Solar energy management as an Internet of Things (IoT) application

Published on Aug 1, 2017
· DOI :10.1109/IISA.2017.8316460
Andreas Spanias29
Estimated H-index: 29
(ASU: Arizona State University)
Photovoltaic (PV) array analytics and control have become necessary for remote solar farms and for intelligent fault detection and power optimization. The management of a PV array requires auxiliary electronics that are attached to each solar panel. A collaborative industry-university-government project was established to create a smart monitoring device (SMD) and establish associated algorithms and software for fault detection and solar array management. First generation smart monitoring devices (SMDs) were built in Japan. At the same time, Arizona State University initiated research in algorithms and software to monitor and control individual solar panels. Second generation SMDs were developed later and included sensors for monitoring voltage, current, temperature, and irradiance at each individual panel. The latest SMDs include a radio and relays which allow modifying solar array connection topologies. With each panel equipped with such a sophisticated SMD, solar panels in a PV array behave essentially as nodes in an Internet of Things (IoT) type of topology. This solar energy IoT system is currently programmable and can: a) provide mobile analytics, b) enable solar farm control, c) detect and remedy faults, d) optimize power under different shading conditions, and e) reduce inverter transients. A series of federal and industry grants sponsored research on statistical signal analysis, communications, and optimization of this system. A Cyber-Physical project, whose aim is to improve solar array efficiency and robustness using new machine learning and imaging methods, was launched recently.
  • References (29)
  • Citations (22)
📖 Papers frequently viewed together
52 Citations
2016MELECON: Mediterranean Electrotechnical Conference
11 Authors (Sunil Rao, ..., Andreas Spanias)
15 Citations
11 Authors (Sunil Rao, ..., Devarajan Srinivasan)
12 Citations
78% of Scinapse members use related papers. After signing in, all features are FREE.
#1Uday Shankar Shanthamallu (ASU: Arizona State University)H-Index: 3
#2Andreas Spanias (ASU: Arizona State University)H-Index: 29
Last. Mike Stanley (NXP Semiconductors)H-Index: 1
view all 4 authors...
52 CitationsSource
#1Sunil Rao (ASU: Arizona State University)H-Index: 5
#2Sameeksha Katoch (ASU: Arizona State University)H-Index: 4
Last. Devarajan SrinivasanH-Index: 6
view all 11 authors...
12 CitationsSource
#1Santolo DalientoH-Index: 20
#2A. ChouderH-Index: 1
Last. Pietro TricoliH-Index: 18
view all 7 authors...
A wide literature review of recent advance on monitoring, diagnosis, and power forecasting for photovoltaic systems is presented in this paper. Research contributions are classified into the following five macroareas: (i) electrical methods, covering monitoring/diagnosis techniques based on the direct measurement of electrical parameters, carried out, respectively, at array level, single string level, and single panel level with special consideration to data transmission methods; (ii) data analy...
37 CitationsSource
Nov 1, 2016 in ASILOMAR (Asilomar Conference on Signals, Systems and Computers)
#1Henry BraunH-Index: 6
#2Pavan TuragaH-Index: 26
Last. Cihan TepedelenliogluH-Index: 26
view all 4 authors...
We examine a potential technique of performing a classification task based on compressively sensed (CS) data, skipping a computationally expensive reconstruction step. A deep Boltzmann machine is trained on a compressive representation of MNIST handwritten digit data, using a random orthoprojector sensing matrix. The network is first pre-trained on uncompressed data in order to learn the structure of the dataset. The outer network layers are then optimized using backpropagation. We find this app...
5 CitationsSource
#1Henry Braun (ASU: Arizona State University)H-Index: 6
#2S. T. Buddha (ASU: Arizona State University)H-Index: 3
Last. Devarajan Srinivasan (ASU: Arizona State University)H-Index: 6
view all 7 authors...
As more utility scale photovoltaic (PV) power plants are installed, there is a need to improve monitoring and management of PV arrays. A procedure is presented here for optimizing the electrical configuration of a PV array under a variety of operating conditions. Computer simulations and analysis with synthetic and real data are presented in this paper. The performance of the optimization system is evaluated for a variety of partial shading conditions using a SPICE circuit simulator. In general,...
