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Energy Communities for the Transition to a Sustainable and Decarbonized...
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Energy Communities for the Transition to a Sustainable and Decarbonized Society

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

Deadline for manuscript submissions: 28 August 2024 | Viewed by 2798

Special Issue Editors

Dr. Sergio Rech

E-Mail Website
Guest Editor
Department of Industrial Engineering, University of Padova, 35131 Padova, Italy
Interests: modeling; simulation; optimization; mixed-integer linear programming; energy engineering; energy conversion; energy storage; renewable energy technologies; smart energy systems; energy communities; predictive maintenance
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Andrea Lazzaretto

E-Mail Website
Guest Editor
Department of Industrial Engineering, University of Padova, Via Venezia 1, 35131 Padova, Italy
Interests: simulation; optimization; environmental and economic aspects and malfunction analysis of energy conversion systems for power; heating or cooling generation
Special Issues, Collections and Topics in MDPI journals
Dr. Gianluca Carraro

E-Mail Website
Guest Editor
Department of Industrial Engineering, University of Padova, Via Venezia 1, 35131 Padova, Italy
Interests: experimental evaluation, study of theoretical aspects and of the dynamic behaviour of energy production and recovery systems powered by renewable, waste heat and fossil fuels; design and off-design modeling, and optimization of the design and operation of complex energy systems, which are composed of groups of generating units that convert fossil, renewable, and unconventional energy sources into different forms of energy required by users

Special Issue Information

Dear Colleagues,

The transition towards a renewable-based energy system poses the challenge to foresee its future shape both on the energy generation and demand sides. On the one hand, the power generation paradigm is shifting from a centralized to a distributed generation scenario; on the other, many consumers are becoming prosumers (individual who both consume and produces energy) with the opportunity to share energy with each other locally. Thus, new forms of aggregation, known as "Energy Communities" (ECs), are emerging at the local level with the potential to increase renewable penetration, enhance energy share, reduce carbon footprint, and make renewable energy more affordable and acceptable for society.

Energy communities are gaining a lot of research interest because of the variety of aspects (not only energy-related) associated with their formation and operation. Among them, it is worth mentioning:

  • The selection of the optimal number, type, and size of the energy conversion and storage units within the EC;
  • Optimal aggregation of users in ECs;
  • Management of the demand side;
  • Development of smart energy grids;
  • Fair criteria for allocation of resources among EC members;
  • Proper incentive values to promote aggregation in EC;
  • Assessment of social impact of ECs and large-scale deployment of renewable technologies;
  • Reduction in energy poverty;
  • Users engagement.

All these aspects are often studied with the aid of advanced modelling techniques involving dynamic–stochastic optimization approaches where both integer and continuous variables are used. These techniques allow for a consideration of the dependence on time (“dynamic”) of the community operation, the uncertainty of renewables, prices and energy demands (“stochasticity”), and the inclusion/exclusion of energy users and assets (“mixed integer” programming).

This Special Issue aims to present and disseminate the most recent advances related to the theory, design, modelling, and application of Energy Communities. It welcomes both papers dealing with specific case studies and papers outlining a broader perspective on the role of Energy Communities in shaping the energy system of the future.

Topics of interest for publication include, but are not limited to:

  • Design and operation optimization of the energy conversion and storage units of the community;
  • Criteria to identify the optimal aggregation of users;
  • Modelling, simulation, and application of demand–response programs;
  • User engagement in demand–response to increase flexibility;
  • Use of storage at the local level;
  • Development of energy grids to accommodate the growth of ECs;
  • The role of uncertainty in the design and operation of ECs;
  • Diagnosis and management of the development and implementation of ECs;
  • Configurations and regulatory framework of ECs (e.g., Renewable Energy Community, Citizen Energy Community);
  • Fostering policies that promote the development of ECs;
  • Investment options and cost allocation in ECs;
  • Risk assessment of EC formation;
  • The impact of the emergence of ECs on society;
  • Cooperation and human involvement within ECs;
  • Nearly zero emissions ECs.

