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Wind power forecasting plays a key role in the design and maintenance of wind power generation which can directly help to enhance environment resilience. Offshore wind power forecasting has become more challenging due to their operation in a harsh and multi-faceted environment. In this paper, the data generated from offshore wind turbines are used for power forecasting purposes. First, fragmented data is filtered and Deep Auto-Encoding is used to select high dimensional features. Second, a mixture of the CNN and LSTM models is used to train prominent wind features and further improve forecasting accuracy. Finally, the CNN-LSTM deep learning hybrid model is fine-tuned with various parameters for reliable forecasting of wind energy on three different offshore Windfarms. A state-of-the-art comparison against existing models is presented based on root mean square error (RMSE) and mean absolute error (MAE) respectively. The forecasting analyses indicate that the proposed CNN-LSTM strategy is quite successful for offshore wind turbines by retaining the lowest RMSE and MAE along with high forecasting accuracy. The experimental findings will be helpful to design environment resilient energy transition pathways.
Mansoor Khan; Essam A. Al-Ammar; Muhammad Rashid Naeem; Wonsuk Ko; Hyeong-Jin Choi; Hyun-Koo Kang. Forecasting renewable energy for environmental resilience through computational intelligence. PLOS ONE 2021, 16, e0256381 .
AMA StyleMansoor Khan, Essam A. Al-Ammar, Muhammad Rashid Naeem, Wonsuk Ko, Hyeong-Jin Choi, Hyun-Koo Kang. Forecasting renewable energy for environmental resilience through computational intelligence. PLOS ONE. 2021; 16 (8):e0256381.
Chicago/Turabian StyleMansoor Khan; Essam A. Al-Ammar; Muhammad Rashid Naeem; Wonsuk Ko; Hyeong-Jin Choi; Hyun-Koo Kang. 2021. "Forecasting renewable energy for environmental resilience through computational intelligence." PLOS ONE 16, no. 8: e0256381.
Concerns related to current harmonics have gained increased attention in recent years due to technological advancement in power electronics and the proliferation of non-linear loads in power distribution system. It has become challenging to limit current total harmonic distortion (THD) at consumer end mainly due to increased penetration of intermittent switching based non-linear loads. Shunt active power filter (SAPF) is considered a marvelous power electronics device to tackle consumer side current harmonics. This paper presents a synchronous reference frame (SRF) based improved control method for compliant working of SAPF to reduce current harmonics in the distribution network with same and different THD levels in three phases. This research work investigates an effectual DC link voltage control technique linked with SRF based control of SAPF to effectively mitigate current harmonics. A fuzzy logic-based automatic switch (FLBAS) is designed according to the THD standards of IET and IEEE for real-time controlling of SRF based control of SAPF. In addition, S-plane stability analysis of the proposed control scheme is performed using the model of SAPF's inverter. It is established that the closed-loop system is asymptotically stable with the proposed control scheme. The presented simulation results validate the effectiveness of the proposed control technique for SAPF robustly.
Essam A. Al-Ammar; Azhar Ul Haq; Ahsan Iqbal; Wonsuk Ko; Marium Jalal; Muhammad Almas Anjum; Hyeong-Jin Choi; Hyun-Koo Kang. Synchronous Reference Frame Theory Based Intelligent Controller for Current THD Reduction. Journal of Electrical Engineering & Technology 2021, 1 -20.
AMA StyleEssam A. Al-Ammar, Azhar Ul Haq, Ahsan Iqbal, Wonsuk Ko, Marium Jalal, Muhammad Almas Anjum, Hyeong-Jin Choi, Hyun-Koo Kang. Synchronous Reference Frame Theory Based Intelligent Controller for Current THD Reduction. Journal of Electrical Engineering & Technology. 2021; ():1-20.
Chicago/Turabian StyleEssam A. Al-Ammar; Azhar Ul Haq; Ahsan Iqbal; Wonsuk Ko; Marium Jalal; Muhammad Almas Anjum; Hyeong-Jin Choi; Hyun-Koo Kang. 2021. "Synchronous Reference Frame Theory Based Intelligent Controller for Current THD Reduction." Journal of Electrical Engineering & Technology , no. : 1-20.
