Decentralized Energy Systems Research Articles

Peer-to-peer energy trading: Innovations, regulatory challenges, and the future of decentralized energy systems

Peer-to-peer (P2P) energy trading represents a transformative approach to energy distribution, where consumers, referred to as prosumers, generate and exchange electricity directly with one another. This decentralized model promotes local generation and consumption balancing, reducing reliance on centralized grids and encouraging the use of renewable energy. The development of platforms and technologies, such as blockchain, smart contracts, and Internet of Things (IoT)-)-enabled devices, has enabled secure, transparent, and automated transactions. These innovations facilitate real-time monitoring and energy matching, while artificial intelligence (AI) optimizes pricing and supply-demand dynamics. Microgrids and energy storage solutions further enhance the efficiency and reliability of local energy balancing in P2P systems. However, the widespread adoption of P2P energy trading faces significant regulatory and market challenges. Current regulatory frameworks, designed for traditional, centralized energy markets, often lack provisions for decentralized trading models. Key issues include grid access, tariffs, consumer protection, and data privacy. Furthermore, regulatory barriers differ widely by region, affecting the pace of P2P adoption. Market mechanisms that support P2P energy trading, such as dynamic pricing, demand-response programs, and real-time settlement systems, are also critical for its success. The role of aggregators and intermediaries in facilitating transactions is evolving, as regulatory bodies explore sandbox environments to test these innovative models. This review explores the technological advancements and regulatory landscape shaping P2P energy trading, highlighting successful case studies and identifying future trends. It underscores the need for adaptable policies and robust platforms to unlock the potential of P2P energy trading in building resilient, sustainable, and decentralized energy systems.

THE POTENTIAL FOR PEER-TO-PEER ELECTRICITY TRADING IN GEORGIA

The global energy transition is fundamentally reshaping electricity markets, moving from centralized systems reliant on fossil fuels to decentralized, renewable energy solutions. Distributed energy resources such as solar panels and storage batteries are empowering consumers to become active participants in the energy market. Peer-to-peer (P2P) electricity trading, enabled by blockchain technology, presents a new model for consumers to trade surplus energy directly with one another, bypassing traditional suppliers. This article explores the potential of P2P electricity trading in Georgia, a country with significant renewable energy resources but limited experience with decentralized energy systems. As Georgia aligns its energy policies with European regulations, the development of a P2P trading market could enhance energy security, empower prosumers, and drive local economic development. Through an analysis of global trends, technological innovations, and the current Georgian energy landscape, this article assesses the opportunities and challenges in implementing P2P trading. By building the necessary infrastructure and fostering public participation, Georgia has the potential to transform its energy market and contribute to a more resilient and sustainable energy future.

Converting lignocellulosic biomass into valuable end products for decentralized energy solutions: A comprehensive overview

This review manuscript delves into lignocellulosic biomass (LCB) as a sustainable energy source, addressing the global demand for renewable alternatives amidst increasing oil and gas consumption and solid waste production. LCB, consisting of lignin, cellulose, and hemicellulose, is versatile for biochemical and thermochemical conversions like anaerobic digestion, fermentation, gasification, and pyrolysis. Recent advancements have led to a 25 % increase in bioethanol yields through alkali pre-treatment and optimized fermentation, a 20 % enhancement in microbial delignification efficiency, and a 35 % improvement in enzyme efficiency via nanobiotechnology. These innovations enhance biofuel production sustainability and cost-effectiveness. Decentralized energy systems utilizing locally produced biomass can reduce transmission losses and greenhouse gas emissions by up to 30 %, fostering community energy independence. These developments significantly contribute to global sustainability and socio-economic development by converting waste into valuable energy, promoting environmental stewardship, and supporting economic resilience. Furthermore, this review also discusses innovative strategies to address technological, economic, and environmental challenges and highlights the role of decentralized solutions in promoting sustainable energy production.

