Journal Description
Electricity
Electricity
is an international, peer-reviewed, open access journal on electrical engineering published quarterly online by MDPI.
- Open Access—free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within ESCI (Web of Science), Scopus, EBSCO and other databases.
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 27.2 days after submission; acceptance to publication is undertaken in 5.9 days (median values for papers published in this journal in the first half of 2024).
- Journal Rank: CiteScore - Q2 (Electrical and Electronic Engineering)
- Recognition of Reviewers: APC discount vouchers, optional signed peer review, and reviewer names published annually.
- Extra Benefits: no space constraints, no color charges.
Latest Articles
Utilizing Soft Open Points for Effective Voltage Management in Multi-Microgrid Distribution Systems
Electricity 2024, 5(4), 1008-1021; https://doi.org/10.3390/electricity5040051 - 6 Dec 2024
Abstract
To enhance stability and reliability, multi-microgrid systems have been developed as replacements for conventional distribution networks. Traditionally, switches have been used to interconnect these microgrids, but this approach often results in uncoordinated power sharing, leading to economic inefficiencies and technical challenges such as
[...] Read more.
To enhance stability and reliability, multi-microgrid systems have been developed as replacements for conventional distribution networks. Traditionally, switches have been used to interconnect these microgrids, but this approach often results in uncoordinated power sharing, leading to economic inefficiencies and technical challenges such as voltage fluctuations, delay in response, etc. This research, in turn, introduces a novel multi-microgrid system that utilizes advanced electronic devices known as soft open points (SOPs) to enable effective voltage management and controllable power sharing between microgrids while also providing reactive power support. To account for uncertainties in the system, the two-point estimate method (2PEM) is applied. Simulation results on an IEEE 33-bus network with high renewable energy penetration reveal that the proposed SOP-based system significantly outperforms the traditional switch-based method, with a minimum voltage level of 0.98 p.u., compared to 0.93 p.u. in the conventional approach. These findings demonstrate the advantages of using SOPs for voltage management in forming multi-microgrid systems.
Full article
(This article belongs to the Special Issue Advances in Operation, Optimization, and Control of Smart Grids)
►
Show Figures
Open AccessArticle
A New Method to Assess the Reliability and Security of Urban Electrical Substations
by
Jorge Silva-Ortega, Jesús Ortíz and John E. Candelo-Becerra
Electricity 2024, 5(4), 991-1007; https://doi.org/10.3390/electricity5040050 - 5 Dec 2024
Abstract
►▼
Show Figures
This paper presents the application of quantitative and qualitative methods to assess reliability and security in urban electrical substations. The method is a visual technique based on a conceptual analysis of the different substation configurations. We also performed a sensitivity analysis considering the
[...] Read more.
This paper presents the application of quantitative and qualitative methods to assess reliability and security in urban electrical substations. The method is a visual technique based on a conceptual analysis of the different substation configurations. We also performed a sensitivity analysis considering the effects of connecting and disconnecting various elements of a power system. The procedure considers evaluating the loadability levels of transformers, buses, and lines, as well as the current state of the individual elements and the number of connected elements. A new index was proposed for urban electrical substations, evaluating the non-attended demand risk. The technique was tested in a power system case study with a meshed subtransmission network and distribution circuits to supply power to the loads. The results showed that the proposed method is a useful qualitative method to obtain a quantitative description of the system during operation in critical cases and the non-attended demand risk. In addition, 30% of the electrical substations showed low reliability indicators for critical cases such as failures in transformers that connect different internal configurations. These findings could be of interest for utilities and operators, as this document provides a simplified and graphic method that can integrate components such as configurations, non-attended demand risk, and loadability indicators as key parameters to identify critical points that affect the reliability and security of power systems. The case study showed that the electrical substations with the highest non-attention demand risk, around 50%, were those with single- and double-bar configurations in their respective switchyards. On the other hand, the substations with the lowest risk of unmet demand, equal to or less than 20%, were electrical substations with a double-bar + bypass switch configuration, a double-bar and ring configuration in the 110 kV switchyard, and a single-bar configuration in the 13.8 kV switchyard. This study showed that those substations that had couplings had a higher probability of withstanding contingencies.
Full article
Figure 1
Open AccessArticle
Energy Management Strategy for Hybrid Electric Vehicles Based on Adaptive Equivalent Ratio-Model Predictive Control
by
Farah Mahdi Ali and Nizar Hadi Abbas
Electricity 2024, 5(4), 972-990; https://doi.org/10.3390/electricity5040049 - 3 Dec 2024
Abstract
►▼
Show Figures
The research and development of hybrid electric vehicles has become a significant goal for large automotive manufacturers. The hybrid electric vehicle integrates a conventional engine and one or more electric motors powered by a battery, offering better fuel economy and lowering exhaust emissions.