In this study, optimal decision-making process in photovoltaic (PV) system location selection in Saudi Arabia is described. First, to identify the criteria that influence the decision of selecting a suitable location for the PV system, the geographical information system (GIS)-based multi-criteria decision making (MCDM) approach is used. Next, to assess the weights of the criteria that present different aspects of the investigated locations, four major criteria and 11 sub-criteria are proposed, and analytic hierarchy process (AHP) is applied to develop comparison decision matrix. Finally, the order preference by similarity to ideal solution (TOPSIS) technique evaluates and classifies 17 cities (such as Riyadh, Jeddah) in Saudi Arabia. The result shows that Tabuk city in the northern of Saudi Arabia is the best location. Among the 17 cities, the performance score of seven cities is above or equal 80%, and Tabuk city has the highest score with 87%. This analytical approach could contribute as an early planning to locate suitable sites for the selection of PV system region in Saudi Arabia.
Sultan Al-Shammari; Wonsuk Ko; Essam A. Al Ammar; Majed A. Alotaibi; Hyeong-Jin Choi. Optimal Decision-Making in Photovoltaic System Selection in Saudi Arabia. Energies 2021, 14, 357 .
AMA StyleSultan Al-Shammari, Wonsuk Ko, Essam A. Al Ammar, Majed A. Alotaibi, Hyeong-Jin Choi. Optimal Decision-Making in Photovoltaic System Selection in Saudi Arabia. Energies. 2021; 14 (2):357.
Chicago/Turabian StyleSultan Al-Shammari; Wonsuk Ko; Essam A. Al Ammar; Majed A. Alotaibi; Hyeong-Jin Choi. 2021. "Optimal Decision-Making in Photovoltaic System Selection in Saudi Arabia." Energies 14, no. 2: 357.
In this article, a combined feedback-feedforward control design scheme is presented to enhance the tracking performance of a piezo-actuated micropositioning stage by compensating the nonlinear hysteretic behavior of the piezoelectric actuator and model uncertainties of the system. Detailed investigation of the presented control scheme is performed not only in simulation by analyzing the robust stability and robust performance but also in real-time with motion trajectories of multiple frequencies. To design the presented control scheme, first of all, the dynamic model of the system is identified from the real-time experimental data by using the recursive least squares parameter adaptation algorithm. Then, Dahl hysteresis model is considered to represent the nonlinear hysteretic behavior of the piezoelectric actuator. To deal with this hysteresis nonlinearity, Dahl feedforward compensator is designed without involving inverse model calculations to avoid any computational complexity. This feedforward compensator is then combined with
Irfan Ahmad; Mahmoud A. Ali; Wonsuk Ko. Robust μ-Synthesis With Dahl Model Based Feedforward Compensator Design for Piezo-Actuated Micropositioning Stage. IEEE Access 2020, 8, 141799 -141813.
AMA StyleIrfan Ahmad, Mahmoud A. Ali, Wonsuk Ko. Robust μ-Synthesis With Dahl Model Based Feedforward Compensator Design for Piezo-Actuated Micropositioning Stage. IEEE Access. 2020; 8 ():141799-141813.
Chicago/Turabian StyleIrfan Ahmad; Mahmoud A. Ali; Wonsuk Ko. 2020. "Robust μ-Synthesis With Dahl Model Based Feedforward Compensator Design for Piezo-Actuated Micropositioning Stage." IEEE Access 8, no. : 141799-141813.
Shunt capacitor banks (SCBs) are used in distribution systems for loss reduction, voltage stability improvement for the system nodes, and system capacity release. However, the size of these capacitors and their placement locations are design factors that have been considered as single or multi-objectives to derive maximum benefits from their installation. To find the optimal location and size of the SCBs, this study proposes the application of multi-objective salp swarm algorithms, considered at ambient temperature, in radial distribution systems. Additionally, a fuzzy-based mechanism has been utilized to identify the best-fit solution of three different objective functions. The proposed method is implemented on IEEE 15-bus and 33-bus radial distribution systems, as well as on real data taken from the Saudi Electricity Company. The results indicate improved effectiveness and higher capability of the proposed method.
