ESCL, Hossam Gaber

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Energy Research Center (ERC)

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ESCL Mission Our mission is to conduct innovative research and develop novel solutions

in the area of energy safety and control to support industrial and societal

development. Members in ESCL investigate advanced safety and control

methods and technologies and their applications on energy infrastructures

and nuclear facilities.

This includes:

- Resilient Interconnected High Performance Micro Energy Grids, and Gas-Power Grids and

Technologies

- Advanced Safety System, Improved Shutdown System for NPPs and Energy Infrastructures

- Protection and Control of Micro Energy Grids, with Integrated Renewable Energy Technologies

- Engineering Design, Control, and Protection of Plasma Experimentation for Fusion Energy

Generation and Industrial Applications

- Hybrid Energy and Transportation Infrastructures Planning, with Energy Conservation

Strategies

- Smart Green Buildings, with Energy Conservation Strategies

- Simulation and Experimentation for Energy Process Systems Engineering

- Intelligent Safety and Control, Real Time Fault Diagnosis and Simulation

- Performance Evaluation and Optimization of Energy and Nuclear Facilities, and Integrated

Small Modular Reactors (SMRs)

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Collaborators

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Building energy management Building energy management is based on an engineering design

framework and methodology to conserve, generate and optimally utilize

energy within buildings.

To achieve this objective, an Energy Semantic Network (ESN) and knowledgebase for buildings have been developed. ESN generates all

possible energy scenarios that can be implemented, evaluate them and provide multi-objective (cost, reliability, quality, comfortability and

emission) optimal solutions for energy conservation, generation and utilization to a given building. The knowledgebase encodes available

information of building energy technologies such as insulation materials, energy resources, energy conversion, building types, and

characteristics of thermal energy zones. ESN is formed by semantic interconnection between energy classes for different types of buildings.

The structure of ESN provides heterogeneous presentation of the classes with fixable architecture to modify, add, or delete significant

energy classes. In addition, ESN structure is designed to satisfy a minimal framework to avoid non-realistic burden of computation during

simulations and evaluation. The structure and processing algorithm of ESN were successfully created and tested for medium size house.

The aim of the current and future work is to develop ESN neuro-fuzzy inference mechanism that has the ability to encode both data driven

(machine learning) and knowledge experience of human expertise to share in forming ESN knowledge base. ESN with neuro-fuzzy inference

mechanism would better present uncertainty about weather, load, building structure and building size and provides more realistic energy

scenarios.

Impacts on building energy industry: (1) provide tool to generate

accurate and optimal energy scenarios for buildings, (2) reduce cost

and time (3) requires less experience engineers (4) deploy different

renewable technologies (5) Provides alternative scenarios with map

of level of satisfaction of energy multi-objectives and (6) reduce

risk of failure of selected scenario to meet the expected

performance.

Ener

gy C

on

vert

ers

FurnaceAC/DC

DC/AC

Users and Stockholder Constrains

Building ESN

Inference Mechanism

Parameters of energy

scenarios

Value range of the

parameters

Change step for each

parmeter

Governmental Constrains

Environmental Constrains

Energy Technology

Knowledge Base

Knowledge Engineering

and Encoding

Energy Expertise

Multi-objective Optimization

algorithm

KPI evaluation

Multi-objective Optimal surface

Hou

se c

on

cep

t an

d s

ize

Ener

gy S

our

ces

Load

s

Gas Supply

WT PV

Gas Generato

r

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Regional gas-power grid planning Investment in natural gas-power technologies increases continuously. Using natural gas fuel for power

generation has seen significant growth for many reasons: 1) short construction times and low initial

investment costs which makes it attractive in a deregulated market; and 2) burning natural gas emits

less harmful emissions compared with other fossil fuels such as coal and oil.

Distributed generation (DG) based on gas engines and micro turbines represent a reliable solution generally for countries that have an access

to natural gas. According to Canadian Association of Petroleum Producers, Canada is the world’s fifth-largest producer of natural gas and

has enough natural gas reserves to meet national energy demand for the upcoming 300 years. Therefore, gas-power technologies are drawing

the attention of power system planners, energy policy makers, and researchers to ensure optimum utilization of natural gas for robust energy

supply networks in Ontario, Canada. Canadian government is looking for ways to increase the reliability and sustainability of power grid;

and gas-power technologies may provide a solution.

This project explores the integration of gas and renewable generation technologies to provide a qualified, reliable, and environmentally

friendly power system while satisfying regional energy demands and reducing generation cost. Scenarios are evaluated using four key

performance indicators (KPIs): economic, power quality, reliability, and environmental friendliness. The proposed scenario analysis tool

has three components: 1) Geographic Information System (GIS) for recording transmission and distribution lines and generation sites; 2)

Energy Semantic Network (ESN) knowledgebase to store information; and 3) An algorithm created in MATLAB/Simulink for evaluating

scenarios.

To interact with the scenario analysis tool, a graphical

user interface (GUI) is used where users can define the

desired geographic area, desired generation percentage

via gas technology, and system parameters. In order to

evaluate the effectiveness of the proposed method,

province of Ontario and Toronto regional zone are used

as case studies.

