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Title: Evaluating and planning flexibility in a sustainable power system with large wind penetration
Author: Ma, Juan
ISNI:       0000 0004 2720 1646
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2012
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Flexibility describes the system ability to cope with events that may cause imbalance between electricity supply and demand while maintaining the system reliability in a cost-effective manner. Flexibility has always been present in the power system to cater for unplanned generator outages and demand uncertainty and variability. The arrival of wind generation with its variable and hard to predict nature increases the overall needs for system flexibility. This thesis provides a systematic approach for investigating the role of flexibility in different power system activities including generation scheduling, generation planning and market operation, and furthermore proposes two 'offline' indices for flexibility evaluation. Using the tools and metrics presented in this thesis, it is possible to perform the following tasks: • Conduct generation scheduling simulation to evaluate the impacts of wind on the flexibility requirement of power systems; • Use the unit construction and commitment algorithm to 1) estimate the maximum allowable wind capacity for an existing system; 2) find the optimal investment of new flexible units for accommodating more wind generation; and 3) decide an optimal generation mix for integrating a given wind penetration; • Use the market model to reveal the value and profitability of flexibility and evaluate the corresponding effects of alternative market design; • Use the two proposed flexibility indices to quantitatively assess the flexibility of individual generators and power systems without undertaking complex and time consuming simulations.
Supervisor: Ochoa, Luis Nando Sponsor: EDF
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Power system ; Wind integration ; Flexibility ; Generation scheduling ; Generation planning ; Electricity market