Essam A. Al-Ammar; Ghazi A. Ghazi; Wonsuk Ko; Yasin Khan; Abderrahmane Beroual; Junhee Hong; Seung-Ho Song. Comprehensive impact analysis of ambient temperature on multi-objective capacitor placements in a radial distribution system. Ain Shams Engineering Journal 2020, 12, 717 -727.
AMA StyleEssam A. Al-Ammar, Ghazi A. Ghazi, Wonsuk Ko, Yasin Khan, Abderrahmane Beroual, Junhee Hong, Seung-Ho Song. Comprehensive impact analysis of ambient temperature on multi-objective capacitor placements in a radial distribution system. Ain Shams Engineering Journal. 2020; 12 (1):717-727.
Chicago/Turabian StyleEssam A. Al-Ammar; Ghazi A. Ghazi; Wonsuk Ko; Yasin Khan; Abderrahmane Beroual; Junhee Hong; Seung-Ho Song. 2020. "Comprehensive impact analysis of ambient temperature on multi-objective capacitor placements in a radial distribution system." Ain Shams Engineering Journal 12, no. 1: 717-727.
Within the next decade, the number of electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) will increase exponentially owing to the environmental benefits related to their utilization. In an ideal framework condition, the vehicle-to-grid (V2G) system provides advantages such as subordinate administration of load leveling and peak shaving guidelines, and minimized upgrade costs. In this paper, deterministic and probabilistic methods of scheduling PHEV charging/discharging are analyzed, and their performances are compared based on a case study. In the case of the deterministic method, an optimization model is proposed to reduce the overall grid output power consumption for utilities and operate a smart charging/discharging schedule for PHEV users. Quadratic programming (QP) is used to solve the optimization cost function. In contrast, the probabilistic method uses Monte Carlo simulation (MCS) to analyze the impact and determine a coordinated time-of-use (TOU) structure for the PHEV charging/discharging schedule. Both methods suggest V2G feasibility for the smart grid system.
Mohammad Mominur Rahman; Essam A. Al-Ammar; Himadry Shekhar Das; Wonsuk Ko. Comprehensive impact analysis of electric vehicle charging scheduling on load-duration curve. Computers & Electrical Engineering 2020, 85, 106673 .
AMA StyleMohammad Mominur Rahman, Essam A. Al-Ammar, Himadry Shekhar Das, Wonsuk Ko. Comprehensive impact analysis of electric vehicle charging scheduling on load-duration curve. Computers & Electrical Engineering. 2020; 85 ():106673.
Chicago/Turabian StyleMohammad Mominur Rahman; Essam A. Al-Ammar; Himadry Shekhar Das; Wonsuk Ko. 2020. "Comprehensive impact analysis of electric vehicle charging scheduling on load-duration curve." Computers & Electrical Engineering 85, no. : 106673.
There is a significant progress in the development of brain-controlled mobile robots and robotic arms in the recent years. New advances in electroencephalography (EEG) technology have led to the possibility of controlling external devices, such as robots, directly via the brain. The development of brain-controlled robotic devices has allowed people with bodily disabilities to enhance their mobility, individuality, and many types of activity. This paper provides a comprehensive review of EEG signal processing in robot control, including mobile robots and robotic arms, especially based on noninvasive brain computer interface systems. Various filtering approaches, feature extraction techniques, and machine learning algorithms for EEG classification are discussed and summarized. Finally, the conditions of the environments in which robots are used and robot types are also discussed.
Majid Aljalal; Sutrisno Ibrahim; Ridha Djemal; Wonsuk Ko. Comprehensive review on brain-controlled mobile robots and robotic arms based on electroencephalography signals. Intelligent Service Robotics 2020, 13, 539 -563.
