Energy Sustainability in

Smart Cities
Success Factors of Smart City

 Energy Efficiency

 Energy Intensity

 Emissions Intensity
Elements of Digital Technology

 Energy Generation

 Energy Distribution

 Energy Consumption

 Demand-side management

 Producer-Consumer Activity
Towards Energy-Efficiency Gain…..

 Networked sensors

 Centralized Monitoring

 Unified Control of Buildings

Energy Emission Statistics

 Buildings, Infrastructure – 40%

 Residential Sector – 7%
Achieving Energy Efficiency…
 By monitoring consumption patterns, cities can identify
areas for improvement, implement demand-side
management strategies, and reduce overall energy
consumption.
 Smart cities leverage technology not only for real-time
monitoring but also for achieving significant energy
savings.
ENERGY AS A
CATLAYST
SUSTAINABLE GOALS

• Reduced carbon emissions

• Operational cost savings
• Decreased need for massive infrastructure investments
• Should be efficient in: information sharing, resiliency to disruptions, increased control
• Should provide high quality living to city residents
URBAN EFFICIENCY

• 30 % energy savings in public lighting energy reduction

• 20 % energy savings in reducing water losses and traffic delays

• 15% energy savings in reducing buildings operational cost

EQUIPMENTS

• Metering equipment and data concentrators:

• electricity meters
• heating meters
• gas meters
• water meters
• optical character recognition equipment
• data converters
• pressure sensors
SERVICES
• Process and activity analysis
• Determining metering points
• Designing the Energy Management System
• Implementing and operating the system
• Analyzing the results of the monitoring and identifying the energy saving opportunities
• Recommending measures to increase consumption efficiency
• Developing customized functions and reports
• Assessing results
• Analyzing the situation and recommending new measures to increase efficiency
EXAMPLES

