Reconfiguration Technique Research Articles

Power enhancement of PV system via physical array reconfiguration based Lo Shu technique

The consistent contribution of renewable resources towards power generation unquestionably fostered world’s energy transformation. Involvement and impact of solar Photovoltaic (PV) system in energy transition and socioeconomic growth have surpassed other resources in every aspect. Since the PV panels are highly susceptible to a very commonly occurring phenomenon called Partial Shading (PS); many array reconfiguration methods evolved in the recent past made a remarkable stride in offering solutions for partial shading. But most of the existing methods still lack in attaining an effective shade dispersion and power enhancement. Therefore, in this research work, a Lo Shu concept based physical array reconfiguration technique is proposed and employed for shade dispersion and power enhancement of standard four shade patterns. Further, to prove its astounding performance, a comparison with other eminent techniques such as Total Cross Tied (TCT), Su Do Ku, Dominance Square (DS) and Competence Square (CS) is carried out. The developed method provides highly satisfactory performance in every aspect like power enhancement, Fill Factor (FF) and energy savings. Further, a more substantial analysis based on additional performance metrics like Capacity Factor (CF), Performance Ratio (PR), Capture Loss (CL) and Execution Ratio (ER) is performed to prove the versatility of proposed methodology.

On Dynamic Service Function Chain Reconfiguration in IoT Networks

Network function virtualization (NFV) technology continues to gain more attention as a paradigm shift, and telecommunication services can be flexibly deployed and managed. Any service can be represented by a service function chain (SFC) that is a set of virtual network functions (VNFs) to be executed based on the strict order. The NFV-enabled SFCs applied in the future Internet-of-Things (IoT) networks emerge a challenging problem, particularly more and more IoT devices are trying to access their telecommunication services whenever and wherever, SFCs are needed to be dynamically and adaptively reconfigured, thus adapting to the service requests’ dynamics for lower resource consumption and higher revenue for Internet service providers (ISPs). In this article, we study the SFC dynamic reconfiguration problem (SFC-DRP) in the IoT networks, a discrete-time Markov decision process (DTMDP)-based IoT SFC-DRP is formulated by guaranteeing the QoS and resource constraints. We subsequently propose a novel deep Dyna-Q (DDQ) approach to solve this model. Our proposal has been evaluated with the obtained results demonstrating an average CPU root-mean-square error (RMSE) of 0.17, compared to 0.75 obtained while using the original approach. Moreover, our proposed SFC reconfiguration technique can approximate the performance of the integer linear programming (ILP) model within a polynomial time, and outperform the existing benchmarks in terms of the reconfiguration overhead and the resource utilization ratio from service provisioning, respectively.

Isolation enhanced MIMO PIFA system with multiple reconfiguration techniques

In this study, a reconfigurable, two-element, multiple-input multiple-output (MIMO) printed inverted-F antenna (PIFA) is presented with an enhanced isolation ability. The MIMO antenna system is designed using three different reconfiguration techniques that are based on positive-intrinsic-negative diodes, radio frequency micro-electromechanical switches and varactors. Their impact on the performance of the PIFA and the MIMO system is evaluated in terms of radiation characteristics, gain, power dissipated, radiation efficiency, linearity, biasing requirements and MIMO performance. Isolation between the two MIMO antenna elements is enhanced by integrating a reconfigurable band-reject filter within the ground plane between the radiating elements. The band-reject filter is reconfigured simultaneously with the radiating elements, hence resulting in less coupling and better isolation. The MIMO system along its various components is fabricated for the three different reconfiguration techniques and the comparison with predicted data shows great agreement.

