Problem-Based Learning Program in Collaboration with RKGIT and Eleve8 Solution Private Limited

Centers around solving real-world problems through Machine Learning, Artificial Intelligence & IoT Technologies in collaboration with RKGIT & Eleve8 Solution Private Limited.

21st Century Learning Program: Reflects the emphasis on skills relevant to the modern world through projects.

Project Objective:- To safeguard solar companies from incurring financial losses

What led to the decision to address this specific business issue?

The business problem of analyzing the performance and efficiency of the solar power plant was selected because of its relevance and significance in the renewable energy industry. Solar power is an increasingly important source of clean energy, and optimizing the performance of solar power plants is crucial to ensure their viability and contribute to sustainable energy generation.

By analyzing the data from the solar power plant, insights can be gained into its operational patterns, energy generation trends, and the impact of weather parameters on performance. Addressing this problem allows for identifying areas of improvement, enhancing power generation efficiency, and maximizing energy output, ultimately leading to better utilization of resources and more sustainable energy production.

There are some multinational Solar power plant companies out there such as SunPower Corporation, Canadian Solar, Tesla Energy, Enphase Energy, and SMA Solar Technology which are leading providers of Solar Inverters and Energy management systems for Commercial, Residential, and Utility-scale solar installation despite the fact that these are big MNCs but they are unable to get high ROI and faces badly financial losses due to the operational expenses and not having proper Energy Production Analysis.

renewable-energy
Photovoltaic solar panels for generating electricityClick here to view more related images:

Here we come up with a solution to avoid these financial losses as the result of these Hypothesis

Hypothesis 1

Weather Parameters Impact Solar Power Generation

Null Hypothesis (H0)

Weather parameters, such as solar irradiance, ambient temperature, and module temperature, do not significantly affect solar power generation.

Alternative Hypothesis (H1)

Weather parameters have a significant impact on solar power generation, and changes in weather conditions lead to variations in energy output.

Energy Utility Project : Coordinated Technology Program by RKGIT and Eleve8 Solution Private Limited

Collaborative learning with RKGIT students and Eleve8 Solutions to explore groundbreaking sustainable tech innovations can be an exciting and impactful endeavor.

It’s fantastic to hear that 30 students have successfully executed an impactful Energy Utility project while mastering a range of technologies such as Machine Learning (ML), Artificial Intelligence (AI), Internet of Things (IoT), databases, and various tech applications. This accomplishment reflects a commendable commitment to innovation and addressing real-world challenges.

During this program, a significant milestone was the successful creation, implementation, and supervision of fault-tolerant, highly accessible, and expandable Machine Learning solutions. This achievement highlighted the students’ ability to apply their academic expertise to practical, real-world scenarios.

Throughout the program’s duration, the students were fully immersed in a practical examination of the Energy Utility sector. They actively participated in the planning and execution of a live project tailored to offer a thorough comprehension of several key components:

Energy Management

Students gained hands-on experience in managing energy resources efficiently, optimizing consumption, and addressing power-related challenges.

Data Analysis

They delved into data analysis, including the collection, processing, and interpretation of data from various sources within the Energy Utility domain.

Predictive Modeling

Students honed their skills in predictive modeling, enabling them to forecast energy demand, identify potential faults, and suggest proactive maintenance strategies.

System Reliability

The program emphasized system reliability, with students working on solutions to ensure uninterrupted energy supply and minimize downtime.

Scalability

Students explored strategies for scaling Machine Learning solutions to accommodate the evolving needs of the Energy Utility sector.

Fault Tolerance

They developed expertise in creating fault-tolerant systems that can withstand unexpected disruptions and maintain operational integrity.

This holistic approach provided students with a well-rounded understanding of the challenges and opportunities within the Energy Utility domain, equipping them with practical skills and knowledge to excel in the field.

How do the selected specific outcomes align with the business problem supported by business and/or academic literature?

The selected specific outcomes are closely aligned with the business problem supported by both business and academic literature in the context of the energy crises and failures in the solar power generation industry. Here’s how they align:

Weather Input Features

Business and academic literature have repeatedly emphasized the importance of considering weather input features in solar power generation. Neglecting these features has led to energy crises in the past. The specific outcomes, which include Energy generation per day, Peak power generated by the inverter per day, and Peak global incident irradiance per day, directly address this concern by incorporating critical weather-related factors into the prediction model.

Financial Analysis and Energy Trading

The outcomes from the prediction model are pivotal in financial analysis, energy trading, and optimizing export strategies. This alignment with the literature is crucial because it underlines the significance of data-driven decision-making in energy utility operations. Academic research often highlights the need for leveraging data to make informed financial decisions in the energy sector.

Operational Cost-Cutting

Business literature frequently discusses the need for operational cost-cutting in the energy industry. The specific outcomes provide multiple options for achieving this objective by optimizing energy generation and export strategies, ultimately contributing to cost savings. This aligns with the broader industry focus on efficiency and cost reduction.

Consumer Demand and Supply Stabilization

Aligning with academic literature, the outcomes also contribute to stabilizing consumer demand and supply in the energy sector. By better predicting energy generation and optimizing export strategies, the industry can ensure a more consistent and reliable energy supply, addressing past issues of energy failures and crises.

Bridging the Gap Between Theory and Application

Business and academic literature often highlight the gap between theoretical knowledge and its practical application. The Energy Utility Project serves as a practical platform for students to bridge this gap, aligning with the literature's emphasis on preparing students for real-world challenges in the dynamic field of energy technology.

In summary, the selected specific outcomes directly address the business problem of energy crises and failures in the solar power generation industry, as supported by both business and academic literature. They incorporate weather input features, enable informed financial decisions, contribute to operational cost-cutting, stabilize consumer demand and supply, and prepare students for the practical challenges of the energy technology sector.

Major Tools use by team to develop the project

Project Strategic Timeline

It provides an overview of the project’s objectives, major activities, and timelines, aligning the project’s strategic goals with its execution plan.

Gratitude for an innovative association: Academic Cooperation with Eleve8 in Practical Learning

I want to extend my heartfelt gratitude to you, as well as to our esteemed Director Sir Dr. BC Sharma, Dean of Accreditation Dr. Ramendra Singh, and our dedicated Head of Department Dr. Jaideep Kumar (Associate Professor & Head CS in IOT), Dr. Vinish Kumar (Prof & Head CS in ML/AI and Dr Priti Sharma ( Prof & Head CS in DS) for your unwavering support and guidance throughout the completion of our project on Machine Learning, Artificial Intelligence, Data Science, and IoT.

Your mentorship and encouragement played a pivotal role in the success of this project. Your insights and expertise enriched our understanding and provided valuable direction at every stage. Your belief in our capabilities motivated us to strive for excellence and achieve our goals.

We are proud to have had the opportunity to work on such a cutting-edge project, and it wouldn’t have been possible without your vision and leadership. Your commitment to fostering innovation and excellence within our institution has made a difference.

As we move forward, we remain inspired by your dedication and look forward to continuing our journey of exploration and discovery under your guidance.

Thank you once again for your invaluable support.

With sincere gratitude,

Team Eleve8 Solution Private Limited

After completion of the project, The trainees have been offered internship opportunities from the

The journey of the project trainee has been one of growth, learning, and valuable experience

We've accumulated numerous cherished memories throughout our journey

Take your career to new height!

Join hands with Eleve8 to elevate your professional journey. Gain valuable experience by tackling real-world industry and data challenges while creating solutions in the fields of Machine Learning and IoT. Receive guidance to effectively address these challenges and build the confidence to present your solutions with expertise.