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A substantial level of significance has been placed on renewable energy systems, especially photovoltaic (PV) systems, given the urgent global apprehensions regarding climate change and the need to cut carbon emissions. One of the main concerns in the field of PV is the ability to track power effectively over a range of factors. In the context of solar power extraction, this research paper performs a thorough comparative examination of ten controllers, including both conventional maximum power point tracking (MPPT) controllers and artificial intelligence (AI) controllers. Various factors, such as voltage, current, power, weather dependence, cost, complexity, response time, periodic tuning, stability, partial shading, and accuracy, are all intended to be evaluated by the study. It is aimed to provide insight into how well each controller performs in various circumstances by carefully examining these broad parameters. The main goal is to identify and recommend the best controller based on their performance. It is notified that, conventional techniques like INC, P&O, INC-PSO, P&O-PSO, achieved accuracies of 94.3, 97.6, 98.4, 99.6 respectively while AI based techniques Fuzzy-PSO, ANN, ANFIS, ANN-PSO, PSO, and FLC achieved accuracies of 98.6, 98, 98.6, 98.8, 98.2, 98 respectively. The results of this study add significantly to our knowledge of the applicability and effectiveness of both AI and traditional MPPT controllers, which will help the solar industry make well-informed choices when implementing solar energy systems. [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]

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]

Pakistan's energy sector has been in crises since 2005. Major reasons behind crises include huge dependence on imported fossil assets and lack of integrated energy planning. These crises have challenged energy sector and require special attention to solve them through proper planning using energy modeling tools. In this research, Long-range Energy Alternatives Planning System (LEAP) is used for modeling Pakistan's energy sector for period 2020 to 2070. Energy demand, production and CO 2 emissions are forecasted under the Progressive (PROG) and Renewable Energy Sources, Technologies and Efficiency Measures (RESTEM) scenarios by considering techno-economic parameters. Results of this study suggest that transition towards defossilized energy system is possible through RESTEM scenario. Model results shows that energy demand for 2020 is 112 TWh and for 2070 is 2684 TWh. On supply side, energy production for 2020 is 114 TWh and for 2070 it is 2696 TWh. Share of renewable sources in total energy mix is increased from 38.5% in 2021 to 59.1% in 2070 and share of non-renewable sources is reduced from 53.1% in 2021 to 40.9% in 2070. CO 2 emissions are also reduced from 153,083.7 million tons to 56,152 million tons under RESTEM scenario. [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. In this regard, the developments have not been done over the past two decades on green energy in Pakistan and in general, the representation of renewable sources especially biomass feedstock supply such as agriculture residue, forest residue, municipal waste and animal waste for green energy transition pathways is limited. Using the Low Emissions Analysis Platform (LEAP®) software, path for green energy transition is analyzed in Pakistan by incorporating the biomass feedstock under the ongoing and sustainable energy scenarios from 2022 to 2050. Results showed that the bioelectricity production will increase from 18.73 TWh (in the ongoing scenario) to the 265.20 TWh (in the biomass based sustainable energy scenario) till 2050. Furthermore, the development of biomass plants would help in reducing the CO 2 emissions from 138.47 million metric tonnes in the current scenario to 8.71 million metric tonnes in the sustainable energy scenario by 2050. This study will provide the fundamental data and aid the policy makers and other stakeholders to shift toward developing renewable and sustainable energy systems in Pakistan. • Role of biomass in energy mix is significant for Pakistan. • Pakistan is producing 560.19 million tons of biomass resource annually. • Bioelectricity production will increase from 18.73 to 265.20 TWh using biomass till 2050. • LEAP® model is developed for sustainable climate change. • Bioelectricity will reduce CO 2 emissions from 138.47 to 8.71 million metric tonnes. [ABSTRACT FROM AUTHOR]