This paper deals with two new methods, based on k-NN algorithm, for fault detection and classification in distance protection. In these methods, by finding the distance between each sample and its fifth nearest neighbor in a predefault window, the fault occurrence time and the faulty phases are determined. The maximum value of the distances in case of detection and classification procedures is compared with pre-defined threshold values. The main advantages of these methods are: simplicity, low calculation burden, acceptable accuracy, and speed. The performance of the proposed scheme is tested on a typical system in MATLAB Simulink. Various possible fault types in different fault resistances, fault inception angles, fault locations, short circuit levels, X/R ratios, source load angles are simulated. In addition, the performance of similar six well-known classification techniques is compared with the proposed classification method using plenty of simulation data.
This study proposes a composite generation and transmission expansion planning (CGTEP) with high renewable penetration in Iran power grid. The goal is to minimise the generation and transmission investment and operation costs, start-up/ shutdown costs, and the cost of energy not served during a 10-year planning horizon. The problem is formulated in a mixedinteger linear format, considering power flow limits, ramping rate limits, minimum up/down times of the generation units, uncertainty of wind and solar generations, and deterministic and probabilistic reliability constrains including reserve margins for generation capacities and expected energy not supplied boundary. In addition, according to the specific geographic characteristics of Iran, import and export of the electricity, as well as the limitation of water resources for power generation, is modelled in the CGTEP problem. The proposed CGTEP method is implemented in business as usual and renewable target cases without considering the uncertainty, and RT case with uncertainty considerations. In RT cases, 30% renewable penetration is targeted to reduce the CO 2 emission by 10%. In addition, the capability of Iran power grid in providing green energy for the neighbouring countries is investigated in this study.
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