Reconfiguration Of Distributed Systems Research Articles

An Efficient Framework for Optimal Allocation of Renewable Energy Sources in Reconfigurable Distribution Systems With Variable Loads

An Efficient Framework for Optimal Allocation of Renewable Energy Sources in Reconfigurable Distribution Systems With Variable Loads

Retraction Notice: A Directed Acyclic Graph Based Architecture for Optimal Operation and Management of Reconfigurable Distribution Systems With PEVs

Retraction Notice: A Directed Acyclic Graph Based Architecture for Optimal Operation and Management of Reconfigurable Distribution Systems With PEVs

Multi-Objective Framework for Optimal Placement of Distributed Generations and Switches in Reconfigurable Distribution Networks: An Improved Particle Swarm Optimization Approach

Distribution network operators and planners face a significant challenge in optimizing planning and scheduling strategies to enhance distribution network efficiency. Using improved particle swarm optimization (IPSO), this paper presents an effective method for improving distribution system performance by concurrently deploying remote-controlled sectionalized switches, distributed generation (DG), and optimal network reconfiguration. The proposed optimization problem’s main objectives are to reduce switch costs, maximize reliability, reduce power losses, and enhance voltage profiles. An analytical reliability evaluation is proposed for DG-enhanced reconfigurable distribution systems, considering both switching-only and repairs and switching interruptions. The problem is formulated in the form of a mixed integer nonlinear programming problem, which is known as an NP-hard problem. To solve the problem effectively while improving conventional particle swarm optimization (PSO) exploration and exploitation capabilities, a novel chaotic inertia weight and crossover operation mechanism is developed here. It is demonstrated that IPSO can be applied to both single- and multi-objective optimization problems, where distribution systems’ optimization strategies are considered sequentially and simultaneously. Furthermore, IPSO’s effectiveness is validated and evaluated against well-known state-of-the-art metaheuristic techniques for optimizing IEEE 69-node distribution systems.

Solar-DG and DSTATCOM Concurrent Planning in Reconfigured Distribution System Using APSO and GWO-PSO Based on Novel Objective Function

The concurrent planning of multiple Distributed Generations (DGs), consisting of solar-DG and DSTATCOM with reconfiguration in IEEE 33 and 69 bus Radial Distribution Network (RDN), using Adaptive Particle Swarm Optimization (APSO) and hybrid Grey Wolf-Particle Swarm Optimization (GWO-PSO), is reported in this paper. For this planning, a novel multiple objective-based fitness-function (MOFF) is proposed based on various performance parameters of the system, such as power losses (both active, as well as reactive loss), system voltage profile, short circuit level of line current (SCLLCurrent), and system reliability. The economic perspective of the system has also been considered based on the various costs, such as fix, loss, and Energy Not Supplied (ENS) cost. Two case studies have been presented on IEEE 33 and 69 bus RDN to validate the efficacy of the proposed methodology. The results analysis of the system shows that better performance can be achieved with the proposed technique for 33 and 69 bus RDN, using GWO-PSO rather than APSO. From this results analysis, a vital point is noticed that the SCLLCurrent is reduced, which causes the short-circuit (fault) tolerance capacity (level) of the RDN to become enhanced. Finally, the comparative analysis of the obtained results, using the proposed method with other methods that exist in different literature, reveals that the proposed method has performed better from a techno-economic prospective.

Stochastic Optimal Sizing of Plug-in Electric Vehicle Parking Lots in Reconfigurable Power Distribution Systems

Charging demand of plug-in electric vehicles (PEVs) can cause reliability and operational challenges in power distribution systems. The aggregated charging control of PEVs in the parking lots (PLs) may alleviate the challenges, if the place and size of PEV PLs are optimally determined. This paper develops a stochastic framework for finding optimal location and sizing of PLs as well as optimal charging profile of PEV PLs with the vehicle to grid capability in a reconfigurable distribution system. The main aims are to reduce distribution system losses and enhance network reliability, subject to numerous constraints of the power distribution system, PLs, and PEVs. To guarantee the global optimum solutions, the proposed optimization problem is linearized to achieve a mixed-integer linear program model. Furthermore, kernel density estimator (KDE) is presented to model the temporal uncertainties associated with PEV owners’ behavior with small number of iterations and no necessary assumptions. Various scenarios and sensitivity analysis are conducted to show the efficacy of the proposed method.