• Smart lightning system: Adjust brightness of street lights with motion sensors to save
energy
• Smart traffic management system: Monitoring traffic flow using camera, radar, GPS for
adjusting traffic signals, speed limits and propose altenative routes
ROLE OF ICT AND IOT IN ENERGY MANAGEMENT?
Smart city efficiency
management
(1)Basic Indicators.
• Building networking is the foundation of smart cities. Smart communities and
smart security in smart city planning are originally important components of
building networking applications. To build a smart city, we must implement smart
construction in various industries and the development of the chain. If the
texture is correct, the model is black; in the file, you can change the three values
of k or d (corresponding to Berg) or print out the model attributes and change the
point color value or other attributes in material color. Among them, the data layer
is mainly responsible for the storage and distribution of big data on the platform;
the system layer is responsible for data management, including data acquisition
and analysis plans to encapsulate data-based services and provide corresponding
interfaces to the service layer. The guarantee system, standard system, and key
technologies are the guarantee of construction, the information foundation and
industrial system are the support of construction, the application system is the
function of construction, and the evaluation system is the measurement standard
of construction.
Protocol Support.
• The application management platform in the “smart city” needs to provide
services for public security prevention and control, traffic management, urban
visualization management, and social services. At present, the industry is
gradually adopting the enterprise service bus (ESB) IT architecture. The Internet
of Things has two communication modes, B/S and C/S. In the field of mobile
Internet, APP communicates with the server in the role of the client in C/S mode;
and the smart city energy efficiency system is a super-APP, which allows users to
program H5 through a built-in browser to control hardware devices ability, so the
communication module of its hardware platform is in B/S mode. The browser in
the Internet of Things protocol uses the HTML text markup language; that is, the
browser initiates a request to the server through the HTTP protocol (the request
content includes the URL, which is what we often say), and the server transmits
the HTML content corresponding to the URL as a response through the HTTP
protocol back to the browser. Use JSP/PHP and other technologies to develop and
design front-end web pages and simple logic in the cloud.
Energy efficient management system
algorithm
• In order to build an enterprise energy efficiency management platform based on
the Internet of Things with high availability, security, reliability, scalability, and
scalability, the master station software uses mature and standard J2EE (Java 2
Enterprise Edition) enterprise platform architecture to build multilayer
distributed application model; component reuse, consistent security model, and
flexible transaction control are adopted to make the system more portable and
adapt to the complex application environment, changeable business rules, and
information release of the enterprise energy efficiency management platform,
the needs of the system, and the need for future expansion of the system. The
experiment adopts the ModbusRTU protocol, and the expansion of the number
of high-order bytes can flexibly realize the deletion, addition, and modification of
sensor data. The intelligent energy efficiency monitoring system is an innovative
energy efficiency management system. Users can log in via a mobile phone,
tablet, or PC at any time and place through a web application interface to achieve
monitoring, optimization, forecasting, control, and other functions. The algorithm
implementation is shown in Figure 3.
• The intelligent energy efficiency monitoring system can implement algorithms including
monitoring current, voltage, energy consumption, power factor, electricity bills, energy demand,
and other electrical parameters in the office building power distribution system anytime and
anywhere: customized interface and asset panorama, intuitive equipment distribution, or single-
line diagram of the system to clearly understand the situation of the electrical system. The energy
efficiency synergy algorithm includes subroutines based on energy output and subroutines based
on energy consumption distribution. The principle of the subroutine based on energy
consumption distribution is as follows: analyze the evaluation of each energy consumption on the
item (by browsing records, usage records, etc.); calculate the similarity between all energy
efficiencies based on the evaluation of energy efficiency on the item; select the current energy
efficiency. N is the most similar energy efficiencies of the households; recommend the N items
with the highest energy efficiency evaluation and the current energy efficiency that has not been
browsed to the system. In addition, the intelligent energy efficiency monitoring system can also
achieve the following advanced functions: full life cycle management of circuit breaker
equipment, reminder of required operation and maintenance items at any time, reasonable
arrangement of spare parts procurement, and saving operation and maintenance costs, which is
the most simplified circuit breaker temperature monitoring program.
Optimization of the Energy Efficiency Management
System
• Data monitoring system is set up. The built-in metering module of the
circuit breaker can collect common parameters without the need to install
a test meter. The accuracy level of the metering module’s electric energy
measurement reaches 1.0, which can meet the requirements of most
applications. Modbus can be used in the equipment room, TCP or Modbus
RTU protocol for communication. In addition, the intelligent power
distribution monitoring system supports multisite deployment. At any local
gateway, it can be uploaded to the cloud platform via a wired network,
WiFi, or GPRS, and there is no need to use a data cable to connect to each
gateway for unified upload. Based on the above characteristics, the
intelligent power distribution monitoring system can reduce the wiring by
60% and the connection by 25%, and only through simple settings, multiple
site devices can be connected to the cloud within 10 minutes, as shown in
Figure 4.
•
Software upgrade and expansion. The intelligent energy efficiency management and
monitoring system supports plug-and-play. The travel time between any two task points
can be set as sequence-related preparation time. The input time promised for each
energy consumption data, including reservation data and instant data, can be mapped to
the early and late penalties in the pipeline scheduling problem. After doing such a
modeling transformation, there are a large number of heuristic algorithms that can be
used for reference in the energy efficiency data scheduling problem. The service layer is
responsible for providing platform functions to users, including user interface display,
interactive response, and the entrance to third-party value-added services. A classic
heuristic algorithm based on problem features is appropriately adapted and improved,
and very good results can be obtained. Compared with the previous algorithm, the time
consumption is reduced by 70%, and the optimization effect is good. Because this is a
deterministic algorithm, the result is the same how many times it is run. The optimized
algorithm is run once. Compared with the optimal results of other algorithms running 10
times, the optimization effect is the same.
•
Strengthen energy efficiency management methods. As an energy
efficiency index layer number dimensionality reduction problem,
dynamic optimization scenarios need to be considered, which
involves a large number of estimation links. By estimating the
completion time of each layer when there is only currently
uncompleted input data, shortening the system delay time,
quantifying business indicators and efficiency indicators,
reinforcement learning can be carried out, and the decision space
dimension needs to be calculated.. The intelligent power distribution
monitoring system supports third-party platforms to call data from
the cloud through API.
•
Improved energy efficiency demanding side management. The enterprise energy
efficiency management service cloud platform mainly provides external services in the
form of contract energy management to promote the development of contract energy
management. The article tries to use the idea of robust optimization or random data
planning, based on random scene sampling, to calculate the output energy efficiency
data of the Internet of Things. At the same time, combining real energy efficiency data
and algorithm design process, design optimization algorithm learns and evolves on cloud
platform. Internet channels are mainly used to realize the pairwise interconnection
between the platform and users and third-party value-added service providers. The
enterprise energy efficiency management service cloud platform can help enterprises
establish a complete power consumption supervision system. Through data analysis,
combined with their own conditions, they can customize energy-saving solutions to
achieve energy-saving effects. In the implementation of the energy-saving plan, a series
of markets such as energy-saving equipment manufacturers and project construction
units will be stimulated.
• In a production area, there are two 10 kV incoming lines, one for use
and the other for backup. 4 transformers: 1# and 2# transformers are
located in the 1# power distribution room with a rated capacity of
630 kVA, and 3# and 4# transformers are located in the 2# power
distribution room with a rated capacity of 1 000 kVA. All circuits in the
power distribution room are required to measure and connect to the
intelligent power distribution monitoring system. 1# and 3# two
transformer master switch circuit breakers, which act as gateways
between the two power distribution rooms and only need to connect
the remaining circuit breakers to the circuit breakers acting as the
gateway in the corresponding distribution room, saving the extra
work of arranging the collection gateway.
• The 1# and 2# power distribution rooms are located at two corners of the factory and are
far away from the monitoring center. According to the conventional energy management
system, network cables are, respectively, laid out from the gateways of the two power
distribution rooms, connected to the monitoring center, and monitored. The center is
equipped with a server to process all the data. This project adopts an intelligent power
distribution monitoring system and supports multisite cloud access. When there is no
network, the two power distribution rooms are directly connected to the cloud through
GPRS signals, eliminating the need for laying network cables, and because the cloud
platform is used, there is no need for local network. Equipped with a high-performance
server, you only need an ordinary computer to connect to the Internet through the
network port of the monitoring room. The platform system collects energy consumption
data of home appliances through the energy efficiency management socket in the user’s
home, provides a variety of power value-added services and recommends appropriate
third-party value-added services to users. The construction of the intelligent power
distribution monitoring system also provides the plant with a wealth of energy efficiency
value. After analyzing the energy consumption data of the intelligent power distribution
monitoring system, we have proposed the plant from three aspects: power distribution
optimization, electricity bills, and equipment energy efficiency.
• Before the installation of the intelligent energy efficiency monitoring system, the basic electricity
fee of the plant was charged according to the installed capacity. The total installed capacity of the
4 transformers in the plant was 3 260 kVA. According to local regulations, the unit price of the
basic electricity fee charged by capacity was 23 yuan/(kVA × month) and the total monthly basic
electricity bill is 74,980 yuan. According to the analysis of intelligent power distribution
monitoring, the maximum monthly demand of the plant fluctuates between 1 300 and 1 900 kW.
According to the local electricity price, the basic electricity charge based on the demand is 32
yuan/(kVA × month); monthly, the basic electricity fee is 41 600–60 800 yuan, which is less than
the basic electricity fee calculated based on the installed capacity. The power module provides
working power for the whole terminal equipment, the working voltage is AC 110–260 V, and the
output voltage is DC 12 V. In view of the above situation, it is recommended that the plant adopts
an energy storage system to achieve peak shaving and valley filling. On the one hand, the
maximum energy demand can be reduced and the basic electricity bill can be reduced; on the
other hand, the peak-hour electricity load can be shifted to the valley hour to reduce energy
costs. Through calculations, the plant can be equipped with an energy storage system with a
capacity of 1,200 kWh, using a maximum charging and discharging power of 200 kW, and shifting
the load can save 315 thousand yuan in electricity costs per year, as shown in F
MITIGATING CLIMATE CHANGE
 WHAT WE KNOW
The level of greenhouse gases in the atmosphere have
increased, causing the Earth’s temperature to rise.