Vanadium Dioxide for Reconfigurable Antennas and Microwave Devices: Enabling RF Reconfigurability Through Smart Materials

We present a comprehensive study of a new method to reconfigure, tune, and/or program antennas and radio-frequency (RF) devices. The method consists of using electrical signals to induce the solid-tosolid phase transition in vanadium dioxide (VO2) thin-film patterned structures that connect the device metallization layer with extensions, thus effectively changing the geometry of the device. Applied voltage pulses to a resistive heater electrically isolated from the antenna metallization layers increase the temperature of the VO2 strip across the phase transition. Hence, the VO2-biasing mechanism and the antenna are electrically decoupled, which enables an additional degree of freedom for antenna and microwave device engineers as the reconfiguration is no longer restricted by any biasing network limitations. Radiation patterns are also maintained unaffected. This decoupling adds into the design spectrum, applications that require wideband tuning, low-loss structures (e.g., arrays and reflectarrays), and even reconfigurable cloaks. The VO2 switch is arguably the smallest ever used to reconfigure an antenna, which requires further circuit element considerations. The presented method is validated through a series of antenna prototypes that demonstrate VO2 applicability on wire and aperture antennas. Details and challenges of the monolithic integration of VO2 thin films and resistive heaters for reconfigurable antennas, along with the measurement setup, are presented. Results unveil this new reconfiguration technique and suggest further applications, as the VO2 may also be activated optically.

The Impact of Reconfiguration on the Energy Performance of the Distributed Maximum Power Point Tracking Approach in PV Plants

The following two approaches can address the drawbacks associated with mismatching phenomena in photovoltaic (PV) plants: distributed maximum power point tracking (DMPPT) architecture and reconfigurable PV array architecture. Until now, these two approaches have represented alternative solutions. In this paper, for the first time, it is suggested that the two approaches can be used together. In particular, it will be shown how the joint adoption of the DMPPT and reconfiguration approaches can improve the performances of mismatched PV plants; here, performance is understood as the best compromise between the efficiency and reliability of the entire PV system. Numerical results confirm the above assumptions, providing the hints for the development of innovative reconfiguration techniques suitable for distributed applications.

Stochastic Modeling and Integration of Plug-In Hybrid Electric Vehicles in Reconfigurable Microgrids With Deep Learning-Based Forecasting

This paper investigates the impact of uncoordinated, coordinated, and smart charging of plug-in hybrid electric vehicles (PHEVs) on the optimal operation of microgrids (MGs) incorporating the dynamic line rating (DLR) security constraint. The DLR constraint, particularly in the islanding mode, influences the ampacity of MG feeders, when distribution lines reach their maximum capacity. To overcome any line outage or contingency situation, smart PHEVs are utilized to help improve the grid security. However, using PHEVs can cause higher power losses and feeder overloading issues. To address these concerns, a reconfiguration technique is employed in this paper. A heuristic algorithm, known as the collective decision-based optimization algorithm, is utilized to overcome the non-convexity and nonlinearity of the problem. The unscented transform technique is employed to model DLR uncertainties caused by solar radiation, load demand, and weather temperature, as well as PHEVs' uncertainties caused by varying charging strategies, numbers of PHEVs being charged, charging start time, and charging duration. Moreover, a deep learning gated recurrent unit technique is designed to forecast renewable power output for mitigating the uncertainties in renewable energy components. A modified IEEE 33-bus test network is deployed to evaluate the efficiency and performance of the proposed model.

Dual technique of reconfiguration and capacitor placement for distribution system

Radial Distribution System (RDS) suffer from high real power losses and lower bus voltages. Distribution System Reconfiguration (DSR) and Optimal Capacitor Placement (OCP) techniques are ones of the most economic and efficient approaches for loss reduction and voltage profile improvement while satisfy RDS constraints. The advantages of these two approaches can be concentrated using of both techniques together. In this study two techniques are used in different ways. First, the DSR technique is applied individually. Second, the dual technique has been adopted of DSR followed by OCP in order to identify the technique that provides the most effective performance. Three optimization algorithms have been used to obtain the optimal design in individual and dual technique. Two IEEE case studies (33bus, and 69 bus) used to check the effectiveness of proposed approaches. A Direct Backward Forward Sweep Method (DBFSM) has been used in order to calculate the total losses and voltage of each bus. Results show the capability of the proposed dual technique using Modified Biogeography Based Optimization (MBBO) algorithm to find the optimal solution for significant loss reduction and voltage profile enhancement. In addition, comparisons with literature works done to show the superiority of proposed algorithms in both techniques.

