Published 2014 | Version v1
Journal article Metadata-only

An automated tool for solar power systems

Creators

  • 1. Department of Computer Engineering, An-Najah National University, Nablus (Palestinian Territory, Occupied)
  • 2. Department of Computerized Information Systems, An-Najah National University, Nablus (Palestinian Territory, Occupied)
  • 3. Advanced Industrial Diagnostics Centre, Manchester (United Kingdom)

Description

In this paper a novel model of smart grid-connected solar power system is developed. The model is implemented using MatLab/SIMULINK software package. Artificial neural network (ANN) algorithm is used for maximizing the generated power based on maximum power point tracker (MPPT) implementation. The dynamic behavior of the proposed model is examined under different operating conditions. Solar irradiance, and temperature data are gathered from a grid connected, 28.8 kW solar power system located in central Manchester. The developed system and its control strategy exhibit excellent performance with tracking efficiency exceed 94.5%. The proposed model and its control strategy offer a proper tool for smart grid performance optimization. (author)

Additional details

Publishing Information

Journal Title
Geliotekhnika
Journal Issue
no.4
Journal Page Range
p. 17-24
ISSN
0130-0997

INIS

Country of Publication
Uzbekistan
Country of Input or Organization
Uzbekistan
INIS RN
49037046
Subject category
S14: SOLAR ENERGY;
Descriptors DEI
ALGORITHMS; COMPUTER CODES; CONTROL; EFFICIENCY; GRIDS; IMPLEMENTATION; NEURAL NETWORKS; OPTIMIZATION; PERFORMANCE; PHOTOVOLTAIC CELLS; RADIANT FLUX DENSITY; SOLAR CELL ARRAYS; TOOLS
Descriptors DEC
DIRECT ENERGY CONVERTERS; ELECTRODES; EQUIPMENT; FLUX DENSITY; MATHEMATICAL LOGIC; PHOTOELECTRIC CELLS; SOLAR EQUIPMENT

Optional Information

Notes
15 refs., 11 figs., 2 tabs.