Javier Rosa

Design and verification of smart and scalable DC microgrids for emerging regions

Roughly 1.3 billion people in developing countries still live without access to reliable electricity. As expanding access using current technologies will accelerate global climate change, there is a strong need for novel solutions that displace fossil fuels and are financially viable for developing regions. A novel DC microgrid solution that is geared at maximizing efficiency and reducing system installation cost is described in this paper. Relevant simulation and experimental results, as well as a proposal for undertaking field-testing of the technical and economic viability of the microgrid system are presented.

Scalable DC Microgrids for Rural Electrification in Emerging Regions

We present the design and experimental validation of a scalable dc microgrid for rural electrification in emerging regions. A salient property of the dc microgrid architecture is the distributed control of the grid voltage, which enables both instantaneous power sharing and a metric for determining the available grid power. A droop-voltage power-sharing scheme is implemented wherein the bus voltage droops in response to low supply/high demand. In addition, the architecture of the dc microgrid aims to minimize the losses associated with stored energy by distributing storage to individual households. In this way, the number of conversion steps and line losses are reduced. We calculate that the levelized cost of electricity of the proposed dc microgrid over a 15-year time horizon is

A scalable dc microgrid architecture for rural electrification in emerging regions

0.35/kWh. We also present the experimental results from a scaled-down experimental prototype that demonstrates the steady-state behavior, the perturbation response, and the overall efficiency of the system. Moreover, we present fault mitigation strategies for various faults that can be expected to occur in a microgrid distribution system. The experimental results demonstrate the suitability of the presented dc microgrid architecture as a technically advantageous and cost-effective method for electrifying emerging regions.

Comparing Cookstove Usage Measured with Sensors Versus Cell Phone-Based Surveys in Darfur, Sudan

We present the design and experimental validation of a scalable dc microgrid architecture for rural electrification. The microgrid design has been driven by field data collected from Kenya and India. The salient features of the microgrid are distributed voltage control and distributed storage, which enable developed world grid cost parity. In this paper, we calculate that the levelized cost of electricity (LCOE) for the proposed dc microgrid system will be less than

Grid watch: mapping blackouts with smart phones

0.40 per kW-hr. We also present experimental results from a locally installed dc microgrid prototype that demonstrate the steady state behavior, the perturbation response, and the overall efficiency of the system. The experimental results demonstrate the suitability of the presented dc microgrid architecture as a technically advantageous and cost effective method for electrifying emerging regions.

Parallel software architecture for experimental workflows in computational biology on clouds

Three billion people rely on combustion of biomass to cook their food, and the resulting air pollution kills 4 million people annually. Replacing inefficient traditional stoves with “improved cookstoves” may help reduce the dangers of cooking. Therefore analysts, policy makers, and practitioners are eager to quantify adoption of improved cookstoves. In this study, we use 170 instrumented cookstoves as well as cellphone-based surveys to measure the adoption of free-of-charge Berkeley-Darfur Stoves (BDSs) in Darfur, Sudan where roughly 34,000 BDS have been disseminated. We estimate that at least 71 % of participants use the stove more than 10 % of days that the sensor was installed on the cookstove. Compared to sensor-measured data, surveyed participants overestimate adoption both in terms of daily hours of cooking and daily cooking events (p < 0.001). Average participants overreport daily cooking hours by 1.2 h and daily cooking events by 1.3 events. These overestimations are roughly double sensor-measured values. Data reported by participants may be erroneous due to difficulty in recollection, courtesy bias, or the desire to keep personal information obscure. A significant portion of sensors was lost during this study, presumably due to thermal damage from the unexpected commonality of charcoal fires in the BDS; thus pointing to a potential need to redesign the stove to accommodate users’ desire to cook using multiple fuel types. The cooking event detection algorithm seems to perform well in terms of face validity, but a database of cooking logs or witnessed accounts of cooking is absent; the algorithm should be trained against expert-labeled data for the local cooking context to further refine its performance.

