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11 pages, 1114 KiB

Open AccessArticle

Regional Grid Power Supply Radius Planning—A Sensitivity Constraint-Based Approach

by You Yu, Jingfu Tian, Tao Li, Zhenting Sun, Jianbin Ci, Jinming Li, Zengqiang Lai, Zhenji Yao and Jingshan Mo

Processes 2024, 12(8), 1769; https://doi.org/10.3390/pr12081769 - 21 Aug 2024

Viewed by 469

Abstract

This paper addresses the correlation between the coverage of regional power grid supply and the sensitivity of line backup protection. Through a theoretical analysis of the calculation method for line backup protection sensitivity in power grids, and in accordance with grid regulations, this [...] Read more.

This paper addresses the correlation between the coverage of regional power grid supply and the sensitivity of line backup protection. Through a theoretical analysis of the calculation method for line backup protection sensitivity in power grids, and in accordance with grid regulations, this paper proposes a planning method for the supply range of power grid lines that meets sensitivity constraints. And the reliability of this method in calculating and evaluating the optimal power supply radius of lines is verified by taking the example of an actual 66 kV grid in a region. This method can be used to optimise network structure, improve the reliability and economy of the grid, and guide the planning and construction of regional grids. Full article

(This article belongs to the Special Issue AC and DC Power Grids System Technologies: Analysis, Control and Practical Applications)

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15 pages, 1646 KiB

Open AccessArticle

A Model and Data Hybrid-Driven Method for Operational Reliability Evaluation of Power Systems Considering Endogenous Uncertainty

by Lingzi Zhu, Qihui Chen, Mingshun Liu, Lingxiao Zhang and Dongxu Chang

Processes 2024, 12(6), 1056; https://doi.org/10.3390/pr12061056 - 22 May 2024

Viewed by 833

Abstract

Renewable energy sources are increasingly integrated into power systems, leading to significant variability in operations. This necessitates robust methods for assessing operational reliability. We propose a novel model–data hybrid approach that incorporates endogenous uncertainty into the reliability evaluation process. First, unlike traditional methods [...] Read more.

Renewable energy sources are increasingly integrated into power systems, leading to significant variability in operations. This necessitates robust methods for assessing operational reliability. We propose a novel model–data hybrid approach that incorporates endogenous uncertainty into the reliability evaluation process. First, unlike traditional methods that treat uncertainties as external factors, this approach recognizes that operational decisions can significantly influence how uncertainties are resolved and impact reliability metrics. The proposed method integrates device reliability indices with operational decision variables. This allows us to evaluate the impact of endogenous uncertainty on operational reliability through a reliability-constrained stochastic unit commitment model. Additionally, a model–data hybrid algorithm is introduced for efficient solution of the formulated optimization problem. Case studies demonstrate the effectiveness of the proposed method. Results also show that endogenous uncertainty may cause a 10% error in power system reliability indices. Full article

(This article belongs to the Special Issue AC and DC Power Grids System Technologies: Analysis, Control and Practical Applications)

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17 pages, 5657 KiB

Open AccessArticle

Performance Improvement of an Electric Vehicle Charging Station Using Brain Emotional Learning-Based Intelligent Control

by Sherif A. Zaid, Hani Albalawi, Aadel M. Alatwi and Atef Elemary

Processes 2024, 12(5), 1014; https://doi.org/10.3390/pr12051014 - 16 May 2024

Cited by 2 | Viewed by 1145

Abstract

Electric vehicle (EV) charging facilities are essential to their development and deployment. These days, autonomous microgrids that use renewable energy resources to energize charging stations for electric vehicles alleviate pressure on the public electricity grid. Nevertheless, controlling and managing such charging stations’ energy [...] Read more.

