INNOVATIONS IN SMART CITY BY DR. PRADEEP KUMAR YEMULA CHARAN TEJA - - PowerPoint PPT Presentation

INNOVATIONS IN SMART CITY

BY

• DR. PRADEEP KUMAR YEMULA

CHARAN TEJA S

Definition of SMART CITY

The Smart cities Council defines a smart city as one that “uses information and communications technology (ICT) to enhance its livability, workability and sustainability.”

Core Functions of a SMART CITY

Collect Communicate Crunch

Responsibilities of Smart City

Built Environment Energy Telecommunications Transportation Water and Wastewater Health and Human Service Public Safety

Technology enablers

Instrumentation and Control Connectivity Interoperability Security and Privacy Data Management Computing Resources Analytics

Smart City Framework

Instrumentation and control Connectivity Interoperability Security and Privacy Data Management Computing Resources Analytics Built Environment Energy Telecommunications Transportation Water and Waste Water Health and Human Service Public Safety

Barriers of a SMART CITY

Siloed, piecemeal implementations

Benefits of SMART CITY

Livability Workability Sustainability

Traditional Cities Vs Smart Cities

Indian Context on Smart Cities

Growing urbanization

Urban Share GDP in India

Paths to Development

Vision for Smart Cities

• As the fruits of development reach an increasingly large number of people, the pace of

migration from the rural areas to the cities is increasing.

• A neo middle class is emerging which has the aspiration of better living standards.
• Unless, new cities are developed to accommodate the burgeoning number of people, the

existing cities would soon become unlivable.

Drivers for Smart City

Competitiveness

Investment Opportunities Quality of Life

Employ ment

Smart Cities

Definition of Smart City

Smart City

Competitiveness Sustainability Quality of Life

Pillars of Smart City

Social Infrastructure Physical Infrastructure Institutional Infrastructure

Sustainability

Emplo yment

Quality

• f Life

Economic Infrastructure

Economic Infrastructure

Industrial Parks and Export Processing Zones IT / BT Parks Trade centers Service Centres, such as tourism centres Skill Development Centers Financial Centers and Services Logistics hubs, warehousing and freight terminals Mentoring and Counselling services

Social Infrastructure

Education Health Care Entertainment

Physical Infrastructure

Mobility Reliable utility services Water Supply Sanitation Solid Waste Management Storm Water Drainage Electricity Internet and Telephony

Institutional Infrastructure

Responsibilities for different services are fragmented across multiple institutions, making the situation complex for any citizen. Governance by Incentives rather than Governance by Enforcement. Smart Cities would have municipal offices fully automated so that citizens have the ability to seek and the municipal offices the ability to deliver services in real time, through IT based facilities. Public participation in governance should be made possible through the social media and by making all information available in the public domain.

Instruments of Smart Cities

Use of Clean Technologies Use of ICT Participation of the Private Sector Citizen Participation Smart Governance

Smart Grid

Self-healing

• The grid rapidly detects, analyzes, responds, and restores.

Empowers and incorporates the consumer

• Ability to incorporate consumer

Equipment and behavior in grid design and operation. Tolerant of attack

• The grid mitigates and is resilient to physical/cyber-attacks

Smart Grid

Provides power quality to users:

• The grid provides quality power consistent with

Consumer and industry needs. Accommodates a wide variety of supply and demand

• The grid accommodates a variety of resources, including demand response, combined heat and power, wind, photovoltaic, and end-use efficiency.

Fully enables and is supported by competitive electricity markets. Transform the Indian power sector into a secure, adaptive, sustainable and digitally enabled ecosystem that provides reliable and quality energy for all with active participation of stakeholders

Identifying Smart Cities

One satellite city of each of the cities with a population of 4 million people or more(9 cities) All the cities in the population range

• f 1 – 4 million people(44 cities)

All State/UT Capitals, even if they have a population of less than one million (17cities) Cities of tourist and religious importance (10 cities) Cities in the 0.5 to 1.0 million population range ( 20 cities) In Delhi, it is being proposed that DDA will develop a new smart city through the land pooling scheme as a demonstrative city and the NDMC area may also be considered for demonstrating all the components of Smart Cities.

Operational Procedures

Citizen Reference Framework Smart Cities Development Plan

GIS Mapping Spatial Mapping ICT Mapping Master Plan

Environmental Sustainability plan

Case Studies on Smart Cities

Case study -1 Rio De Janerio

• Collects information about transportation,

water, energy, weather and other conditions from 30 different cities.

• Communicate the information to powerful

computers.

