Browsing by Author "Mahmoud, Karar"

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Accurate Insulating Oil Breakdown Voltage Model Associated with Different Barrier Effects
(2021-04-09) Ghoneim, Sherif S.M.; Dessouky, Sobhy S.; Boubakeur, Ahmed; Elfaraskoury, Adel A.; Sharaf, Ahmed B. Abou; Mahmoud, Karar; Lehtonen, Matti; Darwish, Mohamed M. F.
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
In modern power systems, power transformers are considered vital components that can ensure the grid’s continuous operation. In this regard, studying the breakdown in the transformer becomes necessary, especially its insulating system. Hence, in this study, Box–Behnken design (BBD) was used to introduce a prediction model of the breakdown voltage (VBD) for the transformer insulating oil in the presence of different barrier effects for point/plane gap arrangement with alternating current (AC) voltage. Interestingly, the BBD reduces the required number of experiments and their costs to examine the barrier parameter effect on the existing insulating oil VBD. The investigated variables were the barrier location in the gap space (a/d)%, the relative permittivity of the barrier materials (εr), the hole radius in the barrier (hr), the barrier thickness (th), and the barrier inclined angle (θ). Then, only 46 experiment runs are required to build the BBD model for the five barrier variables. The BBD prediction model was verified based on the statistical study and some other experiment runs. Results explained the influence of the inclined angle of the barrier and its thickness on the VBD. The obtained results indicated that the designed BBD model provides less than a 5% residual percentage between the measured and predicted VBD. The findings illustrated the high accuracy and robustness of the proposed insulating oil breakdown voltage predictive model linked with diverse barrier effects.
Adaptive LFC incorporating modified virtual rotor to regulate frequency and tie-line power flow in multi-area microgrids
(2022-03-22) Abubakr, Hussein; Guerrero, Josep M.; Vasquez, Juan C.; Mohamed, Tarek Hassan; Mahmoud, Karar; Darwish, Mohamed M.F.; Dahab, Yasser Ahmed
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
This research investigates a new coordination strategy for both isolated single-area and interconnected multi-area microgrids (MGs) using a modified virtual rotor-based derivative technique supported with Jaya optimizer based on balloon effect modulation (BE). Accordingly, the main concept of BE is to assist the classic Jaya to be more sensitive and trackable in the event of disturbances, as well as to provide optimum integral gain value on the secondary frequency controller adaptively for both suggested MGs. The proposed modified virtual rotor mechanism is consisting of virtual inertia and virtual damping that are added as a tertiary controller within proposed MGs considering full participation of the inverter-based energy storage systems. The proposed virtual rotor mechanism is consisting of virtual inertia and virtual damping that are added as a tertiary controller within proposed MGs to emulate the reduction in system inertia and the enhanced damping properties. Several nonlinearities were proposed in this work such as a dead band of governor, generation rate constraints, and communication time-delay are considered within the dynamic model of the suggested MGs. In addition, the proposed design of multi-area MGs takes the interval time-varying communication delays into account for stability conditions. In this study, A comparative study using unimodal (i.e., Sphere) and multimodal (i.e., Rastrigin) benchmark test functions are conducted to validate the proposed direct adaptive Jaya-based BE. Furthermore, Wilcoxon’s rank-signed non-parametric statistical test using a pairwise comparison was performed at a 5 % risk level to judge whether the proposed algorithm output varies from those of the other algorithms in a statistically significant manner. Thence, the superiority and effectiveness of the proposed method have also been verified against a variety of other metaheuristics optimization techniques, including classic electro-search, particle swarm, multi-objective seagull, and Jaya optimizers. In addition, an operative performance is assessed against the conventional integral controller, coefficient diagram method, and classic Jaya with/without virtual inertia. The final findings emphasize the superiority of the proposed direct adaptive Jaya-based BE supported by a modified virtual rotor and state better performance and stability compared to existing controllers.
Assessment of an Improved Three-Diode against Modified Two-Diode Patterns of MCS Solar Cells Associated with Soft Parameter Estimation Paradigms
(2021-02-01) Bayoumi, Ahmed S.; El-Sehiemy, Ragab A.; Mahmoud, Karar; Lehtonen, Matti; Darwish, Mohamed M. F.
