Khalaf, Saad
2021.
Integration of distributed diesel generators in power system, Iraq case study.
PhD Thesis,
Cardiff University.
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Abstract
In this work, existing off-grid diesel generators of the Zyounah region in Baghdad are investigated to provide an understanding of the real challenges of these generators for the consumers in terms of environmental and economic perspectives. The result reveals that if the load in which a generator operates is less than the generator’s size, the generator’s efficiency will drop, and the generator will consume a large amount of fuel and ultimately emit more CO2 emissions. Hence, the selection of a diesel generator should be close to the required load demand. Due to the mismatch between generation and supply in Iraq, the integration of existing off-grid diesel generators into the Iraq power system is important in providing flexibility in localized areas and help avoid or reduce the number of blackouts. The optimal location and sizing of these generation units is a suitable option for improving the operation of electrical networks. This study presents a methodology to find the best placement and the right size of the diesel generators in the distribution network of Ziyounah in the Baghdad area. In this study, demand forecasting using Linear Regression (LR) and Artificial Neural Networks (ANN) is presented to provides the power operator for Ziyounah in Baghdad with valuable information that is used for minimising the operational cost for integrated unit generations and accurately match electricity production to consumption in summer and winter seasons of 2020. Based on the forecasted demand, economic dispatch analysis was carried out using Lagrange multiplier (LM) and linear programming methods (LP) and assisted by the MATLAB application. The overall objective is to determine the optimal dispatch power for various types of generator sources including PV and grid import subject to several constraints to reduce the total operating cost for the integrated generation units while meeting the peak during 24hour in the summer and winter season.
Item Type: | Thesis (PhD) |
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Date Type: | Completion |
Status: | Unpublished |
Schools: | Engineering |
Uncontrolled Keywords: | Distributed Generation , Network Performance , Emission Factor , Load Forecast , Linear programming , Short Term Load Forecast |
Date of First Compliant Deposit: | 14 April 2022 |
Last Modified: | 06 May 2023 02:28 |
URI: | https://orca.cardiff.ac.uk/id/eprint/149179 |
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