[...] Read more.
The research and development of hybrid electric vehicles has become a significant goal for large automotive manufacturers. The hybrid electric vehicle integrates a conventional engine and one or more electric motors powered by a battery, offering better fuel economy and lowering exhaust emissions. This paper develops an optimal energy management algorithm based on Model Predictive Control that can produce optimal control parameters for power distribution between the battery unit and generator. The energy management strategy adapts this optimal power distribution by adjusting the objective function equivalent parameter of the controller according to changes in driving conditions. Dynamic programming is utilized offline to find the reference state of charge of the battery and used as the reference trajectory of our proposed strategy. Simulation results using different driving cycles show that the proposed method has better power distribution compared with two other strategies. The final state of charge reached a higher level, and the energy-saving percentage rose compared to the conventional algorithm.
Full article
Figure 1
Open AccessArticle
Transient Stability-Based Fast Power System Contingency Screening and Ranking
by
Teshome Lindi Kumissa and Fekadu Shewarega
Electricity 2024, 5(4), 947-971; https://doi.org/10.3390/electricity5040048 - 25 Nov 2024
Abstract
Today’s power systems are operated closer to their stability limits due to the continuously growing load demands, interface to open markets, and integration of more renewable energies. In order to provide operators with clear insight on the current system situation, near real-time power
[...] Read more.
Today’s power systems are operated closer to their stability limits due to the continuously growing load demands, interface to open markets, and integration of more renewable energies. In order to provide operators with clear insight on the current system situation, near real-time power systems dynamic security assessment tools are required. One of the core elements of near real-time dynamic security assessment tools is contingency screening and ranking. Most of the commercially available tools screen and rank contingencies by using the traditional numerical integration or Transient Energy Functions (TEFs) or hybrid methods. The traditional numerical integration method is accurate but computationally intensive and has a slow assessment speed which makes it difficult to identify any insecure contingency before it happens. Despite the TEF method of transient stability analysis being relatively fast, it develops less accurate results due to models simplification and assumptions. This paper introduces transient stability based on fast and robust contingency screening and ranking using an Adaptive step-size Differential Transformation (AsDTM) method. Based on the most current snapshot from Supervisory Control and Data Accusation (SCADA) data, the proposed method triggers AsDTM-based transient stability simulation for each credible contingency and evaluates Transient Stability Indices (TSI) as the normalized weighted sum of squares of errors derived from state variables and complex bus voltages at every simulation time step. Finally, contingencies are ranked based on these TSI and the worst contingency is identified for the next detail assessment. The method is tested on IEEE 9 bus and 39 bus test systems. Test results reveal that the proposed method is faster, robust, and can be used in near real-time dynamic security assessment sessions.
Full article
(This article belongs to the Special Issue Advances in Operation, Optimization, and Control of Smart Grids)
►▼
Show Figures
Figure 1
Open AccessArticle
Combined Power Generating Complex and Energy Storage System
by
Rollan Nussipali, Nikita V. Martyushev, Boris V. Malozyomov, Vladimir Yu. Konyukhov, Tatiana A. Oparina, Victoria V. Romanova and Roman V. Kononenko
Electricity 2024, 5(4), 931-946; https://doi.org/10.3390/electricity5040047 - 21 Nov 2024
Abstract
Combining wind and hydropower facilities makes it possible to solve the problems caused by power supply shortages in areas that are remote from the central energy system. Hydropower plants and highly manoeuvrable hydroelectric units successfully compensate for the uneven power outputs from wind
[...] Read more.
Combining wind and hydropower facilities makes it possible to solve the problems caused by power supply shortages in areas that are remote from the central energy system. Hydropower plants and highly manoeuvrable hydroelectric units successfully compensate for the uneven power outputs from wind power plants, and the limitations associated with them are significantly reduced when they are integrated into the regional energy system. Such an integration contributes to increasing the efficiency of renewable energy sources, which in turn reduces our dependence on fossil resources and decreases their harmful impact on the environment, increasing the stability of the power supply to consumers. The results of optimisation calculations show that a consumer load security of 95% allows the set capacity of RESs to be used in the energy complex up to 700 MW. It is shown here that the joint operation of HPPs and WPPs as part of a power complex and hydraulic energy storage allows for the creation of a stable power supply system that can operate even in conditions of variable wind force or uneven water flow. The conclusions obtained allow us to say that the combination of hydro- and wind power facilities makes it possible to solve the problem of power supply deficits in the regions of Kazakhstan that are remote from the central power station. At the same time, hydroelectric power plants and highly manoeuvrable hydroelectric units successfully compensate for the uneven power output from wind power plants and significantly reduce the limitations associated with them during their integration into the regional energy system.
