Nowadays, power systems are interconnected together to provide a reliable and secure source of energy to the consumers and operate at lower operating cost than if they being run separately. As the most important reason for interconnecting power systems is to improve the economic aspects in operation of the entire system, this interconnection between power systems would provide the following economic advantages: 1) lower overall congestion costs for consumers; 2) more consistent prices across the areas; and 3) lower operating cost due to presence of broader pool of mutual benefits shared between systems. In addition, in the event of an emergency in any individual system, such as a shortage of generation capacity and a network outage, an interconnected power system can utilize all available power generation resources and delivery facilities throughout the entire grid to adjust the transferring power among systems; thus, guaranteeing a continuous power supply to customers in their regions and achieving a high-level power system reliability. Also, in the event of transmission line congestion, the interconnected power systems can work closely together to remove the congestion from the entire power grid.
The main motivation of this dissertation is to provide methodologies which enable different regional/virtual system’s operators to efficiently schedule their regional generation resources and optimally coordinate their operations with other neighboring areas while respecting the information privacy between individual systems. Our proposed methodologies rely on decentralized solution philosophies. Using these methods, the original large-scale problems can be divided into several scalable and tractable subproblems, where their solution can be coordinated with each other to find the optimal operating point of the entire system using either sequential or parallel calculation. Furthermore, by providing the flexibility to define the border of the areas, the decentralized solution methodologies can be also utilized to accelerate the solution process of the decision-making process in a large-scale power system where an enormous number of variables should be accommodated into the problem formulation.
|Commitee:||Abdelwahed, Sherif, Karimi-Ghartemani, Masoud, Yarahmadian, Shantia|
|School:||Mississippi State University|
|Department:||Electrical and Computer Engineering|
|School Location:||United States -- Mississippi|
|Source:||DAI-B 79/04(E), Dissertation Abstracts International|
|Subjects:||Engineering, Electrical engineering|
|Keywords:||Decentralized optimization, Optimal transmission switching, Power systems, Stochastic optimization, Wind power|
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