Optimal dual design based on capacitor placement and reconfiguration techniques for loss reduction and voltage enhancement

Distribution System Reconfiguration (DSR) and Optimal Capacitor Placement (OCP) are the most economical and beneficial techniques that have been used in the Radial Distribution Systems (RDSs) to increase the reduction of losses and to perform a better voltage improvement. The DSR technique is a search process to find the shortest path length between the substation and the loads to achieve a maximum reduction in real losses. The OCP technique is used to compensate the reactive power that is required for the inductive loads, which reduces the active and reactive losses and enhances the voltage for the system buses. The approach of combining these techniques provides more improvement than using them individually. In this paper, four cases are implemented that employs either a single or double approach to identify the design with the best performance. The single approach is either DSR or OCP technique as individual technique, while the double approach is either OCP technique for the reconfigured RDS or reconfiguration for the RDS after the application of OCP technique. The optimal selection of tie switches, size and location of capacitors in the individual and dual approaches are achieved by using Qualified Binary Particle Swarm Optimization (QBPSO) and Modified Grey Wolf Optimization (MGWO) algorithms. The four cases are tested for standard IEEE system 33-bus RDS under different loading conditions. The results show the superior performance of the optimal proposed approaches compared to the literature works. Furthermore, the optimal dual techniques have show more effectiveness for loss reduction and voltage enhancement over their individual techniques.

Optimal photovoltaic array reconfiguration for alleviating the partial shading influence based on a modified harris hawks optimizer

Mismatch power loss is the unfortunate problem created as a result of the partial shading phenomenon. To relieve the entire photovoltaic system from this issue, reconfiguring the photovoltaic modules of the considered photovoltaic array is proposed as a favorable solution to disperse the shadow regularly. Therefore, in the current work, a novel developed optimization algorithm named modified harris hawks optimizer is introduced aiming to provide the optimal reconfiguration pattern of the switching matrix to maximize the generated power from the array. The basic version of the harris hawks optimizer is implemented for the same problem over several stages of the analysis, as well. Rearrangements of four patterns of shadow (short broad, long broad, short narrow, and long narrow patterns) are implemented on 9 × 9 photovoltaic array. Moreover, the algorithm is also validated on another two shade patterns with 6 × 4 and 6 × 20 photovoltaic arrays are reported in the simulation part. The results of the proposed techniques are compared to those obtained by a total-cross-tied, competence square, particle swarm optimizer, and genetic-based reconfiguration techniques based on several metrics. The utilized measures are mismatch power, fill factor, percentage power loss, as well as percentage power enhancement. The analysis reveals that the introduced approach enhances the produced power by 33.274%, 27.79%, 6.99%, 7.197% over the first four shaded patterns, respectively and increases the generated power by 20%for the other shade patters. Further, the modified harris hawks optimizer proves its excellency in providing the optimal photovoltaic array configuration in less than 1 s. For intensive justification, the modified harris hawks optimizer reconfiguration approach is validated based on an experimental work for 9 × 9 photovoltaic array with twelve shade patterns during a day from 8 ante meridiem to 7 post meridiem with one hour step. Comparing the produced power based on the modified harris hawks optimizer arrangements to those of total-cross-tied and harris hawks optimizer schemes over the daily hours proves the superiority of the modified harris hawks optimizer interconnected system in generating the highest values of power with a uniform dispersion for the shadow and smooth characteristics with saving the energy by 12.569% compared with that produced by total-cross-tied across the day hours.

