The rapid growth of the transmission networks has brought more uncertainties and new requirements in the transmission expansion planning (TEP) to the planners. The existing methods of solving TEP problem have a drawback since the DC load flow and the relaxed load flow models have been utilized to solve TEP problem. In this work, the TEP problem is solved based on mixed integer nonlinear non-convex programming model. A meta-heuristic algorithm by the means of differential evolution algorithm (DEA) is employed as an optimisation tool. An AC load flow model is used in solving the TEP problem, where accurate and realistic results can be obtained. Furthermore, the work considers the constraints checking and system violation such as real and power generation limits, possible number of lines added and bus voltage limits. The proposed technique is tested on Garver's 6 bus system and IEEE 24 bus system and has shown high capability in considering the active and reactive power in the same manner and solving the TEP problem. The method produced improved results for the test systems. In terms of minimising the cost and the solution quality, the proposed method obtained good and challenging results comparing to the previous works.

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As promising solutions to various social and environmental issues, the generation and integration of renewable energy (RE) into microgrids (MGs) has recently increased due to the rapidly growing consumption of electric power. However, such integration can affect the stability and security of power systems due to its complexity and intermittency. Therefore, an optimal control approach is essential to ensure the efficiency, reliability, and quality of the delivered power. In addition, effective planning of policies for integrating MGs can help promote MG operations. However, outages may render these strategies inefficient and place the power system at risk. MGs are considered an ideal candidate for distributed power systems, given their capability to restore these systems rapidly after a physical or cyber-attack and create reliable protection systems. The energy management system (EMS) in an MG can operate controllable distributed energy resources and loads in real-time to generate a suitable short-term schedule for achieving some objectives. This paper presents a comprehensive review of MG elements, the different RE resources that comprise a hybrid system, and the various types of control, operating strategies, and goals in an EMS. A detailed explanation of the primary, secondary, and tertiary levels of MGs is also presented. This paper aims to contribute to the policies and regulations adopted by certain countries, their protection schemes, transactive markets, and load restoration in MGs.

<p>With the rapid expansion of electricity grid, there yet still places to be covered considering their remote location. Micro-grid (MG) is a solution in this scenario, in fact, there is actually many cases where MG is used in case of emergency and act as a backup to the main electrical grid. By disconnecting itself from the larger grid, a grid that can have many problems, the micro-grid becomes much more flexible in its operations and by continuing to power households and communities alike. Besides grid-connected mode, it is necessary for the MG to operate in autonomous mode. By operating in islanded mode, micro-grids must be able to supply critical load without interruption, run at specific values for voltage and power and extract the maximum power from the distributed generations (DG). Therefore, the modeling of microgrid network considering solar photovoltaic(PV) and wind turbine generation (WTG) system as the distributed generation have been modeled using Matlab/Simulink in this research. Apart from that, the observation of total harmonic distortion(THD) between two operation modes of grid-connected and the islanded-mode is presented in order to analyze the power quality stability towards two operations MG network with same loads size and network parameters.</p>