Associate Professor Dr Thair Mahmoud is an experienced power systems and control specialist, with experience spans across a wide range of disciplines in power systems engineering: academic research, planning and studies, operation optimisation, consulting, construction and manufacturing. From working in a number of industry positions, the skills are focused on optimum operation and expansion planning of power systems at transmission, distribution & generation levels. This includes a wide range of analysis and engineering solutions such as network augmentation, generator-connection, daily generation dispatch planning, extensive energy economics modelling e.g. electricity market and load forecasting modelling.

Having worked at different engineering and acedmic research positions in Edith Cowan University (ECU), Western Power, Australian Energy Market Operator (AEMO) in Western Australia, University of Tasmania in Tasmania and WSP - Parson Brinkerhoff and Vestas Wind Technology in Melbourne Victoria, the technical experience gained are in the following areas:

Academia 

• Electricity Markets Modelling: Modelling Wholesale Electricity Market (Agent-based) - evaluation of the role of Battery Energy Storage System (BESS) in the provision of Ancillary Services (AS)
• Optimising size of Battery Energy Storage on Distribution and Transmission networks
• Adaptive short term load forecasting modelling using ANN and ANFIS 
• Applying intelligence to improve accuracy and speed of optimisation technicques (metaheuristic and linear) 
• Providing supervision to PhD and MSc/MEng students and help connecting students with jobs market. 
   

Industry

Generator network connection (Wind, Solar, Battery and Hybrid Parks)
With total number of more than 2 GW of projects in solar & wind farms and Hybrid Energy Parks, experience in:

• Managing generator network connection process under various grid-codes and network strength levels
• Conducting power system studies for generator connection and negotiating generator performance standards

Real-Time Operation Control (Generation and Transmission)
Having worked in dispatch control centre under electricity market environment, this experience incorporated:

• Scheduling power stations (commitment/de-commitment), portfolio optimisation, economic/security-based constraint dispatch (curtailment) and fuel cost minimisation
• Monitoring daily Wind and Solar farms generation profile and planning Frequency Control Ancillary Services (FCAS) accordingly

Network Planning (Transmission, Distribution and Microgrids)
Working under utilities, regulations and corporate business government environment, this experience included:

• Power system analysis, including network modelling and simulation automation using scripts in PowerFactory DSL/DPL, PSS®E, PSS®SINCAL, PSCAD™/EMTDC™, Python, Matlab Simulink, Java and C/C++
• Applying control theory and control modelling skills to test voltage recovery, rotor angle stability, frequency response and inertia monitoring
   

Technical Software Experience

Power Systems Analysis (PSS®E, PSS®SINCAL, PSCAD™/EMTDC™, DIgSILENT-PowerFactory, and Matlab Simulink/SimPowerSystem):

•    Stability analysis and transient studies (simulation events, network variations and operation scenarios)
•    System Modelling Initialisation and State Equations representation
•    Inverter, electronics, STATCOMs, Exciters and Governors modelling and tunning
•    Complex load modelling and system identification

Wholesale Electricity Market simulation and security-based constrained dispatch optimisation:

• Java, Python, Matlab and C/C++, Agent-based modelling, electronic negotiation, linear-programming based dispatch constrains and fuel management

Artificial Intelligence:

• Knowledge based systems modelling using Matlab Fuzzy Logic toolbox
• Machine learning systems development and trends modelling such as Load Forecasting and System Identifications using R and Matlab Artificial Neural Networks (ANN) and Neuro Fuzzy Inference System (ANFIS) toolbox
• Linear and stochastic programming-based optimisation problems solving using linear solvers and heuristic methods (Genetic Algorithm, Particle Swarm Optimization, Ant Colony and Grey Wold optimization)
• Distributed control and smart-grid autonomous software agent behaviour modelling using Multi-Agent System technology