Power Loss Minimisation on 11kV Distribution Network using Feeder Reconfiguration

The Distribution System can be seen as the networking line that interfaces between the large power generators and transmission lines on one hand and the electricity consumers on the other. The system can exist in different topologies among which, the radial form is popular because of its simplicity and comparative low cost of design. The problem of poor power quality and instability has been a major power systems challenge especially in Nigeria. More reliable and stable power systems among other benefits can be enjoyed when system are optimized. Hence, this paper implements the feeder reconfiguration technique as an optimization procedure to minimize the technical losses on the Ondo Road 11kV Feeder Segment. MATLAB is employed to simulate the optimization process and the results showed that an average of 85.47% active power loss reduction on all phases is obtainable with the proposed technique leading to an estimated financial saving of ?639,999.75 per hour.

Power Loss Minimisation on 11kV Distribution Network using Feeder Reconfiguration

The Distribution System can be seen as the networking line that interfaces between the large power generators and transmission lines on one hand and the electricity consumers on the other. The system can exist in different topologies among which, the radial form is popular because of its simplicity and comparative low cost of design. The problem of poor power quality and instability has been a major power systems challenge especially in Nigeria. More reliable and stable power systems among other benefits can be enjoyed when system are optimized. Hence, this paper implements the feeder reconfiguration technique as an optimization procedure to minimize the technical losses on the Ondo Road 11kV Feeder Segment. MATLAB is employed to simulate the optimization process and the results showed that an average of 85.47% active power loss reduction on all phases is obtainable with the proposed technique leading to an estimated financial saving of ₦639,999.75 per hour.

A Novel Distributed Cloud-Fog Based Framework for Energy Management of Networked Microgrids

Power grid resilience, reliability, and sustainability can be improved by decomposing the large-scale grids into the Networked Microgrids (NMGs). However, different MGs may have different roles and policies. Hence, in comparison with conventional networks, optimal energy management, as well as the grid reconfiguration of the NMGs is more completed and challenging. This article develops a three-layer cloud-fog computing architecture for energy management of reconfigurable NMGs considering dynamic thermal line rating (DLR) constraint. DLR can potentially affect the ampacity of feeders, especially in the islanding mode, when lines approach their maximum capacity. In order to avoid any feeder contingency in the off-grid (islanded) mode, the reconfiguration technique as well as the cloud fogs framework are employed to change the topology of the NMG network swiftly and release the line capacity. Finally, the proposed problem is formulated as a mixed-integer linear optimization problem considering DLR constraint. The proposed model is examined on a modified IEEE 69 bus test network. Results demonstrate the high performance and effectiveness of the developed model and also validate its reliability and economic assets.

A model-driven approach for the verification of an adaptive service composition

The development of web service compositions is a complex task that needs coherent mechanisms in order to maintain the quality of the provided business process and to satisfy user needs. This paper proposes a development process of an adaptable composed web service and mainly focuses on the reliability and the performance properties. It explores the model driven architecture transformation technique in order to formally model the whole service orchestration using the timed coloured Petri net formalism. The software CPN Tools offers, among others, the ASK-computational tree logic, the model checking technique and several monitors that will be exploited to describe and verify different properties at design time. They will also be used via access/CPN library in order to reason about the reconfiguration technique at runtime. An example of an identity card management process is given to prove the feasibility of the proposed solution.

Optimal Photovoltaic Array Dynamic Reconfiguration Strategy Based on Direct Power Evaluation

In actual operation, photovoltaic arrays inevitably encounter shadow problems, resulting in a power output decline and multiple peaks in the output characteristics. The effect of partial shade can be satisfactorily reduced by photovoltaic array reconfiguration. Almost all current reconfiguration techniques are based on the irradiance equalization principle. However, by analyzing the output characteristics of photovoltaic array, it is found that the irradiance equalization principle improves the output power by increasing only the minimum row current without considering the effect of the voltage, so the reconfiguration techniques based on this principle cannot obtain the global optimal configuration under some partial shading conditions. In order to maximize the output power of photovoltaic array under any partial shaded condition, this paper proposes a reconfiguration strategy based on direct power evaluation. In this approach, the reconfiguration problem is formulated as a 0-1 multi-knapsack problem, and a novel mathematical model is established to directly evaluate the maximum output power of photovoltaic array. Then, the optimal reconfiguration scheme is determined by solving the mathematical model. Finally, the effectiveness of the proposed reconfiguration strategy is proved in theory and simulations.

