Meshed Distribution Networks Research Articles

Coordination of Dual-Setting Overcurrent and Distance Relays for Meshed Distribution Networks with Distributed Generations and Dynamic Voltage Restorer

ABSTRACT Simultaneous coordination of dual-setting directional overcurrent relays (DOCRs) and distance relays (DRs) is capable of providing reliable protection in a meshed distribution network (MDN). However, survey of literature on coordination of DRs and dual-setting DOCRs, reveals changes in system topology, especially in the presence of distributed generations (DGs), affects the coordination. As penetrations of DGs are increasing with time and in few years in a row, MDN with 100% penetration is also possible, an improved coordination of dual-setting DOCRs & DRs is targeted in this work. With nonstandard characteristic of DOCR, an innovative objective function is proposed and explored for optimum settings with particle swarm optimization (PSO) and gray wolf optimization (GWO). With various simulation studies, the performance of the proposed approach is investigated with and without compensation using a dynamic voltage restorer (DVR). The proposed method is validated on modified 14-bus and 39-bus test systems. The simulation results depict that the proposed approach can solve the miscoordination problem and the number of relays, operating time, and coordination time interval (CTI) of relays are also minimized. Comparison with convention approach demonstrates the benefits of proposed approach.

Rank-Based Predictive Control for Community Microgrids With Dynamic Topology and Multiple Points of Common Coupling

This article presents a rank-based model predictive control (MPC) scheme for voltage source converters (VSCs) operating in a low voltage, AC community microgrid with dynamically changing topology. The advent of mesh distribution networks with high renewable energy penetration in recent literature prompts the development of an adaptive VSC control technique for optimal performance in a changing environment. Several distributed control strategies have focused on communication less plug-and-play implementation, but the proposed ranking scheme focuses on resilient operation while minimizing physical communication requirements. The proposed framework provides intelligence to enable a fully synchronized microgrid with the ability to connect multiple VSCs to a utility grid simultaneously through multiple points of common coupling (MPCC) and disconnect from grid-forming distributed sources when islanded, attaining a higher margin of stability, robustness, and flexibility. The MPC framework features an adaptive ranking system that assigns operational modes to the VSCs, i.e., voltage control (grid-forming) or current control (grid-following), and defines leader-follower directionality for synchronization. Communication among VSCs is achieved using a topology-mirroring interaction layer. Several RTS case studies are provided to demonstrate the functionality and performance of the proposed intelligent rank-based MPC in a changing microgrid configuration with 10 VSCs.

Use of Energy Storage to Reduce Transmission Losses in Meshed Power Distribution Networks

One of the challenges which the electrical power industry has been facing nowadays is the adaptation of the power system to the energy transition which has been taking place before our very eyes. With the increasing share of Renewable Energy Sources (RES) in energy production, the development of electromobility and the increasing environmental awareness of the society, the power system must constantly evolve to meet its expectations regarding a reliable electricity supply. This paper presents the issue of deploying energy storage facilities in the meshed power distribution network in order to reduce transmission losses. The presented multi-objective approach provides an opportunity to solve this issue using multi-objective optimisation methods such as Non-dominated Sorting Genetic Algorithm II (NSGA-II), Multiobjective Particle Swarm Optimization (MPSO) and Biased Random Keys Genetic Algorithm (BRKGA). In order to increase the efficiency optimisation process, the Pareto Adaptive ϵ-dominance (paϵ-dominance) was used. It was demonstrated that the use of energy storages that cooperate with RES can significantly reduce transmission losses.

Optimal Placement and Sizing of D-STATCOM in Radial and Meshed Distribution Networks Using a Discrete-Continuous Version of the Genetic Algorithm

In this paper, we propose a new discrete-continuous codification of the Chu–Beasley genetic algorithm to address the optimal placement and sizing problem of the distribution static compensators (D-STATCOM) in electrical distribution grids. The discrete part of the codification determines the nodes where D-STATCOM will be installed. The continuous part of the codification regulates their sizes. The objective function considered in this study is the minimization of the annual operative costs regarding energy losses and installation investments in D-STATCOM. This objective function is subject to the classical power balance constraints and devices’ capabilities. The proposed discrete-continuous version of the genetic algorithm solves the mixed-integer non-linear programming model that the classical power balance generates. Numerical validations in the 33 test feeder with radial and meshed configurations show that the proposed approach effectively minimizes the annual operating costs of the grid. In addition, the GAMS software compares the results of the proposed optimization method, which allows demonstrating its efficiency and robustness.

