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Conventionally, a market research and strategy for a product depends on the interviews and an explicit cluster/society to identify the customer’s needs. Customer-created information (CCI), such as call-center data, online reviews, and social media posts, provides an opportunity to recognize the customer’s needs more efficiently. Moreover, developed conventional approaches are not compatible with large CCI datasets because most of the CCI-contents are repetitive and uninformative. In this paper, a machine learning approach for identifying the customer needs from the CCI dataset is proposed and its performance is evaluated for targeting and recommending a new product for project management. After the identification of the needs of the customer, information can be used to develop a market strategy, new product launching, brand positioning and much more long/short term planning.
Hasmat Malik; Asyraf Afthanorhan; Noor Aina Amirah; Nuzhat Fatema. Machine Learning Approach for Targeting and Recommending a Product for Project Management. Mathematics 2021, 9, 1958 .
AMA StyleHasmat Malik, Asyraf Afthanorhan, Noor Aina Amirah, Nuzhat Fatema. Machine Learning Approach for Targeting and Recommending a Product for Project Management. Mathematics. 2021; 9 (16):1958.
Chicago/Turabian StyleHasmat Malik; Asyraf Afthanorhan; Noor Aina Amirah; Nuzhat Fatema. 2021. "Machine Learning Approach for Targeting and Recommending a Product for Project Management." Mathematics 9, no. 16: 1958.
Optimum Photovoltaic (PV) system integration in power grid depend upon the total of power accessible from the PV. To figure the PV systems highest power yield, PV panels must be positioned at an optimal tilt angle (OPTA) to absorb maximum solar radiation (SR). This OPTA is a function of the latitude, clearness index, diffuse SR, global SR, direct SR and optimum PV size. Therefore OPTA has an impact on maximum power generation and optimal PV system sizing. The PV is not installed at OPTA for most of the sites in India which is important for maximum power generation and optimum sizing of standalone PV systems. This results in variation of OPTA from site to site and its effect on PV sizing needs to be investigated. The innovative aspect of this work is the calculation of OPTA, which are employed as sensitive factors in Hybrid Optimization of Multiple Energy Resources (HOMER), to determine their impact on maximum optimum sizing and power generation for 26 cities in India’s various climate zones. This methodology can be applied all over the world to determine the impact of OPTA on maximum power generation and size. It is found that OPTA varies from 63° to 0° throughout year in India and it is maximum for December in India. The results indicates that Net Present Cost varies from
Amit Kumar Yadav; Hasmat Malik; S. S. Chandel; Irfan Ahmad Khan; Sattam Al Otaibi; Hend I. Alkhammash. Novel Approach to Investigate the Influence of Optimum Tilt Angle on Minimum Cost of Energy-Based Maximum Power Generation and Sizing of PV Systems: A Case Study of Diverse Climatic Zones in India. IEEE Access 2021, 9, 110103 -110115.
AMA StyleAmit Kumar Yadav, Hasmat Malik, S. S. Chandel, Irfan Ahmad Khan, Sattam Al Otaibi, Hend I. Alkhammash. Novel Approach to Investigate the Influence of Optimum Tilt Angle on Minimum Cost of Energy-Based Maximum Power Generation and Sizing of PV Systems: A Case Study of Diverse Climatic Zones in India. IEEE Access. 2021; 9 ():110103-110115.
Chicago/Turabian StyleAmit Kumar Yadav; Hasmat Malik; S. S. Chandel; Irfan Ahmad Khan; Sattam Al Otaibi; Hend I. Alkhammash. 2021. "Novel Approach to Investigate the Influence of Optimum Tilt Angle on Minimum Cost of Energy-Based Maximum Power Generation and Sizing of PV Systems: A Case Study of Diverse Climatic Zones in India." IEEE Access 9, no. : 110103-110115.
The presented work employs the multiple random feature kernel mean p-power algorithm (MRFKMP) for the voltage source converter (VSC) control of a three-phase four-wire grid-tied dual-stage photovoltaic-hybrid energy storage system (HESS) to achieve multiple objectives during various induced dynamic conditions. The proposed control enables the VSC to accomplish manifold goals, i.e., reactive power compensation, power quality enhancement, load, power balancing at common coupling point and grid voltage balancing during unity power factor mode of operation. The proposed system is scrutinized under steady-state and numerous dynamic states such as irradiation variation, specified power mode, abnormal grid voltage, load, and grid voltage unbalancing. The seamless control facilitates the swift resynchronization of the grid as well as maintaining stability during islanding and re-synchronization operations while satisfying the necessary load requirements. The associated HESS consisting of battery and ultra-capacitor is competent enough in managing the interruptions occurring on the grid, load and photovoltaic side. The DC bus voltage is controlled by the PI controller, which is tuned by the generalized normal distribution algorithm and kept at the desired level during diverse operating conditions. The optimized DC bus generates an accurate loss component of current and further enhances the VSC performance. The proposed system is investigated by simulation and found acceptable as per IEEE 519 standards.
