Redirigiendo al acceso original de articulo en 20 segundos...
Inicio  /  Applied Sciences  /  Vol: 12 Par: 1 (2022)  /  Artículo
ARTÍCULO
TITULO

A Methodology for Exploiting Smart Prosumers? Flexibility in a Bottom-Up Aggregation Process

Diego Arnone    
Michele Cacioppo    
Mariano Giuseppe Ippolito    
Marzia Mammina    
Liliana Mineo    
Rossano Musca and Gaetano Zizzo    

Resumen

The electrical power system is evolving in a way that requires new measures for ensuring its secure and reliable operation. Demand-side aggregation represents one of the more interesting ways to provide ancillary services by the coordinated management of a multitude of different distributed resources. In this framework, aggregators play the main role in ensuring the effectiveness of the coordinated action of the distributed resources, usually becoming mediators in the relation between distribution system operators and smart prosumers. The research project DEMAND recently introduced a new concept in demand-side aggregation by proposing a scheme without a central aggregator where prosumers can share and combine their flexibility with a collaboration?competition mechanism in a platform called Virtual Aggregation Environment (VAE). This paper, after a brief introduction to the DEMAND project, presents the algorithm for the day-ahead estimation of prosumers? flexibility and the cooperative?competitive algorithm for the bottom-up aggregation. The first algorithm evaluates various couples of power variation and desired remuneration to be sent to the VAE for further elaborations and, for showing its potentiality, is applied to two different case studies: a passive user with only controllable loads and prosumers with controllable loads, photovoltaics and a storage system. The aggregation algorithm is instead discussed in detail, and its performance is evaluated for different population sizes.

 Artículos similares

       
 
Bakht Zaman, Dusica Marijan and Tetyana Kholodna    
The availability of automatic identification system (AIS) data for tracking vessels has paved the way for improvements in maritime safety and efficiency. However, one of the main challenges in using AIS data is often the low quality of the data. Practica... ver más

 
Simone Arena, Giuseppe Manca, Stefano Murru, Pier Francesco Orrù, Roberta Perna and Diego Reforgiato Recupero    
In the industrial domain, maintenance is essential to guarantee the correct operations, availability, and efficiency of machinery and systems. With the advent of Industry 4.0, solutions based on machine learning can be used for the prediction of future f... ver más
Revista: Applied Sciences

 
Rosario Ceravolo, Erica Lenticchia, Gaetano Miraglia, Valerio Oliva and Linda Scussolini    
System identification proves in general to be very efficient in the extraction of modal parameters of a structure under ambient vibrations. However, great difficulties can arise in the case of structures composed of many connected bodies, whose mutual in... ver más
Revista: Applied Sciences

 
Alessandro Renda, Pietro Ducange, Francesco Marcelloni, Dario Sabella, Miltiadis C. Filippou, Giovanni Nardini, Giovanni Stea, Antonio Virdis, Davide Micheli, Damiano Rapone and Leonardo Gomes Baltar    
This article presents the concept of federated learning (FL) of eXplainable Artificial Intelligence (XAI) models as an enabling technology in advanced 5G towards 6G systems and discusses its applicability to the automated vehicle networking use case. Alt... ver más
Revista: Information

 
Petros Zervoudakis, Haridimos Kondylakis, Nicolas Spyratos and Dimitris Plexousakis    
HIFUN is a high-level query language for expressing analytic queries of big datasets, offering a clear separation between the conceptual layer, where analytic queries are defined independently of the nature and location of data, and the physical layer, w... ver más
Revista: Algorithms