DYNAMIC ECONOMIC DISPATCH USING MODIFIED BACTERIAL FORAGING ALGORITHM ORIENTED WITH WEIGHTED PARTICLE SWARM OPTIMIZATION | ||||
| ERJ. Engineering Research Journal | ||||
| Article 4, Volume 39, Issue 1, January 2016, Page 23-33 PDF (886.59 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/erjm.2016.66372 | ||||
 View on SCiNiTO | ||||
| Author | ||||
| Ehab E. Elattar | ||||
| Department of Electrical Engineering, Faculty of Engineering, Menoufia University, Shebin El-Kom, Egypt | ||||
| Abstract | ||||
| The goal of dynamic economic dispatch (DED) is to minimize the total operating cost of all committed generating units considering all physical and operational constraints. The DED problem is very complicated nonlinear optimization problem due to transmission losses, ramp-rate limits and valve-point effects constraints. Both bacterial foraging algorithm (BFA) and particle swarm optimization (PSO) methods have poor convergence characteristics. So, weighted PSO (WPSO) is employed to avoid the drawbacks of original PSO by employing the adaptive inertia weight factor. In this paper, modified BFA (MBFA) oriented with WPSO method is proposed by integrating MBFA and WPSO. By combining these two algorithms, the advantages of both of them can be extracted. This leads to get better solution of DED problem. Also, the diversity strategy is used in the proposed algorithm to solve the problem of early convergence. To prove the efficiency of the proposed method in solving the DED problem, different systems are employed. The obtained results prove the efficiency of the proposed method when comparing with other state of the art methods. | ||||
| Keywords | ||||
| Modified bacterial foraging algorithm; weighted particle swarm optimization; diversity strategy; dynamic economic dispatch; ramp-rate constraint | ||||
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