After the spread of the SARS-CoV-2 epidemic out of China, evolution in the pandemic worldwide shows dramatic differences among countries. In Europe, the situation of Italy first and later Spain has generated great concen, and despite other countries show better prospects, large uncertainties yet remain on the future evolution and the efficacy of containment, mitigation, or attack strategies. This Manuscript was originally written in the last days of March as a way to report on the first current wave of the pandemic. The results were updated several times for March and also for the month of July. Here we applied a modified SEIR compartmental model accounting for the spread of infection during the latent period, in which we also incorporate effects of varying proportions of containment. We fit data to reported infected populations at the beginning of the first peak of the pandemic to account for the uncertainties in case reporting and study the scenario projections for the individual regions (CCAA). The aim of this model it’s to evaluate the confinement rate at the first stages of the epidemic outbreak in order to assess the scenarios that minimize the incidence but also the mortality. Results indicate that with data for March 23, the epidemics follow an evolution similar to the isolation of 1 , 5 percent of the population, and if there were no effects of intervention actions it might reach a maximum of over 1.4 M infected around April 27. The effect on the epidemics of the ongoing partial confinement measures is yet unknown (an update of results with data until March 31st is included), but increasing the isolation around ten times more could drastically reduce the peak to over 100 k cases by early April, while each day of delay in taking this hard containment scenario represents a 90 percent increase of the infected population at the peak. Dynamics at the sub aggregated levels of CCAA show epidemics at the different levels of progression with the most worrying situation in Madrid and Catalonia. Increasing alpha values up to 10 times, in addition to a drastic reduction in clinical cases, would also more than a half the number of deaths. Updates for March 31st simulations indicate a substantial reduction in burden is underway. A similar approach conducted for Italy pre-and post-intervention also begins to suggest a substantial reduction in both infected and deaths has been achieved, showing the efficacy of drastic social distancing interventions. By last we show the real evolution of the pandemic up to the end of May and the beginning of July in order to calculate the real confinement rate from data to compare with the scenarios formulated at March.

A modified SEIR model to predict the COVID-19 outbreak in Spain and Italy: simulating control scenarios and multi-scale epidemics.

Numerical Methods for Ordinary Differential Equations

Integration of solar photovoltaic (PV) and battery storage systems is an upward trend for residential sector to achieve major targets like minimizing the electricity bill, grid dependency, emission and so forth. In recent years, there has been a rapid deployment of PV and battery installation in residential sector. In this regard, optimal planning of PV-battery systems is a critical issue for the designers, consumers, and network operators due to high number of parameters that can affect the optimization problem. This paper aims to present a comprehensive and critical review on the effective parameters in optimal planning process of solar PV and battery storage system for grid-connected residential sector. The key parameters in process of optimal planning for PV-battery system are recognized and explained. These parameters are economic and technical data, objective functions, energy management systems, design constraints, optimization algorithms, and electricity pricing programs. A timely review on the state-of-the-art studies in PV-battery optimal planning is presented. The challenges, trends and latest developments in the topic are discussed. At the end, scopes for future studies are developed. It is found that new guidelines should be provided for the customers based on various electricity rates and demand response programs. Also, several design considerations like grid dependency and resiliency need further investigation in the optimal planning of PV-battery systems. • A timely survey on the state-of-the-art in optimal planning of PV-battery for grid-connected residential sector (GCRS). • A classification of existing studies on optimal planning of PV-battery for GCRS. • A review of the latest research developments on optimal planning of PV-battery for GCRS. • Recent challenges for optimal planning problem of PV-battery for GCRS. • An outlook of the future research scopes in optimal planning of PV-battery for GCRS. 

Optimal planning of solar photovoltaic and battery storage systems for grid-connected residential sector: Review, challenges and new perspectives

Integration of solar photovoltaic (PV) and battery storage systems is an upward trend for residential sector to achieve major targets like minimizing the electricity bill, grid dependency, emission and so forth. In recent years, there has been a rapid deployment of PV and battery installation in residential sector. In this regard, optimal planning of PV-battery systems is a critical issue for the designers, consumers, and network operators due to high number of parameters that can affect the optimization problem. This paper aims to present a comprehensive and critical review on the effective parameters in optimal planning process of solar PV and battery storage system for grid-connected residential sector. The key parameters in process of optimal planning for PV-battery system are recognized and explained. These parameters are economic and technical data, objective functions, energy management systems, design constraints, optimization algorithms, and electricity pricing programs. A timely review on the state-of-the-art studies in PV-battery optimal planning is presented. The challenges, trends and latest developments in the topic are discussed. At the end, scopes for future studies are developed. It is found that new guidelines should be provided for the customers based on various electricity rates and demand response programs. Also, several design considerations like grid dependency and resiliency need further investigation in the optimal planning of PV-battery systems.

Improved wild horse optimizer with deep learning enabled battery management system for internet of things based hybrid electric vehicles

A novel methodology for optimal sizing photovoltaic-battery systems in smart homes considering grid outages and demand response

A comprehensive electrical-gas-hydrogen Microgrid model for energy management applications

An improved wild horse optimization algorithm for reliability based optimal DG planning of radial distribution networks

Operation of energy hubs with storage systems, solar, wind and biomass units connected to demand response aggregators

Battery storage system design has become a crucial task for nanogrids and microgrids planning, as it strongly determines the techno-economic viability of the project. Despite that, most of developed methodologies for optimally planning this kind of systems still present some important issues like high computational burden or insufficient results. This paper develops a novel methodology for battery storage system planning in nanogrids and microgrdis, which aims at overcoming the main issues presented by other methodologies. To achieve this goal, our proposal originally combines different software, clustering techniques and optimization tools. As salient features of the developed approach, it is worth remarking its efficiency, versatility, ability to manage with different time horizons and comprehensiveness. A prospective nanogrid in the region of Cuenca, Ecuador, serves as illustrative case study to show the capabilities, efficiency and effectiveness of the proposed approach as providing sufficient guidelines for its universal applicability. Among other relevant results, our proposal is able to determine that, for the studied grid, the daily operating cost can be reduced up to 17% by using Nickel-Cadmium batteries, however, the usage of Lead-Acid and Sodium-Sulfur technologies resulted more attractive through the project lifetime due to their longer lifetimes and relatively low capital costs.

Marcos Tostado-Véliz

Papers

A novel methodology for optimal sizing photovoltaic-battery systems in smart homes considering grid outages and demand response

A comprehensive electrical-gas-hydrogen Microgrid model for energy management applications

An improved wild horse optimization algorithm for reliability based optimal DG planning of radial distribution networks

Operation of energy hubs with storage systems, solar, wind and biomass units connected to demand response aggregators

A novel methodology for comprehensive planning of battery storage systems