الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
The scarcity of transmission capacity leads to congestion or potential overloading. In spite of the efforts made to create an open, free market, electric power companies still have to cope with the transmission congestion problem. In the new competitive electricity market, maintaining the physical flow of electricity, satisfying consumer’s demand at proper voltage and frequency level, maintaining security, economy and reliability of the system, ensuring proper protection, control and all measures for the proper functioning of the system are treated as separate ancillary services. Ancillary Services in deregulated power system are those services performed by generators, transmission and control equipment, which are necessary to support basic services and to maintain reliable operations and system security. Load following is considered to be an ancillary service in a deregulated power system. Instant adjustment of the generation to track the fluctuations between the power supply and demand so that the system is in perfect balance is called regulation or load following. In this thesis, a proposed procedure is presented to solve the economic power dispatch problem using multi-objective fruit fly optimization (MO-FOA) algorithm as modern optimization technique. The objective function is to minimize the non-linear generation cost function with the valve-point effects that appears in a rectified sinusoidal function introduce ripples in the heat-rate curves, by optimizing the control variables of the generators active power under equality and inequality constraints. The amount of emitted pollutants in the power system cannot be ignored and must be minimized simultaneously with the reduction of fuel cost. As a result the economic dispatch (ED), it becomes a multi-objective problem. The optimal power flow (OPF) problem is solved using modern optimization techniques such as the differential evaluation algorithm (DEA), particle swarm optimization (PSO) and fruit fly optimization algorithm (FOA) algorithm. Different objective functions (OFs) are optimized such as: minimization of production fuel cost, power loss minimization, voltage deviation reduction and preserving generation emission at the lowest levels. However, the multi-objective function is used to optimize all these objectives, simultaneously. Solving the OPF problem aims to optimize the previous objectives and setting the optimal control variables, while all system constraints are satisfied. The comparisons between the obtained results using the proposed algorithm and other optimization methods either in economic dispatch problem or in optimal power flow problem show the capability and effectiveness of the proposed MO-FOA and FFOA algorithms. The proposed procedures are applied to IEEE 30-bus standard test system and ten units generating system.