Effective Utilisation of Weakly Meshed Distribution Network with DG and D-STATCOM

Effective Utilisation of Weakly Meshed Distribution Network with DG and D-STATCOM

Integrated resource planning for a meshed distribution network under uncertainty

Planning of renewable energy based distributed generators (DG) is to be done with utmost care because of the uncertain nature of their outputs. In this paper, a multi-objective PSO based solution methodology for the DG planning problem is proposed taking into account the concerns of the grid operators, distribution network operators and the end consumers. Load shifting along with time of use pricing is the strategy adopted for performing demand side management, thereby reducing the discomfort level and the electricity bill of the customers. DG planning is done for solar and wind based sources along with demand side management in order to minimize the system real power loss, improve voltage profile, increase reliability and reduce the expenses of the distribution network operator. Reliability is evaluated using encoded Markov cut set algorithm considering the failure rates, adequacy transition rates, mechanical failures, and starting and switching probability of the DG. The test network considered is the 102 node meshed distribution network connected to Bus 4 of the Roy Billinton test system. Results prove that load shifting along with dynamic pricing can be used as a viable option to reduce the operational expenses of the network operator.

OPF solution for a real Czech urban meshed distribution network using a genetic algorithm

Electrical distribution networks are facing an energy transition which entails an increase of decentralised renewable energy sources and electric vehicles. The resulting temporal and spatial uncertainty in the generation/load patterns challenges the operations of an infrastructure not designed for such a transition. In this situation, Optimal Power Flow methods can play a key role in identifying system weak points and supporting efficient management of the electrical networks, including the distribution level. In this work, to support distribution system operators’ decision-making process, we aim at attaining a quasi-optimal solution in the shortest time possible in an electrical network experiencing a large growth of distributed energy sources. We propose an optimisation method based on a modified version of a genetic algorithm and the Python pandapower package. The method is tested on a model of a real urban meshed network of a large Czech city. The optimisation method minimises the total operating costs of the distribution network by controlling selected network components and parameters, namely the transformer tap changers and the active power demand at consumption nodes. The results of our method are compared with the exact solution showing that a close-to-optimal solution of the observed problem can be reached in a relatively short time.

Impact of Optimal Control of Distributed Generation Converters in Smart Transformer Based Meshed Hybrid Distribution Network

A smart transformer (ST) based meshed hybrid distribution network is realized by extending ST low voltage dc (LVDC) link to form a LVDC line which connects dc buses of existing distributed generation (DG) converters. This paper proposes a method for optimal operation in such ST based meshed hybrid distribution network. A CIGRE LV residential distribution network with DG sources is connected at ST low voltage ac (LVAC) and LVDC terminals. All the DG sources are proposed to be connected at LVDC line. The power management scheme and method of determining power flow solution for the considered distribution network are proposed. An optimal problem is formulated for determining the active and reactive power references of DG converters while maintaining the load bus voltages within the grid limits and considering the DG converters constraints. The minimization of energy drawn from ST medium voltage (STMV) grid is considered as objective function and solved using genetic algorithm. To know the impact of proposed optimal control DG converters various performance indicators i.e., energy loss, operating energy costs, voltage profile and sizing of ST converters are considered and compared with existing literature.

An Extended Control Strategy for Weakly Meshed Distribution Networks With Soft Open Points and Distributed Generation

As part of the smart grid concept, different strategies specialized for power flow control in distribution networks have been developed. One of the possible solutions to optimize the utilization of existing capacities and increase distributed generation penetration is the implementation of Soft Open Points. Soft Open Points are modular devices based on power electronic converters that enable closing loops in the network without negative consequences regarding fault current propagation. Introducing the concept of soft open points in the distribution network enables power flow control in a particular part of the network and voltage control in the soft open point connecting nodes. The control strategy proposed in this paper addresses the main obstacle for appropriate exploitation of soft open points, defining reference values for control variables in the case of large-scale distribution systems. Furthermore, the proposed strategy also deals with data unavailability problems, that is, soft open point control under communication interruption. The proposed control algorithm incorporates centralized optimal power flow calculations and an estimation algorithm based on a multivariate polynomial regression. The optimal power flow is used to calculate the control variables in normal operation modes. The procedure based on multivariate polynomial regression was used to estimate the reference values of the control variables when the optimal power flow results were unavailable. This feature makes the proposed algorithm applicable to communication interruptions when only limited data capture is available. The algorithm proposed in this study was implemented and tested on a test network considering different scenarios. Conclusions and simulation results make this algorithm applicable to an actual soft open point controller.