Full article
(This article belongs to the Special Issue Recent Advances in Power and Smart Grids)
►▼
Show Figures
Figure 1
Open AccessArticle
The Total Cost of Reliable Electricity Distribution
by
Joel Seppälä, Joonas Kari and Pertti Järventausta
Electricity 2024, 5(4), 916-930; https://doi.org/10.3390/electricity5040046 - 21 Nov 2024
Abstract
Clean transition increases the demand for reliable electricity distribution, but while the capacity can be improved through investments, responding to the demand increases costs for the customers. This study presents a methodological improvement to the assessment of the reasonability of pricing, by comprehensively
[...] Read more.
Clean transition increases the demand for reliable electricity distribution, but while the capacity can be improved through investments, responding to the demand increases costs for the customers. This study presents a methodological improvement to the assessment of the reasonability of pricing, by comprehensively analyzing pricing regulation data to define the total cost of electricity distribution by clustering. A novel systematic view on the volume and distribution of economic steering shows that according to the regulation data in Finland, the total annual cost of distribution for the present level of reliability varies from EUR 490/a in an urban environment to EUR 1220/a per customer in sparsely populated areas. The majority of the total costs of distribution stem from actual utility expenses. The approach and results may be used for implementing TOTEX models for future pricing regulation.
Full article
(This article belongs to the Special Issue Feature Papers to Celebrate the ESCI Coverage)
►▼
Show Figures
Figure 1
Open AccessArticle
Parameter Tuning Method for a Lattice Compensated Wireless Power Transfer System
by
Ebrahim Nasr Esfahani and Indranil Bhattacharya
Electricity 2024, 5(4), 895-915; https://doi.org/10.3390/electricity5040045 - 21 Nov 2024
Abstract
►▼
Show Figures
This study presents a new charging system with lattice compensation for wireless power transfer (WPT) applications. A mathematical model is developed for the proposed system to accurately estimate power transfer capabilities. Furthermore, a linear programming algorithm is used to find the proper values
[...] Read more.
This study presents a new charging system with lattice compensation for wireless power transfer (WPT) applications. A mathematical model is developed for the proposed system to accurately estimate power transfer capabilities. Furthermore, a linear programming algorithm is used to find the proper values for lattice compensation, which helps achieve high efficiency over a wide range of loads and zero voltage switching (ZVS) for the proposed system. The approach is validated through analysis, modeling, and simulation of a 3-kilowatt WPT system. Additionally, a 200-watt prototype with a 100 mm air gap was built and tested, showing an efficiency of 86.3% during charging. This method eliminates the need for an auxiliary DC–DC converter, ensuring efficient charging across various load conditions. The prototype’s performance closely matches the simulation results, indicating its potential for scaling up to electric vehicle (EV) battery charging applications.
Full article
Figure 1
Open AccessArticle
Quadratic Boost Converter with Optimized Switching Ripple Based on the Selection of Passive Components
by
Edgar D. Silva-Vera, Julio C. Rosas-Caro, Jesus E. Valdez-Resendiz, Avelina Alejo-Reyes, Omar F. Ruiz-Martinez, Johnny Posada Contreras and Pedro Martín García-Vite
Electricity 2024, 5(4), 877-894; https://doi.org/10.3390/electricity5040044 - 9 Nov 2024
Abstract
►▼
Show Figures
This work introduces a boost converter with quadratic gain. Its main advantage compared to well-known similar quadratic boost converters is that it requires capacitors with a relatively small capacitance and inductors with small inductance, leading to a reduction in the size or stored
[...] Read more.
This work introduces a boost converter with quadratic gain. Its main advantage compared to well-known similar quadratic boost converters is that it requires capacitors with a relatively small capacitance and inductors with small inductance, leading to a reduction in the size or stored energy while performing a power conversion of similar power rating and the same switching ripples in both the input current and the output voltage. It is inspired by the recently introduced ISB converter and uses a specific PWM method. This results in achieving switching ripple constraints while using smaller energy storage elements (capacitors and inductors). The updated converter offers the same voltage gain compared to the conventional quadratic boost topology with the benefit of compact component sizes. While it has more passive elements, they are of reduced size. An analysis of energy storage revealed that this new converter uses only half the energy in inductors and 14% in capacitors when compared to specific design parameters.
