Optimal microgrid controller design with energy storage optimization considering renewable energy grid integration

This thesis studied the optimal microgrid controller design with energy storage optimization considering renewable energy grid integration. The study presented an optimization technique to enhance the available local distributed energy resources and maximize the use of renewable energy resources. Kh...

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Bibliographic Details
Main Author: Praditpong Suksirithawornkul
Other Authors: Suttichai Premrudeepreechacharn
Format: Theses and Dissertations
Language:English
Published: เชียงใหม่ : บัณฑิตวิทยาลัย มหาวิทยาลัยเชียงใหม่ 2020
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Online Access:http://cmuir.cmu.ac.th/jspui/handle/6653943832/69768
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Institution: Chiang Mai University
Language: English
Description
Summary:This thesis studied the optimal microgrid controller design with energy storage optimization considering renewable energy grid integration. The study presented an optimization technique to enhance the available local distributed energy resources and maximize the use of renewable energy resources. Khun Pae Village in Chiang Mai Province, Thailand was utilized as the testbed location. As a reference, a microgrid simulation was carried out by HOMER Pro with black box code utilization. By comparing the obtained results with the economics of sensitivity analysis, the best possible scenario could be formulated for the hybrid microgrid connected to the main grid. This study proposed a new optimal microgrid controller dispatch using Heuristic, Modified Heuristic and Dynamic Programing techniques to replace the existing HOMER Pro scheme to identify the minimized Net Present Cost (NPC) and Cost of Energy (COE). The results showed that the NPC and COE based on the proposed techniques provided lower costs than HOMER Pro Load Following. In this study, the proposed optimization techniques provided smoother and lower operating costs, as well as annual throughput to extend battery lifetime and the capacity to supply the predicted long-term and mid-term loads for the testbed location.