Rural electrification using renewable energy resources and its environmental impact assessment

Area of Science:

• Renewable Energy Systems
• Microgrid Optimization
• Sustainable Energy Management

Background:

• Microgrids enhance power sustainability, reduce emissions, and lower costs but require advanced energy management.
• Optimizing microgrids involves balancing generation costs and greenhouse gas emissions.
• Accurate cost modeling for energy components, especially renewables, is crucial for low-cost energy.

Purpose of the Study:

• To develop a generation cost model integrating renewable energy to reduce operating costs and emissions.
• To provide a low-cost energy solution for a rural Indian scenario using optimization techniques.
• To analyze the role of battery storage in compensating for generation shortages and minimizing environmental impact.

Main Methods:

• Developed a generation cost model incorporating photovoltaic (PV) and wind turbine energy.
• Employed Particle Swarm Optimization (PSO), a global optimization strategy, to address multi-objective problems (cost and emissions).
• Simulated a microgrid system with PV, diesel generator, battery, and wind turbine against an Indian rural load profile.

Main Results:

• Achieved an optimal configuration with a total net operating cost of $59,195.61 and a per-unit energy cost of $0.20/kWh.
• Reduced annual emissions by 5994 kg/year, demonstrating significant environmental benefits.
• Validated the cost-effectiveness and modular feasibility of the hybrid energy system for rural electrification.

Conclusions:

• The proposed hybrid energy system and optimization approach provide a viable, cost-effective solution for rural microgrids.
• Integrating renewable energy sources with battery storage effectively manages costs and curbs greenhouse gas emissions.
• The findings offer valuable insights for rural communities and stakeholders in planning sustainable energy initiatives.