Load Prediction and Contract Capacity Optimization Research
| Autor: | Yu-Hsin Hung, 洪鈺欣 |
|---|---|
| Rok vydání: | 2011 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 99 In Taiwan, most industrial and commercial enterprises sign power contracts with Taiwan Power Company. Problems occur when deciding the capacity in contracts: the high power capacity leads to increase of total electronic consuming cost. However, if the power capacity is set low, consumers run the risk of high penalty when the actual consumption exceed. The aim of this thesis is to optimize power demand for Taiwanese industries through the model of forecast and optimization. This thesis presents a new combination method by using particle swarm optimization (PSO) to forecast the load capacity, and control uncertainty of forecasting with stochastic simulation. Then optimize the capacity of contract with the improved particle swarm optimization by query based learning (QBLPSO) [1] algorithm. There are two main purposes in this thesis. First, the proposed method will be compared with the other methods, and we analyze separately the forecast and optimization. Second, we make decision analysis framework for determining the optimal power contract capacity and an empirical study in real cases, which included the industry, the commerce. The load forecast has about 90% of accuracy in government units, 92% of accuracy in commerce, 90% of accuracy in manufacturing industry, and 85% of accuracy in service industry. And optimization model help user to save about $195,374 in government units, $4,031 in commerce, $30,978 in manufacturing industry, and $39,905 in service industry. Therefore, the result of experiment explain that this proposed method can help user efficiently to make appropriate contract capacity. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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