Full article
Figure 1
Open AccessArticle
Enhancing Fault Location Accuracy in Transmission Lines Using Transient Frequency Spectrum Analysis: An Investigation into Key Factors and Improvement Strategies
by
Mustafa Akdağ, Mehmet Salih Mamiş and Düzgün Akmaz
Electricity 2024, 5(4), 861-876; https://doi.org/10.3390/electricity5040043 - 6 Nov 2024
Abstract
►▼
Show Figures
Fault location estimation in transmission lines is critical for power system reliability. Various methods have been developed for this purpose, among which transient frequency spectrum analysis (TFSA) stands out as a recent method based on travelling wave (TW) theory. TFSA determines the fault
[...] Read more.
Fault location estimation in transmission lines is critical for power system reliability. Various methods have been developed for this purpose, among which transient frequency spectrum analysis (TFSA) stands out as a recent method based on travelling wave (TW) theory. TFSA determines the fault location by analyzing the frequency spectrum of transient currents and/or voltages at the instant of the fault, offering advantages such as independence from fault impedance and the ability to locate faults with one-side measurements. Despite its success in fault location, TFSA has several considerations that warrant detailed investigation. This study explores the effects of source inductance, series compensation, fault arc, and current transformer (CT) characteristics on transient frequencies. Additionally, the impact of noise on TFSA results is examined. The new proposed source inductance compensation method can reduce the error of 6.55% to 0.88%, where the same error can be reduced to 3.45% with the compensation method given in previous study. Strategies to enhance accuracy are discussed and compared to previous studies, including a proposed detection approach providing appropriate data size and precise wave propagation speed calculations. These findings contribute to a deeper understanding of TFSA’s limitations and inform practical improvements for fault location accuracy in power transmission systems.
Full article
Figure 1
Open AccessArticle
Harnessing Deep Learning for Enhanced MPPT in Solar PV Systems: An LSTM Approach Using Real-World Data
by
Bappa Roy, Shuma Adhikari, Subir Datta, Kharibam Jilenkumari Devi, Aribam Deleena Devi and Taha Selim Ustun
Electricity 2024, 5(4), 843-860; https://doi.org/10.3390/electricity5040042 - 4 Nov 2024
Abstract
Maximum Power Point Tracking (MPPT) is essential for maximizing the efficiency of solar photovoltaic (PV) systems. While numerous MPPT methods exist, practical implementations often lean towards conventional techniques due to their simplicity. However, these traditional methods can struggle with rapid fluctuations in solar
[...] Read more.
Maximum Power Point Tracking (MPPT) is essential for maximizing the efficiency of solar photovoltaic (PV) systems. While numerous MPPT methods exist, practical implementations often lean towards conventional techniques due to their simplicity. However, these traditional methods can struggle with rapid fluctuations in solar irradiance and temperature. This paper introduces a novel deep learning-based MPPT algorithm that leverages a Long Short-Term Memory (LSTM) deep neural network (DNN) to effectively track maximum power from solar PV panels, utilizing real-world data. The simulations of three algorithms—Perturb and Observe (P&O), Artificial Neural Network (ANN), and the proposed LSTM-based MPPT—were conducted using MATLAB (2021b) and RT_LAB (24.3.3) with an OPAL-RT simulator for real-time analysis. The data used for this study were sourced from NASA/POWER’s Native Resolution Daily Data of solar irradiation and temperature specific to Imphal, Manipur, India. The obtained results demonstrate that the LSTM-based MPPT system achieves a superior power tracking accuracy under changing solar conditions, producing an average output of 74 W. In comparison, the ANN and P&O methods yield average outputs of 57 W and 62 W, respectively. This significant improvement, i.e., 20–30%, underscores the effectiveness of the LSTM technique in enhancing the power output of solar PV systems. By incorporating real-world data, valuable insights into solar power generation specific to the selected location are provided. Furthermore, the outputs of the model were verified through real-time simulations using the OPAL-RT simulator OP4510, showcasing the practical applicability of this approach in real-world scenarios.
Full article
(This article belongs to the Special Issue Feature Papers to Celebrate the ESCI Coverage)
►▼
Show Figures
Figure 1
Open AccessArticle
A Novel Non-Unit Protection Method for MMC-HVDC Transmission Lines Based on the Ratio of Line-Mode Voltage Second Derivative
by
Yanting Wang, Jiayuan Ouyang, Zhaoyuan Shi and Shunyue Fan
Electricity 2024, 5(4), 826-842; https://doi.org/10.3390/electricity5040041 - 1 Nov 2024
Abstract
The modular multilevel converter (MMC) high-voltage direct current (HVDC) transmission technology is essential for overcoming the challenges of large-scale renewable energy integration. Line protection is critical for ensuring system safety. However, existing protection methods for MMC-HVDC transmission lines face difficulties in withstanding both
[...] Read more.
