An unequivocal normalization-based paradigm to solve multi-objective optimization problems-an engineering application

Abstract

This chapter presents a straightforward compromising methodology of dynamic economic and emission active-reactive optimal power flow (AROPF). AROPF considering environmental effects is a highly nonlinear problem, and the dynamic consideration of such problem makes it even more complicated and extra-high nonlinear; find an appropriate compromising solution for such problems is considered as a complicated task. On one hand, the traditional compromising methodologies cannot find an acceptable compromise point for large-scale systems, and on the other hand metaheuristic methods are time consuming. In this chapter an unequivocal normalizationbased paradigm (UNBP) is proposed, while instead of maximum output-based pollution control cost, an adaptive pollution control cost is used to consider the system topology in dynamic scheduling and under various system conditions such as normal, outage, and critical conditions. By using a normalization process and adaptive pollution control cost, a uniform compromising procedure is obtained. Three case studies such as 14-bus, 30- bus, and 118-bus IEEE test systems are conducted and results are compared to those reported in literature. Results confirm the potential, effectiveness, and superiority of the proposed UNBP compared to traditional and heuristic-based multi-objective optimization techniques.