Calculation and Monte Carlo uncertainty analysis of the levelized cost of electricity for different energy power generation in the smart grid under time scales

Multiple power systems, encompassing both fossil fuels and renewable energy sources, play a vital role in the supply side of the smart grid. While research on smart grid electricity pricing has predominantly focused on intelligence and forecasting, there is a notable paucity of studies addressing the fundamental pricing principles and long-term cost management strategies for electricity. The aim of this paper is to propose a foundational framework for estimating energy generation costs, focusing on both fossil fuel and renewable energy sources within the context of smart grid electricity pricing. To assess approximate cost changes over time, the study calculates the Levelized Cost of Electricity (LCOE) utilizing Life Cycle Assessment (LCA) and Life Cycle Cost (LCC) methodologies, which account for economic and environmental impacts. The findings indicate that, assuming a 20-year time horizon, the final levelized costs for each type of power plant are as follows: coal power plant at 96 USD/MWh, gas power plant at 111 USD/MWh, nuclear power plant at 86 USD/MWh, hydroelectric power plant at 87 USD/MWh, solar power plant at 71 USD/MWh, and wind power plant at 69 USD/MWh. Furthermore, the analysis uses Monte Carlo analysis to explore uncertainties associated with carbon prices, the Weighted Average Cost of Capital (WACC), capital costs, and raw material prices, which offers a strategic approach for government institutions to implement regulatory policies of the energy power market. • Total Life Cycle Cost (TLCC) covering economic and environmental costs. • Comparison of renewable energy and fossil energy power generation. • Levelized cost of electricity on different time scales. • Multiple factors affecting tariff cost volatility.