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Erschienen in:
Impact of Reverse Power Flow Due to High Solar PV Penetration on Distribution Protection System Kapitel lesen Erstes Kapitel lesen

2022 | OriginalPaper | Buchkapitel

33. Genetic Algorithm-Based Load Frequency Control of a Grid-Connected Microgrid in Presence of Electric Vehicles

verfasst von : Krosuru Anuradhika, Puja Dash

Erschienen in: Sustainable Energy and Technological Advancements

Verlag: Springer Singapore

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Abstract

The frequency stability of the power system is becoming more serious with the increase in renewable energy penetration. Due to fast response and vehicle to grid capability, electric vehicles (EVs) are involved in improving the frequency stability of the power system. In this paper, hybrid generation consists of thermal power generation involving solar photovoltaic (PV), wind turbine generators (WTGs), geothermal power plant (GTPP) renewable generations and electric vehicle aggregators. An improvement in stability is achieved with different number of electric vehicles. Genetic algorithm (GA) with integral time absolute error (ITAE) performance indices as objective function is used to obtain the optimality of the controllers. The effects on transient behaviour of the microgrid is probed with PI, PID and GAPID controllers. Susceptibility analysis is executed on GAPID controller to prove the robustness under uncertainty conditions with both SLP and RLP.

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Vorheriges Kapitel Comparative Analysis of Fuzzy Logic and Synchronous Reference Frame Controlled LVRT Capability Enhancement in Wind Energy System Using DVR and STATCOM
Nächstes Kapitel Multi-area Load Frequency Control Using a Novel PID-Based Sliding Mode Controller
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Metadaten
Titel
Genetic Algorithm-Based Load Frequency Control of a Grid-Connected Microgrid in Presence of Electric Vehicles
verfasst von
Krosuru Anuradhika
Puja Dash
Copyright-Jahr
2022
Verlag
Springer Singapore
Buch
Sustainable Energy and Technological Advancements

Print ISBN: 978-981-16-9032-7

Electronic ISBN: 978-981-16-9033-4

Copyright-Jahr: 2022

DOI
https://doi.org/10.1007/978-981-16-9033-4_33