Mukul Chankaya; Ikhlaq Hussain; Aijaz Ahmad; Hasmat Malik; Fausto García Márquez. Generalized Normal Distribution Algorithm-Based Control of 3-Phase 4-Wire Grid-Tied PV-Hybrid Energy Storage System. Energies 2021, 14, 4355 .
AMA StyleMukul Chankaya, Ikhlaq Hussain, Aijaz Ahmad, Hasmat Malik, Fausto García Márquez. Generalized Normal Distribution Algorithm-Based Control of 3-Phase 4-Wire Grid-Tied PV-Hybrid Energy Storage System. Energies. 2021; 14 (14):4355.
Chicago/Turabian StyleMukul Chankaya; Ikhlaq Hussain; Aijaz Ahmad; Hasmat Malik; Fausto García Márquez. 2021. "Generalized Normal Distribution Algorithm-Based Control of 3-Phase 4-Wire Grid-Tied PV-Hybrid Energy Storage System." Energies 14, no. 14: 4355.
A new algorithm for biometric templates using a 6D-chaotic system, and 2D fractional discrete cosine transform (FrDCT) is proposed in this paper. In this technique, the
Dhanesh Kumar; Anand B. Joshi; Sonali Singh; Vishnu Narayan Mishra; Hamurabi Gamboa Rosales; Liang Zhou; Arvind Dhaka; Amita Nandal; Hasmat Malik; Satyendra Singh. 6D-Chaotic System and 2D Fractional Discrete Cosine Transform Based Encryption of Biometric Templates. IEEE Access 2021, 9, 103056 -103074.
AMA StyleDhanesh Kumar, Anand B. Joshi, Sonali Singh, Vishnu Narayan Mishra, Hamurabi Gamboa Rosales, Liang Zhou, Arvind Dhaka, Amita Nandal, Hasmat Malik, Satyendra Singh. 6D-Chaotic System and 2D Fractional Discrete Cosine Transform Based Encryption of Biometric Templates. IEEE Access. 2021; 9 ():103056-103074.
Chicago/Turabian StyleDhanesh Kumar; Anand B. Joshi; Sonali Singh; Vishnu Narayan Mishra; Hamurabi Gamboa Rosales; Liang Zhou; Arvind Dhaka; Amita Nandal; Hasmat Malik; Satyendra Singh. 2021. "6D-Chaotic System and 2D Fractional Discrete Cosine Transform Based Encryption of Biometric Templates." IEEE Access 9, no. : 103056-103074.
The unpredictable nature of the loads and non-linearity of the components of microgrid systems make optimal scheduling more complex. In this paper, a deterministic optimal load-scheduling problem is developed for microgrids operating in both islanding and grid-connected mode under different energy scenarios. Various cases are considered in this research, based on the interaction and dynamic behavior of the microgrid, considering electric vehicles (EVs) in the scenario. The aim of this research is to minimize the overall cost of microgrid operations. The concept of dynamic pricing has also been introduced in order to optimize the energy cost for the consumers. For ensuring the stability of the microgrids, a load variance index has been considered, and the fuzzy-based approach has been used for cost and load variance minimization to reduce the operation cost without compromising the stability of the microgrid. The grid-to-vehicle (G2V) and vehicle-to-grid (V2G) operations of EVs are integrated into the microgrid, which would help in valley filling and peak shaving of the loads during the off-peak and peak hours, respectively. In order to solve the proposed complex combinatorial optimization problem, elephant herding optimization (EHO) is modified and implemented. The performance of the proposed improved EHO (IEHO) is first tested on the latest CEC test functions. The results obtained by IEHO after 100 different trials are compared with the latest published methods and are found to be better based on the average value and the standard deviation for different CEC test functions. In addition, the simulation results obtained by particle swarm optimization (PSO), EHO, and proposed IEHO on a microgrid test system for different scenarios with all cases reveal that the proposed model with a mix of energy resources in the dynamic load dispatch environment bring the maximum benefits of microgrid systems. Furthermore, the results obtained from the simulation verifies that if free trade of power is allowed between the microgrids and the main grid, the process of power generation can be more economical, and further introduction of dynamic pricing into the scenario proves to be even cheaper. The implementation of the G2V and V2G operations of EVs operations in the proposed scenario not only helped in cost minimization but also helped in stabilizing the grid.
Vinay Jadoun; Nipun Sharma; Piyush Jha; Jayalakshmi S.; Hasmat Malik; Fausto Garcia Márquez. Optimal Scheduling of Dynamic Pricing Based V2G and G2V Operation in Microgrid Using Improved Elephant Herding Optimization. Sustainability 2021, 13, 7551 .
AMA StyleVinay Jadoun, Nipun Sharma, Piyush Jha, Jayalakshmi S., Hasmat Malik, Fausto Garcia Márquez. Optimal Scheduling of Dynamic Pricing Based V2G and G2V Operation in Microgrid Using Improved Elephant Herding Optimization. Sustainability. 2021; 13 (14):7551.