Electric vehicle (EV) charging facilities are essential to their development and deployment. These days, autonomous microgrids that use renewable energy resources to energize charging stations for electric vehicles alleviate pressure on the public electricity grid. Nevertheless, controlling and managing such charging stations’ energy is difficult due to the nonlinearity and irregular character of renewable energy sources. The current research recommends using a Brain Emotional Learning Intelligent Control (BELBIC) controller to enhance an autonomous EV charging station’s performance and power management. The charging station uses a battery to store energy and is primarily powered by photovoltaic (PV) solar energy. The principles of BELBIC are dependent on emotional cues and sensory inputs, and they are based on an emotion processing system in the brain. Noise and parameter variations do not affect this kind of controller. In this study, the performance of a conventional proportional–integral (PI) controller and the suggested BELBIC controller is evaluated for variations in solar insolation. The various parts of an EV charging station are simulated and modelled by the MATLAB/Simulink framework. The findings show that, in comparison to the conventional PI controller, the suggested BELBIC controller greatly enhances the transient responsiveness of the EV charging station’s performance. The EV keeps charging while the storage battery perfectly saves and keeps steady variations in PV power, even in the face of any PV insolation disturbances. The suggested system’s simulation results are provided and scrutinized to confirm the concept’s suitability. The findings validate the robustness of the suggested BELBIC control versus parameter variations. Full article

(This article belongs to the Special Issue AC and DC Power Grids System Technologies: Analysis, Control and Practical Applications)

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16 pages, 2129 KiB

Open AccessArticle

A Fast Reliability Evaluation Strategy for Power Systems under High Proportional Renewable Energy—A Hybrid Data-Driven Method

by Jiaxin Zhang, Bo Wang, Hengrui Ma, Yunshuo Li, Meilin Yang, Hongxia Wang and Fuqi Ma

Processes 2024, 12(3), 608; https://doi.org/10.3390/pr12030608 - 19 Mar 2024

Cited by 5 | Viewed by 1411

Abstract

With the increasing scale of the power system, the increasing penetration of renewable energy, and the increasing uncertainty factors, traditional reliability evaluation methods based on Monte Carlo simulation have greatly reduced computational efficiency in complex power systems and cannot meet the requirements of [...] Read more.

With the increasing scale of the power system, the increasing penetration of renewable energy, and the increasing uncertainty factors, traditional reliability evaluation methods based on Monte Carlo simulation have greatly reduced computational efficiency in complex power systems and cannot meet the requirements of real-time and rapid evaluation. This article proposes a hybrid data-driven strategy to achieve a rapid assessment of power grid reliability on two levels: offline training and online evaluation. Firstly, this article derives explicit analytical expressions for reliability indicators and component parameters, avoiding the computational burden of repetitive Monte Carlo simulation. Next, a large number of samples are quickly generated by parsing expressions to train convolutional neural networks (CNNs), and the system reliability index is quickly calculated under changing operating conditions through CNNs. Finally, the effectiveness and feasibility of the proposed method are verified through an improved RTS-79 testing system. The calculation results show that the method proposed in this article can achieve an online solution of second-level reliability indicators while ensuring calculation accuracy. Full article

(This article belongs to the Special Issue AC and DC Power Grids System Technologies: Analysis, Control and Practical Applications)

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16 pages, 3228 KiB

Open AccessArticle

Precise Lightning Strike Detection in Overhead Lines Using KL-VMD and PE-SGMD Innovations

by Xinsheng Dong, Jucheng Liu, Shan He, Lu Han, Zhongkai Dong and Minbo Cai

Processes 2024, 12(2), 329; https://doi.org/10.3390/pr12020329 - 2 Feb 2024

Viewed by 881

Abstract

When overhead lines are impacted by lightning, the traveling wave of the fault contains a wealth of fault information. The accurate extraction of feature quantities from transient components and their classification are fundamental to the identification of lightning faults. The extraction process may [...] Read more.

