New optimization techniques for power system generation scheduling
Sun, Wei (2011) New optimization techniques for power system generation scheduling. PhD thesis, Iowa State University.
Full text available as:
Generation scheduling in restructured electric power systems is critical to maintain the stability and security of a power system and economical operation of the electricity market. However, new generation scheduling problems (GSPs) are emerging under critical or new circumstances, such as generator starting sequence and black-start (BS) generator installation problems in power system restoration (PSR), and generation operational planning considering carbon dioxide (CO2) emission regulation. This dissertation proposes new optimization techniques to investigate these new GSPs that do not fall into the traditional categories. Resilience and efficient recovery are critical and desirable features for electric power systems. Smart grid technologies are expected to enable a grid to be restored from major outages efficiently and safely. As a result, power system restoration is increasingly important for system planning and operation. In this dissertation, the optimal generator start-up strategy is developed to provide the starting sequence of all BS or non-black-start (NBS) generating units to maximize the overall system generation capability. Then, based on the developed method to estimate the total restoration time and system generation capability, the optimal installation strategy of blackstart capabilities is proposed for system planners to develop the restoration plan and achieve an efficient restoration process. Therefore, a new decision support tool for system restoration has been developed to assist system restoration planners and operators to restore generation and transmission systems in an on-line environment. This tool is able to accommodate rapidly changing system conditions in order to avoid catastrophic outages. Moreover, to achieve the goal of a sustainable and environment-friendly power grid, CO2 mitigation policies, such as CO2 cap-and-trade, help to reduce consumption in fossil energy and promote a shift to renewable energy resources. The regulation of CO2 emissions for electric power industry to mitigate global warming brings a new challenge to generation companies (GENCOs). In a competitive market environment, GENCOs can schedule the maintenance periods to maximize their profits. Independent System Operator’s (ISO) functionality is also considered from the view point of system reliability and cost minimization. Considering these new effects of CO2 emission regulation, GENCOs need to adjust their scheduling strategies in the electricity market and bidding strategies in CO2 allowance market. This dissertation proposes a formulation of the emission-constrained GSP and its solution methodology involving generation maintenance scheduling, unit commitment, and CO2 cap-and-trade. The coordinated optimal maintenance scheduling and CO2 allowance bidding strategy is proposed to provide valuable information for GENCOs’ decision makings in both electricity and CO2 allowance markets. By solving these new GSPs with advanced optimization techniques of Mixed Integer Linear Programming (MILP) and Mixed Integer Bi-level Liner Programming (MIBLP), this dissertation has developed the highly efficient on-line decision support tool and optimal planning strategies to enhance resilience and sustainability of the electric power grid.
Archive Staff Only: edit this record