Mohamed Bahloul

Bio: Mohamed Bahloul is an academic researcher from Tyndall National Institute. The author has contributed to research in topics: Fuzzy logic & Vector control. The author has an hindex of 6, co-authored 19 publications receiving 91 citations. Previous affiliations of Mohamed Bahloul include University of Sfax.

Robust sensorless vector control of an induction machine using Multiobjective Adaptive Fuzzy Luenberger Observer.

Abstract: This paper presents an inherent speed estimation scheme associated to the Indirect Field Oriented Control in case of Induction motor sensorless control. Indeed, through the design of a Multiobjective Adaptive Fuzzy Luenberger Observer, the speed sensorless control issue even at low speed, the observer poles' assignment issues and the speed estimation's sensitivity to rotor resistance uncertainties issue are treated concurrently. First of all, the structure of the proposed Takagi-Sugeno adaptive observer is described. Secondly, based on Lyapunov theory, observer gains are designed and a fuzzy speed estimation scheme is provided. The design's objectives consist of minimizing the sensitivity of the proposed observer to rotor resistance uncertainties (using the L2 techniques) and to guarantee a specified observer dynamic performances through a D-stability analysis. The design conditions are formulated into Linear Matrix Inequalities terms. Finally, experiments are conducted to demonstrate the effectiveness of the proposed results regardless of uncertainties in the rotor resistance.

Impact of Power Sharing Method on Battery Life Extension in HESS for Grid Ancillary Services

Abstract: Hybrid energy storage system (HESS) based on Li-ion and supercapacitor (SC) can play a potential role to stabilize the grid by providing the fast frequency ancillary services. The SC helps to reduce the battery charge/discharge stress and, hence, assists to extend the battery lifespan. The power sharing method (PSM) is the heart in control part to improve the HESS performance and reduce the battery stress. This paper proposes a hybrid PSM and investigates its impact on battery life extension along with its relation to the system design and regulation signal. The performance of hybrid PSM is compared with three other PSMs (low-pass filter, first and second rule based) in a 10 MW/10 MWh full-active parallel HESS for frequency regulation service in two networks: U.K. (national grid) and USA (PJM). Considering maximum possible battery lifetime upto 25 years, result shows that the hybrid PSM approach allows a degree of the better performance for both grid while the sharing of SC is kept maximum 2.0% and 2.5% (for U.S. and U.K. grid, respectively) of the HESS capacity. This study also analyses the impact of PSM on shared capacity and design of HESS for different grid regulation signals.

Design and control of energy storage system for enhanced frequency response grid service

Abstract: Nowadays, new regulations are taking place that impose to integrate more renewable energy sources (RES) to the grid. The intermittent characteristics of these uncontrollable sources have a negative impact on the grid quality and stability. On the other hand, the ancillary services (ASs) have potential role in maintaining the grid stability and balancing the frequency and the voltage at the fundamental values. Thus, AS market exhibits a great expansion in the recent years and novel regulation frameworks are also developing. Very recently in UK, the distribution network operator, National Grid (NG) have developed a novel portfolio for providing a primary active power AS known as Enhanced Frequency Response (EFR) service. In this paper, a design guideline of electrical energy storage system (ESS) for this EFR provision is given. In addition, a power management system is described to ensure the control of a hybrid energy battery-supercapacitor storage system (HESS). Simulations are carried out for both battery only energy storage system (BESS) and HESS to analyze the regulation dynamics and to compare the performances for each system.

An analytical approach for techno-economic evaluation of hybrid energy storage system for grid services

Abstract: This paper presents an analytical approach to study the techno-economic sustainability of hybrid ESS (HESS) for grid ancillary services. As an example, Li-ion battery and supercapacitor (SC) based HESS is considered for the recently developed enhance frequency response (EFR) service to improve the UK grid stability. The design objective is to optimize the shared capacity of storage units that enables extending battery lifetime and maximize the economic benefits. A heuristic method for power sharing algorithm is also proposed to efficiently define the shared power of SC with its state-of-charge condition. Extensive simulation and case studies are carried out for a 10MW HESS solution. Studies include the impacts of battery degradation model, power management system and the HESS design capacity/sizing on the optimal share of SC capacity and annual profit estimation. Results show that 10% error in battery degradation model (over/under) can also lead up to 18% increase or 25% decrease in profit estimation. Optimal SC share of 7% can be possible with a maximum annual profile of 137.26%. Share can be reduced to 5–6% by 10% over-sized of HESS capacity, but the overall profit then reduces to 133.36%. This approach can also be implemented for other HESS solutions.

