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• W3211702016 abstract "Favourable renewable energy policies led to a higher proportion of renewable energy in the country’s entire energy generation. However, these regulatory affairs caused the lower capacity utilisation factor of thermal power stations. It is not prudent to burden the thermal stations by enforcing ramp rates during peak hours as this would cause serious operational issues. Hence, further renewable additions must be supported by battery-energy storage systems (BESS) to meet the grid ramping requirements. BESS being quite expensive and require heavy maintenance, municipal solid waste-based waste-to-energy (WtE) plants play a crucial role in enhancing grid reliability under a high renewable energy (RE) environment. In this paper, the potential of four renewable energy technologies, such as floating solar, bifacial rooftop, wind energy conversion system, and WtE plant, are evaluated for a smart city, Visakhapatnam, India. This paper identifies a total of 439 MW of RE potential in the selected location. Mutation-enabled adaptive local attractor-based quantum behaved particle swarm optimisation (ALA-QPSO), supported by the combination of BESS and WtE plant, and is applied to obtain the optimal configuration of photovoltaic (PV) and wind energy conversion system (WECS) by minimising the techno-economic objectives of a municipal body. The results are compared with four variants of differential evolution. The results show that for an optimal set of BESS and hybrid renewable energy sources (HRES), the grid can offer better reliability with the presence of the WtE plant. The obtained optimal configuration results in a levelized cost of US $ 0.0539, high reliability with a loss of power supply probability of 0.049%, and reduced battery degradation with minimal life cycle loss of 0.048. The municipality requires a total investment of US $ 40.5 M, a significant part of which can be met by acting as a renewable energy service company between the rooftop owners and the distribution companies." @default.
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• W3211702016 date "2022-02-01" @default.
• W3211702016 modified "2023-10-18" @default.
• W3211702016 title "Multi-objective mutation-enabled adaptive local attractor quantum behaved particle swarm optimisation based optimal sizing of hybrid renewable energy system for smart cities in India" @default.
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• W3211702016 doi "https://doi.org/10.1016/j.seta.2021.101689" @default.
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