Search Results (701)

Power systems are undergoing a transformative transition as consumers seek greater participation in managing electricity systems. This shift has given rise to the concept of “prosumers,” individuals who both consume and produce electricity, primarily through renewable energy sources. While renewables offer undeniable environmental benefits, they also introduce significant energy management challenges. One major concern is the variability in energy consumption patterns within households, which can lead to inefficiencies. Also, improper energy management can result in economic losses due to unbalanced energy control or inefficient systems. Home Energy Management Systems (HEMSs) have emerged as a promising solution to address these challenges. A well-designed HEMS enables users to achieve greater efficiency in managing their energy consumption, optimizing asset usage while ensuring cost savings and system reliability. This paper presents a comprehensive systematic review of optimization techniques applied to HEMS development between 2019 and 2024, focusing on key technical and computational factors influencing their advancement. The review categorizes optimization techniques into two main groups: conventional methods, emerging techniques, and machine learning methods. By analyzing recent developments, this study provides an integrated perspective on the evolving role of HEMSs in modern power systems, highlighting trends that enhance the efficiency and effectiveness of energy management in smart grids. Unifying taxonomy of HEMSs (2019–2024) and integrating mathematical, heuristic/metaheuristic, and ML/DRL approaches across horizons, controllability, and uncertainty, we assess algorithmic complexity versus tractability, benchmark comparative evidence (cost, PAR, runtime), and highlight deployment gaps (privacy, cybersecurity, AMI/HAN, and explainability), offering a novel synthesis for AI-enabled HEMS. Full article

Given the construction industry’s significant contribution of approximately 39% of global CO₂ emissions, implementing effective carbon reduction strategies is becoming increasingly critical. In this context, Internet of Things (IoT) technologies present promising solutions for monitoring and reducing emissions. However, there is a lack of comprehensive understanding regarding specific IoT applications, implementation barriers, and opportunities for carbon reduction in construction practices. This study investigates the role of IoT in reducing carbon emissions in the construction industry. Following PRISMA guidelines, this study analyzed bibliometric data from Scopus and Web of Science databases using VOSviewer for science mapping visualization. Content analysis was conducted on 17 carefully selected articles to identify key research topics and applications. The analysis identified four mainstream application areas: (1) IoT-based smart monitoring systems for carbon emissions, (2) energy efficiency and management applications, (3) sustainable construction implementation frameworks, and (4) smart cities and other built environment applications. Key findings highlight growing research interest in IoT applications for sustainable construction, with China, the United States, and the United Kingdom leading collaborative efforts. Despite demonstrated carbon reduction potential, significant implementation barriers exist, including technical limitations, organizational resistance, skill gaps, and economic constraints. Key opportunities include Artificial Intelligence (AI) integration, Building information modeling (BIM)-IoT synergies, energy prosumer models, and standardization frameworks. This study provides the first focused review of IoT applications specifically targeting carbon reduction in construction, highlighting a critical technology-practice gap where organizational factors frequently outweigh technological barriers. A proposed socio-technical integration framework in this study bridges technical and organizational elements to overcome adoption barriers. Full article

The transition of electric systems from a centralized, fossil-based model toward a decentralized, renewable-powered architecture is reshaping the way electricity is generated, managed and consumed. As distributed energy resources (DERs) proliferate, grid management becomes increasingly complex, especially at the distribution level. In this context, flexibility emerges as a key enabler for more stable and efficient grid operation, while also facilitating greater integration of DER and supporting the electrification of energy demand. Local flexibility markets (LFMs) are gaining importance as structured mechanisms that allow grid operators to procure flexibility services from prosumers, aggregators and other actors. However, to ensure widespread participation, it is essential to develop digital tools that accommodate users of different profiles, regardless of their size, technical background or market experience. The REEFLEX project addresses this challenge by designing and developing 14 interoperable flexibility tools tailored to diverse stakeholder needs. To ensure that these tools are aligned with real market conditions and user expectations, REEFLEX conducted extensive stakeholder-centric surveys. This paper presents the methodology and key findings of those surveys, providing insights into user perceptions, technical requirements and adoption barriers. Results are contextualized within existing literature and other funded initiatives, highlighting implications for the design of inclusive and scalable flexibility markets. Full article

