Proposed Reconfiguration Method Research Articles

Mismatch losses mitigation of PV-TEG hybrid system via improved RIME algorithm: Design and hardware validation

The heat dissipated during the working process of the photovoltaic (PV) system may cause the working temperature to be too high, which will affect the power generation efficiency of the system. To make full use of solar energy and maintain suitable operating temperature, this article designs an array model of stacked photovoltaic-thermoelectric generation (PV-TEG) hybrid power generation system. Meanwhile, considering that partial shielding conditions (PSC) may lead to component mismatch, power reduction and so on, this paper proposes a PV-TEG hybrid system reconfiguration method based on the improved RIME (IRIME) algorithm. Firstly, according to the irradiance data on the PV modules, the IRIME algorithm is used to obtain the optimal electrical connection scheme. Then, according to the optimal scheme, the electrical connection of the hybrid system is reconfigured to achieve the purpose of suppressing the multi-peak phenomenon in the generation process and increasing the power generation. To verify the feasibility of the IRIME algorithm, ten PSCs are simulated on two PV-TEG hybrid systems of different scales to carry out simulation experiments. The simulation results show that the average output power of the hybrid system in both 6 × 6 and 6 × 10 scales has been improved by 26.76% and 30.47% after reconfiguration, respectively. Meanwhile, to further test the performance of this method, this article used PSO, GA, ACO, BWO, GWO, ALO and RIME for comparative experiments. The experimental results showed that the IRIME algorithm has better universality in the reconfiguration problem of hybrid systems. In addition, this article utilized the RTLAB platform to conduct hardware in the loop (HIL) experiments on the proposed reconfiguration method, which further verified the hardware feasibility of the method.

Pavement PV array reconfiguration strategy based on traveling salesman problem

The dynamic random vehicle shadow caused by high-speed vehicles on the pavement PV arrays not only easily induces the series and parallel mismatch of the PV array on the pavement, resulting in power loss, but also leads to the complex fast-changing multi-peak phenomenon of its output characteristics, which increases the difficulty of the maximum power point tracking control and intensifies the power loss. To address this issue, this paper proposes a novel dynamic reconfiguration strategy for pavement PV arrays based on the traveling salesman problem (TSP). In the proposed method, the optimal pavement PV array reconfiguration is transformed into a traveling salesman problem. Through comparative experiments, the simulated annealing (SA) algorithm is verified to be able to effectively solve the reconfiguration problem based on TSP. Finally, the simulation and experiment results show that the proposed reconfiguration method can reduce the number of local maximum power points, improve the global maximum power of pavement PV array, and effectively improve the power generation efficiency of the PV system.

Dynamic reconfiguration of AC/DC hybrid distribution network considering non-ideal linear BES model

The charging and discharging process of battery energy storage (BES) directly affects its cycle aging. Therefore, considering the cycle aging cost and demand response of BES, this paper proposes a dynamic reconfiguration method of AC/DC hybrid distribution network. By sampling the operation area of charging and discharging power, the BES model in the non-ideal state is reconstructed into a linear model in the convex envelope set of sampling points. On this basis, the cycle aging cost models based on the cumulative throughput and discharge depth are established respectively, and the AC/DC hybrid distribution network reconfiguration model with the minimum comprehensive cost is constructed, and the mixed integer second-order cone programming method is used to solve it. The effectiveness and economy of the proposed reconfiguration method for AC/DC hybrid distribution network are verified by simulation on a modified 33-bus and 70-bus system.

Reconfiguration of nondestructively readable superconductor memory by direct injection of magnetic flux to storage loop

In this study, we demonstrate a novel method for the reconfiguration of a nondestructively readable memory cell for superconductor integrated circuits. The proposed reconfiguration method involves the direct injection of flux quantum to the storage loop of the memory cell, which has been achieved using interface circuits in previous studies. By applying this method, the footprint of the superconductor memory cell can be reduced by half. We experimentally demonstrate the proof-of-concept of the investigated reconfiguration method. We expect that the memory cell reconfigured using the proposed method will be suitable for building large-scale lookup tables using superconductor circuits.

