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Title: Economic scheduling for power systems with significant wind generation
Author: Tang, Xiaoqing
Awarding Body: Queen's University Belfast
Current Institution: Queen's University Belfast
Date of Award: 2013
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Full text unavailable from EThOS. Thesis embargoed until 01 Dec 2018
Economic scheduling is a resource optimisation problem in power systems. To minimize the operating cost, wind power is encouraged to replace conventional generation as much as possible since the counterpart fuel cost for conventional generation is saved. However, a serious problem is that wind power is often cUl1ailed, which partly reduces the economic benefit of wind power. Except for the fuel cost, the second largest operating cost is from the emergency reserve provision that generally falls on conventional generation. Further, the improvement of wind power forecast accuracy can also reduce the operating cost. Finally; due to significant wind power curtailment, it is difficult to determine wind power capacity and capacity credit in many countries. This thesis mainly addresses these four problems within the economic scheduling framework. Two scheduling methods, based on Lagrangian relaxation and heuristic algorithms, are developed. Simulation results have shown that the heuristic algorithm outperforms the Lagrangian relaxation and another widely used method, namely dynamic programming. To improve wind power forecast accuracy, a novel forecast error reduction method is proposed, which employs the autoregressive (AR) model to predict the commercial forecast error. The effectiveness of the new method is demonstrated using a whole year data of Eirgrid wind power, in comparison with the commercial forecast techniques. To reduce the amount of cUl1ailed wind .power and cost on emergency reserve, a new concept of active wind power curtailment is proposed to address these two challenges simultaneously. This is achieved by adopting a proportion of curtailed wind power potential as emergency reserve, which is the main idea of this thesis. Its benefits are demonstrated in comparison with passive curtailment using wind generation and system load data from Eirgrid. The thesis fUl1her examines the impacts of the proposed active curtailment on the wind power capacity planning in Ireland. Finally, a kernel based probabilistic algorithm is employed to estimate wind power capacity credit. The effectiveness of the new method is illustrated using Eirgrid demand and wind generation data, and compared with the normal distribution method.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available