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Recently, the use of multi-crystalline silicon solar cells (MCSSCs) has been increasing worldwide. This work proposes a novel MCSSC pattern for achieving a more accurate emulation of the electrical behavior of solar cells. Specifically, this pattern is dependent on the modification of the double diode model of MCSSCs. Importantly, the proposed pattern has an extra diode compared to the previously modified double-diode model (MDDM) described in the literature for considering the defect region of MCSSC to form a modified three diode model (MTDM). For estimating the parameters of the proposed MTDM, two metaheuristic algorithms called closed-loop particle swarm optimization (CLPSO) and elephant herd optimization (EHO) are developed, which have superior convergence rates. The competitive algorithms are executed on experimental data based on a MCSSC of area 7.7 cm2 from Q6-1380 and CS6P-240P solar modules under different irradiance and temperature levels for both MDDM and MTDM. Also, the proposed elephant herd optimization soft paradigm is extended for a high irradiance level at 1000 W/m2 on an R.T.C. France Solar cell. The proposed new optimization models are more efficient in dealing with the natural characteristics of the MCSSC. The simulation results show that the MTDM gives more accurate solutions as a model to the MCSSC compared with the results reported in the literature. From the viewpoint of soft computing paradigms, the EHO outperforms CLPSO in terms of the solution quality and convergence rates.
Book Review on “Antonio Moreno-Munoz; Neomar Giacomini; Energy Smart Appliances: Applications, Methodologies, and Challenges (2023)‏”
(2024-04-25) Mousa, Hossam H. H.; Mahmoud, Karar; Lehtonen, Matti
Book/Film/Article review
Recently, the integration of new industrial technologies is significantly increased into the utility grid such as renewable energy sources (RESs), distributed energy resources (DERs), energy source systems (ESSs), electric vehicles (EVs), and multi-carrier energy systems (MESs). So, robust energy management strategies are required to regulate the power-exchange between the generations and end-users for improving the power system's reliability and stability and reducing the energy costs. Thus, the demand-side management (DSM) strategies and demand response (DR) programs are utilized to control the energy smart appliances for residential building which achieving by various strategies, required infrastructure, energy market signals, etc. Several textbooks and articles investigate this important topic. However, the book entitled “Antonio Moreno-Munoz; Neomar Giacomini; Energy Smart Appliances: Applications, Methodologies, and Challenges (2023)”, is the most recent prominent comprehensive reference for DSM strategies in smart grids. Hence, this article proposes a book review and discussion of its most important contributions to DSM strategies by dividing them into four main contributions. Which helps the reader in realizing the recent developments on DSM strategies based on this book’s contents.
Book Review on Hosting Capacity for Smart Power Grids, Ahmed F. Zobaa, Shady HE Abdel Aleem et al. Springer, 1 2020
(2024-06) Mousa, Hossam H. H.; Mahmoud, Karar; Lehtonen, Matti
Book/Film/Article review
Nowadays, the growing integration of new industrial technologies into modern power systems (MPSs) such as distributed energy resources (DERs) such as various types of renewable energy sources (RESs), electric vehicles (EVs), and energy storage systems (ESSs), caused various adverse impacts that should be considered broadly. These technologies cause various deteriorations on the performance indices (PIs), eg voltage deviation and reverse power flows. Therefore, the hosting capacity (HC) concept is declared to ensure that integration is managed efficiently to accommodate them without any PI violations. Various research fields investigated HC technologies in terms of calculation methods, tools, enhancement techniques, etc. in several articles and books. However, the book entitled “Hosting Capacity for Smart Power Grids, Ahmed F. Zobaa, Shady HE Abdel Aleem et al. Springer, 1 2020”, is the most recent prominent comprehensive reference for HC strategies in MPSs. Hence, this article proposes a book review and discussion of its most important contributions which helps the reader in realizing the recent developments in HC technologies based on this book’s contents.