DatabaseSystem data GIS GUI

Simulation/Evaluation/

Optimization Algorithm

User

Physical System

- Region of interest- Desired percentage of power generation by gas and non-gas

- Weightages for KPIs

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Interconnected micro energy grids

(MEGs) MEG can provide reliable, high-quality power and heat to customers at an

economical cost. MEG can operate in a grid-connected mode where energy

resources interact with the main electrical grid, or in an islanded mode where

the MEG feeds local loads without the use of the main electrical grid.

This project presents an economic generation scheduling algorithm for interconnected-MEGs in order to determine the optimal output

powers of DERs and transferred power among MEGs and between each MEG and the main grid. The performance of MEGs is evaluated

from the economical (total operational cost) and environmental (carbon dioxide emission) viewpoints.

New control design techniques will be investigated with the use of advanced devices Flexible AC Transmission Systems (FACTS) to

support AC/DC circuits by enhancing the quality and controllability of microgrids (MGs). The project will propose intelligent control

designs for integrated FACTS with the target MG, and their implementation in Canadian power grids. FACTS-based MG (WF-PV-storage)

will be modeled, and performance will be optimized by simulations for different operating conditions

Energy Semantic Network (ESN) was proposed as a dynamic and adaptive superstructure to model and simulate energy supply and

production chains. ESN provides means to integrate generation (G), storage (S), and loads (L). Furthermore, ESN is used to integrate

electricity (E), gas (G), and thermal (T) grids. ESN is used to interconnect MEGs with transfer lines.

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ESN includes nodes of energy generation: electricity generation (EG), gas generation (GG), and thermal generation (TG); energy storage: electricity storage (ES), gas storage (GS), and thermal storage (TS); and energy loads: electricity loads (EL), gas loads (GL), and thermal loads (TL). The interconnection between MEGs includes: electricity transfer lines (ET), thermal transfer lines (TT), gas transfer lines (GT), water transfer lines (WT), and transportation transfer lines (RT). ESN static structures are synthesized and dynamically tuned with computational intelligence techniques using real time data and simulation.

Advanced Plasma Engineering & Applications Investigate plasma simulation, experimentation, and their applications on fusion energy, waste-to-energy, and industrial applications. The research includes: Plasma Diagnostics, Thomson Scattering Diagnostics, High Current Plasma Beams Experimentation and Simulation, MHD and Monte Carlo Simulation of Intersecting Plasma Beams, Electrode-less Dense Plasma Generator for Industrial Application, Safety and Protection System Design and Evaluation.

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Real time fault diagnosis and safety verification Small and major accidents and near misses are still occurring in nuclear power plants (NPPs). Risk level has increased with the degradation

of NPP equipment and instrumentation. In order to achieve NPP safety, it is important to continuously evaluate risk for all potential hazard

and fault propagation scenarios and map protection layers to fault / failure / hazard propagation scenarios to be able to evaluate and verify

safety level during NPP operation. The main goal of this research is to develop real time safety verification with co-simulation tool to be

integrated with plant operation support systems. Faults are abnormal conditions that occur in plant equipment/process. This can be caused

by various factors including human errors, environmental stresses or material deficiencies. Effective fault diagnosis and safety verification

are important for the operation of nuclear power plants in terms of their safety and cost effectiveness.

ESCL has been developing computer models that use real-time utility data to simulate problems or faults at nuclear power plants. This

model-based approach can be implemented in parallel with a real plant. It is expected to enhance system performance by improving plant

safety. This will also enable operators like OPG and Bruce Power to actually model the fault as well as the problems in critical equipment

and to identify what is the protection barriers and what is the probability of different faults occurring.

Despite past accomplishments, there is a continuous desire and need

to improve industry’s safety performance, particularly after the

Fukushima disaster. New methods and improvements to existing

methods are therefore being investigated by ESCL in the areas of

systems analysis, accident causation, human factors, error reduction,

and measurement of safety performance.

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Current / Recent Projects - Intelligent Green Commercial and Industrial Facilities – Smart Green Buildings (IEEE-SMC)

- MHD and MCNP Modeling and Simulation of Intersecting High Current Plasma Beams (HOPE Innovations Inc.)

- Performance Optimization of CHP Systems with Co-Simulation and Intelligent Control Systems (CEM Engineering,

NSERC)

- Design and Operation Support for Building Energy Conservation (QNRF, Qatar University)

- Regional Gas-Power Grid Modeling, Planning, and Optimization (NSERC, OCE, Hydrogenics, Veridian, MaRS,

Intergraph, IESO)

- Intelligent Safety Systems for Green Energy and Production Facilities (NSERC, Bruce Power, OPG)

- Investigative Simulation and Experimentation of High Current Plasma For Clean Fusion Energy (HOPE Innovation Inc.)

- Development of reactor power transient control module for severe accident scenarios for CANDU nuclear reactors

(Megawatt Solutions Inc., NSERC)

Selected Publications - Hossam A. Gabbar, Daniel Bondarenko, Sayf Elgriw, Anas Abdel Rihem, Evaluation of Potential Designs for High

Performance Fusion Energy Technologies, International Journal of Latest Research in Science and Technology (IJLRST),

volume 4, Issue 3 , 2015.