Photovoltaic Array Reconfiguration under Partial Shading Conditions Based on Short-Circuit Current Estimated by Convolutional Neural Network

Partial shading conditions (PSC) have negative effects on the operation of photovoltaic (PV) systems. In this paper, a PV array reconfiguration method is developed to minimize power losses of PV arrays under partial shading conditions. The proposed reconfiguration method is based on equalizing the reduction of the short-circuit current of the PV modules in the PV array. Eight state-of-the-art Convolutional Neural Network models are employed to estimate the effect of shading on the short-circuit current of a PV module. These models include LeNet-5, AlexNet, VGG 11, VGG 19, Inception V3, ResNet 18, ResNet 34, and ResNet 50. Among eight models, the VGG 19 achieves the best accuracy on 1842 sample images. Therefore, this model is used to estimate the ratio of the actual short-circuit current and the estimated short-circuit current in four studied shading scenarios. This ratio decides the switching rule between PV modules throughout the PV array under PSC. A 2×2 experimental PV array shows that the proposed reconfiguration method improves the output power from 5.81% to 25.19% in four shading patterns. Accordingly, the power losses are reduced from 1.32% to 13.75%. The power improvement and the reduction of power losses of the proposed dynamic PV array reconfiguration system under four case studies demonstrates its effectiveness in addressing the effects of PSC on the PV array.

A new contour balancing rearrangement technique to enhance the solar PV array power under a realistic partial shading condition

Under partial shading conditions, the solar photovoltaic (PV) array receives an irregular pattern of solar light intensity which results in the creation of multiple peaks in the power vs voltage (P-V) and current vs voltage (I-V) plot and ultimately leads to hot spots creation and reduced power generation. Therefore, in this paper, redistribution of the shadow effect is assessed using a newly proposed reconfiguration method for the PV array called Contour Balancing Rearrangement (CBR) method. The proposed CBR method is based on the “Smash n′ Throw” approach which is applied to reconfigure the total-cross-tied (TCT) topology of the PV array that redistributes the shading pattern in such a way that the average irradiance of each row is almost the same. Further, a novel pragmatic dynamic cloud model is formulated to realize the partial shading condition as in realistic form at a particular location of the earth’s surface. For a more realistic analysis, the movement and acceleration of moving clouds are taken into account along with the coordinates of the place of interest for more accurate values of solar irradiation. Furthermore, different comparative studies are also carried out among the proposed and existing methods of various PV array reconfiguration methods to show the efficacy.

A Novel Magic Square Based Physical Reconfiguration for Power Enhancement in Larger Size Photovoltaic Array

Partial shading is the prevailing problem in Photovoltaic arrays. It results in severe consequences like multiple peaks in electrical characteristics, hot spots on Photovoltaic panels, disruptions in tracking maximum power and reduced output power. During most of the shading conditions, the shade concentrates in a particular area of the Photovoltaic (PV) array. This shading reduces PV array efficiency. Several physical reconfiguration schemes based on puzzle patterns are proposed to minimize this problem. The majority of these methods deduced to fixed PV array size for which the algorithm has proposed. Further, few of them are applicable only to lower size PV array. This paper presents a novel magic square puzzle for scattering the shade in the PV array to overcome the above constraints. In this method, the module physical position remains the same. However, the electrical wiring alters according to the puzzle pattern to change the row current in the Total-Cross-Tied topology PV array. The efficiency of the proposed system is examined under different shading conditions using characteristic curves. The relative analysis was carried between the conventional Total-Cross-Tied topology and the proposed Novel Magic Square-based Total-Cross-Tied topology. The MATLAB/SIMULATION results demonstrate that placing the modules according to the proposed reconfiguration method minimizes the peaks and enhances the output power (11.53%), with the global peak always on the right side of the PV curve under partial shading conditions.

Switching Matrix Enabled Optimal Topology Reconfiguration for Maximizing Power Generation in Series–Parallel Organized Photovoltaic Systems

Mismatch losses (ML) problem can directly reduce the power generation of a photovoltaic (PV) array as well as complicate maximum power point tracking (MPPT) algorithms by causing multiple peaks to appear in the P-V characteristic. Hence, PV array reconfiguration techniques have become highly popular to minimize the ML of PV arrays. In this article, an optimal dynamic topology reconfiguration method based on a switching matrix is presented for series–parallel (SP) interconnected PV array to mitigate the ML, thereby maximizing the power generation of the PV array. The design of the switching matrix is presented that enables each string of the PV array to be divided into two sections to carry out the efficient dynamic topology reconfiguration with improved flexibility and scalability. The proposed reconfiguration method is assessed and compared with the SP scheme and the recently developed cross diagonal view method. The effectiveness of the proposed solution for the TCT scheme is also confirmed through simulation experiments. The numerical results indicate that the multiple peaks on P-V curves can be reduced and MPPT can be implemented with a simple control algorithm. Additionally, the maximum power generation improved by 20.13% and 14.39% on average compared to the SP scheme and TCT scheme, respectively, for different mismatch conditions of partial shading and random PV module failures.

