Research themes

AI-Based Applications for Renewable Energy and Storage Systems

The integration of renewable energy resources (RES) and energy storage systems (ESS) reduces the dependence on conventional power generation which is largely responsible for carbon emissions and climate change. In addition, the entire power system is usually made observable by installing phasor measurement units (PMUs) and SCADA systems at specific buses. As a result, power system operators can access various measurements such as voltage and current phasors which provide useful information that can be used for monitoring, protection and control. Furthermore, different measurement devices are augmented into the renewable power plants and ESSs. Consequently, collected measurements are fed to the control center to enable power system operators take fast and accurate corrective actions when contingencies are experienced. Meanwhile, the recent developments of artificial intelligence (AI) techniques can be employed to provide better understanding of the inherent dynamic and operational characteristics of a renewable based power system through the large data collected from different locations.

Therefore, the applications of Machine learning and deep learning models such as support vector machine (SVM), Decision trees, recurrent neural networks (RNN), long short-term memory (LSTM), convolutional neural network (CNN), artificial neural network (ANN), and Autoencoders to power systems are tremendously increasing. These techniques have the ability to capture the inherent static and dynamic states of an electrical network when a fault or loss of equipment are experienced as well as the operation performance of RES power plants and ESSs. In addition, the extraction of spatial and temporal distributions of features within the network facilitates taking fast, accurate and informed decisions in the form of classifications and regression analyses. For example, a set of data collected from a power network can be used to train different deep learning models to characterize the required support for the power grid. The developed models can predict the full states of the system from few tens or hundreds of similar datasets without having to build the grid from the scratch as done in time domain simulations. Additionally, transfer learning techniques can be used to solve the problem of insufficient data and changes in operating conditions especially with high penetration levels of the stochastic renewable power generation. In this context, this theme will focus and not limited to the following applications in well-designed projects for high RES penetration and ESS toward 100% renewable based power system:

  • Power Frequency Stability Assessment and Control for RES/ESS based power systems: The intermittent nature of renewable power generation causes frequent changes in operating points due to their reliance on weather conditions. In addition, the occurrence of contingencies such as generator, line and load tripping may result in stressed scenarios where different forms of instabilities can be experienced. In this context, frequency stability represents a crucial aspect of power system operation and planning. It refers to the ability of a power system to maintain steady frequency following a severe disturbance that results in imbalance between generation and load. Therefore, preventive control actions should be taken to avoid possible cascading outages and even complete blackout. To achieve this objective, deep learning techniques such as CNNs, RNNs and LSTM can be employed to provide fast and accurate predictions of the frequency dynamics using collected measurements from phasor measurement units (PMUs) across the entire system. Therefore, the training of these models will be carried out using a dataset that is either collected from real-time measurements or generated through extensive time domain simulations for wide range of operation conditions and penetration levels of renewable energy resources (RES). The predicted power frequency dynamics may be utilized to identify the required load shedding amount and suboptimal operation point of RES to maintain the maximum frequency deviation value within the acceptable operating limits.
  • Voltage Stability Assessment, Control and Enhancement for 100% Renewable/ESS based Power Systems: Voltage stability refers to the ability of a power system to maintain steady voltages at all buses after being subjected to a disturbance from a given initial operating condition. Voltage instability can be experienced in the form of a cascaded fall or rise of voltage at specific buses. In addition, voltage instability may result in loss of load(s) in an area, or tripping of transmission lines that may be followed by cascading outages or voltage collapse. This phenomenon can be avoided through real-time monitoring of wide-area measurements that provide useful information about system voltage magnitudes and angles. In this context, deep learning models based on CNNs or LSTM can be trained to provide fast predictions of the voltage stability and inform power system operators about the consequences of severe disturbances if proper control actions are not taken. If properly trained and tuned, these models have the ability to predict how the system will respond to specific contingencies based on the learned dynamics. Therefore, deep learning techniques can provide a more thorough overview and understanding of various interactions at the components and system levels. In the literature, different deep learning techniques are applied to address short-term voltage stability (extracting short-term feature from scarce instability data) assessment; long-term voltage stability assessment, TSSC-based SVS margin estimation and cost-sensitive corrective controls, class imbalance between stable and unstable data.

For the aforementioned applications, the efficacy of Machine learning / deep learning (ML/DL) models lies in the efficient data preparation. Since models are built as networks of graphs with high shareable features that are akin to high dimensional complex interconnections of power grid, they can learn the nonlinearity phenomena of power systems from well prepared data beyond mathematical representation.


