Optimal Feeder Reconfiguration Optimization problem in Power Distribution Networks

Optimal feeder reconfiguration is a method used to determine optimal on/off statuses of tie and sectionalizing switches in order to reconfigure the network and improve certain objective goals. Mathematically, OFR is a mixed-integer nonlinear programsubjected to system constraints consisting of power flow equations, voltage limits, feeder capability limits and requirements for maintaining radial configuration of the network.In this paper, network reconfiguration problem is solved using branch exchange method. Solution involves a search for optimal on/off switch positionby transferring loads from one feeder to another, until no load transfer can further reduce the power losses, violations of voltage limits, and violations of branch capacity limits.Branch exchange method is applied on two feeder network, and results show that this method can be successfully used to decrease losses, improve voltage profile and resolve the overloading problem

Control algorythm of a smart grid device for optimal radial feeder load reconfiguration

Abstract Secondary distribution network, generally speaking, performs as well as the performance of its LV feeders. The main problem a feeder is experiencing is the load unbalancing due to the stochastic nature of its individual single-phase loads: bigger losses in certain phase accompanied with bed voltage regulation and voltage unbalance. The aim of this paper is to address the issue of automatic balancing as progressing from the end of the feeder towards the front using smart device based on three-ways switch selector and artificial intelligence algorithm to minimize the neutral current

Novel heuristic and SVM based optimization algorithm for improving distribution feeder performance

Abstract: Secondary distribution networks generally perform as well as its LV feeders are performing. The main problem that a feeder is experiencing would be the load unbalancing due to the stochastic nature of its individual single-phase loads: larger losses in certain phases accompanied by bad voltage regulation and voltage unbalance. In order to address this problem, it may be economical to install apparatus to automatically balance or partially balance the loads progressing from the end of the feeder towards the front using smart devices based on a three-ways switch selector and an artificial intelligence algorithm to minimize the neutral current. The main idea behind this paper is therefore to keep the three phases progressively balanced along the whole length of the line. A Support Vector Machines (SVM) implementation and a heuristic method are presented as the numerical algorithm

Reverse Engineering of Short Circuit Analyses

The electrical distribution system has evolved with embedded computer systems that can better manage the electrical fault that occurred around the feeders. Such random events can affect the reliability indices of overall systems. Computerized management system for distribution operation has been improving with the advanced sensing technologies. The general research question is here to articulate is the responsiveness for utility crew to pinpoint the exact location of a fault based on the SCADA fault indicators from pole-mounted feeder remote terminal units (FRTUs). This has been a tricky question because it relies on the information received from the sensors that can conclude fault with logic\u27s of over currents. The merit of this work can benefit at large the grid reliability because of time-saving in searching the exact location of a fault. The main contribution of this thesis is to utilize the 3-phase unbalanced power flow method to incrementally search for narrowing the localization of electrical short circuits. This is known as the reversal of the typical short circuit approach where a location of the fault is presumed. The 3 topological configurations of simulation studied in this thesis exhibit the typical radial configuration of a distribution feeder have been researched based on unidirectional and bidirectional power flow simulation. The exact fault location is carried in two steps. Firstly, a bisection search algorithm has been employed. Secondly, an incremental adjustment to match the simulated currents of fault with the measurements is conducted. Finally, the sensitivity analysis of a search can be improved with the proposed algorithm that leads to matching of telemetered and calculated values. The analysis of exact fault location is carried in unidirectional and bidirectional flow of power. Distributed energy resources (DER) such as residential PV at a household level as well the wind energy changes affect the protective relaying within a feeder as well as the reconfigurability of the switching sequences. Furthermost, the bidirectionality of power flow in an unbalanced manner would also be a challenging issue to deal with the power quality in automation. Finally, the simulation results based on unidirectional and bidirectional power flow are extensively discussed along with the future scope

Immune System Based Control and Intelligent Agent Design for Power System Applications