When overhead lines are impacted by lightning, the traveling wave of the fault contains a wealth of fault information. The accurate extraction of feature quantities from transient components and their classification are fundamental to the identification of lightning faults. The extraction process may involve modal aliasing, optimal wavelet base issues, and inconsistencies between the lightning strike distance and the fault point. These factors have the potential to impact the effectiveness of recognition. This paper presents a method for identifying lightning strike faults by utilizing Kullback–Leibler (KL) divergence enhanced Variational Mode Decomposition (VMD) and Symmetric Geometry Mode Decomposition (SGMD) improved with Permutation Entropy (PE) to address the aforementioned issues. A model of a 220 kV overhead line is constructed using real faults to replicate scenarios of winding strike, counterstrike, and short circuit. The three-phase voltage is chosen and then subjected to Karenbaren decoupling in order to transform it into zero mode, line mode 1, and line mode 2. The zero-mode voltage is decomposed using KL-VMD and PE-SGMD methods, and the lightning identification criteria are developed based on various transient energy ratios. The research findings demonstrate that the criteria effectively differentiate between winding strike, counterstrike, and short-circuit faults, thus confirming the accuracy and efficacy of the lightning fault identification criteria utilizing KL-VMD and PE-SGMD. Full article

(This article belongs to the Special Issue AC and DC Power Grids System Technologies: Analysis, Control and Practical Applications)

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22 pages, 19793 KiB

Open AccessArticle

Control Approach of Grid-Connected PV Inverter under Unbalanced Grid Conditions

by Mohammed Alharbi

Processes 2024, 12(1), 212; https://doi.org/10.3390/pr12010212 - 18 Jan 2024

Viewed by 2410

Abstract

In grid-connected photovoltaic (PV) systems, power quality and voltage control are necessary, particularly under unbalanced grid conditions. These conditions frequently lead to double-line frequency power oscillations, which worsen Direct Current (DC)-link voltage ripples and stress DC-link capacitors. The well-known dq frame vector control [...] Read more.

In grid-connected photovoltaic (PV) systems, power quality and voltage control are necessary, particularly under unbalanced grid conditions. These conditions frequently lead to double-line frequency power oscillations, which worsen Direct Current (DC)-link voltage ripples and stress DC-link capacitors. The well-known dq frame vector control technique, which is effective under normal conditions, struggles with oscillatory component management in unbalanced grid conditions. To address this issue, this paper presents an advanced control approach designed for grid-connected PV inverters. The proposed approach is effective at reducing oscillations in the DC-link voltage at double the grid frequency, thereby enhancing system stability and component longevity. This method introduces a feedback control method designed to regulate oscillatory components that appeared within the dq frame and suppress the DC-link voltage oscillations under imbalance conditions, including single line-to-ground (SLG) faults. Additionally, the control scheme incorporates a maximum power point tracking (MPPT) controller to optimize PV efficiency. Comprehensive simulations demonstrate the effectiveness of this method in maintaining sinusoidal current injections and stabilizing DC-link voltage during unbalanced grid conditions. Simulation results show that the control scheme effectively stabilizes DC-link voltage, maintains balanced grid current, and ensures constant active power under various conditions, including SLG faults and solar irradiance changes. Full article

(This article belongs to the Special Issue AC and DC Power Grids System Technologies: Analysis, Control and Practical Applications)

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21 pages, 4860 KiB

Open AccessArticle

Energy Storage Deployment and Benefits in the Chinese Electricity Market Considering Renewable Energy Uncertainty and Energy Storage Life Cycle Costs

by Yichao Meng, Ze Ye, Lei Chen, Shanshan Huang and Tiantian Li

Processes 2024, 12(1), 130; https://doi.org/10.3390/pr12010130 - 3 Jan 2024

Viewed by 1362

Abstract

The construction and development of energy storage are crucial areas in the reform of China’s power system. However, one of the key issues hindering energy storage investments is the ambiguity of revenue sources and the inaccurate estimation of returns. In order to facilitate [...] Read more.