  • Integration of Renewable Energy and Energy Storage Systems

 The deployment of small and large scale integration of Renewable Energy Systems (RES) is rapidly increasing worldwide. In this theme, the research team will focus on the integration of RES and energy storage systems (ESS), virtual power plant and 100% renewable based power systems. These trends are expected to continue in the foreseeable future augmented with AI applications. The associated challenges with renewable energy integration cover wide range of different disciplines which are related to aerodynamics, forecasting (e.g solar, wind, and dust), data analytics, mapping of potential locations, RESs technology development, power plant design, power plant controllers (centralized and decentralized), energy storage systems (ESS) augmentation, coordination with demand response, grid interface schemes and integration studies. Environmental concerns have brought global pressures to replace conventional generation with RE power plants (e.g. PV, Wind, CSP) and distributed generation in both transmission and distribution networks. Therefore, the key question raised by all power utilities, manufactures and market operators is “Can RE sources behave like conventional power plant?” The ultimate goal in some countries is to achieve 100% renewable energy sources operating in conjunction with several means of energy storage systems (e.g electrical, mechanical, thermal and hydro) to address the vulnerabilities posed to the electric grid. As a result, the main objective of this theme is to envision different methods for seamless and coordinated integration of sustainable energy systems (PV, Wind, CSP, ESS) along with the traditional power plants while ensuring economical and secure operation.


The rapid growth of energy consumption and increased penetration of RES have mandated the development of several strategies that enhance the economical and dispatch reliability of these intermittent resources. The current practice for utilizing the installed RES in electricity markets is just to reduce fossil-fuel consumption. However, the stochastic and non-dispatchable nature of renewable power generation imposes several constraints concerning the entire integrity of a power system and thus requires utilities to maintain power balancing reserves to match supply and demand power levels. Maintaining these reserves for the uncertain renewable power generation represents an additional cost for the utility, referred to as the short-term balancing cost, which is mainly the cost of flexibility. Therefore, the power system flexibility represents a critical issue for concurrent power grids with the witnessed increased penetration levels of renewable power generation worldwide. Therefore, the novelty and contributions of this theme of APEC will be realized through the implementation of the following research projects:


Project T1-P1: PV Power Plant Design and Control with Dispatching Capability

This project aims to develop a standard design for large-scale photovoltaic (PV) power plant at transmission level interconnection with dispatching capability. The PV plant architecture including hybrid AC/DC grid, advanced AC/DC protection schemes, centralized and decentralized controllers and communication infrastructure will be developed. An advanced SCADA power plant controller will be structured modularly to integrate Hybrid Energy Storage Systems (HESS) and other types of renewable power generation for future expansion. The PV Power plant controllers aim to smooth output power generation, ensure dispatching capability and achieve efficient ancillary services to comply with grid code requirement. The project introduces a novel Renewable Energy Management System (REMS) to facilitate increased penetration of PV Power Plant. The REMS will determine the dispatch of energy and ancillary services for a PV Power Plant and HESS to mitigate the associated variability and intermittency of PV power generation. The PV Power Plant augmented with renewable energy management system (REMS) tool will have promising potential for cost reduction by lowering the required primary and secondary spinning reserve for transmission system operation along with achieving efficient ancillary services for grid support.


Project 2: A Masterplan for Sharing, Hybridizing, Coordinating, and Aggregating Energy Storage System Facilities for Electric Power and Electrified Transportation Systems

The energy storage systems (ESS) are crucial components in electric power and electrified transportation systems due to the strict requirement on power balance between generation and load demand. The ESS add valuable flexibility to the power grid and transportation by mitigating the mismatch of generation and load demand. Specially, with recent trends on renewable distributed generation sources (DGS) and electric vehicles (EVs), distributed ESS are becoming more popular in several applications such as DGS based microgrids and EVs. However, several ESS technologies differ in their nominal capacities, discharge/response time, lifetime, and participation scales in ancillary services. Therefore, the proper coordination and aggregation between various technologies/facilities of ESS are required to ensure efficient ancillary services and cost-effective investments. In addition, the ESSs will be utilized for several applications such as smoothing RES power generation, load shifting, energy arbitrage, scheduled power generation of hybrid renewable power plant (HRPP), blackout restoration, and efficient ancillary services. Therefore, we propose different strategies on sharing, hybridizing, coordinating, and aggregating among different ESS facilities and technologies for multitasking multi-scale applications in the context of deregulated distributed power energy and electrified transportation systems. We aim to investigate the proposed strategies on different types and scales of ESS considering its functionalities on distribution and transmission level of power systems, especially the interlinks between electric power and electrified transportation systems.


Project 3: Development of Virtual Power Plant: Design, Operation and Control

The power and energy sectors are going through a major transformation, as energy sustainability, efficiency, reliability, and environmental concerns are becoming significant concerns in the twenty-first century. The old power system is being re-structured and re-architected, creating a paradigm shift in electricity generation, transmission, and distribution systems, collectively termed the Smart Grid. To realize the efficacy of the Smart Grid, the present distributed generations including or excluding renewables should also function smartly. Here, the Virtual Power Plant (VPP) appears into the picture revealing enormous opportunity to make the upcoming energy transformation smoother without compromising grid stability and reliability along with offering many other techno-economic benefits.  The purpose of this project is to develop a next-generation energy-management mechanism enabling Peer-to-peer (P2P) energy trading approach for VPP that allows each prosumer (consumes and produces electricity) to trade energy with other prosumers and the grid.


