A New Approach to Environmental Economic Dispatch Using Multiobjective Differential Evolution: A Case Study

In electricity generation systems, problems related to economic and environmental dispatch represent potential for improvement in generating plants. The Environmental Economic Dispatch (EED) consists of minimizing the cost of generation and emission of pollutants such as CO2, SO2 and NOx. In addition to possible financial benefits, addressing economic and environmental aspects can also generate a business competitive advantage. The EED problem comprises a multi-objective optimization challenge in power plants and various approaches have been developed to formulate and solve this problem. Problems associated with EED generally adopt quadratic functions to directly relate cost and emissions to generation power. This paper presents a new modeling approach which consists of using a hyperbolic function to predict generation costs. This new approach was applied together with the Differential Evolution Algorithm in two case studies which comprise a real thermal power plant with ten generating units and an IEEE test system with thirteen generating units. The results obtained were compared with the application of the quadratic function, showing that the new approach successfully solves the multi-objective EED problem, providing better results.