Session: 01-03: AI for Energy Sustainability III

Paper Number: 132208

132208 - Ai and Machine Learning in Bipv of Indian Cities: State-of-the-Art Solution or Newfangled Idea 

Abstract: 

As the world picks the pace of renewable energy integration in the energy supply matrix of cities, solar energy is still at the forefront. Despite being one of the fastest growing sources of renewable energy, widespread adoption and rapid expansion of solar energy is hindered by significant challenges in terms of build efficiency, interconnection with existing power systems, grid scaling, and cost.  Solar photovoltaic (SPV) systems such as Building Integrated Photovoltaic (BIPV) systems are the key to harnessing solar energy in heavily urbanized cities. The multiple horizontal and vertical surfaces of urban fabric can be used to generate energy while alleviating some of material and structural costs which go into adding solar panels on the roofs as an afterthought.

As the solar technology becomes advanced, artificial intelligence (AI) and machine learning may help the installations perform in an optimum and efficient manner and pave the path for developing smart and resilient solar photovoltaic systems to achieve decarbonization in the cities. Machine learning has become more common in forecasting and classification because it reliably processes complex or nonlinear problems; and can determine relationships between input and output variables in the unlikely scenarios. The unpredictability of sunshine, obstruction from other surfaces, cleanliness, installation angles, and new variants of colored BIPV modules are some of the factors which affect the robustness, reliability, automation, flexibility, and performance of solar panels. It is prudent to explore the latest technologies and data driven methods to critically analyze the multivariable problems, and accurately predict the system losses, fault diagnosis, performance anomalies, and output data. 

This review paper analyses and summarizes the connections between AI, machine learning, and solar systems such as BIPV. It aims to comprehensively review, and analyze AI- based modeling techniques, artificial neural networks, fuzzy logic, genetic algorithm, maximum power point tracking (MPPT) based AI techniques, decision tree, multi-level stochastic uncertainty analysis, smart controls, and single & multiple objective optimizations along with the ways they can be leveraged to optimize energy generation from solar photovoltaic panels. The objective is to report current progress, and identify potential, opportunities, and gaps from the studies being done at the global level. The learnings are distilled for application in the Indian context as the subject is relatively unexplored in the country’s context. The paper shall be a roadmap on historical development, recent advances, latest technologies and techniques, and future challenge of AI and machine learning in solar systems in Indian context.

Presenting Author: Khushal Matai School of Planning and Architecture, New Delhi

Presenting Author Biography: He is an architect, researcher and academician with experience of more than 12 years in the field of sustainable design and energy efficient buildings. He has a PhD and masters in environmental and sustainable architecture stream.
His major research work focuses on Renewable Energy in Building sector with specialization in Solar Photovoltaics and architecture. Building Integrated Photovoltaic Architecture, hybrid integration of renewable energy systems at campus level, RE retrofits in heritage type construction. He has worked on various other interdisciplinary research areas such as; urban heat island effect, Eco-Tourism, wood architecture.
He has authored 12 publications spanning over 6 journals and magazines. He has been the reviewer for various Journals, papers and reports in the field of architecture and renewable energy.
He has been a member of organizing committee, review committee, moderator and resource person for various international and national conferences such as IEREK “International Experts for Research Enrichment and Knowledge Exchange”, GRIHA Summit on climate change, National Institute of Technical Teachers Training and Research (NITTTR), Chandigarh, MNIT. Additionally, he has been a subject expert in Annual Refresher Programme in Teaching (ARPIT) and several other faculty development programs as well as pedagogical workshops. Moreover, he has organized various Faculty development programmes, conferences and chaired various international conferences. He is the coordinator for ‘Wood from Finland’ course in India from SPA- ND. This is a course run by LAB-UAS, Finland with support from Business Finland.
He has played a pivotal role in research and pedagogy advancement by facilitating the signing of several MoU’s and collaborations with various international universities and organizations from different countries. He has been a member of Rajasthan Scrutiny Committee for the Prime Minister Skill Development scheme (PMKVY). He is registered with Council of Architecture, an associate of Indian Institute of Architects, Rajasthan chapter, and an active member of Indian Science Congress Association. He is a Section managing committee member of ISTE, Rajasthan Section.

Authors:

Khushal Matai School of Planning and Architecture, New Delhi
Ashu Dehadani GREEN BUSINESS CERTIFICATION INC.