Fault Reconfiguration of Distribution Networks with Soft Open Points Considering Uncertainties of Photovoltaic Outputs and Loads

Conventional fault reconfiguration methods assume determinant values for loads and distributed generators outputs, which may lead to a reconfiguration solution that cannot satisfy operational constraints. This paper proposes a fault reconfiguration method for distribution networks with soft open points (SOPs) considering the uncertainties of photovoltaic (PV) output power and loads. Firstly, a fast probabilistic power flow method based on voltage sensitivity for distribution networks with SOPs is proposed to evaluate each reconfiguration scheme. Then a fault reconfiguration model considering uncertainties of PV output powers and loads is formulated and solved to minimize load shedding and line losses. The effectiveness of the proposed reconfiguration method is verified using the modified 33 and 69-bus distribution systems. The proposed method is shown to be very fast and can provide reliable reconfiguration schemes satisfying all system operation constraints.

Power optimisation of small scale SPV array using field programmable reconfiguration topology for dynamic non‐uniform illumination state

The power output of the solar-photovoltaic (SPV) array is affected significantly by non-uniformly incident solar radiation. Such non-uniform illumination (NUI) condition(s) occur due to shadows of terrestrial structures (like buildings, trees, etc.) or through the creation of hotspot(s) in the contribution of moisture-dust accumulation, bird droppings, etc. which are predictable in nature. Furthermore, projected images of cloud(s) also cause NUI impact which is unpredictable and is/are subject to variables such as 3-D cloud coverage, cloud density, wind speed, etc. Literature also affirms that SPV array architecture plays a critical role in NUI effect mitigation. The novelty of this paper is the introduction of switching network system with the flexibility in the arrangement of the SPV panel series–parallel connections as per solar light intensity, NUI pattern, and data obtained from panel's peripheral light sensors. The field programmable reconfiguration strategy proposed here will get the power vs voltage curve and current vs voltage curve to identify maximum power-point. Multiple NUI patterns are simulated in MATLAB with variance in SPV array matrix and peripheral sensor matrix. This proposed reconfiguration method is cost-effective and includes embedded devices that could be widely implemented for domestic as well as commercial applications with the nested sub-array scheme.

Cost Effective Offline Reconfiguration for Large-Scale Non-Uniformly Aging Photovoltaic Arrays Efficiency Enhancement

In the past decades, a huge number of large-scale photovoltaic (PV) plants have been constructed all around the world. However, the capital and operational costs can be high, which limits their widespread applications. Because the installed PV modules often operate in harsh environments (i.e. storm, high temperature, dust, hail, etc.), non-uniform aging phenomena of PV modules cannot be avoided and it impacts adversely on the performance of PV plants, especially in the middle and late periods of their service life. This paper develops an offline PV module reconfiguration strategy for the non-uniform aging PV array to mitigate this effect. In order to maximize the economic benefit, electricity price and labor cost are considered in the offline reconfiguration. The Branch-and-Bound based optimization algorithm is proposed to find the highest economic benefit. In order to verify the proposed algorithm, MATLAB software-based modelling and simulation have been performed in four case studies, in which a typical 42kW PV array with 7 × 20 connection is employed in a testing benchmark, and the manpower cost and electricity price in USA, UK, China and Turkey are considered in the case study. The results demonstrate that the economic benefit from a non-uniformly aged PV array is further enhanced with the proposed reconfiguration method.

Dynamic Reconfiguration of Multiobjective Distribution Networks Considering DG and EVs Based on a Novel LDBAS Algorithm

Aiming to improve the operation economy and power quality of distribution systems subject to the fluctuating and stochastic power outputs of distributed generation (DG) units and electric vehicles (EVs), a multiobjective optimization model for network reconfiguration and its corresponding solution method are proposed. First, a dynamic reconfiguration model is constructed based on the power loss rate (PLR) as well as the active power loss, the load balancing index and the maximum node voltage deviation, which serve as the optimization indexes. Second, the Levy flight and chaos disturbed beetle antennae search (LDBAS) algorithm is presented based on the grey target decision-making technique, which can not only improve the computational efficiency but also find the most satisfactory solution for the proposed dynamic reconfiguration model. Considering the uncertainties of loads and DG outputs, the influence on the load curve of EV connecting to the distribution network at different penetration rates and under different charging/discharging modes is analysed. Additionally, the modified IEEE 33-bus and 118-bus test radial distribution networks are simulated to verify the effectiveness and superiority of the presented reconfiguration model and the improved LDBAS method, and the results illustrate that the proposed reconfiguration method can improve the operation economy and power quality of the distribution system and encourage the penetration of EVs.