A Comparative Study on Power Flow Methods for Direct-Current Networks Considering Processing Time and Numerical Convergence Errors

This study analyzes the numerical convergence and processing time required by several classical and new solution methods proposed in the literature to solve the power-flow problem (PF) in direct-current (DC) networks considering radial and mesh topologies. Three classical numerical methods were studied: Gauss–Jacobi, Gauss–Seidel, and Newton–Raphson. In addition, two unconventional methods were selected. They are iterative and allow solving the DC PF in radial and mesh configurations. The first method uses a Taylor series expansion and a set of decoupling equations to linearize around the desired operating point. The second method manipulates the set of non-linear equations of the DC PF to transform it into a conventional fixed-point form. Moreover, this method is used to develop a successive approximation methodology. For the particular case of radial topology, three methods based on triangular matrix formulation, graph theory, and scanning algorithms were analyzed. The main objective of this study was to identify the methods with the best performance in terms of quality of solution (i.e., numerical convergence) and processing time to solve the DC power flow in mesh and radial distribution networks. We aimed at offering to the reader a set of PF methodologies to analyze electrical DC grids. The PF performance of the analyzed solution methods was evaluated through six test feeders; all of them were employed in prior studies for the same application. The simulation results show the adequate performance of the power-flow methods reviewed in this study, and they permit the selection of the best solution method for radial and mesh structures.

On the Matricial Formulation of Iterative Sweep Power Flow for Radial and Meshed Distribution Networks with Guarantee of Convergence

This paper presents a general formulation of the classical iterative-sweep power flow, which is widely known as the backward–forward method. This formulation is performed by a branch-to-node incidence matrix with the main advantage that this approach can be used with radial and meshed configurations. The convergence test is performed using the Banach fixed-point theorem while considering the dominant diagonal structure of the demand-to-demand admittance matrix. A numerical example is presented in tutorial form using the MATLAB interface, which aids beginners in understanding the basic concepts of power-flow programming in distribution system analysis. Two classical test feeders comprising 33 and 69 nodes are used to validate the proposed formulation in comparison with conventional methods such as the Gauss–Seidel and Newton–Raphson power-flow formulations.

A Reliability-Constrained Expansion Planning Model for Mesh Distribution Networks

To achieve high reliability, the urban distribution networks are mesh-constructed and radial-operated, in which the outage load can be restored to adjacent feeders via tie-lines after faults. Conventionally, iterative optimization-simulation methods and heuristics are adopted for distribution network planning, which cannot guarantee global optimality. Besides, existing reliability-constrained planning model cannot explicitly assess the reliability indices for mesh distribution networks, so the resulted plan scheme may be overly invested. In this paper, we propose a novel multistage expansion planning model for mesh distribution networks, in which reliability assessment is explicitly implemented as constraints. The different investment/reliability preferences for buses are also customized. Specifically, post-fault load restoration between feeders through tie-lines is modeled as a case of post-fault network reconfiguration. The planning model is then cast as an instance of mixed-integer linear programming and can be effectively solved by off-the-shelf solvers. We use a 54-node system to test the performance of proposed model. Simulation results show the effectiveness and flexibility of this methodology.

On the numerical analysis based on successive approximations for power flow problems in AC distribution systems

This paper proposes a new power flow formulation for alternating-current distribution networks for radial and mesh topologies. This formulation corresponds to a successive approximation based on a modification of the conventional Gauss-Seidel numerical method by using a successive approximation approach. This power flow method allows working with complex variables by reducing the number of required calculations and avoiding the transformation of the power flow model into polar coordinates. Additionally, it does not use derivatives for approximating the problem as it occurs with Taylor-based approaches. Simulation results confirm that the proposed method is faster concerning computational time, as well as in the total number of iterations required. Numerical comparisons with classical methods such as Gauss-Seidel, Newton-Raphson, Levenberg-Marquardt, graph-based methods, and linear approximations have been made and implemented in MATLAB software to demonstrate the effectiveness of the proposed approach regarding power flow solutions in radial and mesh distribution networks.

