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Content Provider | IET Digital Library |
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Author | Pal, Kanwar Kumar, Shailendra Singh, Bhim Kandpal, Tara C. |
Abstract | An adaptive approach based on a neural network is presented here for the control of a grid interactive solar power generating system. This control approach is based on a summation and a product neuron, which are used to process the non-linearity of load currents. A sigmoidal and Gaussian functions are used to linearise the response of summation and product neurons. In this control, the product and summation neurons, and sigmoidal and Gaussian functions are within a single layer, which reduces the complexity of control. This control algorithm is superior over artificial neural network (ANN)-based control algorithm, which has large number of unknown weights and layers. It reduces the computational burden and complexity of the control algorithm. It shows the inherent improved performance at non-linear balanced and unbalanced loads. The control of net active and reactive components of the power separately improves the efficacy of the control at unbalanced non-linear load and reduces the voltage transients in the grid voltages. The ANN-based control also plays an active role in enhancing the power quality of the grid. The reduced complexity of control and direct power feed forward of photovoltaic array (PVA) to the grid improve the dynamic response of the grid-connected PVA-based system. |
Starting Page | 5471 |
Ending Page | 5479 |
Page Count | 9 |
ISSN | 17518687 |
Volume Number | 14 |
e-ISSN | 17518695 |
Issue Number | Issue 23, Dec (2020) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-gtd/14/23 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2020.0790 |
Journal | IET Generation, Transmission & Distribution |
Publisher Date | 2020-09-09 |
Access Restriction | Open |
Rights Holder | © The Institution of Engineering and Technology |
Subject Keyword | Adaptive Approach ANN-based Control Artificial Neural Network Artificial Neural Network-based Control Algorithm Control of Electric Power System Direct Power Feed Forward Dynamic Response Gaussian Distribution Gaussian Function Grid Interactive Solar Energy System Grid Interactive Solar Power Generating System Grid Voltage Grid-connected PVA-based System Harmonics Load Current Nonlinearity Neural Computing Technique Neural Neuron Technique Neurocontrol Neurocontrollers Photoelectric Conversion Photovoltaic Array Photovoltaic Power System Power Generation Control Power Grid Power Quality Improvement Power Supply Quality Probability Theory Product Neuron Sigmoidal Function Solar Cell And Array Solar Cell Array Solar Power Solar Power Stations Statistics Stochastic Linearised SCUC Summation Neuron Unbalanced Nonlinear Load Voltage Transients |
Content Type | Text |
Resource Type | Article |
Subject | Control and Systems Engineering Energy Engineering and Power Technology Electrical and Electronic Engineering |
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