{"id":916,"date":"2016-09-08T11:05:41","date_gmt":"2016-09-08T11:05:41","guid":{"rendered":"http:\/\/www.etfos.unios.hr\/ijeces\/?p=916"},"modified":"2017-03-23T08:04:46","modified_gmt":"2017-03-23T08:04:46","slug":"optimal-load-shedding-using-an-ensemble-of-artificial-neural-networks","status":"publish","type":"post","link":"http:\/\/www.etfos.unios.hr\/ijeces\/vol-7-no-2-2016\/optimal-load-shedding-using-an-ensemble-of-artificial-neural-networks\/","title":{"rendered":"Optimal Load Shedding Using an Ensemble of Artificial Neural Networks"},"content":{"rendered":"
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Muhammad FaizanTahir, Hafiz Teheeb-Ul-Hassan, Kashif Mehmood, Hafiz Ghulam Murtaza Qamar, Umair Rashid<\/h3>
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Abstract<\/strong><\/div>\n
Optimal load shedding is a very critical issue in power systems. It plays a vital role, especially in third world countries. A sudden increase in load can affect the important parameters of the power system like voltage, frequency and phase angle. This paper presents a case study of Pakistan\u2019s power system, where the generated power, the load demand, frequency deviation and load shedding during a 24-hour period have been provided. An artificial neural network ensemble is aimed for optimal load shedding. The objective of this paper is to maintain power system frequency stability by shedding an accurate amount of load. Due to its fast convergence and improved generalization ability, the proposed algorithm helps to deal with load shedding in an efficient manner.<\/div>\n
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Keywords<\/strong><\/div>\n
ensemble of artificial neural network, load shedding, power system stability<\/div>\n
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