Reconfiguration of NPC Multilevel Inverters to Mitigate Short Circuit Faults Using Back-to-Back Switches

The main focus of this paper is to propose a reconfiguration method to mitigate short circuit faults in a neutral point clamped multilevel inverter which is widely used as a power conversion system with distributed energy resources. Existing reconfiguration methods use either a redundant strategy or need a large number of additional devices pre-installed in the circuit; these will increase the bulk and complexity of the system. Most existing control-strategy-based methods distort the phase-toneutral voltage, which results in degradation of power quality. To maintain control-strategy-based reconfiguration, avoid significant change to the circuit topology, and avoid phase voltage distortion, a new and practical reconfiguration method is proposed in this paper. The proposed method is applicable to neural point clamped (NPC) multilevel inverters at any voltage level and can mitigate short circuit faults in any device. A technique of switching series connected switches is selected to combine with the proposed reconfiguration method since it's a practical design consideration for realistic implementation. MATLAB/Simulink is used to simulate a five-level NPC inverter with non-idealities to verify the proposed reconfiguration method. A five-level NPC is also built and tested to experimentally verify the proposed method. Short circuit faults are injected to different devices and the proposed method is verified to quickly and effectively recover the NPC inverter from these faulty conditions.

How the structure of system problems influences system behavior

We consider the possibility to explain manifestations of collective intelligence via the presence of structure in the set of tasks may being fulfilled. A distributed system corresponds to a lattice of tasks that the system can fulfill. On this lattice, we define an external multiplication operation for lattice elements and respective operations of linear logic. The implication operation is used to choose the version of system reconfiguration, i.e., choose an executor for a new task. We show that this choice is to a large extent defined by the structure of the lattice of tasks and the definition of the multiplication operation on it. The proposed reconfiguration method is applied to an example of operation for a group of janitor robots.

Low voltage ride-through strategies for doubly fed induction machine pumped storage system under grid faults

Pumped storage units bring stability to the electrical power system, so they must remain connected to the grid even during grid faults. In this paper, the authors propose efficient and simple solutions for a doubly fed induction machine pumped storage (DFIMPS) system during grid faults. In case of balanced grid faults, a control reconfiguration strategy is introduced and a hardware solution is applied in the case of unbalanced grid faults. The reconfiguration strategy consists of a commutation between different control strategies; when a balanced grid voltage fault occurs during pumping mode, the control algorithm switches to the synchronization one but based on the new grid conditions. So the proposed reconfiguration method reduces the negative impacts of grid fault occurrence on the DFIMPS system by cancelling rotor and stator over-currents and decreasing the electromagnetic torque and stator power oscillations. Simulation results carried out on a 4 kW DFIMPS system illustrate the effectiveness of the proposed approach.

Model-Driven Development of Reconfigurable Protocol Stack for Networked Control Systems

In networked control systems (NCS), the performance degradation introduced by the heterogeneous and dynamic environment has intensified the need for reconfigurable protocol stacks (RPS). In this paper, an IEC61499-based method is proposed for the model-driven development of RPS. The method is enabled by defining a novel RPS function block (FB), which unifies the communication behavior and interface of nodes in NCS. Beyond existing communication FBs in IEC61499, the parameter reconfiguration of routing and scheduling table in RPS FB is highlighted as the core of communication layer function to adapt environment and system variations. Furthermore, the method allows for the code reconfiguration on Java algorithms in RPS FB under different application requirements. Through porting the Java virtual machine on different platforms, the code reconfiguration is implemented by reloading the .class file for a specified protocol FB. A case study on the embedded platform, such as DSP/BIOS and ARM/Linux, is conducted to demonstrate the effectiveness and feasibility of the proposed reconfiguration method for maintaining stable and predictable behavior in NCS.

A novel power system reconfiguration for a distribution system with minimum load balancing index using bacterial foraging optimization algorithm

In this paper, the objective of minimum load balancing index (LBI) for the 16-bus distribution system is achieved using bacterial foraging optimization algorithm (BFOA). The feeder reconfiguration problem is formulated as a non-linear optimization problem and the optimal solution is obtained using BFOA. With the proposed reconfiguration method, the radial structure of the distribution system is retained and the burden on the optimization technique is reduced. Test results are presented for the 16-bus sample network, the proposed reconfiguration method has effectively decreased the LBI, and the BFOA technique is efficient in searching for the optimal solution.

