4.8 Article

A sustainable rural electrification based on a socio-techno-economic-environmental-political microgrid design framework

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ENERGY & ENVIRONMENTAL SCIENCE
卷 15, 期 10, 页码 4213-4246

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ROYAL SOC CHEMISTRY
DOI: 10.1039/d2ee01175a

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This study proposes a sustainable microgrid design framework that utilizes locally accessible energy sources for rural electrification. The framework combines social-political evaluation, techno-market analysis, feasibility analysis, and environmental-economic analysis to determine the optimal electrification solution.
This work proposes a sustainable socio-techno-economic-environmental-political (STEEP) microgrid design framework utilizing locally accessible energy sources for rural electrification for developing/least-developing countries. In the proposed STEEP microgrid framework, four layers of the sub-design process are combined into a single comprehensive design process to find appropriate electrification solutions based on sustainable indices. This study combines various energy sources and storage technologies to find the best viable solution. The first stage of the proposed framework deals with a socio-political evaluation of different energy and storage technologies using decision analysis based on sustainable performance indicators considering variant decision scenarios. In lieu of that, an enhanced decision-making model is proposed to accommodate multiple performance indices with multi-variable scenarios. In the second level of the design process, a techno-market analysis is introduced to check the market suitability of various alternatives for microgrid design. A detailed feasibility analysis is then performed to obtain optimal solutions considering multiple architectures in the subsequent design stage. Furthermore, a control algorithm is also introduced for power management, considering annual load growth at the tertiary level. In the fourth stage of the framework, an extensive environmental and economic analysis is performed using multi-criteria decision making (MCDM) models. Finally, a case study is introduced to determine the optimal electrification solutions based on specific characteristics and requirements for an unelectrified remote community. Various detailed system behavioural results based on yearly, monthly and hourly power profiles with seasonal variations considering annual load growth are also illustrated to show the performance of the optimal microgrid solution.

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