Project 4: Center of technologies for the design and operation of 100% Renewable Power Systems

In this project, the research team will develop optimal design and control strategies for hybrid AC/DC power grid toward achieving 100% Renewable Power Systems. This includes the integration of PV and Wind power generation, various types of ESSs with optimized capacity, Demand Response and other flexibility elements in hybrid AC/DC power grid.  Several aspects of power system stabilities and flexibility along with advanced control strategies will be investigated to improve the dynamic performance and to guarantee continuous power supply.


It is generally recognized that power electronic systems play a crucial role in modern power systems, transportation, consumer electronics and industrial drive and control systems. Applications of power electronics span switched mode power supplies, battery chargers, all modern consumer electronics, renewable energy system integration, industrial drive (VFD/ASD), active power filtering, FATCS devices, electric vehicles, more electric aircraft, ship propulsion systems, navigation system, monitoring and protection system, HVDC transmission, electrical locomotives, to satellites. New generation power semiconductor devices, such as silicon carbide (SiC) and gallium nitride (GaN), are proving to be effective in providing further enhancements of the overall power electronic system’s efficiency, reliability, scalability and compactness.  This theme acts as a backbone for the entire center, conducting advanced research in the area of power electronics including converter/inverter topologies, modularity and control that supports other projects within the center at large. One of the key roles of this theme is to work closely with newly added themes on Electrified Transportation and AI to provide advanced power electronics converters for holistic solutions as well as the widespread utilization of newly develop technologies. In this theme, we are developing modern power electronics-based solutions for different application with emphasis on fast charges for EVs, electric power system for CubeSats and Drones. Following are the key research areas that are covered under this theme:


  • Multiport Converters for Small and Medium Power Applications

The use of battery integrated PV systems is now widespread and in isolated systems there could be additional sources (such as Fuel Cells). In case of EV, type-2 charges allow both AC and DC charging. Furthermore, many countries are making a steady transition towards deployment/inclusion of DC sub power system as most of the generation and storage, such as, PV, batteries, Fuel cells, and most modern loads are DC in nature. Often, many power electronics converters are used to interface them together and with the AC supply system. This increases the system complexity and footprint and reduces the system efficiency and reliability. Thus, there is a need to develop technologies and solutions that would tackle the aforementioned issues. Multiport power electronics converters along with hybrid inverters that will allow connection of different sources and loads within the same architecture would transform the role of power electronics in many applications. In multiport converters, several ports are provided to connect different resources (such as, PV, battery storage, EV and fuel cells) as well as different loads. This helps to reduce the number of conversion stage and offers the flexibility to control the entire topology as unified system. Challenges involved are: offering higher number of ports with less number of circuit components (ex: switches, diodes, L and C), high voltage conversion gains, complex control and power management, redundancy, reliability and so forth. Under this research topic, we will be developing innovative multiport converter topologies for the key areas listed below:

  • Electric power subsystem (EPS) for CubeSats
  • Electric propulsion systems for Drones
  • Development of new multiport converter topologies for DC microgrids
  • New PWM algorithms and control techniques for multiport converters
  • Effective power management as well as load sharing among different sources in CubeSats, drones and DC microgrid applications


  • High Power Density Converters for Medium to High-Power Applications

The power handled by the converters/inverters in the modern industrial applications as well as end user equipment is increasing significantly. For example, in case of PV system, the inverter that interfaces the PV generated DC power to the AC grid varies from few kW to 1MW capacities. In case of wind power generation, recent wind turbines are capable of producing 13-14MW power from a single turbine. Similarly, the capacity of power transfer through HVDC systems is increasing. In case of EVs, the charging time is restricted mainly due to the size (footprint) and weight of on-board power electronics. EVs when charged through single-phase AC supply take somewhere 8-12 hours to fully charge their batteries. With three-phase AC supply, the charging time reduces to 3 to 6 hours. And to further reduce the charging time, DC fast/ultra-fast charges are used that can charge the EV batteries from 15 minutes to around 1hour. Usually, AC charging is done through on-board converters while DC charging is done through off-board converters (power transfer through them is significantly high thus they require larger footprint). Nevertheless, all these applications necessitate the development of compact high power density converters/inverters topologies, modular architectures and multifunctionalities. Apart from the topological architecture development, the control techniques (advanced PWM, soft switching, etc) play an important role in achieving efficient operation and better utilization of converter switches and thus, further enhancing the operational performance. The research work would utilize of SiC and GaN semiconductor devices for the prototype development as these devices offer smaller footprint and are more efficient. Under this research topic, innovative high power density converter topologies as well as new control concepts will be developed for different applications with the focus on the following:

  • Multilevel converter topologies for high-power PV and wind system
  • Modular converter configuration for HVDC system
  • Converters for fast AC and DC charging of EVs
  • Current fed converters for fuel cell powered systems
  • New control techniques and innovative concepts for overall system operation and control
  • Reality and fault tolerant enhancement


  • Power Electronics and its Control for Power Distribution System Applications

The widespread use of power electronic based systems has put the burden on power system by generating harmonics in voltages and currents along with increased reactive current. Furthermore, the penetration level of small/large-scale distributed generation (DG) systems, based on wind energy and PV, installed at distribution as well as transmission levels has been increased significantly. This integration of renewable energy sources is further imposing new challenges in terms of impact on system voltage and voltage distortion as well interact with the operation of capacitors, voltage regulators and protection coordination. Apart from this, another important aspect in power electronics systems is the synchronization of inverters with the utility grid. It is a common practice to use phase-locked loop (PLL) or frequency-locked loop (FLL) techniques to estimate the frequency and ensure the synchronization of the reference currents with the main supply voltages. However, PLL introduces instability issues and reduces the controller robustness. This research topic covers several power electronics based solutions to enhance the power quality, reliability, power flow management and efficiency of power system.

