Service Restoration In Distribution Systems Research Articles

A Method of Restoring Distribution Systems Using Adjacent Networks and Two Levels Search

This paper presents an adjacent feeders search based method for service restoration of distribution systems after single faults. The developed algorithm makes a search for sections that belong to adjacent feeders and comply with two conditions: have normally open equipment installed or have a three or more derivations. As soon as the sections are selected, an exhaustive search is executed to achieve the restoration plan. To demonstrate the effectiveness of the proposed method, service restoration on a typical distribution system of Taiwan Power Company is applied. The results are compared with others approaches and show that the proposed method can provide a restoration plan very efficiently even under different load levels.

Analysis of Solution Quality of Multiobjective Evolutionary Algorithms for Service Restoration in Distribution Systems

This paper presents a comparative study of six multiobjective evolutionary algorithms (MOEAs) with the node-depth encoding (NDE) which have been used to solve the service restoration in distribution systems. The study has been divided into three steps: (1) the MOEAs have been evaluated taking into account the switching operations necessary to find adequate restoration plans considering multiple nonlinear constraints and objective functions; (2) the MOEAs have been employed to solve four different datasets with 3860, 7720, 15,440 and 30,880 buses, respectively; (3) comparisons have been performed using the hypervolume indicator and the results obtained with each approach are statistically compared using Kruskal–Wallis nonparametric tests and multiple comparisons. In addition, this paper provides a comprehensive evaluation of six combinations of MOEAs based on NDE and our objective is to identify the features of each approach that consistently produce best results applied to network reconfiguration for service restoration in distribution systems. Simulations results have shown that MOEA based on NDE with crowding distance and strength pareto found good configurations with low switching operations and explored the search space better than others approaches used in this paper, approximating better the pareto-optimal front.

Fault Detection, Isolation, and Service Restoration in Distribution Systems: State-of-the-Art and Future Trends

This paper surveys the conceptual aspects, as well as recent developments in fault detection, isolation, and service restoration (FDIR) following an outage in an electric distribution system. This paper starts with a discussion of the rationale for FDIR, and then investigates different areas of the FDIR problem. Recently reported approaches are compared and related to discussions on current practices. This paper then addresses some of the often-cited associated technical, environmental, and economic challenges of implementing self-healing for the distribution grid. The review concludes by pointing toward the need and directions for future research.

Networked microgrids for service restoration in resilient distribution systems

This study presents a novel networked microgrid (MG)-aided approach for service restoration in power distribution systems. This study considers both dispatchable and non-dispatchable distributed generators (DGs), and energy storage systems. The uncertainty of the customer load demands and DG outputs are modelled in a scenario-based form. A stochastic mixed-integer linear program is formulated with the objective to maximise the served load, while satisfying the operation constraints of the distribution system and MGs. The interaction among MGs is modelled using the type 1 special ordered set. Two approaches are developed and compared: (i) a centralised approach where all MGs are controlled by a distribution system operator, and (ii) a decentralised approach where the distribution system and MGs are managed by different entities. The proposed restoration models are tested on a modified IEEE 123-bus distribution system. The results demonstrate the advantages of leveraging networked MGs to facilitate service restoration.

A Network Reconfiguration Method for BESS based Service Restoration in Distribution Systems

A Network Reconfiguration Method for BESS based Service Restoration in Distribution Systems

Load Priority Modeling for Smart Service Restoration

Enhancing the reliability of distribution systems (DSs) has become a necessity due to society's dependence on electric power and the high costs associated with service interruptions. One key technique for improving system reliability is to apply efficient power restoration methodologies, which must include a systematic load prioritization method that considers several practical factors that make the process of load prioritization a complicated and challenging one. This paper presents a dynamic load prioritization model for service restoration in DSs. The method ranks loads by priority and assigns a calculated weight for each load in the system. These weights are dynamic (i.e., time dependent), and can be used as an input for any restoration optimization problem. The proposed load prioritization procedure considers the criticality of the load, the amount of energy consumed, the number of connected customers, the cost of interruption, and the practice of demand side management programs. The Roy Billinton Test System (RBTS) Bus 4 system and the 3-feeder 16-bus test system are used as case studies to implement this method. The results of the case studies show that the proposed prioritizing method was able to quantify the importance of each individual load, and systems' reliability was improved.