Chicago/Turabian StyleVinay Jadoun; Nipun Sharma; Piyush Jha; Jayalakshmi S.; Hasmat Malik; Fausto Garcia Márquez. 2021. "Optimal Scheduling of Dynamic Pricing Based V2G and G2V Operation in Microgrid Using Improved Elephant Herding Optimization." Sustainability 13, no. 14: 7551.
A new hybrid meta-heuristic approach Jaya–PPS, which is the combination of the Jaya algorithm and Powell’s Pattern Search method, is proposed in this paper to solve the optimal power flow (OPF) problem for minimization of fuel cost, emission and real power losses and total voltage deviation simultaneously. The recently developed Jaya algorithm has been applied for the exploration of search space, while the excellent local search capability of the PPS (Powell’s Pattern Search) method has been used for exploitation purposes. Integration of the local search procedure into the classical Jaya algorithm was carried out in three different ways, which resulted in three versions, namely, J-PPS1, J-PPS2 and J-PPS3. These three versions of the proposed hybrid Jaya–PPS approach were developed and implemented to solve the OPF problem in the standard IEEE 30-bus and IEEE 57-bus systems integrated with distributed generating units optimizing four objective functions simultaneously and IEEE 118-bus system for fuel cost minimization. The obtained results of the three versions are compared to the Dragonfly Algorithm, Grey Wolf Optimization Algorithm, Jaya Algorithm and already published results using other methods. A comparison of the results clearly demonstrates the superiority of the proposed J–PPS3 algorithm over different algorithms/versions and the reported methods.
Saket Gupta; Narendra Kumar; Laxmi Srivastava; Hasmat Malik; Alberto Pliego Marugán; Fausto García Márquez. A Hybrid Jaya–Powell’s Pattern Search Algorithm for Multi-Objective Optimal Power Flow Incorporating Distributed Generation. Energies 2021, 14, 2831 .
AMA StyleSaket Gupta, Narendra Kumar, Laxmi Srivastava, Hasmat Malik, Alberto Pliego Marugán, Fausto García Márquez. A Hybrid Jaya–Powell’s Pattern Search Algorithm for Multi-Objective Optimal Power Flow Incorporating Distributed Generation. Energies. 2021; 14 (10):2831.
Chicago/Turabian StyleSaket Gupta; Narendra Kumar; Laxmi Srivastava; Hasmat Malik; Alberto Pliego Marugán; Fausto García Márquez. 2021. "A Hybrid Jaya–Powell’s Pattern Search Algorithm for Multi-Objective Optimal Power Flow Incorporating Distributed Generation." Energies 14, no. 10: 2831.
It is expected that large-scale producers of wind energy will become dominant players in the future electricity market. However, wind power output is irregular in nature and it is subjected to numerous fluctuations. Due to the effect on the production of wind power, producing a detailed bidding strategy is becoming more complicated in the industry. Therefore, in view of these uncertainties, a competitive bidding approach in a pool-based day-ahead energy marketplace is formulated in this paper for traditional generation with wind power utilities. The profit of the generating utility is optimized by the modified gravitational search algorithm, and the Weibull distribution function is employed to represent the stochastic properties of wind speed profile. The method proposed is being investigated and simplified for the IEEE-30 and IEEE-57 frameworks. The results were compared with the results obtained with other optimization methods to validate the approach.
Satyendra Singh; Manoj Fozdar; Hasmat Malik; Maria Fernández Moreno; Fausto García Márquez. Influence of Wind Power on Modeling of Bidding Strategy in a Promising Power Market with a Modified Gravitational Search Algorithm. Applied Sciences 2021, 11, 4438 .
AMA StyleSatyendra Singh, Manoj Fozdar, Hasmat Malik, Maria Fernández Moreno, Fausto García Márquez. Influence of Wind Power on Modeling of Bidding Strategy in a Promising Power Market with a Modified Gravitational Search Algorithm. Applied Sciences. 2021; 11 (10):4438.
Chicago/Turabian StyleSatyendra Singh; Manoj Fozdar; Hasmat Malik; Maria Fernández Moreno; Fausto García Márquez. 2021. "Influence of Wind Power on Modeling of Bidding Strategy in a Promising Power Market with a Modified Gravitational Search Algorithm." Applied Sciences 11, no. 10: 4438.
The fast globalization of renewable energy-based technologies has enabled its wide speared utilization as well. This has shaped a new prospect of operation in the modern electricity system. But, its dependency on environmental factors leads to an uncertain scenario in the day-ahead electricity market. During this period, compromises are made in the genuine process of expenditure and resources of the producers to offset the capacity that decreases the profits for the producers. In general, a significant variety of scenarios need to be taken into account when describing uncertainty, thereby necessitating the need for techniques of scenario reduction. Therefore, to manage the intractable effects of solar radiation and wind speed instability, the function of the Beta and Weibull distribution of probability is implemented, respectively, and scenarios are minimized using forward-reduction algorithms. Besides, an underestimation and overestimation of the cost function are used to calculate the deviation of renewable influence. Thus, this paper is suggesting a valuable bidding strategy to maximize the remuneration of electricity producers in the presence of rival competitors and the instability of solar and wind energy. This problem has been prepared by taking the benchmark IEEE 30-bus network with and without renewable energy sources, and this problem has been solved by using the Gravitational Search Algorithm. The observations of the outcome demonstrate the appropriateness of the projected bid strategy in the presence of volatility of renewable energy.
