2023
DOI: 10.1177/0309524x231185492
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Investigation of PBUC problem with RES and EV in restructured environment

Abstract: This research proposes a novel solution for the optimal day-ahead scheduling problem in the GAMS environment using the BARON approach. The challenge is extended to include Renewable Energy Sources (RESs) and Electric Vehicles (EVs), making it more complex and practical. EVs serve as loads, energy suppliers, and storage during RESs’ uncertainties. The framework improves cost savings, quality, reliability, and stability of the power supply system by modeling solar, wind, and EV power in the scheduling problem. T… Show more

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“…The researchers developed various approaches for solution of PBUC problems which are Stochastic optimization approach (2) , Branch and reduce optimization navigator (3) , robust optimizations (4) , Emerald algebraic modeling system with BARON solver (5) , Two-layer nested optimization method (6) , moth fly optimization with levy flight search (7) , Monarch butterfly optimization (8) , modified bald eagle search Algorithm (9) , binary differential evolution and binary local search optimizer (10) , IPPD table and Analytical Hierarchy method (11) , BARON solver (12,13) , Enhanced-interval linear programming (14) and Harris Hawks Optimizer (15) .…”
Section: Introductionmentioning
confidence: 99%
“…The researchers developed various approaches for solution of PBUC problems which are Stochastic optimization approach (2) , Branch and reduce optimization navigator (3) , robust optimizations (4) , Emerald algebraic modeling system with BARON solver (5) , Two-layer nested optimization method (6) , moth fly optimization with levy flight search (7) , Monarch butterfly optimization (8) , modified bald eagle search Algorithm (9) , binary differential evolution and binary local search optimizer (10) , IPPD table and Analytical Hierarchy method (11) , BARON solver (12,13) , Enhanced-interval linear programming (14) and Harris Hawks Optimizer (15) .…”
Section: Introductionmentioning
confidence: 99%