Optimal procurement of energy and ancillary services in smart grid | |
| Author | Do Quang Viet |
| Call Number | AIT Thesis no.ET-18-08 |
| Subject(s) | Smart power grids Electric power |
| 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 | From the depletion of non-renewable energy resources, climate change issues and increased energy demand, this time is the age of renewable energy resources, sustainable energy technology and efficient techniques should be focus and invented. The advancement of technology has been bringing a flexible of load in the distributed network, increasing many distributed generation, new operation methods for small generation and demand thereby transfer the traditional network to more active than ever. The integration and coordination of the electrical grid and information network has made power system intelligent. However, this threatens the stability, economics and pollution of existing power infrastructures and new equipment will be plus. In this context, this thesis suggests a model to deploy Electric Vehicles through their bidding price inactive distribution network. The participation of Electric Vehicles, Distribution Generations, Demand Response Program would solve the uncertainty output power of Renewable Energy Sources with include Wind and Solar. This work used three scenarios to analysis the proposed methodology as follow: The first scenario only uses traditional Distribution Generations to minimize the energy cost, ancillary service cost, start-up cost and emission of greenhouse gases. In the second scenario, this work implemented the Demand Response Program for the purpose to supply energy and ancillary services, and along reduce the emission. In the final scenario, this work deploys the Aggregators of Electric Vehicles to flatten load pattern and supply a source/load/storage dynamic device for network to support ancillary services and reduce emission of greenhouse gases. In this thesis, the proposed problem formulations are considered with the best optimal of 24 hours’ period along with individual hours. On the other hand, this work suggest a way to determine the energy and reserve prices depending upon characteristics of battery, e.g., State of Charge, Depth of Discharge and cost of charging affected by the behavior of customer and capability of EVs. The problem formulations, as cost minimization, is solved by Binary Particle Swarm Optimization for optimal operation cost and emission in the network. The result shows that the participation of Demand Response Program and Electric Vehicles have an efficiency to reduce operation cost and also emission of greenhouse gases. |
| Year | 2018 |
| 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) | Kumar, Sivanappan;Weerakorn Ongsakul |
| Scholarship Donor(s) | Electricity of Vietnam (EVN) |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 2018 |