dc.contributor.authorZhang, Lingxi
dc.date.accessioned2017-08-30T06:17:33Z
dc.date.available2017-08-30T06:17:33Z
dc.date.issued2017
dc.identifier.urihttp://hdl.handle.net/10356/72610
dc.description.abstractIn recent years, energy supply from renewable energy sources (RESs) is a main trend towards future smart grid. Many countries including Singapore have increased their energy supply from RESs. However, power fluctuation can become more severe and unpredictable with the increase of RESs, which brings risk to the stability and reliability of power systems. To address the problem, more battery energy storage systems (BESSs) are connected to modern power systems. The optimal power coordination among different energy resources considering lifespan of BESSs is crucial. The author first establishes a state space model for the aging effect of lithium-ion battery. The effect of battery is later used as constraints for control. Then, the objectives are divided into two categories, long-time-scale and short-time-scale applications. The roles of BESSs in these applications are respectively investigated. For long-time-scale applications, peak load shifting is studied because it can save energy and reduce energy cost. For short-time-scale applications, the author focuses on real-time power balancing and power smoothing. There are two kinds of approaches, conventional PI (proportional–integral) controller and MPC (Model Predictive Control). They are studied and simulated separately. Finally, the comparison between them demonstrates the advantages of the proposed MPC approach. The key idea of this dissertation is to maintain system stability according to the swing equation. Meanwhile we keep batteries in the optimal status. The significance of this study can be summarized as the pursuit of secure and economical operation of a power system. Key words: BESS, battery aging effect, MPC, load frequency controlen_US
dc.format.extent70 p.en_US
dc.language.isoenen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen_US
dc.titleModel predictive control based optimal energy management considering the effect of battery agingen_US
dc.typeThesis
dc.contributor.supervisorGooi Hoay Beng (EEE)en_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMSC(POWER ENGINEERING)en_US


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