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GEP (Generation Expansion Planning) is one of the most complex tasks in which planning is done to find the best possible distinct solutions to install new generating units to meet future load demands. This paper uses the Low Emission Analysis Platform (LEAP) software environment to analyse the GEP for the AP Power sector from 2021 to 2050. In recent years, the AP power sector has faced several issues, such as frequent service cuts due to power shortages. In this paper, five scenarios such as Business As Usual (BAU), Low Demand Growth (LDG), High Demand Growth (HDG), Least Cost Optimization (LCO) and Climate Mitigation Scenarios, have been analysed with environmental, technical, and economic parameters. This study has estimated the total environmental emissions and total cost of all scenarios. At present, Andhra Pradesh has a total installed capacity of 25.4 GW. The best scenarios can be selected based on environmental impact, cost-effectiveness, efficiency, and reliability. The results show that the LDG scenario will be an optimal choice for AP due to the state's economic crisis, and the government should also focus on energy conservation and limit demand growth to 4.5%. While presenting a general GEP, the study presents comprehensive system performance scenarios from which planners can choose. • Making a generation expansion planning • Making a sustainable environment • Presented a good solution for power generation • Analysed the total environmental emissions • Analysed the energy demands. [ABSTRACT FROM AUTHOR]

In this article, the Improved Mayfly Algorithm (IMA) is used as an upgraded form of the Mayfly Algorithm (MA), featuring simulated binary crossover and polynomial mutation operators replacing the arithmetic crossover and standard distribution mutation operators of the MA. With MA, IMA's achievements and significance are acknowledged. The algorithms achieve a final best solution for the investigated objective functions of the optimal power flow problem in a deregulated electrical power market under different load conditions. The overall load of the power system varies between half of the base load (-50%) and twice the base load (+100%). The investigated objective functions are associated with the financial worth of generators, dissipation of active power in transmission lines, variation of voltage magnitudes at the system bus, and voltage stability index at the load bus of the power system networks. The result achieved by GA, PSO, MA and IMA are attained using the IEEE-30 bus test system in a deregulated power system. Investigations are conducted on the best solutions for each objective function; offers of generators and bids of loads; generator sales and load purchases; and system revenues associated with different load scenarios. The simulated outcomes have confirmed that IMA would triumph over GA, PSO and MA. [ABSTRACT FROM AUTHOR]