Combined DR Pricing and Voltage Control using Reinforcement Learning based multi-agents and Load Forecasting
(2022) Khan, Danyal Afgan; Arshad, Ammar; Lehtonen, Matti; Mahmoud, Karar
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
The demand for energy around the world continues to increase at a very high rate. To sufficiently supply this high demand, it is imperative to employ efficient methods so that the total costs for fulfilling such high demand in energy are minimized. To achieve this ambitious goal, this paper proposes a multi-agent reinforcement learning system for time of use pricing based combined demand response and voltage control. For this purpose, a long short term memory network is employed for day-ahead load forecasting in order to remove future uncertainties. The Q-learning algorithm is used which is a model free algorithm and hence, doesn't require the agent(s) to have prior knowledge of the environment. The role of reinforcement learning in this work is very important since it allows the agent(s) to determine their respective optimal behavior(s) autonomously without explicit training by the end user. To allow effective cooperation among multiple agents, each household is controlled by its own agent, whereas all the household agents are directed by a master agent or service provider. Accordingly, the voltage control agent serves the purpose of checking voltage level violations in the system and removing them through optimal decision making. The proposed system yields very good results, whereby, not only is the overall cost of electricity reduced, but voltage level violations are also removed from the entire system. The implementation of this mechanism reduces the total average aggregated load demand from 5.23 kW to 3.86 kW, while reducing the total aggregated average cost from 94.01 Rs to 60.80 Rs, thanks to the proposed effective multi-agent based system.
Comparative Analysis of Three-Phase PV Grid Connected Inverter Current Control Schemes in Unbalanced Grid Conditions
(2023-04-25) Ibrahim, Nagwa F.; Mahmoud, Karar; Lehtonen, Matti; Darwish, Mohamed M. F.
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Recently, the regulation of photovoltaic inverters, effectively under imbalanced voltages on the grid, has been crucial for the operation of grid-connected solar systems. In this regard, determining the output current reference is an integral aspect of managing a solar inverter with an unbalanced voltage. Based on evaluations of Instantaneous Active-reactive Control (IARC), Positive Negative Sequence Control (PNSC), Balanced Positive Sequence Control (BPSC), and Average Active-reactive Control (AARC), this paper proposes a novel variable-current-t-reference calculation method for minimizing power fluctuations and current harmonics. The controller is employed to regulate both constructive and destructive sequences inside a static framework, therefore enhancing dynamic performance and facilitating the selection of suitable controls in the presence of significant network defects. This study also suggests comparing the four MPPT methodologies examined (fuzzy logic, current only, Incremental Conductance, and Perturb & Observe) to maximize energy output. The simulation results efficiently validate the suggested computation approach that is presented in the current reference.
Comprehensive Analytical Expressions for Assessing and Maximizing Technical Benefits of Photovoltaics to Distribution Systems
(2021-11-01) Mahmoud, Karar; Lehtonen, Matti
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
The proliferation of photovoltaic (PV) can cause several operational problems in distribution systems. In this paper, comprehensive analytical expressions (CAEs) are proposed for maximizing the technical benefits of multiple PV units to distribution systems considering the uncertainty of PV generation and load profiles. Specifically, the proposed CAEs quantify and optimize the following five vital indices with multiple PV units: 1) active energy losses, 2) reactive losses, 3) voltage deviations, 4) line congestion margin, and 5) voltage stability index. The smart functions of the PV inverter (i.e. reactive power support and active power curtailment) are also incorporated in the CAEs, complying with the revised IEEE 1547:2018 standard. Further, various PV tracking options are considered, including fixed, one-axis, and two-axis trackers. Unlike existing approaches, the CAEs can simultaneously solve the optimal allocation problem of multiple PV units in a direct manner without needing optimization algorithms, iterative processes, or simplifying procedures. The calculated results reveal the high performance of the CAEs in terms of accuracy, flexibility and computational speed while providing further PV planning options. Moreover, CAEs are effectively utilized for two other applications with promising computational performance, i.e. rapid assessment of PV impacts with annual datasets and optimal centralized/decentralized inverter control.