The construction and development of energy storage are crucial areas in the reform of China’s power system. However, one of the key issues hindering energy storage investments is the ambiguity of revenue sources and the inaccurate estimation of returns. In order to facilitate investors’ understanding of revenue sources and returns on investment of energy storage in the existing electricity market, this study has established multiple relevant revenue quantification models. The research methodology employed in this paper consists of three main components: Firstly, we established a revenue model and a cost model for energy storage participation in the electricity market. These models focus on arbitrage revenue, subsidy revenue, auxiliary services revenue, investment cost, operational and maintenance cost, and auxiliary service cost of energy storage. Subsequently, we utilized an enhanced Grey Wolf Optimizer algorithm to solve the optimization problem and maximize revenue, thus obtaining the optimal capacity and revenue scale of energy storage in the electricity market. Finally, we compared the whole-lifecycle ROI of different energy storage options in various scenarios. The evaluation results demonstrate that the difference between peak and off-peak loads impacts the investment demand and charging/discharging depth of energy storage. In addition, the discrepancy between peak and off-peak prices affects the arbitrage return of energy storage. These two factors can serve as criteria for energy storage investors to assess their return expectations. When solely considering economic returns and disregarding technical factors, pumped storage energy storage emerges as the most suitable mechanical energy storage option requiring investment. The main contribution of this study lies in the estimation of the lifecycle investment returns for various energy storage technologies in the Chinese electricity market, thus providing valuable insights for the investment and operational practices of market participants. Full article

(This article belongs to the Special Issue AC and DC Power Grids System Technologies: Analysis, Control and Practical Applications)

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19 pages, 3135 KiB

Open AccessArticle

Optimal Control of Hybrid Photovoltaic/Thermal Water System in Solar Panels Using the Linear Parameter Varying Approach

by Faycel Jamaaoui, Vicenç Puig and Mounir Ayadi

Processes 2023, 11(12), 3426; https://doi.org/10.3390/pr11123426 - 13 Dec 2023

Cited by 1 | Viewed by 1140

Abstract

During photovoltaic (PV) conversion in solar panels, a part of the solar radiation is not converted to electricity by the cells, producing heat that could increase their temperature. This increase in temperature deteriorates the performance of the PV panel. In this paper, a [...] Read more.

During photovoltaic (PV) conversion in solar panels, a part of the solar radiation is not converted to electricity by the cells, producing heat that could increase their temperature. This increase in temperature deteriorates the performance of the PV panel. In this paper, a hybrid PV/thermal (PV/T) water system is proposed to mitigate this problem. This system combines a PV panel and a thermal collector. In this paper, we focused on the modeling and control of this hybrid system in the linear parameter varying (LPV) framework. An optimal linear quadratic regulator (LQR) is proposed to control the PV cell temperature around an optimal value that maximises electricity generation. Since the system model is nonlinear, an optimal LQR gain-scheduling state-feedback control approach based on an LPV representation of the nonlinear model is designed using the Linear Matrix Inequality (LMI) method. The goal is to obtain the maximum electrical power for each solar panel. Since a reduced number of sensors is available, an LPV Kalman filter is also proposed to estimate the system states required by the state-feedback controller. The obtained results in a laboratory setup in simulation are used to assess the proposed approach, showing promise in terms of control performance of the PV/T system. Full article

(This article belongs to the Special Issue AC and DC Power Grids System Technologies: Analysis, Control and Practical Applications)

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14 pages, 1974 KiB

Open AccessArticle

Mobile Energy Storage System Scheduling Strategy for Improving the Resilience of Distribution Networks under Ice Disasters

by Xiaofang Guo, Guixi Miao, Xin Wang, Liang Yuan, Hengrui Ma and Bo Wang

Processes 2023, 11(12), 3339; https://doi.org/10.3390/pr11123339 - 30 Nov 2023

Cited by 4 | Viewed by 1336

Abstract

The distribution system is easily affected by extreme weather, leading to an increase in the probability of critical equipment failures and economic losses. Actively scheduling various resources to provide emergency power support can effectively reduce power outage losses caused by extreme weather. This [...] Read more.