The dynamic growth of the photovoltaic (PV) market in Poland, driven by declining technology costs, government support programs, and the decentralization of energy generation, has created a strong demand for accurate short-term forecasts to support sales planning, logistics, and resource management. This study investigates the application of long short-term memory (LSTM) recurrent neural networks to forecast two key market indicators: the monthly number of completed PV installations and their average unit capacity. The analysis is based on proprietary two-year data from one of the largest PV companies in Poland, covering both sales and completed installations. The dataset was preprocessed through cleaning, filtering, and aggregation into a consistent monthly time series. Results demonstrate that the LSTM model effectively captured seasonality and temporal dependencies in the PV market, outperforming multilayer perceptron (MLP) models in forecasting installation counts and providing robust predictions for average capacity. These findings confirm the potential of LSTM-based forecasting as a valuable decision-support tool for enterprises and policymakers, enabling improved market strategy, optimized resource allocation, and more effective design of support mechanisms in the renewable energy sector. The originality of this study lies in the use of a unique, proprietary dataset of over 12,000 completed PV micro-installations, rarely available in the literature, and in its direct focus on market demand forecasting rather than energy production. This perspective highlights the practical value of the model for companies in sales planning, logistics, and resource allocation. Full article

Energy storage facilities serve as flexible resources that comprehensively support grid operations; they are also essential, especially when the thermal power plants that previously served as regulators run out. Electricity is becoming the dominant carrier through which the bulk of consumers’ energy needs are met. The efficiency of long-distance transmission and the ease of conversion to other forms of energy in Poland are attributed to the national grid. Thanks to the development of new technologies and distribution channels, energy is changing its supply network system. The purpose of this article is to discuss the economic viability of energy storage systems and their strategic role in the energy transition. The research methods used are data analysis, and the dependence on capital expenditures ($CAPEX$) and operating costs ($OPEX$) of energy storage in distribution channels. Energy storage facilities operated by grid companies account for 90% of the installed capacity, but there is a noticeable increase in the number of prosumer installations, with an energy storage of up to 50 KWh at microinstallations. Full article

The paper presents a linear optimisation model aimed at improving the design and operational efficiency of home energy systems (HESs). It focuses on integrating photovoltaic (PV) installations, hybrid heating systems, and emerging energy storage systems (ESSs). Driven by the EU climate policy and the evolution of the Polish electricity market, which have caused price volatility, the model examines the economic and technical feasibility of shifting detached and semi-detached houses towards low-emission or zero-emission energy self-sufficiency. The model simultaneously optimises the sizing and hourly operation of electricity and heat storage systems, using real-world data from PV output, electricity and gas consumption, and weather conditions. The key contributions include optimisation based on large data samples, evaluation of the synergy between a hybrid heating system with a gas boiler (GB) and a heat pump (HP), analysis of the impact of demand-side management (DSM), storage capacity decline, and comparison of commercial and emerging storage technologies such as lithium-ion batteries, redox flow batteries, and high-temperature thermal storage (HTS). Analysis of multiple scenarios based on three consecutive heating seasons and projected future conditions demonstrates that integrated PV and storage systems, when properly designed and optimally controlled, significantly lower energy costs for prosumers, enhance energy autonomy, and decrease CO₂ emissions. The results indicate that under current market conditions, Li-ion batteries and HTS provide the most economically viable storage options. Full article

This paper deals with the optimal scheduling of prosumers equipped with energy storage facilities within renewable energy communities, and proposes a novel strategy for optimizing storage usage within a price–volume demand response framework. The problem is formulated as a scalable, low-complexity mixed-integer linear program. Furthermore, a heuristic procedure is introduced to ensure redistribution of demand response rewards among participants according to their contribution to achieving demand–response goals. The proposed approach is designed to enhance the benefits for prosumers operating within a community compared to running independently. Full article

The integration of small-scale photovoltaic (PV) systems in heritage districts poses a significant challenge: balancing sustainability and energy transition goals while preserving cultural and historical values. This study addresses the problem that existing planning and regulatory frameworks often exclude residents’ perspectives, leading to solutions that are technically feasible but socially contested. The objective is to explore how residents, as potential prosumers, can be effectively integrated into decision-making processes for PV adoption in heritage districts. Focusing on Öjeby Church Town in Piteå, northern Sweden, we employed transdisciplinary participatory design methods, including stakeholder workshops, interviews, council meetings, and a tailored resident design workshop to capture both explicit and tacit knowledge. These design methods were combined with spatial analysis and visual assessment. The findings reveal that residents favour PV solutions that minimise visual impact on heritage buildings, preferring installations in green and grey infrastructure over direct building integration. The process also enhanced awareness, legitimacy, and agency among participants, while exposing regulatory gaps, ownership complexities, and aesthetic tensions. The study contributes a replicable participatory framework that integrates community values with technical and heritage expertise, offering a pathway toward value-sensitive energy transitions in protected cultural environments. Full article

