Algorithms – EnergyTech Ventures

November 25, 2017February 13, 2019

CAN- Compressed Air Network Optimisation Algorithm! #EnergyAnalytics #EEHub

Compressed Air is one of the forms of energy that finds use in most industries, in some industries like Textiles it contributes to significant portion of the overall energy consumption.

Compressed Air Networks i.e. multiple number of compressors operating in tandem, offer potential for optimisation and improve energy productivity CFM/KW by around 5%-7% (in some cases going as high as ~12%)

Multiple factors must be looked at while considering optimising the generation and distribution of Compressed Air and the overall network.

CAN- Compressed Air Network Optimisation Algorithm

Our Algorithm works on the operational data I.e. data from each of the compressor, operating behaviour and over a period suggests optimisation possibilities resulting in better utilisation of the network, correct operation settings, resulting in energy productivity gains.

Factors/Aspects considered by the algorithm:-

Weather Conditions
Set Points for each compressor
Operational behaviour of each compressor under the influence of the network.
Maintenance

Algorithm would be available on EE Hub, users could either purchase API calls or use the algorithm as DIY tool through our web based application EnView.

September 17, 2017February 13, 2019

Optimising Energy Consumption in Humidification Plants #Textile #EnergyEfficiency

Humidification plants in Textile (spinning) consume almost 15%-18% of the total electricity consumption. Out of which nearly 80% to 90% goes to circulating “air” and is consumed by significant number of Fans (Industrial), hence even if the H plant has automation it at most impacts the 10% to 20% of the total electricity consumption, delivering gains of around ~1%.

Carefully playing around with the air flow during different time zones (day wise) could deliver gains of around 5%-7% at no or minimum cost (VFDs are installed across all Fans)

Knowing when to “manipulate” air flow

Operators do intervene and manipulate the air flow during the day based on in room conditions etc, however it is something that is mostly “reactive” in nature. If we can collect data sets like Heat Load, In Room Condition etc from different data acquisition systems, we would be able to predict exact hours when the air flow could be optimised and to what %, this allows the operator to plan the changes and be more scientific and data driven without having to indulge in any complexity.

2. Automating the “manipulation”

For organisations that do not want to have this done manually, we have developed integrated logic for providing feedback to VFD on control of air flow factoring in room and outside conditions.

Want to give our algorithm a test? Visit www.boostenergyefficiency.com , register your request and our team will take it ahead from there!

September 13, 2017February 13, 2019

Discussions, Deliberations and Engagement at India’s First Energy Data Analytics Summit

The Energy Data Analytics Summit 2017 hosted by EnergyTech Ventures at The Claridges, New Delhi, on 8^th September 2017 was a grand success. The event saw around 90+ delegates and 15 speakers from reputed organisations take part and have engaging discussions on the Future of Energy Data Analytics in today’s emerging economies.

There were high ranking officials from Businesses like – Coca-Cola, Aditya Birla Group, Welspun, United Phosphorus Limited, Vardhaman; from IoT/IIoT companies like – Bosch, Zenatix, Loudcell; from Development Agencies like – SIDBI, World Bank, IFC, GiZ, Shakti Foundation and from Think Tanks like – TERI, WRI; and NGOs like – Carbon Disclosure Project and The Climate Group; present at the Summit as delegates as well as speakers. TERI, The Climate Group and Inc42 were Supporting Partners to the Summit.

Opening & Key Note Address

Mr. Abhishek Rungta, (Founder & Advisor at EnergyTech Ventures) welcomed the delegates and was followed by the Keynote Address from Mr. Umesh Bhutoria (Founder & CEO at EnergyTech Ventures) who set the tone for the day by speaking about the ‘Why and How of Energy Data Analytics’. He touched upon the importance of Energy Data Analytics in today’s Industrial age and why there is immense potential in the field of IIoT.

Numerous future possibilities like better Resource Productivity, Open markets in terms of data sharing/ value creation, better Governance in framing enabling policies were addressed by him along with some immediate challenges like the need for a single platform, need for collaboration among the various members of the entire IIoT ecosystem.

There were 3 Thematic Sessions and a Fire-Side Chat Session which saw lively discussions from the participants and the audience.

During the first thematic session, the topic addressed was – What would inspire Businesses to invest in an Energy Data Analytics Strategy.

Mr. Jarnail Singh (India-Head, The Climate Group) touched upon the fact the Businesses need to prepare for Climate Change and not treat Climate Change as a Business. He also said that more and more companies are demanding tools that could allow them to understand their data better and hence take decisions towards Energy Productivity improvement targets.

Mr. Nandakumar Sankar (Head-Sales, Energy Solutions and Analytics, Bosch) talked about Industry 4.0 and what kind ROI can Data Analytics bring about for organisation. He also said that they came across a lot of organisations that have either no data or very low data and he feels that can be changed once there is a better understanding of how data can be used and we see an evolution of the use cases.

The second thematic session talked about – How can Data and Technology be leveraged to scale Supply Chain Programmes and reach out to more SMEs.

Mr. Shubhashis Dey (Program Manager, Energy Efficiency, Shakti Foundation) mentioned that Manufacturing SMEs have a multiplier effect on Energy Efficiency Programs if proven to work positively.

This was concurred by Mr. Deepak Krishnan (Manager, Energy program, World Resources Institute) and he added that the trust factor is also very important for SMEs as they need to truly believe that their Data cannot be used by anyone else for their benefit.

Mr. Rajiv Kumar (CEO, ISTSL) also agreed with these views and explained how Data Digitization is helping bringing about easy sharing of this data in a trusted manner. MSMEs can are now being able to adopt and implement Energy Conservation Measures in an easier manner due to various initiatives taken up by various Organizations.