Harnessing biomass waste-to-energy for sustainable electricity generation: prospects, viability, and policy implications for low-carbon urban development

AbstractBiomass waste-to-energy (WtE) generation is a potential pathway for green urban transition in developing countries which can contribute significantly to sustainable development goal 7: affordable and clean energy. However, unlike fossil fuel energy systems, the economic returns from WtE systems are low because WtE generation is capital-intensive and requires subsidies. This study examines the prospects of a sustainable biomass electricity generation from rice husk (RH) using a large dataset of rice milling activities in a fast paced urban transition economy. The study analyzes the viability of several RH biomass electricity generation scenarios using indicators such as net electricity output, economic returns (benefits), and levelized cost of electricity (LCOE). The results show that several mills/mill clusters generate sufficient daily RH that can power between 0.8 and 2.2 MW plant with a combined electricity output of about 500,000 MWh per annum. The economic analyses show that all RH biomass electricity generation scenarios return positive economic benefits under reduced social discount rates of 2–6%. Moreover, the LCOE of all scenarios are less than those of electricity generated from other sources. These results demonstrate that biomass waste-to-energy generation is viable for green urban development through low-carbon decentralized energy systems. Several policy implications of the findings are highlighted, including the need for policymakers and energy stakeholders to adopt sustainable biomass energy generation models such as “design, build, and operate” (DBO) to achieve sustainable WtE generation regimes that ensure green urban transition. Such a model will contribute to a circular economy and facilitates sustainable urban development that satisfies climate-related SDGs. Graphic abstract

Assessing Yield Disparities: Anticipated versus Optimal Rooftop Photovoltaic Systems and Implications for Prosumer Viability

Solar photovoltaics, especially rooftop systems also called distributed solar photovoltaics, are crucial in the ongoing energy transition. Modeling these systems is vital to understanding their role in a decentralized energy system. While ground‐mounted photovoltaic power plants are easier to model, generalizing yield profiles for rooftop systems is challenging. This study aims to estimate yield loss effects for rooftop solar photovoltaic systems compared to optimized ground‐mounted systems. Anticipated yield losses are 18% for residential, 7% for commercial, and 4% for industrial rooftop systems. The impact on residential prosumers’ viability is assessed by comparing prosumer system optimization results with and without yield losses. Results show a non‐uniform change in installed solar photovoltaic and battery capacities, with a tendency to compensate for reduced yields by increasing photovoltaic capacity by up to 20%, given favorable cost prospects by 2050. The annualized total cost of energy for prosumer households could therefore increase by up to 20% by 2050. Despite yield reductions, installing a solar photovoltaic prosumer system remains more favorable than relying entirely on‐grid electricity. This study highlights the importance of considering yield losses in rooftop solar photovoltaics and the significant role of prosumers despite identified yield losses.

Dispatch of Decentralized Energy Systems using Artificial Neural Networks: A Comparative Analysis with Emphasis on Training Methods

Due to the availability of flexibility, Decentralized Energy Systems (DES) play a central role in integrating renewable energies. To efficiently utilize renewable energy, dispatchable components must be operated to bridge the time gap between inflexible supply and energy demand. Due to the large number of energy converters, energy storage systems, and flexible consumers, there are many ways to achieve this. Conventional rule-based dispatch strategies often reach their limits here, and optimized dispatch strategies (e.g., model predictive control or the optimal dispatch) are usually based on very good forecasts. Reinforcement learning, particularly the application of Artificial Neural Networks (ANN), offers the possibility to learn complex decision-making processes. Since long training times are required for this, an efficient training framework is needed. The present paper proposes different training methods to learn an ANN-based dispatch strategy. In Method I, the ANN attempts to learn the solution to the corresponding optimal dispatch problem. In method II, the energy system model is simulated during the training to compute the observation state and operating costs resulting from the ANN-based dispatch. Method III uses the fast executable Method I solution as a warm-up solution for the computationally expensive training with Method II. In the present paper, a model-based analysis compares the different ANN-based dispatch strategies with rule-based dispatch strategies, model predictive dispatch (MPC), and optimal dispatch regarding their computational efficiency and the resulting operating costs. The dispatch strategies are compared based on three case studies with different system topologies for which training and test data are applied.Training method I proved to be non-competitive. However, training methods II and III significantly outperformed rule-based dispatch strategies across all case studies for both training and test data sets. Notably, methods II and III also surpassed MPC-based dispatch strategies under high and medium uncertainty forecasts for the training data in the first two case studies. In contrast, MPC-based dispatch was superior in the third case study, likely due to the higher system’s complexity and in the test data set due to the methodological advantage of being optimized for each specific data set. The effectiveness of training method III depends on the performance of the warm-up training with method I: warm-up is beneficial only if this results in an already promising dispatch (as seen in case study two). Otherwise, training method II proves more effective, as observed in case studies one and three.

