الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
 |  | from | 50 |  |  |
| | | from | 50 | | |
Abstract
Economic dispatch (ED) is an essential part of any power system network. ED is how to schedule the real power outputs from the available generators to get the minimum cost with satisfying all constraints of the network. Also it can be explained as allocating generation among the committed units with the most effective minimum way in accordance with all constraints of the system.
There are many traditional methods for solving ED as the Newton-Raphson Method, Lambda-Iterative technique, Gaussian-Seidel Method, etc. All these traditional methods need the generators’ incremental fuel cost curves to be increasing linearly. But practically the input-output characteristics of a generator are highly non-linear. This causes a challenging non-convex optimization problem. Recent techniques like Genetic Algorithms (GA), Artificial Intelligence (AI), Dynamic Programming (DP) and Particle Swarm Optimization (PSO) solve nonconvex optimization problems in a powerful way and obtain a rapid and near global optimum solution.
In addition, there’s another important parameter that must be taken into considerations which is emissions. Electricity generation is recognized as the second largest share in greenhouse gas emissions by Environmental Protection Agency (EPA). While transportation sector generates the largest share of greenhouse gas emissions. So strict action plans have been implemented by the government to reduce those emissions. Subsequently, the global warming will decrease and we will maintain the existence of all the human beings. Renewable energy resources as wind and photovoltaic have been a promising option due to the environmental concerns as the fossil fuels reserves are being consumed and fuel price increases rapidly and emissions are getting higher. Therefore, the world tends to replace the old power stations into renewable ones or hybrid stations. This leads the problem to be converted to Combined Economic and Emission Dispatch (CEED) problem.
In this thesis, the operation of electrical power networks is enhanced by CEED. Firstly, An ED problem is solved using various techniques as Particle Swarm Optimization (PSO), Sine-Cosine Algorithm (SCA), Whale Optimization Algorithm (WOA) and Archimedes Optimization Algorithm (AOA). The results are compared. Moreover, case studies are executed using a Photovoltaic-based Distributed Generator (PV based DG) on the IEEE 14 bus system. The results are observed. Afterwards, a CEED problem is solved using the mentioned previously techniques Which are PSO, SCA, WOA and AOA. The results are compared. Moreover, case studies are performed to examine each type of emission and the effect of concentrating on the weight of this type on the multi-objective function. All the analyses are performed on MATLAB software.