On July 11,2017,an agreement was signed in Beijing to renew and strengthen the collaboration between the CAS Institute of Automation(CASIA,China),Institut National de Recherche en Informatique et en Automatique(Inria,...On July 11,2017,an agreement was signed in Beijing to renew and strengthen the collaboration between the CAS Institute of Automation(CASIA,China),Institut National de Recherche en Informatique et en Automatique(Inria,France),and Centrum Wiskunde&Informatica(CWI,the Netherlands),which are the founding members of the Sino-European Laboratory in Computer Science,展开更多
The artificial bee colony(ABC) algorithm is improved to construct a hybrid multi-objective ABC algorithm, called HMOABC, for resolving optimal power flow(OPF) problem by simultaneously optimizing three conflicting obj...The artificial bee colony(ABC) algorithm is improved to construct a hybrid multi-objective ABC algorithm, called HMOABC, for resolving optimal power flow(OPF) problem by simultaneously optimizing three conflicting objectives of OPF, instead of transforming multi-objective functions into a single objective function. The main idea of HMOABC is to extend original ABC algorithm to multi-objective and cooperative mode by combining the Pareto dominance and divide-and-conquer approach. HMOABC is then used in the 30-bus IEEE test system for solving the OPF problem considering the cost, loss, and emission impacts. The simulation results show that the HMOABC is superior to other algorithms in terms of optimization accuracy and computation robustness.展开更多
文摘On July 11,2017,an agreement was signed in Beijing to renew and strengthen the collaboration between the CAS Institute of Automation(CASIA,China),Institut National de Recherche en Informatique et en Automatique(Inria,France),and Centrum Wiskunde&Informatica(CWI,the Netherlands),which are the founding members of the Sino-European Laboratory in Computer Science,
基金Projects(61105067,61174164)supported by the National Natural Science Foundation of China
文摘The artificial bee colony(ABC) algorithm is improved to construct a hybrid multi-objective ABC algorithm, called HMOABC, for resolving optimal power flow(OPF) problem by simultaneously optimizing three conflicting objectives of OPF, instead of transforming multi-objective functions into a single objective function. The main idea of HMOABC is to extend original ABC algorithm to multi-objective and cooperative mode by combining the Pareto dominance and divide-and-conquer approach. HMOABC is then used in the 30-bus IEEE test system for solving the OPF problem considering the cost, loss, and emission impacts. The simulation results show that the HMOABC is superior to other algorithms in terms of optimization accuracy and computation robustness.