Satyendra Singh; Manoj Fozdar; Abdulaziz Almutairi; Saeed Alyami; Hasmat Malik. Strategic Bidding in the Presence of Renewable Sources for Optimizing the Profit of the Power Suppliers. IEEE Access 2021, 9, 70221 -70232.
AMA StyleSatyendra Singh, Manoj Fozdar, Abdulaziz Almutairi, Saeed Alyami, Hasmat Malik. Strategic Bidding in the Presence of Renewable Sources for Optimizing the Profit of the Power Suppliers. IEEE Access. 2021; 9 ():70221-70232.
Chicago/Turabian StyleSatyendra Singh; Manoj Fozdar; Abdulaziz Almutairi; Saeed Alyami; Hasmat Malik. 2021. "Strategic Bidding in the Presence of Renewable Sources for Optimizing the Profit of the Power Suppliers." IEEE Access 9, no. : 70221-70232.
Elevated price of renewable energy (RE) systems slowed its adoption in many countries. Hence, it is important to select an optimal size of the system in order to decrease cost, excess energy produced by RE system. The RE system is used to minimize air pollution and energy security. The aim of this study is to evaluate and compare the techno-economic performance of grid-connected photovoltaic (PV) power systems for a rooftop solar PV building containing 14 families in six regions with different climate zones in India. For this purpose, grid connected PV (Grid-PV) is installed at optimum tilt angles (OTA). Then, techno-economic performance of these systems is performed in the six climatic zones in India, which is the novelty of this study. RE resources and ambient temperature for different seasons are considered during analysis. The load is fixed for all the sites for a better comparison in the study. The results show that using OTA in Grid-PV system reduces greenhouse gas emissions, e.g. COx, SOx and NOx, decreases payback time while increasing overall PV production and other project productivity parameters. These include specific yield, PV penetration, return on investment, Internal Rate of Interest, Net Present Value, Annualized Saving, Energy sold to the grid for all climatic zones in India proving useful for industry. Using these metrics and results in this paper, researchers and project developers, policy makers can promote better use of renewable energy. Therefore, it is necessary to use Grid-PV with OTA for different climatic zones.
Amit Kumar Yadav; Hasmat Malik; S. M. Suhail Hussain; Taha Selim Ustun. Case Study of Grid-Connected Photovoltaic Power System Installed at Monthly Optimum Tilt Angles for Different Climatic Zones in India. IEEE Access 2021, 9, 60077 -60088.
AMA StyleAmit Kumar Yadav, Hasmat Malik, S. M. Suhail Hussain, Taha Selim Ustun. Case Study of Grid-Connected Photovoltaic Power System Installed at Monthly Optimum Tilt Angles for Different Climatic Zones in India. IEEE Access. 2021; 9 ():60077-60088.
Chicago/Turabian StyleAmit Kumar Yadav; Hasmat Malik; S. M. Suhail Hussain; Taha Selim Ustun. 2021. "Case Study of Grid-Connected Photovoltaic Power System Installed at Monthly Optimum Tilt Angles for Different Climatic Zones in India." IEEE Access 9, no. : 60077-60088.
In this paper, a self-learning multi-class intelligent model for wind turbine fault diagnosis is proposed by using MFQL (Modified-Fuzzy-Q-Learning) technique. The MFQL is adaptive in nature and extension of fuzzy-Q-learning method where look-up table of Q-learning is conquered by fuzzy based approximation strategy to reduce the curse of dimensionality of the Q-learning. The proposed MFQL classifier diagnoses the mechanical and imbalance faults without using mechanical sensors. Proposed methodology is addressed with relying on PMSG (Permanent Magnet Synchronous Generator) stator current signals, which is already being used by protection system of wind turbines. According to the aforementioned description, non-stationary current signals of PMSG have been pre-processed to extract the input features by empirical mode decomposition followed with J48 algorithm based most relevant input feature selection. For the one-step ahead performance demonstration of the proposed MFQL approach, results have been compared with neural network, support vector machines, fuzzy logic, and conventional Fuzzy-Q-Learning techniques. Demonstrated results outperform the capability of proposed MFQL approach. Moreover, MFQL is developed first time to implement in the area of WTGS fault diagnosis in the literature.
Hasmat Malik; Abdulaziz Almutairic. Modified Fuzzy-Q-Learning (MFQL)-Based Mechanical Fault Diagnosis for Direct-Drive Wind Turbines Using Electrical Signals. IEEE Access 2021, 9, 52569 -52579.
