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Nowadays, electricity theft is a major issue in many countries and poses a significant financial loss for global power utilities. Conventional Electricity Theft Detection (ETD) models face challenges such as the curse of dimensionality and highly imbalanced electricity consumption data distribution. To overcome these problems, a hybrid system Multi-Layer Perceptron (MLP) approach with Gated Recurrent Units (GRU) is proposed in this work. The proposed hybrid system is applied to analyze and solve electricity theft using data from the Chinese National Grid Corporation (CNGC). In the proposed hybrid system, first, preprocess the data; second, balance the data using the k-means Synthetic Minority Oversampling Technique (SMOTE) technique; third, apply the GTU model to the extracted purified data; fourth, apply the MLP model to the extracted purified data; and finally, evaluate the performance of the proposed system using different performance measures such as graphical analysis and a statistical test. To verify the consistency of our proposed hybrid system, we use three different ratios for training and testing the dataset. The outcomes show that the proposed hybrid system for ETD is highly accurate and efficient compared to the other models like Alexnet, GRU, Bidirectional Gated Recurrent Unit (BGRU) and Recurrent Neural Network (RNN). [ABSTRACT FROM AUTHOR]

Autonomous vehicles can transform the transportation sector by offering a safer and more effective means of travel. However, the success of self-driving cars depends on their ability to navigate complex road conditions, including the detection of potholes. Potholes pose a substantial risk to vehicles and passengers, leading to potential damage and safety hazards, making their detection a critical task for autonomous driving. In this work, we propose a robust and efficient solution for pothole detection using the "you look only once (YOLO) algorithm of version 8, the newest deep learning object detection algorithm." Our proposed system employs a deep learning methodology to identify real-time potholes, enabling autonomous vehicles to avoid potential hazards and minimise accident risk. We assess the effectiveness of our system using publicly available datasets and show that it outperforms existing state-of- the-art approaches interms of accuracy and efficiency. Additionally, we investigate different data augmentation methods to enhance the detection capabilities of our proposed system. Our results demonstrate that YOLO V8-based pothole detection is a promising solution for autonomous driving and can significantly improve the safety and reliability of self-driving vehicles on the road. The results of our study are also compared with the results of YOLO V5. [ABSTRACT FROM AUTHOR]

The energy demand in Pakistan is escalating owing to the growing population, rapid urbanization, and industrial growth. Therefore, the development and execution of Energy Efficiency and Conservation (EE&C) policies and initiatives are critical for the Government in order to enhance energy efficiency and to address the country's increasing energy demand. In this study, the Low Emission Analysis Platform (LEAP) tool is used to develop and analyze the effects of load control, energy efficiency, and conservation-based measures. Based on the policy analysis and energy consumption patterns, macro-economic modeling has been undertaken using LEAP for the study period 2020-2050. The two scenarios developed are Business-As-Usual (BAU) and Demand-Side-Management (DSM). The model results forecast 1910.2 TWh electricity demand by 2050 under the BAU scenario, with an average annual growth rate of 5.5%, which is eighteen times greater than energy demand in the base year. The sustainable electricity generation path followed under the DSM scenario ensures a lower demand of 1597.5 TWh and an average annual growth rate of 4.5%. This scenario will reduce energy use by 16% compared to the BAU scenario. Therefore, it is proposed that policy may be envisaged using infrastructural and consumer engagement approaches to encourage DSM development in Pakistan. The proposed LEAP model can be used to undertake the supply policy selection and demand assumption for future power production in Pakistan. [ABSTRACT FROM AUTHOR]

Climate change threats demand unprecedented economic shifts around the world, including a fundamental transformation of the global energy system. An energy transition is underway in most regions, predominantly in the power sector. This research depicts the energy transition pathway for achieving 100% renewable energy systems through bioenergy in Pakistan. The growth rate of 20%, 30%, and 40% in biomass projects were considered for the study period 2023 to 2053 using the Low Emissions Analysis Platform (LEAP) software. It presents a technology‐rich, multi‐sectoral and cost‐optimal energy transition pathway for limiting global mean temperature below 1.5°C. The results revealed that Pakistan's electricity generation undergoes a rapidly evolving transition from predominantly fossil fuels 62.1% in 2023 to 81.3% renewables in 2053, and entirely zero CO2 emissions by 2060. Hydro source is costly, wind and solar sources are seasonal so biomass emerges as the major electricity supply source in a cost optimal energy transition of Pakistan. Share of biomass is increasing from a mere 0.81% in 2023 to around 9.44% by 2053 under the 20% growth rate, which then increase to 39.67% by 2053 under the 30% growth rate and further increases to 78.33% by 2053 under the 40% growth rate. Pakistan contributes 0.8% of the global carbon footprint, but we are among the 10 most climate‐stressed countries on the planet in 2023 so this study helps to reduce cumulative CO2 emissions from 151.63 million metric tons to 8.90 million metric tons from 2023 to 2053 across the power, heat, transport, and desalination sectors. [ABSTRACT FROM AUTHOR]