The National Academy of Engineering has selected the US Electric Power Grid as the supreme engineering achievement of the 20th century. Yet, this same grid is struggling to keep up with the increasing demand for electricity, its quality and cost. A growing recognition of the need to modernize the grid to meet future challenges has found articulation in the vision of a Smart Grid in using new control strategies that are intelligent, distributed, and adaptive. The objective of this work is to develop smart control systems inspired from the biological Human Immune System to better manage the power grid at the both generation and distribution levels. The work is divided into three main sections. In the first section, we addressed the problem of Automatic Generation Control design. The Clonal Selection theory is successfully applied as an optimization technique to obtain decentralized control gains that minimize a performance index based on Area Control Errors. Then the Immune Network theory is used to design adaptive controllers in order to diminish the excess maneuvering of the units and help the control areas comply with the North American Electric Reliability Corporation\u27s standards set to insure good quality of service and equitable mutual assistance by the interconnected energy balancing areas. The second section of this work addresses the design and deployment of Multi Agent Systems on both terrestrial and shipboard power systems self-healing using a novel approach based on the Immune Multi-Agent System (IMAS). The Immune System is viewed as a highly organized and distributed Multi-Cell System that strives to heal the body by working together and communicating to get rid of the pathogens. In this work both simulation and hardware design and deployment of the MAS are addressed. The third section of this work consists in developing a small scale smart circuit by modifying and upgrading the existing Analog Power Simulator to demonstrate the effectiveness of the developed technologies. We showed how to develop smart Agents hardware along with a wireless communication platform and the electronic switches. After putting together the different designed pieces, the resulting Multi Agent System is integrated into the Power Simulator Hardware. The multi Agent System developed is tested for fault isolation, reconfiguration, and restoration problems by simulating a permanent three phase fault on one of the feeder lines. The experimental results show that the Multi Agent System hardware developed performed effectively and in a timely manner which confirms that this technology is very promising and a very good candidate for Smart Grid control applications

Optimal Distribution Reconfiguration and Demand Management within Practical Operational Constraints

This dissertation focuses on specific aspects of the technical design and operation of a `smart\u27 distribution system incorporating new technology in the design process. The main purpose of this dissertation is to propose new algorithms in order to achieve a more reliable and economic distribution system. First, a general approach based on Mixed Integer Programming (MIP) is proposed to formulate the reconfiguration problem for a radial/weakly meshed distribution network or restoration following a fault. Two objectives considered in this study are to minimize the active power loss, and to minimize the number of switching operations with respect to operational constraints, such as power balance, line ow limits, voltage limit, and radiality of the network. The latter is the most challenging issue in solving the problem by MIP. A novel approach based on Depth-First Search (DFS) algorithm is implemented to avoid cycles and loops in the system. Due to insufficient measurements and high penetration of controllable loads and renewable resources, reconfiguration with deterministic optimization may not lead to an optimal/feasible result. Therefore, two different methods are proposed to solve the reconfiguration problem in presence of load uncertainty. Second, a new pricing algorithm for residential load participation in demand response program is proposed. The objective is to reduce the cost to the utility company while mitigating the impact on customer satisfaction. This is an iterative approach in which residents and energy supplier exchange information on consumption and price. The prices as well as appliance schedule for the residential customers will be achieved at the point of convergence. As an important contribution of this work, distribution network constraints such as voltage limits, equipment capacity limits, and phase balance constraints are considered in the pricing algorithm. Similar to the locational marginal price (LMP) at the transmission level, different prices for distribution nodes will be obtained. Primary consideration in the proposed approach, and frequently ignored in the literature, is to avoid overly sophisticated decision-making at the customer level. Most customers will have limited capacity or need for elaborate scheduling where actual energy cost savings will be modest

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

Optimal network reconfiguration for congestion management optimization in active distribution networks

Recently, the distribution networks are working close to their physical device limits. When congestion takes place, distributed switches can be controlled to change their status in order to find a new optimal network configuration that solves that congestion. In this paper, a new methodology for congestion management by means of distributed network reconfiguration is presented. Switches and controllable voltage units such as PV units were used in the optimization process. The optimization process is guided by a weighted objective function that takes into account real power losses as well as operational limits of the power system under study. The methodology is tested in an Italian real power distribution system.The research leading to these results has received funding from the European Union seventh framework program FP7-SMARTCITIES-2013 under grant agreement 608860 IDE4L – Ideal grid for all