Two-Stage Robust Distribution Network Reconfiguration Against Failures of Lines and Renewable Generations

Network reconfiguration is a significant strategy to enhance the resiliences of distribution systems against contingencies. This paper proposes a two-stage robust network reconfiguration model to maximize the power supply under the uncertain failures of both lines and renewable generators. In stage 1, before the contingencies are realized, the network topology is reconfigured into several subsystems supplied by conventional generators. Then the contingencies are launched to the reconfigured distribution system, inducing load curtailments. In stage 2, the flexible resources, e.g., conventional and renewable generators, and energy storages, are dispatched to guarantee the maximal power supply under the worst-case contingencies. To solve the two-stage robust model, we develop a column & constraint generation (C&CG) algorithm. The network reconfiguration decision is made in the master problem according to an increasing amount of worst-case scenarios generated by the subproblem. Simulation results demonstrate the performance of the network reconfiguration decision of the two-stage robust model and verify the effectiveness of the C&CG algorithm to deal with the proposed model.

Reconfiguration-Based Stochastic Operation Management of Automated Distribution Systems Considering Smart Sensors, Electric Vehicle, and Social-Economic Targets

This paper suggests an intelligent smart stochastic framework for operating the automated reconfigurable distribution systems from the social and economic perspectives. The proposed framework utilizes the unscented conversion to reinforce the reliability of model for enhancing the upstream and consumer electricity quality in the high presence of wind units. In such an automated system, there are remotely controllable sectionalizers that will let the operator make an hourly restructuring in the grid topology for enhancing the operating point with load alterations. Due to the high randomness of the system owing to the wind forecast error and electricity forecast error, the presented framework handles this portion of uncertainty throughout the optimization process, based on sensors. In order to solve the problem, a novel optimization solution based on crow algorithm is suggested in this work. Also, a new modification technique is developed to help the algorithm diversity in the search space. An IEEE standard test system is deployed as the case study to check the model performance.

Optimal participation of demand response aggregators in reconfigurable distribution system considering photovoltaic and storage units

Feeder reconfiguration is an important operational process in power distribution grids, which is implemented to enhance the system’s performance by managing the switches. Given variations of the electricity price and load pattern in smart distribution networks, the operational problems of the distribution system are largely time-dependent and very complex. To deal with these temporal dependencies, it is important to extend the problem across different time intervals. Toward this end, a multi-objective optimization model is presented in this study for dynamic feeder reconfiguration problem in the distribution system over multiple time intervals considering distributed generators, energy storage systems, and solar photovoltaic units. The demand response program including interruptible/curtailable service is proposed to enable energy consumers to rethink their energy consumption patterns based on incentive and punitive policies. The common objectives considered in the feeder reconfiguration problem are power loss and voltage deviation which are important objectives for traditional distribution systems, but less attention has been paid to distribution network voltage security. This study considers operational cost, energy loss and voltage stability index as objective functions that can meet operational and voltage security expectations. Dynamic feeder reconfiguration problem is a complex integer nonlinear program problem and hence it is difficult to solve which requires the use of appropriate optimization algorithms to converge to global optima or find close to global optima. In this paper, a modified honey bee matting optimization algorithm based on the new mating mechanism is presented to solve the multi-objective dynamic feeder reconfiguration problem. The proposed approach uses an eliminating zone concept to finds a set of non-dominated solutions during the search process. Furthermore, a fuzzy decision-maker is adopted to select the best compromise solution among the non-dominated solutions. The suggested approach is tested on the IEEE 33-node and 136-node test systems and its superiorities are shown through comparison with other evolutionary algorithms.

Retracted: A Directed Acyclic Graph Based Architecture for Optimal Operation and Management of Reconfigurable Distribution Systems with PEVs

Retracted: A Directed Acyclic Graph Based Architecture for Optimal Operation and Management of Reconfigurable Distribution Systems with PEVs

Resilience-oriented intentional islanding of reconfigurable distribution power systems

Participation of distributed energy resources in the load restoration procedure, known as intentional islanding, can significantly improve the distribution system reliability. Distribution system reconfiguration can effectively alter islanding procedure and thus provide an opportunity to supply more demanded energy and reduce distribution system losses. In addition, high-impact events such as hurricanes and earthquake may complicate the procedure of load restoration, due to disconnection of the distribution system from the upstream grid or concurrent component outages. This paper presents a two-level method for intentional islanding of a reconfigurable distribution system, considering high impact events. In the first level, optimal islands are selected according to the graph model of the distribution system. In the second level, an optimal power flow (OPF) problem is solved to meet the operation constraints of the islands by reactive power control and demand side management. The proposed problem in the first level is solved by a combination of depth first search and particle swarm optimization methods. The OPF problem in the second level is solved in DIgSILENT software. The proposed method is implemented in the IEEE 69-bus test system, and the results show the validity and effectiveness of the proposed algorithm.