AMA StyleMajid Aljalal, Sutrisno Ibrahim, Ridha Djemal, Wonsuk Ko. Comprehensive review on brain-controlled mobile robots and robotic arms based on electroencephalography signals. Intelligent Service Robotics. 2020; 13 (4):539-563.
Chicago/Turabian StyleMajid Aljalal; Sutrisno Ibrahim; Ridha Djemal; Wonsuk Ko. 2020. "Comprehensive review on brain-controlled mobile robots and robotic arms based on electroencephalography signals." Intelligent Service Robotics 13, no. 4: 539-563.
In this paper, we show the development of a demand-side management solution (DSMS) for demand response (DR) aggregator and actual demand response operation cases in South Korea. To show an experience, Korea’s demand response market outline, functions of DSMS, real contracted capacity, and payment between consumer and load aggregator and DR operation cases are revealed. The DSMS computes the customer baseline load (CBL), relative root mean squared error (RRMSE), and payments of the customers in real time. The case of 10 MW contracted customers shows 108.03% delivery rate and a benefit of 854,900,394 KRW for two years. The results illustrate that an integrated demand-side management solution contributes by participating in a DR market and gives a benefit and satisfaction to the consumer.
Wonsuk Ko; Hamsakutty Vettikalladi; Seung-Ho Song; Hyeong-Jin Choi. Implementation of a Demand-Side Management Solution for South Korea’s Demand Response Program. Applied Sciences 2020, 10, 1751 .
AMA StyleWonsuk Ko, Hamsakutty Vettikalladi, Seung-Ho Song, Hyeong-Jin Choi. Implementation of a Demand-Side Management Solution for South Korea’s Demand Response Program. Applied Sciences. 2020; 10 (5):1751.
Chicago/Turabian StyleWonsuk Ko; Hamsakutty Vettikalladi; Seung-Ho Song; Hyeong-Jin Choi. 2020. "Implementation of a Demand-Side Management Solution for South Korea’s Demand Response Program." Applied Sciences 10, no. 5: 1751.
Microgrids being an important entity in the distribution system, and to get their full advantages by incorporating maximum distributed generation, standalone hybrid renewable energy systems (HRESs), being environmentally-safe and economically-efficient, are considered as the promising solution to electrify remote areas where the grid power is not available. In this work, a techno-economic investigation with an optimal design of HRES is presented to fulfill the domestic electricity need for a residential area of the Sherani district in the Province of Baluchistan, Pakistan. Nine case studies based on PV/wind/diesel/battery are analyzed based on net present cost (NPC), cost of energy (COE), and emission to decide the feasible solution. HOMER tool is utilized to accomplish modeling and simulation for economic analysis and optimal sizing. Simulation results demonstrated that HRES with PV-wind-battery is the most viable option for the specified area, and the optimal sizing of components are also obtained with $ 28,620 NPC and 0.311 $/kWh COE which shows 81.65% reduction in cost and 100% preserving in toxic emission while fulfilling 100% energy demand with 67.3% of excess energy. Furthermore, MATLAB/Simulink modeling for the optimally designed system is built for technical analysis while its effectiveness is proved by keeping dc and ac buses voltage constant, safe operating range of battery state of charge (SOC) with active power balance between HRES components, as well as efficient ac voltage quality, regardless of generation disturbances and load fluctuations. The output signal has total harmonic distortion (THD) of 0.30% as compared to 5.44% with the conventional control scheme. The novelty lies in the sequential application of both HOMER and MATLAB simulations of the proposed HRES model and validation of the proposition for the studied area; by using and implementing model predictive control (MPC) of a reconfigurable inverter.
Essam A. Al-Ammar; Habib Ur Rahman Habib; Kotb M. Kotb; Shaorong Wang; Wonsuk Ko; Mahmoud F. Elmorshedy; Asad Waqar. Residential Community Load Management Based on Optimal Design of Standalone HRES With Model Predictive Control. IEEE Access 2020, 8, 12542 -12572.