AMA StyleHasmat Malik, Abdulaziz Almutairic. Modified Fuzzy-Q-Learning (MFQL)-Based Mechanical Fault Diagnosis for Direct-Drive Wind Turbines Using Electrical Signals. IEEE Access. 2021; 9 (99):52569-52579.
Chicago/Turabian StyleHasmat Malik; Abdulaziz Almutairic. 2021. "Modified Fuzzy-Q-Learning (MFQL)-Based Mechanical Fault Diagnosis for Direct-Drive Wind Turbines Using Electrical Signals." IEEE Access 9, no. 99: 52569-52579.
In the above article [1] , a minor typo error should be corrected via this correction article. The unit of filter’s capac-itances, in Table 8, is microfarad (symbolized $\mu $ F) as per the obtained results.
Mohit Bajaj; Naveen Kumar Sharma; Mukesh Pushkarna; Hasmat Malik; Majed A. Alotaibi; Abdulaziz Almutairi. Correction to “Optimal Design of Passive Power Filter Using Multi-Objective Pareto-Based Firefly Algorithm and Analysis Under Background and Load-Side’s Nonlinearity”. IEEE Access 2021, 9, 45399 -45399.
AMA StyleMohit Bajaj, Naveen Kumar Sharma, Mukesh Pushkarna, Hasmat Malik, Majed A. Alotaibi, Abdulaziz Almutairi. Correction to “Optimal Design of Passive Power Filter Using Multi-Objective Pareto-Based Firefly Algorithm and Analysis Under Background and Load-Side’s Nonlinearity”. IEEE Access. 2021; 9 ():45399-45399.
Chicago/Turabian StyleMohit Bajaj; Naveen Kumar Sharma; Mukesh Pushkarna; Hasmat Malik; Majed A. Alotaibi; Abdulaziz Almutairi. 2021. "Correction to “Optimal Design of Passive Power Filter Using Multi-Objective Pareto-Based Firefly Algorithm and Analysis Under Background and Load-Side’s Nonlinearity”." IEEE Access 9, no. : 45399-45399.
In the present era, electrical power system is evolving to an inverter-dominated system from a synchronous machine-based system, with the hybrid power systems (HPS) and renewable energy generators (REGs) increasing penetration. These inverters dominated HPS have no revolving body, therefore, diminishing the overall grid inertia. Such a low system inertia could create issues for HPS with REG (HPSREG) such as system instability and lack of resilience under disturbances. A control strategy, therefore, is required in order to manage this task besides benefitting from the full potential of the REGs. A virtual inertia control for an HPSREG system built with the principle of fractional order (FO) by incorporation of proportional-integral-derivative (PID) controller and fuzzy logic controller (FLC) has been projected. It is utilized by adding virtual inertia into HPSREG system control loop and referred to as FO based fuzzy PID controller for this study. Simulation outcomes states that the advocated FO based fuzzy PID controller has superior control in frequency of the system under frequent load variations. It has been noted that the proposed control scheme exhibits improved efficiency in maintaining specific reference frequency and power tracking as well as disturbance diminution than optimal classic and FO-based controller. It has been validated that, the developed controller effectively delivers preferred frequency and power provision to a low-inertia HPSREG system against high load demand perturbation. In the presented paper, analysis based on sensitivity has also been performed and it has been found that the HPSREG system’s is not effected by system parameter and load variations.
Tarkeshwar Mahto; Rakesh Kumar; Hasmat Malik; S. Hussain; Taha Ustun. Fractional Order Fuzzy Based Virtual Inertia Controller Design for Frequency Stability in Isolated Hybrid Power Systems. Energies 2021, 14, 1634 .
AMA StyleTarkeshwar Mahto, Rakesh Kumar, Hasmat Malik, S. Hussain, Taha Ustun. Fractional Order Fuzzy Based Virtual Inertia Controller Design for Frequency Stability in Isolated Hybrid Power Systems. Energies. 2021; 14 (6):1634.
Chicago/Turabian StyleTarkeshwar Mahto; Rakesh Kumar; Hasmat Malik; S. Hussain; Taha Ustun. 2021. "Fractional Order Fuzzy Based Virtual Inertia Controller Design for Frequency Stability in Isolated Hybrid Power Systems." Energies 14, no. 6: 1634.
This paper proposes an Exponentially Varying Whale Optimization Algorithm (EVWOA) to solve the single-objective non-convex Cogeneration Units problem. This problem seeks to evaluate the optimal output of the generator unit to minimize a CHP system’s fuel costs. The nonlinear and non-convex characteristics of the objective function demands a powerful optimization technique. The traditional Whale Optimization Algorithm (WOA) is improved by incorporating four different acceleration functions to fine-tune its performance during exploration and exploitation phases. Among the four variants of the proposed WOA, the emphasis is laid on the EVWOA which uses the exponentially varying acceleration function (EVAF). The proposed EVWOA is tested on six different small-scale to large-scale systems. The results obtained for these six test systems, followed by a statistical study highlight the supremacy of EVWOA for finding the best optimal solution and the convergence traits.