  • Development of solid-state transformer (SST) topologies
  • Matrix converters for direct AC to AC conversion
  • Dual active bridge (DAB) and dual half bridge (DHB) converter topologies
  • Converters for battery energy storage system
  • Reduced switch count converter topologies
  • Advanced synchronizing techniques through novel PLLs and FLLs
  • Advanced and intelligent control techniques for active power filters (APFs), including shunt APF, series APF, UPQC, DVR, STATCOM and hybrid APF
  • EV as ancillary service provider
  • Power quality enhancement in micro-grids


Project 1: Next Generation Multiport Converters for Integrating Multiple Energy Resources

Most of the energy sources discussed previously require power electronic converters for optimal energy conversion and to meet load requirements. In conventional architectures, each energy source is integrated with dedicated dc-dc converters, and the extracted energy is fed to the loads via a common-dc bus. This configuration provides flexibility for integration of multiple energy sources and control simplicity but has the following drawbacks: lower efficiency due to multiple conversion stages, larger footprints, and higher cost due to higher number of components. In some applications like all electric airplanes, CubeSats and drones, the power density and footprint become critical aspects.  Thus, there is ever-growing a need to develop new converter topologies and architectures which can integrate multiple energy resources, with reduced power electronic components, as a multi-input system. Additionally, these topologies should provide flexibility to connect multiple loads such that the entire system can be controlled as a centralized multi-input multi-output system. In this paradigm, multiport converters can play a crucial role to integrate multiple energy sources, multiple loads, and energy storage. One of the main challenges in developing new multiport converter topologies is the trade-off between different objectives as each energy resource has different characteristics and operational requirements. This however offers new challenges as well as opportunities for innovation in terms of circuit topologies and architectures.


Project 2: High Power Density Advanced Converter Topologies and Controllers for Fuel Cell Vehicles

The research and development activities in FCV industry have increased multifold in the recent years. As highlighted in the previous section, developing compact and efficient high step-up dc-dc converter for fuel-cell stack is one of the important research challenges in addition to optimal energy management strategies for hybrid energy sources. When it comes to energy system of FCVs, there are several verticals in which considerable developments are happening with tremendous opportunities to develop new solutions, concepts and architectures. They can be categorized as: high step-up dc-dc converters, multiport converters for interfacing hybrid energy sources, converters with enhanced power quality, hybrid energy storage system, vehicle to vehicle charging, and so forth. The overall philosophy of this project is, to address the challenges in the above verticals, finding new converter topologies with multi functionality, high efficiency, higher power density and lesser device count; and developing advanced control schemes to achieve enhanced operation with low losses for the existing and new converter configurations. Particularly, high power density converters with SiC and GaN devices with lesser device count need to be designed for efficient solution. Further the problem of energy management between multiple energy sources (battery, fuel cell and ultra-capacitor) and designing a converter configuration/new multifunctional converter topology to accept and control power from multiple energy sources during steady state driving/charging mode or transient drive mode loads require further investigation. Another dimension is to innovate different mechanisms, and converter topologies to charge the EV from FCV and vice versa.


Traditionally, transmission and distribution infrastructure and operation practices have been designed to cope with specific types of generation and loads. On one hand, transmission systems, equipped with all-dispatchable resources strives to maintain its dispatching ability, adequate spinning reserve, optimal restoration plans and enhanced system stability. On the other hand, distribution systems, whether radial or meshed, equipped with one interconnected source of energy (distribution substation) is not merely meeting electricity demand, but also ensuring system adequacy and strive to provide ancillary services, to ensure that the power is delivered at the required quality. Recently, with the smart grid evolution, the system has witnessed lots of changes that resulted in a paradigm shift in how the transmission and distribution systems are operated and controlled. An increasing reliance on communication technology to control the operation of the system is evident. A step that, although helped in developing more accurate and precise control, introduced more challenges related to possible delays and cyber-physical security threats. Increasing the share of renewable energy (RE) resources in the energy supply portfolio is envisioned and anticipated to reach up to 50% of total generation capacity. A change that, although addresses lots of environmental concerns and increases the energy security by diversifying energy supply, it increases the intermittent and stochastic nature of the power supply. To top up the challenges, there is an accelerated change in both generation and load types by migrating from ac to dc nature in order to cope with the new advancements in generation/load technologies. Generation such as wind, PV, and fuel cells along with loads such as EV, home appliances, computers and LED are proliferating the system. All those changes mandate that the existing power grid infrastructure, operational practices, management plans and protection schemes must undergo radical developments to accommodate these new advancements leading to an economic, clean, efficient, resilient, and responsive smart grid.


