Optimal allocation of FACTS devices in distribution networks using Imperialist Competitive Algorithm

Copyright © 2005-2015 Praise Worthy Prize. The publisher granted a permission to the author to archive this article in BURA.FACTS devices are used for controlling the voltage, stability, power flow and security of transmission lines. Imperialist Competitive is a recently developed optimization technique, used widely in power systems. This paper presents an approach to finding the optimal location and size of FACTS devices in a distribution network using the Imperialist Competitive technique. IEEE 30-bus system is used as a case study. The results show the advantages of the Imperialist Competitive technique over the conventional approaches. © 2013 Praise Worthy Prize S.r.l. - All rights reserved

Improving power system static security margins by means of a real coded genetic algorithm

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. P. Martín and A. Sierra, "Improving Power System Static Security Margins by Means of a Real Coded Genetic Algorithm," in IEEE Transactions on Power Systems, vol. 31, no. 3, pp. 1915-1924, May 2016. doi: 10.1109/TPWRS.2015.2439579This paper introduces a new method of removing thermal overloads and voltage limits in an electric power system by means of the Evolution of Corrective and Preventive control Actions (ECPA). The goal is to find the minimum number of control actions that solve the identified limit violations at minimum cost. A recombination operator based on form theory allows the codification of control actions in a natural and simple way. ECPA has been tested on the IEEE 30-bus and the IEEE 118-bus systems. The limit violations are solved at minimum cost and with fewer control actions on average than alternative methods

Optimal operation of DC networks to support power system outage management

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The penetration of dc networks for different applications in power systems is increasing. This paper presents a novel methodology for security-constrained optimal power flow (SCOPF) operation of a power system, such as a smart grid or a supergrid, with an embedded dc network. The methodology demonstrates that dc networks can be operated to provide support to ac systems, increasing its security of supply and resilience in case of outages, while reducing operational costs. Moreover, the outage management support can be achieved via a preventive SCOPF – i.e. the combined network stays N-1 secure after outages without need for further control action – or via a corrective SCOPF, by using the fast controls of the ac-dc converters to react to the contingencies. The methodology relies on the construction of a binary outage matrix and optimizes only the control variables of the ac and dc networks. It was successfully tested in system with 12 buses and in the IEEE30 network with 35 buses. Operational savings of up to 1% and 0.52% were obtained for the first and second networks, respectively, while network violations for the N-1 contingency scenarios were completely eliminated in the first and reduced by 70% in the former.Postprint (author's final draft

An enhanced contingency-based model for joint energy and reserve markets operation by considering wind and energy storage systems

This paper presents a contingency-based stochastic security-constrained unit commitment to address the integration of wind power producers to the joint energy and reserve markets. The contingency ranking is a popular method for reducing the computation burden of the unit commitment problem, but performing the contingency analysis changes the high-impact events in previous ranking methods. This paper employs an intelligent contingency ranking technique to address the above issue and to find the actual top-ranked outages based on the final solution. Also, energy storage systems are considered to evaluate the impact of the scheduling of storage under uncertainties. Numerical results on a six-bus and the IEEE 118-bus test systems show the effectiveness of the proposed approach. Furthermore, it shows that utilizing both wind farms and storage devices will reduce the total operational cost of the system, while the intelligent contingency ranking analysis and enough reserves ensure the security of power supply.©2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed

A Review on Application of Artificial Intelligence Techniques in Microgrids

A microgrid can be formed by the integration of different components such as loads, renewable/conventional units, and energy storage systems in a local area. Microgrids with the advantages of being flexible, environmentally friendly, and self-sufficient can improve the power system performance metrics such as resiliency and reliability. However, design and implementation of microgrids are always faced with different challenges considering the uncertainties associated with loads and renewable energy resources (RERs), sudden load variations, energy management of several energy resources, etc. Therefore, it is required to employ such rapid and accurate methods, as artificial intelligence (AI) techniques, to address these challenges and improve the MG's efficiency, stability, security, and reliability. Utilization of AI helps to develop systems as intelligent as humans to learn, decide, and solve problems. This paper presents a review on different applications of AI-based techniques in microgrids such as energy management, load and generation forecasting, protection, power electronics control, and cyber security. Different AI tasks such as regression and classification in microgrids are discussed using methods including machine learning, artificial neural networks, fuzzy logic, support vector machines, etc. The advantages, limitation, and future trends of AI applications in microgrids are discussed.©2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed

An Analytical Framework for Evaluating the Impact of Distribution-Level LVRT Response on Transmission System Security

Low voltage ride through (LVRT) is a solution to increase the tolerance of distributed energy resources (DERs) against the voltage sags. However, the possibility of DERs trip according to the present grid codes exists. Such trips are essential for transmission systems with connected DER-penetrated distribution networks (DPDNs). This paper investigates an analytical framework to see the impact of distribution-level LVRT response on transmission system security. LVRT response stands for the total amount of lost DER capacity due to the inability to meet the LVRT requirement during the voltage sag. This generation loss in the distribution sector can expose the transmission network to lines overloading after fault clearance. The proposed novel approach is based on a source contingency analysis that lets TSOs conduct an LVRT-oriented security assessment. A mathematical function is defined as the LVRT response function of DPDNs. This function gives the lost DER capacity in response to the transmission level transient faults and is constructed by distribution system operators (DSOs). The TSO can use these functions to assess the loading security of transmission lines in post-clearance conditions. In this analytical framework, LVRT-oriented security is evaluated by calculating the risk of lines overloading under a large number of random faults.The proposed approach is implemented in two test power systems with a considerable DER penetration level to obtain the risk of line overloading due to the LVRT response in distribution networks.©2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed

Digital Architecture as Crime Control

This paper explains how theories of realspace architecture inform the prevention of computer crime. Despite the prevalence of the metaphor, architects in realspace and cyberspace have not talked to one another. There is a dearth of literature about digital architecture and crime altogether, and the realspace architectural literature on crime prevention is often far too soft for many software engineers. This paper will suggest the broad brushstrokes of potential design solutions to cybercrime, and in the course of so doing, will pose severe criticisms of the White House\u27s recent proposals on cybersecurity. The paper begins by introducing four concepts of realspace crime prevention through architecture. Design should: (1) create opportunities for natural surveillance, meaning its visibility and susceptibility to monitoring by residents, neighbors, and bystanders; (2) instill a sense of territoriality so that residents develop proprietary attitudes and outsiders feel deterred from entering a private space; (3) build communities and avoid social isolation; and (4) protect targets of crime. There are digital analogues to each goal. Natural-surveillance principles suggest new virtues of open-source platforms, such as Linux, and territoriality outlines a strong case for moving away from digital anonymity towards psuedonymity. The goal of building communities will similarly expose some new advantages for the original, and now eroding, end-to-end design of the Internet. An understanding of architecture and target prevention will illuminate why firewalls at end points will more effectively guarantee security than will attempts to bundle security into the architecture of the Net. And, in total, these architectural lessons will help us chart an alternative course to the federal government\u27s tepid approach to computer crime. By leaving the bulk of crime prevention to market forces, the government will encourage private barricades to develop - the equivalent of digital gated communities - with terrible consequences for the Net in general and interconnectivity in particular