Effective Fuzzy Logic Control of a Stand-alone Photovoltaic Pumping System

Abstract: This paper presents an effective control of a stand-alone batteryless photovoltaic (PV) pumping system. The whole design (configuration and control) is oriented in order to minimize the cost and maximize the effectiveness, the efficiency and the reliability of the whole system. Beyond the withdrawal of the battery and the rotor speed sensor, the system is composed only of a DC-DC boost converter, a DC-AC inverter, an Induction Motor (IM) and a centrifugal pump. In order to control the dc-link voltage and maximize the efficiency of the IM, a Fuzzy Logic Controller (FLC) is introduced. The validity and the effectiveness of the proposed FLC is tested and confirmed by a simulation under various climate changes.

Fast Frequency Response From Energy Storage Systems—A Review of Grid Standards, Projects and Technical Issues

Abstract: Electric power systems foresee challenges in stability due to the high penetration of power electronics interfaced renewable energy sources. The value of energy storage systems (ESS) to provide fast frequency response has been more and more recognized. Although the development of energy storage technologies has made ESSs technically feasible to be integrated in larger scale with required performance, the policies, grid codes and economic issues are still presenting barriers for wider application and investment. Recent years, a few regions and countries have designed new services to meet the upcoming grid challenges. A number of grid-scale ESS projects are also implemented aiming to trial performance, demonstrate values, and gain experience. This paper makes a review on the above mentioned aspects, including the emerging frequency regulation services, updated grid codes and grid-scale ESS projects. Some key technical issues are also discussed and prospects are outlined.

Deep Reinforcement Learning-Based Controller for SOC Management of Multi-Electrical Energy Storage System

Abstract: The ongoing reduction of the total rotational inertia in modern power systems brings about faster frequency dynamics that must be limited to maintain a secure and economical operation. Electrical energy storage systems (EESSs) have become increasingly attractive to provide fast frequency response services due to their response times. However, proper management of their finite energy reserves is required to ensure timely and secure operation. This paper proposes a deep reinforcement learning (DRL) based controller to manage the state of charge (SOC) of a Multi-EESS (M-EESS), providing frequency response services to the power grid. The proposed DRL agent is trained using an actor-critic method called Deep Deterministic Policy Gradients (DDPG) that allows for continuous action and smoother SOC control of the M-EESS. Deep neural networks (DNNs) are used to represent the actor and critic policies. The proposed strategy comprises granting the agent a constant reward for each time step that the SOC is within a specific band of its target value combined with a substantial penalty if the SOC reaches its minimum or maximum allowable values. The proposed controller is compared to benchmark DRL methods and other control techniques, i.e., Fuzzy Logic and a traditional PID control. Simulation results show the effectiveness of the proposed approach.

A Comparative Study on Adaptive EKF Observers for State and Parameter Estimation of Induction Motor

Abstract: In this article, conventional extended Kalman filter (EKF) and adaptive extended Kalman filters (AEKFs) based on adaptive fading, strong tracking, and innovation are compared for state and parameter estimation problem of induction motor (IM) by considering their estimation performances and computational burdens. The estimation performance of EKFs depends on the proper selection of system and measurement noise covariance matrices. However, it is hard to select optimum elements of those matrices using the trial-and-error method, and those are affected by the operating conditions of IM. Therefore, different AEKF approaches with the ability to update those matrices online according to the operating conditions have been proposed in the literature. However, to the best of the author's knowledge, no comparison has been yet reported as to which observer is more effective for real-time state and parameter estimation problem of IM. This paper focuses on the detailed comparison of those observers and provides useful results to the literature.