Choosing the least-operating cost combination of electric power generation to meet demand is at the heart of utility and Independent System Operator (ISO) functions in the running of an electric power system. Additionally, utilities and ISOs must ensure that transmission lines will be operated within limits both under normal conditions and in the event of an outage, or failure, of a line. These transmission limitations can limit the choices available for dispatch of generators. A generation and transmission system operated within these limits is said to be secure. Maintaining security while seeking to minimize the operating costs of generation is a central function of utility and ISO operations and involves pro-active consideration of the many possible outages that might occur. If an outage does actually occur, then the dispatch must subsequently be changed so that the system can withstand the next outage. Generally, however, these actions needed to restore security are not explicitly modeled in the procedures of utilities and ISOs. The implication is that current systems might be operated in a manner that under-utilizes transmission capacity there resulting in more expensive dispatch than necessary or operated in a manner that could threaten reliability in the event of a single failure. This work seeks systematic methods to better represent the limitations on transmission and better represent the post-contingency restoration to security so as to improve electric generator dispatch. The graduate students will be trained in electric power engineering, optimization theory, and control systems. Students will be provided opportunities to interact with the Texas Legislative and Public utility commission, and the STEM outreach activities will extend to the South Harlem middle and high schools that serve underrepresented minorities.
This proposal aims at improving representation of post-contingency states in Regional Transmission Organization (RTO) and Independent System Operator (ISO) dispatch optimization to better ensure that transmission capability is neither under-utilized nor operated at levels that jeopardize reliability. Improved utilization of transmission capacity will contribute to lowering the overall cost of electricity supply by enabling more of the lower cost resources to be dispatched, and contribute to enhancing the integration of renewable resources by reducing transmission-related wind curtailment. Conversely, in cases where transmission may be operated in an optimistic manner, improved representation of post-contingency states will improve reliability. These improvements will be achieved by more comprehensive dispatch methodologies, that explicitly model post-contingency corrective actions, rather than through costly transmission upgrades. The capability of the transmission system to support flows of power is typically limited by both continuous and short-term thermal limits due to the interaction of resistive heating of lines and line temperature ratings. The limits vary from line to line and also depend to some extent on ambient conditions. These limits are incorporated into RTO/ISO dispatch models. Standard formulations of RTO/ISO dispatch use security-constrained optimal power flow (SCOPF) that represent contingencies by approximating the post-contingency flows on lines and other elements given a pre-contingency dispatch. Typically, the limits allowed for post-contingency flows reflect short-term transmission limits and are higher than the continuous ratings, with the implicit assumption that the flows can be reduced to being within continuous ratings through (unmodeled) post-contingency corrective actions before the temperature rise on the lines exceeds acceptable limits. The approach is to utilize recent advances in fine-grain distributed optimal power flow to explicitly represent the trajectory of post-contingency flows into the optimal power flow formulation, so that the implied limit on pre-contingency flows will neither be conservative or optimistic. This will enable better utilization of existing transmission capacity. Systematic methods to reduce the number of contingency constraints that must be explicitly represented in the optimization will also be investigated.
