Case Problem and mathematical Draft Model is required for the following research topic:

Proposal Energy Modelling: Methods and Applications Energy modeling is a formidable tool for comprehending and forecasting the behavior of energy systems as well as for evaluating the possible effects of various technological and policy alternatives. In a variety of contexts, including energy policy, energy planning, and energy investment, it may be used to guide decisions. Planning an energy system is only one of the many methodologies and uses for energy modeling, which also includes simulation modeling and optimization modeling. Applications include energy policy analysis, analysis of energy investments, and improvements to energy efficiency. Decision-makers may create more sustainable and effective energy policies and systems that satisfy societal and environmental demands by combining a variety of approaches and applications.

Methodology Review Introduction Energy transition modeling is a powerful tool that enables decision-makers to analyze the potential impacts of different energy policies and technologies on the energy system. This methodology review will explore the different methods and techniques used in energy transition modeling, including how it is modeled, how it is calculated, and why certain metrics such as NPW are used. Additionally, I will explain why I prefer to use this method and provide examples of how it has been applied in real-world scenarios. Modeling energy transitions is essential for grasping the feasibility and implications of transitioning to healthier, more sustainable energy systems. It entails evaluating the technical, economic, and environmental effects of switching from one energy source to another using a variety of analytical techniques and approaches. The two basic groups of energy transition models are top-down and bottom-up. Top-down models examine the overall energy system and how various policies, technologies, and behaviors interact to bring about change, whereas bottom-up models examine the specifics of particular technologies and systems to evaluate their costs, advantages, and viability. The study topic, the data that is available, and the amount of detail that is sought all influence the model that is selected. To fully comprehend the viability and effects of switching to more sustainable energy sources, energy transition models are crucial. System dynamics, optimization, and simulation models are just a few of the techniques employed. The system dynamics technique and its advantages will be discussed in this article. To represent complex systems, including energy systems, system dynamics uses feedback loops, stocks, and flows. It is employed to examine the interactions between various energy sources, technologies, and regulations to comprehend how they impact the system. Understanding the complexity and dynamics of energy systems requires the use of system dynamics. It enables the modeling of intricate interactions and feedback loops, which can assist stakeholders and policymakers in comprehending the effects of various technologies and policies on the system as a whole. The modeling of energy system uncertainties, such as shifts in demand, fluctuating fuel costs, and environmental restrictions, is made possible by system dynamics. This can aid in understanding the possible risks and possibilities linked to various energy transition scenarios by stakeholders and policymakers. Through the use of system dynamics, stakeholder opinions and feedback can be incorporated into the modeling process, which can make the resulting energy transition 10 scenarios more plausible and realistic. Stakeholders with varied viewpoints and goals on energy transitions include lawmakers, business representatives, and members of the community. System dynamics makes it possible to examine the long-term effects and unexpected effects of energy transitions, which may result in growing reliance on energy sources or technologies. This can aid in the development of measures by stakeholders and governments to lessen them. System dynamics is an open and simple way of modeling the energy transition that enables the easy explanation of complicated scenarios to many stakeholders. This can aid in facilitating conversations and negotiations, resulting in better-informed and more efficient decisionmaking. Modeling Approach Energy transition modeling involves the use of various mathematical models that simulate the energy system's production, consumption, and distribution. These models use input data on the current energy system and assumptions about future trends and policies to simulate the impact of different energy transition scenarios. Two commonly used modeling approaches in energy transition modeling are the integrated assessment model (IAM) and the system dynamics model (SDM) . The IAM combines models of the energy system with models of the economy and the environment to evaluate the tradeoffs between different energy transition strategies and identify optimal paths for achieving specific policy objectives. The SDM simulates the dynamic behavior of complex systems over time and analyzes the interactions between different components of the energy system, identifying feedback loops and other nonlinearities that can impact the effectiveness of energy transition policies. Calculation of Metrics The calculation of metrics in energy transition modeling involves the use of various key performance indicators (KPIs) that can help quantify the potential benefits and costs of different energy transition scenarios. These metrics are used to compare