Research ProposalPDF Available

Title of Research Proposal Towards Green World: Renewable Energy Source based Energy Management in Residential Sector making Appliances, Homes and Buildings Smart

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Signature of Student: Summary of the Research This synopsis describes that residential energy management systems which are leveraged by the penetration of the renewable energy sources (RESs) such as: photovoltaic (PV) systems and wind turbines. These are the major sources used in residential energy and the concurrent penetration of these resources will considerably change the residential energy management systems' (EMS) functionality. This research focuses on smart homes and buildings which are equipped with automation technologies to enhance occupants' comfort level and provides savings on the electricity bills. The occupants' activities can be controlled or monitored by the EMS in order to schedule the appliances daily energy consumption patterns. Another significant aspect of this research is integration of the smart homes into smart grid architecture. It can support the traditional power grid by integrating smart grid's energy management programs (i.e., demand side management programs). In addition, energy management in the residential sector is challenged by many factors. The major challenge is that energy consumption is continuously growing despite of the enforcement of the various energy efficiency policies. Some important factors of the energy growth are: increasing the usage and number of appliances, improper schedules and control of the appliances and more comfort demand. For improving these challenges, EMSs are used to manage and reduce residential energy usage and cost by incorporating different energy management programs, such as: energy conservation and energy efficiency. EMSs utilize RESs for residential energy generation to fulfill users' requirements and to support reliability and robustness of energy supply systems. For effectively managing the residential users' energy, home energy management systems (HEMS) and buildings energy management systems (BEMS) are the focus of this research and they are comprised of the following applications which are based on controlling the daily usage of appliances and seasonally usage of appliances: 1) monitoring and scheduling the flexible loads for accommodating daily activities, user preferences and requirements of residential consumers, 2) reduction of peak load demand through optimal control of flexible residential loads, storages and generation systems, 3) cost effectiveness with market oriented strategy of implementing EMSs by effectively managing energy use in response of fluctuating energy prices. Furthermore, we also consider the prevention measures for rebound effects by informing consumers to utilize more energy after the implementation of RESs. In addition, some major barriers to the large scale (multiple homes and residential buildings) implementations are also considered as: peak formation, cost maximization and user comfort sacrifices by analyzing complexity of the proposed solutions. For solving the aforementioned issues, this research considers the meta-heuristic algorithms (genetic wind driven algorithm (GWD)) for the efficient HEMS in the residential units (single and multiple homes) at first stage. Since meta-heuristic algorithms are well suited for solving the stochastic nature of problems as randomness in energy consumption patterns and users' schedules. Using these algorithms; we are simulating two scenarios for the above mentioned applications: 1) energy cost and user comfort without RESs for single, multiple homes and buildings, 2) energy cost and user comfort with RESs for single, multiple homes and buildings. We will also consider the HEMS and BEMS using fuzzy logic in our subsequent work for the aforementioned scenarios while considering the seasonally used appliances (i.e., by providing heating and air conditioning system control). Furthermore, the comparative analysis of these techniques will also be conducted.
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COMSATS Institute of Information Technology,
Islamabad Campus
Synopsis For the degree of  M.S/M.Phil. Ph.D.
PART-1
Name of Student
Sakeena Javaid
Department
Department of Computer Science
Registration No.
SP16-PCS-007
Date of Thesis
Registration
Spring 2017
Name of Research
(i) Supervisor
(ii) Co-Supervisor
(i) Dr. Nadeem Javaid
(ii) Dr. Mariam Akbar
Research Area
Energy Management in Smart Grid
Members of Supervisory Committee
1.
Dr. Nadeem Javaid
2.
Dr. Mariam Akbar
3.
Dr. Manzoor Illahi Tamimi
Title of Research Proposal
Towards Green World: Renewable Energy Source based Energy
Management in Residential Sector making Appliances, Homes
and Buildings Smart
Signature of Student:
Summary of the Research
This synopsis describes that residential energy management systems which are leveraged
by the penetration of the renewable energy sources (RESs) such as: photovoltaic (PV)
systems and wind turbines. These are the major sources used in residential energy and the
concurrent penetration of these resources will considerably change the residential energy
management systems’ (EMS) functionality. This research focuses on smart homes and
buildings which are equipped with automation technologies to enhance occupants’
comfort level and provides savings on the electricity bills. The occupants’ activities can
be controlled or monitored by the EMS in order to schedule the appliances daily energy
consumption patterns. Another significant aspect of this research is integration of the
smart homes into smart grid architecture. It can support the traditional power grid by
integrating smart grid’s energy management programs (i.e., demand side management
programs).
