| Author: | Tong, Zhou |
| Title: | Optimal dispatch for integrating renewable energy to the grid |
| Degree: | M.Sc. |
| Year: | 2013 |
| Subject: | Electric power systems -- Mathematics Hong Kong Polytechnic University -- Dissertations |
| Department: | Faculty of Engineering |
| Pages: | x, 59 leaves : ill. ; 30 cm. |
| Language: | English |
| Abstract: | The widely installed smart meters make demand responsive more feasible to the changes in supply capacity. These responsive loads will have increasingly significance in electric power system, as renewable energy has accounted rising proportion of electricity generation. Due to the variability of renewable energy, the flexible energy system with the ability to balance the supply and demand is necessitated. The algorithm incorporated in the system used to plan optimal dispatch should also include relevant factors. As electricity market has been created in many countries, real time pricing are piloted in many regions. This will definitely aid to the implementation of load management, so the conventional dispatch algorithm should be reformulated. In this dissertation, the incremental fuel cost of various generation sources will be reviewed first. Different economic dispatch methods will then be discussed and relevant analyses as well as comments are also given. Genetic algorithm is selected as the algorithm to solve the dispatch problem in this dissertation as it's much more suitable to solve real-time case. On the basis of hybrid energy system, wind prediction and demand response will be discussed in detail. The load management profile integrated economic dispatch and load management profile integrated environment dispatch will then be analyzed. The Matlab genetic optimal tool box is used to stimulate the case. The result will be generalized and presented. They will then be compared with different levels of load management. Finally the multi-objective sense will be proposed in order to pave the way to the EED problems. Pareto-front curve will be plotted with Matlab toolbox. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b26493111.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 2.59 MB | Adobe PDF | View/Open |
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