As aforementioned, the IR4TD considers three main areas of research in the future, therefore, as expected, research plans will include expansion of the above-described research in those areas. The transition to 100% renewable energy grid is facing many challenges including prediction uncertainty, renewable resources fluctuation, and introduction of additional hazards associated with storage systems. Although we have proposed various methods by which many of these challenges could be resolved [1, 2, 3, 4], there are still shortcomings to be addressed. As an example, for the approach we proposed in [2] to be fully implementable, other aspects must be investigated. These include grid stability in terms of variables like voltage and power dissipation through long-distance transmission, and other factors pertaining to landscape and cities-urban planning. Such challenging problems are multidisciplinary; and therefore, collaboration with researchers from diverse fields and backgrounds at various energy institutes throughout the University of Kentucky and others, becomes essential to advance those projects. Additionally, we are currently investigating the viability of using the excess energy available from the RES transition plan for various applications. This work will cover different topics and areas, which we are currently working on. Once those pieces are all tackled individually, artificial neural network and multi-objective optimization algorithms that we previously utilized for tuning energy systems, can be implemented to achieve the maximum efficient utilization of the RES systems installed; reducing the waste and hazards, at the same time achieving a carbon-neutral energy sector.

Additional research topics under this area also include:

• Developing a machine learning based model to find the optimal PV/wind capacities with different energy storage systems
  • Advantages of this model:
    • Less computation cost
    • Can be applied anywhere with given that solar and wind resources as well as the ambient temperatures are available.
• Efficient utilization of biogas using different power cycles and assessment of their techno-economic feasibility, which also covers solid waste management conversion to energy at landfills.
  • Could incorporate the social cost of GHG emissions
• Investigating different techniques and design improvements to enhance the efficiency of concentrated solar power system.
• Developing a methodology for fast EV battery replacement instead of charging. 
• Investigating the techno-economic feasibility of carbon capture in countries like Jordan (with suitable natural reservoirs)      
  • Can these countries sell their CO2 emission share to other countries? 
• Conceptual to Actual Thermal Regenerative Electrochemical Cycles (TREC): Towards deployment and commissioning of optimized TREC modules in different sectors of low waste heat. 
• Investigating the transition from high to low global warming potential refrigeration for sustainable cooling in different sectors.

In addition to the energy research, there is a great potential for the integration of machine learning tools in wildfires modeling, which we will investigate in the next years. Furthermore, we are investigating the acoustic technique’s ability to create reliable pressure estimates from micro-explosion decibels. If successful, this technique will be of a great use for estimating the pressure inside the live fuels before they exhibit the micro-explosion behavior, which in turn will provide estimates needed for the scaling analysis and fire behavior modeling. Besides that, two main projects will be the core focus of future fire research, first, there is an urgent need to create a well-controlled live fuel surrogate in order to experiment on and model wildfires accurately. This problem is becoming of increasing importance, particularly in the United States, where we have witnessed fire outbreaks in the past few years. Researchers have developed fuel surrogates to simulate dead fuels behavior, however, after we discovered the fundamental difference in the burning behavior of live fuels [5], and since the latter various dramatically from species to species, and even seasonally withing the same species, it is important that we design a well-controlled surrogate that is able to replicate the fire behavior of live fuels. This will be a significant advancement in the field, as researchers have not yet found a good surrogate for experimental investigations. The second project involves examining the ability of live fuels to resist flame extinction at higher wind speeds. As mentioned earlier, live fuels burn with micro-explosion or jetting behaviors, which makes them dynamically more similar to torch flames as opposed to candle flames which better resembles dead fuels burning behavior. This means that live fuels are able to withstand higher gusts before extinction and therefore spread during windy conditions. This second project is also a very significant advancement in this field, as this have not been previously envisioned or examined by any other researcher.

Although these research areas are slightly different in nature, the experimental, simulations, machine learning and optimization tools that are developed can be used efficiently across the different areas, which we will exploit as we continue our endeavor towards sustainability, climate change and environmental hazards mitigation.

For more information, please contact us.

 

References

1. Al-Ghussain, L., et al., A Demand-Supply Matching-Based Approach for Mapping Renewable Resources Towards 100% Renewable Grids in 2050. IEEE Access, 2021. 9: p. 58634-58651.

2. Al-Ghussain, L., A.M. Abubaker, and A. Darwish Ahmad, Superposition of renewable-energy supply from multiple sites maximizes demand-matching: Towards 100% renewable grids in 2050. Applied Energy, 2021. 284: p. 116402.

3. Hassan, M.A., et al., Aggregated independent forecasters of half-hourly global horizontal irradiance. Renewable Energy, 2022. 181: p. 365-383.

4. Al-Ghussain, L., et al., Techno-Economic Feasibility of Thermal Storage Systems for the Transition to 100% Renewable Grids. Available at SSRN 3916215.

5. Darwish Ahmad, A., et al., Ignition and burning mechanisms of live spruce needles. Fuel, 2021. 304: p. 121371.