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Value Sharing within Renewable Energy Communities

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A: Sustainable Energy".

Deadline for manuscript submissions: closed (11 November 2023) | Viewed by 5931

Special Issue Editors


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Guest Editor
1. Department of Energy “Galileo Ferraris”, Politecnico di Torino, Turin, Italy
2. Energy Center Lab, Politecnico di Torino, 10138 Turin, Italy
Interests: intermittent renewable energy sources; energy storage systems; energy system design; user demand; energy communities; energy policies

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Guest Editor
1. Department of Energy, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
2. Energy Center Lab, Politecnico di Torino, 10138 Turin, Italy
Interests: synthetic fuels; electron fuels; renewable fuels; biogas; biomethane; power-to-gas; power-to-liquids
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
1. Energy Center, Politecnico di Torino, 10138 Turin, Italy
2. Energy Center Lab, Politecnico di Torino, 10138 Turin, Italy
Interests: energy transition; energy communities; business models; financial tools

Special Issue Information

Dear Colleagues,

Renewable energy communities (RECs) have recently been regulated by many countries as a policy to foster the transition toward a net-zero energy system. REC initiatives aim to encourage a more active role of citizens in the energy sector, for example by converting energy consumers into collective or self-prosumers, promoting the ownership of distributed renewable energy power plants.

Renewable energy community initiatives are complex projects. Their technical and economic viability depends on multiple interdependent factors. In the literature, authors have investigated the optimal design of RECs for the integration of different distributed renewable energy source technologies in the energy system. Many have analysed how REC projects can reduce energy costs for REC members and reduce their GHG footprint.

This Special Issue focuses on the topic of value sharing within a Renewable Energy Community. With the term “value”, we refer to a broad spectrum of benefits from a perspective of different stakeholders: citizens (energy saving, cost reduction, automation, social inclusion, energy poverty, etc.), countries (primary energy demand, net-zero transition, energy sources, energy autarchy, mineral resources, economy, islanded and rural areas, etc.), energy grid (energy quality and reliability, grid efficiency, energy loss, grid expansion, grid optimization, etc.), and service companies (REC management, hardware and software control devices, optimization algorithms, etc.). In this Special Issue, we encourage contribution to bi-level trading with the market and among REC members; distributing revenues and sharing algorithms among REC members; optimal design of REC energy system technologies to reduce energy cost, energy security and reliability; planning of RECs for achieving net-zero energy transition target at national or local level, or in isolated and rural areas; optimization of REC operation using flexibility provided by load shift, demand-side management, demand response and storage systems; adoption of REC policies in different countries; business models for RECs.

Contributions reporting real-world case studies are also welcome. All submitted manuscripts will be peer-reviewed in accordance with the quality standards of the Energies journal. This Special Issue strongly encourages the submission of original research and literature review manuscripts. In the case of submission of an original research manuscript, the results must be new, replicable, and supported by a formal methodology, such as comprehensive mathematical models, algorithmic procedures, and numerical experiments. Results data presented as an illustration or figures should be provided (in the paper or as supplementary material) to ensure the replicability of the results.

Dr. Francesco Demetrio Minuto
Dr. Andrea Lanzini
Dr. Sergio Olivero
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • policy adoption
  • energy shares
  • energy community internal trade
  • REC business models
  • optimization of REC assets schedule
  • energy system optimization
  • decentralized/centralized optimization
  • diffusion innovation
  • design of REC energy system
  • energy security
  • net-zero transition
  • ledger technology
  • distribution or sharing algorithms
  • optimization algorithms
  • work from home behavior
  • energy behavior shift
  • storage flexibility
  • cost minimization
  • uncertainty of load demand and generation
  • REC isolated or rural distribution system
  • citizen energy consumption awareness

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Published Papers (2 papers)