Service Restoration with Prioritization of Customers and Switches and Determination of Switching Sequence

Distribution system (DS) service restoration (SR) in contingency situations is one of the most complex and challenging problems in DS operation. It is usually formulated as a multi-objective and multi-constraint optimization problem that must be quickly solved. Several methods have been proposed for its solution, however, most of them still have limitations. Some demand long running time when applied to large-scale DSs modeled with no simplification, whereas others disregard some important aspects of the SR problem. This paper proposes a methodology based on multi-objective evolutionary algorithms for the SR problem and overcoming of such limitations. In contrast to methods reported in the literature, the methodology: 1) deals with large-scale DSs with relatively soft computing time and requires no network topology simplification; 2) prioritizes the operation of remotely controlled switches; 3) prioritizes supply to three levels of priority customers; and 4) provides switching sequences. A mathematical formulation of the problem is also proposed. Several tests were conducted for the evaluation of the methodology and single and multiple fault cases in large-scale DSs (from 631 to 5158 switches) were considered.

Service restoration of distribution systems under distributed generation scenarios

A novel extended network for service restoration optimization problem under distributed generation scenarios is presented in which the main network restoration and DG island restoration problems are integrated into a unified spanning-tree problem. The proposed technique is aimed to realize synchronous optimization of both main network and island restorations, and thus ensure the algorithms that are used find the global optimization solution. A fast loop-breaking technique is also proposed in this paper. Based on the circuit-branch correlation matrix, the proposed technique can break the loops in the distribution systems through matrix operations that significantly improve calculation speeds. Simulation results verify the correctness and advantage of the proposed algorithms: the proposed integrated optimization strategy based on the extended network has better performance compared with a two-step restoration strategy; also, the proposed loop-breaking technique has faster calculation speed compared with prim algorithm and DFS based on adjacent matrix.

Optimisation‐based switch allocation to improve energy losses and service restoration in radial electrical distribution systems

This study presents a new methodology for the optimal allocation of switching devices in radial electrical distribution systems (EDSs). A specialised greedy randomised adaptive search procedure (GRASP) algorithm defines the location of a number of switching devices in order to simultaneously improve the following optimisation subproblems related to the use of the allocated switches: (i) the optimal reconfiguration of EDS and (ii) the optimal service restoration of EDS. Eventually, the objective function of the proposed switch allocation algorithm minimises the cost of the total expected energy not supplied, computed after deploying the service restoration, plus the cost of the total annual energy loss computed for every load level in a year, plus the investment costs associated with the number of installed switches. Both optimisation subproblems, i.e. the reconfiguration and the restoration of EDS, are represented by mixed-integer non-linear programming (MINLP) models and transformed into mixed-integer linear programming (MILP) models, using linearisation strategies. MILP models guarantee convergence to optimality by using convex optimisation techniques. Finally, all tests were carried out using a real 136-node distribution system, considering dispatchable and non-dispatchable distributed generation resources.

Multi-objective service restoration of distribution systems using user-centered methodology

A multi-objective problem formulation of service restoration and a three-stage methodology tailored to user-centered service restoration for large-scale, unbalanced distribution systems are presented. One feature is that the experience and engineering judgment of operators is integrated into the three-stage methodology. Since solutions suggested by a method need to be compromised with engineering judgment, this methodology involves system users (at Stage II), meta-heuristics (at Stage I), and local heuristics in combination with restoration strategies (at Stage III) for efficient and robust performance in service restoration. An adaptive K-means method is incorporated in the proposed group-based PSO (Stage I) for global search. It also assists users in their decision making. Evaluation results of the proposed user-centered methodology on the IEEE 123-node test system and a 1101-node practical unbalanced network show its effectiveness and flexibility in restoring service after faults.

Combining exhaustive search and multi-objective evolutionary algorithm for service restoration in large-scale distribution systems

Service restoration problem in distribution systems emerges after the faulted areas have been identified and isolated. A solution is obtained by determining the minimal number of switching operations that results in a configuration with a minimal number of healthy out-of-service areas without violating the operational and radiality constraints. Recently a practical and efficient methodology was developed and demonstrated through tests performed on the real and large-scale distribution system of Londrina city (Brazil). This methodology, named MEAN-MH, combines a Multi-objective Evolutionary Algorithm with Node-Depth Encoding, Multiple criteria tables and an alarming Heuristic. As any methodology based on meta-heuristics, the MEAN-MH does not guarantee to find the optimal solution of the service restoration problem, even when the optimal solution requires operations only in normally open switches incident to the healthy out-of-service areas (named as Tier 1 normally open switches). This paper proposes an extension of MEAN-MH that incorporates an Exhaustive Search (ES) procedure as a previous stage before MEAN-MH. The proposed ES guarantees the generation and analysis of all possible radial configurations that restore the service to all healthy out-of-service areas requiring operations only in Tier 1 normally open switches. Therefore, when the optimal solution of the service restoration problem requires operations only in Tier 1 NO switches, the proposed methodology, named MEAN-MH+ES, guarantees the optimum. However, when the optimal solution requires operations also in other switches, the MEAN-MH+ES searches by a feasible solution minimizing both the number of switching operations and the number of healthy out-of-service areas. To demonstrate the effectiveness of the proposal, both MEAN-MH and MEAN-MH+ES are applied to two real and large-scale distribution systems of Brazil. Moreover, the results obtained by MEAN-MH+ES are compared with those found in another published work.

