Session: 18-03 HelioCon Solar Field

Paper Number: 142181

142181 - Heliocomm: A Wireless Communications Autonomous System for Concentrated Solar Power Fields 

Abstract: 

This research work introduces HELIOCOMM, a fully autonomous wireless communication system engineered to exemplify resilience and efficiency in Concentrated Solar Power (CSP) fields. Next generation heliostat-based CSP systems are envisioned to cover an area with radius ranging from 1 Km to 5 Km, supporting a number of connected heliostats that will range from hundred to several hundreds of thousands, e.g., 70,000 connected heliostats. Hence, adopting a resilient wireless control system, coupled with wireless power becomes a need rather than a desire in order to guarantee the stable and undisrupted online control of the heliostats and support scalability. Focusing on overcoming the limitations of the conventional mesh networking technology-based communication in CSP fields, HELIOCOMM is designed based on the principles of the Integrated Access and Backhaul (IAB) technology, entropy-based routing, dynamic spectrum management, and interference mitigation to implement a fully autonomous wireless communications system to support the closed-loop autocalibration of the heliostats. In this regard, HELIOCOMM introduces an algorithmic approach to divide the CSP field into multiple segments based on radial distances and angular orientations of the heliostats with respect to the central station, and also to determine specific groups of heliostats which perform closed-loop autocalibration (CLA). The group of heliostats performing CLA are chosen such that each of the segments in a CLA group are not within the communication range of each other and thereby mitigating the inter-segment interference. Consequently, the segments which are not considered in a CLA group are executing regular communication with the central station. Depending on the direct normal irradiance (DNI) at an interval of five minutes, the decision to perform CLA is made (DNI greater than 500 enables the heliostats to perform CLA). The specific end-to-end latency constraints associated to the CLA and regular communication are 0.25 and 2 seconds respectively. The HELIOCOMM’s primary objectives include the modular design and fine-tuning of IAB-based networks to optimize energy efficiency and minimize latency of communication through an optimization problem with two degrees of freedom consisting of the transmission power and bandwidth splitting ratio, the rigorous testing of IEEE 802.11ax and IEEE 802.15.4 protocols within the IAB paradigm, the dynamic clustering-driven network reconfiguration, the design of real-time entropy-based routing algorithms, as well as the orchestration of dynamic spectrum management mechanisms for both access and wireless backhaul, while introducing intra- and inter-cluster interference mitigation strategies. Results of preliminary simulation and emulation-based experiments accounting for real hardware metrics, e.g., bandwidth availability, maximum transmission power, receiver sensitivity, etc., will be presented demonstrating an achieved communication latency less than 250 msec regarding the communication of each heliostat with the central station in a multi-hop manner in a CSP field consisting of ~7700 heliostats. The large number of heliostats within the CSP field supports the novelty of the IAB technology in terms of optimally allocating the limited ISM spectrum among the heliostats in access and backhaul networks. Coupled with the optimal bandwidth allocation, the optimal transmission power determination not only optimizes the energy efficiency of the heliostats but also effectively limits the interference experienced within the IAB-based network. Additionally, the preliminary results suggest clustering with dynamic cluster-head selection and intelligent routing within the CSP field minimizes the end-to-end communication latency by strategically distributing the overhead across the IAB nodes as well as limiting the intra- and inter-cluster interference.  Specifically, selecting the heliostat with the highest closeness centrality score and energy availability, i.e., the heliostat that is the most suitable to forward the data of heliostats in the access network of the cluster given it has the most superior channel conditions (the least path loss) with the other heliostats in the cluster and has the most sufficient energy in its battery which finds a next-hop IAB relay with the similar characteristics while also accounting for the network traffic balances out the data overhead across the IAB nodes (relays).

Presenting Author: Eirini Eleni Tsiropoulou University of New Mexico

Presenting Author Biography: Dr. Eirini Eleni Tsiropoulou is an Associate Professor, Computer Engineering Area Chair, and Director of Recruiting and Admissions at the Department of Electrical and Computer Engineering, University of New Mexico. She obtained her Diploma in Electrical and Computer Engineering from National Technical University of Athens in 2008 and her MBA in techno-economics from the same institute in 2010. She graduated with a Ph.D in Electrical and Computer Engineering from National Technical University of Athens in 2014. Her main research interests lie in the area of cyber-physical social systems and wireless heterogeneous networks, with emphasis on network modeling and optimization, resource orchestration in interdependent systems, reinforcement learning, game theory, network economics, and Internet of Things. Five of her papers received the Best Paper Award at IEEE WCNC in 2012, ADHOCNETS in 2015, IEEE/IFIP WMNC 2019, INFOCOM 2019 by the IEEE ComSoc Technical Committee on Communications Systems Integration and Modeling, and IEEE/ACM BRAINS 2020. She was selected by the IEEE Communication Society - N2Women - as one of the top ten Rising Stars of 2017 in the communications and networking field. She received the NSF CRII Award in 2019, the Early Career Award from the IEEE Communications Society Internet Technical Committee in 2019, and the Junior Faculty Teaching Excellence Award, School of Engineering, University of New Mexico in 2018. Her research is mainly supported by the Department of Energy, National Science Foundation, and industry. She is an Associate Editor for IEEE Transactions on Green Communications and Networking, IEEE Transactions on Machine Learning in Communications and Networking, IEEE Networking Letters, IEEE Transactions on Network Science and Engineering, IEEE IT Professional, IEEE Vehicular Technology Magazine, and IEEE/ACM Transactions on Networking.

Authors:

Md Sadman Siraj University of New Mexico
Aisha B Rahman University of New Mexico
Eirini Eleni Tsiropoulou University of New Mexico