Optimal Sizing and Energy Management of a Hybrid Solar-Wind-Battery-Diesel System for Rural Electrification: A Fuzzy Logic Control Approach

Rural electrification in India remains an unfinished agenda despite significant progress under the Saubhagya and DDUGJY schemes, with approximately 30 million households in remote and geographically isolated villages lacking reliable grid connectivity. Hybrid Renewable Energy Systems (HRES) combining solar photovoltaic, wind turbine, battery energy storage, and diesel generator backup offer a techno-economically viable pathway for off-grid rural electrification at per-unit costs that have declined substantially due to rapidly falling PV module and lithium-ion battery prices. However, the intermittent and stochastic nature of solar and wind resources necessitates an intelligent Energy Management System (EMS) capable of dynamically dispatching generation and storage assets to satisfy load demand while minimising diesel consumption, maximising renewable energy fraction, and prolonging battery lifetime through controlled depth-of-discharge management. This paper presents the design, optimal sizing, and fuzzy logic-based energy management of a hybrid solar-wind-battery-diesel system for a representative rural cluster of 150 households (peak load 45 kW, annual energy demand 118 MWh) in Jaipur district, Rajasthan. System sizing optimisation using HOMER Pro minimises the Net Present Cost (NPC) subject to loss of power supply probability (LPSP) less than 2%. Five system configurations are evaluated: PV-only, wind-only, PV-wind, PV-wind-battery, and PV-wind-battery-diesel. The fuzzy logic EMS uses battery State-of-Charge (SOC) and net power surplus/deficit as inputs to generate dispatch decisions for battery charging/discharging and diesel generator start-stop commands. Results demonstrate that the optimal PV-wind-battery-diesel configuration achieves a Cost of Energy (COE) of USD 0.13/kWh, a Renewable Energy Fraction (REF) of 96%, and an annual diesel consumption reduction of 94% relative to a diesel-only baseline, with a project Net Present Cost of USD 187,400 over a 25-year project lifetime.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-23
DOI
https://doi.org/10.5281/zenodo.20352253
Primary Topic
Hybrid Renewable Energy Systems
Type
article
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article

Optimal Sizing and Energy Management of a Hybrid Solar-Wind-Battery-Diesel System for Rural Electrification: A Fuzzy Logic Control Approach

Anil Kumar Verma, Sunita Yadav, Manish Tripathi
Zenodo (CERN European Organization for Nuclear Research)
Hybrid Renewable Energy Systems
article

Optimal Sizing and Energy Management of a Hybrid Solar-Wind-Battery-Diesel System for Rural Electrification: A Fuzzy Logic Control Approach

Anil Kumar Verma, Sunita Yadav, Manish Tripathi
article en

Abstract

Rural electrification in India remains an unfinished agenda despite significant progress under the Saubhagya and DDUGJY schemes, with approximately 30 million households in remote and geographically isolated villages lacking reliable grid connectivity. Hybrid Renewable Energy Systems (HRES) combining solar photovoltaic, wind turbine, battery energy storage, and diesel generator backup offer a techno-economically viable pathway for off-grid rural electrification at per-unit costs that have declined substantially due to rapidly falling PV module and lithium-ion battery prices. However, the intermittent and stochastic nature of solar and wind resources necessitates an intelligent Energy Management System (EMS) capable of dynamically dispatching generation and storage assets to satisfy load demand while minimising diesel consumption, maximising renewable energy fraction, and prolonging battery lifetime through controlled depth-of-discharge management. This paper presents the design, optimal sizing, and fuzzy logic-based energy management of a hybrid solar-wind-battery-diesel system for a representative rural cluster of 150 households (peak load 45 kW, annual energy demand 118 MWh) in Jaipur district, Rajasthan. System sizing optimisation using HOMER Pro minimises the Net Present Cost (NPC) subject to loss of power supply probability (LPSP) less than 2%. Five system configurations are evaluated: PV-only, wind-only, PV-wind, PV-wind-battery, and PV-wind-battery-diesel. The fuzzy logic EMS uses battery State-of-Charge (SOC) and net power surplus/deficit as inputs to generate dispatch decisions for battery charging/discharging and diesel generator start-stop commands. Results demonstrate that the optimal PV-wind-battery-diesel configuration achieves a Cost of Energy (COE) of USD 0.13/kWh, a Renewable Energy Fraction (REF) of 96%, and an annual diesel consumption reduction of 94% relative to a diesel-only baseline, with a project Net Present Cost of USD 187,400 over a 25-year project lifetime.

Zenodo (CERN European Organization for Nuclear Research)
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Hybrid Renewable Energy Systems
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