The distribution system is easily affected by extreme weather, leading to an increase in the probability of critical equipment failures and economic losses. Actively scheduling various resources to provide emergency power support can effectively reduce power outage losses caused by extreme weather. This paper proposes a mobile energy storage system (MESS) scheduling strategy for improving the resilience of distribution networks under ice disasters. First, the influence of wind and ice loads on power transmission lines is analyzed, and a detailed fault statistical model of transmission lines under an ice disaster is established. Then, the MESS scheduling problem considering the coupling of transportation-distribution networks is transformed into a two-stage optimization problem. The first stage determines the optimal configuration scheme for MESS, and in the second stage, the optimal path selection for MESS can be obtained. Finally, the effectiveness and feasibility of the algorithm proposed in this paper are verified through an improved IEEE-33 node testing system. Full article

(This article belongs to the Special Issue AC and DC Power Grids System Technologies: Analysis, Control and Practical Applications)

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21 pages, 17992 KiB

Open AccessArticle

Reduction in the Number of Current Sensors of a Semi-Bridgeless PFC Rectifier Based on GaNFET Characteristics

by Chen-Bin Yu and Kuo-Ing Hwu

Processes 2023, 11(12), 3259; https://doi.org/10.3390/pr11123259 - 21 Nov 2023

Cited by 1 | Viewed by 1058

Abstract

The semi-bridgeless power factor correction (PFC) rectifier is widely used due to its high power factor, high efficiency, and low electromagnetic interference. However, in this rectifier, the inductor current will flow through the body diode of the metal–oxide–semiconductor field-effect transistor (MOSFET) when the [...] Read more.

The semi-bridgeless power factor correction (PFC) rectifier is widely used due to its high power factor, high efficiency, and low electromagnetic interference. However, in this rectifier, the inductor current will flow through the body diode of the metal–oxide–semiconductor field-effect transistor (MOSFET) when the MOSFET does not work, causing a problem in detecting the inductor current. Consequently, the current transformers are generally used as current sensors. This means that using many current sensors will make the cost and the peripheral detection circuit complicated. In this paper, our new method is to use a gallium nitride field-effect transistor (GaNFET) to replace the metal–oxide–semiconductor field-effect transistor (MOSFET) in the main switch selection. The reverse-biased conduction voltage of the third quadrant of the GaNFET is higher than the forward-biased conduction voltage of the diode, which solves the problem in detecting the inductor current, reduces the number of current sensors, and simplifies the corresponding peripheral circuits and components. Eventually, via mathematical deduction and hardware implementation, a semi-bridgeless PFC prototype with a GaNFET was built to verify the effectiveness of the proposed structure. Full article

(This article belongs to the Special Issue AC and DC Power Grids System Technologies: Analysis, Control and Practical Applications)

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13 pages, 4316 KiB

Open AccessArticle

An Improved Dual Second-Order Generalized Integrator Phased-Locked Loop Strategy for an Inverter of Flexible High-Voltage Direct Current Transmission Systems under Nonideal Grid Conditions

by Lai Peng, Zhichao Fu, Tao Xiao, Yang Qian, Wei Zhao and Cheng Zhang

Processes 2023, 11(9), 2634; https://doi.org/10.3390/pr11092634 - 4 Sep 2023

Cited by 2 | Viewed by 1229

Abstract

High-voltage flexible power systems, with their intrinsic characteristics, play an increasingly important role in electronic power systems. Synchronization between the inverter and the grid needs to be achieved by a phase-locked loop (PLL), the performance of which determines the quality of power transmission. [...] Read more.

High-voltage flexible power systems, with their intrinsic characteristics, play an increasingly important role in electronic power systems. Synchronization between the inverter and the grid needs to be achieved by a phase-locked loop (PLL), the performance of which determines the quality of power transmission. This paper proposes a PLL adapted to extremely harsh grid conditions. Firstly, the traditional synchronous reference frame PLL and the dual second-order generalized integrator (DSOGI-PLL) are analyzed, and the errors in phase-locking and the shortcomings of these two methods in the presence of DC components in the grid are pointed out. Secondly, based on the harmonic grid voltage, a repetitive control internal model is introduced by DSOGI to realize the real-time tracking and regulation of the harmonic signals in order to suppress the harmonic voltage disturbance. In addition, a DC bias elimination and frequency adaptive method is proposed to solve the problems of DC bias and grid voltage frequency fluctuation in order to achieve adaptive tracking of the grid phase. Finally, the superiority of the proposed strategy is verified through simulations and experiments. Full article

