hydrogen is a promising solution in Libya for converting renewable energy into usable fuel. This paper covers the types of hydrogen, its features, preparation methods, and uses. Green hydrogen production is still limited in the world due to safety requirements because hydrogen has a relatively low ignition temperature and an extensive ignition range and is considered a hazardous element, the lack of infrastructure in Libya, as well as the high cost of production currently. However, the production costs of one megawatt of green hydrogen and fossil fuels are insignificant. This suggests that electricity production from green hydrogen could become an economic competitor to fossil fuels in Libya. This is due to the cost of adding renewable energy to the public electricity grid. Also, the production of gray hydrogen is possible in Libya because of oil through the installation of systems for converting methane gas and capturing carbon dioxide gas.

Due to the increasing energy demand, traditional fossil fuels are gradually decaying day by day as analyzed by many researchers. Fossil fuels are not sufficient to fulfil the requirement of energy demand and it also produces greenhouse gas emissions. In this regard, worldwide research is going on related to renewable energy sources (RESs) like solar photovoltaic (SPV), wind turbines, fuel cells etc. The source of SPV is plentiful and environment friendly which converts solar radiation to non-linear electrical power. This power is not suitable for a stable system. Therefore, the maximum power point tracking (MPPT) controller is required to find the optimum maximum power point (MPP) to the load. The MPPT technology regulates the duty-cycle in favour of the DC-DC converter to continuously obtain maximum power from the SPV arrays. In the past few decades, the learning of MPPT techniques has made substantial progress in the RESs. This research article analyzes the performance of various MPPT techniques in the proposed SPV framework. The main investigation is to assess different MPPT techniques to optimize power from the SPV framework. The artificial neural network (ANN)-MPPT method has been observed to be more effective in output power production and transient response about the MPP than conventional perturb and observe (P&O)-MPPT and fuzzy logic controller (FLC)-MPPT technology.

A unified power quality conditioner (UPQC) has two converters interlinked with back to back DC voltage source. The UPQC is used to improve the multiple power quality (MPQ) of the AC distribution network. The quality of the UPQC depends on the selection of series and shunt control algorithms. The series converter injects the voltage and improves voltage quality whereas the shunt converter injects current and improves the current quality of the AC distribution network. The UPQC works properly if the DC link voltage maintains constant under abnormal or normal condition of AC grid system. Thus, in this paper, DC link voltage is controlled using intelligent model, adaptive neuro fuzzy inference system (ANFIS). The ANFIS result is compared with fuzzy model and conventional PI controller to enhance the mitigation capability of the UPQC. Moreover, the series and shunt converters are controlled by modified second order generalised integrator (SOGI) based algorithm. The performance of intelligent control model is verified by MATLAB based simulation results.

In this work, a hardware model of solar photovoltaic system-based water filter is designed to support the Qatrah program of Kingdom of Saudi Arabia. A solar photovoltaic system provides active energy to charge the battery of 24 Volt via dc to dc boost converter (step-up converter) and battery energy is used to run the dc pump of water filter in remote areas. A boost converter increases the input voltage level of solar panel upto 25 Volt fix to run the dc motor of solar pump and at same time it charges the batteries in sun light. The boost converter switch is pulsed at maximum output power of solar. It is extracted using maximum power point tracking (MPPT) system. An Arduino Nano microcontroller is used to extract the pulse of dc to dc boost converter at MPPT of solar photovoltaic system.