An Integrated Approach and Tool Support for the Design of FPGA-Based Multi-Grain Reconfigurable Systems

Dynamic partial reconfiguration technique can be used to modify regions of an FPGA as large as the whole reconfigurable fabric or as small as individual logic elements. However, FPGA manufacturers have focused their efforts on designing tools that support the design of monolithic reconfigurable accelerators spanning large regions of the device. Nevertheless, in some applications, it is enough to fine-tune the accelerators' behavior instead of changing them entirely. In these cases, rather than allocating new accelerators, it is possible to reconfigure individual logic elements of the circuit, such as look-up tables or flip-flops. There is also an intermediate approach that targets the reconfigurability of accelerators composed of several tightly interconnected modules, such as overlays. In those architectures, it is possible to reconfigure only the modules that differ between the existing accelerator versions, thus reducing the reconfigurable footprint granularity. This article proposes a classification of the approaches above, categorizing them as coarse, fine, and medium grain, respectively. There are neither commercial nor academic tools supporting multi-grain reconfiguration to take advantage of each granularity strength on commercial FPGAs. Differently, this article proposes a tool called IMPRESS, that provides design-time and run-time support for multi-grain reconfiguration in Xilinx 7 Series FPGAs. Specific criteria are provided to combine the different granularity levels, trading off the benefits in terms of flexibility and performance, with different design and run-time costs. Two use cases in the image processing and neural network domains have been implemented to show how IMPRESS can build multi-grain reconfigurable systems.

A typical review on static reconfiguration strategies in photovoltaic array under non-uniform shading conditions

Maximum power extraction from the photovoltaic (PV) system plays a critical role in increasing efficiency during partial shading conditions (PSCs). It directly reduces the output power of the PV array. There are different factors like, bypass diode configuration, array size, array configuration, shade intensity, environmental conditions etc. affecting on the performance of solar photovoltaic panel. Furthermore, series (S), parallel (P), series-parallel (SP), total-cross-tied (TCT), bridge-linked (BL), and honey-comb (HC), etc. are the various configurations to deal with mentioned issues. But these PV array configurations are also having drawbacks like low dispersion factor, mismatch losses, line losses under partial shading condition. To overcome these issues, the reconfiguration of the PV array is one of the effective measures. A comprehensive study of literature shows that PV modules are connected under different reconfigured schemes namely Sudoku, Optimal Sudoku, Magic square, zig-zag, Skyscraper, etc. In this paper, a comprehensive review is performed to highlight the advantages and limitations of each scheme. This study can be used as a sort of viewpoint to address the advancement in this area since some parameter comparison is made at the end of every technique, which might be a prominent base-rule for picking the most gainful sort of reconfiguration technique for further research.

A Robust Strategy Based on Marine Predators Algorithm for Large Scale Photovoltaic Array Reconfiguration to Mitigate the Partial Shading Effect on the Performance of PV System