A Comprehensive Review on Recent Developments of Hosting Capacity Estimation and Optimization for Active Distribution Networks
(2024-01-29) Mousa, Hossam H. H.; Mahmoud, Karar; Lehtonen, Matti
A2 Katsausartikkeli tieteellisessä aikakauslehdessä
Recently, several types of distributed energy resources (DERs) have been developed to reduce the environmental impact and support the global demand for electrical energy. However, the continuous penetration of the DERs into modern power systems (MPSs) may cause several adverse impacts in terms of operation performance indices (PIs) and power quality issues, especially in low-voltage distribution systems (LVDSs). To cope with these serious impacts and achieve optimal control, the hosting capacity (HC) of DERs must be accurately estimated and optimally optimized. However, it requires an extensive communication infrastructure, which is hardly offered without clear financial benefits. In this regard, this article investigates the historical developments of HC definitions as well as the recent developments in terms of operational performance indices, and estimation methods for active distribution networks (ADNs) with the high-penetration level existence of the DERs, energy storage systems (ESSs), electric vehicle (EV) charging systems, sector coupling, hydrogen technologies, and multi-carrier energy systems (MESs) to deal with electrical, thermal, and cooling demands. In this regard, this review article is intended to exhibit an appropriate reference for comprehensive research trends in HC estimation and optimization based on ADNs. Additionally, it involves and covers most current research HC topics in detail compared to other published review articles. Moreover, the authors deliberate the recent approaches for evaluating and improving the HC, especially concerning data-driven methods, with the aid of various software for simulating real systems. Moreover, modern research trends and main factors of MPS operations are deliberated with current energy market developments. Also, prominent challenges, current status, and future aspects are discussed.
Comprehensive Review on Renewable Energy Sources in Egypt - Current Status, Grid Codes and Future Vision
(2022-01-04) Abubakr, Hussein; Vasquez, Juan C.; Mahmoud, Karar; Darwish, Mohamed M.F.; Guerrero, Josep M.
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
The development of the energy sector in Egypt is considered an urgent issue due to the rapid population rise rate. In particular, renewable energy sources (RESs) applications play an essential role in the coverage of energy demand. Therefore, Egypt has ambitious plans towards RESs to combine a sustainable energy future with economic growth. Egypt has high potentiality for RESs and their applications, nevertheless, the study of this modality remains below the required level. Due to the widespread use of RESs, communities are facing stability issues as the power converters-based RESs create a significant lack of power inertia, causing system instability and power blackouts as well as issues of power quality such as harmonics or resonances due to the power converters and their interactions with the system. This work presents a recent review supported by a statistical analysis about the current situation in Egypt according to the last data carried out from local/global reports. In addition, this review discusses specifications of technical design standards, terms, and equipment parameters for connecting small, medium, and large-scale solar plants, respectively to the Egyptian grid in accordance with the Electricity Distribution Code (EDC), Solar Energy Grid Connection Code (SEGCC), and the Grid Code (GC). Interestingly, the use of hydropower and emergent solar energy is considered the most promising RES variant, besides the wind energy at the coastal sites. This review characterizes the progress in Egypt and classifies interest areas for RESs recent study, e.g., photovoltaic (PV), solar chimney (SC), concentrated solar plant (CSP), and wind energy in Egypt. To maximize the RES hosting capacity in Egypt, various energy storage systems are required to be integrated into the distribution networks. Finally, a view of existing gaps, future visions and projects, and visible recommendations are defined for the Egyptian grid.
A Comprehensive Study of Power Distribution Planning Perspectives: Modelling, Tools, Goals, and Criteria
(2024-01-03) Mousa, Hossam H. H.; Mahmoud, Karar; Lehtonen, Matti
A2 Katsausartikkeli tieteellisessä aikakauslehdessä
To cope with the recent developments in the energy transition sector, several sustainable and renewable energy resources have been utilized to eradicate the harmful impacts of conventional energy sources. However, their increased integration causes adverse impacts on both the utility grid (UG) infrastructure and performance besides variations in the consumption patterns. So, it is crucial to accomplish accurate power system planning, especially at the distribution level, in order to sustain the acceptable limits of reliability and end-user satisfaction in cost-effective procedures. Several textbooks and articles investigate this important topic. However, the book entitled “Power Distribution Planning Reference Book (H. Lee Willis) 2nd Edition, 2004”, is still an important and comprehensive reference for power distribution planning. Hence, this article proposes a book review and discussion of its most important contributions to power distribution planning by dividing them into six parts, each part has its subject associated with the planning topic. Which aids the reader in performing an overview conclusion of this book and its contents. Moreover, providing a comprehensive review of this topic in terms of modelling, tools, goals, and criteria.
