Energy Institute Research Collection

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The Energy Institute engages in robust industry collaboration to execute a dynamic programme of global partnerships and research initiatives that promote enhanced energy performance as sustainable, reliable, and affordable as possible.

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Recent Submissions

Now showing 1 - 5 of 105
  • Publication
    Self-Controlled PMSM Drive Employed in Light Electric Vehicle-Dynamic Strategy and Performance Optimization
    This proposed work demonstrates the illustration of dynamic performance intensification of a Permanent Magnet Synchronous Motor (PMSM) employed by a PWM controlled inverter which synchronizes with the rotor movement intimation. PMSM are widely hired in electric vehicles since it possesses better dynamic response, improved torque-speed property, and reduced noise, energy-efficient and power factor in comparison with traditional motors. In the present work, it is observed that by few modifications of the position control strategy as good as sinusoidal stator currents response generates less torque ripples. The mathematical model for PMSM is derived from park’s transformation. Further, a maiden attempt is taken to introduce the performance indicator ’sensor angle’ to estimate the rotor position in this strategy. From the established model, the various dynamic behavior of the drive system is determined analytically without and under various load disturbances. Additionally, a particle swarm optimization (PSO) technique is adopted to optimize the performance of the proposed dynamic strategy. An efficient speed control strategy by the variation of DC bus voltage is achieved which is equivalent to the armature voltage control of the conventional dc machine. Further, efficient and simple control circuitry of the voltage source inverter (VSI) is obtained in this strategy. To verify the efficacy of the proposed algorithm, necessary tests are carried out in a real-time setup. Therefore, an improved control strategy obtained from the simulation and an experimental approach meets the dynamic behavior employed in light weight electric vehicles.
      12Scopus© Citations 11
  • Publication
    Comparative Study of Hysteresis Controller, Resonant Controller and Direct Torque Control of Five-Phase IM under Open-Phase Fault Operation
    The need for regulating the operation of unhealthy motor drives has motivated the researchers to modify the control techniques in order to be valid for the new drive state. The use of a fault-tolerant facility is an attractive feature of multiphase machines; therefore, the applicability of different controllers has been established for the operation under open-phase fault conditions. The considered control algorithms were utilized to analyze the operation of the unhealthy system and evaluating the capability of the control to regulate the speed and torque under the fault condition. However, the majority of these studies considered only one control algorithm to be tested with the faulty system without comparing its performance with other techniques. The performance comparison is a vital way to visualize the features and characteristics of each algorithm. For this purpose, this paper deals with the performance comparison of the hysteresis controller, RFOC based on resonant controller and direct torque control (DTC) control under open-circuit fault conditions. A detailed comparison between the three control techniques is presented to outline the main differences between the three control procedures and identify the most appropriate technique in between
      12Scopus© Citations 16
  • Publication
    Scenario-Based Stochastic Framework for Optimal Planning of Distribution Systems Including Renewable-Based DG Units
    Renewable energy-based distributed generators are widely embedded into distribution systems for several economical, technical, and environmental tasks. The main concern related to the renewable-based distributed generators, especially photovoltaic and wind turbine generators, is the continuous variations in their output powers due to variations in solar irradiance and wind speed, which leads to uncertainties in the power system. Therefore, the uncertainties of these resources should be considered for feasible planning. The main innovation of this paper is that it proposes an efficient stochastic framework for the optimal planning of distribution systems with optimal inclusion of renewable-based distributed generators, considering the uncertainties of load demands and the output powers of the distributed generators. The proposed stochastic framework depends upon the scenario-based method for modeling the uncertainties in distribution systems. In this framework, a multi-objective function is considered for optimal planning, including minimization of the expected total power loss, the total system voltage deviation, the total cost, and the total emissions, in addition to enhancing the expected total voltage stability. A novel efficient technique known as the Equilibrium Optimizer (EO) is actualized to appoint the ratings and locations of renewable-based distributed generators. The effectiveness of the proposed strategy is applied on an IEEE 69-bus network and a 94-bus practical distribution system situated in Portugal. The simulations verify the feasibility of the framework for optimal power planning. Additionally, the results show that the optimal integration of the photovoltaic and wind turbine generators using the proposed method leads to a reduction in the expected power losses, voltage deviations, cost, and emission rate and enhances the voltage stability by 60.95%, 37.09%, 2.91%, 70.66%, and 48.73%, respectively, in the 69-bus system, while in the 94-bus system these values are enhanced to be 48.38%, 39.73%, 57.06%, 76.42%, and 11.99%, respectively.
      9Scopus© Citations 13
  • Publication
    Transformers Improvement and Environment Conservation by Using Synthetic Esters in Egypt
    Distribution transformer (DT) is a crucial component in power systems as it exchanges energies between different voltage levels or between utility grid and DC microgrids. Nevertheless, the operation of an oil-immersed DT is limited by the thermal and electrical capabilities of the internal insulating liquid. This paper aims to raise the efficiency of distribution transformers and preserve the environment by using a biodegradable insulating liquid instead of the conventional mineral insulating oil (MIO). This work examines the Egyptian case, where a real distribution network located in middle Egypt is selected as a pilot project. Study and analysis of the status que of the insulation system inside DTs are done with the aid of fault-tree analysis. The deficiency of the insulation system is confirmed by conducting an electronic survey of 100 expert participants. The most appropriate solution among three different alternatives is confirmed using the weighting and ranking method. The best choice suitable for the selected area is the substitution of MIO by synthetic ester (SE). The technical and environmental advantages achieved by the presented solution are discussed. The feasibility studies have proven that the solution is positively acceptable in all aspects. An execution plan is established for the application of proposed solution on the selected Egyptian distribution network.
      14
  • Publication
    Optimal Multi-Operation Energy Management in Smart Microgrids in the Presence of RESs Based on Multi-Objective Improved DE Algorithm: Cost-Emission Based Optimization
    Today, in various leading power utilities in developing countries, achieving optimal operational energy management and planning, taking into account the costs reduction of generation, transmission and distribution of electricity, and also reducing the emission of an environmental pollutant becomes more and more important. Optimal use of renewable energy sources (RESs) is an effective way to achieve these goals. In this regard, in this research article, an improved multi-objective differential evolutionary (IMODE) optimization algorithm is suggested and performed to dispatch electricity generations in a smart microgrid (MG) system, taking into account economy and emission as competitive issues. In this paper, a nonlinear equation of multi-objective optimization issue with various equality and inequality limitations is formulated in order to lower the total operational costs of the MG considering environmental pollution effects simultaneously. In order to address the issue of optimal operation of the MG in single-objective and multi-objective forms, an intelligent method according to the improved differential evolutionary (IDE) optimization is utilized and performed and the proposed algorithm is implemented on different problems. First, it is assumed that there is no limit to the exchange of power overhead, and secondly, the limitation of power exchange with the upstream grid is considered. In multi-objective mode, these two modes are also considered. In order to show the impact of renewable energy on the cost, in the third part of the simulations, the operation is solved with maximum participation of renewable energy sources. In the final section, the sensitivity analysis on the number of populations in this problem is performed. The obtained results of the simulation are compared to differential evolutionary (DE) and particle swarm optimization (PSO) techniques. The effectiveness of the suggested multi-operational energy management method is confirmed by applying a study case system.
      13Scopus© Citations 44