scholarly journals Effects of scale on load prediction algorithms

2013 ◽  
Author(s):  
A. Tidemann ◽  
P. ztrk ◽  
H. Langseth ◽  
B.A. Hverstad
Keyword(s):  
Load Prediction ◽  
Prediction Algorithms

scholarly journals IMPEC: An Integrated System for Monitoring and Processing Electricity Consumption in Buildings

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1048 ◽  
Author(s):  
Mohamed Aymane Ahajjam ◽  
Daniel Bonilla Licea ◽  
Mounir Ghogho ◽  
Abdellatif Kobbane
Keyword(s):  
Power Consumption ◽  
Data Acquisition ◽  
Electricity Consumption ◽  
Integrated System ◽  
Load Prediction ◽  
Integrated Monitoring ◽  
Prediction Algorithms ◽  
Load Monitoring ◽  
Industrial Settings ◽  
Validation Tests

Non-intrusive Load Monitoring (NILM) systems aim at identifying and monitoring the power consumption of individual appliances using the aggregate electricity consumption. Many issues hinder their development. For example, due to the complexity of data acquisition and labeling, datasets are scarce; labeled datasets are essential for developing disaggregation and load prediction algorithms. In this paper, we introduce a new NILM system, called Integrated Monitoring and Processing Electricity Consumption (IMPEC). The main characteristics of the proposed system are flexibility, compactness, modularity, and advanced on-board processing capabilities. Both hardware and software parts of the system are described, along with several validation tests performed at residential and industrial settings.

Seaway Load Prediction Algorithms for High Speed Hull Forms

2005 ◽  
Author(s):  
Jerome P. Sikora ◽  
Nathan B. Klontz
Keyword(s):  
High Speed ◽  
Scaling Laws ◽  
Surface Effect ◽  
Concept Design ◽  
Load Prediction ◽  
Design Studies ◽  
Prediction Algorithms ◽  
Scale Test ◽  
Hull Forms ◽  
Computational Analyses

This paper documents the generation of several seaway load prediction algorithms for catamarans, trimarans, and surface effect ships based on available model and full-scale test data. Froude scaling laws are used for geometrically different ships for each ship and load type using first principles and empirically derived studies. Simple seaway load prediction algorithms are then developed and expressed as functions of ship displacement and various key ship particulars. These global load algorithms are quickly computed, making them suitable for preliminary or concept design studies. In some cases, algorithms were developed from a minimum amount of data, and it is anticipated that as more data is gathered in the future, these algorithms will be further refined. As the ship design progresses, more accurate but time consuming computational analyses and model tests are appropriate.

scholarly journals Electrical Load Prediction Using Interval Type-2 Atanassov Intuitionist Fuzzy System: Gravitational Search Algorithm Tuning Approach

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3591
Author(s):  
Mojtaba Ahmadieh Khanesar ◽  
Jingyi Lu ◽  
Thomas Smith ◽  
David Branson
Keyword(s):  
State Of The Art ◽  
Renewable Energy Sources ◽  
Superior Performance ◽  
Electrical Load ◽  
Load Prediction ◽  
Prediction Algorithms ◽  
Simulation Results ◽  
Gravitational Search ◽  
Interval Type

Establishing accurate electrical load prediction is vital for pricing and power system management. However, the unpredictable behavior of private and industrial users results in uncertainty in these power systems. Furthermore, the utilization of renewable energy sources, which are often variable in their production rates, also increases the complexity making predictions even more difficult. In this paper an interval type-2 intuitionist fuzzy logic system whose parameters are trained in a hybrid fashion using gravitational search algorithms with the ridge least square algorithm is presented for short-term prediction of electrical loading. Simulation results are provided to compare the performance of the proposed approach with that of state-of-the-art electrical load prediction algorithms for Poland, and five regions of Australia. The simulation results demonstrate the superior performance of the proposed approach over seven different current state-of-the-art prediction algorithms in the literature, namely: SVR, ANN, ELM, EEMD-ELM-GOA, EEMD-ELM-DA, EEMD-ELM-PSO and EEMD-ELM-GWO.

Sign in / Sign up

Export Citation Format

Share Document