Energy Harvesting for Smart Energy Systems

Shirin Momen (), Javad Nikoukar (), Arsalan Hekmati (), Soheil Majidi (), Zahra Zand, Mohammad Zand and Mostafa Eidiani ()
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Shirin Momen: Islamic Azad University
Javad Nikoukar: Islamic Azad University
Arsalan Hekmati: Revterra Co.
Soheil Majidi: Research and Development Department, BLUE&P Group
Zahra Zand: Razi University
Mohammad Zand: Denmark and Renewable Energy Lab (REL), Aarhus University
Mostafa Eidiani: Khorasan Institute of Higher Education

A chapter in Handbook of Smart Energy Systems, 2023, pp 1589-1612 from Springer

Abstract: Abstract With increasing the amount of electricity demand by subscribers, increasing attention to the quality of energy delivered to consumers and welcoming planners and independent users of the power system from the presence of distributed generation resources as a part of the network needs, formulating a technical and economic framework How much better are these resources in the power grid. One of the current research areas on distributed generation resources is to study how these resources are optimally allocated in the power grid. Optimal allocation of distributed generation resources in the network means locating and determining the appropriate size of production of these resources in order to achieve specific goals. These goals include maximizing investor profits, minimizing supply costs, reducing losses, improving voltage profiles, improving reliability indicators, and reducing emissions from electricity generation. The existence of distributed generation (DG) is no longer valid. One of the important issues and challenges in the field of distribution networks is the discussion of power losses and in fact its optimization, which needs to be analyzed for safe operation. In this chapter of the book Optimal Allocation of Distributed Generation Units in a Nonlinear Optimization Problem with Constraints to Minimize Loss Using the Improved Shuffled Frog Leaping Algorithm (ISFLA) Analysis is located. This study uses the ISFLA optimization algorithm to minimize losses in a standard 33-bus radial distribution system. Voltage followed that this is very important in distribution systems.

Keywords: Particle Swarm Optimization (PSO); Scattered Production Resources; Distribution Production Unit; Restructuring; Frog Jump Algorithm; Sequential Quadratic Programming; Versatile Energy Resource Allocation (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/978-3-030-97940-9_12

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