  • Microgrids as a Smart Grid Building Block:

Microgrids are envisioned to be the building blocks of smart grids due to the numerous advantages that they bring to the system including improving system efficiency, reliability and providing enabling technologies for grid-independence to end-user sites. Conventionally, microgrid, whether grid-connected or autonomous, is configured from a group of interconnected loads and distributed-energy resources within clearly defined electrical boundaries that acts as a single controllable entity with respect to the grid. Such microgrids, when properly controlled, can help in increasing the system reliability and maintaining adequate supply to customers. However, under contingencies and severe dynamics these microgrids can fail and collapse due to mismatch in active/reactive power or being destabilized. Dynamic microgrids with flexible and movable boundaries can change their borders continuously in response to any system change (occurred or anticipated), hence, providing an attractive solution to enhance system operation, efficiency, stability and reduce overall operational costs. 

Consequently, groups of interconnected microgrids can be dynamically restructured (to be connected or disconnected) to achieve a specific operational objective. This track, will investigate advanced dynamic protection coordination for multiple interconnected microgrids with flexible boundaries and mix of dispatchable and intermittent resources as well as electrical storage units and capacitor stations. As those microgrids will potentially reconfigure often, a seamless reconfiguration methodology that minimizes switching transients will be developed along with optimized switching sequence in order to minimize the system power loss during the reconfiguration process. In addition, this track will focus on developing novel centralized and distributed control strategies to ensure seamless operation during different configurations. Furthermore, this track will introduce a novel concept of mobile microgrid architecture (MMG), where mobile generation and load (MGL) units are introduced to help improve system stability and adequacy under normal and contingency situation. MGLs are mobile units equipped with small-scale generation units (microturbines or fuel cells) and/or electrical storage units (batteries). MGLs could be connected to microgrids to inject or absorb power from point of common coupling with the microgrid. Yet MGLs can move from one microgrid to another for efficient operation. Different mobile unit’s structures could be considered including; mobile electric generation (MEG), mobile electric storage (MES) and hybrid mobile electric generation storage (MEGS) units. Optimized dynamic sizing and allocation algorithms will be developed for MGLs to maximize systems operational benefits including but not limited to; minimize system losses, maximize system reliability, and systems upgrade deferral. Further, the utilization of microgrids along with MGL units, as a backbone to improve system restoration and black start capabilities, considering generation intermittency, will be designed. Advanced coordinated control strategies will be also being developed for MGLs to provide system ancillary services.


  • Electric Vehicles Charging Infrastructure and Protocols:

There is an increasing interest in large-scale deployment of electric vehicle (EV) worldwide. By the end of 2020, the global electric car fleet exceeded 10 million. UAE targets for large-scale EV deployment aims to have 20% of their vehicles to be electric by 2030. This will impose drastic changes on how distribution system be efficiently operated and present great challenges for system operators and planners. These challenges include, impact of uncontrolled charging schemes, how to optimally allocate and size charging infrastructure, and how to efficiently manage various charging protocols. Under this track, it is aimed to develop new planning frameworks to optimally size and locate charging stations considering both transportation and power network constraints. Uncertainties in traffic, system demands, and renewable generation will be considered by adopting state-of-art non-parametric modeling approaches for stochastic data. Moreover, various charging protocols will be investigated including; grid-to-vehicle (G2V), vehicle-to-vehicle (V2V) and vehicle-to-grid (V2G). Battery swap combined with coordinated charging schemes will be developed to efficiently manage the EV charging infrastructure and optimally operate the distribution networks. In addition, integration of utility-owned mobile charging stations (MSCs) fleet will be studied. At the planning level, novel optimization algorithms will be developed to size the MSC fleet, i.e. identifying the optimum number of MSC units and their sizes. At the operational level, graph-theory based optimization algorithms will be developed for dynamically allocating and sizing those MSCs considering areas population dense, power network demands, and traffic conditions to minimize operational costs of the power network, charging costs, time and traffic congestion.


Project 1: A Novel Approach for Estimating Dominant Modes of Droop Controlled Inverter Based Microgrid

Online detection of the microgrid stability is crucial for determining and adjusting the power-sharing droop controllers’ gains adaptively. Maintaining minimum relative stability should be ensured at different operating conditions to accommodate any sudden system changes. Detailed modeling of inverter-based microgrids (IBMGs) is essential for precise assessment of stability margins. Although detailed analytical models for droop based microgrids are available, they are both computationally complex and do consider possible real time variations in microgrid parameters and operating conditions. This project aims to propose a novel approach to identify the dominant modes of IBMGs using local measurements. A short-duration small disturbance is applied to one of the DGs active power droop gain then the dominant modes of the system are estimated from the local measurements with the highest participation factor in the microgrid.  The effectiveness of the developed approach was validated via MATLAB/SIMULINK simulation considering different droop gains and microgrid parameters, where the estimated dominant modes are compared with those obtained from the microgrid’s small signal model. The estimated dominant modes using the proposed approach can be utilized for online assessment of the microgrid stability.


