الفهرس 
Chapter 1 INTRODUCTIONOnly 14 pages are availabe for public view
 |  | from | 170 |  |  |
| | | from | 170 | | |
Abstract
The transmission network expansion planning (TNEP) aims to determine
the transmission paths between substations (both existing and new) as well as their characteristics (voltage level, number of circuits, conductor type, and so on). In doing so, the investment and operational cost should be minimized with various constraints being met during normal conditions as well as contingency conditions.
This thesis presents a proposed procedure based on improved binary bat
algorithm (IBBA) for solving the transmission system expansion planning
(TSEP) problem. The proposed IBBA is applied to achieve the comprehensive
objective function with the lowest investment and operation costs by finding the optimal distributions of new transmission lines at different operating conditions.
The suggested operating conditions are the normal and the contingency such as
any single line outage (one by one). The AC optimal power flow (AC-OPF)
using MATPOWER is utilized to find the OPF calculations. The simulation
results are compared with other techniques to prove the robustness of the proposed procedure for solving the TSEP problem considering different technical and economic benefits.
This thesis uses IBBA for solving static and dynamic TNEP problems for
standard and realistic networks considering different objective functions (OFs). The proposed IBBA has two modifications to enhance the solution quality based on multi V-shaped transfer function and adaptive search space (ASS). The IBBA is applied to solve the static TNEP (STNEP) problem. Two-stage
procedures are employed to solve the dynamic TNEP (DTNEP) problem. In
stage-1, the adaptive neuro-fuzzy inference system (ANFIS) is utilized to find the long-term load forecasting (LTLF) up to 2039 based on the historical peak load data from 2009 to 2018. In stage-2, the IBBA is used for solving the DTNEP problem. The proposed static and dynamic TNEP problems aim to find the optimal number and locations of new transmission routes by optimizing two OFs to meet the forecasted peak load. The first OF aims to minimize the investment cost, while the second OF is to minimize the total costs which include investment cost, the total costs of energy losses and reactive power compensation (RPC) cost. The MATPOWER is utilized to find the OPF calculations. The numerical results of the proposed procedure are compared with other methods to show the superiority for solving TNEP problems.