AMA StyleEssam A. Al-Ammar, Habib Ur Rahman Habib, Kotb M. Kotb, Shaorong Wang, Wonsuk Ko, Mahmoud F. Elmorshedy, Asad Waqar. Residential Community Load Management Based on Optimal Design of Standalone HRES With Model Predictive Control. IEEE Access. 2020; 8 (99):12542-12572.
Chicago/Turabian StyleEssam A. Al-Ammar; Habib Ur Rahman Habib; Kotb M. Kotb; Shaorong Wang; Wonsuk Ko; Mahmoud F. Elmorshedy; Asad Waqar. 2020. "Residential Community Load Management Based on Optimal Design of Standalone HRES With Model Predictive Control." IEEE Access 8, no. 99: 12542-12572.
Feed-in tariff (FIT) is the most commonly used strategy worldwide for promoting renewable energy. The FIT strategy mainly consists of three key elements—certain admission to the grid, long-term contracts (10 to 20 years), and reimbursement levels that are founded on the prices of renewable energy production. The most common renewable energy in the Kingdom of Saudi Arabia (KSA) is solar energy, and it can be incorporated into the main grid through a favorable feed-in tariff that will attract investment. This paper aims to review the FIT rates in Germany and the United States, then the design of FIT in these countries to study the results, which helps to determine the most appropriate FIT in the KSA for different regions with regard to investment costs, household electricity consumption, compatibility with the existing grid, period required for return on assets, and long-term benefits. This study will also explain the importance of interest rates for residential investors and the challenge created by the recent tariff increase to 0.18 SAR/kWh. Saudi Arabia has the advantage of being able to use this information to assess the best approach to the economic and environmental impacts of FIT.
Wonsuk Ko; Essam Al-Ammar; Mohammad Almahmeed. Development of Feed-in Tariff for PV in the Kingdom of Saudi Arabia. Energies 2019, 12, 2898 .
AMA StyleWonsuk Ko, Essam Al-Ammar, Mohammad Almahmeed. Development of Feed-in Tariff for PV in the Kingdom of Saudi Arabia. Energies. 2019; 12 (15):2898.
Chicago/Turabian StyleWonsuk Ko; Essam Al-Ammar; Mohammad Almahmeed. 2019. "Development of Feed-in Tariff for PV in the Kingdom of Saudi Arabia." Energies 12, no. 15: 2898.
In electrical distribution systems, shunt capacitors are installed in order to reduce system losses, to enhance the voltage profile, and to free up system capacity. Nevertheless, the installation of shunt capacitors in distribution systems with distorted waveforms will magnify the distortion level of harmonics if they are not set at appropriate locations relative to the harmonics. This paper proposes a hybrid method to determine the placement and sizing of shunt capacitors in distorted radial distribution systems, taking into account the presence of harmonic distortion with consideration of ambient temperature effects, (this technique consists of the fuzzy expert system approach and the Genetic Algorithm method). This hybrid technique is applied to an IEEE 34-bus radial standard distribution system as well as a real distribution system in the Saudi Electricity Company. The simulation results show that harmonic distortion considerably reduces and the efficiency of distribution systems increases with a reduction in power loss and enhancement of voltage regulation.
Essam A. Al-Ammar; Ghazi A. Ghazi; Wonsuk Ko. Impact of Ambient Temperature on Shunt Capacitor Placement in a Distorted Radial Distribution System. Energies 2018, 11, 1585 .
AMA StyleEssam A. Al-Ammar, Ghazi A. Ghazi, Wonsuk Ko. Impact of Ambient Temperature on Shunt Capacitor Placement in a Distorted Radial Distribution System. Energies. 2018; 11 (6):1585.
Chicago/Turabian StyleEssam A. Al-Ammar; Ghazi A. Ghazi; Wonsuk Ko. 2018. "Impact of Ambient Temperature on Shunt Capacitor Placement in a Distorted Radial Distribution System." Energies 11, no. 6: 1585.