The third session was taken via video call by Mr. Steven Fawkes (Founder of EnergyPro, London). He spoke about – Business Model Innovation in context of Industrial Energy Efficiency and Energy Productivity. One of the most significant message from his presentation was

“There is no market for Energy Efficiency, there is only market for Stuffs and Services”. This is where data and technology play a role in making the conventional markets work in an unconventional way.

EnergyTech Ventures also then announced the launch of the Energy Efficiency Mirco-Services Hub at the end of these 3 sessions. Boost EE is a hub of sector specific Algorithms/APIs that allows Technology players /IoT Platforms to leverage sector specific algorithms, enhance offerings and thus create more value for all Stakeholders.

Currently 20 APIs from across 4 sectors and 6 categories have been hosted on the Hub, EnergyTech Ventures aspires to take the API count to 100 by the end of 2018.

The final session for the day was the Fire Side Chat which was panelled by Mr. Girsh Sethi (Senior Director, TERI), Dr. Satish Kumar (Ex-Executive Chairperson, AEEE), Mr. Damandeep Singh (Director, CDP-India), Mr. Prabir Niyogi (Chief Executive, RP-Sanjiv Goenka Group), Dr. G C Datta Roy (Founder & CEO, DESL), and Ms. Vandana Gombar (Editor, Bloomberg New Energy Finance).

Mr. Singh spoke about the importance of disclosure when it comes to Energy Efficiency and Clean Energy as large funds companies to document, estimate and make public any environmental risks. Around 6000 companies and 600 cities have disclosed to CDP and how this Data is used for the betterment of the economy as a whole.

Dr. Roy, with over 50 years of experience in the field of Energy spoke about need to take orbital approach in mainstreaming Energy Efficiency as against to the incremental approach being taken currently.

Dr. Kumar postulated that Data is required from the consumption side as well as the production side and Data cannot work in isolation. According to him, Data brings Accountability, Responsibility and finally Action.

Mr. Neogi spoke from the Utility point-of-view and agreed that the economics are changing and utilities have to adapt to the same. The emergence of renewable energy is bringing about a shift in how Utilities conduct their business and what has to be done to keep abreast of the same.

Ms. Gombar from Bloomberg New Energy Finance presented some interesting statistics on how for some development banks spend on Energy Efficiency had surpassed spend on Clean/Renewable Energy.

The end of this session was followed by the final announcement of the next Energy Data Analytics Summit in September 2018 in Jaipur, it’s going to be a 2 day event and we are hoping to have some International flavour to it as well!

Also announced conducting Sector Specific Workshops on Energy Data Analytics under our “AIR Series” Workshops.

For more details one can visit https://haveyouaired.com/ .

August 27, 2017February 13, 2019

Retrospective assessments before moving to predictive alerts #DataAnalytics #EnergyAnalytics

Greetings!

I was recently onsite for a data discovery exercise, unit has one of the largest single location manufacturing capacity in its sector. Of a lot of data sets we looked at, one of the interesting case that came in front of us was that of a vibration of a Fan, one that is very important in the entire process, lowering of the operational RPM could result in significant production loss.

We took past data sets and wanted to understand how the retrospective assessment is done by the team, as expected a lot of time went into fact finding and was dependent on a lot of people. Besides taking time, no one could point out exactly when the issue started building up and when would have been the right time to respond to it?

What did our algorithms (series of logics, no ML really) find out?

1. Total of 1953 peaks happened, where in the rise in vibration % was such that if continued it could have mean an X% increase over 24 hours.

2. 1606 cases where the peaks where in consecutive points the vibration increased by 50% of X%, we have called them as Alerts. (In the current scheme of things alarm only goes when things are out of control)

3. 823 out of 1606 cases had consecutive alerts, in quite of a few of them 4-5 alerts came in successively. (Remember these alerts are not simply a>b “raise alarm”, it tracks the tendency and past pattern)

4. There were 7 occasions (exact date and time pointed out) when plant had an unplanned shutdown (over 8 hours) and the problem could have been addressed. (Next time when that happens an maintenance team already has a ticket to address the issue)

5. Algorithm automatically pointed out how maintenance activity in one of the cases could normalize the increase in vibration %, while in the other they couldn’t or perhaps no action was taken. (So if a ticket is marked resolved and technically the problem stays, the algorithms points out it close to real time)

6. Because of last two tickets going un attended the unit lost out 7% production over a stretch of 5 weeks and had to wait for another unplanned shutdown to address the issue!

Point 1 to 6 happened even after people were looking at the screens 24X7! Time to have people taking actions and not looking at screens, real time monitoring is a thing of past, but to move to future the team needs to of adequate tools to do retrospective assessments and eventually go on to work on systems/tools that predict an anomaly building up well in advance!

Well that’s a real case study! Liked it? Would love to hear your views/thoughts!

Best Regards,

Umesh Bhutoria

August 13, 2017February 13, 2019

Micro Services in #IoT #EnergyAnalytics

Greetings of the day!

A year back i saw a video of Steve Singh, he was talking on the context of “micro-services” and how large technology companies want to leverage that to have more customers and more importantly more revenue/customer.

That’s when we started to work on our Energy Efficiency Micro-Services Hub (releasing on 8th September, 2017 on the sidelines of #EDASummit17). We open up our existing IPs (via APIs) as we continue to focus on developing more such IPs.

Interestingly our first #B2B engagement based (Cement Sector) on #API pricing has got a green signal. Our efforts of enabling more value creation in the #IoT ecosystem gets a boost and encourages us to continue to take our top of the value chain approach.

I look forward to seeing you at #EDASummit17 and having an engaging discussion. Visit www.haveyouAIRed.com for more details/registration.