Decision Making in Power Distribution System Reconfiguration by Blended Biased and Unbiased Weightage Method

The term smart grid (SG) has been used by many government bodies and researchers to refer to the new trend in the power industry of modernizing and automating the existing power system. SGs must utilize assets optimally by making use of the information, like equipment capacity, voltage drop, radial network structure, minimizing investment and operating costs, minimizing energy loss and reliability indices, and so on. One way to achieve this is to re-route or reconfigure distribution systems (DSs). Distribution systems are reconfigured to choose a switching combination of branches of the system that optimize certain performance parameters of the power supply, while satisfying some specified constraints. In this paper, a blended biased and unbiased weightage (BBUW) multiple attribute decision-making (MADM) method is proposed for finding the compromised best configuration and compared it with other decision-making methods, such as the weighted sum method (WSM), weighted product method (WPM), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The BBUW method is implemented for two distribution systems, and the result obtained shows a good co-relationship between BBUW and other decision-making methods. Further weights obtained from the BBUW method are used for the WSM, WPM and TOPSIS methods for decision making. Examples of the distribution system are worked out in this paper to demonstrate the validity and effectiveness of the method.

A Reliability-Oriented Fuzzy Stochastic Framework in Automated Distribution Grids to Allocate $\mu$ -PMUs

This paper proposes a reliability-oriented stochastic aggregated integer linear framework for full observability of the automated distributed systems based on the $\mu $ -synchrophasor units. The $\mu $ -synchrophasor unit as a newly introduced high-tech device makes it possible for an accurate and high-speed measurement of the voltage and current waveforms in the distribution systems. This paper proposes a multi-stage strategy for the $\mu $ -synchrophasor unit placement together with the communication system requirements in the reconfigurable distribution systems, considering the zero-injection constraints in the model. To determine the optimal topology at the end of each phase, a reliability-based cost function is developed to optimize the customer interruption costs and power losses simultaneously. In order to model the uncertainties of forecast error in the active and reactive load demands as well as the failure rate and repair rate parameters, a stochastic framework based on the fuzzy cloud theory is employed. The proposed bi-level mixed integer linear programing approach is used to co-optimize the network switching scheme as well as the optimal $\mu $ -synchrophasor positions and communication infrastructure costs in the same framework. The simulation results on a practical test system verify the observability of the automated reconfigurable distribution system during the reconfiguration process.

Branch current decomposition method for loss allocation in contemporary distribution systems

The presence of distributed generation (DG) units in reconfigured distribution systems introduces complexity in loss allocation (LA). DG integration alters feeder power losses so DG owners (DGOs) may be incentivized or penalized accordingly, whereas network reconfiguration alters feeding path of network user’s thus further increases complexity in LA. The LA method should judiciously allocate losses among load points and simultaneously reward DGOs and distribution network operator (DNO) for their contribution towards loss reduction. Moreover, the LA method should take care of the reactive power transactions of network users. This paper proposes a branch current decomposition method (BCDM) based upon circuit theory for allocating losses in active reconfigured distribution system while giving due consideration to reactive power transactions of network users. BCDM considers virtual branch voltage drops which is well supported by analytical treatment. In addition, Superposition is utilized to incentivize/penalize DGOs. A new LA strategy is proposed for fair allocation of loss/loss incentives among network users and DNO. Proposed method is thoroughly investigated under varying loading, load power factors and under varying network topologies. The comparison results obtained on standard test distribution system highlights the importance of proposed method.

Designing Efficient Reconfigurable Control Systems Using IEC61499 and Symbolic Model Checking

IEC 61499 provides a standardized approach for the development of distributed control systems. The standard introduces a component architecture, based on function blocks that are event-triggered components processing data and signals. However, it gives only limited support for the design of reconfigurable architectures. In particular, handling of several reconfiguration scenarios is quite heavy on this level since a scenario changes the execution model of the system due to requirements. To this end, a new IEC 61499-based model named reconfigurable function blocks (RFBs) is proposed. An RFB processes the reconfiguration events and switches directly to the suitable configuration using a hierarchical state machine model. The latter represents the reconfiguration model which reacts on changes in the environment in order to find an adequate reconfiguration scenario to be executed. Each scenario presents a particular sequence of algorithms, encapsulated in another execution control chart slave which represents the control model of an RFB. This hierarchy simplifies the design and separates the reconfiguration logic from control models. To verify its correctness and alleviate its state space explosion problem in model checking, this paper translates an RFB system automatically into a generalized model of reconfigurable timed net condition/event systems (GR-TNCES), a Petri net class that preserves the semantics of an RFB system. In this paper, along with verification of deterministic properties, we also propose to quantify and analyze some probabilistic properties. As a case study, we consider a smart-grid system, interpreting permanent faults in it as reconfiguration events, and we characterize them with the expected occurrence probability and the corresponding repair time. A tool chain ZiZo is developed to support the proposed approach. Note to Practitioners —For reconfigurable distributed control systems, two models are indispensable: a control model that defines the hardware and software behaviors and a reconfiguration model that manages unpredictable changes in the related environment for configuring accordingly the system behavior. The proposed RFB approach is based on hierarchical state chart specification within function blocks, its automatic conversion to a reconfigurable Petri net GR-TNCES, which models all possible reconfiguration scenarios and a probabilistic model checking for qualitative and quantitative analysis. The system flexibility is ensured by a decision algorithm and a reconfiguration matrix which selects dynamically the right scenario to execute. The approach is supported by ZiZo tool chain which creates and edits reconfigurable function blocks model and converts it automatically to GR-TNCES, and then to specific PRISM models. The detection of the worst cases before deployment is a major virtue of the approach that practitioners need to estimate and enhance the design process. Several properties are easily checked and estimated such as system feasibility before and after reconfiguration, deadlock detection, confluence, estimation of the reconfiguration failure, system availability, and best repair time. The developed software package can be applied in any domain requiring flexibility and failure estimation, such as new medical technologies, transportation systems, smart and microgirds, and manufacturing systems.