One greenhouse gas in particular, carbon dioxide (CO2) has

steadily increased over the past century largely due to
human activity (anthropogenic).

We know that emissions have a significant impact on the

world around us. How can we reduce the amount of
carbon that is emitted?
 What is mitigation?
• To decrease force or intensity. To lower risk.

• Earthquake mitigation
• Flood mitigation
• Climate change mitigation
How can we reduce carbon emissions?
• Work in pairs to talk about ways in which we
could reduce (mitigate) carbon emissions in
the following areas. Feel free to write your
answers in the appropriate column on the
board:
– Transportation
– Heating and Cooling Buildings
– Industry Carbon Output
– Electricity Use
 Mitigation Strategy #1:
Transportation Efficiency

A car that gets 30 mpg releases 1 ton of carbon into the air
for every 10,000 miles of driving

Fuel efficient cars get more miles per gallon (mpg)

Increasing the fuel efficiency of cars will reduce the amount

of CO2 emitted into the atmosphere
 Mitigation Strategy #2:
Transport Conservation

With more cars on the road, the amount of CO2 emitted

steadily increases.
Reducing the time and number of cars on the road will
reduce emissions.
Increasing the use of public transportation would reduce the
amount of individual driving time.
 Mitigation Strategy #3:
Building Efficiency

Providing electricity, transportation, and heat for buildings

produces high levels of CO2 emission.