Project 2: Dynamic and Flexible Distribution Systems with Mobile Generation and Loads

Microgrids are envisioned to be the building blocks of smart grids due to the numerous advantages that they bring to the system including improving system efficiency, reliability and providing enabling technologies for grid-independence to end-user sites. Conventionally, microgrid, whether grid-connected or autonomous, is configured from a group of interconnected loads and distributed-energy resources within clearly defined electrical boundaries that acts as a single controllable entity with respect to the grid. Such microgrids, when properly controlled, can help in increasing the system reliability and maintaining adequate supply to customers. However, under contingencies and severe dynamics these microgrids can fail and collapse due to mismatch in active/reactive power or being destabilized. Typically, generation and loads are static in the sense that they are allocated at specific locations with no capability of mobilization. Distribution systems with flexible and movable generation as well as loads can change their composition continuously in response to any system change (occurred or anticipated), hence, providing an attractive solution to enhance system operation, efficiency, stability and reduce overall operational costs. Consequently, groups of interconnected microgrids can dynamically restructure (to be connected or disconnected) to achieve a specific operational objective.


Project 3:  Optimized EV Charging Infrastructure Allocation and Smart Charging Protocols

Transportation electrification is looked at, not only as a way to reduce environmental pollution by reducing harmful emissions, but also as a trend that is proliferating our society to form what is known as smart cities. Electric Vehicles (EV), not only provide a massive reduction of tailpipe emissions; but also present a massive improvement in vehicle performance and efficiency. The Electric Power Research Institute (EPRI) envision that EVs will contribute to 20%, 60%, or 80% of the entire U.S. vehicle fleet by 2050 using low, medium, and high vehicle fleet penetration scenarios. Further, the UAE also is following the same trend and aims to have 20% of their vehicles on roads to be electric by 2030.

Optimizing the transportation electrification dictates several collaborative and interlinked directions, some relates to the device design and others relates to the system operation and practices. On the device level, the innovative design of the power train to improve its efficiency and response is vital. Further, the development of better charging equipment, whether fast chargers or wireless chargers is seen as a crucial step. On the other hand, on the system level, two main directions are of increased importance, charging infrastructure optimized allocation and smart charging protocols development. This project will focus on the two important system aspects of transportation electrification, specifically Electric Vehicles charging stations (EVCS) and charging protocols. We will aim to optimize the location and size (number and type of chargers) of required EVCS. In order to achieve the optimal station location and capacity, we will take into consideration both transportation and electrical constraints. Road capacity and traffic models will be used to allocate the charging stations in the most populated locations to serve more customers. Electrical grid strength and regulation will be brought into the optimization constraints in order to guarantee energy availability without violating any of the grid regulation practices. Further, this project will focus on developing a smart AI-aided charging protocols that will work on increasing the customer satisfaction level along with maximizing the EVCS profits. All possible affecting parameters such as state of charge (SOC), arrival and departure times, battery type and capacity, chargers type and payments will be considered.


Project 4: Artificial Intelligence Based Fault Diagnosis for Condition Assessment of Power System Networks

This project is intended to fulfil the need to develop new artificial intelligence-based autonomous incipient fault detection and condition assessment techniques for power system components and networks. Essential system components such as generators, cables, transformers and switchgear are prone to deficiencies over their lifetime and existing fault detection methods are not fully able to diagnose the type and severity of deficiency without human intervention.  This research project aims to fulfil this gap by applying artificial intelligence methods to help diagnose faults autonomously and efficiently, by focusing specifically on the application of deep learning (DL) for (i) the detection and diagnosis of incipient insulation defects in cables, transformers and gas insulated systems (GIS) due to partial discharge (PD), an excellent indicator of insulation condition and  for (ii) providing novel and accurate interpretation of swept and impulse frequency response analysis data (SFRA and IFRA) in transformers and machines. The potential of deep learning methods in improving the effectiveness of condition monitoring in future smart grids is recognized and research in this field is expanding. This project proposes an in-depth investigation of the characteristics of various types of partial discharges and FRA transfer functions, derived from extensive experiments within APEC’s lab facilities and from published data. This data will be used to validate the DL models that will be able to automatically learn the most representative characteristics of each type of defect from PD signals or FRA plots and provide accurate incipient fault detection and classification.