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Research

24 pages, 4234 KiB  
Article
Forecasting Electricity Demand by Neural Networks and Definition of Inputs by Multi-Criteria Analysis
by Carolina Deina, João Lucas Ferreira dos Santos, Lucas Henrique Biuk, Mauro Lizot, Attilio Converti, Hugo Valadares Siqueira and Flavio Trojan
Energies 2023, 16(4), 1712; https://doi.org/10.3390/en16041712 - 8 Feb 2023
Cited by 6 | Viewed by 2320
Abstract
The planning of efficient policies based on forecasting electricity demand is essential to guarantee the continuity of energy supply for consumers. Some techniques for forecasting electricity demand have used specific procedures to define input variables, which can be particular to each case study. [...] Read more.
The planning of efficient policies based on forecasting electricity demand is essential to guarantee the continuity of energy supply for consumers. Some techniques for forecasting electricity demand have used specific procedures to define input variables, which can be particular to each case study. However, the definition of independent and casual variables is still an issue to be explored. There is a lack of models that could help the selection of independent variables, based on correlate criteria and level of importance integrated with artificial networks, which could directly impact the forecasting quality. This work presents a model that integrates a multi-criteria approach which provides the selection of relevant independent variables and artificial neural networks to forecast the electricity demand in countries. It provides to consider the particularities of each application. To demonstrate the applicability of the model a time series of electricity consumption from a southern region of Brazil was used. The dependent inputs used by the neural networks were selected using a traditional method called Wrapper. As a result of this application, with the multi-criteria ELECTRE I method was possible to recognize temperature and average evaporation as explanatory variables. When the variables selected by the multi-criteria approach were included in the predictive models, were observed more consistent results together with artificial neural networks, better than the traditional linear models. The Radial Basis Function Networks and Extreme Learning Machines stood out as potential techniques to be used integrated with a multi-criteria method to better perform the forecasting. Full article
(This article belongs to the Special Issue Value Sharing within Renewable Energy Communities)
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33 pages, 1217 KiB  
Article
Renewable Energy-Based Energy-Efficient Off-Grid Base Stations for Heterogeneous Network
by Khondoker Ziaul Islam, Md. Sanwar Hossain, B. M. Ruhul Amin, G. M. Shafiullah and Ferdous Sohel
Energies 2023, 16(1), 169; https://doi.org/10.3390/en16010169 - 23 Dec 2022
Cited by 3 | Viewed by 2799
Abstract
The heterogeneous network (HetNet) is a specified cellular platform to tackle the rapidly growing anticipated data traffic. From a communications perspective, data loads can be mapped to energy loads that are generally placed on the operator networks. Meanwhile, renewable energy-aided networks offer to [...] Read more.
The heterogeneous network (HetNet) is a specified cellular platform to tackle the rapidly growing anticipated data traffic. From a communications perspective, data loads can be mapped to energy loads that are generally placed on the operator networks. Meanwhile, renewable energy-aided networks offer to curtailed fossil fuel consumption, so to reduce the environmental pollution. This paper proposes a renewable energy based power supply architecture for the off-grid HetNet using a novel energy sharing model. Solar photovoltaics (PV) along with sufficient energy storage devices are used for each macro, micro, pico, or femto base station (BS). Additionally, a biomass generator (BG) is used for macro and micro BSs. The collocated macro and micro BSs are connected through end-to-end resistive lines. A novel-weighted proportional-fair resource-scheduling algorithm with sleep mechanisms is proposed for non-real time (NRT) applications by trading-off the power consumption and communication delays. Furthermore, the proposed algorithm with an extended discontinuous reception (eDRX) and power saving mode (PSM) for narrowband internet of things (IoT) applications extends the battery lifetime for IoT devices. HOMER optimization software is used to perform optimal system architecture, economic, and carbon footprint analyses while the Monte-Carlo simulation tool is used for evaluating the throughput and energy efficiency performances. The proposed algorithms are validated through the practical data of the rural areas of Bangladesh from which it is evident that the proposed power supply architecture is energy-efficient, cost-effective, reliable, and eco-friendly. Full article
(This article belongs to the Special Issue Value Sharing within Renewable Energy Communities)
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