Efficient solving of strategic bidding issues under no Karush–Kuhn–Tucker optimality constraints

摘要: A typical bidding procedure is to maximize the profit of strategic producers, in a manner that offer curve yields solutions ISO marketing clearing problem. The literature portrays form searching problem with dual levels, wherein minimization market function along maximization yielded using curve. But, elevated levels complexity computing and solving bi-level have forced researchers transform it as one-level through employing Karush–Kuhn–Tucker (KKT) optimality conditions. Yet, serious problems emerge algorithms incorporating KKT conditions (for instance, classical optimization algorithms). grows size, if transmission constraints get vital deregulated environment. Our research contribution devises be function, lacking consideration on for functions, operating limits constraints. modified group search optimizer (GSO), one currently popular algorithms, provides developed model. conventional GSO, an algorithm operates population, has its motivation from animals’ activities. GSO changes maximum pursuit angle animal activity relative number iterations. testing proposed method employs both IEEE 30 bus system well 14 system. Performance comparison among method, approaches rely particle swarm optimization, genetic reveal excessive superiority method.