The conventional vehicles in the transportation sector use fossil fuel, account for approximately 40% to 50% of the energy use, and are major contributors (about 30%) to greenhouse gas emission. This has prompted governments across the world to plan for electrification of transportation sector. The number of electric vehicles on the road has been increasing considerably worldwide. By 2035, and according to Bloomberg Intelligence, the annual EV sales are projected to exceed 48 million units, up from roughly 2 million in 2020. The UAE government, in its 2030 vision that is in line with the UN’s agenda 2030, has given emphasis on reducing greenhouse gas emission through several measures. One of the action plans in UAE vision 2030 is transportation electrification. Another emphasis in UAE vison 2030 is sustainable smart cities, with autonomous vehicles, efficient public transportation and integration of renewable energy sources. At present, the transportation electrification technology is in the early stages of development. There are several research challenges to be addressed in order to achieve the transportation electrification goals. There is a great need for research in this area and this has motivated APEC to set up a theme dedicated to research on electric transportation in phase II. The transportation electrification is a broad area of research covering the electric ground vehicles (Electric bikes, Electric cars, Electric SUVs, Electric Bus, and Electric Trucks) commonly referred as electric vehicles (EVs), Electric trains, all electric ships (AES), all electric aircrafts (AEA) and drones. For the next three years, Theme 4 will focus its research mainly on electric vehicles and has plans to expand its research into AES and AEA in the later stage. Transportation electrification has impacted battery technology, motor technology, power electronics and the power system. The energy demand on power system will increase and the power system network should be in a position to meet this additional energy demand. The future sustainable smart cities will require intelligent energy management and close coordination between the power network and electrified transportation network through evolving technologies such as internet of things (IOT), artificial intelligence, advanced control and secured communication through cyber security. There is great potential to develop PV powered green parking and charging stations for EVs, especially in cities where vehicle density is high. For optimal energy use and efficient transportation, cities need to plan for infrastructure to meet additional energy demand, setting up charging stations, modification of roads for dynamic wireless charging. Large number of parked EVs in the cities can offer auxiliary service to power system such as secondary storage of electrical energy, power factor correction, active filtering, etc. This will call for research in the area of bidirectional wireless charging and grid to vehicle (G2V) and vehicle to grid (V2G) energy flow. Theme 4 will develop interaction with chemical engineering, mechanical engineering and basic science (Mathematics, Physics and Chemistry departments) on allied research related to battery technology and hydrogen fuel cells and developing new materials. Following are the main research areas under theme 4 in phase II of APEC and will be carried out with close collaborative research with other themes of APEC.


Ø Ferrite Based High-Speed Coreless Permanent Magnet Motor for Traction Application

Permanent magnet motors are utilized in more than 60% of existing electric vehicles existing in the market. The cost of rare-earth permanent magnets and limited stockpile are however limiting factor in wider utilization of these motors. Alternatives currently being researched are (i) permanent magnet motors utilizing with less-rare earth permanent magnets, (ii) Motors utilizing no rare-earth permanent magnets such as ferrite based permanent magnet motors and switched reluctance motors. This project will focus on developing alternative motor topologies that achieve comparable or better performance to conventional permanent magnet synchronous motors. In particular, we propose an evolutionary objective optimization design of high-speed ferrite based permanent magnet motor to achieve a high-power density propulsion motor suitable for traction application. Numerical simulation and experimental validation shall be used to show the improved performance compared to conventional Neodymium based permanent magnet synchronous motors.


Ø Efficient Power Train for high power vehicles (SUVS, Buses and Trucks)

Research in this area involves multidisciplinary tasks such as research on drive control and arrangement, modular structure of power converters, battery arrangement, regenerative braking and energy management. At high power levels, the research is directed towards using induction motors or combination of induction motors and synchronous reluctance motors. Multiphase motors with open-end winding (OEW) configuration is one of the solutions. The research team has recently developed novel four-wheel differential drive (FWDD) train based on three-phase OEW induction motors, which has several promising features. Multi-phase combined with OEW is a novel solution and has built in fault tolerant operation, which results in modular converters, improved ratability and low DC bus voltage. Low DC bus voltage will enable parallel operation of batteries and uniform distribution of battery mass. This theme will collaborate with theme 2 in developing modular converters and the focus is mainly on efficiency, power density reliability and adverse operating conditions (ex: vibration, high temperature, dust, dirt, conductive particles and water). Through efficient regenerative braking, the braking energy can be captured. Also damping energy associated with the mechanical shock absorbers can be captured by using electrical shock absorbers. Controlled regenerative braking and electrical shock absorbers will result in smooth driving experience and reduce the wear and tear of vehicle thus reduced maintenance. In order to get the best drive range AI based optimal energy management algorithms will be developed through collaborative research with theme 5. Monitoring the health of the power converters, motors and batteries are essential requirements of EVs and this theme will interact with theme 3 and theme 5 in developing AI based condition monitoring algorithms for EVs.


  • Efficient Bidirectional Wireless Charging


With autonomous vehicles are the focus of future EVs, wireless charging will be preferred. The inductive wireless charging can offer distinct advantages compared to conductive charging such as galvanic isolation and convenience. Development of high-coupling wireless charging pads and integrating them with the EV system is the focus of this thrust. Increasing the power transfer efficiency, increasing the power capacity, mitigation of miss-alignment problems and distance between transmitter and receiver coils are the main focus of the research. For large power vehicles such as buses and trucks, dynamic wireless charging a better option. The research team has good experience in developing wireless chargers and the team under this thrust area will expand its research to high power wireless charging and also dynamic wireless charging. Another challenging dimension the team likes to add to the wireless charging is bidirectional power flow, which will be useful in grid to vehicle (G2V) and vehicle to grid (V2G) power exchange.