different energy policies and technologies and identify the most cost-effective and environmentally sustainable strategies. Two commonly used KPIs in energy transition modeling are the levelized cost of energy (LCOE) and the net present value (NPV). LCOE is used to compare the cost of producing different types of energy, such as renewable versus fossil fuels, and to identify the most cost-effective options for meeting energy demand. NPV is used to calculate the present 11 value of future cash flows and is often used to evaluate the profitability of investment opportunities. In energy transition modeling, NPV is used to calculate the net present value of different energy transition scenarios and identify the most economically viable options . Energy transition models must account for several factors, including capital expenses, operational expenses, fuel expenses, and environmental externalities. The initial expenses of constructing or installing energy infrastructure are referred to as capital costs; continuing maintenance costs are referred to as operational costs; and fuel prices vary depending on the energy source. Environmental externalities are the expenses associated with pollution and other harmful effects on the environment and the general public's health. Policymakers and other stakeholders that want to know if switching to more sustainable energy sources is feasible and what the effects will be should consider modeling energy transitions. The advantages and costs of various scenarios for the energy transition are quantified using key performance indicators (KPIs). The methodology for calculating KPIs in energy transition modeling will be covered in this essay. A popular KPI in energy transition modeling is the Levelized Cost of Energy (LCOE). When operational, finance, and capital expenditures are all taken into consideration, it represents the typical cost of producing a unit of energy during a power plant. The whole lifetime costs of the power plant are divided by the plant's overall lifetime energy production to determine the LCOE. A KPI used in energy transition modeling is the net present value (NPV). It is the difference between the benefits and costs of an energy transition project at their respective present values, considering the time value of money. NPV is calculated by subtracting the present value of the anticipated cash outflows (costs) from the present value of the anticipated cash inflows (benefits). In energy transition modeling, the internal rate of return (IRR) is a key performance indicator (KPI) that is used to evaluate project returns and assess a project's financial viability. The present value of anticipated cash inflows is set to equal the present value of anticipated cash withdrawals, and the discount rate is computed to make this equation true in order to calculate IRR. Calculating carbon reductions, energy savings, and other environmental and social effects of various energy transition scenarios is a part of energy transition modeling. Utilizing techniques like life cycle assessment (LCA) and environmental impact assessment (EIA), these effects are frequently quantified. Energy transition modeling frequently uses sensitivity analysis, which includes changing important input parameters to see how robust the outcomes are, to take this uncertainty into consideration. Modeling the energy transition 12 depends heavily on the facts and assumptions that are employed. The quality of the data and the suitability of the assumptions affect the findings' accuracy and dependability. As a result, it's critical that stakeholders have access to the data and underlying assumptions utilized in energy transition modeling, as well as for those processes to be accessible. Why NPW is used. The net present value of a project is a key metric used in energy transition modeling because it provides decision-makers with an estimate of the project's profitability. NPV takes into account the time value of money, which means that future cash flows are discounted to their present value. This allows decision-makers to compare the profitability of different projects over time and account for the fact that money received in the future is worth less than money received today . Why Everything is taken Annually. In energy transition modeling, everything is taken annually because it provides decision-makers with a standardized way of comparing different energy transition scenarios. By calculating the annual costs and benefits of different scenarios, decision-makers can compare them directly and identify the most cost-effective options. Annual calculations also allow decision-makers to account for changes in technology costs, energy prices, and other factors that can impact the profitability of energy transition projects over time . Conclusion As an AI language model, I don't have preferences, but as a tool used by researchers and decision-makers, energy transition modeling offers several advantages. One of the primary advantages is that it allows decision-makers to evaluate the potential impacts of different energy policies and technologies before implementing them. This can help reduce the risk of making costly mistakes and enable decision-makers to identify the most cost-effective and environmentally sustainable strategies. Energy transition modeling also provides decisionmakers with a standardized way of comparing different energy transition scenarios and identifying the most cost-effective options. By using a common set of KPIs and modeling techniques, decision-makers can ensure that their analyses are comparable and easily understood by others