The modular multilevel converter (MMC) high-voltage direct current (HVDC) transmission technology is essential for overcoming the challenges of large-scale renewable energy integration. Line protection is critical for ensuring system safety. However, existing protection methods for MMC-HVDC transmission lines face difficulties in withstanding both high resistance and noise interference, frequently leading to failures in detecting internal high-resistance faults or triggering false operations due to noise. This paper first derives the theoretical expression of the line-mode voltage through analytical methods. By analyzing the second derivative of the line-mode voltage under different fault conditions, this paper constructs a criterion based on the ratio of the integrals of the positive and negative components of the second derivative of the line-mode voltage. This criterion enables effective fault discrimination by utilizing the characteristic differences in the second-derivative waveform. The proposed criterion allows for precise fault identification, requiring only a 0.5 ms time window to detect faults. Additionally, this criterion is highly resistant to transition resistance, remaining unaffected by resistances up to 500 Ω. Moreover, an entropy-based auxiliary criterion is introduced to prevent false operations caused by noise interference. Simulation results using PSCAD/EMTDC demonstrate that the proposed protection scheme can swiftly and reliably detect faults, with a detection time of 0.5 ms and robust performance against both high transition resistance and noise interference.
Full article
(This article belongs to the Special Issue Recent Advances in Power and Smart Grids)
►▼
Show Figures
Figure 1
Open AccessArticle
Increasing Renewable Energy Penetration on Low-Voltage Networks: An Expert Knowledge Approach
by
Lohan A. Jansen, Mel G. Botha, George van Schoor and Kenneth R. Uren
Electricity 2024, 5(4), 804-825; https://doi.org/10.3390/electricity5040040 - 31 Oct 2024
Cited by 1
Abstract
While South Africa is deemed one of the countries with the highest irradiation levels, it still utilises coal as its primary energy source due to its abundance. Due to the world-wide drive towards carbon neutrality, residential, commercial, agricultural, and industrial consumers are considering
[...] Read more.
While South Africa is deemed one of the countries with the highest irradiation levels, it still utilises coal as its primary energy source due to its abundance. Due to the world-wide drive towards carbon neutrality, residential, commercial, agricultural, and industrial consumers are considering small-scale embedded generation systems. The National Rationalised Specifications 097-2-3 document specifies the scale of the embedded generation capacity a consumer is allowed to install. However, specifications do not yet make the required provisions for the addition of energy storage. The effective collective management of the grouped small-scale embedded generation systems could provide a high level of energy security and increase the percentage of renewable energy generation in the total energy mix. Potential challenges come into play when considering the stochastic nature of photovoltaic generation and its effect on the storage capacity and the dispersion in load profiles of the residential units typically present on a low-voltage network. This paper contributes by investigating the utilisation of photovoltaic generation in conjunction with storage as the basis for virtual power plant control, with the aim to safely increase renewable energy penetration and improve energy security, all while remaining within the South African low-voltage regulatory limits. A two-level virtual power plant controller is proposed with the dispersed energy storage units as the primary controllable resources and the dispersed photovoltaic generation as the secondary controllable resources. The objective of the controller is to achieve nodal energy management, energy sharing, and ancillary service provision and finally to increase renewable energy penetration. A representative single-feeder low-voltage network is simulated, and test cases of 50% and 75% renewable energy penetration are investigated as the basis for evaluation. The proposed controller architecture proved to maintain network integrity for both test cases. The adaptability of the controller architecture was also confirmed for a changed feeder topology; in this case, it was a multi-feeder topology. Future work is warranted to inform policy on the allowed levels of renewable energy penetration to be based not only on demand but also on the level of energy storage present in a network.
Full article
(This article belongs to the Collection Optimal Operation and Planning of Smart Power Distribution Networks)
►▼
Show Figures
Figure 1
Open AccessArticle
Physics-Informed Neural Network for Load Margin Assessment of Power Systems with Optimal Phasor Measurement Unit Placement
by
Murilo Eduardo Casteroba Bento
Electricity 2024, 5(4), 785-803; https://doi.org/10.3390/electricity5040039 - 31 Oct 2024
Abstract
The load margin is an important index applied in power systems to inform how much the system load can be increased without causing system instability. The increasing operational uncertainties and evolution of power systems require more accurate tools at the operation center to
[...] Read more.