Dominated GSO algorithm for optimal microgrid construction to improve consumer side properties in a distribution system

Introducing the concepts of distributed generation (DG) and microgrid (MG) are known as key points, which lead the conventional distribution systems toward novel smart grids. Utilizing DG infrastructures would facilitate local supply of loads. Hence, it is necessary to optimally distribute DG units all over the distribution network. MGs with ability of operating in the grid-connected and islanded modes enhance the system performance. Obviously, it is important to implement an appropriate procedure for optimal construction of MGs in a distribution system. This paper proposes optimized methods to allocate DG units and construct a set of MGs with the aim of improving system performance and consumer side properties. It is also taken into account that the generated power by DG units and the consumed power by loads are stochastic. The considered objective functions for optimal DG placement problem are decreasing system losses and improving voltage profile. On the other hand, MG construction is carried out with the aim of maximizing system load factor and minimizing system load variance. In this paper, an improved version of group search optimization (GSO) algorithm named as dominated groups search optimization (DGSO) algorithm is proposed and implemented in order to solve mentioned optimization problems. The proposed DGSO algorithm facilitates the comprehensive search which results in achieving to better solutions. The related formulation, optimization algorithms and simulation results are presented in this paper. Moreover, the proposed strategy is evaluated in the PG&E 69-bus distribution system and a custom meshed distribution network.

Optimal allocation of D-STATCOM in distribution networks including correlated renewable energy sources

Gradual depletion of fossil fuel resources, poor energy efficiency, and environmental pollution problems have led to the use of renewable energy sources (RESs) such as wind turbines (WTs) and solar photovoltaic (PV) cells in distribution networks all around the world. The uncertain nature of these sources, along with network power demands, necessitates probabilistic evaluation to extract results with high applicability and efficiency. Distribution network flexible AC transmission system (D-FACTS) devices such as distribution static compensator (D-STATCOM) can be efficiently used for making the modern distribution networks with high penetration of RESs more flexible.This paper presents a probabilistic technique for optimal allocation of the D-STATCOM, considering the correlation between uncertain variables. The proposed solution method helps to mitigate expected active power losses, improve expected voltage deviation index (VDI), and decrease D-STATCOM expected installation cost for radial/mesh distribution networks. The k-means based data clustering method (DCM) and Latin hypercube sampling (LHS) method are used for probabilistic evaluation of distribution networks. In addition, the particle swarm optimization (PSO) algorithm is employed as the optimization tool. The proposed algorithm is applied to the IEEE 69 node test network, and the results are compared with the Monte Carlo simulation (MCS) method. Also, the efficacy of the proposed study method has been investigated for a real meshed distribution network.

Linear Formulations for Topology-Variable-Based Distribution System Reliability Assessment Considering Switching Interruptions

Continuity of supply plays a significant role in modern distribution system planning and operational studies. Accordingly, various techniques have been developed for reliability assessment of distribution networks. However, owing to the complexities and restrictions of these methods, many researchers have resorted to several heuristic optimization algorithms for solving reliability-constrained optimization problems. Therefore, solution quality and convergence to global optimality cannot be guaranteed. Aiming to address this issue, two salient mathematical models are introduced in this paper for topology-variable-based reliability evaluation of both radial and radially-operated meshed distribution networks. Cast as a set of linear expressions, the first model is suitable for radial networks. The second model relies on mixed-integer linear programming and allows handling not only radial networks but also radially-operated meshed distribution grids. Therefore, the proposed formulations can be readily incorporated into various mathematical programming models for distribution system planning and operation. Numerical results from several case studies back the scalability of the developed models, which is promising for their further application in distribution system optimization studies. Moreover, the benefits of the proposed formulations in terms of solution quality are empirically evidenced.

