Techno-economic evaluation of meshed distribution network planning with load growth and expansion with multiple assets across multiple planning horizons

The smart grid paradigm has ushered in an era where modern distribution systems are expected to be both robust and interconnected in topology. This paper presents a techno-economic-based sustainable planning (TESP) strategy, which can be used as a planning framework for linked distribution systems, seeking to discover a realistic solution among competing criteria of diverse genres. In this comparative analysis-based study, three voltage stability assessment indices—VSA_A, VSA_B, and VSA_W—and a loss minimization condition (LMC)-based framework are used in the initial stage to achieve optimal distributed generation (DG)-based asset optimization for siting, followed by sizing. The respective techniques are evaluated across two variants of multiple load growth horizons spread across 10 years. The suggested TESP technique is tested on two variants of a mesh-configured microgrid (MCMG) with varied load growth scenarios. One variant considers a 65-bus MG with a fixed load growth of 2.7% across two load growth horizons. The other variant considers a 75-bus MG with varied load growth across four load growth horizons, encapsulating an expansion-based planning perspective. The numerical results of the suggested TESP approach in a comparative study demonstrate its effectiveness, and it can be used by researchers and planning engineers as a planning framework for interconnected distribution tools across multiple planning horizons. The proposed study would contribute to enhancing the robustness and interconnectivity of smart grid distribution systems. This dual focus could lead to more cost-effective and reliable power distribution systems

Reliability of power systems with climate change effects on PV and wind power generation

Concerns over global climate change has led utilities to reduce greenhouse gas (GHG) emissions by decarbonising the power sector. The accelerating rate of climate change is likely to expose a decarbonised power system to climate related stresses. In particular, Photo Voltaic (PV) and wind power generation systems comprise a significant share in the power grid, which is potentially vulnerable to climate change, and therefore may impact the reliability of power systems with their integrations. Typical reliability assessments do not consider the climate effects and related stresses either on the PV or wind power generating systems or at their component levels. Therefore, this thesis investigates and addresses the challenges of reliability assessment of power grid with the interaction of climate changes and renewable power generation systems. As a part of the investigation, the thesis proposes a novel systematic framework to assess the PV system components’ availability with the interaction of future changes in climate. The framework is developed to quantify the climate related stresses on the hierarchical levels of a PV system, which include component, subsystem, PV system and the grid. The framework was formed by considering multiple elements including thermal stress, bathtub curve, ageing and degradation level and operated on Markov chain embedded Monte Carlo simulation. The uniqueness of the framework is its ability to identify the critical components in a PV system that lead to climate-associated failures. Thesis also proposes a comprehensive framework to assess the reliability of a PV and wind power integrated power system accounting climate change impacts by deploying diverse levels of GHG emission scenarios. Uncertainties in the future climate scenarios were established by proposing an advanced stochastic model considering likelihood-based Markov chain method for generating future climate scenario. The proposed model is integrated to the reliability assessment framework to assess realistic impacts on the reliability of a power system. Investigations were suggested the impacts of climate change effects on PV and wind power generation system were true and in quantitative terms PV systems are more vulnerable to climate change effects than wind power generating systems. The climate change related true impacts on PV and wind power generating systems could be mitigated by quantifying change in impacts quantitatively and then systematic replacement of vulnerable sub system components in time before their end of life. Further investigations suggest that IGBTs and capacitors are key components that are more sensitive to thermal stresses of climate change effects resulting a considering impacts on their availability and on the power system reliability with their presence. Further assessments also revealed that the impacts on power system reliability due to the climate change effects on PV and wind power generation system were not uniform over the long run which further emphasises the need of a quantitative and system assessment in order to expose true impacts of climate change on PV and wind power generation system extending to the entire power system reliability. The thesis provides a solid foundation of frameworks required in the quantitative assessment

The effect of COVID-19 on the characteristics of adult emergency department visits:A retrospective cohort tertiary hospital experience in Riyadh

BACKGROUND: On March 2, 2020, Saudi Arabia identified the first positive COVID-19 case. Since then, several aspects of the COVID-19 impact on Emergency Departments (EDs) use have been reported. The objective of this study is to describe the pattern and characteristics of Emergency Department visits during the COVID-19 pandemic period, compared with the same period in the previous year, including the patients’ demographic information, acuity level, length of stay, and admission rate. METHODS: Data were collected from King Abdulaziz Medical City in Riyadh, Saudi Arabia. The health records of all the patients who presented at the Emergency Department from January 2019 to September 2020 were retrospectively reviewed. The variations in the patient and the visit characteristics were described for the periods before and during COVID-19. RESULTS: The records of 209,954 patients who presented at the Emergency Department were retrieved. In contrast to 2019, the number of visits during the pandemic period reduced by 23%. A dramatic decrease was observed after the announcement of the first COVID-19 diagnosed case in Saudi Arabia, and subsequently the numbers gradually increased. The patients who presented at the Emergency Department during the pandemic period were slightly older (mean age, 43.1 versus 44.0 years), more likely to be older, more urgent and had a higher admission rate compared to the pre-pandemic period. There was a slight increase in visits during the daytime curfew hours and a decrease during the nighttime. CONCLUSION: We report a considerable decrease in the number of Emergency Department visits. The reduction was higher in non-urgent and less urgent cases. Patients presenting at the Emergency Department during the curfew times were more likely to stay longer in the Emergency Department and more likely to be admitted, compared with the pre-pandemic period