The load margin is an important index applied in power systems to inform how much the system load can be increased without causing system instability. The increasing operational uncertainties and evolution of power systems require more accurate tools at the operation center to inform an adequate system load margin. This paper proposes an optimization model to determine the parameters of a Physics-Informed Neural Network (PINN) that will be responsible for predicting the load margin of power systems. The proposed optimization model will also determine an optimal location of Phasor Measurement Units (PMUs) at system buses whose measurements will be inputs to the PINN. Physical knowledge of the power system is inserted in the PINN training stage to improve its generalization capacity. The IEEE 68-bus system and the Brazilian interconnected power system were chosen as the test systems to perform the case studies and evaluations. Three different metaheuristics called the Hiking Optimization Algorithm, Artificial Protozoa Optimizer, and Particle Swarm Optimization were applied and evaluated in the test system. The results achieved demonstrate the benefits of inserting physical knowledge in the PINN training and the optimal selection of PMUs at system buses for load margin prediction.
Full article
(This article belongs to the Special Issue Advances in Operation, Optimization, and Control of Smart Grids)
►▼
Show Figures
Figure 1
Open AccessArticle
Receiving-End Voltage Compensation Method with NPC-Inverter-Based Active Power Line Conditioner in Three-Phase Four-Wire Distribution Feeder
by
Yuka Sabi and Hiroaki Yamada
Electricity 2024, 5(4), 770-784; https://doi.org/10.3390/electricity5040038 - 30 Oct 2024
Abstract
►▼
Show Figures
This study proposes a receiving-end voltage compensation method employing a phase-specific reactive power control strategy with a neutral-point-clamped (NPC) inverter in a three-phase four-wire distribution system. The principle of the proposed receiving end voltage compensation method is explained. Further, the proposed control strategy
[...] Read more.
This study proposes a receiving-end voltage compensation method employing a phase-specific reactive power control strategy with a neutral-point-clamped (NPC) inverter in a three-phase four-wire distribution system. The principle of the proposed receiving end voltage compensation method is explained. Further, the proposed control strategy can solve the problems of the three-phase, four-wire distribution system, which are an increase in the neutral-line current and the unbalanced voltage. Computer simulation is performed to confirm the validity of the proposed method. The simulation results indicate the receiving-end voltages can be compensated using the proposed method.
Full article
Figure 1
Open AccessArticle
Hydropower Plant Available Energy Forecasting Using Artificial Neural Network and Particle Swarm Optimization
by
Suriya Kaewarsa and Vanhkham Kongpaseuth
Electricity 2024, 5(4), 751-769; https://doi.org/10.3390/electricity5040037 - 22 Oct 2024
Abstract
►▼
Show Figures
Accurate forecasting of the available energy portion that corresponds to the reservoir inflow of the month(s) ahead provides important decision support for hydropower plants in energy production planning for revenue maximization, as well as for environmental impact prevention and flood control upstream and
[...] Read more.
Accurate forecasting of the available energy portion that corresponds to the reservoir inflow of the month(s) ahead provides important decision support for hydropower plants in energy production planning for revenue maximization, as well as for environmental impact prevention and flood control upstream and downstream of a basin. Therefore, a reliable forecasting tool or model is deemed necessary and crucial. Considering the fluctuation and nonlinearity of data which significantly influence the forecasting results, this study develops an effective hybrid model by integrating an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) called “PSO-ANN” model based on the hydrological and meteorological data pre-processed by cross-correlation function (CCF), autocorrelation function (AFC), and normalization techniques for predicting the available energy portion corresponding to the reservoir inflow mentioned above for a case study hydropower plant in Laos, namely, the Theun-Hinboun hydropower plant (THHP). The model was evaluated by using correlation coefficient (r), relative error (RE), root mean square error (RMSE), and Taylor diagram plots in comparison with popular single-algorithm approaches such as ANN, and NARX models. The results demonstrated the superiority of the proposed PSO-ANN approach over the other two models, in addition to being comparable to those proposed by previous studies.
Full article
Figure 1
Open AccessReview
A Review of Photovoltaic Waste Management from a Sustainable Perspective
by
Abolfazl Babaei and Ali Nasr Esfahani
Electricity 2024, 5(4), 734-750; https://doi.org/10.3390/electricity5040036 - 14 Oct 2024
Abstract
►▼
Show Figures
The rapid deployment of solar photovoltaic (PV) systems underscores their potential as vital clean energy solutions with reduced carbon emissions and increasingly competitive installation costs. This review examines PV waste management from a sustainable perspective, focusing on environmental impacts and technological advancements. Various
[...] Read more.
