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Abstract: 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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1 Introduction
In recent years, electric power systems have turned into highly complex interconnected systems. To cater to this growth, transmission expansion planning (TEP) is vital and priority for the system planners. Generally, the TEP problem is a large scale of mixed integer non-linear and non-convex optimisation problem. The well planning of the transmission system is the main factor which can lead to power system adequacy and security. The main objective of transmission planning is to decide when, where and what kind of reinforcement should be installed to meet the future operational conditions that requires tedious and complex computational process.
Latorre et al.[1] classified the models commonly used in the process of TEP, development and improvements. This process can be done via three kinds of methods as follows:
Mathematical optimisation models: This kind of models has always been used to solve the optimisation problem such as TEP. Traditionally, they search for an optimal expansion plan by using a calculation procedure that solves the mathematical formulation of the planning problem....