Method for a Parallel Solution of a Combined Economic Emission Dispatch Problem

The power system simulation software tools are traditionally designed for serial codes and optimized using single-processor computers. They are inadequate in terms of computational efficiency and execution time for the ever-increasing complexity of the power grid. Due to the above-mentioned sequential computing demerits, this paper used MATLAB data parallelism message passing interface software to execute the Lagrange's and Particle Swarm Optimization (PSO) algorithms in parallel with multiple processor units with different and large data sets for the solution of the Combined Economic Emission Dispatch (CEED) problem. The two important advantages of using parallel computing approach to solve the power system economic dispatch problem are 1) to increase the efficiency (solution quality) and 2) to reduce the execution time (speed-up) of the parallelization process for the CEED problem solution. The comparison between the Lagrange's and PSO data-parallel solution quality and execution time is presented for the CEED problem for Institute of Electrical and Electronic Engineers (IEEE) 30 bus and IEEE 118 bus systems. The paper contributes to the on-line real-time market analyses of the deregulated power system, which need improved solution quality and a fast computation process to solve the power system energy management (CEED) problems for proper discussion and decision making at the control center level.