Towards decarbonizing large-scale industries: A decision support framework for optimizing grid-connected PV-battery energy systems planning – Case study of an OCP mining site, Morocco, North Africa

Incorporating renewable energy into forthcoming grid-connected or decentralized energy systems assumes an escalating significance and can potentially enhance endeavors toward accomplishing Sustainable Development Goal 7 (SDG7). Nevertheless, deploying sustainable renewable energy-intensive systems may present challenges related to their intermittency and cost instability. This paper proposes the development of a decision support model aimed at planning an optimal on-grid PV battery system. The model builds upon the Open Energy Modeling Framework (OEMOF) and defines asset capacities, energy dispatch, operational strategies, and optimal costs for the designated system. Key factors considered include energy demand profile, photovoltaic potential, electricity tariffs, and the availability of the National Grid. Furthermore, the model evaluation incorporates the computation of pertinent performance, feasibility, and viability indicators, notably the Levelized Cost of Energy (LCOE). To validate the framework, the article conducts a case study to determine the optimal sizing and planning of a grid-connected PV battery energy system. The objective is to cater to the electricity needs of an OCP (Office Chérifien des Phosphates) mining site in Morocco. The study considers the characteristics of the national power grid, incorporating time-varying electricity tariffs based on a Demand-Response program taking into account various rates according to the time of use (ToU). The case study includes a sensitivity analysis that examines different factors, namely the proportion of renewable energy, the investment costs of photovoltaic systems and batteries, and the financial parameter known as the weighted average cost of capital (WACC). Through this analysis, the study assesses the impact of these variables on the calculated cost of energy. Experimental results revealed a range of LCOE values from $0.07111/kWh to $0.11847/kWh for high renewable energies integration.

Power to the People: Advancing Resilient and Sustainable Decentralized Energy Distribution Systems

This research explores decentralized energy distribution systems (DEDs) as a transformative approach to modernizing power grids. DEDs, including solar photovoltaics, wind turbines, microgrids, and battery storage, offer localized, resilient, and sustainable alternatives to traditional centralized power systems. This study examines the technological components, economic and environmental impacts, policy frameworks, and the challenges associated with DED implementation. Through a comprehensive analysis of case studies and current advancements, we highlight the potential of DEDs to enhance energy security, reduce carbon emissions, and promote economic development. By addressing technical and social challenges, this paper underscores the critical role of innovative solutions, such as artificial intelligence and blockchain, in optimizing decentralized energy systems. The findings contribute to a deeper understanding of how decentralized energy can support global sustainability goals and pave the way for a resilient and efficient energy future.

A Comprehensive Review Based on the Game Theory with Energy Management and Trading

This paper reviews the use of game theory tools to study the operation and design of modern power grids. The contribution of this work is to summarize the literature to highlight the versatile solution capability of game theory by focusing on the interconnected objectives of energy trading and energy management. This review was conducted with a focus on various applications in energy systems, including general energy markets, micro grids (MGs), virtual power plants (VPP), electric vehicles (EVs), and smart homes, and explores how game theory can summarize the solutions for pricing, bidding, demand side management, and resource optimization. A key finding is the suitability of game theory for modeling decentralized energy systems where strategic incentives can lead to outcomes that benefit both individuals and society. It also discusses the limitations, challenges, and potential benefits of game theory in complex power systems. This study provides researchers and policy makers with a comprehensive overview of current research and insights into the potential of game theory to shape the future of energy systems.

Assessment of the Technical Impacts of Electric Vehicle Penetration in Distribution Networks: A Focus on System Management Strategies Integrating Sustainable Local Energy Communities

Aligned with the objectives of the energy transition, the increased penetration levels of electric vehicles as part of the electrification of economy, especially within the framework of local energy communities and distributed energy resources, are crucial in shaping sustainable and decentralized energy systems. This work aims to assess the impact of escalating electric vehicles’ deployment on sustainable local energy community-based low-voltage distribution networks. Through comparative analyses across various levels of electric vehicle integration, employing different charging strategies and system management approaches, the research highlights the critical role of active system management instruments such as smart grid monitoring and active network management tools, which significantly enhance the proactive management capabilities of distribution system operators. The findings demonstrate that increased electric vehicle penetration rates intensify load violations, which strategic electric vehicle charging management can significantly mitigate, underscoring the necessity of load management strategies in alleviating grid stress in the context assessed. This study highlights the enhanced outcomes derived from active system management strategies which foster collaboration among distribution system operators, demand aggregators, and local energy communities’ managers within a local flexibility market framework. The results of the analysis illustrate that this proactive and cooperative approach boosts system flexibility and effectively averts severe grid events, which otherwise would likely occur. The findings reveal the need for an evolution towards more predictive and proactive system management in electricity distribution, emphasizing the significant benefits of fostering robust partnerships among actors to ensure grid stability amid rising electric vehicle integration.

