Journal of Electrical Systems and Information Technology
EISSN : 2314-7172
Published by: Springer Science and Business Media LLC (10.1186)
Total articles ≅ 36
Latest articles in this journal
Published: 15 June 2021
Journal of Electrical Systems and Information Technology, Volume 8, pp 1-1; doi:10.1186/s43067-021-00037-8
Following publication of the original article , the authors reported an error in the title and body text.
Published: 19 May 2021
Journal of Electrical Systems and Information Technology, Volume 8, pp 1-22; doi:10.1186/s43067-021-00035-w
This paper presents the impact of optimal location and sizing of renewable and non-renewable-based distributed generators in the AC/DC micro-grid system using the latest optimizer called butterfly optimization algorithm with an aim to minimize power loss. Generally, hybrid AC/DC micro-grids systems are modeled by separating AC and DC feeders with the help of high-power converters (HPC).AC grids sustained by substation and DC grids are maintained by their individual DG units. While planning of DGs in the hybrid AC/DC systems, the power loss incurred by HPCs is not considered avoiding complexity by many authors. In this paper, the sizing of DGs is determined by the operational area required by the type of DG technology as one variable and all possible candidate buses in the respective zones of AC/DC micro-grid system are another variable with due consideration of HPC losses in AC/DC micro-grid system. A hybrid AC/DC MG system is developed by classifying the existing benchmark 33-bus and 69-bus radial distribution systems into various AC/DC zones. To evaluate the proposed approach, it is implemented on aforementioned micro-grid systems and the obtained results are verified with other existing approaches in the literature. The results proved that the proposed approach is better than the other approaches in technical aspects.
Published: 1 May 2021
Journal of Electrical Systems and Information Technology, Volume 8, pp 1-15; doi:10.1186/s43067-021-00036-9
An improvement of the traditional grey system model, GM(1,1), to enhance forecast accuracy, has been realized using the particle swarm optimization (PSO) algorithm. Unlike the GM(1,1) which uses a fixed adjacent neighbor weight for all data sets, the proposed PSO-improved model, PSO-GM(1,1), determines an optimal adjacent neighbor weight, based on the presented data set. This optimal adjacent neighbor weight so determined is the principal factor that enhances forecast accuracy. The performance of the proposed model was evaluated using generated monotonic increasing and decreasing data sets as well as measured energy consumption data for a laptop computer, desktop computer, printer, and photocopier. The performance of PSO-GM(1,1) was compared with that of GM(1,1), and two other models in literature that sought to improve the performance of GM(1,1). The PSO-GM(1,1) outperformed the traditional model and the two other models. For the monotonic increasing data, the mean absolute percentage error (MAPE) for the proposed model was 0.007% as against a MAPE value of 20.383% for the GM(1,1). For the monotonic decreasing data, the PSO-GM(1,1) again outperformed GM(1,1), yielding a MAPE of 0.057% compared to a value of 13.407% for the traditional model. For the measured laptop computer energy data, the obtained MAPE for the PSO-GM(1,1) was 0.675% while the values for the two models were 4.052% and 2.991%. For the measured desktop computer energy data, the obtained MAPE for the PSO-GM(1,1) was 0.0018% while the values for the two models were 0.0018% and 1.163%. For the data associated with the printer, the MAPEs were 8.414% for the PSO-GM(1,1), 20.957% for the first model and 9.080% for the second model. For the measured photocopier energy data, the obtained MAPE for the PSO-GM(1,1) was 0.901% while the values for the two models were 3.799% and 0.943%. Thus, the proposed PSO-GM(1,1) greatly improves forecast accuracy and is recommended for adoption, for forecasting.
Published: 1 April 2021
Journal of Electrical Systems and Information Technology, Volume 8, pp 1-21; doi:10.1186/s43067-021-00033-y
In the current situation, operation and control of power system is a greater challenge. The most significant situation in power system control is load frequency control. In the present work, a hybrid differential evolution and pattern search (hDE-PS) method has been suggested for frequency regulation of electrical power systems. Fractional-order proportional integral derivative (FOPID) controller is implemented for design and analysis purpose. The suggested control method has been applied for two electrical power systems model, i.e., 2-area diverse source power system with/without HVDC linkage and 2-area thermal system. The performances of the suggested controller have been evaluated with PID and optimal controller. The simulation results indicate that system performances are enhanced with the suggested approach for identical structure. Robustness of the suggested approach has been analyzed by variation in random load and the system parameters. The suggested method (hDE-PS tuned FOPID) is further investigated with a 2-area thermal system. The performance of the recommended approach is analyzed by equating the results with other newly available approaches, like Genetic Algorithm (GA), Bacteria Foraging Optimization Algorithm (BFOA), Particle Swarm Optimization (PSO), hybrid BFOA and PSO (hBFOA-PSO), multi-objective Non-dominated Sorting Genetic Algorithm (NSGA)-II and Firefly Algorithm for the similar structure.
Published: 29 March 2021
Journal of Electrical Systems and Information Technology, Volume 8, pp 1-10; doi:10.1186/s43067-021-00028-9
Power line communication technology is a retrofit alternative technology for last mile information technology. Despite several challenges, such as inadequate standards and electromagnetic compatibility, it is maturing. In this review, we have analysed these obstacles and its current application status.