Vinay Jadoun; G. Prashanth; Siddharth Joshi; Anshul Agarwal; Hasmat Malik; Majed Alotaibi; Abdulaziz Almutairi. Optimal Scheduling of Non-Convex Cogeneration Units Using Exponentially Varying Whale Optimization Algorithm. Energies 2021, 14, 1008 .
AMA StyleVinay Jadoun, G. Prashanth, Siddharth Joshi, Anshul Agarwal, Hasmat Malik, Majed Alotaibi, Abdulaziz Almutairi. Optimal Scheduling of Non-Convex Cogeneration Units Using Exponentially Varying Whale Optimization Algorithm. Energies. 2021; 14 (4):1008.
Chicago/Turabian StyleVinay Jadoun; G. Prashanth; Siddharth Joshi; Anshul Agarwal; Hasmat Malik; Majed Alotaibi; Abdulaziz Almutairi. 2021. "Optimal Scheduling of Non-Convex Cogeneration Units Using Exponentially Varying Whale Optimization Algorithm." Energies 14, no. 4: 1008.
In this paper, the optimal designing of passive power filter (PPF) is formulated as a multi-objective optimization (MOO) problem under several constraints of system’s performance indices (PIs) such as individual as well as total harmonic distortion (THD) in the line current and the point of common coupling’s (PCC) voltage, distribution line’s ampacity under harmonic currents overloading, steady-state voltage profile, load power factor (PF) and a few associated with the filter itself. The optimal design parameters of a third-order damped filter are simultaneously determined for achieving maximum PF at the PCC while keeping system’s other indices such as total demand distortion (TDD) in the line current, total voltage harmonic distortion (TVHD) at the PCC and total filter cost (FC) incurred at a minimum by obtaining a best-compromised solution using the newly proposed multi-objective Pareto-based firefly algorithm (pb-MOFA). A novel MOO approach inspired by the modified firefly algorithm and Pareto front is established in order to deal with PPF design problems. The extension of MOFA is considered for producing the Pareto optimal front and various conclusions are drawn by analysing the trade-offs among the objectives. The efficiency and accuracy of the proposed pb-MOFA, in solving the concerned MOO problem, is validated by comparing an obtained solution and three computed PIs viz. convergence metric (CM), generational distance (GD) and diversity metric (DM) with those obtained from popular multi-objective Pareto-based PSO (pb-MOPSO), non-dominated sorting genetic algorithm (NSGA-II) and recently introduced multi-objective slime mould algorithm (MOSMA). The need for true Pareto front (TPF) is served by the one obtained by Monte Carlo method. At last, the impacts of different background voltage distortion (BVD) levels and load-side’s nonlinearity levels (NLLs) on filter performance are analysed.
Mohit Bajaj; Naveen Kumar Sharma; Mukesh Pushkarna; Hasmat Malik; Majed A. Alotaibi; Abdulaziz Almutairi. Optimal Design of Passive Power Filter Using Multi-Objective Pareto-Based Firefly Algorithm and Analysis Under Background and Load-Side’s Nonlinearity. IEEE Access 2021, 9, 22724 -22744.
AMA StyleMohit Bajaj, Naveen Kumar Sharma, Mukesh Pushkarna, Hasmat Malik, Majed A. Alotaibi, Abdulaziz Almutairi. Optimal Design of Passive Power Filter Using Multi-Objective Pareto-Based Firefly Algorithm and Analysis Under Background and Load-Side’s Nonlinearity. IEEE Access. 2021; 9 ():22724-22744.
Chicago/Turabian StyleMohit Bajaj; Naveen Kumar Sharma; Mukesh Pushkarna; Hasmat Malik; Majed A. Alotaibi; Abdulaziz Almutairi. 2021. "Optimal Design of Passive Power Filter Using Multi-Objective Pareto-Based Firefly Algorithm and Analysis Under Background and Load-Side’s Nonlinearity." IEEE Access 9, no. : 22724-22744.
This work primarily focuses on electrical characteristics of a hybrid power system (HPS) incorporating renewable energy generation (REG) (HPSREG). The major components of HPSREG are the resources coordinated with multi-unit of photovoltaic cells, multi-unit of wind turbine generators, a diesel engine generator (DEG), energy storage system (ESS) with diverse nature and an electric vehicle (EV). The performance characteristics of HPSREG are determined by constant generation of power from the various sources as well as varying load perturbations. As the variation in load demand will introduce fluctuation in frequency and power with constant generation. In few of overcome the frequency and power deviation under both the above-mentioned generation and load demand conditions, proper control technique is required. In order to control the deviation in frequency and power, an integration in the environment of fractional order (FO) calculus for proportional–integral–derivative (PID) controller and fuzzy controller, termed with FO-Fuzzy PID controller tuned with quasi-opposition based harmonic search (QOHS) algorithm has been proposed. The results acquired with the proposed FO-Fuzzy-PID controller are then analyzed along with FO-PID and PID controller route for quantify effectiveness for the same under the considered cases to determine the effectiveness of the algorithm undertaken. Sensitivity investigation is also conducted in order to show the strength of the technique under study of differences in HPSREG parameters of magnitude.