Comprehensive analysis of integrating smart grids with renewable energy sources: Technological advancements, economic impacts, and policy frameworks

This study presents a comprehensive analysis of integrating smart grids with renewable energy sources, focusing on technological advancements, economic impacts, and policy frameworks. The primary objective is to explore how smart grid technologies can efficiently incorporate renewable energy sources, thereby enhancing grid reliability, efficiency, and sustainability. Utilizing a multidisciplinary approach, the study examines successful case studies, pilot projects, and innovative practices that highlight the potential and challenges of this integration. Key findings reveal that advanced technologies such as artificial intelligence (AI), the Internet of Things (IoT), and blockchain are crucial for the real-time monitoring, predictive maintenance, and optimized management of energy systems. These technologies address the inherent variability and intermittency of renewable energy sources like solar and wind power. Case studies, including the Brooklyn Microgrid and Germany’s Energiewende, demonstrate significant improvements in energy resilience, efficiency, and consumer empowerment through decentralized energy systems. Economic analysis underscores the dual impact of cost savings from operational efficiencies and the financial challenges posed by substantial upfront investments in smart grid infrastructure. Policy frameworks play a pivotal role, with recommendations for supportive regulatory policies, increased funding for research and development, and enhanced public-private partnerships to drive innovation and consumer engagement. The study concludes that overcoming the technical, economic, and regulatory barriers requires coordinated efforts among stakeholders. Recommendations include developing consistent regulatory frameworks, fostering public-private partnerships, and implementing educational programs to encourage consumer participation in renewable energy initiatives. By addressing these challenges, the integration of smart grids with renewable energy sources can pave the way for a more sustainable, resilient, and efficient energy future. Keywords: Smart Grids, Renewable Energy Integration, Technological Advancements, Economic Impacts, Policy Frameworks, Grid Management Innovations.

Integrating Renewable Energy Produced by a Library Building on a University Campus in a Scenario of Collective Self-Consumption

Rising fossil fuel costs and environmental concerns are driving the search for new energy sources, particularly renewable energy. Among these sources, solar photovoltaic (PV) is the most promising in southern European countries, mainly through the use of decentralised PV systems designed to produce electricity close to the point of demand and primarily to meet local energy needs. In an urban scenario, a decentralised energy system usually operates in parallel with the grid, allowing excess power generated to be injected into the grid. Solar carports and rooftop systems are excellent examples of distributed photovoltaic systems, which are far more sustainable than large centralised systems because they do not compete for land use. Despite their operational advantages, these decentralised photovoltaic production plants, which are in most cases financed by specific energy efficiency programs, present challenges in a regulated market where the injection of energy into the electricity grid is restricted by law and support programs. The aim of this work is to integrate two different photovoltaic systems within an academic campus where the only PV source currently available is a solar car park, a solution designed both to provide shaded space for vehicles and to produce energy to be consumed within the facilities. Due to legal restrictions, surplus electricity cannot be sold to the national grid, and solar batteries to store the generated energy are expensive and have a short lifespan. Therefore, since the campus has two different grid connections and a 102.37 kWp PV system, the newly designed system to be installed on the library roof must be calculated to support the installed electricity system during the most critical working hours, determining the specific angle and orientation of the solar panels. On this basis, the energy management of a school campus is fundamental to creating a collective self-consumption system, the basis of a local energy community that can meet energy, environmental, and social objectives.

Techno-economic optimization and working fluid selection of a biogas-based dual-loop bi-evaporator ejector cooling cycle involving power-to-hydrogen and water facilities

Biogas-fueled decentralized energy systems featuring gas turbines emerge as pivotal players in the quest for more adaptable and eco-friendly energy solutions. This study presents the design of a cutting-edge multigeneration system that harnesses the potential of a gas turbine coupled with ejector-driven dual-loop bi-evaporator technology, reverse osmosis desalination, proton exchange membrane electrolysis, and an organic Rankine cycle. The research encompasses an extensive sensitivity analysis and deploys a genetic algorithm-based optimization technique. Through meticulous Optimization, the system achieves remarkable outcomes, including electricity generation, cooling capacity, heating capacity, desalinated water production, and hydrogen yield, measured at 957.3 kW, 231.4 kW, 272.3 kW, 7.336 kg/s, and 0.99 kg/h, respectively. Notably, this performance surpasses the base case by 2% and 8.9%, yielding exergy efficiency and total unit cost improvements of 33.3% and 16.4 $/GJ. Among the critical decisions made was selecting an organic working fluid for the organic Rankine cycle. Through rigorous evaluation, isobutene emerged as the optimal choice, demonstrating significantly improved output power compared to alternatives. Isobutane as the working fluid led to a substantial increase in overall exergy efficiency and a resultant total unit cost of 18.06 $/GJ, accompanied by an impressive 23.48% exergy efficiency.