Coordinated Allocation of PV and Capacitors with Var Capability for Voltage Unbalance Mitigation in LV Distribution Grids
(2024-10-14) Mousa, Hossam H. H.; Mahmoud, Karar; Lehtonen, Matti
A4 Artikkeli konferenssijulkaisussa
The increased penetration of photovoltaic systems (PVs) and unbalanced loads in low-voltage (LV) distribution systems can adversely affect the overall performance of the utility grid (UG). These impacts include voltage unbalance, power losses, thermal overloading of lines, and various power quality issues. To mitigate voltage unbalance, reactive power control (RPC) techniques are employed by regulating PV inverters and capacitor banks. This study focuses on coordinating the sizing and placement of PVs with reactive power capability (Var) to reduce voltage unbalance and maintain acceptable limits for other power quality indices, particularly in unbalanced three-phase systems. During full load conditions, there is insufficient excess capacity available for reactive power injection or absorption by PV inverters. Therefore, to improve their reactive power capability, the inverters must be oversized relative to the nominal rating of the installed PV systems, which increases capital costs and harmonic levels within distribution networks. To address this, both PVs and capacitor banks are optimally allocated using a multi-objective grey wolf optimization (MOGWO) algorithm within the IEEE 123-bus unbalanced distribution system, using MATLAB and OpenDSS platforms. As a result of this proposed planning, voltage unbalance, power loss, and voltage deviation are significantly decreased by 19%, 34%, and 14% (under 100% overloading), respectively, along with a 215% increase in PV penetration levels. Furthermore, the proposed planning emphasizes that the combination of PVs and capacitor banks can effectively reduce voltage unbalance, which in turn reduces power losses and thermal line overloading.
Deep Learning-Based Industry 4.0 and Internet of Things Towards Effective Energy Management for Smart Buildings
(2021-02-02) Elsisi, Mahmoud; Tran, Minh-Quang; Mahmoud, Karar; Lehtonen, Matti; Darwish, Mohamed M. F.
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Worldwide, energy consumption and saving represent the main challenges for all sectors, most importantly in industrial and domestic sectors. The internet of things (IoT) is a new technology that establishes the core of Industry 4.0. The IoT enables the sharing of signals between devices and machines via the internet. Besides, the IoT system enables the utilization of artificial intelligence (AI) techniques to manage and control the signals between different machines based on intelligence decisions. The paper’s innovation is to introduce a deep learning and IoT based approach to control the operation of air conditioners in order to reduce energy consumption. To achieve such an ambitious target, we have proposed a deep learning-based people detection system utilizing the YOLOv3 algorithm to count the number of persons in a specific area. Accordingly, the operation of the air conditioners could be optimally managed in a smart building. Furthermore, the number of persons and the status of the air conditioners are published via the internet to the dashboard of the IoT platform. The proposed system enhances decision making about energy consumption. To affirm the efficacy and effectiveness of the proposed approach, intensive test scenarios are simulated in a specific smart building considering the existence of air conditioners. The simulation results emphasize that the proposed deep learning-based recognition algorithm can accurately detect the number of persons in the specified area, thanks to its ability to model highly non-linear relationships in data. The detection status can also be successfully published on the dashboard of the IoT platform. Another vital application of the proposed promising approach is in the remote management of diverse controllable devices.
Direct approach for optimal allocation of multiple capacitors in distribution systems using novel analytical closed-form expressions
(2020-08-01) Mahmoud, Karar; Lehtonen, Matti
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
In this paper, novel and efficient analytical closed-form expressions are proposed for the optimal allocation of multiple capacitors in distribution systems to maximize the total cost reduction (CR) while considering power losses. The proposed expressions are novel since they can directly solve the allocation problem without requiring iterative processes or optimization algorithms. Specifically, two analytical closed-form expressions are introduced to determine the optimal number, locations, and sizes of multiple capacitors. The first analytical expression computes directly the optimal sizes of multiple capacitors where it is employed for the optimal sizing of capacitors for all possible combinations of locations. In turn, the best combination is then assigned by using a second analytical expression which directly evaluates all the combinations in terms of their contribution in CR. Unlike the existing methods/expressions that utilize sensitivity factors or optimize each capacitor individually, the proposed analytical closed-form expressions involve a unified mathematical model for multiple capacitors. The proposed direct approach is tested using a 69-bus distribution system. The accuracy and efficacy of the proposed analytical closed-form expressions are verified by comparisons with existing methods and intensive simulations of various allocation scenarios.
