Economic Dispatch Planning Based on Considerations of Renewable Energy and Carbon Emissions

• Main Authors: Tai-Hsien Huang, 黃岱嫻
• Other Authors: Ming-Tse Kuo
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/kz3rcy

碩士 === 國立臺灣科技大學 === 電機工程系 === 107 === With the development of economy ,science and technology, human beings enjoy the modern technology life while causing many damage to the environment. How to balance environmental protection and economy is a major issue for all countries. The government of the Republic of China has set many goals and norms for the development of renewable energy. More green energy power plants are Expected to establish in 2025 to achieve the ultimate goal of reducing thermal power generation and energy transformation to non-nuclear homes. However, green energy has a higher cost problem, and thermal power generation is cheap but has excessive carbon emissions. Therefore, this thesis aims to simulate the power dispatching plan by using simulated annealing (SA) method and interactive best-compromise method under the climatic environment and load demand in the 2025. The goal of minimizing power generation costs, reducing carbon dioxide emissions, and increasing the proportion of green energy generation will be achieved. This thesis uses the generator systems in 2025 and uses the existing firepower, solar power, wind power and the other power plants in Taipower system for simulation. First, the mathematical cost model of power generation and carbon emission is proposed for units with different power generation modes. The experiments are then divided into two parts. The first part is an example of using a neural network to predict temperature. It proves that the prediction results of the neural network are extremely accurate. Then, based on historical data, the daily radiation, wind speed and load forecast in 2025 are predicted, and the simulated background environment in 2025 is as much as possibly predicted. The second part is to find a balanced compromise solution by using SA method combined with interactive best-compromise method. How to schedule various units under peak, half-peak, and off-peak load requirements in 2025 is simulated and 24-hour load planning of one day is added. The purpose of both environmental protection and economy can effectively achieved by using the scheduling methods of this thesis.