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http://hdl.handle.net/10603/479606
Title: | Electricity generation expansion Planning with optimum cost and Minimum carbon emission for Power industry |
Researcher: | AMOSEDINAKARAN S |
Guide(s): | MALA, K |
Keywords: | Engineering and Technology Engineering Engineering Electrical and Electronic Socio-Economic Growth Electricity Demand Generation Expansion Plannin |
University: | Anna University |
Completed Date: | 2022 |
Abstract: | Electricity is an essential part for sustained socio-economic growth of any developing county like India. It is a primary input for residential, commercial and industrial applications. Similarly, Electricity Demand Forecasting (EDF) and Generation Expansion Planning (GEP) are essential for the power systems. EDF problem is vital for an electrical utility to formulate power generation policy to meet the demand accurately. GEP intends to find the types, capacity, place, operating time of new power plants along with existing power plants to satisfy the growing demand. Nowadays, the integration of Renewable Energy Sources (RES) such as wind and solar power plants has attained more attention. The objectives of GEP problem are minimization of generation cost, minimization of CO2 emission and maximization of reliability. The GEP problem becomes non-linear, large-scale, mixed variable and discrete. Hence, the optimization techniques or software are required to solve the problem. newlineIn this study, the power generating system of Tamil Nadu, a state in India, has been taken as the test system. In Tamil Nadu, the electricity demand is increased from 704 megawatts (MW) during 1980 to 15,673 MW during 2018, with the annual growth rate of 8.5%. A huge addition of new generating capacity is required to meet the increasing demand. Moreover, the optimal EDF and GEP are required. These optimal plan should consider both qualitative and quantitative factors such as minimized error, minimized cost and maximized reliability. The aim of this study is to develop and solve the mathematical models of EDF and GEP problems using the optimization algorithms. newline newline |
Pagination: | xxvi,193p. |
URI: | http://hdl.handle.net/10603/479606 |
Appears in Departments: | Faculty of Electrical Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 21.85 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 11.78 MB | Adobe PDF | View/Open | |
03_content.pdf | 1.41 MB | Adobe PDF | View/Open | |
04_abstract.pdf | 1.85 MB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 9.83 MB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 6.38 MB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 2.68 MB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 4.65 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 5.84 MB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 5.08 MB | Adobe PDF | View/Open | |
11_annexures.pdf | 11.98 MB | Adobe PDF | View/Open | |
80_recommendation.pdf | 92.62 kB | Adobe PDF | View/Open |
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