- Hossam A.Gabbar, Jason Runge, Daniel Bondarenko, Lowell Bower, Devarsh Pandya, Farayi Musharavati, and

Shaligram Pokharel, Performance Evaluation of Gas-Power Strategies for Building Energy Conservation, Energy

Conversion and Management, Volume 93, 15 March 2015, Pages 187-196.

- Hossam A.Gabbar, Emmanuel Boafo, FSN-based co-simulation for fault propagation analysis in nuclear power plants,

Process Safety Progress, AIChE, (DOI: 10.1002/prs.11725), 8-Dec-2014, Online ISSN: 1547-5913.

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- Hossam A.Gabbar, Negar Honarmand, Abdelazeem A. Abdelsalam, Resilient Microgrids for Continuous Production in

Oil & Gas Facilities, Journal of Advances in Robotics and Automation, November 28, 2014, 3:3.

- Hossam A. Gabbar, Daniel Bondarenko, Sayf Elgriw, Functional Modeling for the Analysis of High Density Plasma

Experimentation, International Journal of Latest Research in Science and Technology (IJLRST), volume 3, Issue 5

October 2014.

- Hossam A.Gabbar, Ming Xiaoli, Abdelazeem Abdelsalam, Negar Honarmand, Key Performance Indicator Modeling for

Micro Grid Design and Operation Evaluation, International Journal of Distributed Energy Resources and Smart Grids,

Volume 10, Number 4, October – December 2014, ISSN 1614-7138, pp 219-242.

- Hossam A.Gabbar, Daniel Bondarenko, Sajid Hussain, Farayi Musharavati and Shaligram Pokharel, Building Thermal

Energy Modelling with Loss Minimization, Journal of Simulation Modelling Practice and Theory, 49 (2014) 110–121.

- Book Chapter, Hossam A.Gabbar, Adel Sharaf, Ahmed S. Eldessouky, Ahmed Othman, Abdelazeem A.Abdelsalam,

Intelligent Control Systems with Applications on Power Systems, New Approaches in Intelligent Control and Image

Analysis: Techniques, Methodologies and Applications, Book series “Intelligent Systems Reference Library”,

http://www.springer.com/series/8578, Publisher: SPRINGER-VERLAG

- Hossam A. Gabbar, Daniel Bondarenko, Sayf Elgriw, Functional Modeling for the Analysis of High Density Plasma

Experimentation, International Journal of Latest Research in Science and Technology (IJLRST), volume 3, Issue 5

October 2014.

- Achint Rastogi, Hossam A.Gabbar, Fuzzy Logic-Based Safety Verification Framework for Nuclear Power Plants, Journal

of Risk Analysis, 1539-6924, 2012.

- Hossam A.Gabbar, Abdelazeem A. Abdelsalam, Adel Sharaf, PSO-Based Control Optimization of Microgrid with D-

FACTS, International Journal of Power and Energy Conversion (Accepted)

- Hossam A.Gabbar, Manir Isham, Sajid Hussain, Luping Zhang, BBN-Based Reasoning Approach for Safety Verification

Using FSN, Journal of Chemical Engineering of Japan (Accepted)

- Daniel Bondarenko, Hossam A.Gabbar, Safety Design of Plasma Experiment and Generation System (Submitted)

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- Elnara Nasimi, Hossam A.Gabbar, Application of safety instrumented system in older nuclear power plants

(Submitted)

- Aboelsood Zidan, Hossam A.Gabbar, Ahmed Eldessouky, Optimal planning of combined heat and power within

microgrids (Submitted)

- Ahmed S. Eldessouky, Hossam A.Gabbar, Improved Power Grid Stability by applying PID Fuzzy Model Reference

Learning Controller to SVC, (In Submit).

- Harsh Deol, Hossam A.Gabbar, Self-Tuning Fuzzy Logic PID Controller, Applications in Nuclear Power Plants,

International Journal of Intelligent Systems Technologies and Applications (Accepted)

- Sajid Hussain, Hossam A.Gabbar, Farayi Musharavati, Shaligram Pokharel, Comfort-Based Fuzzy Control

Optimization for Energy Conservation in HVAC Systems, Journal of Control Engineering Practice, (2014), pp. 172-

182.

- Abdelazeem A. Abdelsalam, Hossam A. Gabbar, and Adel M. Sharaf, Performance Enhancement of Hybrid AC/DC

Microgrid based D-FACTS, International Journal of Electrical Power and Energy Systems, Volume 63, December

2014, Pages 382-393.

- Razibul Islam, Hossam A.Gabbar, Study of Small Modular Reactors in Modern Microgrids, International Transactions

on Electrical Energy Systems, DOI: 10.1002/etep.1945.

- Abdelazeem Abdelsalam, Hossam A.Gabbar, Farayi Musharavati, Shaligram Pokharel, Dynamic Aggregated Building

Electricity Load Modeling and Simulation, Journal of Modeling and Simulation Theory and Practice, Volume 42,

March 2014, Pages 19–31.