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Intelligent Methods for Power System Analysis: Advancement in Optimization and Its Application

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Intelligent Data Analytics for Power and Energy Systems

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 802))

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Abstract

Optimization problems often entail scenarios wherein the user's purpose is to decrease and/or maximize not a single but multiple, usually conflicting, objective functions simultaneously. Optimization problems often arise in real-world situation concerning engineering and design, chemical operation, and so forth. In this scenario, attaining an optimum for one goal/objective function necessitates certain compromises on one or more of the others and in such cases, we will end up with a collection of equally good solutions rather than just one in such issues. It is usually hard to address the multi-objective optimization problems since its optimal goals are frequently discordant. From a mathematical standpoint, finding an optimal solution that meets all objectives is troublesome and problematic. The chapter begins with a brief history of global optimization. The combined influence of innovative ideas and challenging applications has led to the establishment/formation of multi-objective optimization techniques. The emerging methods are predicated upon evolutionary algorithms that were inspired by nature. This also contributes to the study of numerous optimization challenges and the development/advancement of multiple cutting-edge intelligent algorithms in the effort of power system analysis. Furthermore, we provide an outline of multiple intelligent and advanced optimization methods used in different perspective and its application to electrical engineering among other goals. Finally, a comprehensive assessment of current challenges in the multi-objective optimization problem is provided, as well as ideas or direction for future research. The chapter is intended for readers (students, researchers or any), who wish to acquire the foundation or basic knowledge about the conceptual fundamentals of optimization as well as cutting-edge methodologies of evolutionary multi-objective optimization. The vision is to offer a general framework for research in this vibrant field, as well as to assist the advanced researchers and scholars in identifying untapped research opportunities.

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Authors and Affiliations

  1. Department of EEE, Amity University, Noida, India

    Ushakiran Huiningsumbam, Ashish Mani & Anjali Jain

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  1. Ushakiran Huiningsumbam
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Editors and Affiliations

  1. BEARS, National University of Singapore (NUS), Singapore, Singapore

    Hasmat Malik

  2. Department of Electrical and Electronics Engineering, National Institute of Technology Karnataka, Surathkal, Karnataka, India

    Md. Waseem Ahmad

  3. THDC Institute of Hydropower Engineering and Technology, Chairman, Board of Governors, Tehri, Uttarakhand, India

    D.P. Kothari

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Huiningsumbam, U., Mani, A., Jain, A. (2022). Intelligent Methods for Power System Analysis: Advancement in Optimization and Its Application. In: Malik, H., Ahmad, M.W., Kothari, D. (eds) Intelligent Data Analytics for Power and Energy Systems. Lecture Notes in Electrical Engineering, vol 802. Springer, Singapore. https://doi.org/10.1007/978-981-16-6081-8_13

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