Optimal scheduling of active distribution network considering DG placement, network reconfiguration and electric vehicles | |
| Author | Paudel, Amrit |
| Call Number | AIT Thesis no.ET-16-12 |
| Subject(s) | Electric vehicles--Power supply Electric power distribution |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Energy |
| Publisher | Asian Institute of Technology |
| Abstract | Recent advances in electric utility sector shows that it is beneficial to inject the power and store energy at the distribution levels. But non-optimal placement of distributed generations may adversely affect the distribution system performance. So, distributed generations should be installed optimally. Electric Vehicle (EV) which is becoming another important component of power system network and considered as flexible loads since batteries can be used for energy storage. The economic scheduling of smart distribution network should be determined in the presence of distributed generations and electric vehicles in the form of Mobile Energy Storage System (MESS), where each of them can participate in market as independent power producer by submitting their own bid rather than centrally controlled by distribution system operator. A hybrid GA/PSO-TVAC algorithm is developed and applied to determine the optimal DG location and size along with network topology to reduce power losses and improve voltage profile. Simulations are carried out in different scenarios such as only the reconfiguration of the system, sole installation of DGs, optimal placement and sizing of DGs after network reconfiguration, reconfiguration after optimal placement of DGs, and optimal placement of DG & reconfiguration simultaneously. The simulation results show that simultaneous reconfiguration and DG placement is superior to improve the network performance. The power loss reductions after installation of type I DG together with network reconfiguration are 73.91% and 85.06% in 33-bus and 69-bus distribution network respectively, which is better than the reduction achieved from the CSA in both cases. Also, after installation of type II DG in the same scenario, power loss reductions are 93.7% and 98.21% in 33-bus and 69-bus network respectively. Moreover, voltage profiles are improved significantly in all scenarios as compared to the base case profile. An economic operational schedule for active distribution network is strategically developed without violating any of the DG constraints, network constraints and EV constraints using PSO-TVAC. In nutshell, a hybrid GA/PSO-TVAC is efficient to solve the optimal DG placement problem along with network reconfiguration. The scheduling of ADN with EVs and DGs participation is very important from smart grid implementation perspective. |
| Year | 2016 |
| 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) | Weerakorn Ongsakul |
| Examination Committee(s) | Singh, Jai Govind;Dhakal, Shobhakar |
| Scholarship Donor(s) | Thailand (HM Queen) |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 2016 |