Analytical and Data-driven Strategies to Advance Operational Flexibility of Smart Grids with Bulk System Renewables and Distributed Energy Resources

Due to the new and old challenges, modern-day market management systems continue ‎to evolve, including market reformulations, introducing new market products, and ‎proposing new frameworks for integrating distributed energy resources (DERs) into the ‎wholesale markets. Overall, questions is regarding how to reflect these essential changes in ‎the market models (design, reformulation, and coordination frameworks), design market-‎based incentive structures to adequately compensate participants for providing ancillary ‎services, and assess these impacts on market settlements.‎First, this dissertation proposes the concept of securitized-LMP to solve the issue of how ‎market participants should be compensated for providing N-1 reliability services. Then, ‎pricing implications and settlements of three state-of-art market models are compared. The ‎results show that with a more accurate representation of contingencies in the market ‎models, N-1 grid security requirements are originally captured; thereby, the value of service ‎provided by generators is reflected in the prices to achieve grid security.‎ Also, new flexible ramping product (FRP) designs are proposed for different market ‎processes to (i) schedule day-ahead (DA) FRP awards that are more adaptive concerning ‎the real-time (RT) 15-min net load changes, and (ii) address the FRP deployability issue in ‎fifteen-minute market (FMM). The proposed market models performance with enhanced ‎FRP designs is compared against the DA market and FMM models with the existing FRP ‎design through a validation methodology based on California independent system operator ‎‎(ISO) RT operation. The proposed FRP designs lead to less expected final RT operating ‎cost, higher reliability, and fewer RT price spikes.‎ Finally, this dissertation proposes a distribution utility and ISO coordination framework ‎to enable ISO to manage the wholesale market while preemptively not allowing ‎aggregators to cause distribution ‎system (DS) violations. To this end, this coordination ‎framework architecture utilizes the statistical information obtained using different DS ‎conditions and data-mining algorithms to predict the aggregators qualified maximum ‎capacity. A validation phase considering Volt-VAr support provided by distributed PV smart ‎inverters is utilized for evaluate the proposed model performance. The proposed model ‎produces wholesale market awards for aggregators that fall within the DS operational limits ‎and, consequently, will not impose reliable and safety issues for the DS.‎