This study suggested a plan for making low carbon society (LCS) in Pakistan by 2050. Low Emissions Analysis Platform is used for simulation the entire energy system and forecasted the future CO2 emissions in relation to the use of renewable and fossil fuel resources under the two scenarios namely high carbon society (HCS) and LCS. Additionally, marginal abatement cost of future energy system is forecasted for the study period 2022–2050. The results revealed that, 100% de‐carbonization is possible under the LCS scenario. Further, this scenario suggested that 1123.15 TWh units of green energy are generated to meet the total energy demand of 966.05 TWh till 2050. Biomass has greater share of 380.16 TWh followed by wind 370.67 TWh, solar 358.74 TWh, and hydro 13.58 TWh respectively. CO2 emissions are reduced from 151.63 million metric tons in HCS scenario to 8.90 million metric tons in LCS scenario till 2050 but cost is increased from 46.36 billion US dollar in HCS scenario to 546.49 billion US dollar in LCS scenario for the year 2050. The technique can also be applicable to the developing, under‐developed and developed nations around the globe. [ABSTRACT FROM AUTHOR]

Due to the recent climate change, organizations all over the globe are developing plans for reducing carbon emissions by developing clean energy technologies and energy efficient devices. However, the path for transition to green energy system is still unclear and in general, the representation of green energy supply for transition pathways is limited. Therefore, this study outlines a plan for getting Swedish energy sector completely carbon neutral by 2050. The approach can also be applicable to the majority of nations worldwide. Computer based simulations are performed on Energy PLAN software for making clean, green and sustainable energy system that can balance every component of entire energy system during the study period 2022 to 2050. This study takes into account the sustainable use of renewable sources for all economic sectors as well as the interchange of energy with nearby nations under the two scenarios. Additionally, the energy system works in tandem with other industries to create a fully carbon-free environment. The results revealed that, 50% de-carbonization is possible till 2035 and 100% de-carbonization is possible till 2050. This enables a discussion of how ambitious 10-year goals might serve as a first step toward the mid-century elimination of fossil fuels from the energy sector. [ABSTRACT FROM AUTHOR]

The Government of Pakistan has established clean energy transition goals in the national Alternative and Renewable Energy (ARE) Policy. The goal of this policy is to increase the 30% capacity of green energy in total energy mix by 2030. In this regard, the aim of this study is to develop a de-carbonization plan for achieving net zero emissions through the deployment of a green energy system for the period 2021 to 2040 by incorporating the ARE policy targets. The Low Emissions Analysis Platform (LEAP®) software is used for finding the unidirectional causality among gross domestic product, population within the country, energy demand, renewable energy production and CO2 emissions for Pakistan. The results revealed that energy production of 564.16 TWh is enough to meet the energy demand of 480.10 TWh with CO2 emissions of 22.19 million metric tons, having a population of 242.1 million people and GDP growth rate of 5.8%, in the year 2040 in Pakistan. The share of green energy production is 535.07 TWh, which can be utilized fully for meeting energy demand in the country, and almost zero emissions will produce till 2040. CO2 emissions produced by burning natural gas were 20.64 million metric tons in 2020, which then reduced to 3.25 million metric tons in 2040. CO2 emissions produced by burning furnace oil are also reduced from 4.19 million metric tons in 2020 to 2.06 million metric tons in 2040. CO2 emissions produced by burning coal were 24.85 million metric tons in 2020, which then reduced to 16.88 million metric tons in 2040. Energy demand is directly related to the population and GDP of the country, while renewable utilization is inversely proportional to carbon emissions. The declining trend of carbon emissions in Pakistan would help to achieve net zero emissions targets by mid-century. This technique would bring prosperity in the development of a clean, green and sustainable environment. [ABSTRACT FROM AUTHOR]

