This paper presents the results of a field study undertaken all over the Punjab, Pakistan, to evaluate the socio-economic and climatic impact of photovoltaic-operated high-efficiency irrigation systems (HEIS), i.e., drip and sprinkler irrigation systems. Nearly half of the rural population relies on agriculture for a living, and the recent energy crisis has had a negative impact on rural communities. Farmers’ reliance on fossil fuels for the operation of irrigation systems has increased exponentially, resulting in the high costs of agricultural production. Primary data regarding on-farm agriculture and irrigation practices used in this study were collected through an intensive on-farm survey, while secondary data were taken from published reports and statistics. The results of the current investigation show that the installation of PV systems has resulted in the increased adoption of high-efficiency irrigation systems, a reduction in the high operational costs incurred on account of old diesel-powered pumping systems (with an annual saving of 6.6 million liters of diesel), a 100% increase in farmer’s income, a reduction of 17,622 tons of CO2 emissions per annum, and 41% savings in water. The unit cost of PV-powered HEIS was found to be 0.1219 USD/kWh, which was 4% and 66% less than subsidized electricity cost and diesel cost, respectively.

This paper presents the optimal design of a photovoltaic (PV) drip irrigation system. Designing a PV system is based on calculated motor power, solar irradiance level and other meteorological parameters at a certain geographical location. Therefore, a simulation study of the designed PV system were performed by a PVGIS simulation tool. The PVGIS simulation tool analyzes the potential of power generation with optimal PV modules tilt angle and orientation on a monthly and annual basis, and an analysis of the overall shading situation (horizon) as well as the internal shading between the PV module rows. The selection of water pump and motor depends upon the depth of water table and desired discharge and head to operate the irrigation system. Furthermore, a locally developed Solar-Drip Simulation Tool (SoSiT) was used for load and supply optimization. Based on ambient temperature, solar irradiation and water requirements, SoSiT calculates net generation by a PV system and resultant water output of the irrigation system. The particular drip irrigation site has two zones; the maximum water requirement for zone 1 (row crop) is 50,918.40 Liters/day and for zone 2 (orchards) is 56,908.80 L/day. From PVGIS simulation results, the maximum daily energy production of the designed PV system was 6.48 kWh and monthly energy production was 201 kWh in the month of May. SoSiT results showed that the PV system fulfilled the required crop requirement by only using 28% of the potential water supply, and 72% of the potential water supply from a solar-powered pump was not used. This value is high, and it is recommended to grow more or different crops to utilize the fuel-free electricity from the PV system. The unit cost of PV-powered drip irrigation is USD 0.1013/kWh, which is 4.74% and 66.26% lower than the cost of subsidized electricity and diesel, respectively.

The purpose of this study is to investigate the potential of airborne particulate matter (PM10 and PM2.5) and its impact on the performance of the photovoltaic (PV) system installed in the Sargodha region, being affected by the crushing activities in the hills. More than 100 stone crushers are operating in this region. Four stations within this region are selected for taking samples during the summer and winter seasons. Glass–fiber papers are used as a collection medium for particulate matter (PM) in a high-volume sampler. The concentration of PM is found above the permissible limit at all selected sites. The chemical composition, concentration, and the formation of particulate matter (PM10 and PM2.5) layers on the surface of the photovoltaic module varies significantly depending on the site’s location and time. The accumulation of PM layers on the PV module surface is one of the operating environmental factors that cause significant reduction in PV system performance. Consequently, it leads to power loss, reduction of service life, and increase in module temperature. For the PV system’s performance analysis, two PV systems are installed at the site, having higher PM concentration. One system is cleaned regularly, while the other remains dusty. The data of both PV systems are measured and compared for 4 months (2 months for the summer season and 2 months for the winter season). It is found that when the level of suspended particulate matter (PM10 and PM2.5) increases, the energy generation of the dusty PV system (compared to the cleaned one) is reduced by 7.48% in May, 7.342% in June, 10.68% in December, and 8.03% in January. Based on the obtained results, it is recommended that the negative impact of PM on the performance of the PV system should be considered carefully during the decision-making process of setting solar energy generation targets in the regions with a high level of particulate matter.

Power augmentation in a small-scale horizontal axis wind turbine, with its rotor encased in a flanged diffuser is explored. The power output of the wind turbine varies with changes in the diffuser design and the resulting back pressure. Reduction in this back pressure also results in early flow separation at the diffuser surface, which hinders turbine performance. The main aim of this study is to numerically investigate the local configuration of the wind turbine location inside the diffuser by varying diffuser angles and wind speeds. Therefore, shroud and flange were modeled and analyzed using the computational fluid dynamic (CFD) analyses and experiments were performed at two wind speeds 6 m/s and 8 m/s with and without the diffuser for model validation. The divergence angle of 4° was found to have no flow separation, thus maximizing flow rate. The proposed design shows wind speed improvement of up to 1.68 times compared to the baseline configuration. The corresponding optimum flange height was found to be 250 mm. However, increasing the divergence angle had a similar output. The dimensionless location of wind turbine was found to be between 0.45 and 0.5 for 2° and 4° divergence angle respectively. Furthermore, the maximum augmentation location varies with wind speed and diffuser’s divergence angle as described by dimensionless location of wind turbine, thus presenting a noteworthy contribution to the horizontal axis wind turbine area with the flanged diffuser.

