A Process Integration Technique for Targeting Hybrid Power Systems

• Main Authors: Chieh-Ting Lai, 賴玠廷
• Other Authors: Cheng-Liang Chen
• Format: Others
• Language: zh-TW
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/93698370525896376588

博士 === 國立臺灣大學 === 化學工程學研究所 === 104 === In recent years, renewable energy (RE) has been proposed to address global warming and energy shortage problems. However, to solve the discontinuity and unpredictability of RE, researchers and industries problems have integrated RE with public grid electricity to develop a hybrid power system (HPS). This study applies mathematical programming (MP) to the design of HPS to find the optimal targets and power distribution, which includes the minimum electricity outsourced from the grid and the minimum capacity for electricity storage. Two mathematical models—condensed transshipment model (CTM) and expanded transshipment model (ETM)—are developed to solve HPS optimization problems by making use of the design concept of traditional chemical heat exchanger networks (HEN''s). ETM is divided into two categories: those with single storage equipment (ETM1) and those with multiple equipment (ETM2). Two types of HPS are considered in this study: those involving no electricity loss (the ideal type) and that involving three types of loss (charging/discharging electricity loss, and self-discharging loss). Recently, many researchers use power pinch analysis (PPA) method to solve HPS optimization problems. This method uses a tremendous amount of procedures to calculate physical quantities, which renders this method complicated and time-consuming. To deal with the disadvantages of PPA, this article considers all the supply electricity routes in CTM and ETM, and establishes mathematical models using mathematical programming (MP). With the construction of CTM and ETM models in General Algebraic Modeling System (GAMS), the optimized results of HPS can be obtained nearly instantly, indicating the indispensability of MP. Adjusting the parameters of ETM2, we can consider different types of energy storage devices (e.g.: battery, reservoirs, etc.) and different types of public grids in HPS, in which the costs of energy and equipment can be analyzed for later design. Most parameters in this article—including charging and discharging recovery ratios, and self-discharging recovery ratios—are assumed to be constant. In the future research, these parameters can be thought to be variables to establish a more complete HPS.