Analytical and Data-driven Strategies to Advance Operational Flexibility of Smart Grids with Bulk System Renewables and Distributed Energy Resources
Description
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.
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2022
Agent
- Author (aut): Ghaljehei, Mohammad
- Thesis advisor (ths): Khorsand, Mojdeh
- Committee member: Vittal, Vijay
- Committee member: Wu, Meng
- Committee member: Weng, Yang
- Publisher (pbl): Arizona State University