Mitigating unbalance using distributed network reconfiguration techniques in distributed power generation grids with services for electric vehicles: A review

© 2019 Elsevier Ltd With rapid movement to combat climate change by reducing greenhouse gases, there is an increasing trend to use more electric vehicles (EVs) and renewable energy sources (RES). With more EVs integration into electricity grid, this raises many challenges for the distribution service operators (DSOs) to integrate such RES-based, distributed generation (DG) and EV-like distributed loads into distribution grids. Effective management of distribution network imbalance is one of the challenges. The distribution network reconfiguration (DNR) techniques are promising to address the issue of imbalance along with other techniques such as the optimal distributed generation placement and allocation (OPDGA) method. This paper presents a systematic and thorough review of DNR techniques for mitigating unbalance of distribution networks, based on papers published in peer-reviewed journals in the last three decades. It puts more focus on how the DNR techniques have been used to manage network imbalance due to distributed loads and DG units. To the best of our knowledge, this is the first attempt to review the research works in the field using DNR techniques to mitigate unbalanced distribution networks. Therefore, this paper will serve as a prime source of the guidance for mitigating network imbalance using the DNR techniques to the new researchers in this field

Efficient and Risk-Aware Control of Electricity Distribution Grids

This article presents an economic model predictive control (EMPC) algorithm for reducing losses and increasing the resilience of medium-voltage electricity distribution grids characterized by high penetration of renewable energy sources and possibly subject to natural or malicious adverse events. The proposed control system optimizes grid operations through network reconfiguration, control of distributed energy storage systems (ESSs), and on-load tap changers. The core of the EMPC algorithm is a nonconvex optimization problem integrating the ESSs dynamics, the topological and power technical constraints of the grid, and the modeling of the cascading effects of potential adverse events. An equivalent (i.e., having the same optimal solution) proxy of the nonconvex problem is proposed to make the solution more tractable. Simulations performed on a 16-bus test distribution network validate the proposed control strategy

Recent trends of the most used metaheuristic techniques for distribution network reconfiguration

Distribution network reconfiguration (DNR) continues to be a good option to reduce technical losses in a distribution power grid. However, this non-linear combinatorial problem is not easy to assess by exact methods when solving for large distribution networks, which requires large computational times. For solving this type of problem, some researchers prefer to use metaheuristic techniques due to convergence speed, near-optimal solutions, and simple programming. Some literature reviews specialize in topics concerning the optimization of power network reconfiguration and try to cover most techniques. Nevertheless, this does not allow detailing properly the use of each technique, which is important to identify the trend. The contributions of this paper are three-fold. First, it presents the objective functions and constraints used in DNR with the most used metaheuristics. Second, it reviews the most important techniques such as particle swarm optimization (PSO), genetic algorithm (GA), simulated annealing (SA), ant colony optimization (ACO), immune algorithms (IA), and tabu search (TS). Finally, this paper presents the trend of each technique from 2011 to 2016. This paper will be useful for researchers interested in knowing the advances of recent approaches in these metaheuristics applied to DNR in order to continue developing new best algorithms and improving solutions for the topi

Non-Uniform Aged Modules Reconfiguration for Large-Scale PV Array

© 2001-2011 IEEE. In the past decades, a large number of photovoltaic (PV) plants have been built. Due to the minor physical differences between PV cells and the influence of environmental factors such as rains, temperature, and humidity, the aging of a PV array is often distributed unevenly within each PV module. This non-uniform aging causes further decreased output power, which is often easily observed for large size PV arrays. Although the global maximum power point tracking (GMPPT) strategy can improve the output power, the GMPPT cannot exploit the maximal power generation potential from non-uniform aging PV arrays. In order to exploit further the power generation potential and extend the service time of non-uniform aging PV arrays, a novel PV array reconfiguration method is developed in this paper. The concept of cell unit is applied to investigate the aging phenomenon of PV modules, and each PV module is assumed to be composed of three submodules, while these three submodules within any single PV module might have different aging conditions and, thus, different power-output capacities. The challenge is how to rearrange the PV array under the cases where: 1) each PV module has non-uniformly aged cell units; 2) there are a large number of PV modules; and 3) the voltage working range is restricted. To solve these problems, a nonlinear integer programming problem is formulated to maximize the power output under the constraints of non-uniformly aging and voltage restrictions. A small size 7×10 PV array is simulated to illustrate the proposed method. Furthermore, medium size 20×10 and large size 125×20 PV arrays are employed to verify the feasibility of the proposed method. A 1.5 kW 2×4 real PV array under non-uniform aging conditions is presented and experimentally tested to confirm the proposed rearrangement method

Review of trends and targets of complex systems for power system optimization

Optimization systems (OSs) allow operators of electrical power systems (PS) to optimally operate PSs and to also create optimal PS development plans. The inclusion of OSs in the PS is a big trend nowadays, and the demand for PS optimization tools and PS-OSs experts is growing. The aim of this review is to define the current dynamics and trends in PS optimization research and to present several papers that clearly and comprehensively describe PS OSs with characteristics corresponding to the identified current main trends in this research area. The current dynamics and trends of the research area were defined on the basis of the results of an analysis of the database of 255 PS-OS-presenting papers published from December 2015 to July 2019. Eleven main characteristics of the current PS OSs were identified. The results of the statistical analyses give four characteristics of PS OSs which are currently the most frequently presented in research papers: OSs for minimizing the price of electricity/OSs reducing PS operation costs, OSs for optimizing the operation of renewable energy sources, OSs for regulating the power consumption during the optimization process, and OSs for regulating the energy storage systems operation during the optimization process. Finally, individual identified characteristics of the current PS OSs are briefly described. In the analysis, all PS OSs presented in the observed time period were analyzed regardless of the part of the PS for which the operation was optimized by the PS OS, the voltage level of the optimized PS part, or the optimization goal of the PS OS.Web of Science135art. no. 107