Erratum to: Is entheses ultrasound reliable? A reading Latin American exercise

The power grid is one of humanitys most significant engineering undertakings and it is essential in developed and developing nations alike. Currently, transparency into the power grid relies on utility companies and more fine-grained insight is provided by costly smart meter deployments. We claim that greater visibility into power grid conditions can be provided in an inexpensive and crowd-sourced manner independent of utility companies by leveraging existing smartphones. Our key insight is that an unmodified smartphone can detect power outages by monitoring changes to its own power state, locally verifying these outages using a variety of sensors that reduce the likelihood of false power outage reports, and corroborating actual reports with other phones through data aggregation in the cloud. The proposed approach enables a decentralized system that can scale, potentially providing researchers and concerned citizens with a powerful new tool to analyze the power grid and hold utility companies accountable for poor power quality. This paper demonstrates the viability of the basic idea, identifies a number of challenges that are specific to this application as well as ones that are common to many crowd-sourced applications, and highlights some improvements to smartphone operating systems that could better support such applications in the future.

Enabling Micro-level Demand-Side Grid Flexiblity in Resource Constrained Environments

Cloud computing opens new possibilities for computational biologists. Given the pay-as-you-go model and the commodity hardware base, new tools for extensive parallelism are needed to make experimentation in the cloud an attractive option. In this paper, we present EasyProt, a parallel message-passing architecture designed for developing experimental workflows in computational biology while harnessing the power of cloud resources. The system exploits parallelism in two ways: by multithreading modular components on virtual machines while respecting data dependencies and by allowing expansion across multiple virtual machines. Components of the system, called elements, are easily configured for efficient modification and testing of workflows during ever-changing experimentation. Though EasyProt, as an abstract cloud programming model, can be extended beyond computational biology, current development brings cloud computing to experimenters in this important discipline who are facing unprecedented data-processing challenges, with a type system designed for proteomics, interactomics and comparative genomics data, and a suite of elements that perform useful analysis tasks on biological data using cloud resources. Availability: EasyProt is available as a public abstract machine image (AMI) on Amazon EC2 cloud service, with an open source license, registered with manifest easyprot-ami/easyprot.img.manifest.xml.

MDB: A Metadata Tracking Microcontroller Micro-Database

1 Rheumatology Unit, La Paz University Hospital, P° de la Castellana 261, 28046 Madrid, Spain 2 Musculoskeletal Ultrasound Laboratory, Instituto Nacional de Rehabilitacion, Mexico City, Mexico 3 Rheumatology Unit, CentroMedico Clinica Santa Maria La Dehesa, Santiago, Chile 4 Rheumatology Unit, Hospital Edgardo Rebagliati Martins, Lima, Peru 5 Rheumatology Unit, Hospital Felix Bulnes Cerda-Universidad Mayor, Santiago, Chile 6 Rheumatology Unit, Facultad de Ciencias Medicas, Hospital Nacional de Clinicas, Cordoba, Argentina 7 Rheumatology Unit, Instituto Reumatologico Strusberg, Cordoba, Argentina 8 Rheumatology Unit, Instituto de Rehabilitacion Psicofisica, Buenos Aires, Argentina 9 Reumatoligya SA, Rheumatology Medellin, Medellin, Colombia 10 Rheumatology Unit, Hospital Universitario Fundacion Santa Fe de Bogota, Bogota, Colombia

Electrification for “Under Grid” households in Rural Kenya

The increased penetration of uncertain and variable renewable energy presents various resource and operational electric grid challenges 1 . Micro-level (household and small commercial) demand-side grid flexibility could be a cost-effective strategy to integrate high penetrations of wind and solar energy, but literature and field deployments exploring the necessary information and communication technologies (ICTs) are scant. This paper presents an exploratory framework for enabling information driven grid flexibility through the Internet of Things (IoT), and a proof-of-concept wireless sensor gateway (FlexBox) to collect the necessary parameters for adequately monitoring and actuating the micro-level demand-side. In the summer of 2015, thirty sensor gateways were deployed in the city of Managua (Nicaragua) to develop a baseline for a near future small-scale demand response pilot implementation. FlexBox field data has begun shedding light on relationships between ambient temperature and load energy consumption, load and building envelope energy efficiency challenges, latency communication network challenges, and opportunities to engage existing demand-side user behavioral patterns. Information driven grid flexibility strategies present great opportunity to develop new technologies, system architectures, and implementation approaches that can easily scale across regions, incomes, and levels of development.