Techno-economic optimisation of stand-alone hybrid renewable energy systems for concurrently meeting electric and heating demand

Abstract

Current power sector around the world is mostly dependent on unsustainable, environmentally hazardous non-renewable energy system. As such, a cost-effective and sustainable yet environmentally benign renewable energy system should be developed to meet the ever increasing energy demand. The hybrid renewable energy system generates a considerable amount of excess energy while meeting the reliable power in an off-grid condition. Research into the recovering excess energy from the stand-alone renewable energy resources to meet the residential heating demand gets less attention. The key objective of this research is to investigate the optimisation of hybrid renewable energy system using the excess energy generated by its own sources to satisfy the electric and thermal loads for a remote community. Hybrid optimization model for electric renewable software tool is used to examine the techno-economic feasibility of the hybrid energy system. The proposed system configuration consists of photovoltaic module, wind turbine, battery, thermal load controller, and gas boiler. An electric boiler utilizing the excess energy from renewable energy sources only is used as the thermal load controller to meet the thermal demand. A detailed comparison between the hybrid system meeting both electric and thermal, hybrid system meeting only electric load, and the diesel-only option has been investigated. Results of these analyses indicate that the optimised PV/Wind/Batt-based hybrid option offers a lower cost of energy (COE = 0.255 $/kWh) when the system meets the thermal load by using the thermal load controller and the gas boiler than without utilising excess energy (0.274 $/kWh). In addition, a substantial reduction of hardware components capacity and the associated net present cost can be achieved by utilising excess energy via thermal load controller and the gas boiler to meet the thermal demand than without using excess energy. Potential cost reduction and environmental benefits can be attained by the optimised PV/Wind/Batt-based hybrid system than that of the diesel generator-based option. Finally, the optimised system is compared with the results obtained using genetic algorithm to validate the findings of the hybrid optimization model for electric renewable software tool. The genetic algorithm optimisation technique shows that the proposed system is highly reliable (99.92 %) while meeting the electric and thermal demands.