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Metaheuristics Paradigms for Renewable Energy Systems: Advances in Optimization Algorithms

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Metaheuristic and Evolutionary Computation: Algorithms and Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 916))

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Abstract

In recent days, many novel techniques and technologies are develo** for power generation. Most of them are in its developed phase but its efficiency and reliability are low. Some of them have no running cost but its installation is costly. Some others are not cost effective and its cost to benefit ratio is poor. Because of all these reasons optimization techniques are required to expand the productivity, reliability and decrease the expense by optimal utilization of the resources and controlling methods. This chapter is mainly deals with basic and important metaheuristics optimization techniques used for power generation through renewable energy resources. Metaheuristic optimization approaches like Particle-Swarm Optimization (PSO), Differential-Evolution (DE), Tabu-Search (TS), Simulation-Annealing (SA), Genetic-Algorithm (GA), Artificial-Bee Colony (ABC), Ant-Colony Optimization (ACO), Cuckoo-Search (CS), and Biogeography-Based Optimization (BBO) are applicable on power generation using renewable energy resources. Some optimization techniques are good for solar PV system like PSO, ACO, ABC, DE etc., and some other optimization techniques like GA, CS, TS, BBO etc. for Battery storage using renewable hybrid system and design wind farm layouts. Applications of various metaheuristics optimization approaches for different renewable energy and hybrid systems are present in this chapter.

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Authors and Affiliations

  1. Department of Electrical Engineering, Integral University, Lucknow, UP, India

    Ahmad Faiz Minai

  2. Division of ICE, NSIT Delhi, New Delhi, India

    Hasmat Malik

  3. BEARS, University Town, NUS Campus, Singapore, Singapore

    Hasmat Malik

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  1. Ahmad Faiz Minai
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Correspondence to Ahmad Faiz Minai .

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Editors and Affiliations

  1. ICE Division, NSUT, Delhi, India

    Hasmat Malik

  2. Dept. of Electrical Engineering, Qatar University, Qatar, Qatar

    Atif Iqbal

  3. Electrical Engineering Department, Rajkiya Engineering College, Uttar Pradesh, India

    Puneet Joshi

  4. Electrical Engineering Department, Rajkiya Engineering College, Uttar Pradesh, India

    Sanjay Agrawal

  5. Electrical Engineering Department, National Institute of Technology, Srinagar, India

    Farhad Ilahi Bakhsh

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Minai, A.F., Malik, H. (2021). Metaheuristics Paradigms for Renewable Energy Systems: Advances in Optimization Algorithms. In: Malik, H., Iqbal, A., Joshi, P., Agrawal, S., Bakhsh, F.I. (eds) Metaheuristic and Evolutionary Computation: Algorithms and Applications. Studies in Computational Intelligence, vol 916. Springer, Singapore. https://doi.org/10.1007/978-981-15-7571-6_2

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