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    <name>Article</name>
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          <name>Title</name>
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              <text>Optimal Load Control for Economic Energy Equilibrium in Smart Grid Using Adaptive Inertia Weight Teaching-Learning-Based Optimization</text>
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          <name>Subject</name>
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              <text>Adaptive teaching-learning-based optimization; Multi-objective optimization; Optimal load control; Smart grid</text>
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              <text>Due to numerous operational restrictions and economic purposes, optimal load management for energy balance in the smart grid (SG) is one of the compensating responsibilities. This research provides a novel multiobjective optimization technique for attaining energy balance in SG, with the goal of avoiding fines due to excessive upstream network power extraction beyond contractual demand. Due to a lack of capacity to create the whole optimization towards the global optimum after each run, optimal load control (OLC) is a prevalent challenge. Adaptive-TLBO, the most recent variation of Teaching Learning Based Optimization (TLBO), comprises both alterations during the exploitation and exploration phases (ATLBO). Because the ATLBO is used on a modified IEEE 33-bus system, the results obtained in this mode are extraordinary. The energy balance has improved in addition to the enhancement of the voltage profile and the reduction of distribution losses. As evidenced by comparisons with PSO, basic TLBO, backtracking search algorithm (BSA), and cuckoo search algorithms, the suggested ATLBO algorithm has precedence over any other proposed algorithm (CSA)  2022, International Journal of Intelligent Engineering and Systems.All Rights Reserved.</text>
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          <name>Creator</name>
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              <text>John N.; Janamala V.; Rodrigues J.</text>
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              <text>International Journal of Intelligent Engineering and Systems, Vol-15, No. 2, pp. 243-250.</text>
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              <text>Intelligent Network and Systems Society</text>
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          <name>Date</name>
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              <text>2022-01-01</text>
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              <text>&lt;a href="https://doi.org/10.22266/ijies2022.0430.22" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.22266/ijies2022.0430.22&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126823587&amp;amp;doi=10.22266%2Fijies2022.0430.22&amp;amp;partnerID=40&amp;amp;md5=0e3019688c96fa892fb2a4027fcee942" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126823587&amp;amp;doi=10.22266%2fijies2022.0430.22&amp;amp;partnerID=40&amp;amp;md5=0e3019688c96fa892fb2a4027fcee942&lt;/a&gt;</text>
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          <name>Rights</name>
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              <text>All Open Access; Bronze Open Access</text>
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              <text>ISSN: 2185310X</text>
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              <text>Online</text>
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              <text>English</text>
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              <text>John N., Department of Electrical and Electronics Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, Bangalore, 560074, India; Janamala V., Department of Electrical and Electronics Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, Bangalore, 560074, India; Rodrigues J., Department of Electrical and Electronics Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, Bangalore, 560074, India</text>
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