(This article belongs to the Special Issue AC and DC Power Grids System Technologies: Analysis, Control and Practical Applications)

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23 pages, 8555 KiB

Open AccessArticle

Exponential Curve-Based Control Strategy for Auxiliary Equipment Power Supply Systems in Railways

by Shoeb Azam Farooqui, Chang-Hua Lin, Shiue-Der Lu, Hwa-Dong Liu, Adil Sarwar and Liang-Yin Huang

Processes 2023, 11(4), 1285; https://doi.org/10.3390/pr11041285 - 20 Apr 2023

Cited by 1 | Viewed by 1817

Abstract

An exponential curve-based (ECB) control strategy has been proposed in this paper. The proposed ECB control strategy is based on the growth and decay of charge in the series RC circuit and the harmonic elimination by detecting the Fourier expansion series of the [...] Read more.

An exponential curve-based (ECB) control strategy has been proposed in this paper. The proposed ECB control strategy is based on the growth and decay of charge in the series RC circuit and the harmonic elimination by detecting the Fourier expansion series of the auxiliary equipment power supply system’s (AEPSS) three-phase output voltage level. It can quickly adjust each duty cycle to the best value for driving the isolated three-phase inverter (ITPI) and produce a three-phase 380 V_AC/60 Hz output. A comparison of the AEPSS output performance using the traditional voltage cancellation method (VCM) and the proposed ECB control strategy was performed. The hardware implementation of the system was performed on the prototype developed in the laboratory. These control strategies are tested under three conditions, i.e., (i) V_i = 550 V_DC. (ii) V_i = 750 V_DC. (iii) V_i = 800 V_DC. The total harmonic distortion (THD) is 13.7%, 14.5%, and 14.9%, and the output voltage V_o is 372.3 V_AC, 377.3 V_AC, and 385.3 V_AC using the traditional control strategy at three test conditions, respectively. However, the THD is 7.2%, 7.8%, and 8.0%, and the output voltage V_o is 382.2 V_AC, 381.2 V_AC, and 381.9 V_AC using the proposed ECB control strategy under the test conditions. It is obvious from the hardware results that the output voltage harmonics and output voltage level for the proposed ECB control strategy are superior to the traditional VCM. The voltage produced from the AEPSS using the proposed ECB control strategy is more stable and has better quality. In addition, the filter size is also reduced. Full article

(This article belongs to the Special Issue AC and DC Power Grids System Technologies: Analysis, Control and Practical Applications)

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19 pages, 2625 KiB

Open AccessArticle

Power and Energy Management Strategies for a Microgrid with the Presence of Electric Vehicles and CAES Considering the Uncertainty of Resources

by Reza Doosti, Alireza Rezazadeh and Mostafa Sedighizadeh

Processes 2023, 11(4), 1156; https://doi.org/10.3390/pr11041156 - 10 Apr 2023

Cited by 2 | Viewed by 2304

Abstract

We are witnessing the growth of microgrid technology and the development of electric vehicles (EVs) in the world. These microgrids seek demand response (DR) and energy storage for better management of their resources. In this research, microgrids, including wind turbines, photovoltaics, battery charging/discharging, [...] Read more.

