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This paper proposes a new methodology to solve the transmission expansion planning (TEP) problem based on relaxed N-1 criteria. An optimization technique is used to determine the best TEP plans through an adaptive multi-operator evolutionary approach. These plans are obtained by ensuring the N-1 security criterion and also relaxing it to accept pre-specified levels of equipment overload. The major...
This paper presents a methodology for assessing the reliability indices for composite generation and transmission systems based on Support Vector Machines (SVM). The importance of SVMs is its high generalization ability. The SVMs are used to classify data into two distinct classes. These can be named positive and negative. Thus, the basic idea is to classify the system states into success or failure...
This paper presents a new approach to assess reliability indices in composite generation and transmission systems, considering high penetration of renewable energy. The main idea is to combine a Cross-Entropy (CE)-based optimization approach and quasi-sequential Monte Carlo simulation (MCS) to obtain an auxiliary sampling distribution, which can minimize the variance of the reliability index estimators...
This paper proposes a methodology to solve the multi-stage transmission expansion planning (TEP) problem based on metaheuristic optimization techniques, as load and generation evolve. A discussion on how to consider security criteria using the well-known deterministic “N-1” approach and the probabilistic reliability-based method is presented through a case study system.
This paper proposes a new methodology to assess system reliability considering time-dependent power sources and loads. Based on a non-sequential Monte Carlo simulation (MCS), the proposed method uses a multilevel non-aggregate Markov model to represent different chronological load patterns per area or bus. As a result, the fluctuation of generating capacities, a characteristic of renewable energy...
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