Many-objective power flow optimization problems based on an improved MOEA/D with dynamical resource allocation strategy

Abstract

Due to the rapid development of the society, increasing power demand is needed as well as the higher power quality and the stricter requirement to the living environment. In such a circumstance, the single-objective optimization only involving economics obviously does not meet the requirements of the contemporary operation and management in modern power system. Aiming at this issue, many-objective power flow optimization problem, which more than three optimizing objective functions are considered, has become one of the most important research hotspots. This paper firstly build a mathematical optimizing model considering the economic, environmental, reliability and stability of the power system. Then, this paper proposes the improved MOEA/D-GRA algorithm, here noted as IMOEA/D-GRA, and applys it to solve the established manyobjective power flow optimization problems model. In the new algorithm, a new aggregate function is proposed to replace the original tchebyshev aggregate function, thus enhancing population diversity and accelerating searching convergence. In the new aggregate function, the vertical distance and horizontal distance between subproblem and the ideal point are equipped with weights which will vary with the evolutionary generation and then added together. Finally, IEEE30-bus system is utilized to confirm the superiority of IMOEA/D-GRA in solving manyobjective power flow optimization problems. The numerical results demonstrate its competitiveness for many-objective power flow optimization problems when it is compared with other algorithms.