20 CitationsSource
Apr 18, 2016 in MELECON (Mediterranean Electrotechnical Conference)
#1Sunil Rao (ASU: Arizona State University)H-Index: 5
#2David Ramirez Dominguez (ASU: Arizona State University)H-Index: 7
Last. Andreas Spanias (ASU: Arizona State University)H-Index: 29
view all 11 authors...
15 CitationsSource
#1Visar Berisha (ASU: Arizona State University)H-Index: 13
#2Alan Wisler (ASU: Arizona State University)H-Index: 5
Last. Andreas Spanias (ASU: Arizona State University)H-Index: 29
view all 4 authors...
Information divergence functions play a critical role in statistics and information theory. In this paper we show that a nonparametric f-divergence measure can be used to provide improved bounds on the minimum binary classification probability of error for the case when the training and test data are drawn from the same distribution and for the case where there exists some mismatch between training and test distributions. We confirm these theoretical results by designing feature selection alg...
31 CitationsSource
#1Mohd Nafis Akram (UCF: University of Central Florida)H-Index: 1
#2Saeed Lotfifard (WSU: Washington State University)H-Index: 17
In this paper, a health monitoring method for photovoltaic (PV) systems based on probabilistic neural network (PNN) is proposed that detects and classifies short- and open-circuit faults in real time. To implement and validate the proposed method in computer programs, a new approach for modeling PV systems is proposed that only requires information from manufacturers datasheet reported under normal-operating cell temperature (NOCT) conditions and standard-operating test conditions (STCs). The pr...
38 CitationsSource
#1Henry Braun (ASU: Arizona State University)H-Index: 6
#2Shwetang Peshin (ASU: Arizona State University)H-Index: 2
Last. Devarajan SrinivasanH-Index: 6
view all 7 authors...
Electrical mismatch between modules in a PV array due to partial shading causes energy losses beyond the shaded module. This occurs because unshaded modules are forced to operate away from their maximum power point in order to compensate for the shading. Here we present an irradiance estimation algorithm for use in a mismatch mitigation system. Irradiance is estimated using measurements of module voltage, current, and back surface temperature. These estimates may be used to optimize an array's e...
2 CitationsSource
Jul 12, 2015 in IJCNN (International Joint Conference on Neural Network)
#1Lian Lian Jiang (NTU: Nanyang Technological University)H-Index: 9
#2Douglas L. Maskell (NTU: Nanyang Technological University)H-Index: 27
Long term exposure of photovoltaic (PV) systems under relatively harsh and changing environmental conditions can result in fault conditions developing during the operational lifetime. The present solution is for system operators to manually perform condition monitoring of the PV system. However, it is time-consuming, inaccurate and dangerous. Thus, automatic fault detection and diagnosis is a critical task to ensure the reliability and safety in PV systems. The current state-of-the-art technique...
18 CitationsSource
Cited By22
The Internet of Things (IoT) refers not only to the connectivity of systems and devices but to the related applications and services that provide monitoring and control of complex systems and services. Micro inverters due to their advantages to central inverters, get more attentions. Conventional micro inverters in solar applications only transfer energy from solar cells to grid or loads. Solar smart inverters in addition to transferring energy, can monitor condition to detect faults and also op...
Since it’s advent in the 1970’s, renewable energy has been seen as an important step in the future towards a greener and more sustainable earth. As of 2017, 19.3% of the world’s electricity consumption was generated by renewable means. This along with recent advancements in technology has made harvesting renewable energy sources like solar energy cheaper and more accessible to the public. 2% or about 460kWh of the world’s consumable energy is from solar power and this number is said to rise as t...
#1C. Birk Jones (SNL: Sandia National Laboratories)H-Index: 4
#2Adrian R. Chavez (SNL: Sandia National Laboratories)H-Index: 5
Last. Shamina Hossain-McKenzie (SNL: Sandia National Laboratories)H-Index: 3
view all 4 authors...
Reducing the risk of cyber-attacks that affect the confidentiality, integrity, and availability of distributed Photovoltaic (PV) inverters requires the implementation of an Intrusion Detection System (IDS) at the grid-edge. Often, IDSs use signature or behavior-based analytics to identify potentially harmful anomalies. In this work, the two approaches are deployed and tested on a small, single-board computer; the computer is setup to monitor and detect malevolent traffic in-between an aggregator...