• Crunch the data and present in a unified control

center.

• It can predict some conditions in advance, such

as where floods will occur during severe storms providing the advantage of situational awareness

Case Study-2 Quebec, Canada

• One-stop

shopping for city services

• Permits
• Licensing
• Taxes
• Taking care of business

needs with numerous different city departments

Case Study-3 London

• Love Clean London

portal and mobile app

• Litter and graffiti

Case Study-4 Malta

• Worlds first smart island
• Goal of Smart City Malta is to put everything a

high-tech company needs to succeed in one place, including state-of-the-art ICT infrastructure along with a host of IT, media and production services.

• Roll out smart meters for all electric and

water customers.

• Metering data is integrated into new back-
• ffice applications for billing. It is also used for

analytics that locate problems and determine when and whether to expand the grid

Case Study-5 Indiana City

• South Bend, Indiana had a serious problem:

wastewater spilling into the St. Joseph River and welling up in basements.

• The integration of IBM technology with smart

valves and sensors from business partner EmNet helped the city to be proactive in its wastewater management, avoiding additional infrastructure investments while improving public health.

• Notre

Dame students came up with innovative apps to allow residents to report flooding, social media tools that collect information on water systems and more.

Case Study-6 Eco-City in Tianjin

• In

June 2013, Council member Itron completed the installation of 25,000 smart meters for water, heat and gas.

• The network allows the city to achieve its

vision

• f

energy and water resource conservation by providing actionable data such as high accuracy readings and reading rates automatic meter reading and graphical data analysis to educate residents about their energy and water usage.

Case Study-7 Seattle, Washington

• The result is a smart buildings pilot for the

downtown area inspired by the smart buildings pilot implemented

• n

Microsoft’s Redmond campus.

• Microsoft has joined with the Seattle 2030

District, a public-private collaborative

• f

downtown Seattle property

• wners

and managers that has established a 50% energy use reduction goal by 2030.

• A cloud solution based on Microsoft Azure cloud

technology will collect data from the myriad systems in those buildings and use data analytics to provide a prescriptive approach to how the building management systems can be tuned to improve energy efficiency.

Case Study-8 Seattle, Washington

• SeeClickFix allows anyone to report and track

non-emergency issues anywhere in the world via computer or mobile device, empowering citizens, community groups and governments to improve their neighborhoods.

• It uses distributed sensing to recognize patterns

such as those that gradually take place on a

• street. Citizens can report issues on the go, and

set up watch areas to monitor their block.

• Governments can watch for potholes and cracked

sidewalks.

• Police can monitor crime issues reported within

the precinct.

Case Study-9 Paris

• Syndicat Mixte Autolib is an electric car-sharing

program established by the city of Paris and 46 surrounding municipalities to relieve traffic congestion, reduce noise and air pollution and provide people with more flexible transit options.

• Implemented by logistics company IER, the

intelligent system based on Council member Microsoft’s Windows Embedded provides connectivity between the in-car system, registration and rental kiosks, charging stations and a central management system.

• The

solution has reduced carbon dioxide emissions by 1.5 metric tons annually and replaced 25,000 privately owned gas vehicles. By using Autolib, former car owners have cut their transportation costs by approximately 90 percent annually

Case Study-10 Vancouver

• Milestones to mark progress.

Vancouver has annual implementation updates and monitors what’s been accomplished so far and what still needs to be done as 2020 approaches.

Conclusion

THANK YOU

BY

• DR. PRADEEP KUMAR YEMULA (YPRADEEP@IITH.AC.IN)

CHARAN TEJA S (EE14RESCH01005@IITH.AC.IN)

SMART CITY MISSION

Ministry of Housing and Urban Affairs Presentation to the Parliamentary Standing Committee on Urban Development 26 April 2018

Outline

• Planning
• Mission Strategy
• Selection Process
• Financial Landscape
• Timeline for Completion
• Recent International Recognitions
• Implementation
• Urban Infrastructure & Services
• Use of Digital Technology
• Ease of Living

2

Planning

3

Mission Strategy

Integrated Smart Solutions through Command & Control Centre

Basic Infrastructure and Services Area based development Pan City

etc.

Selection Process

Stage – I

Intra-State city selection by State govts.