Reliability improvement of reconfigurable distribution system using GA and PSO

This paper presents an effective method for optimal reconfiguration of distribution system using genetic algorithm and particle swarm optimization. It identifies the optimal number and position of tie switch for serving maximum amount of load under all contingencies. A risk-based reliability index is used to obtain the optimal number of switches. The essential/non-essential loads are incorporated using different weightage. The proposed algorithm is tested on 15-bus and 69-bus distribution systems, and results showing the effectiveness of proposed system are presented.

An Analytical Approach for DG Placement in Reconfigured Distribution Networks

<p>A novel approach is proposed in this paper for optimal placement of DG units in reconfigured distribution system with the aim of reduction of real power losses while satisfying operating constraints. The proposed analytical method for optimal DG placement is developed based on a new mathematical formulation. Type-I and type-II DG units are used here. The results of the proposed technique are validated on IEEE 69 bus distribution system. The level of DG penetration is also considered in a range of 0–50% of total system load. A novel index is also proposed which incorporates level of DG penetration and percentage reduction in real power losses. The results are promising when compared with recently proposed algorithms.</p>

Critical Components for Maintenance Outage Scheduling Considering Weather Conditions and Common Mode Outages in Reconfigurable Distribution Systems

This paper proposes a model for identifying critical components that affect the maintenance outage scheduling in reconfigurable distribution systems. The model considers critical factors such as prevailing severe weather conditions and component aging conditions, common mode outages, and repair rates in distribution systems. The effects of critical factors on forced outage rates of distribution system components are quantified by the proportional hazard model. A recursive sampling method is proposed to generate Monte Carlo scenarios with the given forced outage rate. In each scenario, the distribution system reconfiguration is optimized efficiently using a standard mixed-integer second-order cone program. Then absolute and relative criticality indices are calculated to describe the criticality of components. A new scenario is generated subsequently and the process is continued in the following iteration until the convergence condition is satisfied. The overall convergence of multiple scenarios is quantified by the coefficient of variation of criticality index. The final absolute and relative criticality indices are the average over multiple scenarios. The influence of component aging condition and forced outage characteristics, weather condition, and the system reconfiguration on component criticality for the maintenance outage scheduling is distinguished and exhibited in case studies. The case studies illustrate the effectiveness of proposed model and the solution method for identifying the critical components.

Energy efficiency analysis of reconfigured distribution system for practical loads

Summary In deregulated rate structure, the performance evaluation of distribution system for energy efficiency includes; loss minimization, improved power quality, loadability limit, reliability and availability of supply. Energy efficiency changes with the variation in loading pattern and the load behaviour. Further, the nature of load at each node is not explicitly of any one type rather their characteristics depend upon the node voltages. In most cases, load is assumed to be constant power (real and reactive). In this paper voltage dependent practical loads are represented with composite load model and the energy efficiency performance of distribution system for practical loads is evaluated in different configurations of 33-node system.

Intake chamber of the tundish in a continuous slab-casting machine

The configuration of the intake chamber for the tundish in a single-strand continuous slab-casting machine equipped with a special metal reservoir and barrier mounted at the boundary of the intake chamber. The metal reservoir and barrier contain casting holes positioned symmetrically relative to the longitudinal axis of the tundish. The influence of the reconfigured distribution system on the parameters of the steel flux in the tundish and on the removal of nonmetallic inclusions is considered.

Reliability Improvement in a Radial Distribution System Using DG

Reliability analysis plays a very vital role in designing and planning of radial distribution systems that operate for minimal interruption of customer loads. The Distributed Generation (DG) in a radial distribution network has been slowly increasing for the last few years due to advancement of technologies and institutional changes in the electric power industry. This paper presents a reliability analysis for large scale, radial (with respect to substation) and reconfigurable electrical distribution systems. This paper evaluates the improvement in reliability over a time varying load curve.