A Droop-Based Frequency Controller for Parallel Operation of VSCs and SG in Isolated Microgrids
(2023-01-26) Hafez, Wessam Arafa; Mahmoud, Karar; Ali, Abdelfatah; Shaaban, Mostafa F.; Astero, Poria; Lehtonen, Matti
A4 Artikkeli konferenssijulkaisussa
Microgrids are a novel concept for modern power distribution networks that integrate renewable power sources and increase power control capabilities. This system's essential problem is controlling the frequency in island mode. Using the synchronous generator (SG) control approach, the microgrid frequency is more stable due to the inertial features of the SG. In this regard, this paper presents a control algorithm for voltage source converters (VSC)-based distributed generators (DGs), which emulates the principal behavior of synchronous machines and can support inertia to the grid and reduce frequency gradients considering the parallel operation of the SG. The controller is designed based on droop control theory, and a supervisory center controller is implemented to maintain system frequency close to a nominal value of the whole microgrid. The simulation results demonstrate that the system frequency is stabilized even in different and sudden load changes in the island mode where the microgrid is fed by multiple VSC units and a SG. The Simulink model of the system is designed using MATLAB Simulink Software.
Dynamic Performance Evaluation of Inverter Feeding a Weak Grid Considering Variable System Parameters
(2021-09-07) Harasis, Salman; Mahmoud, Karar; Albatran, Saher; Alzaareer, Khaled; Salem, Qusay
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Interfacing a weak grid imposes challenges on distributed generators (DGs). These challenges include transient frequency and voltage dynamics that can destabilize the system. Accordingly, this paper investigates the grid stiffness based on different scenarios and the dynamics of a grid feeding DG connected to a weak grid. Moreover, the dynamic effects of the physical and control parameters on the system’s stability are deeply analyzed and evaluated. Specifically, complete mathematical models and graphical representation are carried out to precisely examine the impact of the system parameters on the stability and performance of the DG. Therefore, stable deployment of renewable energy resources into power networks can be achieved as well as an efficient and robust performance of DGs can be ensured when connected to weak grids. The obtained results show the importance of the performed study in optimal sizing and designing the output filter of the inverter and the impact of tuning the control parameters on the system dynamics. As a result, a proper design of system physical and control parameters can be accurately achieved considering all factors affect the system performance. The paper also conducts detailed and elaborated analyses and simulations to evaluate the performance of a PI-controlled RC damped inverter connected to a weak grid. The proposed filter design of the interfacing inverter can significantly extend the integration of DGs into microgrids without requiring complex control schemes or oversized components.
An Effective Bi-Stage Method for Renewable Energy Sources Integration into Unbalanced Distribution Systems Considering Uncertainty
(2021-03) Ali, Eman S.; El-Sehiemy, Ragab A.; El-Ela, Adel A. Abou; Mahmoud, Karar; Lehtonen, Matti; Darwish, Mohamed M. F.
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
The output generations of renewable energy sources (RES) depend basically on climatic conditions, which are the main reason for their uncertain nature. As a result, the performance and security of distribution systems can be significantly worsened with high RES penetration. To address these issues, an analytical study was carried out by considering different penetration strategies for RES in the radial distribution system. Moreover, a bi-stage procedure was proposed for optimal planning of RES penetration. The first stage was concerned with calculating the optimal RES locations and sites. This stage aimed to minimize the voltage variations in the distribution system. In turn, the second stage was concerned with obtaining the optimal setting of the voltage control devices to improve the voltage profile. The multi-objective cat swarm optimization (MO-CSO) algorithm was proposed to solve the bi-stages optimization problems for enhancing the distribution system performance. Furthermore, the impact of the RES penetration level and their uncertainty on a distribution system voltage were studied. The proposed method was tested on the IEEE 34-bus unbalanced distribution test system, which was analyzed using backward/forward sweep power flow for unbalanced radial distribution systems. The proposed method provided satisfactory results for increasing the penetration level of RES in unbalanced distribution networks.