A Multi-objective Evolutionary Algorithm with Efficient Data Structure and Heuristic Initialization for Fault Service Restoration

Service restoration in energy distribution systems is a complex optimization problem with many restrictions. After a fault occurrence, the challenge is obtain a service restoration plan reconnecting all the healthy out-of-service areas satisfying all the operational and technical constraints. Recent works have study the use of meta-heuristics in order to find a sub-optimal solution with low computational complexity. One of these works include the use of a multi-objective algorithm with a new data structure called node depth encoding. This paper proposes and analyses the use of a new heuristic initialization procedure to be used with node depth encoding which guarantees the analysis of all possible solutions considering only a restricted number of switches incident to the out-of-service areas. The proposed methodology is evaluated by applying it to the real and large-scale distribution system of Londrina city (Brazil). The results showed that the new heuristic improves the overall performance reducing the number of switches operations to reconfigure the distribution system.

A Fuzzy-Multiagent Service Restoration Scheme for Distribution System With Distributed Generation

This paper proposes a new multiagent control system (MACS) for service restoration in distribution systems with integrated distributed generation (DG) units. First, the MACS detects and locates faults, then decides the optimal reconfiguration of the network for restoring de-energized loads, and finally regulates the nodes voltages. Unintentional islanding operation of DG units is avoided and different postfault response modes of DG unit are addressed in the MACS design. The MACS has a hybrid centralizeddecentralized structure where agents are arranged in two layers with different responsibilities and communication capabilities. Agents at load buses in the first layer can only communicate directly with its next neighbor load agents on the same feeder and to its feeder agent, whereas the higher level agents in the second layer can communicate directly with each other. This MACS structure reduces the possibilities of control system failures for a moderate communication network infrastructure. Full dynamic simulation model for evaluating the MACS is implemented.

Power distribution system service restoration bases on a committee-based intelligent agent architecture

Multi-agent technology is applied in this paper to solve the distribution system service restoration problems. Specifically, switches in the distribution systems are modeled as intelligent agents and organized as local power committees in a distribution system. The advantage of this approach is to utilize the solving ability of a local committee of agents who could coordinate with neighboring committees to achieve an agreement that satisfies the global objective of the power distribution system service restoration problems without relying on a pre-determined centralized optimization algorithm as traditional approaches. The proposed coordination method helps switches in the distributed local power committees to reach a consensus among many proposed service restoration solutions after faults are detected and isolated. We also take the voltage violations into consideration in the search of solutions. Two examples of different power distribution systems are presented to demonstrate how the algorithms of the coordination method can identify the best restoration solution among many proposed local candidate solutions. The simulation results show that the proposed committee-based multi-agent approach yields better performance than the previous methods.

Differential evolution using ancestor tree for service restoration in power distribution systems

Problems in power distribution system reconfiguration (PDSR), such as service restoration, power loss reduction, and expansion planning, are usually formulated as complex multi-objective and multi-constrained optimization problems. Several evolutionary algorithms (EAs) have been developed to deal with PDSR problems, but the majority of EAs still demand high running time when applied to large-scale distribution systems (thousands of buses and switches). This paper presents a new approach for service restoration in large scale distribution systems that employs a discrete differential evolution with ancestor tree (DE-Tree). We combine the node-depth encoding (NDE) to represent computationally the electrical topology of the system and the ancestor tree presented here to implement differential evolution for service restoration problems. The ancestor tree is used to build a list of elementary movements that maps one solution in the search space into another, thus capturing the “difference” between forests encoded with the NDE, which is essential in the search engine of differential evolution. The use of an ancestor tree is not only central to implement differential mutation in our algorithm but also can track the sequence of switching operations in the restoration of the system after the optimization process is finished. The proposed approach makes differential evolution suitable for treating combinatorial optimization problems related to PDSR. Results presented on distribution system reconfiguration problems suggest the benefits and fast convergence of the proposed approach.