Academic researchers in technical and policy fields tend to pay little attention to the metaphysical and ontological ‘priors’ that nevertheless structure and determine scientific strategies and results. Green political agendas rooted in ecological modernization (EM) are distinguished from antecedent visions predicated on biophysical limits. Net zero is shown to be rooted in a project of global EM. Ecomodernism is analyzed in relation to its principal actors, geopolitical context and underlying metaphysics and anthropology. It is driven by non-negotiable societal priorities (‘ends’), which themselves derive from a particular set of technical ‘means’. The top-down version of the Fourth Industrial Revolution (IR4.0) and new paradigm of global net zero constitute an integrated agenda of eco-modernism. Global net zero cannot hope to achieve its own metabolic goals in respect of either energy flows or the circular economy. A competing, bottom-up and distributed model of the IR4.0 could potentially achieve these targets without falling prey to the Jevons paradox. This potential turns on the greater capacity of low-overhead, prosumer models to nurture less materialist cultural priorities that are more communitarian and family-oriented. A smart energy system that emerges in the context of distributed, domestic and informal production is much more likely to mirror the complex, infinitely gradated and granular pattern of oscillating energy transfers that are characteristic of biological systems. From an ecological economic perspective, such a bottom-up approach to the IR4.0 is much more likely to see the orders of magnitude reduction in the unit energetic cost of social complexity envisaged, in principle, by net zero. Through this comprehensive review of the metaphysical and ontological priors of mainstream IR4.0, researchers in the linked fields of energy and circular economy are presented with a wider range of potential options less constrained by preconceived assumptions about the ‘ends’ of societal development and progress. Full article

This study proposes “Prosuming-Parks,” spatial models that integrate industrial activities with green infrastructure to revitalize South Korea’s border regions. A dataset of 2126 brownfields—including aging industrial sites, military facilities, water infrastructure, public buildings, schools, and railways—was compiled and evaluated through a Prosuming-Park Typology Index linking brownfield types with eight industrial sectors. Six models are derived and applied to fifteen municipalities, suggesting tailored strategies for industrial restructuring and ecological restoration. The framework demonstrates how brownfields can seed scalable green networks and, with future inter-Korean cooperation, evolve into transboundary ecological systems. Full article

Solar photovoltaic (PV) net energy metering (NEM) scheme adoption is generally known for its advantages. However, limited research has been conducted on the prosumers’ behaviors, especially in the industrial and commercial sectors. This study is exploratory and explanatory in identifying the variables; therefore, preliminary research was conducted by interviewing 15 firms and collecting 372 usable responses from the cross-sectional survey questionnaires. The conceptual framework consists of antecedents and outcomes of prosumers’ energy-conserving behaviors (PECB). The antecedent consists of theories conceptualized from the extended TOE called STOPE and institutional theory (INT), with energy-saving culture (ESC) as a moderator. Meanwhile, the outcomes include sustainable energy consumption and production (SECP) and provider–consumer relationships (PCR) as moderators. The outcomes of SECP further revealed the significant results of energy-conserving behavior on the economic, environmental, social, governance, and technical aspects of the sustainable outcome of PECB. Additionally, the findings offer a transformative power and valuable knowledge for policymakers, scholars, and stakeholders in the industry that can significantly contribute to realizing sustainable practices. Future research may explore other variable factors, theories, sampling techniques, and larger samples. Also, different analytic approaches were considered and mixed methods were used to investigate the long-term impacts of prosumers’ energy-conserving behavior patterns and overall sustainability. Full article