Ø Power Train for All Electric Ships (AES) and All Electric Aircrafts (AEA)


The power in megawatt range call for entirely different research as per as AES and AEA are concerned. The theme will expand its research in this area and will develop suitable drive train models with high power density motors, fault-tolerant performance, distributed battery layout and multi-level modular converts. Reducing the power conversion levels, developing new materials, repeatability as per as converters are concerned, electrical network and wiring layout and battery layout are key requirements.



Industry engagement is a key part of APEC mission and considered as one of the center’s strategic priorities. APEC industry engagement strategy will support the mission of the center by ensuring regular, mutually beneficial communication between APEC and a broad range of relevant industrial (and other) stakeholders. Such interaction will also identify and prioritize current industrial needs leading to new research and development avenues. The generated research knowledge and technology will be transferred to industry through industry‐academia colloquia, training workshops and demonstrations of the developed methods and tools. An active engagement with numerous industrial partners has been developed. This theme will aim to continue building on this active industrial collaboration to engage and broaden industrial stakeholders, to boost the long‐term mutual activities focused on industry-based research, Testing & Development, Training & Continuing Education. Furthermore, the Theme will work on increasing the visibility and international exposure by organizing well-established international conferences in relevant areas. Moreover, during this stage, APEC will be working toward initiating a spin-off company on training, testing, and consultancy. Furthermore, APEC will have other measurable outcomes in the form of prototypes that is industry-guided to address needs.

Industry-Based Research

APEC targets to be the university research center with the highest number and value of industrial-financed research collaborations. With this purpose, APEC will actively search for new and better ways to partner with industries from within UAE and around the world. APEC will market its capabilities in providing research facilities, expertise and resources and inform potential industrial partners with an in-depth view of the most current and groundbreaking developments in the power and energy industry. APEC is well positioned to serve the three major UAE government utilities: (i) TAQA (TRANSCO, ADDC, and AADC), EWEC and DEWA. Such collaboration between KU and the utilities in UAE could help in the delivery of reliable, efficient, and affordable power supply as well as fulfil KU’s requirement to provide excellence in service of training and research. In addition, KU-APEC can be envisioned as a regional hub for power grid innovative technologies serving, not only the UAE, but also neighboring GCC countries. Furthermore, APEC has been exploring opportunities with major industrial entities such as Emirates Steel, which has been materialized to a commitment of financial support of KU VRI for Sustainable Energy Production, Storage, and Utilization. Such efforts will be continued to involve APEC with more of the relevant key industrial players.

Testing & Development

Testing Services at APEC will provide high-quality engineering solutions to industrial clients in areas of testing and development at a competitive price. APEC engineering services can offer a controlled testing environment that can be manipulated precisely to achieve goals by working with clients to create specific laboratory conditions to test their technologies. For example, major manufacturers use real-time digital simulators (RTDS or Opal-RT, both of which are available within APEC) to test their HVDC controls during factory systems testing.  Systems successfully tested include LCC- and VSC-based HVDC, modular multi-level converters, network and industrial SVCs, STATCOM, TCSC, DVR, and UPFC. Furthermore, high-voltage tests may be carried out on plant and insulation materials using test and measurement equipment in the High‐Voltage and Dielectric Materials laboratory.

Training & Continuing Educations

APEC has been working on offering a training and continuing education programs for industry to provide professional engineers with cutting-edge knowledge essential for innovation in the power and energy industry. Such programs will tap into theoretical and laboratory aspects of post graduate courses and the center’s research expertise.

Community and Professional Activities

APEC will continue working on organizing national and international workshops/symposiums open to the academic and industrial bodies as part of the efforts to promote Khalifa University as one of the top universities in the region. Furthermore, APEC has been participating in several undergraduate competitions as well as graduate students’ conferences. Recently, APEC have organized a flagship conference of the IEEE Power & Energy Society in Abu Dhabi and, more specifically, KU. ISGT (Innovative Smart Grid Technology) on 12-15 March 2023. ISGT is one of the most prestigious conferences dealing with Smart Grid, which has branches in North America, Europe, and Asia. It was an excellent opportunity to be the first ones to launch ISGT-Middle East, and to host it in Khalifa University.

A crucial contribution of APEC to Khalifa University and the local community is the establishment and development of five state of the art research laboratories which constitutes well-designed setups and testbeds that has been used by many graduate students as part of their validation tasks. Furthermore, these labs have equipped our researchers and students with unique skills and experience that empowered them to secure international scholarships or high technical jobs.

Research Translation and Prototyping

Although APEC focuses on developing high impact publications, another important aspect is how this research will be translated into useful products. In this regard, APEC has developed a translation plan to clearly define the intended outcomes of the research beyond high-impact academic publications. Action plans such as working with Khalifa University Technology Management and Innovation Office to support intellectual property licensing as well as engaging different companies and utilities for joint technology development are set.