Genetic characterization of Echinococcus granulosus from a large number of formalin-fixed, paraffin-embedded tissue samples of human isolates in Iran

Cystic echinococcosis (CE), caused by the larval stage of Echinococcus granulosus, presents an important medical and veterinary problem globally, including that in Iran. Different genotypes of E. granulosus have been reported from human isolates worldwide. This study identifies the genotype of the parasite responsible for human hydatidosis in three provinces of Iran using formalin-fixed paraffin-embedded tissue samples. In this study, 200 formalin-fixed paraffin-embedded tissue samples from human CE cases were collected from Alborz, Tehran, and Kerman provinces. Polymerase chain reaction amplification and sequencing of the partial mitochondrial cytochrome c oxidase subunit 1 gene were performed for genetic characterization of the samples. Phylogenetic analysis of the isolates from this study and reference sequences of different genotypes was done using a maximum likelihood method. In total, 54.4%, 0.8%, 1%, and 40.8% of the samples were identified as the G1, G2, G3, and G6 genotypes, respectively. The findings of the current study confirm the G1 genotype (sheep strain) to be the most prevalent genotype involved in human CE cases in Iran and indicates the high prevalence of the G6 genotype with a high infectivity for humans. Furthermore, this study illustrates the first documented human CE case in Iran infected with the G2 genotype. Copyright © 2015 by The American Society of Tropical Medicine and Hygiene

On the sensitivity of local flexibility markets to forecast error: A bi-level optimization approach

The large-scale integration of intermittent distributed energy resources has led to increased uncertainty in the planning and operation of distribution networks. The optimal flexibility dispatch is a recently introduced, power flow-based method that a distribution system operator can use to effectively determine the amount of flexibility it needs to procure from the controllable resources available on the demand side. However, the drawback of this method is that the optimal flexibility dispatch is inexact due to the relaxation error inherent in the second-order cone formulation. In this paper we propose a novel bi-level optimization problem, where the upper level problem seeks to minimize the relaxation error and the lower level solves the earlier introduced convex second-order cone optimal flexibility dispatch (SOC-OFD) problem. To make the problem tractable, we introduce an innovative reformulation to recast the bi-level problem as a non-linear, single level optimization problem which results in no loss of accuracy. We subsequently investigate the sensitivity of the optimal flexibility schedules and the locational flexibility prices with respect to uncertainty in load forecast and flexibility ranges of the demand response providers which are input parameters to the problem. The sensitivity analysis is performed based on the perturbed Karush-Kuhn-Tucker (KKT) conditions. We investigate the feasibility and scalability of the proposed method in three case studies of standardized 9-bus, 30-bus, and 300-bus test systems. Simulation results in terms of local flexibility prices are interpreted in economic terms and show the effectiveness of the proposed approach. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)

A market-based framework for demand side flexibility scheduling and dispatching

The massive integration of renewable energy resources increases the uncertainty with respect to real-time operation of the electrical systems. This transition introduces new challenges and opportunities for various entities that are involved in energy generation, transmission, distribution and consumption such as system operators and market participants in the wholesale electricity market. The concept of Decentralized Energy Management or Demand Response is emerging as one of the main approaches to resolve the violations of the network operation limits and to increase the flexibility of the system. This paper introduces an interaction framework for trading flexibility among proactive end-users in an economically efficient way. It proposes new market participants with their roles and functionalities, that will operate alongside the existing ones to ensure market efficiency and to enable secure operation of distribution grids. The proposed framework consists of a main mechanism called ‘ahead-markets scheduling’. The ahead-markets scheduling includes two sub-mechanisms, day-ahead and intra-day, which are operated by a local flexibility market operator. The ahead-markets scheduling provides a trading platform that allows market participants to reflect their need(s) for flexibility and to monetize flexibility services in a fair and competitive manner. It enables flexibility trades which will eventually facilitate network management for the system operator

On the sensitivity of local flexibility markets to forecast error: A bi-level optimization approach

The large-scale integration of intermittent distributed energy resources has led to increased uncertainty in the planning and operation of distribution networks. The optimal flexibility dispatch is a recently introduced, power flow-based method that a distribution system operator can use to effectively determine the amount of flexibility it needs to procure from the controllable resources available on the demand side. However, the drawback of this method is that the optimal flexibility dispatch is inexact due to the relaxation error inherent in the second-order cone formulation. In this paper we propose a novel bi-level optimization problem, where the upper level problem seeks to minimize the relaxation error and the lower level solves the earlier introduced convex second-order cone optimal flexibility dispatch (SOC-OFD) problem. To make the problem tractable, we introduce an innovative reformulation to recast the bi-level problem as a non-linear, single level optimization problem which results in no loss of accuracy. We subsequently investigate the sensitivity of the optimal flexibility schedules and the locational flexibility prices with respect to uncertainty in load forecast and flexibility ranges of the demand response providers which are input parameters to the problem. The sensitivity analysis is performed based on the perturbed Karush-Kuhn-Tucker (KKT) conditions. We investigate the feasibility and scalability of the proposed method in three case studies of standardized 9-bus, 30-bus, and 300-bus test systems. Simulation results in terms of local flexibility prices are interpreted in economic terms and show the effectiveness of the proposed approach. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)