An Effective Coordination Strategy for Voltage Regulation in Distribution System Containing High Intermittent Photovoltaic Penetrations
(2021-08-23) Bedawy, Ahmed; Yorino, Naoto; Mahmoud, Karar; Lehtonen, Matti
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
In recent years, with increasing the penetration of renewable-based distributed generation (DGs), voltage control plays a vital role in operating distribution systems (DS). Furthermore, the traditional voltage control devices are not fast enough to regulate the voltage due to transient events and the intermittent characteristics of renewable energy sources (RESs). On the other hand, because of the fast response of power electronic components, the DG inverter can cope with the intermittent and uncertainty of power generation due to environmental changes. Therefore, this paper proposes a cooperative voltage control scheme to solve the voltage problems associated with high DG penetration. The scheme is developed based on a multi-agent system (MAS) with a distributed control architecture using time coordination between voltage regulators and reactive power control of the renewable-based DGs. The scheme’s objective is to minimize voltage deviations and reduce the stress on the traditional voltage control devices by utilizing the available reactive power of the DGs. Different simulations are carried out and analyzed for various operating conditions over 24 hours using the IEEE 34-node and 123-node test feeders. The simulation results show that the proposed control scheme can successfully reduce the total voltage deviation and decrease the number of tap changes of voltage regulators at different sun profiles.
Effective Nonlinear Model Predictive Control Scheme Tuned by Improved NN for Robotic Manipulators
(2021-04) Elsisi, Mahmoud; Mahmoud, Karar; Lehtonen, Matti; Darwish, Mohamed M. F.
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
The nonlinearities of the robotic manipulators and the uncertainties of their parameters represent big challenges against the controller design. Moreover, the tracking of regular and irregular trajectories with fewer overshoots, short settling time, and small steady-state error is the main target for the robotic response. The model predictive control (MPC) is an efficient controller to handle the performance requirements. However, the conventional MPC requires the linearization of the system model. The linearization of the model does not cover all dynamics of the robotic system. Thus, this paper introduces the nonlinear MPC (NLMPC) as a proper control method for the nonlinear systems instead of the conventional MPC. Specifically, this work proposes the use of NLMPC for controlling robotic manipulators. However, the NLMPC gains need proper tuning to attain good performance rather than the conventional methods. The neural network algorithm (NNA) considers a sufficient adaptive intelligent technique that can be utilized for this purpose. The restriction in a local optimum reveals the main issue versus artificial intelligence techniques. This paper suggests a new improvement to reinforce the exploration behavior of the NNA to overcome the local restriction issue. This modification is carried out by utilizing the polynomial mutation as an effective method to promise the exploration manner of the intelligence techniques. The proposed system can estimate all states from only the output to reduce the cost of the required sensors to measure all states. The results confirm the superiority of the proposed systems with the estimator with negligible change in the output response. The proposed modified NNA (MNNA) is evaluated with the main NNA, genetic algorithm-based PID control scheme, besides the cuckoo search algorithm-based PID control scheme from other works. The results confirm the robustness and effectiveness of the suggested MNNA-based NLMPC to track regular and irregular trajectories compared with other techniques.
Effective Transmission Congestion Management via Optimal DG Capacity using Hybrid Swarm Optimization for Contemporary Power System Operations
(2022) Gupta, Prashant; Sarwar, Md; Siddiqui, Anwar Shahzad; Ghoneim, Sherif S.M.; Mahmoud, Karar; Darwish, Mohamed M.F.
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Managing transmission congestion had been a major problem with growing competition in the power networks. Accordingly, competitiveness emerges through the network's reconfiguration and the proliferation of secondary facilities. Congestion of transmission lines is a critical issue, and their regulation poses a technical challenge as the power system is deregulated. Therefore, the present research illustrates a multi-objective strategy for reaching the optimal capabilities of distributed generators (DG) like wind power plants and geothermal power-producing plants to alleviate congestion throughout the transmission network. Goals such as congestion management during power delivery, power loss reduction, power flow improvement with the enhancement of voltage profile, and investment expenditure minimization are considered to boost the network's technological and economic reliability. The congestion management is achieved using the locational marginal price (LMP) and calculation of transmission congestion cost (TCC) for the optimal location of DG. After identification of congested lines, DG is optimally sized by particle swarm optimization (PSO) and a newly proposed technique that combines the features of modified IL-SHADE and PSO called hybrid swarm optimization (HSO) which employs linear population size reduction technique which improves its performance greatly by reducing the population size by elimination of least fit individuals at every generation giving far better results than those obtained with PSO. In addition, optimal rescheduling of generations from generators has been done to fulfill the load demand resulting in alleviation of congested lines thereby enhancing the performance of the network under investigation. Furthermore, the performance of the proposed methodology of HSO and PSO has been tested successfully on standard benchmark IEEE-30 & IEEE-57 bus configurations in a MATLAB environment with the application of MATPOWER power system package.