Dr. Sergio Rech
Prof. Dr. Andrea Lazzaretto
Dr. Gianluca Carraro
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

  • energy communities
  • multi-energy systems
  • smart energy systems
  • aggregation of energy users
  • renewable energy technologies
  • energy storage
  • decarbonization
  • sustainable energy system

Published Papers (4 papers)

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Research

21 pages, 3656 KiB  
Article
A Dynamic Analysis of Biomethane Reforming for a Solid Oxide Fuel Cell Operating in a Power-to-Heat System Integrated into a Renewable Energy Community
by Francesco Calise, Francesco Liberato Cappiello, Luca Cimmino and Maria Vicidomini
Energies 2024, 17(13), 3160; https://doi.org/10.3390/en17133160 - 27 Jun 2024
Viewed by 264
Abstract
This paper aims to develop a dynamic simulation model for the reduction of energy consumption through the use of organic waste from a residential district, supplied by a hybrid renewable energy plant. The proposed layout is based on a novel paradigm of a [...] Read more.
This paper aims to develop a dynamic simulation model for the reduction of energy consumption through the use of organic waste from a residential district, supplied by a hybrid renewable energy plant. The proposed layout is based on a novel paradigm of a renewable energy community focused on the biocircular economy and a sustainable approach. The novelty with respect to the majority of papers developed in the literature on renewable energy communities lies in the use of both solar photovoltaic production and the organic fraction of municipal solid waste collected by the community. Energy production by biomass conversion and by photovoltaic fields shared among the buildings is used to satisfy in a sustainable manner the community loads for heating, cooling, and power. The district heating network is based on water loop heat pumps and air-to-air heat pumps and it includes the power-to-heat energy storage strategy. The biogas produced by the anaerobic digestion process is cleaned in order to supply a solid oxide fuel cell for the production of additional power, mainly during the hours of poor or null solar energy production. Then, the layout integrates several innovative topics, such as the power-to-heat strategy, the biocircular economy, the low-temperature district heating, the use of a solid oxide fuel cell, and a renewable energy community. The dynamic model of the proposed hybrid renewable layout is developed in the TRNSYS environment, but some innovative energy components, such as anaerobic digestion, the biogas upgrading unit, and the solid oxide fuel cell, are dynamically modeled in MATLAB and then integrated into the whole plant model. The proposed plant has been confirmed to be extremely profitable and able to obtain important energy savings, considering the achieved payback period of 4.48 years and the primary energy saving of 23%. This layout resulted in an interesting solution for pushing the development of smart and sustainable cities. Full article
(This article belongs to the Special Issue Energy Communities for the Transition to a Sustainable and Decarbonized Society)
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36 pages, 8750 KiB  
Article
Multi-Objective Optimization of an Energy Community Powered by a Distributed Polygeneration System
by Ronelly José De Souza, Mauro Reini, Luis M. Serra, Miguel A. Lozano, Emanuele Nadalon and Melchiorre Casisi
Energies 2024, 17(13), 3085; https://doi.org/10.3390/en17133085 - 22 Jun 2024
Viewed by 310
Abstract
This paper presents a multi-objective optimization model for the integration of polygeneration systems into energy communities (ECs), by analyzing a case study. The concept of ECs is increasingly seen as beneficial for reducing global energy consumption and greenhouse gas emissions. Polygeneration systems have [...] Read more.
This paper presents a multi-objective optimization model for the integration of polygeneration systems into energy communities (ECs), by analyzing a case study. The concept of ECs is increasingly seen as beneficial for reducing global energy consumption and greenhouse gas emissions. Polygeneration systems have the potential to play a crucial role in this context, since they are known for producing multiple energy services from a single energy resource, besides the possibility of being fed also by renewable energy sources. However, optimizing the configuration and operation of these systems within ECs presents complex challenges due to the variety of technologies involved, their interactions, and the dynamic behavior of buildings. Therefore, the aim of this work is developing a mathematical model using a mixed integer linear programming (MILP) algorithm to optimally design and operate polygeneration systems integrated into ECs. The model is applied to a case study of an EC comprising nine buildings in a small city in the northeast of Italy. The work rests on the single- and multi-objective optimization of the polygeneration systems taking into account the sharing of electricity among the buildings (both self-produced and/or the purchased from the grid), as well as the sharing of heating and cooling between the buildings through a district heating and cooling network (DHCN). The main results from the EC case study show the possibility of reducing the total annual CO2 emissions by around 24.3% (about 1.72 kt CO2/year) while increasing the total annual costs by 1.9% (about 0.09 M€/year) or reducing the total annual costs by 31.9% (about 1.47 M€/year) while increasing the total annual CO2 emissions by 2.2% (about 0.16 kt CO2/year). The work developed within this research can be adapted to different case studies, such as in the residential–commercial buildings and industrial sectors. Therefore, the model resulting from this work constitutes an effective tool to optimally design and operate polygeneration systems integrated into ECs. Full article
(This article belongs to the Special Issue Energy Communities for the Transition to a Sustainable and Decarbonized Society)
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Graphical abstract

