A multi-objective approach to allocate distributed generations in balanced and unbalanced distribution networks by using ant lion optimizer | |
| Author | Tong Menghour |
| Call Number | AIT Thesis no.ET-19-05 |
| Subject(s) | Distributed generation of electric power Ant lions Electric networks |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Energy, School of Environment, Resources and Development |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. ET-19-05 |
| Abstract | The distributed generation (DG) has become crucially important for the distribution system due to the massive increase in energy demand and the tremendous benefits offered from DGs in technical and economical aspect. The overall voltage and losses in the network profoundly affected by the capacity and location of the connected DGs. In this thesis work, a novel optimization algorithm named Ant Lion Optimizer was applied to figure out the optimum capacity and connected location of multiple distributed generators in both the balanced and unbalanced distribution system. The ALO and direct load flow for balanced system have been entirely programmed in Matlab and implemented on different scale of balanced distribution systems including IEEE 33,69 and 118 bus. While an open source software (OpenDSS) was utilized for three-phase unbalanced load flow and interchange data between Matlab through Component Object Model (COM) interface to solve the allocation of multiple distributed generations into the three-phase unbalanced distribution system including IEEE 13, 37 and 123 bus. Three main objectives for this study consists of power loss minimization, bus voltage enhancement and voltage stability improvement with respect to the system operational constraints. In addition, fuzzy logic theory has been applied to select the best compromise solution from the Pareto optimal solutions. The simulation results have been compared with others well-known algorithm to demonstrate its effectiveness in finding the optimal solutions and prove its superiority over the other algorithms. The obtained results from ALO confirm its dominance in term of power loss reduction, bus voltage improvement and voltage stability enhancement with different types and scale of distribution systems |
| Year | 2019 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. ET-19-05 |
| Type | Thesis |
| School | School of Environment, Resources, and Development (SERD) |
| Department | Department of Energy and Climate Change (Former title: Department of Energy, Environment, and Climate Change (DEECC)) |
| Academic Program/FoS | Energy Technology (ET) |
| Chairperson(s) | Singh, Jai Govind; |
| Examination Committee(s) | Weerakorn Ongsakul;Attaphongse Taparugssanagorn; |
| Scholarship Donor(s) | Deutscher Akademischer Austausch Dienst (DAAD) Germany;Asian Institute of Technology Fellowship; |
| Degree | Thesis (M. Eng.) - Asian Institute of Technology, 2019 |