Reducing heating and energy use would reduce the amount

of carbon released into the atmosphere.

Insulating buildings, using alternative energy sources, and

solar water heating are ways to reduce emissions.
 Mitigation Strategy #4:
Efficient Electricity Production

25% of the world’s carbon emissions come from the

production of electricity at coal plants.

Since nearly 50% of electricity comes from coal combustion,

improving coal plant efficiency will significantly reduce
carbon emission.

To do this requires alternative ways of using coal to produce

electricity.
Module 5
Indicators
• Indicators can be classified into three broad categories according to what they measure: input
indicators, output indicators and outcome indicators.
• Input indicators: Input indicators measure the amount of resources that are allocated to a policy.
Typical input indicators are the funds spent on a certain policy or the number of people working
on a project. Input indicators therefore provide a measure of the effort that is devoted to
pursuing a policy but they do not give any information whether the resources are efficiently spent
or whether a policy is effective in achieving an objective.
• Output indicators: Output indicators measure quantities produced by a policy in order to achieve
its objectives, but not progress towards the policy objectives. Outputs are therefore means to
achieve a policy objective, but no ends in themselves. Typical output indicators might show the
number of motorway kilometres built, the number of people trained to fulfil a task, or the
percentage of households equipped in smart energy metres. Output indicators do not tell
whether a policy is effective in achieving its desired objective or not.
• Outcome indicators: Outcome indicators monitor the effectiveness of a policy in achieving its
objectives. While outcomes are the underlying motivation behind policies, they can only be
affected through the inputs and outputs. Typical outcome indicators might be the reduction in
commuting time to the place of work, satisfaction with life or the city, or energy savings.
1. How road traffic control in smart city design is addressed in the below picture? Illustrate the
issues, challenges and possible solutions.

2. Identify the major problems associated with the design and development of Smart dustbins in
urban area.
3. Depict the design goals in order to ensure the smart cities to be sustainable in terms of
conserving natural environment infrastructure and optimized energy utilization.
Retrofitting vs. Greenfield: Key Roles in Smart City Decision-Making

When planning for smart cities, two key approaches come into play: retrofitting
existing infrastructure and greenfield development in new areas. Deciding which
approach to prioritize involves careful consideration of various factors, with each
playing a different but crucial role:

Retrofitting

● Definition: Upgrading and integrating smart technologies into existing

urban infrastructure and buildings.
● Role in smart cities:
○ Advantages:
■ More cost-effective than greenfield development.
■ Leverages existing resources and avoids urban sprawl.
■ Easier to gain community buy-in due to less disruption.
■ Promotes sustainability by reusing existing structures.
○
○ Disadvantages:
■ Can be challenging to integrate technology seamlessly due to
older infrastructure.
■ May encounter resistance from residents and businesses due
to disruption.
■ Limited scalability compared to greenfield development.
○
●
Greenfield Development

● Definition: Building new city areas from scratch with integrated smart
technologies and sustainable practices.
● Role in smart cities:
○ Advantages:
■ Offers a blank canvas for implementing cutting-edge
technology and urban design.
■ Allows for complete control over infrastructure and planning.
■ Enables faster and more comprehensive transformation.
 ○
○ Disadvantages:
■ Significantly higher cost compared to retrofitting.
■ Can lead to urban sprawl if not carefully planned.
■ May displace existing communities or require land acquisition.
■ Longer development timeline due to starting from scratch.
○
●
Decision-Making Factors

Several factors influence which approach is preferable:

● Available budget: Retrofitting is generally more budget-friendly, while
greenfield offers more flexibility but requires significant investment.
● Existing infrastructure: The city's current infrastructure condition
determines the feasibility and cost of retrofitting.
● Desired level of change: Greenfield enables more transformative change,
while retrofitting provides incremental improvements.
● Community needs and concerns: Balancing disruption with potential
benefits is crucial for public acceptance.
● Environmental sustainability: Both approaches can be sustainable, but
greenfield offers greater control over eco-friendly design.

Conclusion

Both retrofitting and greenfield development have valuable roles in creating

smart cities. The ideal approach depends on specific circumstances and priorities.
A hybrid approach combining both strategies can also be effective, leveraging the
strengths of each for a balanced and sustainable urban transformation.
Additional considerations:
● Public-private partnerships can help finance and implement smart city
projects.
● Citizen engagement is crucial for successful planning and implementation.
● Data-driven decision-making ensures solutions are targeted and effective.
By carefully considering these factors, cities can make informed decisions to
leverage the best aspects of both retrofitting and greenfield development,
building smarter and more sustainable communities for the future.