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Reservoirs are major indicators of sustainable socio-economic development, agriculture and energy. This study focused on genetic algorithm based optimization of rule curves for maximizing the hydropower and associated benefits through cascade reservoirs. Optimization has been carried out using RESOOSE model for maximizing hydro-power, irrigation and evacuation of sediment from multipurpose Diamer Basha and Terbela Reservoirs on Indus River in Pakistan. The best methods and values of Genetic Algorithm computed through sensitivity analysis were tournament selection method with 2 teams, population size 288, single point crossover method with crossover probability 0.8 and adapt feasible mutation method. The policy equations on storage, outflows and hydropower for the cascade reservoirs in series were formulated. The maximum annual overall benefits were 3380 Million US$ for multi-objective optimization of joint operation of Terbela and Diamer Basha Reservoirs, where hydropower was major contributor among all the associated benefits with highest annual benefits of 2724.7 Million US$. The results demonstrate that hydropower has been optimized along with maximization of the associated benefits. The optimized rule curves of the cascade reservoirs developed in the study have enhanced the overall benefits for achieving SDGs of zero hunger, affordable clean energy, economic growth and water availability. [ABSTRACT FROM AUTHOR]

Recently, there has been an urgent need to fully implement renewable energy sources to realise green energy transitions and combat environmental pollution. This study uses a benchmark estimation model to analyse the links between green economic growth, green financing, and green energy from 2010 to 2020 and green energy advancement in China. Within the context of renewable energy, scholars have investigated various, unequal, and mediating influence connections. According to the extant literature, green economic expansion and green finance are significantly linked with renewable energy, but with diverse influences in various types of renewable technology and in various regions. The effect of green growth in the economy on green energy is non-linear, while green finance is coherent. Green technological advancement is efficiently facilitates green productivity expansion and green energy, and the investment impact is partially mediated. This study contributes significantly to the formulation of several practical initiatives to strengthen the green energy sector and facilitate sustainable growth. The results indicate that it is essential to maximise the potential of green economic activity to advance the green energy sector through the full utilisation of green accomplishments in their transformed forms. • Urgent need for renewable energy: Implementing renewables for green transitions. • Linking green growth, financing, and energy: Analyzing connections in China. • Diverse influences on renewables: Varied impacts by region and technology. [ABSTRACT FROM AUTHOR]

Countries in the global South, or developing and emerging economies, are experiencing rapid economic growth, and increased economic integration with other countries in the global South, including trade. Some analysts have raised concerns that such South-South trade might encourage the use of outdated conventional energy technologies, and lock developing countries into high carbon growth paths. Here, trade data from the UN Comtrade database is analyzed with a gravity model of trade. Results show that levels of clean energy technologies in South-south trade were relatively low up until the first half of the 2010's, but that these are entirely comparable to North-North or other trade flows in recent years. The analysis thus finds no evidence to support concerns that South-South trade might encourage high carbon development. South-South trade contains particularly high levels of solar PV, hydropower, and electric two-wheeler technologies, whilst exporters in the global North are more competitive in markets for wind power equipment and electric vehicles. Trade in electric vehicles is the fastest growing class of clean energy technologies, and the dominance of Northern countries in their exports may mean that South-South trade could, in the foreseeable future, once again lag behind in levels of clean energy technologies. • UN Comtrade data is used to identify shares of clean energy tech in international trade. • Trade between countries in the global South is compared with other trade flows. • South-South trade contains as much clean energy technologies as other trade flows. • South-South trade has high levels of PV, hydropower, and electric two-wheelers. • South-South trade has low levels of wind power and electric vehicles. [ABSTRACT FROM AUTHOR]