Economic/Environmental Optimal Power Flow Using a Multiobjective Convex Formulation

This paper addresses the problem of economic/environmental optimal power flow with a multiobjective formulation using a second-order conic programming (SOCP) optimization model. This problem formulation considers renewable energy sources (RES), fossil-fuel-based power generation units, and voltage control. The proposed SOCP model is a stochastic scenario-based approach to deal with RES and load behavior uncertainties. An e-constrained algorithm is used to handle the following three objective functions: (1) the costs of power generation, (2) active power losses in the branches, and (3) the emission of pollutant gases produced by fossil-fuel-based power generation units. For comparative purposes, the SOCP model is also presented using a linearized formulation, and numerical results are presented using a 118-bus system. The results confirm that changing the energy matrices directly affects the cost of objective functions. Additionally, using a linearized SOCP model significantly reduces reactive power violation in the generation units when compared to the nonlinearized SOCP model, but also increases the computational time consumed.

Automated summary

This paper proposes a multiobjective economic/environmental optimal power flow problem using a second-order conic programming (SOCP) model. It considers renewable energy sources, fossil-fuel-based power generation units, and voltage control. The proposed SOCP model adopts a stochastic scenario-based approach to deal with uncertainties in renewable energy sources and load behavior. The results show that the change in energy matrices directly affects the cost of objective functions, and using a linearized SOCP model reduces reactive power violation but increases computational time.