Decentralized electricity markets are increasingly shaped by the proliferation of distributed energy resources, the rise of prosumers, and growing demands for privacy-aware analytics. In this context, federated learning (FL) emerges as a promising paradigm that enables collaborative model training without centralized data aggregation. This review systematically explores the application of FL in energy systems, with particular attention to architectures, heterogeneity management, optimization tasks, and real-world use cases such as load forecasting, market bidding, congestion control, and predictive maintenance. The article critically examines evaluation practices, reproducibility issues, regulatory ambiguities, ethical implications, and interoperability barriers. It highlights the limitations of current benchmarking approaches and calls for domain-specific FL simulation environments. By mapping the intersection of technical design, market dynamics, and institutional constraints, the article formulates a pluralistic research agenda for scalable, fair, and secure FL deployments in modern electricity systems. This work positions FL not merely as a technical innovation but as a socio-technical intervention, requiring co-design across engineering, policy, and human factors. Full article

Electrical grids are undergoing a transformation driven by the increasing integration of renewable energy sources on the consumer side. This shift, alongside the electrification of consumption—particularly in areas such as electric mobility—has the potential to significantly reduce CO₂ emissions. However, it is also contributing to a rise in electricity prices due to growing demand and infrastructure costs. Paradoxically, these higher prices serve as a catalyst for further investment in renewable energy technologies by reducing the payback periods of such systems. Recent European legislation has accelerated this transformation by mandating the liberalization of energy markets. This regulatory shift enables the emergence of prosumers—consumers who are also producers of energy—by granting them the right to generate, store, and trade electricity using the existing distribution grid. In this new landscape, photovoltaic systems represent a viable and increasingly attractive investment option for both households and businesses. This study presents an economic evaluation of photovoltaic system investments across different European countries, focusing on key indicators such as payback periods and the impact of local solar irradiation on the resulting electricity price. The analysis provides insight into the varying economic feasibility of distributed solar energy deployment, offering a comparative perspective that supports both policymakers and potential investors in making informed decisions about renewable energy adoption. Full article

Micro and small wind turbines (MAWTs) are increasingly integrated into residential and prosumer hybrid energy systems. However, their real-world performance often falls short of catalog specifications due to mismatched wind resources, siting limitations, and insufficient attention to human comfort. This paper presents a comprehensive decision-support framework for selecting the type and scale of MAWTs under actual local conditions. The energy assessment module combines aerodynamic performance scaling, wind speed-frequency modeling based on Weibull distributions, turbulence intensity adjustments, and component-level efficiency factors for both horizontal and vertical axis turbines. The framework addresses three key design objectives: efficiency—aligning turbine geometry and control strategies with local wind regimes to maximize energy yield; comfort—evaluating candidate designs for noise emissions, shadow flicker, and visual impact near buildings; and climate adaptation—linking turbine siting, hub height, and rotor type to terrain roughness, turbulence, and built environment characteristics. Case studies from low and moderate wind locations in Central Europe demonstrate how multi-criteria filtering avoids oversizing, improves the autonomy of hybrid PV–wind systems, and identifies configurations that may exceed permissible limits for noise or flicker. The proposed methodology enables evidence-based deployment of MAWTs in decentralized energy systems that balance technical performance, resilience, and occupant well-being. Full article

As the energy transition advances toward a low-carbon economy, small- and medium-sized consumers are increasingly becoming active prosumers, capable of generating, storing, and managing their own electricity. However, the intermittent nature of renewable sources poses significant challenges in matching generation with consumption, making energy storage a key element for prosumer participation in smart grids. This work assesses the performance of various energy storage technologies suitable for prosumer applications, focusing on parameters such as efficiency, lifecycle behavior, and system integration. Lithium-ion batteries, supercapacitors, and hydrogen-based technologies were tested under real-world operating conditions within residential, commercial, and industrial scenarios. The results confirm that hybrid configurations deliver the most balanced performance, with supercapacitors improving short-term stability in commercial contexts and hydrogen storage enabling long-duration autonomy in industrial settings. In terms of battery state of charge, the experimental tests showed clear differences across prosumer types: in the residential case, it dropped to about 20–25% in the morning, but recovered to nearly full capacity by midday and stabilized at around 70–75% by the end of the day; in the commercial case, it fluctuated more widely, between roughly 18% and 100%, evidencing the highest stress on batteries; while in the industrial case, it reached 25–30% at peak demand, with hydrogen sustaining autonomy under extended load and ensuring greater long-term reliability. Overall, the findings reinforce the importance of tailored storage strategies to unlock the full potential of prosumers in smart grids. Full article