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This paper presents an optimized scheduling method for Plugged-in Electric Vehicles (PEV) that are connected to a residential smart microgrid. Two modes of operation are studied: grid-tied and islanded mode. A Genetic Algorithm (GA)-based method is utilized to optimize an objective function, which includes the cost of energy production, and guarantees the best possible energy consumption profile....
In this paper a Genetic Algorithm (GA) is used to partition a distribution network with the aim to minimize the energy exchange among the microgrids (i.e. maximize self-consumption) in presence of distributed generation. The proposed GA is tested on the IEEE prototypical network PG & E 69-bus. The microgrid partitioning is tested over a period of one year with hourly sampled data of real household...
This paper proposes an efficient methodology to optimally determine the best location and optimum size for Distributed Generators (DG), in a distribution network, while minimizing energy losses and improving voltage profile. The proposed methodology has been designed to consider variable demand and variable DG production scenarios, offering a set of optimum values for DG active power output and power...
The post-crowdfunding refers to the sale of products “very successful” in reward-based crowdfunding after the backers have been rewarded. It offers an opportunity for the creators to exploit the remaining untapped profit after the crowdfunding period. The post-crowdfunding includes the resale and normal sale stage, which involves the creators' various policies under the capital constraint based on...
This article presents the digital twin concept, which is an augmented manufacturing project created in close collaboration by SOVA Digital and the Institute of Automation, Measurement and Applied Informatics (ÚAMAI), of the Faculty of Mechanical Engineering, Slovak University of Technology in Bratislava with the support of SIEMENS. The project is a technological concept focusing on the continuous...
The electricity load of large consumers has the characteristics of fluctuating randomly in a short period and changing periodically over a longer time scale. In recent years, the influence of these kind of consumers on regional load has been increasing year by year, which has become an important factor to improve the forecasting accuracy of the entire load. In this paper, we use parameters-improved...
Data Envelopment Analysis (DEA) is a nonparametric methodology for estimating technical efficiency of a set of Decision Making Units (DMUs) from a dataset of inputs and outputs. This paper is devoted to computational aspects of DEA models under the application of the Principle of Least Action. This principle guarantees that the efficient closest targets are determined as benchmarks for each assessed...
The flexible variable-speed control system of rod pumping well is designed to increase the oil production speed and to reduce both the rod stress and motor energy consumption by changing the motor drive speed rapidly during a stroke cycle. This paper establishes a flexible variable-speed control model as well as the optimization algorithm for rod pumping well. The optimal motor speed profile is determined...
This paper presents an application of Genetic Algorithm (GA) to solve Economic Load Dispatch problem which aims to determine minimum fuel cost and Environmental Load Dispatch problem which aims to determine minimum gas emission for required energy production of the chosen power system. Test system is chosen as IEEE-30 bus system which includes 6 generators with necessary values given for ease of simulation...
The planning of maintenance activities can hinder manufacturing operations in term of cost, quality and time, but it is necessary to ensure the availability of the production equipment to meet customer demands. We propose to model the function of maintenance tasks and production operations by the sum of the two costs under a set of constraints. As a method of resolution, we use genetic algorithms...
Accurate prediction of the crude oil output decline rate is crucial to ensure the stability of oil field. This paper presents a new method that utilizes the neural networks optimized by Genetic Algorithm(GA) to dynamically predict the crude oil output decline rate. Firstly, choose the best weights for neural network by the GA's survival of the fittest mechanism. Next, learn the rules of production...
In this paper, Genetic Algorithm (GA) is used to solve the Unit Commitment (UC) Problem. Unit commitment problem was formulated with consideration of up & down time, startup cost (Hot & Cold start), and production cost. Unit commitment schedule as well as economic dispatch is obtained to obtain total cost of generation. Problem specific operators are used in the algorithm to improve the quality...
Nowadays, in order to maintain their competitiveness, manufacturing companies must adapt their production methods quickly, with minimum expenditure, to frequent variations on demand. With the shortage of the product life time, flexibility, efficiency and reusability of industrial processes are important factors, which may determine the survival of the company. The ReBORN project is working around...
Discusses the design of machine-building production, certain steps of which are formalized problems of the forecast of the number of parts and calculate their estimated time. Simulation of application tasks is performed by the approximation of the fractional — power series. The possibility is shown for the numerical solution of models using combined genetic algorithms.
Nowadays, one of the primary problems in the energy industry is ensuring rational operating conditions of electric power systems under variable loads and with regard to cost-effectiveness and technical capabilities of power plants. Supply fluctuated load considerably increases the costs in the power systems. The price of electricity in the case by changed load is generally higher than by constant...
This paper presents the implementation of a system based on genetic algorithm multiobjective optimizer NSGA-II (Non-Dominated Sorting Genetic Algorithm), which offers a decision support tool and automates the search for alternatives to the development of the oilfield submitted to water injection process. Each alternative refers to how an oil field, known and defined, is put into production, that is,...
Utilizing thermal generation alone to meet the energy demand leads to adverse effects on environment. So, to minimize the environmental pollution, there is a need to enhance the renewable energy contribution in the grid. In this paper a hybrid Priority List and Particle Swarm Optimization (PL-PSO) approach to solve Unit Commitment (UC) and Economic Load Dispatch (ELD) of thermal units integrated with...
Case-Based Reasoning (CBR) interests the scientific community, whom are concerned with scalability in knowledge representation and processing. CBR systems scale far better than rule-based systems. Rule-based systems are limited by the need to know the rules of engagement, which is practically unobtainable. The work presented in this paper pertains to knowledge generalization based on randomization...
This paper proposes a hybrid neuro-evolutive algorithm (NEA) that uses a compact indirect encoding scheme (IES) for representing its genotypes, moreover has the ability to reuse the genotypes and automatically build modular, hierarchical and recurrent neural networks. A genetic algorithm (GA) evolves a Lindenmayer System that is used to design the neural network's architecture. This basic neural codification...
Production safety is concerned continuously in coalmine, especially the gas safety is a key issue in the working management of coal production. With the development of information technology, a large volume of data should collected from sensors deployed in coalmine. Therefore, it is necessary to forecast gas concentration or evaluate the gas safety in the key point, for example, the underground working...
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