#1Shamkumar Chavan (Shivaji University)H-Index: 2
#2Mahesh S. ChavanH-Index: 2
Information and communication technology has wide applications; nowadays, the focus is on use of ICT services in multiple areas for easy and rapid communications. Renewable energy systems are in greater demand, and experimentation is going on in optimization, efficiency improvement, development of fault-tolerant architectures, etc. Recently, a trend is seen to use ICT-enabled services in renewable energy applications. In this manuscript, an overview of ICT-enabled services in renewable energy ap...
#1Adel MellitH-Index: 41
#1A. HamiedH-Index: 1
Last. A. Mellit
view all 5 authors...
In this paper a smart remote sensing prototype for fault detection and identification of photovoltaic arrays is presented. A simple fault detection and identification algorithm has been incorporated into the designed prototype. The designed system detect automatically the fault, and then identify the origin of some investigated faults (such as open circuit, short circuit, dust accumulation and shedding effect). The prototype has been tested experimentally at the Renewable Energy Laboratory of Ji...
1 CitationsSource
#1Mohd Sajid Khan (Jamia Millia Islamia)
#2Ahteshamul Haque (Jamia Millia Islamia)H-Index: 8
Last. Kurukuru Varaha Satya Bharath (Jamia Millia Islamia)H-Index: 3
view all 3 authors...
This paper proposes real-time energy monitoring system based on the Internet of Things (IoT) for photovoltaic (PV) systems. For the purpose of monitoring various circuits and sensors are combined with a multipurpose microcontroller for collecting the output parameters. An IoT examination stage is adjusted to imagine the amassed information and assess the vitality created for a given conveyed age framework. This aide in persistent distant checking and results in better proficiency of the solar po...
#1Kaushal Kishore (AcSIR: Academy of Scientific and Innovative Research)H-Index: 3
#2Bala Pesala (CSIR: Council of Scientific and Industrial Research)H-Index: 11
Last. S.A. Akbar (CSIR: Council of Scientific and Industrial Research)H-Index: 6
view all 5 authors...
The presented work describes an interconnected multi-server IoT network for monitoring and control of smart solar tree. The IoT enabled solar tree is introduced as a smart street light with air quality monitoring capability and has been implemented in the Central Electronics Engineering Research Institute, Pilani. The presented network is a three-layer architecture with a sensor node at the lowermost layer for collecting the sensor data. The solar tree server above it performs the sampling of th...
#1Juan Andrade (ASU: Arizona State University)H-Index: 1
#2Sameeksha Katoch (ASU: Arizona State University)H-Index: 4
Last. Kristen Jaskie (ASU: Arizona State University)H-Index: 1
view all 6 authors...
Ground-based sky imaging has won popularity due to its higher temporal and spatial resolution when compared with satellite or air-borne sky imaging systems. Cloud identification and segmentation is the first step in several areas, such as climate research and lately photovoltaic power generation forecast. Cloud-sky segmentation involves several variables including sun position and type and altitude of clouds. We proposed a training-free cloud/sky segmentation based on a threshold that adapts to ...
#1Emma Pedersen (ASU: Arizona State University)H-Index: 1
#2Sunil Rao (ASU: Arizona State University)H-Index: 5
Last. Elias Kyriakides (UCY: University of Cyprus)H-Index: 27
view all 7 authors...
An increase in grid-connected photovoltaic arrays creates a need for efficient and reliable fault detection. In this paper, machine learning strategies for fault detection are presented. An Artificial Neural Network was studied with the goal of detecting three photovoltaic module conditions. In addition, an unsupervised approach was successfully implemented using the -means clustering algorithm, successfully detecting arc and ground faults. To distinguish and localize additional faults such as s...
1 CitationsSource
#1Kristen Jaskie (ASU: Arizona State University)H-Index: 1
#2Andreas Spanias (ASU: Arizona State University)H-Index: 29
This paper will address the Positive and Unlabeled learning problem (PU learning) and its importance in the growing field of semi-supervised learning. In most real-world classification applications, well labeled data is expensive or impossible to obtain. We can often label a small subset of data as belonging to the class of interest. It is frequently impractical to manually label all data we are not interested in. We are left with a small set of positive labeled items of interest and a large set...
4 CitationsSource