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Title: Coordinated scheduling of hydroelectric and wind power generation in power systems
Author: Chen, Qiyu
Awarding Body: Queen's University Belfast
Current Institution: Queen's University Belfast
Date of Award: 2015
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Wind generation has emerged as an important renewable resource for power systems in recent years. However, the stochastic availability and variability of wind make scheduled generation dispatch complex. Therefore, a Coordinated Hydro and Wind Generation (CHWG) strategy is proposed to improve scheduled dispatch and thereby contribute to preservation of system stability, while offering access to wind energy at grid level. The CHWG is described in detail and a feasibility study has been conducted. In CHWG strategy, the hydroelectric generation is proposed for energy reserve and compensation in the context of wind power fluctuation in order to avoid curtailment of wind generation to benefit wind providers. An optimal dispatch model for CHWG proposed, which includes a wind forecasting confidence interval and electricity tariff. The boundary constraint and inertia coefficient of a particle swarm optimization algorithm are adopted and used to solve the optimal dispatch model. The model is applied to a wind farm system in North China to exemplify the proposed strategy. The following work and achievements are related to the use of the CHWG method. CHWG enhances the capacity of peak load regulation with offshore wind power integration. A model is presented to study the capacity of peak load regulation with offshore wind power integration. Meantime, a CHWG strategy mode is adopted to provide peak load regulation and some measures are proposed to improve regulation. A power system model is used to demonstrate that wind power fluctuations can readily render Over-frequency generator tripping (OFGT) and under-frequency load shedding (UFLS) mal-operation. Using the proposed CHWG strategy, a coordinated approach is proposed to resolve problems associated with OFGT and UFLS and preserve system stability. Finally, a risk assessment model (RAM) for wind generator tripping is established and verified by simulation results from a provincial Power Grid of China on line data.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available