22 pages, 4804 KiB  
Article
Generating Synthetic Electricity Load Time Series at District Scale Using Probabilistic Forecasts
by Lucas Richter, Tom Bender, Steve Lenk and Peter Bretschneider
Energies 2024, 17(7), 1634; https://doi.org/10.3390/en17071634 - 28 Mar 2024
Viewed by 711
Abstract
Thanks to various European directives, individuals are empowered to share and trade electricity within Renewable Energy Communities, enhancing the operational efficiency of local energy systems. The digital transformation of the energy market enables the integration of decentralized energy resources using cloud computing, the [...] Read more.
Thanks to various European directives, individuals are empowered to share and trade electricity within Renewable Energy Communities, enhancing the operational efficiency of local energy systems. The digital transformation of the energy market enables the integration of decentralized energy resources using cloud computing, the Internet of Things, and artificial intelligence. In order to assess the feasibility of new business models based on data-driven solutions, various electricity consumption time series are necessary at this level of aggregation. Since these are currently not yet available in sufficient quality and quantity, and due to data privacy reasons, synthetic time series are essential in the strategic planning of smart grid energy systems. By enabling the simulation of diverse scenarios, they facilitate the integration of new technologies and the development of effective demand response strategies. Moreover, they provide valuable data for assessing novel load forecasting methodologies that are essential to manage energy efficiently and to ensure grid stability. Therefore, this research proposes a methodology to synthesize electricity consumption time series by applying the Box–Jenkins method, an intelligent sampling technique for data augmentation and a probabilistic forecast model. This novel approach emulates the stochastic nature of electricity consumption time series and synthesizes realistic ones of Renewable Energy Communities concerning seasonal as well as short-term variations and stochasticity. Comparing autocorrelations, distributions of values, and principle components of daily sequences between real and synthetic time series, the results exhibit nearly identical characteristics to the original data and, thus, are usable in designing and studying efficient smart grid systems. Full article
(This article belongs to the Special Issue Energy Communities for the Transition to a Sustainable and Decarbonized Society)
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27 pages, 1038 KiB  
Article
Diagnosis of the Development of Energy Cooperatives in Poland—A Case Study of a Renewable Energy Cooperative in the Upper Silesian Region
by Bożena Gajdzik, Magdalena Jaciow, Radosław Wolniak, Robert Wolny and Wieslaw Wes Grebski
Energies 2024, 17(3), 647; https://doi.org/10.3390/en17030647 - 30 Jan 2024
Cited by 5 | Viewed by 1120
Abstract
Renewable energy sources (RESs) offer key transformative potential from a societal point of view due to their modularity and ability to generate energy at the local level, allowing for the development of grassroots democratic and participatory initiatives. The paper aims to share insights [...] Read more.
Renewable energy sources (RESs) offer key transformative potential from a societal point of view due to their modularity and ability to generate energy at the local level, allowing for the development of grassroots democratic and participatory initiatives. The paper aims to share insights into the processes of creating RES cooperatives in Poland. One of the first cooperatives to be established in the Upper Silesian region in Poland was the energy cooperative (EC) “Our Energy”. This study presents an in-depth empirical analysis of a community-based renewable energy cooperative. The study employed a case study methodology, including a SWOT analysis framework, to describe the research subject and identify its strengths, weaknesses, opportunities, and threats. Key findings indicate that members benefit from stable energy prices and full recovery of the energy produced, and the cooperative is at the forefront of energy-sharing practices that minimize costs through direct transactions with the local municipality. The strategic goals of the EC focus on expanding membership, increasing the number of photovoltaic installations, implementing energy balancing, combating energy poverty, and reducing emissions. Challenges such as financial constraints and a lack of real-time monitoring of energy distribution are acknowledged, and carbon footprint reduction innovations and stakeholder engagement are highlighted as forward-looking approaches. The study highlights the role of cooperatives as a model for community-led sustainable energy initiatives. However, the study acknowledges the limitations of its small sample size, suggesting the need for broader research to understand the impact of collaborative energy on decarbonization. Future research directions are proposed, focusing on the long-term sustainability and socioeconomic impacts of energy cooperatives. This study contributes to the scholarly discourse on renewable energy cooperatives by offering insight into their potential to bridge the gap between energy producers and consumers and support sustainable community development. The main novelty of this paper lies in its detailed examination of a specific renewable energy cooperative, incorporating SWOT analysis, stakeholder perspectives, quantitative assessments, and a forward-thinking approach. This multifaceted analysis contributes to the existing literature on renewable energy initiatives, providing a valuable reference for researchers, policymakers, and practitioners in the field. Full article
(This article belongs to the Special Issue Energy Communities for the Transition to a Sustainable and Decarbonized Society)
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