A Techno-Economic Centric Integrated Decision-Making Planning Approach for Optimal Assets Placement in Meshed Distribution Network Across the Load Growth

The modern distribution networks under the smart grid paradigm have been considered both interconnected and reliable. In grid modernization concepts, the optimal asset optimization across a certain planning horizon is of core importance. Modern planning problems are more inclined towards a feasible solution amongst conflicting criteria. In this paper, an integrated decision-making planning (IDMP) approach is proposed. The proposed methodology includes voltage stability assessment indices linked with loss minimization condition-based approach, and is integrated with different multi-criteria decision-making methodologies (MCDM), followed by unanimous decision making (UDM). The proposed IDMP approach aims at optimal assets sitting and sizing in a meshed distribution network to find a trade-off solution with various asset types across normal and load growth horizons. An initial evaluation is carried out with assets such as distributed generation (DG), photovoltaic (PV)-based renewable DG, and distributed static compensator (D-STATCOM) units. The solutions for various cases of asset optimization and respective alternatives focusing on technical only, economic only, and techno-economic objectives across the planning horizon have been evaluated. Later, various prominent MCDM methodologies are applied to find a trade-off solution across different cases and scenarios of assets optimization. Finally, UDM is applied to find trade-off solutions amongst various MCDM methodologies across normal and load growth levels. The proposed approach is carried out across a 33-bus meshed configured distribution network. Findings from the proposed IDMP approach are compared with available works reported in the literature. The numerical results achieved have validated the effectiveness of the proposed planning approach in terms of better performance and an effective trade-off solution across various asset types.

Novel fault location algorithm for meshed distribution networks with DERs

Modern electrical networks are continuously evolving due to the increasing deployment of Information Technologies and Distributed Energy Resources (DERs). This scenario affects the quality of the electricity supply of distribution systems. For this reason, this quality plays a key role on the evolution of electrical networks into Smart Grids.Quality of the electricity supply is defined through three main skills: reliability of the electric power system, power quality and customer relationships, all of them under safety layer. From the network operation point of view, availability in a distribution network is crucial to maintain reliability. Fault location is a priority for electrical network operators in their efforts to ensure high quality for loads, generators and prosumers. The presence of DERs in current electrical distribution networks poses a new scenario where bidirectional current flow complicates fault detection. Implementation of the Smart Grid concept in these networks depends on the automation of procedures such as Fault Location, Isolation and Service Restoration, which enable a rapid response to faults. This paper proposes a fault detection algorithm for grid topologies such as radial, ring, meshed with or without DER penetration.

Reliability based optimal DG planning for a meshed distribution network

Distributed generation (DG) sources are becoming more popular nowadays because of their technoeconomic and environmental benefits. These benefits are maximized only when the DG sources are properly planned and installed in the distribution networks. Several studies have been carried out in this field considering various objectives and constraints, for single as well as multiple DG placement and sizing. In this paper, an optimization methodology based on particle swarm optimization is used for the optimal planning of multiple DG sources in a meshed distribution network. The solution consists of the possible DG locations, DG capacities, and its operating power factor. The objectives considered are the improvement of reliability indices namely the system average interruption frequency index and system average interruption duration index, reduction of real power loss, and voltage profile improvement. Unlike other works, reliability evaluation is done considering many realistic constraints and it is used as one of the criteria for DG planning. Reliability indices are evaluated using the encoded Markov cut set algorithm. The real power loss and the voltage index are obtained by means of a simple load flow technique. The stochastic nature of the renewable DG output and the load are taken into account during the reliability evaluation along with islanding probability. The optimal planning of DG sources is done for bus 4 of the Roy billinton test system consisting of seven feeders, 102 nodes, and 106 components. Optimal planning for solar based DG sources is done considering three different load models namely residential, commercial, and mixed load.

Optimal Coordination of Overcurrent Relay Using Crow Search Algorithm

ABSTRACTThis paper proposed a novel optimization technique derived from the crow search algorithm (CSA) for overcurrent (OC) relay coordination in mesh distribution networks. CSA is a meta-heuristic optimizer algorithm, influenced by the cleverness approach of crows. This algorithm can be treated easily by changing only two parameters like, flock size and iteration. In the present work an objective function (OF) is build up to work out the problems of relay coordination developed from time dial (TDS) setting and also the competence of the proposed technique is verified for four different power system networks and compared with existing techniques. Result and performances are the evidence that the suggested scheme is efficient, precise and simple.