Multi-dimensional potential assessment of grid-connected mega-scale floating PV power plants across heterogeneous climatic zones

Floating Photovoltaic (FPV) systems are gradually becoming more desirable due to a multitude of reasons, encompassing proximity to urban water reservoirs (facilitating city access) and their technical advantages. Climate change potentially presents risks of drought and FPV can potentially benefit by providing clean energy as well as saving water from evaporation. However, detailed studies are required to comprehensively evaluate the potential of FPV considering not only the technical parameters but evaluating the climatic effects as well. This paper presents an integrated multi-dimensional framework for the analysis of 2.5 MW grid-connected FPV systems over different climatic zones. In the first layer, a techno-economic and performance evaluation is carried out by fine-tuning different inputs of systems to make it ideal for proposed analyses under actual FPV conditions. Similarly, in the second layer environmental along with forest absorbing carbon analyses are performed. While socio analysis observed in the third fold is based on various SDGs and their indicators. Results reveal that the Dam with cold in winter and hot in summer climate conditions observed a most feasible site with a Levelized cost of energy (LCOE) of $0.047/kWh and a Net present value (NPV) of million$1.7705, respectively. In contrast, a Dam with mild cold climate conditions proves the least feasible site with LCOE of $0.057/kWh and NPV of million$1.0256, respectively. Similarly, the former Dam saved 20.50% higher CO2 emissions as compared to the latter, as well as required hectares of forest absorbing carbon. A comparative analysis observes a capacity factor of 22% and a performance ratio (PR) of 5%–10% higher as compared to solar photovoltaic (SPV) for dams with extreme weather

A Forensic Scheme for Revealing Post-processed Region Duplication Forgery in Suspected Images

Recent researches have demonstrated that local interest points alone can be employed to detect region duplication forgery in image forensics. Authentic images may be abused by copy-move tool in Adobe Photoshop to fully contained duplicated regions such as objects with high primitives such as corners and edges. Corners and edges represent the internal structure of an object in the image which makes them have a discriminating property under geometric transformations such as scale and rotation operation. They can be localised using scale-invariant features transform (SIFT) algorithm. In this paper, we provide an image forgery detection technique by using local interest points. Local interest points can be exposed by extracting adaptive non-maximal suppression (ANMS) keypoints from dividing blocks in the segmented image to detect such corners of objects. We also demonstrate that ANMS keypoints can be effectively utilised to detect blurred and scaled forged regions. The ANMS features of the image are shown to exhibit the internal structure of copy moved region. We provide a new texture descriptor called local phase quantisation (LPQ) that is robust to image blurring and also to eliminate the false positives of duplicated regions. Experimental results show that our scheme has the ability to reveal region duplication forgeries under scaling, rotation and blur manipulation of JPEG images on MICC-F220 and CASIA v2 image datasets

An environmental‐friendly green energy system with a real wind speed prediction based on innovative hierarchical forecast error correction model

Precise forecasting of wind speed is an important technology to permit the reliable and efficient operation of sustainable energy system. Here, the authors offer an effective windspeed prediction (EWSP) technique based on advanced forecast error correction model(AFECM). Ramapuram, Chennai is selected to fit the wind-energy-based systems and ENNORE thermal power station, Chennai is selected to decrease the carbon footprints. In the proposed technique, the error correction model is made to produce the final forecast. The proposed wind speed prediction based on innovative hierarchical forecast error correction model reveals that with the proposed AFEC+MSVM technique, the hourly aver-age RMSEs, MADs, MSEs and MAPEs in Delivery 24 are decreased by 2.277%, 1.012%,0.234%, and 1.245 % as compared to the normal SVM technique, while with AFEC+SVM method, average errors in RMSEs, MADs, MSEs and MAPEs in Delivery-24 are reduced by 3.385%, 2.056%, 1.956% and 2.546% as compared with the normal SVM technique, whereas the forecasting errors with AFEC+BP method, the middling errors in RMSEs, MADs, MSEs and MAPEs in Delivery-24 are decreased by 2.867%, 1.654%, 1.834% and2.298%, compared with simple BP method. The study displays that 1,485,550 kg CO2emission is decreased from the ENNORE thermal power plant.Deanship of Scientific Research, Majmaah University, Grant/Award Number: R-2021-27

Prospects of Hybrid Energy in Saudi Arabia, Exploring Irrigation Application in Shaqra

Dynamics in rainfall patterns due to climate change are posing a threat to crop production globally. The core issue of food security is expected to intensify, and improving crop yield using motorized power irrigation mechanisms can help in curtailing the impact of drought and changing weather patterns to meet the crop water requirement. To meet the energy demand of irrigation systems, this paper explores the use of hybrid energy sources, i.e., wind and solar energy, taking Shaqra Saudi Arabia as case study. This paper presents a systematic case study that evaluates crop water requirements for 3 different crops using the United Nations Food and Agriculture Organization’s software CROPWAT 8.0 and converts the water requirement into energy demand to design the water pumping system. The energy requirement water pumping system is used to design a hybrid energy system using HOMER PRO 3.14.4 that can reliably meet the energy demand. The results suggests that, contrary to the common consideration in Saudi Arabia, a hybrid of wind and solar energy proves to be more cost effective and yields a higher amount of energy. The results suggest that a significant reduction in cost can be achieved with a hybrid energy system as compared to a solar PV system only