Large-scale solar photovoltaic (PV) plants play an essential role in providing the increasing demand for energy in recent time. Therefore, in the purpose of achieving the highest harvested power under the partial shading conditions as well as protecting the PV array from the hot-spot calamity, the PV reconfiguration strategy is established as an efficient procedure. This is performed by redistribution of PV modules according to their levels of shading. Motivated by this, the authors in this article have introduced a novel population-based algorithm that is known as marine predators algorithm (MPA) to restructure the PV array dynamically. Moreover, a novel objective function is introduced to enhance the algorithm performance rather than utilizing the regular weighted objective function in the literature. The effectiveness of the proposed algorithms based on the novel objective function is evaluated using several metrics such as fill factor, mismatch losses, percentage of power loss, and percentage of power enhancement. Besides, the obtained results are compared with a regular total-cross-tied (TCT) connection, manta ray foraging optimization (MRFO), harris hawk optimizer (HHO) and particle swarm optimizer (PSO) based reconfiguration techniques. Furthermore, to demonstrate the suitability of the proposed methods, large scale PV arrays of $16\times16$ and $25\times25$ are considered and evaluated. The results reveal that MPA enhanced the PV array power by percentage of 28.6 %, 2.7 % and 5.7 % in cases of $9\times9$ , $16\times16$ and $25\times25$ PV arrays, respectively. The comprehensive comparisons endorse that MPA shows a successful shade dispersion; hence the number of multiple peaks in the PV characteristics has reduced, and high values of power have been harvested with least mean execution time in comparison with PSO, HHO and MRFO. Moreover, the Wilcoxon signed-rank test has been accomplished to confirm the reliability and applicability of the proposed approach for the PV large scale arrays as well.

A Novel Adaptive Topology for Photovoltaic Array under Partial shadings to Increase Energy Yields

 Abstract- This paper proposed a new adaptive reconfiguration technique for total cross-tied (TCT) PV array to reduce the loss of mismatch and to increase energy output under partial shadings (PS) through MATLAB-SIMULINK. During this work, the electrical connections between PV modules are modified with the help of proposed pattern search algorithm to maintain equal currents in each row on the basis of shading conditions, thus increasing the current of the array. The proposed algorithm classifies the possible number of PV array connections for adaptive system and determines the optimal connection between them. This approach is implemented on a 3A—3 array and evaluated under various possible conditions of shadings. In contrast, this proposed method is validated with current reconfiguration methods and compares the global maximum power point (GMPP), shadow loss, and fill factor. Based on the findings of this study, it is acknowledged that the proposed adaptive method strengthened the TCT array energy yield compared to other methods under partial shadings.

A BBO PSO based Hybrid Technique for Distribution System Feeder Reconfiguration

A cooperative strategy to reconfigure the feeder network by maximizing the location and volume of the distribution generator (DG) in the power system was addressed in this report. The new feature of the proposed method is the integrated output of the Biography Based Optimization (BBO) and PSO techniques. The above methods are the optimization techniques used to configure the radial distribution system for the optimal position and capacities of the DG. For determining the optimum position and strength of the DG, the BBO algorithm includes radial distribution network voltage, actual and reactive energy. The input parameters of BBO are classified into sub settings here and are allowed as the optimization of the PSO algorithm. The PSO synthesizes the problem and uses sub-parameters to create the sub-solution. The method of BBO migration and mutation is used to determine the optimal position and ability of DG for the sub solution of PSO. The cooperative strategy introduced is then applied on the system MATLAB / Simulink, and the usefulness is evaluated using BBO and PSO techniques. The findings of the analysis demonstrate the strength of the solution suggested and affirm its capacity for resolving the problem.

Electrical Reconfiguration Techniques for Frequency Agility in Patch Antennas

Wireless Systems are subjected to overwhelming advancements with the exponential demands in the field of Communication. This has led to the evolution of Reconfigurable antennas which gained enough significance as they are capable of modifying them.selves to different operating frequencies, patterns or polarizations. Out of these, Frequency Reconfigurable Antennas which can be operated at multi-frequency environment have been found to have a wide range of applications. The reconfiguration can be achieved using various switching mechanisms like, electrical, optical, etc. These are found to support various communication standards, ensure effective utilization of spectrum, reduce system complexity and hence cost. The recent researches on frequency reconfigurable antennas using electrical switches are analyzed in this paper based on their performances and a comparison on various switching techniques is presented.