• 100 cities allocated to States
• Intra-state competition
• Cities selected by States
• 110 Potential Smart Cities

prepared Smart City Proposals

Stage – II

All India competition

• 4 rounds completed
• 99 cities selected in 4

rounds

• Shillong given time to

submit SCP

• City Selection is based on the idea of Cooperative and Competitive

Sub-Federalism

• City Selection Process follows a Challenge method: Two stages to

select cities

5

99 Smart Cities to make investment of Rs. 2.04 lakh crores

Financial landscape

• No. of Selected

Cites

20 40 30 9

Period of selection

Jan 2016 Sept 2016 June 2017 Jan 2018

Total no. of Projects

829 1809 1890 262

Investment (in Rs Crores)

48,064 83,698 57,393 12,823

Round 1 Round 2 Round 3

Four rounds of competition

Round 4

99 Smart Cities to make investment of Rs. 2.04 lakh crores

Financial landscape

Center + State Govt., 45% Convergence, 21% PPP, 21% Debt/Loans, 5% Own, 1% Others, 8%

16.60% 15.00% 12.70% 10.10% 9.50% 6.40% 5.50% 4.70% 4.20% 3.50% 2.60% 2.50% 2.50% 2.40% 1.80% Urban Transport Area Development Economic Development Energy IT/ICT solutions Housing Water Supply Sewerage NMT & Pedestrian Others Environment Storm Water Drainage Social Sectors Solid Waste Management Safety

Sector wise investments in 99 cities

Timeline for completion

(as given in the SCP)

• Round 1 cities- 2019-20 to 2020-21
• Round 2 cities- 2019-20 to 2021-22
• Round 3 cities- 2020-21 to 2021-22
• Round 4 cities- 2020-21 to 2022-23

10

Recognition to Bhubaneswar – American Planners Association Award 2017

12

Recognition to Bhubaneswar – Canadian Institute of Planners

13

Challenge process reviewed-London School of Economics

“…the Smart Cities Challenge has generated enthusiasm and galvanised city leaders and citizens … India’s experience navigating the process will have implications and lessons for other rapidly urbanising regions. India’s smart cities can be ‘Lighthouses’- not just for Indian cities but also for cities around the world”

14

7385 9037 10214 11597 14672 16978 18761 19937 23243 626 937 1246 1765 1872 2355 3113 4438 4960 Aug-2017 Sep-2017 Oct-2017 Nov-2017 Dec-2017 Jan-2018 Feb-2018 Mar-2018 Apr-2018 (All figures are in Rs. crore)

Mission – momentum is picking up !

Note: Data from Online MIS of MoHUA SPV formed PMC selected Work Completed Work Order Issued Tender issued 91 67 4,960 23,243 17,212 Increase in Work started in projects over last nine months

214%

Increase in Work Completed

• f projects in last nine months

691%

15

Urban Infrastructure & Services

Work Started/Completed

• Smart Water- 36 cities; Rs. 3,887 cr.
• Smart Solar- 46 cities; Rs. 833 cr.

Tenders called

• Smart Water- 10 cities; Rs. 996 cr.
• Smart Solar- 7 cities; Rs. 190 cr.

18

Key projects- Water, Sewerage & SWM

• 24x 7 Water Supply (Rs. 5 cr.), Surat- Completion by

July 2018

• Water Supply (Rs. 48 cr.), Thanjavur- Completion by

April 2018

• Sewage Treatment Plant (Rs. 234 cr.), 2 locations in

Surat- Completion by June 2019

• Waste to Energy Plant (Rs. 178 cr.), Jabalpur- Work

Completed

ESR, Surat Waste to energy plant, Jabalpur

19

Key projects - Solar

• Solar Rooftop on public buildings (Rs. 34 cr.),

Chandigarh- Completion by 2022

• Solar City Program Rooftop- (Rs. 8 cr. per MW),

Bhubaneswar- Phase 1 completed; Phase 2 completion by April 2019

Solar Rooftop at ISBT Sec-43, Chandigarh Solar City Program Rooftop, Bhubaneswar

20

Use of Digital Technology

Work Started/Completed

• Smart City Centre- 23 cities, Rs 2,965 cr.

Tenders called

• Smart City Centre- 31 cities, Rs 2,566 cr.