The rapid deployment of solar photovoltaic (PV) systems underscores their potential as vital clean energy solutions with reduced carbon emissions and increasingly competitive installation costs. This review examines PV waste management from a sustainable perspective, focusing on environmental impacts and technological advancements. Various solar cell technologies, including crystalline silicon, thin-film, and emerging third-generation cells like perovskite and organic photovoltaics, are analyzed for their life cycle and environmental effects. Effective disposal and recycling methods, such as physical separation and thermal and chemical treatments, are critically evaluated to mitigate ecological harm. The study highlights the need for improved recycling processes and sustainable practices to enhance the environmental benefits of PV systems. Future solutions call for better recycling techniques, increased efficiency in renewable materials, and comprehensive life cycle assessments to support the global transition to sustainable energy. This review aims to foster the integration of sustainable practices in the renewable energy sector, ensuring that PV systems contribute to a cleaner and more sustainable future.
Full article
Figure 1
Open AccessReview
Exploring Evolutionary Algorithms for Optimal Power Flow: A Comprehensive Review and Analysis
by
Harish Pulluri, Vedik Basetti, B. Srikanth Goud and CH. Naga Sai Kalyan
Electricity 2024, 5(4), 712-733; https://doi.org/10.3390/electricity5040035 - 3 Oct 2024
Abstract
►▼
Show Figures
It has been more than five decades since optimum power flow (OPF) emerged as one of the most famous and frequently used nonlinear optimization problems in power systems. Despite its long-standing existence, the OPF problem continues to be widely researched due to its
[...] Read more.
It has been more than five decades since optimum power flow (OPF) emerged as one of the most famous and frequently used nonlinear optimization problems in power systems. Despite its long-standing existence, the OPF problem continues to be widely researched due to its critical role in electrical network planning and operations. The general formulation of OPF is complex, representing a large-scale optimization model with nonlinear and nonconvex characteristics, incorporating both discrete and continuous control variables. The inclusion of control factors such as transformer taps and shunt capacitors, and the integration of renewable energy sources like wind power further complicates the system’s design and solution. To address these challenges, a variety of classical, evolutionary, and improved optimization techniques have been developed. These techniques not only provide new solution pathways but also enhance the quality of existing solutions, contributing to reductions in computational cost and operational efficiency. Multi-objective approaches are frequently employed in modern OPF problems to balance trade-offs between competing objectives like cost minimization, loss reduction, and environmental impact. This article presents an in-depth review of various OPF problems and the wide array of algorithms, both traditional and evolutionary, applied to solve these problems, paying special attention to wind power integration and multi-objective optimization strategies.
Full article
Figure 1
Open AccessArticle
Design and Experimental Verification of Electric Vehicle Battery Charger Using Kelvin-Connected Discrete MOSFETs and IGBTs for Energy Efficiency Improvement
by
Borislav Dimitrov and Richard McMahon
Electricity 2024, 5(4), 684-711; https://doi.org/10.3390/electricity5040034 - 30 Sep 2024
Abstract
►▼
Show Figures
This research investigates the advantages of Kelvin-connected 4-pin discrete transistors, both MOSFETs and IGBTs, in onboard battery chargers for electric vehicles. The study compares the standard 3-pin and the extended 4-pin packages based on averaged data collected from leading manufacturers. The investigation shows
[...] Read more.
This research investigates the advantages of Kelvin-connected 4-pin discrete transistors, both MOSFETs and IGBTs, in onboard battery chargers for electric vehicles. The study compares the standard 3-pin and the extended 4-pin packages based on averaged data collected from leading manufacturers. The investigation shows significant potential power loss reduction, thermal operation mitigation, and reduced gate-drive oscillation for the 4-pin package. The benefits have been quantified by analysing the operation of actual switches in an automotive battery charger based on Boost-PFC and DC-DC LLC converters. The converters’ practical design demonstrates a procedure for integrating the Kelvin-connected package into the design methodology. The results have been verified experimentally.
Full article
Figure 1
Open AccessArticle
Optimal Placement and Sizing of Battery Energy Storage Systems for Improvement of System Frequency Stability
by
Amrit Parajuli, Samundra Gurung and Kamal Chapagain
Electricity 2024, 5(3), 662-683; https://doi.org/10.3390/electricity5030033 - 13 Sep 2024
Abstract
►▼
Show Figures
Modern power systems are growing in complexity due to the installation of large generators, long transmission lines, the addition of inertialess renewable energy resources (RESs) with zero inertia, etc., which can all severely degrade the system frequency stability. This can lead to under-/over-frequency
[...] Read more.