Vigya; Tarkeshwar Mahto; Hasmat Malik; V. Mukherjee; Majed A. Alotaibi; Abdulaziz Almutairi. Renewable generation based hybrid power system control using fractional order-fuzzy controller. Energy Reports 2021, 7, 641 -653.
AMA StyleVigya, Tarkeshwar Mahto, Hasmat Malik, V. Mukherjee, Majed A. Alotaibi, Abdulaziz Almutairi. Renewable generation based hybrid power system control using fractional order-fuzzy controller. Energy Reports. 2021; 7 ():641-653.
Chicago/Turabian StyleVigya; Tarkeshwar Mahto; Hasmat Malik; V. Mukherjee; Majed A. Alotaibi; Abdulaziz Almutairi. 2021. "Renewable generation based hybrid power system control using fractional order-fuzzy controller." Energy Reports 7, no. : 641-653.
Bearingless motor development is a substitute for magnetic bearing motors owing to several benefits, such as nominal repairs, compactness, lower cost, and no need for high-power amplifiers. Compared to conventional motors, rotor levitation and its steady control is an additional duty in bearingless switched reluctance motors when starting. For high-speed applications, the use of simple proportional integral derivative and fuzzy control schemes are not in effect in suspension control of the rotor owing to inherent parameter variations and external suspension loads. In this paper, a new robust global sliding-mode controller is suggested to control rotor displacements and their positions to ensure fewer eccentric rotor displacements when a bearingless switched reluctance motor is subjected to different parameter variations and loads. Extra exponential fast-decaying nonlinear functions and rotor-tracking error functions have been used in the modeling of the global sliding-mode switching surface. Simulation studies have been conducted under different testing conditions. From the results, it is shown that rotor displacements and suspension forces in X and Y directions are robust and stable. Owing to the proposed control action of the suspension phase currents, the rotor always comes back rapidly to the center position under any uncertainty.
Pulivarthi Nageswara Rao; Ramesh Devarapalli; Fausto Pedro García Márquez; Hasmat Malik. Global Sliding-Mode Suspension Control of Bearingless Switched Reluctance Motor under Eccentric Faults to Increase Reliability of Motor. Energies 2020, 13, 5485 .
AMA StylePulivarthi Nageswara Rao, Ramesh Devarapalli, Fausto Pedro García Márquez, Hasmat Malik. Global Sliding-Mode Suspension Control of Bearingless Switched Reluctance Motor under Eccentric Faults to Increase Reliability of Motor. Energies. 2020; 13 (20):5485.
Chicago/Turabian StylePulivarthi Nageswara Rao; Ramesh Devarapalli; Fausto Pedro García Márquez; Hasmat Malik. 2020. "Global Sliding-Mode Suspension Control of Bearingless Switched Reluctance Motor under Eccentric Faults to Increase Reliability of Motor." Energies 13, no. 20: 5485.
The occupancy level of the room in a building is responsible for consumption of electrical power within the building. The occupancy level in a room depend on several controllable and/or uncontrollable parameters within and/or outside environment of the building. So, for the optimal demand forecasting and planning within the building, occupancy detection play an important role. In this study, the occupancy is determined by using simple measureable parameters of the inside environment of the building such as light (in lux), temperature (in Celsius), relative humidity (in %), CO2 level (in ppm) and humidity ratio (in kg water-vapor/kg-air). The data-driven occupancy detection using particle swarm optimization (PSO) based artificial neural network (ANN) is designed in R language and proposed approach is validated with different seventeen models by using the measured dataset. The occupancy detection for these models are 77.9–98.95% for ANN models and 87.8–99.5% for PSO-ANN models, which shows that PSO based ANN model’s performance is more acceptable in comparison to only ANN models.
Nuzhat Fatema; Hasmat Malik. Data-Driven Occupancy Detection Hybrid Model Using Particle Swarm Optimization Based Artificial Neural Network. Metaheuristic and Evolutionary Computation: Algorithms and Applications 2020, 283 -297.
AMA StyleNuzhat Fatema, Hasmat Malik. Data-Driven Occupancy Detection Hybrid Model Using Particle Swarm Optimization Based Artificial Neural Network. Metaheuristic and Evolutionary Computation: Algorithms and Applications. 2020; ():283-297.
Chicago/Turabian StyleNuzhat Fatema; Hasmat Malik. 2020. "Data-Driven Occupancy Detection Hybrid Model Using Particle Swarm Optimization Based Artificial Neural Network." Metaheuristic and Evolutionary Computation: Algorithms and Applications , no. : 283-297.
