electrical load


Automatically disaggregating the total electrical load in residential buildings: a profile of the required solution
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Renewed emphasis on the cost and environmental impacts of electricity are leading to a greater awareness for the need to measure and manage loads in buildings of all types. In this paper we focus on the residential buildings sector by looking at best available

Agent-based optimisation systems for electrical load management
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Electrical load management can potentially offer significant benefits in reducing both greenhouse gas emission and energy costs. It is a comparatively new application domain for agent-based technologies, with few existing approaches. Three novel optimal management

Forecasting electrical load using ANN Combined with multiple regression method
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This paper combined artificial neural network and regression modeling methods to predict electrical load . We propose an approach for specific day, week and/or month load forecasting for electrical companies taking into account the historical load . Therefore, a

Application of neural network to load forecasting in Nigerian electrical power system
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Load forecasting is very essential to the operation of electricity companies. It enhances the energy-efficient and reliable operation of a power system. This paper presents a study of short-term load forecasting using Artificial Neural Networks (ANNs) and applied it to the

Developing building archetypes for electrical load shifting assessment: Analysis of Irish residential stock
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Appropriate use of demand side management (DSM) strategies in residential buildings, when placed in a smart grid environment, can help reduce power supplydemand mismatches by shifting electrical loads, thus leading to better integration of renewable

Leveraging data from environmental sensors to enhance electrical load disaggregation algorithms
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The idea of sustainable or green buildings generally stops after the design and construction phases. Little effort is made to continuously monitor and control the energy profile throughout the life-cycle of these facilities. To effectively identify opportunities for

Electrical load forecasting using genetic algorithm based back-propagation method
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Forecasting is the way of knowing the future value based on some past records. In electrical power systems, there is a great need for accurate forecasting of the future load and energy requirements. Accurate load forecast provides system dispatchers with timely information to

High performance direct torque control of electrical aerodynamics load simulator using fractional calculus
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Electrical load simulator system (ELSS) is a test rig used to apply medium range aerodynamics loads on flight actuation system in real time experiments. A novel high performance fractional order adaptive robust torque control law is proposed for Electrical

Representative electrical load profiles of residential buildings in Germany with a temporal resolution of one second
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Precise and representative electrical load profiles of households are an essential basis for a variety of scientific research questions in the field of energy supply and storage. Firstly, this document describes the data basis and preparation of a freely available dataset of highly

Enhanced Neuro-Fuzzy Architecture for Electrical Load Forecasting
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Previous researches about electrical load time series data forecasting showed that the result was not satisfying. This paper elaborates the enhanced neuro-fuzzy architecture for the same application. The system uses Gaussian membership function (GMF) for Takagi

Electrical load characteristics of domestic heat pumps and scope for demand side management
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Domestic heat pumps are a key part of the UK Governments decarbonisation strategy and are expected to form a substantial part of national electrical demand by 2050. This paper reports on the practical performance and electrical load characteristics of a group of ten heat

Electrical load forecasting using adaptive neuro-fuzzy inference system
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Electrical load forecasting is well-known as one of the most important challenges in the management of electrical supply and demand and has been studied extensively. Electrical load forecasting is conducted at different time scales from short-term, medium-term and long

Electrical power load forecasting using hybrid self-organizing maps and support vector machines
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Forecasting of future electricity demand is very important for decision making in power system operation and planning. In recent years, due to the privatization and deregulation of the power industry, accurate forecasting of future electricity demand has become an

Modelling of an electrical load
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This paper describes the development of a mathematical model to be used for statistical evaluation of power consumption from a region consisting of different companies with workshop activities as well as office activities. The model proposed, is based on the results

A novel model of intelligent electrical load management by goal programming for smart houses, respecting consumer preferences
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Energy management is being highly regarded throughout the world. High-energy consumption in residential buildings is one of the dominant reasons of excessive energy consumption. There are many recent works on the demand-side management (DSM) and

Mathematical model for failure cause analysis of electrical systems with load -sharing redundancy of component
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In the paper, a mathematical reliability model for an electrical repairable system with parallel load -sharing redundancy of components is proposed. Such a model adequately accounts for the impact of load -sharing redundancy on cut set probability indexes. For reliability

Building a vector-based load taxonomy using electrical load signatures
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A load signature of an appliance describes the appliance behaviour in an electrical circuit. By comparing load signatures of various loads, we can separate the loads in terms of their differences, and cluster them to the same class in terms of their similarities. The process

Forecasting electrical load for home appliances using genetic algorithm based back propagation neural network
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The combining usage of genetic algorithms and artificial neural networks, were originally motivated by the astonishing success of these concepts in their biological counterparts. Despite their totally deferent approaches, both can merely be seen as optimization methods

Analysis of methods of electrical load of permanent magnet synchronous generator for small wind turbines
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The article compares the different ways to create and regulate electrical load of synchronous generator with permanent magnets (PMSG) in the low-power wind turbines with vertical axis (VAWT). Briefly describes the methods that allow you to adjust the electromotive force of

Neuro-Fuzzy Forecaster for Modeling and Forecasting Electrical Load Competition using Multivariate Inputs on Takagi-Sugeno Networks
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Multivariate inputs play important role in system with many dependent variables. By using some different inputs as input in neuro-fuzzy networks, complex nonlinear model can be modeled and also forecast with better results. The paper describes a neuro-fuzzy approach



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