Modern power systems are growing in complexity due to the installation of large generators, long transmission lines, the addition of inertialess renewable energy resources (RESs) with zero inertia, etc., which can all severely degrade the system frequency stability. This can lead to under-/over-frequency load shedding, damage to turbine blades, and affect frequency-sensitive loads. In this study, we propose a methodology to improve the two critical frequency stability indices, i.e., the frequency nadir and the rate of change of frequency (RoCoF), by formulating an optimization problem. The size and placement location of battery energy storage systems (BESSs) are considered to be the constraints for the proposed optimization problem. Thereafter, the optimization problem is solved using the three metaheuristic optimization algorithms: the particle swarm optimization, firefly, and bat algorithm. The best performing algorithm is then selected to find the optimal sizing and placement location of the BESSs. The analyses are all performed on the IEEE 9-bus and IEEE 39-bus test systems. Several scenarios which consider multiple generator outages, increased/decreased loading conditions, and the addition of RESs are also considered for both test systems in this study. The obtained results show that under all scenarios, the proposed method can enhance system frequency compared to the existing method and without BESSs. The proposed method can be easily upscaled for a larger electrical network for obtaining the optimized BESS size and location for the improvement of the system frequency stability.
Full article
Figure 1
Open AccessArticle
Comparison of Reactive Power Compensation Methods in an Industrial Electrical System with Power Quality Problems
by
Salim Adolfo Giha Yidi, Vladimir Sousa Santos, Kelly Berdugo Sarmiento, John E. Candelo-Becerra and Jorge de la Cruz
Electricity 2024, 5(3), 642-661; https://doi.org/10.3390/electricity5030032 - 6 Sep 2024
Abstract
►▼
Show Figures
This paper compares concentrated and distributed reactive power compensation to improve the power factor at the point of common connection (PCC) of an industrial electrical system (IES) with harmonics. The electrical system under study has a low power factor, voltage variation, and harmonics
[...] Read more.
This paper compares concentrated and distributed reactive power compensation to improve the power factor at the point of common connection (PCC) of an industrial electrical system (IES) with harmonics. The electrical system under study has a low power factor, voltage variation, and harmonics caused by motors operating at low loads and powered by variable-speed drives. The designed compensation system mitigates harmonics and reduces electrical losses with the shortest payback period. Four solutions were compared, considering concentrated and distributed compensation with capacitor banks and harmonic filters. Although the cost of investment in concentrated compensation is lower than that of distributed compensation, a higher reduction in electrical losses and a lower payback period are obtained with distributed compensation. Although the lowest payback period was obtained with distributed compensation with capacitor banks (0.4 years), it is not recommended in the presence of harmonics because the effects of current harmonics significantly reduce the useful life of these elements. For this reason, distributed compensation with harmonic filters obtained a payback period of 0.6 years, and it was proposed as the best solution. These results should be considered in projects aimed at power factor compensation in IESs with harmonics. The concentrated compensation of the capacitor bank at the PCC is proposed because of the lower investment cost and ease of installation. However, the advantages of distributed compensation with harmonic filters have not been evaluated. An energy efficiency approach is used to analyze the impact of the location methods of the power factor compensation equipment on the electrical losses of the IES.
Full article
Figure 1
Highly Accessed Articles
Latest Books
E-Mail Alert
News
Topics
Topic in
Energies, Sustainability, Processes, Electricity
District Heating and Cooling Systems
Topic Editors: Ahmad Arabkoohsar, Meisam SadiDeadline: 20 December 2024
Topic in
Electricity, Electronics, Energies, Processes, Sustainability
Integration of Renewable Energy
Topic Editors: Xiandong Ma, Mohamed Benbouzid, Sinisa Durovic, Hao ChenDeadline: 31 December 2024
Topic in
Electricity, Energies, Modelling, Sustainability, Wind
Market Integration of Renewable Generation
Topic Editors: Ana Estanqueiro, Nikolaos Chrysanthopoulos, Hugo AlgarvioDeadline: 31 January 2025
Topic in
Electricity, Energies, Mathematics, Sustainability, Symmetry
Intelligent Control in Smart Energy Systems
Topic Editors: Eduard Petlenkov, Larbi Chrifi-AlaouiDeadline: 10 March 2025
Conferences
Special Issues
Special Issue in
Electricity
Planning, Operation and Control of Power Systems with Large Amounts of Variable Renewable Generation
Guest Editor: Emilio Gomez-LazaroDeadline: 31 December 2024
Special Issue in
Electricity
Advances in Operation, Optimization, and Control of Smart Grids
Guest Editors: Murilo E.C. Bento, Hugo MoraisDeadline: 31 January 2025
Special Issue in
Electricity
Feature Papers to Celebrate the ESCI Coverage
Guest Editor: Andreas SumperDeadline: 28 February 2025
Special Issue in
Electricity
Recent Advances in Power and Smart Grids
Guest Editor: Yang HanDeadline: 20 March 2025
Topical Collections
Topical Collection in
Electricity
Optimal Operation and Planning of Smart Power Distribution Networks
Collection Editor: Pavlos S. Georgilakis