Fossil fuel-based energy systems are mostly used for supplying energy that creates negative impacts on the environment, so in this study, the development of a 100% renewable energy system is evaluated for Pakistan for sustainable climate change. This study modeled three scenarios, namely, ongoing (ONG), energy saving policy (ESP), and green energy policy (GEP) scenarios using low emission analysis platform (LEAP) software for the study period 2022 to 2050 for Pakistan. The results revealed that a 100% renewable energy supply could be achieved through the GEP scenario. Model results show that the share of renewable sources in the total energy mix is 1117.08 TWh and non-renewable sources contribute only 18.12 TWh to meet the energy demand of 966.05 TWh until 2050. Non-renewable production leads to the generation of 8.85 million metric tons of carbon emissions, which is too low compared with the 135.47 million metric tons under the ONG scenario. The USD 1482.46 billion investment cost required for adding renewable energy capacity until 2050 is too high as compared with the USD 46.80 billion under the ONG scenario. Energy demand and production requirements are reduced by 34.18% under the ESP scenario until 2050. This approach can also be applicable to the majority of nations worldwide. [ABSTRACT FROM AUTHOR]

Thar desert is located in south-east Pakistan carries 175 billion tons of coal and is the biggest coalfield in Asia. In this paper mathematical framework is developed for the accurate estimation of power production from the available Thar coal capacity. Annual TWh possible energy production the period 2020 to 2040 followed by detailed analysis of capacity factor and Maximizing the share percentage of coal in total energy mix at least 40% by 2040 is presented. The findings reveal that Thar coal has the capability of producing 100,000 MW power up to the next 250 years. The energy generation for the years 2020, 2032, and 2040 is calculated 744 TWh per year, 700 TWh per year, and 665 TWh per year respectively and it produces negligible negative impacts on the environment. The long-term energy planning presented in this paper would attract foreign investment and Pakistan's energy needs would be fulfilled for sustainable development of the country. [ABSTRACT FROM AUTHOR]

Authors used Long-range Energy Alternatives Planning (LEAP) model in this paper to develop and analyze future energy demand, production and CO2 emissions in Pakistan from 2020 to 2040. The model is developed based on Governmental Progressive Scenario (GPS), which forecasts sector wise (agriculture, commercial, domestic, industrial and others) energy demand of the country, and analyzes future energy supply pattern based on the domestic energy sources like RLNG, hydro, coal, natural gas, nuclear, furnace oil and renewable (wind, solar, biomass). The results of this study show that the growth rates of future energy supply and demand are 18% and 11% respectively. CO2 emissions based on future energy production are also forecasted from 2020 to 2040 which is showing declining trend due to the use of cleaner technologies in the future. The total cost of energy projects is also forecasted based on net present value at a discount rate of 4%, 8% and 12%. It is found that energy projects cost will be 50% less at discount rate of 8%. The results of this study are useful in making long term energy and environmental planning and policy formulation in Pakistan. [ABSTRACT FROM AUTHOR]

The rapid increase of the electrical power demand gave rise to many challenging situations for power system control engineers as the transmission lines are operating at their maximum capacity in most developing economies. To solve this, Distributed Generation (DG), i.e. the generation of electrical power in a distribution network that provides clean energy, is gaining popularity. There are several challenges the protection of distribution networks faces after DG installation, such as variations in short circuit levels, protection blinding, reverse power flow, protection coordination, change in fault impedance, recloser-fuse coordination, selectivity, unsynchronized reclosing, false tripping, etc. In this paper, an IEEE 13-Bus System Radial Distribution System is simulated using Electrical Transient Analyzer Program (ETAP), various scenarios of DG placement are considered, their impact on the protection system is analyzed, and different techniques are proposed to minimize the effect on protection coordination. The use of directional relays, current limiting reactors, and small magnitude DGs is tested and analyzed. The way this effect varies by changing the location of DG is also analyzed. [ABSTRACT FROM AUTHOR]

This paper presents an energy plan for harnessing electrical power from hybrid energy resources, including biomass and solid waste, through hybrid technologies for microgrid development to overcome the current energy crisis and provide future sustainable electricity pathways for a developing country. Biomass and solid waste were collected from different dumping sites in Pakistan and were tested for their calorific value, which was found to be 6519Kcal/Kg. The total power was calculated based on this calorific value and it was found that there is a potential of total 11,989.5GW of power generation. Thus, hybrid energy resources are suitable for harnessing electrical energy through hybrid technologies. Different hybrid systems were examined for these resources and the gasification technique is finally proposed as the most suitable method for producing energy from biomass and solid waste resources in Pakistan. This technique is also found to be economically feasible for processing all kinds of waste. [ABSTRACT FROM AUTHOR]