Multiobjective evolutionary algorithm with a discrete differential mutation operator developed for service restoration in distribution systems

Network reconfiguration for service restoration in distribution systems is a combinatorial complex optimization problem that usually involves multiple non-linear constraints and objective functions. For large scale distribution systems no exact algorithm has found adequate restoration plans in real-time. On the other hand, the combination of Multi-Objective Evolutionary Algorithms (MOEAs) with the Node-Depth Encoding (NDE) has been able to efficiently generate adequate restoration plans for relatively large distribution systems (with thousands of buses and switches). The approach called MEAN results from the combination of NDE with a technique of MOEA based on subpopulation tables. In order to improve the capacity of MEAN to explore both the search and objective spaces, this paper proposes a new approach that results from the combination of MEAN with characteristics from the mutation operator of the Differential Evolution (DE) algorithm. Simulation results have shown that the proposed approach, called MEAN-DE, is able to find adequate restoration plans for distribution systems from 3860 to 30,880 switches. Comparisons have been performed using the Hypervolume metric and the Wilcoxon rank-sum test. In addition, a MOEA using subproblem Decomposition and NDE (MOEA/D-NDE) was investigated. MEAN-DE has shown the best average results in relation to MEAN and MOEA/D-NDE.

Multi-period service restoration of distribution systems incorporating interruptible load

SUMMARY A multi-period service restoration optimization method incorporating interruptible load is presented, which considers operational constraints based on the practical requirements of dispatching interruptible load, such as notification time, interruption duration and interruption capacity. The Node-Depth Encoding (NDE) technique is introduced into the Non-Dominated Sorting Genetic Algorithm-II. This enhanced algorithmic procedure substitutes restructuring operations based on the NDE technique for the traditional crossover and mutation operations, and hence it can ensure a radial configuration, as well as determine the topological structure of the network within a reduced calculation time. A new restructuring operation referred to as Load Curtailment Operation (LCO) is proposed as an addition to the original restructuring operations. LCO provides effective load curtailment recommendations and hence increases the variety of the solution population. The simulation results show the feasibility of the proposed model and the advantage of LCO. Copyright © 2014 John Wiley & Sons, Ltd.

Multi-Objective Evolutionary Algorithm for single and multiple fault service restoration in large-scale distribution systems

Network reconfiguration for service restoration (SR) in distribution systems is a complex optimization problem. For large-scale distribution systems, it is computationally hard to find adequate SR plans in real time since the problem is combinatorial and non-linear, involving several constraints and objectives. Two Multi-Objective Evolutionary Algorithms that use Node-Depth Encoding (NDE) have proved able to efficiently generate adequate SR plans for large distribution systems: (i) one of them is the hybridization of the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) with NDE, named NSGA-N; (ii) the other is a Multi-Objective Evolutionary Algorithm based on subpopulation tables that uses NDE, named MEAN. Further challenges are faced now, i.e. the design of SR plans for larger systems as good as those for relatively smaller ones and for multiple faults as good as those for one fault (single fault). In order to tackle both challenges, this paper proposes a method that results from the combination of NSGA-N, MEAN and a new heuristic. Such a heuristic focuses on the application of NDE operators to alarming network zones according to technical constraints. The method generates similar quality SR plans in distribution systems of significantly different sizes (from 3860 to 30,880 buses). Moreover, the number of switching operations required to implement the SR plans generated by the proposed method increases in a moderate way with the number of faults.

Improving Service Restoration of Power Distribution Systems Through Load Curtailment of In-Service Customers

Load curtailment programs including direct load control and demand response allow system operators to directly and/or indirectly reduce a portion of total customer demand. One system application which can be improved by implementation of load curtailment is service restoration. As such, this work presents a problem formulation, solution algorithm, and simulation results for service restoration of power distribution systems incorporating load curtailment of in-service customers via direct load control. It is shown that the addition of load curtailment allows for one or more of the following: a reduction of the total number of switch operations required, an increase to the number of customers served, and/or an increase to the total amount of load restored. These improvements are demonstrated through simulation results from a 416-bus multiphase distribution system.

Service restoration on distribution systems using Multi‐MicroGrids

AbstractLarge scale integration of distributed generation of both medium and low voltage (LV) networks can be achieved by exploiting the Multi‐MicroGrid (MMG) concept, a new distribution system architecture comprising a hierarchical control system, which allows the coordination among distributed generation units and MicroGrids (MGs) and therefore the operation of such a system in islanded mode. After a general blackout the MMG capabilities can also be used to provide service restoration in distribution systems. A new procedure for MMGs black start is then addressed in this paper. A sequence of control actions is defined and evaluated through numerical simulations. Fully automation of the entire MMG black start procedure is discussed along the paper. The results obtained demonstrate the feasibility of the proposed sequence of control actions and highlight some accomplishments that should be considered in order to successfully restore the MMG service, ensuring system stability and power quality. Copyright © 2010 John Wiley & Sons, Ltd.