A multi-objective artificial hummingbird algorithm for dynamic optimal volt-var controls for high electric vehicle load penetration in a photovoltaic distribution network
Renewable energy systems (RESs) and electric vehicles (EVs) have become global necessities to meet the sustainable development goals (SDGs). Because they are intermittent and stochastic, these two technologies have caused power grid operation and regulation challenges despite their environmental ben...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-03-01
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| Series: | e-Prime: Advances in Electrical Engineering, Electronics and Energy |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772671124000561 |
| _version_ | 1797256255245385728 |
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| author | Lalitha Kondisetti Swarnasri Katragadda |
| author_facet | Lalitha Kondisetti Swarnasri Katragadda |
| author_sort | Lalitha Kondisetti |
| collection | DOAJ |
| description | Renewable energy systems (RESs) and electric vehicles (EVs) have become global necessities to meet the sustainable development goals (SDGs). Because they are intermittent and stochastic, these two technologies have caused power grid operation and regulation challenges despite their environmental benefits. A new combined dynamic optimal network reconfiguration (DONR) and capacitor bank switching (CBS) optimization technique reduces solar and multi-type load effects on the distribution network performance. Considering substantial EV load penetrations, ONR and CBS should coordinate to reduce energy loss, improve the voltage profile, and save money during 24 h operation. The artificial hummingbird algorithm (AHA) solves this difficult optimization problem for the first time. An enhanced IEEE 33-bus benchmark test system was used to simulate various instances to evaluate the computational characteristics of the AHA and compare it with other similar algorithms. The obtained results demonstrate the superiority of the combined DONR and CBS for real-time scenarios over any individual approach. |
| first_indexed | 2024-03-07T21:27:30Z |
| format | Article |
| id | doaj.art-1c088af0a06f4b79b803f7e27ee57261 |
| institution | Directory Open Access Journal |
| issn | 2772-6711 |
| language | English |
| last_indexed | 2024-04-24T22:18:50Z |
| publishDate | 2024-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | e-Prime: Advances in Electrical Engineering, Electronics and Energy |
| spelling | doaj.art-1c088af0a06f4b79b803f7e27ee572612024-03-20T06:12:00ZengElseviere-Prime: Advances in Electrical Engineering, Electronics and Energy2772-67112024-03-017100474A multi-objective artificial hummingbird algorithm for dynamic optimal volt-var controls for high electric vehicle load penetration in a photovoltaic distribution networkLalitha Kondisetti0Swarnasri Katragadda1Dr. YSR. ANU College of Engineering and Technology, Acharya Nagarjuna University, Guntur 522510, Andhra Pradesh, India; Corresponding author.Department Electrical & Electronics Engineering, R.V.R. & J.C. College of Engineering, Guntur 522 019, Andhra Pradesh, IndiaRenewable energy systems (RESs) and electric vehicles (EVs) have become global necessities to meet the sustainable development goals (SDGs). Because they are intermittent and stochastic, these two technologies have caused power grid operation and regulation challenges despite their environmental benefits. A new combined dynamic optimal network reconfiguration (DONR) and capacitor bank switching (CBS) optimization technique reduces solar and multi-type load effects on the distribution network performance. Considering substantial EV load penetrations, ONR and CBS should coordinate to reduce energy loss, improve the voltage profile, and save money during 24 h operation. The artificial hummingbird algorithm (AHA) solves this difficult optimization problem for the first time. An enhanced IEEE 33-bus benchmark test system was used to simulate various instances to evaluate the computational characteristics of the AHA and compare it with other similar algorithms. The obtained results demonstrate the superiority of the combined DONR and CBS for real-time scenarios over any individual approach.http://www.sciencedirect.com/science/article/pii/S2772671124000561Active distribution networkArtificial hummingbird algorithmCapacitor bank switchingDynamic optimal network reconfigurationElectric vehiclesMulti-objective optimization |
| spellingShingle | Lalitha Kondisetti Swarnasri Katragadda A multi-objective artificial hummingbird algorithm for dynamic optimal volt-var controls for high electric vehicle load penetration in a photovoltaic distribution network e-Prime: Advances in Electrical Engineering, Electronics and Energy Active distribution network Artificial hummingbird algorithm Capacitor bank switching Dynamic optimal network reconfiguration Electric vehicles Multi-objective optimization |
| title | A multi-objective artificial hummingbird algorithm for dynamic optimal volt-var controls for high electric vehicle load penetration in a photovoltaic distribution network |
| title_full | A multi-objective artificial hummingbird algorithm for dynamic optimal volt-var controls for high electric vehicle load penetration in a photovoltaic distribution network |
| title_fullStr | A multi-objective artificial hummingbird algorithm for dynamic optimal volt-var controls for high electric vehicle load penetration in a photovoltaic distribution network |
| title_full_unstemmed | A multi-objective artificial hummingbird algorithm for dynamic optimal volt-var controls for high electric vehicle load penetration in a photovoltaic distribution network |
| title_short | A multi-objective artificial hummingbird algorithm for dynamic optimal volt-var controls for high electric vehicle load penetration in a photovoltaic distribution network |
| title_sort | multi objective artificial hummingbird algorithm for dynamic optimal volt var controls for high electric vehicle load penetration in a photovoltaic distribution network |
| topic | Active distribution network Artificial hummingbird algorithm Capacitor bank switching Dynamic optimal network reconfiguration Electric vehicles Multi-objective optimization |
| url | http://www.sciencedirect.com/science/article/pii/S2772671124000561 |
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