Contingency-Constrained Unit Commitment With Intervening Time for System Adjustments

The N-1-1 contingency criterion considers the con- secutive loss of two components in a power system, with intervening time for system adjustments. In this paper, we consider the problem of optimizing generation unit commitment (UC) while ensuring N-1-1 security. Due to the coupling of time periods associated with consecutive component losses, the resulting problem is a very large-scale mixed-integer linear optimization model. For efficient solution, we introduce a novel branch-and-cut algorithm using a temporally decomposed bilevel separation oracle. The model and algorithm are assessed using multiple IEEE test systems, and a comprehensive analysis is performed to compare system performances across different contingency criteria. Computational results demonstrate the value of considering intervening time for system adjustments in terms of total cost and system robustness.Comment: 8 pages, 5 figure

Critical Infrastructure Systems: Distributed Decision Processes over Network and Uncertainties

Critical infrastructure systems (CISs) provide the essential services that are vital for a nation's economy, security, and health, but the analysis of CISs are challenged due to their inherent complexity. This dissertation focuses primarily on the system analysis of critical infrastructure systems, with a particular interest to address the modeling and computational challenges brought by uncertainties, interdependencies and distributed decision making of various components and stakeholders involved in CISs, so that a secure, reliable, efficient and resilient system can be further pursued. Through two examples, the first one is on electric vehicle charging infrastructure planning in a competitive market, and the second one is on power generators planning in a restructured electricity market, we illustrate how our general modeling framework, N-SMOPEC, can be adapted to formulate the specific problems in transportation and energy system. Each example is solved by decomposition based approach with convergence properties developed based on recent theoretical advances of variational convergence. Median size numerical experiments are implemented to study the performance of proposed method and draw practical insights. In addition, we have shown some knowledge from different domains, such as microeconomics, energy and transportation, can be shared to facilitate the formulation and solution process of seemingly unrelated problems of each other, which could possibly foster the communication between different fields and open up new research opportunities from both theoretical and practical perspectives

A Stochastic Multi-Agent Optimization Model for Energy Infrastructure Planning Under Uncertainty and Competition

This paper presents a stochastic multi-agent optimization model that supports energy infrastructure planning under uncertainty. The interdependence between different decision entities in the system is captured in an energy supply chain network, where new entrants of investors compete among themselves and with existing generators for natural resources, transmission capacities, and demand markets. Directly solving the stochastic energy supply chain planning problem is challenging. Through decomposition and reformulation, we convert the original problem to many traffic network equilibrium problems, which enables efficient solution algorithm design.View the NCST Project Webpag

A Stochastic Multi-Agent Optimization Model for Energy Infrastructure Planning Under Uncertainty and Competition

This paper presents a stochastic multi-agent optimization model that supports energy infrastructure planning under uncertainty. The interdependence between different decision entities in the system is captured in an energy supply chain network, where new entrants of investors compete among themselves and with existing generators for natural resources, transmission capacities, and demand markets. Directly solving the stochastic energy supply chain planning problem is challenging. Through decomposition and reformulation, we convert the original problem to many traffic network equilibrium problems, which enables efficient solution algorithm design.View the NCST Project Webpag

Contingency-Constrained Unit Commitment With Intervening Time for System Adjustments

The N-1-1 contingency criterion considers the con- secutive loss of two components in a power system, with intervening time for system adjustments. In this paper, we consider the problem of optimizing generation unit commitment (UC) while ensuring N-1-1 security. Due to the coupling of time periods associated with consecutive component losses, the resulting problem is a very large-scale mixed-integer linear optimization model. For efficient solution, we introduce a novel branch-and-cut algorithm using a temporally decomposed bilevel separation oracle. The model and algorithm are assessed using multiple IEEE test systems, and a comprehensive analysis is performed to compare system performances across different contingency criteria. Computational results demonstrate the value of considering intervening time for system adjustments in terms of total cost and system robustness