21

Key projects – Smart City Centre

• Command & Control Centre (Rs. 89 cr.), Vadodara- Work

Completed

• Command Centre (Rs. 135 cr.), Vishakhapatnam- Work

Completed

• Rajkot Eye Way (Rs. 69 cr.), Rajkot- Work Completed
• Command & Communication Centre(Rs. 95 cr.),

Kakinada – Inaugurated

Command & Control Centre, Vadodara Command & Communication Centre, Kakinada

22

Key projects – Smart City Centre

• City Operation Centre(Rs. 28 cr.), Nagpur- Phase 1 completed
• Command & Control Centre(Rs. 239 cr.), Ahmedabad- Work

completed

• Traffic Management (Rs. 15 cr.), Bhubaneswar- Completion by

Dec 2018

• Kochi One Card- (Rs. 25 cr.), Kochi- Work completed

City Operation Centre, Nagpur One Card, Kochi

23

IIT Hyderabad

Building Monitoring System for Data Analytics and Demand Characterization: Case Studies from (i) IIT Hyderabad and (ii) Swansea University

Pradeep Kumar Yemula (IITH) and Richard Lewis (Swansea University)

IIT Hyderabad

Evolution of the Grid

IIT Hyderabad

Plan of Action

05

• 1. Gather feedback from the Sept 2018 review meeting.
• 2. Dr. Pradeep from IITH will be visiting Swansea

university during Nov-Dec under the JUICE Early Exchange Programme for further collaboration.

• 3. Data Sharing Platform to be made available to IndoUK

researchers

Overview of Work Package MGD 2.2

Present Status

04

Installation of (i) 5KW rooftop solar PV microgrid with storage, and (ii) Building Monitoring System, completed at IITH. Similar systems existing at Swansea University and collaboration is ongoing on Data exchange and Demand Analytics.

Expected Outcomes

03

Demonstration that data analytics can identify trends in energy use in solar homes and microgrids that indicate growing economic activity and need to expansion to meet development goals

Collaborators

02

Pradeep Yemula (IITH), K. Sivakumar (IITH), Richard Lewis (Swansea University), Tim Green (ICL), + looking for more India and UK partners

Title of Collaboration

01

Data Analytics for Demand Characterisation / Forecasting

4

IIT Hyderabad

TimeLine

March 2018 Procured Hardware and Software, Initiated work on Building Monitoring System, Published 1 conference paper March 2020 Further Research March 2017 Start of the project March 2021 End of Project March 2019

Collaboration with UK partners, Joint Research, Exchange of researchers 1 2 3 4

IIT Hyderabad

Comparison of Case Studies

Sno Project Parameter IITH Case Study Swansea Case Study Collaboration Opportunity 1 Objective of the Building Monitoring System Building energy monitoring for load characterization Obtaining evidence for Buildings as Power Stations Large scale data collection and processing 2 Size and Scope Two academic buildings in campus Two buildings in campus Benchmarking buildings against both sites 3 Applications Data Analytics (descriptive and predictive) Self supporting / Off grid buildings Data driven building energy management

IIT Hyderabad

Building Monitoring System at IITH Case Study 1:

IIT Hyderabad

Scope of Building Monitoring System at IITH

8

IIT Hyderabad

Academic Block A panels

Normal Panel Emergency panel 9

IIT Hyderabad

Block Diagram of Building Monitoring System

10

IIT Hyderabad

Test setup developed @ IITH

Components:

• LnT Nova Multi function

meter

• Raspberry pi 3b
• RS 485 to USB converter
• 5A & 16A sockets
• Bulb Holders

11

IIT Hyderabad

Data collection setup

IIT Hyderabad

Link to Sample Raw Data from 4 meters

https://www.dropbox.com/s/7f05v6ktjtwrbut/RawData-IITH.zip?dl=1 This folder contains 4 raw data files:

• 1. IITH_A_Block_First_Floor_East_side.txt
• 2. IITH_A_Block_First_Floor_West_side.txt
• 3. IITH_A_Block_Second_Floor_East_side.txt
• 4. IITH_A_Block_Second_Floor_West_side.txt

13

IIT Hyderabad

Data acquisition from meter

14

IIT Hyderabad

Data Visualization

15

IIT Hyderabad

16

Plots from Raw Data:

Plot of Instantaneous Power

X-axis - row number of data (each row represents one minute) - Total X-axis is about 30 days Y-axis - Total Power - (in KW)

The daily pattern of the loads can be seen here

IIT Hyderabad

Data Analytics based on Building Monitoring System

Alerts:

• 1. Under voltage (<220 V) and over voltage (>240 V).
• 2. Power Failure.
• 3. Excessive Consumption at each Circuit/Panel than their max rated power.
• 4. Crossing EMD more than prescribed limit.
• 5. Energy leakages due to human mistakes.
• 6. Auto Email/SMS to each block on their monthly power usage.

Analysis:

• 1. Break even analysis of energy consumption for each floor and/or meter.
• 2. Normalised Consumption pattern (KWH/Sqm) for each floor and common area.
• 3. Benchmarking Each office/block etc against the standard green building practises
• 4. Weekend/holiday consumption.
• 5. Comparison of average power consumption against peak consumption for each

meter.