Powering the Future: An Integrated Framework for Clean Renewable Energy Transition

The transition to renewable energy has been recognized as a crucial step in addressing climate change and achieving greenhouse gas reduction targets, but it can also cause energy sprawl if not planned properly. Clean renewable energy communities (CREC) are emerging globally as an approach for decentralized energy systems and an alternative to traditional centralized energy systems. CREC aim to lower the energy carbon footprint, enhance local energy resilience, and improve the quality of life of residents. Through a comprehensive literature review, this study reviews metrics that can assess the impact of energy transition plans and support decision-making to select technologies that create efficient, reliable, and accessible energy systems. It classifies these metrics into a five-dimensional sustainability approach including environmental, technical, social, economic, and political and institutional dimensions. The paper proposes a conceptual framework to guide decision-makers in recognizing the role of sustainable land development, sustainable energy planning, and resiliency as an integrated approach to energy transition planning. This framework stresses mapping the place-based potential for clean renewable energy at various scales, highlights the importance of resilience in energy planning, and addresses challenges associated with energy source selection, built environment efficiency, and the energy trade. While the framework can serve as a starting point for evaluating energy transition plans, further work is needed to address the limitations of existing metrics and identify additional evaluations for mixed-energy land use that are critical to managing energy sprawl in terms of ecosystem services and other land uses.

Technological Elements behind the Renewable Energy Community: Current Status, Existing Gap, Necessity, and Future Perspective—Overview

The Renewable Energy Community (REC) in Europe promotes renewable energy sources (RESs), offering social, economic, and environmental benefits. This new entity could alter consumer energy relationships, requiring self-consumption, energy sharing, and full utilization of RESs. Modernizing energy systems within the REC requires addressing self-consumption, energy sharing, demand response, and energy management system initiatives. The paper discusses the role of decentralized energy systems, the scenarios of the REC concept and key aspects, and activities involving energy generation, energy consumption, energy storage systems, energy sharing, and EV technologies. Moreover, the present work highlights the research gap in the existing literature and the necessity of addressing the technological elements. It also highlights that there is no uniform architecture or model for the REC, like in the case of microgrids. Additionally, the present work emphasizes the role and importance of technological elements in RECs, suggesting future recommendations for EMS, DSM, data monitoring and analytics, communication systems, and the software or tools to ensure reliability, efficiency, economic, and environmental measures. The authors also highlight the crucial role of policymakers and relevant policies, which could help in implementing these technological elements and show the importance of the RECs for a sustainable energy shift and transition.

What drives energy storage deployment in local energy transitions? Stakeholders’ perspective

The global shift towards decentralised energy systems has assigned municipalities a key role in achieving national climate neutrality objectives. As the main stakeholders in the local energy transition, municipalities are responsible for the decarbonization of the local energy system through the extensive integration of renewable energy sources into existing systems. However, this integration requires new approaches and system adjustments, such as energy storage deployment, to satisfy the variable nature of renewable energy sources. The integration of novel solutions, such as energy storage, is difficult because of the diverse range of stakeholders involved, each with their own perceptions and expertise. This study uses the Fuzzy Cognitive Mapping (FCM) methodology to analyse the mental models of different stakeholders regarding their perceived importance of different factors influencing the implementation of energy storage in municipalities. The approach of this study enables a better understanding of municipal energy systems and its dynamics. The results reveal that support schemes such as subsidies and awareness campaigns are key to all stakeholders. Municipalities tend to focus on local needs and technological solutions, while energy experts prioritize technical aspects and national policies. Municipalities address challenges linearly, missing interconnections, whereas energy experts consider feedback loops and system requirements. The study highlights the need for common ground to drive effective policy and infrastructure development. The results could be used to facilitate discussions with policy makers on why energy storage is important and what policy measures should be considered to accelerate its deployment.