We are witnessing the growth of microgrid technology and the development of electric vehicles (EVs) in the world. These microgrids seek demand response (DR) and energy storage for better management of their resources. In this research, microgrids, including wind turbines, photovoltaics, battery charging/discharging, and compressed air energy storage (CAES), are considered. We will consider two scenarios under uncertainty: (a) planning a microgrid and DR without considering CAES, and (b) planning a microgrid and DR considering CAES. The cost of charging the battery in the second study decreased by $0.66 compared to the first study. The battery is charged with a difference of $0.7 compared to the case of the first study. We will also pay for unsupplied energy and excess energy in this microgrid. Then, we test the scheduling of vehicles to the grid (V2G) in the IEEE 33-bus network. The first framework for increasing network flexibility is the use of EVs as active loads. The scheduling of vehicles in the IEEE 33-bus network is simulated. Every hour, plug-in hybrid electric vehicle (PHEV) charging and discharging, active power loss, and cost will be compared with IHS and PSO algorithms. The difference obtained using the IHS algorithm compared to the PSO algorithm is 1.002 MW and the voltage difference is 9.14

p u

. Full article

(This article belongs to the Special Issue AC and DC Power Grids System Technologies: Analysis, Control and Practical Applications)

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23 pages, 6561 KiB

Open AccessArticle

A Novel Isolated Intelligent Adjustable Buck-Boost Converter with Hill Climbing MPPT Algorithm for Solar Power Systems

by Bushra Sabir, Shiue-Der Lu, Hwa-Dong Liu, Chang-Hua Lin, Adil Sarwar and Liang-Yin Huang

Processes 2023, 11(4), 1010; https://doi.org/10.3390/pr11041010 - 27 Mar 2023

Cited by 12 | Viewed by 2221

Abstract

This study proposes a new isolated intelligent adjustable buck-boost (IIABB) converter with an intelligent control strategy that is suitable for regenerative energy systems with unsteady output voltages. It also serves as a reliable voltage source for loads such as battery systems, microgrids, etc. [...] Read more.

This study proposes a new isolated intelligent adjustable buck-boost (IIABB) converter with an intelligent control strategy that is suitable for regenerative energy systems with unsteady output voltages. It also serves as a reliable voltage source for loads such as battery systems, microgrids, etc. In addition, the hill climbing (HC) maximum power point tracking (MPPT) algorithm can be utilized with this innovative IIABB converter to capture the MPP and then enhance system performance. In this converter, five inductors (L_A, L_B, L_C, L_D, and L_E) and four power MOSFETs (S_A, S_B, S_C, and S_D) are used in the proposed novel isolated intelligent adjustable buck-boost (IIABB) converter to adjust the applied voltage across the load side. It also has a constant, stable output voltage. The new IIABB converter is simulated and verified using MATLAB R2021b, and the performances of the proposed IIABB converter and conventional SEPIC converter are compared. The solar photovoltaic module output voltages of 20 V, 30 V, and 40 V are given as inputs to the proposed IIABB converter, and the total output voltage of the proposed converter is 48 V. In the new IIABB converter, the duty cycle of the power MOSFET has a small variation. The proposed IIABB converter has an efficiency of 92~99%. On the other hand, in the conventional SEPIC converter, the duty cycle of a power MOSFET varies greatly depending on the relationship between the output and input voltage, which deteriorates the efficiency of the converter. As a result, this research contributes to the development of a novel type of IIABB converter that may be employed in renewable energy systems to considerably increase system performance and reduce the cost and size of the system. Full article

(This article belongs to the Special Issue AC and DC Power Grids System Technologies: Analysis, Control and Practical Applications)

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15 pages, 3191 KiB

Open AccessArticle

Grid-Connected Microbial Fuel Cell Modeling and Control in Distributed Generation

by Fangmei Jiang, Liping Fan, Weimin Zhang and Naitao Yang

Processes 2023, 11(2), 466; https://doi.org/10.3390/pr11020466 - 3 Feb 2023

Cited by 1 | Viewed by 1586

Abstract

Water shortages and water pollution have seriously threatened the sustainable development of the community. The grid-connected microbial fuel cell is an effective way to control the cost of wastewater treatment plants. Moreover, it solves the problem of low efficiency and high energy consumption. [...] Read more.

