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Park, D., El-Sharkawi, M., Marks II, R., Atlas, L. and Damborg, M. (1991) Electric Load Forecasting Using an Artificial Neural Network. IEEE Transactions on Power Systems, 6, 442–449.
https://doi.org/10.1109/59.76685

has been cited by the following article:

• TITLE: Design & Implementation of an Optimization Loading System in Electric by Using Genetic Algorithm

  AUTHORS: Ali Abdulhafidh Ibrahim, Anmar L. Dawood

  KEYWORDS: Power Distribution System, Genetic Algorithm, Active Demand

  JOURNAL NAME: Journal of Computer and Communications, Vol.7 No.7, July 12, 2019

  ABSTRACT: The purpose of this paper is to propose a new system for the distribution of electric power by using the concept of Active Demand procedures to obtain a low cost and ensure the continuity of energy. This paper consists of two parts: the first includes the method of optimal distribution of electricity in the presence of Active Demand based on the price of energy for the specific time in the system; this feature will help the consumer to determine the process of consumption through the advertised price; all this will appear through the energy box. The second part involves the introduction of the genetic algorithm to obtain the best solutions for costs and also the best choice for the distribution of electrical power, which makes this method optimize by introducing the genetic algorithm with electrical energy. The main drivers of this work are to provide continuous electrical energy at the lowest cost and also to simulate active demand, in addition to the rapid processing of energy failures by the aggregator and raising awareness of the process of energy conservation for the consumer.