Name
Abstract | ||
|---|---|---|
This paper proposes an improved bat algorithm to solve multi-objective optimal power flow problem (MOPF) based on the weighted method. The MOPF problem is formulated as a non-linear constrained optimization problem where two objective functions (minimization of fuel cost and emission) and various constraints are considered. After having found the Pareto solutions with the improved bat algorithm, the fuzzy set theory is used to find the compromise solution. Finally, the IEEE 57-bus system is applied to verify the performance of the proposed method for the MOPF problem. The results are compared with those obtained by the state-of-the-art optimization algorithms reported in literature. The simulation results demonstrate the superiority of the proposed method for solving the MOPF problem in terms of solution quality. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/s10489-017-1081-2 | Appl. Intell. |
Keywords | Field | DocType |
Bat algorithm,Multi-objective optimization,Optimal power flow,Fuzzy logic | Mathematical optimization,Power flow,Bat algorithm,Computer science,Fuzzy logic,Fuzzy set,Multi-objective optimization,Minification,Fuel cost,Pareto principle | Journal |
Volume | Issue | ISSN |
48 | 8 | 0924-669X |
Citations | PageRank | References |
0 | 0.34 | 13 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yanbin Yuan | 1 | 0 | 0.34 |
| Xiaotao Wu | 2 | 6 | 1.45 |
| Pengtao Wang | 3 | 0 | 1.01 |
| Xiaohui Yuan | 4 | 36 | 4.61 |