Published: 29 March 2021
Journal of Electrical Systems and Information Technology, Volume 8, pp 1-43; doi:10.1186/s43067-021-00032-z
An advanced hybrid algorithm (haDEPSO) is proposed in this paper for small- and large-scale engineering design optimization problems. Suggested advanced, differential evolution (aDE) and particle swarm optimization (aPSO) integrated with proposed haDEPSO. In aDE a novel, mutation, crossover and selection strategy is introduced, to avoid premature convergence. And aPSO consists of novel gradually varying parameters, to escape stagnation. So, convergence characteristic of aDE and aPSO provides different approximation to the solution space. Thus, haDEPSO achieve better solutions due to integrating merits of aDE and aPSO. Also in haDEPSO individual population is merged with other in a pre-defined manner, to balance between global and local search capability. The performance of proposed haDEPSO and its component aDE and aPSO are validated on 23 unconstrained benchmark functions, then solved five small (structural engineering) and one large (economic load dispatch)-scale engineering design optimization problems. Outcome analyses confirm superiority of proposed algorithms over many state-of-the-art algorithms.
Published: 25 March 2021
Journal of Electrical Systems and Information Technology, Volume 8, pp 1-18; doi:10.1186/s43067-021-00031-0
This paper presents an improved load flow technique for a modern distribution system. The proposed load flow technique is derived from the concept of the conventional backward/forward sweep technique. The proposed technique uses linear equations based on Kirchhoff’s laws without involving matrix multiplication. The method can accommodate changes in network structure reconfiguration by involving the parent–children relationship between nodes to avoid complex renumbering of branches and nodes. The IEEE 15 bus, IEEE 33 bus and IEEE 69 bus systems were used for testing the efficacy of the proposed technique. The meshed IEEE 15 bus system was used to demonstrate the efficacy of the proposed technique under network reconfiguration scenarios. The proposed method was compared with other load flow approaches, including CIM, BFS and DLF. The results revealed that the proposed method could provide similar power flow solutions with the added advantage that it can work well under network reconfiguration without performing node renumbering, not covered by others. The proposed technique was then applied in Tanzania electric secondary distribution network and performed well.
Published: 25 March 2021
Journal of Electrical Systems and Information Technology, Volume 8, pp 1-17; doi:10.1186/s43067-021-00034-x
The work presented herein is focusing on mitigating sub-synchronous-resonance (SSR) oscillatory torque and speed responses developed in power network equipped with series capacitor compensation as an outcome of the network perturbations. The mitigation effect of a battery-energy-storage (BES) controlled via a fuzzy-logic-controller (FLC) is explored. It is also explored accompanied by a fuzzy-bases resistor brake controlled via FLC. The IEEE second benchmark system is selected as a test grid under the MATLAB™/Simulink simulation environment. The signal utilized for the propositioned controller is the alternator rotor speed deviation. The key conclusions of this investigation are the employment of a BES in the discharging mode alone might be utilized to alleviate the SSR relative speed, and torque oscillations, the BES employment accompanied with dynamic resistive brake is supplying faster-decaying rates for the SSR oscillations in observation with the BES employment only.
Published: 23 March 2021
Journal of Electrical Systems and Information Technology, Volume 8, pp 1-24; doi:10.1186/s43067-021-00030-1
This paper presents a methodology for voltage and frequency (V–f) control of a standalone wind-driven self-excited reluctance generator (WDSERG). The methodology is based on proposing two different compensation configurations using two switching capacitors (short-shunt and long-shunt compensation) for (V–f) control. The dynamic and steady-state performances of the two configurations are discussed under different operating conditions: wind speeds, load currents and power factors. This analysis is done by developing a complete dynamic model of WDSERG including the excitation capacitors and load. Therefore, complete equivalent circuits are proposed. The values of capacitors are controlled by adjusting the duty cycle of H-bridge circuits with PI controllers. To validate the proposed configurations and their dynamic models and equivalent circuits, simulation results for a 1.5-kW standalone WDSERG and experimental results for 0.2 kW reluctance generator driven by a DC motor, emulating the wind turbine, are carried out. The results show a significant enhancement in voltage and frequency regulation with the selected optimal capacitances for each configuration; however, short-shunt compensation is the preferred configuration as it controls the output voltage and frequency with minimum values of capacitances and minimum required duty variation.
Published: 3 March 2021
Journal of Electrical Systems and Information Technology, Volume 8, pp 1-73; doi:10.1186/s43067-020-00026-3
Conventional unit commitment problem (UCP) consists of thermal generating units and its participation schedule, which is a stimulating and significant responsibility of assigning produced electricity among the committed generating units matter to frequent limitations over a scheduled period view to achieve the least price of power generation. However, modern power system consists of various integrated power generating units including nuclear, thermal, hydro, solar and wind. The scheduling of these generating units in optimal condition is a tedious task and involves lot of uncertainty constraints due to time carrying weather conditions. This difficulties come to be too difficult by growing the scope of electrical power sector day by day, so that UCP has connection with problem in the field of optimization, it has both continuous and binary variables which is the furthermost exciting problem that needs to be solved. In the proposed research, a newly created optimizer, i.e., Harris Hawks optimizer (HHO), has been hybridized with sine–cosine algorithm (SCA) using memetic algorithm approach and named as meliorated Harris Hawks optimizer and it is applied to solve the photovoltaic constrained UCP of electric power system. In this research paper, sine–cosine Algorithm is used for provision of power generation (generating units which contribute in electric power generation for upload) and economic load dispatch (ELD) is completed by Harris Hawks optimizer. The feasibility and efficacy of operation of the hybrid algorithm are verified for small, medium power systems and large system considering renewable energy sources in summer and winter, and the percentage of cost saving for power generation is found. The results for 4 generating units, 5 generating units, 6 generating units, 7 generating units, 10 generating units, 19 generating units, 20 generating units, 40 generating units and 60 generating units are evaluated. The 10 generating units are evaluated with 5% and 10% spinning reserve. The efficacy of the offered optimizer has been verified for several standard benchmark problem including unit commitment problem, and it has been observed that the suggested optimizer is too effective to solve continuous, discrete and nonlinear optimization problems.