Parallel Multi-population Improved Brain Storm Optimization with Differential Evolution strategies for State Estimation in Distribution Systems using Just in Time Modeling and Correntropy
| Autor: | Hisashi Fujimoto, Daichi Azuma, Yoshikazu Fukuyama, Akihiro Oi, Toru Jintsugawa |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Speedup Computer science Computation 020208 electrical & electronic engineering Storm 02 engineering and technology Evolutionary computation Nonlinear system 020901 industrial engineering & automation Differential evolution Outlier 0202 electrical engineering electronic engineering information engineering Algorithm Voltage |
| Zdroj: | SSCI |
| DOI: | 10.1109/ssci44817.2019.9002964 |
| Popis: | This paper proposes parallel multi-population improved brain storm optimization with differential evolution strategies (PMP-IBSODE) for state estimation in distribution systems (SEDS) using just in time (JIT) modeling and correntropy. SEDS is a function which estimates system conditions such as voltage and current everywhere in the distribution system using limited measurement data. When outliers, which are not true values, are measured at the measurement points, JIT modeling and correntropy can be effective. Moreover, application of evolutionary computation techniques is necessary for the SEDS considering of a nonlinear characteristic of an objective function caused by equipment in distribution systems. Various evolutionary computation techniques including IBSODE have been applied to the SEDS. However, speed-up of calculation and high quality estimation results are required because of penetration of renewable energies. An evolutionary computation technique using multi-population and parallel distributed computing is one of solutions for the challenges. The proposed method is verified to speed up computation time and obtain higher quality estimation results than conventional methods. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|