For the past decade, the main problem that has attracted researchers’ attention in aerial robotics is the position estimation or Simultaneous Localization and Mapping (SLAM) of Unmanned Aerial Vehicles (UAVs) where the GPS signal is poor or denied. This article reviews the strengths and weaknesses of existing methods in the field of aerial robotics. There are many different techniques and algorithms that are used to overcome the localization and mapping problem of these UAVs. These techniques and algorithms use different sensors, such as Red Green Blue-Depth (RGB_D), Light Detecting and Ranging (LIDAR), and Ultra-wideband (UWB). The most common technique is used, i.e., probability-based SLAM, which uses two algorithms: Linear Kalman Filter (LKF) and Extended Kalman Filter (EKF). LKF consists of five phases and this algorithm is just used for linear system problems. However, the EKF algorithm is used for non-linear systems. Aerial robots are used to perform many tasks, such as rescue, transportation, search, control, monitoring, and different military operations because of their vast top view. These properties are increasing their demand as compared to human service. In this paper, different techniques for the localization of aerial vehicles are discussed in terms of advantages and disadvantages, practicality and efficiency. This paper enables future researchers to find the suitable SLAM solution based on their problems; either the researcher is dealing with a linear problem or a non-linear problem.

The photovoltaic energy generation system is one of the most promising technology to meet our future electricity demand as well as mitigate climate change. This study aims to design, simulate and evaluate the performance of hybrid photovoltaic (PV) system using PVsyst software to supply electricity for energy efficient streetlights in educational institute. Meteonorm database of daily and monthly irradiation, temperatures, precipitation and sunlight hours are utilized while performing the analysis. The photovoltaic system consists of 56 bifacial-polycrystalline 360-watt PV modules having 17.9% efficiency. The photovoltaic modules were installed at 0° azimuth angle and 15° tilt angle. Two hybrid inverters with rated capacity of 10 kW are used. The energy storage system consists of 16 batteries (2 in series x 8 in parallel) with a nominal capacity of 1600 ampere-hours and discharging minimum SOC is 20 %. A total of 100 streetlight poles with 8 working-hours/day are installed to cover both sides of the road, with monthly energy consumption of 672 kilowatt-hours. The average annual ambient temperature is 23.66℃, and the annual GH irradiation is 1693 kilowatt-hour/m2. The annual production of the hybrid PV system is 25.96 MWh/year, the specific energy production of the system is 1288 kWh/kWp/year with 70.38% performance ratio. By means of proposed photovoltaic system for energy efficient street lightning structure, 157.9t CO2 is reduced. The project can save 0.004737 million tonnes of CO2 emissions over its lifetime of 30 years. The proposed system is a viable solution for public lighting with the right selection of system components.

The demand for cloud computing has drastically increased recently, but this paradigm has several issues due to its inherent complications, such as non-reliability, latency, lesser mobility support, and location-aware services. Fog computing can resolve these issues to some extent, yet it is still in its infancy. Despite several existing works, these works lack fault-tolerant fog computing, which necessitates further research. Fault tolerance enables the performing and provisioning of services despite failures and maintains anti-fragility and resiliency. Fog computing is highly diverse in terms of failures as compared to cloud computing and requires wide research and investigation. From this perspective, this study primarily focuses on the provision of uninterrupted services through fog computing. A framework has been designed to provide uninterrupted services while maintaining resiliency. The geographical information system (GIS) services have been deployed as a test bed which requires high computation, requires intensive resources in terms of CPU and memory, and requires low latency. Keeping different types of failures at different levels and their impacts on service failure and greater response time in mind, the framework was made anti-fragile and resilient at different levels. Experimental results indicate that during service interruption, the user state remains unaffected.

Renewable energy resources are promising in power generation due to their sustainability aspect and environment friendliness as they are means of pollution free power production. Wind energy.y is utilized for power production with the help of wind turbines. The offshore and onshore windfarms consisting of horizontal axis wind turbines are major contributors in the wind energy. However, this type of turbine is not domestically viable mainly due to limitations of directionality and noise. Vertical axis wind turbines do not have these constraints and may blend in the urban environments. In built environments, the wind flow is quite complex due to large scale effects and turbulence. In this paper, the academic building of a university is studied as a possible platform for harnessing the wind energy resources. This case study is performed on academic blocks of University of Gujrat. These building environments were modeled and analyzed with computational fluid dynamic software to model the wind behavior on the building roof top. These results show that there is potential in setting up micro windfarms for the academic environments. The simulation for single building showed a potential for 61.8kW whereas this potential decreased substantially when terrain effects are considered using the circular arrangement for the simulation.