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Energy Systems Optimization

West Virginia University researchers focus on dynamic modeling and simulation of interconnected energy systems, and the development of algorithms for advanced process control, dynamic real-time and multi-objective optimization. The developed methods have been applied to several energy systems, including coal-fired (subcritical, supercritical, cycling) and natural-gas fired power plants, hybrid and cyber-physical systems. These applications considered the presence of carbon capture systems, energy storage technologies such as batteries/pumped hydro as well as renewable energy sources in solar and wind.

Energy systems networks comprising of power, transportation and communications networks are sources of vital needs on which the economy depends. These networks are in a transformative stage going well beyond their traditional operations. These networks are being operated on multiple time scales with spatial and temporal dependencies and rigorous operational requirements. The proliferation of renewable generation, consumer interaction and electric vehicles has resulted in stochastic variations which though bring in significant benefits but also create formidable challenges for optimized operations of these networks under various operational conditions.

Affiliated Faculty

Recent Publications

  1. S. Kasani, D. Tiwari, M. R. Khalghani, J. Solanki, S. Solanki, “Coordinated Charging of Plug-in Hybrid Electric Vehicles with Demand Response in a Microgrid,” IET Smart Grid 

  2. H. U. Banna, Z. Yu, D. Shi, Z. Wang, D. Su, C. Xu, S. K. Solanki, J. Solanki, “Online Coherence Identification using Dynamic Time Warping for Controlled Islanding,” Journal of Modern Power and Clean Energy, 2018

  3. Junbiao Han; Khushalani Solanki, S.; Solanki, J., Jiaqi Liang, “Adaptive Critic Design-Based Dynamic Stochastic Optimal Control Design for a Microgrid with Multiple Renewable Resources,” IEEE Transactions on Smart Grid, vol.6, no.6, pp.2694-2703.

  4. D. Tiwari, S. Solanki, J. Solanki, “Vehicle-to-Grid Integration for enhancement of Grid: A Distributed Resource Allocation Approach,” IEEE Access, Access-2020-33673