Reliability-oriented distribution network reconfiguration considering uncertainties of data by interval analysis

This paper presents a new reliability-oriented reconfiguration method to enhance distribution system performance. The major purpose is to deal with imprecision and ambiguity in reliability inputs, electrical parameters and load data. The presented method uses the interval analysis techniques to enclose data uncertainties and to maximize the possibility of reliability improvement and/or loss reduction. Case studies have demonstrated the effectiveness and efficiency of the proposed reconfiguration method.

An efficient hybrid evolutionary algorithm based on PSO and HBMO algorithms for multi-objective Distribution Feeder Reconfiguration

This paper introduces a robust searching hybrid evolutionary algorithm to solve the multi-objective Distribution Feeder Reconfiguration (DFR). The main objective of the DFR is to minimize the real power loss, deviation of the nodes’ voltage, the number of switching operations, and balance the loads on the feeders. Because of the fact that the objectives are different and no commensurable, it is difficult to solve the problem by conventional approaches that may optimize a single objective. This paper presents a new approach based on norm3 for the DFR problem. In the proposed method, the objective functions are considered as a vector and the aim is to maximize the distance (norm2) between the objective function vector and the worst objective function vector while the constraints are met. Since the proposed DFR is a multi objective and non-differentiable optimization problem, a new hybrid evolutionary algorithm (EA) based on the combination of the Honey Bee Mating Optimization (HBMO) and the Discrete Particle Swarm Optimization (DPSO), called DPSO–HBMO, is implied to solve it. The results of the proposed reconfiguration method are compared with the solutions obtained by other approaches, the original DPSO and HBMO over different distribution test systems.

Control Reconfiguration of Discrete Event Systems With Dynamic Control Specifications

This paper defines a reconfiguration method for the class of discrete-event systems (DES) that is subject to linear constraints as their control specifications. Some existing methods for enforcing these constraints make use of Petri-net P-invariants for controller synthesis. These methods are quite appealing because their computational complexity is much more tractable than most other methods for controller synthesis. However, a common limitation of all existing P-invariant-based control architectures for DES plants is the assumption that the linear constraints defining the control specification of the plant do not change over time. Here, we relax this assumption and allow the control specifications to change during controller runtime. Under certain assumptions on DES behavior, we automatically reconfigure the DES controller after the control specification is changed. In addition, if the current state of the controlled DES has become infeasible under the new control specification, we automatically generate a so-called plant reconfiguration procedure whose execution leads the system back to a feasible state. This reconfiguration procedure is optimal in that it seeks to minimize the cost of reconfiguration actions through an Integer Programming (IP) model. The objective function of the IP model can be used to generate reconfiguration solutions that meet some desired properties. Depending on the cost of each reconfiguration action, a minimum cost reconfiguration solution may use only actions contained in the current plant configuration (an internal response), or ask for a change in the plant configuration, for instance, by adding new resources (an external response), or a combination of both strategies. Finally, we illustrate our method by applying it to a hospital control system example. Note to Practitioners-This paper proposes a dynamic reconfiguration framework that can revise the operations of systems whose control requirements change over time. The proposed framework can be applied to systems that satisfy the following two assumptions. First, the behavior of the system under study is described in terms of a set of discrete states and events. Events will cause the system to transition between states. Second, the control requirements must be expressed by linear equalities and inequalities on the system states. Under these circumstances, the proposed framework can identify an optimal transition to a new control policy that satisfies the new control requirements. Moreover, the system under consideration will continue operating while this transition is taking place. One application of this method is in modifying hospital control strategies when a hospital experiences unexpected events. In this case, the hospital operations-such as patient handling, resource assignment, and procedure scheduling-can be represented by discrete state models (e.g., Petri nets). Constraints on these operations can be modeled by linear inequalities on hospital and patient state. Upon a change in the constraints, the proposed reconfiguration method revises the hospital control strategies. For example, a shift in the hospital service demands (e.g., an increase in the flow of patients to the hospital due to a mass casualty situation) can be translated to changes in the constraints. In this case, the hospital operations must be revised to accommodate the new constraints without disrupting the operation of the hospital. The reconfiguration method of this paper provides a framework for modeling the reconfiguration steps and for calculating the least cost reconfiguration solution.