Prosumer Aggregators in Romania

Abstract The European Union has pledged to transform Europe into the first climate neutral continent by 2050, and the first step towards achieving this goal is to reduce greenhouse gas emissions by 55% by 2050, compared to levels recorded in 1990. The two main paths the EU has chosen to follow to ensure its climate neutrality goals are electrification and the increase of the integration of renewable energy technologies. If the 2010 period was characterized by the development and adoption of large-scale production of energy by using renewable sources, the 2020s seem to encompass a decentralization process, meant to bring energy production closer to the final consumer. In Romania, the past three years saw a rapid growth in the overall production of energy through distributed energy sources. Although this development is encouraging for achieving the broader environmental targets of the EU, at a local level there are several disadvantages that are starting to appear, such as issues in the distribution grid and confusion of both consumers and prosumers regarding the economic advantages of producing energy locally. The main goal of the research that has been conducted for a doctoral thesis was to develop a set of recommendations for aggregators regarding prosumers, based on mathematical model and calculations centered around a specific time frame. Research was spread into identifying and analyzing existing renewable technologies, detailing concepts such as decentralization, electrification, demand response and power aggregators, and the study of the main power aggregator business models. For these aspects to be covered, secondary research was used in the form of both academic and industry state-of-the-art papers. The main contributions of the research are the synthesizing of available information on aspects related to decentralized energy systems, and a set of recommendations aimed at aggregators, as a business, and existing and potential future prosumer.

Global high-resolution growth projections dataset for rooftop area consistent with the shared socioeconomic pathways, 2020–2050

Assessment of current and future growth in the global rooftop area is important for understanding and planning for a robust and sustainable decentralised energy system. These estimates are also important for urban planning studies and designing sustainable cities thereby forwarding the ethos of the Sustainable Development Goals 7 (clean energy), 11 (sustainable cities), 13 (climate action) and 15 (life on land). Here, we develop a machine learning framework that trains on big data containing ~700 million open-source building footprints, global land cover, road, and population datasets to generate globally harmonised estimates of growth in rooftop area for five different future growth narratives covered by Shared Socioeconomic Pathways. The dataset provides estimates for ~3.5 million fishnet tiles of 1/8 degree spatial resolution with data on gross rooftop area for five growth narratives covering years 2020–2050 in decadal time steps. This single harmonised global dataset can be used for climate change, energy transition, biodiversity, urban planning, and disaster risk management studies covering continental to conurbation geospatial levels.

Optimizing renewable energy systems through artificial intelligence: Review and future prospects

The global transition toward sustainable energy sources has prompted a surge in the integration of renewable energy systems (RES) into existing power grids. To improve the efficiency, reliability, and economic viability of these systems, the synergistic application of artificial intelligence (AI) methods has emerged as a promising avenue. This study presents a comprehensive review of the current state of research at the intersection of renewable energy and AI, highlighting key methodologies, challenges, and achievements. It covers a spectrum of AI utilizations in optimizing different facets of RES, including resource assessment, energy forecasting, system monitoring, control strategies, and grid integration. Machine learning algorithms, neural networks, and optimization techniques are explored for their role in complex data sets, enhancing predictive capabilities, and dynamically adapting RES. Furthermore, the study discusses the challenges faced in the implementation of AI in RES, such as data variability, model interpretability, and real-time adaptability. The potential benefits of overcoming these challenges include increased energy yield, reduced operational costs, and improved grid stability. The review concludes with an exploration of prospects and emerging trends in the field. Anticipated advancements in AI, such as explainable AI, reinforcement learning, and edge computing, are discussed in the context of their potential impact on optimizing RES. Additionally, the paper envisions the integration of AI-driven solutions into smart grids, decentralized energy systems, and the development of autonomous energy management systems. This investigation provides important insights into the current landscape of AI applications in RES.

Owning the just transition: comparing citizen participation in South African and German wind farms

ABSTRACT The global effort to reduce carbon emissions, driven by industrialised countries in the north is increasingly perceived as an unfair imposition by countries in the south. Wind turbine technology importantly contributes to the energy transition and its introduction has produced new players in energy systems, for instance through financial citizen participation in wind farms. The shape and degree of citizen participation is geographically variegated even within countries. Taking a multi-scalar perspective inspired by institutional theory, we explore the micro, meso and macro institutional and regulatory frameworks perceived as supportive or restrictive in the development of citizen participation in Germany and South Africa. Our findings highlight the importance of citizens’ ability and will to create legal structures for inclusive collective action and their ability to access affordable investment capital through local banks and other financing arrangements. Under the right institutional conditions decentralised energy systems, such as small-scale wind farms, provide an opportunity for fostering emotive and economic ownership by citizens in the global north and south alike.