• 6. Analysis to track health condition of any critical equipment like Motors and Lifts
• 7. Billing calculation.
• 8. Accountability of diesel consumption.

IIT Hyderabad

5KW solar panel and grid tied inverter

18

IIT Hyderabad

Microgrid Team at IITH and Publications

Faculty: 1.

• Dr. Pradeep

Kumar Yemula, 2.

• Dr. Siva Kumar,

PhD Students under IndoUK project: 1.

• Ms. Sandhya

CSR (Joined Jul 2017) 2.

• Mr. Vikram

Cherala (Joined Jul 2018) Other PhD Student (MHRD funded): 1.

• Mr. Charan Teja

Accepted: 1. Charan Teja S, Sandhya CSR and Pradeep Yemula, “Load Curve Monitoring and Data Analytics: Case Study on a Campus Building”, Innovative technologies in engineering (ICITE 2018), Hyderabad

• 2018. (Link)

2. Charan Teja S and Pradeep Yemula, "Reducing the Ageing of Transformer using Demand Responsive HVAC," 2018 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), Singapore

• 2018. (Link)

3. Anil Kumar Mathur, Charan Teja S, Pradeep Yemula, “Optimal Charging Schedule for Electric Vehicles in Parking Lot with Solar Power Generation”, 2018 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia), Singapore 2018. (Link) 4. Sandhya CSR, Sri Vaishnavi tirunagari, Subhasmitha sahoo and Pradeep Yemula, “Extraction of Data from a RS 485 enabled Multi Function Meter for building monitoring systems”, 20th National Power Systems Conference (NPSC-2018) NIT Tiruchinapalli, Dec

• 2018. (Link)

IIT Hyderabad

Work to be Done

• Initial stages of implementation of BMS
• User Interface to be further Developed
• Data Sharing Platform to be made available to the JUICE and

IUCERCE teams.

• Integration of 5 KW grid connected rooftop solar system with storage
• Development of Energy Management algorithms
• Any other collaboration activity

IIT Hyderabad

Active Buildings at Swansea University Case Study 2:

IIT Hyderabad

Active Classroom

Photovoltaic roof Battery storage Solar air collectors Living wall Steel screw pile foundations Low energy use appliances Fabric-first approach Re-usable, recyclable materials Design for Deconstruction De-mountable superstructure Minimal materials Circular economy in buildings Whole-life costing Biodiversit y Natural daylight

IIT Hyderabad

Data capture

• Power information obtained from 9 sections of 16.2kW PV array
• V, I, P and Wh readings taken once every 5 seconds
• Power information obtained from charge controllers
• V, I, P, Wh, SOC and Bank Temperature every 5 seconds
• Power information obtained from inverters
• V, I, P, VA, Wh, Line frequency every 5 seconds
• In-plane insolation collected per-second, located in middle of array
• Building fabric temperatures including outside steel cladding surface

temperature, duct temperatures and floor temperatures

• 90 temperature readings taken every 5 seconds, internal & external
• Data all processed into single relational Database

IIT Hyderabad

Active Classroom - Panel Structure

Design for Deconstruction New construction method – lightweight, steel framed

interlocking panels forming walls, floors and roof Steel screw pile foundations

IIT Hyderabad

• Renewable energy generation 16.2kW Photovoltaic panels
• Building integrated, low voltage
• DC bus charging, compact high efficiency units

Building Integrated PV Roof

IIT Hyderabad

Plant Room – Power System

• AHI Battery storage
• 2x 30kWh Aquion M-Line battery modules, Cradle-to-Cradle certified

IIT Hyderabad

Solar irradiance, battery state of charge, and PV power output on a clear day – PV output reduces to building load when batteries reach capacity, limiting generation. Transient response of PV generation to increase building load is observed

Curtailment in Island mode

IIT Hyderabad

Available solar resource

Heat map of daily PV generation (kWh) for the year 2017 – seasonal variability is high, with winter output almost 60% less than summer

IIT Hyderabad

Active Buildings

Active Office Active Classroom

IIT Hyderabad

Energy transfer Classroom Office EV PV Battery Battery PV Grid

IIT Hyderabad

Building Monitoring System for Data Analytics and Demand Characterization: Case Studies from (i) IIT Hyderabad and (ii) Swansea University Pradeep Kumar Yemula (IITH) and Richard Lewis (Swansea University)

Thank you….!