A Study of Power System Capacity Expansion under Limitation of GreenhouseGas Emission - Applying Harmonic Search Algorithm

• Main Authors: Kai-Ping Hsu, 徐開評
• Other Authors: Mei-Shiang Chang
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/99629192636501919264

碩士 === 中原大學 === 土木工程研究所 === 97 === Abstract The raising price of fossil fuels, the uncertainty of power demand and supply in future, and the international limitation of greenhouse gas emission by Kyoto Protocol prompt people to face the problem of transferring the structure of power system. Non-polluted or Low-polluted power generating should replace high-polluted one in the long run. However, it will take ten to fifteen years to adjust the structure of energy systems and industrial strategies because of much uncertainty. This thesis proposes a time-dependent stochastic programming model to formulate the power expansion problem under limitation of greenhouse gas emission. The uncertainty of producing cost, green power supply, and regional electric loads in future can be considered simultaneously. By using scenario analysis to present environment parameters, we can determine the appropriate capacity allocation among different methods of power generation, such as thermal power generating, hydraulic power generating, nuclear power generating, and wind power generating. Because this problem is NP-hard, this study develops a meta-heuristic algorithm based on harmony search to solve it. Several numerical examples are utilized to demonstrate the validness of the developed algorithm. The parameter analysis of this harmony search-based algorithm is done to increase the quality and the speed of searching processes. Sensitivity analysis is performed to understand the influence of increasing the renewable power generation, and decreasing the capacity of high-polluted electric generating sets. Finally, some conclusions and suggestions are provided according to the testing results.