In addition, energy management in the residential sector is challenged by many factors.
The major challenge is that energy consumption is continuously growing despite of the
enforcement of the various energy efficiency policies. Some important factors of the
energy growth are: increasing the usage and number of appliances, improper schedules
and control of the appliances and more comfort demand. For improving these challenges,
EMSs are used to manage and reduce residential energy usage and cost by incorporating
different energy management programs, such as: energy conservation and energy
efficiency. EMSs utilize RESs for residential energy generation to fulfill users’
requirements and to support reliability and robustness of energy supply systems. For
effectively managing the residential users’ energy, home energy management systems
(HEMS) and buildings energy management systems (BEMS) are the focus of this
research and they are comprised of the following applications which are based on
controlling the daily usage of appliances and seasonally usage of appliances: 1)
monitoring and scheduling the flexible loads for accommodating daily activities, user
preferences and requirements of residential consumers, 2) reduction of peak load demand
through optimal control of flexible residential loads, storages and generation systems, 3)
cost effectiveness with market oriented strategy of implementing EMSs by effectively
managing energy use in response of fluctuating energy prices. Furthermore, we also
consider the prevention measures for rebound effects by informing consumers to utilize
more energy after the implementation of RESs. In addition, some major barriers to the
large scale (multiple homes and residential buildings) implementations are also
considered as: peak formation, cost maximization and user comfort sacrifices by
analyzing complexity of the proposed solutions.
For solving the aforementioned issues, this research considers the meta-heuristic
algorithms (genetic wind driven algorithm (GWD)) for the efficient HEMS in the
residential units (single and multiple homes) at first stage. Since meta-heuristic
algorithms are well suited for solving the stochastic nature of problems as randomness in
energy consumption patterns and users’ schedules. Using these algorithms; we are
simulating two scenarios for the above mentioned applications: 1) energy cost and user
comfort without RESs for single, multiple homes and buildings, 2) energy cost and user
comfort with RESs for single, multiple homes and buildings. We will also consider the
HEMS and BEMS using fuzzy logic in our subsequent work for the aforementioned
scenarios while considering the seasonally used appliances (i.e., by providing heating and
air conditioning system control). Furthermore, the comparative analysis of these
techniques will also be conducted.
PART II
Recommendation by the Research Supervisor
Name: Dr. Nadeem Javaid Signature_____________________ Date________
Recommendation by the Research Co-Supervisor
Name: Dr. Mariam Akbar Signature_____________________ Date________
Signed by Supervisory Committee
S.#
Name of Committee member
Designation
Signature & Date
1.
Dr. Nadeem Javaid
Associate Professor
2.
Dr. Mariam Akbar
Assistant Professor
3.
Dr. Manzoor Ilahi Tamimi
Associate Professor
Approved by Departmental Advisory Committee
Certified that the synopsis has been seen by members of DAC and considered it suitable
for putting up to BASAR.
Secretary
Departmental Advisory Committee
Name:__________________________________ Signature:_____________________
Date: _________________
Chairman/HoD ____________________________
Signature: _____________________________
Date: _____________________________
PART III
Dean, Faculty of Information Sciences & Technology
_________________Approved for placement before BASAR.
_________________Not Approved on the basis of following reasons
Signature ____________________________ Date__________________
Secretary BASAR
_________________Approved from BASAR.
_________________Not Approved on the basis of the following reasons
Signature ____________________________ Date__________________
Dean, Faculty of Information Sciences & Technology
________________________________________________________________________
________________________________________________________________________
Signature:_______________________________ Date__________________
Please provide the list of courses studied
1. Special Topics in Artificial Intelligence
2. Special Topics in Wireless Technologies
3. Performance Evaluation of Networks
4. Advanced Topics in Multimedia Technologies
5. Advanced Topics in Machine Learning
6. Special Topics in Computer Networks
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