الفهرس 
The Transition to Smart Grid
Modelling of Domestic LoadsOnly 14 pages are availabe for public view
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Abstract
In future SG, DP will represent an important solution for uncertainties and fluctuations of the electricity generation and load demand. The main objective of this thesis is to develop an advanced and simple optimization approach to implement an effective DP methodology for DSM within SG environment and to evaluate the effectiveness of DP over the whole system. There are many optimization methods, which consume large time when dealing with the complex power system’s problems. For instance, the numerical integration methods require time-consuming procedures, while the evolutionary computation needs repeating the calculations a huge number of times. This would make the method ineffective and unsuitable for real time implementations. Thus, a proposed composite technique is developed depending on particle swarm optimization (PSO) technique with a heuristic algorithm. In this algorithm, the focus is on generating a generalized set of equations that directly define the best solution in an accurate and rapid manner under any condition. The developed algorithm is designed according to three phases. The first focus of this thesis is to design an AC-OPF using PSO to define the network sensitivity to demand at each load centre. The optimal power flow (OPF) and the sensitivity factors are used with a heuristic algorithm to determine the best and critical demand responses at each load centre. To make the proposed algorithm more effective and less time-consuming, a generic set of formulas is developed based on a composite PSO-heuristic optimization technique.