Secara konvensional, penjanaan tenaga elektrik membawa jumlah besar pelepasan
karbon dioksida. Pembinaan loji kuasa untuk memenuhi permintaan elektrik disebabkan
oleh industrilization dan pembandaran akan membawa perubahan iklim. Untuk
menangani krisis tersebut, teknologi elektrik mesti seiring dengan kemajuan teknologi
terkink. Grid pintar boleh ditakrifkan sebagai grid kuasa yang boleh mengesan dan
bertindak balas terhadap keubahan tempatan dan membolehkan komunikasi dua hala
antara syarikat utiliti dan grid. Tesis ini bermula dengan menyediakan latar belakang
penyelidikan yang termasuk struktur sistem kuasa, kaedah analisis sistem kuasa dan
kebolehpercayaan sistem kuasa dalam bab 1. Seterusnya, IEEE standard 738, simulasi
Monte Carlo dan analisis aliran kuasa Optimum telah dikaji dalam bab 2. Dalam bab 3,
metodologi yang digunakan dalam tesis ini dijelaskan dengan terperinci. Contohnya
simulasi Monte Carlo, kebolehpercayaan Dynamic Thermal System (DTR) dan analisis
sensitiviti bagi sistem DTR. Selepas itu, analisis menggunakan kaedah yang dicadangkan
dan membuktikan bahawa sistem DTR mampu meningkatkan kebolehpercayaan sistem
kuasa dengan mengurangkan Expected Energy Not Served (EENS). Tambahan pula,
didapati bahawa ujian Reliability Test Network (RTN) indeks kebolehpercayaan biasanya
tidak sensitif terhadap kebolehpercayaan sistem DTR. Akhir sekali, kesimpulan dibuat
dan kerja masa depan dicadangkan dalam bab 5.
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Conventionally, generation of electrical energy comes with a large amount of
carbon dioxide emission. The unceasing construction of power plant to meet the demand
due to industrialization and urbanization will inexorably lead to climate change. To
mitigate the crisis, the current electrical technology has to keep pace with the
advancement of smart grid technology.Smart grid technology can be defined as the power
grid that can detect and react to local changes and allow two-way communication between
the utility company and the grid. This thesis begins by providing the research background
that includes structural of the power system, the method of power system analysis and
power system reliability in chapter 1. Next, IEEE 738 standard, Monte Carlo simulation
and Optimum power flow analysis have been reviewed in chapter 2. In chapter 3, the
methodology used in this thesis is explained in detail such as sequential Monte Carlo
simulation, reliability impact of Dynamic Thermal Rating system(DTR) and sensitivity
analysis for DTR system. Thereafter, the analyses are performed by using the proposed
methodology and proved that DTR system is able to improve the reliability of power
system by reducing Expected Energy Not Served (EENS). Furthermore, it was found that
Reliability Test Network(RTN) reliability indices are normally not sensitive toward the
reliability of the DTR system. Lastly, a conclusion is made and future work is suggested
in chapter 5
Reliability impact of dynamic thermal rating system on power system / Lai Lik Chin