Wai, Lip Theo and Jeng, Shiun Lim and Wai, Shin Ho and Hashim, Haslenda and Othman, Muhamad Nazrin (2017) Optimisation and targeting of supply-demand of biogas system through gas system cascade analysis (gasca) framework. Renewable and Sustainable Energy Reviews, 146 . pp. 101-115. ISSN 0959-6526
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Official URL: https://doi.org/10.1016/j.rser.2016.09.063
Abstract
An overview of numerical and mathematical modelling-based distributed generation (DG) system optimisation techniques is presented in this review paper. The objective is to compare different aspects of these two broad classes of DG optimisation techniques, explore their applications, and identify potential research directions from reviewed studies. Introductory descriptions of general electrical power system and DG system are first provided, followed by reviews on renewable resource assessment, load demand analysis, model formulation, and optimisation techniques. In renewable resource assessment model review, uncertain solar and wind energy resources are emphasised whereas applications of forecasting models have been highlighted based on their prediction horizons, computational power requirement, and training data intensity. For DG optimisation framework, (solar, wind and tidal) power generator, energy storage and energy balance models are discussed; in optimisation technique section, both numerical and mathematical modelling optimisation methods are reviewed, analysed and criticised with recommendations for their improvements. In overall, this review provides preliminary guidelines, research gaps and recommendations for developing a better and more user-friendly DG energy planning optimisation tool.
Item Type: | Article |
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Additional Information: | RADIS System Ref No:PB/2016/02803 |
Uncontrolled Keywords: | mathematical modelling methods, optimisation |
Subjects: | T Technology > TP Chemical technology |
Divisions: | Chemical Engineering |
ID Code: | 66540 |
Deposited By: | Fazli Masari |
Deposited On: | 08 Oct 2017 03:23 |
Last Modified: | 08 Oct 2017 03:23 |
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