Journal Article10.1016/J.RSER.2018.05.032
Sizing methods and optimization techniques for PV-wind based hybrid renewable energy system: A review
326
TL;DR: An updated literature review, of the most applied method and techniques used in sizing and optimization of PV-Wind based hybrid system (PWHS) for an isolated area aiming to reach the best compromise between power reliability and hybrid system costs is provided.
read more
Abstract: Solar and wind energy are considered as promising electrical generating sources. These renewable energies are omnipresent, with free access, and a friendly environmental impact. Their integration remains technically and economically advantageous for electrical generation in isolated areas (IS). In several cases, the separate use of solar and wind energy sources may result in considerable over-sizing, which makes the single renewable energy sources in implementation very costly. It is found that the use of one of the optimization sizing techniques could help to guarantee the maximum power reliability and the minimum system cost for the future hybrid implementation. Moreover, a remarkable interest is manifesting for the use of solar and wind renewable energy sources (RES), which provide a realistic form of electrical generation in isolated areas. This paper provides an updated literature review, of the most applied method and techniques used in sizing and optimization of PV-Wind based hybrid system (PWHS) for an isolated area aiming to reach the best compromise between power reliability and hybrid system costs. Furthermore, this work discusses a comparison of the most common topologies used for the implementation of PWHS, then, presents a mathematical model of the hybrid system components with an emphasis on the importance of power reliability and system cost, Finally, provides an extensive analysis of software tools and algorithm approach used in sizing optimization.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
A review on recent sizing methodologies of hybrid renewable energy systems
TL;DR: Hybrid methods with high accuracy and fast convergence that can surmount the defects of single methods are the most promising sizing method compared to the other three sizing methods.
462
A review of hybrid renewable energy systems in mini-grids for off-grid electrification in developing countries
Emília Inês Come Zebra,Emília Inês Come Zebra,Henny van der Windt,Geraldo Nhumaio,André Faaij +4 more
TL;DR: In this paper, the levelized cost of energy (LCOE) of different mini-grids was compared and analyzed, and the results reveal that diesel is the most expensive technology.
269
How to make better use of intermittent and variable energy? A review of wind and photovoltaic power consumption in China
TL;DR: In this article, the authors systematically review the explorations and the practices related to wind and photovoltaic power consumption in China and provide several suggestions, including promoting multi-energy complementary microgrid application and installing large-scale pumped storage hydropower, for improving the efficiency of renewable energy development in China.
220
Review of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applications
Mahammad A. Hannan,M. Faisal,Pin Jern Ker,Rawshan Ara Begum,Rawshan Ara Begum,Zhao Yang Dong,Cuo Zhang +6 more
TL;DR: This review highlights details of ESS sizing to optimize storage capacity, reduce consumption, minimize storage cost, determine the optimal placement and mitigate carbon emission for decarbonization.
195
References
Genetic algorithms in search, optimization and machine learning
David E. Goldberg
- 01 Jan 1989
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
58.6K
•Book
Genetic algorithms in search, optimization, and machine learning
David E. Goldberg
- 01 Sep 1988
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Particle Swarm Optimization.
James Kennedy
- 01 Jan 2017
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
35K
Particle swarm optimization
TL;DR: A snapshot of particle swarming from the authors’ perspective, including variations in the algorithm, current and ongoing research, applications and open problems, is included.
Ant colony system: a cooperative learning approach to the traveling salesman problem
TL;DR: The results show that the ACS outperforms other nature-inspired algorithms such as simulated annealing and evolutionary computation, and it is concluded comparing ACS-3-opt, a version of the ACS augmented with a local search procedure, to some of the best performing algorithms for symmetric and asymmetric TSPs.
8.3K