Reconfiguration of Electric Power Distribution Systems: Comprehensive Review and Classification

Abstract

Distribution systems play an important role, delivering the electric power of generation system to individual consumers. Distribution system reconfiguration (DSR) is a large-scale combinatorial optimization problem. For the last 45 years, the DSR problem has been widely studied; nowadays, DSR, combined with new challenges, is being highly investigated, as researchers aim to reach a better solution. This paper presents a complete review and classification of the most significant works to date, providing a literary framework for DSR specialists. A categorization of solution methods, case studies, and novelties of the most relevant works regarding DSR are provided. In order to establish a complete background, not only traditional approaches, but also those involving uncertainty, reliability, electricity market, power quality, distributed generation, capacitor placement, and switching time in DSR are highlighted. This framework can help researches to improve previous formulations and methods and can propose more efficient models to better exploit the existing infrastructure. INDEX TERMSDistributed generation, literary framework, network reconfiguration, power distribution systems, uncertainty. NOMENCLATURE Abbreviations used throughout the manuscript are reproduced below for quick reference. 1 AACO Adaptive ant colony optimization. AC Alternating current. ACO Ant colony optimization. ADC Automated distribution control. ADP Approximated dynamic programming. AENS Average energy not supplied. AGA Adoptive genetic algorithm. AIS Artificial immune system. AMPL A mathematical modeling language. ANN Artificial neural network. APSO Adaptive particle swarm optimization. ASIFI Average system interruption frequency index.

Allocation of 0.4 kV PTL Sectionalizing Units under Criteria of Sensitivity Limits and Power Supply Reliability

“…Study [26] presents a methodology for the allocation of distributed generators and reclosers in a security-constrained distribution network through analyzing reliability indices SAIFI, SAIDI, and MAIFI and power flow equations. It should be noted that power flow analysis is a powerful tool to assess PS reliability [27] in order to solve such tasks as optimal network configuration [28,29] and PS restoration process [30].…”

Improved Successive Branch Reduction for Stochastic Distribution Network Reconfiguration

“…The existing methods for DNR mostly fall into three categories: mathematical programming, heuristics or metaheuristics, and machine learning [4], [5]. Various mathematical programming techniques have been developed to improve the computational efficiency of DNR, including Benders decomposition [6], column-and-constraint generation [7], [8], linearization into a mixed-integer linear program [9], and convex relaxation into a mixed-integer quadratic, quadratically constrained, or conic program [4], [10], [11]. However, the computation process of mathematical programming can be timeconsuming for large systems [4].…”

“…Various mathematical programming techniques have been developed to improve the computational efficiency of DNR, including Benders decomposition [6], column-and-constraint generation [7], [8], linearization into a mixed-integer linear program [9], and convex relaxation into a mixed-integer quadratic, quadratically constrained, or conic program [4], [10], [11]. However, the computation process of mathematical programming can be timeconsuming for large systems [4]. Common tricks to alleviate computational burdens, such as linearization, often sacrifice the accuracy and optimality of solutions.…”

“…Moreover, their performance relies heavily on parameter tuning, and they may have difficulty in satisfying the radiality condition. Reference [4] provided a detailed review of the methods above and their pros and cons.…”

A Game Theory Based Retail Market Framework With DSO’s Operational Considerations

“…Network reconfiguration takes into account the network parameters and comes up with the best topology for the required objective. Different techniques [22]- [25] are available to implement network reconfiguration. A complete review and classification of the most significant works are presented in [26].…”