Water shortages and water pollution have seriously threatened the sustainable development of the community. The grid-connected microbial fuel cell is an effective way to control the cost of wastewater treatment plants. Moreover, it solves the problem of low efficiency and high energy consumption. In view of the characteristics of strong coupling, non-linearity, and internal load in the process of microbial fuel cell grid connection, it is necessary to design the grid-connected unit of power electronic device. Based on the establishment of the microbial fuel cell stack model, the stability control and the constant power control scheme were designed for the chopper and inverter, respectively. The simulation results showed that the control strategy with the combination of voltage stabilizer and constant power can make a grid-connected system of all phase voltage and frequency output. The three-phase voltage U_abc was steady at 7 h and the voltage amplitude was controlled at roughly 380 V, according to the output voltage waveform. The value was 50 Hz, which satisfies the criteria for grid connection. Full article

(This article belongs to the Special Issue AC and DC Power Grids System Technologies: Analysis, Control and Practical Applications)

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15 pages, 1543 KiB

Open AccessArticle

A Modified Multiparameter Linear Programming Method for Efficient Power System Reliability Assessment

by Jing Zuo, Sui Peng, Yan Yang, Zuohong Li, Zhengmin Zuo, Hao Yu and Yong Lin

Processes 2022, 10(11), 2188; https://doi.org/10.3390/pr10112188 - 25 Oct 2022

Cited by 4 | Viewed by 1583

Abstract

Power systems face adequacy risks because of the high integration of renewable energy. It is urgent to develop efficient methods for power system operational reliability assessment. Conventional power system reliability assessment methods cannot achieve real-time assessment of system risk because of the high [...] Read more.

Power systems face adequacy risks because of the high integration of renewable energy. It is urgent to develop efficient methods for power system operational reliability assessment. Conventional power system reliability assessment methods cannot achieve real-time assessment of system risk because of the high computational complexity and long calculation time. The high computational complexity is mainly caused by a large number of optimal power flow (OPF) calculations. To reduce the computational complexity, this paper transfers the optimal power flow model as a multiparameter linear programming model. Then, the optimal power flow can be obtained by linear calculations. Furthermore, this paper proposes a state reduction method considering the importance index of transmission lines for further improving the calculation efficiency. Case studies are carried out on IEEE standard systems and a provincial power grid in China. Compared with the conventional reliability assessment method, the reliability assessment efficiency of the proposed method increases by 10–40 times, and the assessment error is less than 1%. Full article

(This article belongs to the Special Issue AC and DC Power Grids System Technologies: Analysis, Control and Practical Applications)

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15 pages, 6171 KiB

Open AccessArticle

The Total Low Frequency Oscillation Damping Method Based on Interline Power Flow Controller through Robust Control

by Jingbo Zhao, Ke Xu, Zheng Li, Shengjun Wu and Dajiang Wang

Processes 2022, 10(10), 2064; https://doi.org/10.3390/pr10102064 - 12 Oct 2022

Cited by 2 | Viewed by 1545

Abstract

The interline power flow controller (IPFC) can control the active power and reactive power of different lines in power system. To utilize the flexible control ability of IPFC and increase the damping characteristic of its controller AC system, this paper proposes a low-frequency [...] Read more.

The interline power flow controller (IPFC) can control the active power and reactive power of different lines in power system. To utilize the flexible control ability of IPFC and increase the damping characteristic of its controller AC system, this paper proposes a low-frequency oscillation (LFO) suppress method through IPFC. The LFO suppress method is designed by adding supplementary signals to the outer current control loop of IPFC. In addition to adding supplementary active power signals, the reactive supplementary signals are also added to related control loop, which is the total control scheme. To obtain the power system’s small signal model, the identification technology based on the PRONY algorithm is used. In addition, the robust control theory is also applied to make the controllers more adaptive. To verify the effectiveness of the proposed method, two controllers including both the active and reactive controllers are designed for in PSCAD software. Furthermore, the simulation results prove the proposed method can reach a better control effect and is also of robustness. Full article

(This article belongs to the Special Issue AC and DC Power Grids System Technologies: Analysis, Control and Practical Applications)

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