A reliable and cost-effective planning framework of rural area hybrid system considering intelligent weather forecasting
نویسندگان
چکیده
The use of hybrid systems for electrification remote areas has been increased dramatically in recent years, and the optimal sizing these is a significant challenge cost-effectiveness reliability. This paper aims to propose predictable planning framework that increases renewable energy penetration (REP) rate minimizes annualized cost system (ACS) considering CO2 emission different loss power supply probability (LPSP). Due unavailability precise weather data areas, an intelligent forecasting scheme developed using adaptive neuro-fuzzy process based on fuzzy c-means clustering technique estimate solar radiation, wind speed, ambient temperature. also examines various evolutionary algorithms compare collected result proposed Multi-Verse Optimizer (MVO) with other meta-heuristic methods terms total LPSP, REP amounts. Moreover, assess impact irradiation, lifespan battery storage systems, fuel price diesel engine generators problem, sensitivity analysis performed values LPSP. effectiveness approach verified realistic case study Sistan & Balouchestan province Iran. Simulation results illustrate photovoltaic panels, turbine generators, (PV/WTG/BESS/DEG) most cost-effective strategy resulting 96.13% decrease compared DEG at REPmin=97% LPSPmax=1%. growth causes increase production resources (RESs) usage generators. Consequently, LPSPmax=10% REPmin=91%, 50% rise fuel, number drops zero, PV BESS from 311 172 411 228, respectively.
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ژورنال
عنوان ژورنال: Energy Reports
سال: 2021
ISSN: ['2352-4847']
DOI: https://doi.org/10.1016/j.egyr.2021.08.196