A Multi-objective PSO (MOPSO) algorithm for optimal active power dispatch with pollution control

A Multi-objective PSO (MOPSO) algorithm for optimal active power dispatch with pollution control

Govind D. Sen Jitendra Sharma  Govind R. Goyal  Alok K. Singh 

Jaipur Institute of Technology, Jaipur 302037, India

Vivekananda Global University, Jaipur 303012, India

Corresponding Author Email: 
30 September 2017
| Citation



This article provides the solution of the optimal power flow (OPF) problem of medium electrical systems through an artificial intelligence algorithm. The goal is to minimize the total cost of generated fuel and environmental pollution caused by power generation units based on fossils. System performance is also maintained by limiting generator real and reactive power outputs and power flow of transmission lines in acceptable limits. The power flow equations and load balance equation are considered as equality constraints. The performance analysis of this OPF problem using the Particle Swarm Optimization technique is carried out by checking various combinations of values of the associated parameters. The biobjective problem of generation cost and emission dispatch is solved via weighted sum method for different combinations of weights and a multi-objective problem of minimizing power generation cost and flue gases (NOx, CO2, SO2), is solved by a new algorithm named as Multi-Objective PSO (MOPSO) technique, to find out optimal solution and optimal value of weights. Simulation results for the IEEE 30-bus network with 6 generators system show that by proposed method, an optimal solution can be given quickly.


Optimal Power Dispatch, Swarm Intelligence, Particle Swarm Optimization (PSO), Multi-objective PSO

(MOPSO), Pareto- front Technique

1. Introduction
2. Problem Formulation
3. Multi-Objective Particle Swarm Optimization
4. Simulation Study & Results
5. Conclusion

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