In recent days, many novel techniques and technologies are developing for power generation. Most of them are in its developed phase but its efficiency and reliability are low. Some of them have no running cost but its installation is costly. Some others are not cost effective and its cost to benefit ratio is poor. Because of all these reasons optimization techniques are required to expand the productivity, reliability and decrease the expense by optimal utilization of the resources and controlling methods. This chapter is mainly deals with basic and important metaheuristics optimization techniques used for power generation through renewable energy resources. Metaheuristic optimization approaches like Particle-Swarm Optimization (PSO), Differential-Evolution (DE), Tabu-Search (TS), Simulation-Annealing (SA), Genetic-Algorithm (GA), Artificial-Bee Colony (ABC), Ant-Colony Optimization (ACO), Cuckoo-Search (CS), and Biogeography-Based Optimization (BBO) are applicable on power generation using renewable energy resources. Some optimization techniques are good for solar PV system like PSO, ACO, ABC, DE etc., and some other optimization techniques like GA, CS, TS, BBO etc. for Battery storage using renewable hybrid system and design wind farm layouts. Applications of various metaheuristics optimization approaches for different renewable energy and hybrid systems are present in this chapter.
Ahmad Faiz Minai; Hasmat Malik. Metaheuristics Paradigms for Renewable Energy Systems: Advances in Optimization Algorithms. Econometrics for Financial Applications 2020, 35 -61.
AMA StyleAhmad Faiz Minai, Hasmat Malik. Metaheuristics Paradigms for Renewable Energy Systems: Advances in Optimization Algorithms. Econometrics for Financial Applications. 2020; ():35-61.
Chicago/Turabian StyleAhmad Faiz Minai; Hasmat Malik. 2020. "Metaheuristics Paradigms for Renewable Energy Systems: Advances in Optimization Algorithms." Econometrics for Financial Applications , no. : 35-61.
The overall cost of a building depends on several variables such as economical, project physical and financial variables. The CCB (construction cost of building) also depends on deviations of several indices which are not control in an easy way. Therefore, the overall sales prices of a building may not be controlled due to these indices. In this chapter, a metaheuristic algorithm based hybrid model for identification of building’s sales prices is presented, which is developed by using conventional Feedforward Neural Network (FNN).table The identification accuracy of FNN is varies with respect to the number of input variables and its modal parameters such as weight (w) and bias (b). In this chapter, the number of most relevant input variables are selected by using Relief F Attribute evaluator (RFAE) with the help of ranker search method. After selecting most appropriate variables, the FNN parameters are optimized by using particle swarm optimization (PSO) based metaheuristic algorithm (MA). The total 208 intelligent models have been designed and validated using 372 real side construction cost dataset of three to nine story buildings. The validated results by FNN and PSO-FNN show that selected variables gives better results as compared with other models.
Nuzhat Fatema; Hasmat Malik; Atif Iqbal. Metaheurestic Algorithm Based Hybrid Model for Identification of Building Sale Prices. Metaheuristic and Evolutionary Computation: Algorithms and Applications 2020, 689 -704.
AMA StyleNuzhat Fatema, Hasmat Malik, Atif Iqbal. Metaheurestic Algorithm Based Hybrid Model for Identification of Building Sale Prices. Metaheuristic and Evolutionary Computation: Algorithms and Applications. 2020; ():689-704.
Chicago/Turabian StyleNuzhat Fatema; Hasmat Malik; Atif Iqbal. 2020. "Metaheurestic Algorithm Based Hybrid Model for Identification of Building Sale Prices." Metaheuristic and Evolutionary Computation: Algorithms and Applications , no. : 689-704.
The traffic light controlling strategy has noteworthy impressions on the traffic congestion, risks of accidents, waiting time and unnecessary consumption of fuel. But, regardless of over 50 years of researches on theory of traffic flow, the most of traffic light controlling systems are not reconfigured on a routine basis. Also, the efficiency of traffic light controlling strategy is subject to greatly on information and understanding of the circulation team. So, recently, the growing congestion in road traffic has drown portion of thoughtfulness of the researchers pool targeting to propose innovative solutions to diminish the economical losses in form of fuel cost and trip time. In this chapter, first the default traffic light controlling strategy was simulated the tripe time of each vehicle has been recorded. And, also, provide comprehensive study of the results attained with a reconfigured traffic light controlling strategy on the open source traffic simulator SUMO (Simulation of Urban Mobility) by revamping its predefined static routes during the runtime of simulation. The projected reconfigured traffic light controlling strategy has been implemented and the obtained results on the basic SUMO have established high efficiency in defining reduction in commutation or tripe time.
Tarkeshwar Mahto; Hasmat Malik. Traffic Signal Control to Optimize Run Time for Energy Saving: A Smart City Paradigm. Metaheuristic and Evolutionary Computation: Algorithms and Applications 2020, 491 -497.
AMA StyleTarkeshwar Mahto, Hasmat Malik. Traffic Signal Control to Optimize Run Time for Energy Saving: A Smart City Paradigm. Metaheuristic and Evolutionary Computation: Algorithms and Applications. 2020; ():491-497.
Chicago/Turabian StyleTarkeshwar Mahto; Hasmat Malik. 2020. "Traffic Signal Control to Optimize Run Time for Energy Saving: A Smart City Paradigm." Metaheuristic and Evolutionary Computation: Algorithms and Applications , no. : 491-497.