Search

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. [ABSTRACT FROM AUTHOR]

This research, conducted throughout the years 2022 and 2023, examines the role of blockchain technology in optimizing Demand Response (DR) within Smart Grids (SGs). It critically assesses a range of blockchain architectures, evaluating their impact on enhancing DR's efficiency, security, and consumer engagement. Concurrently, it addresses challenges like scalability, interoperability, and regulatory complexities inherent in merging blockchain with existing energy systems. By integrating theoretical and practical viewpoints, it reveals the potential of blockchain technology to revolutionize Demand Response (DR). Findings affirm that integrating blockchain technology into SGs effectively enhances the efficiency and security of DR, and empirical data illustrate substantial improvements in both cases. Furthermore, key challenges include scalability and interoperability, and also identifying opportunities to enhance consumer engagement and foster system transparency in the adoption of blockchain within DR and SGs. Finally, this work emphasizes the necessity for further investigation to address development hurdles and enhance the effectiveness of blockchain technology in sustainable energy management in SGs. [ABSTRACT FROM AUTHOR]

Energy management and efficiency in port terminals play a crucial role in addressing the environmental challenges of the maritime industry. This article presents a bibliometric review of the existing literature on the subject, focusing on trends in the field of energy management in port terminals. Through a systematic analysis of relevant academic articles, this study identifies key themes and emerging areas of interest. The findings highlight the growing attention to sustainable practices and energy optimization strategies in the maritime and port industry. The review reveals a growing body of research examining energy efficiency measures, renewable energy integration, and the application of advanced technologies. In addition, the analysis highlights the importance of stakeholder collaboration, policy frameworks and regulatory initiatives to promote sustainable energy management practices in port environments. This bibliometric review provides valuable information for researchers, practitioners and policy makers involved in the field of energy management in the maritime industry and port terminals. It provides a comprehensive overview of the current state of knowledge, identifies emerging trends, and points to possible areas for future research. The results of this study contribute to a better understanding of the current state of knowledge, identify emerging trends and point to possible areas for future research. The results of this study contribute to a better understanding of the challenges and opportunities associated with sustainable energy management in port terminals, facilitating the development of effective strategies to mitigate environmental impacts and optimize energy use in this critical sector. [ABSTRACT FROM AUTHOR]

The implementation of non-intrusive load monitoring has gained significant attention as a promising solution for disaggregating and identifying individual appliances' energy consumption within households and commercial buildings. The issue at the core of non-intrusive load monitoring is the accurate separation of the aggregated energy consumption signal into the energy contributions of distinct appliances without requiring additional sensors or invasive measurements. The erroneous implementation of non-intrusive load monitoring model leads to poor results and a waste of time where the criteria for the implementation are necessary. This paper presents an overview of non-intrusive load monitoring's implementation, addressing the stages of non-intrusive load monitoring and advancements in the field. The overview explores the various techniques, methodologies, and algorithms employed in non-intrusive load monitoring systems to achieve load identification and energy disaggregation. By addressing the problem statement and reviewing the state of the art, this paper sets the stage for understanding the significance of non-intrusive load monitoring in commercial buildings and modern energy-efficient households. Moreover, the limitations, applications, and recommended criteria for the implementation of non-intrusive load monitoring are highlighted as a contribution to the field of load disaggregation. Future research should address scalability, privacy concerns, and the integration of non-intrusive load monitoring with smart grids to propel energy disaggregation towards more efficient, accessible, and sustainable energy management systems. We envision that this endeavour can serve as a guiding beacon, offering a roadmap for researchers and professionals. [ABSTRACT FROM AUTHOR]

Given its adaptable and efficient energy consuming devices during peak hours, the residential building sector is urged to take part in demand response (DR) initiatives with the use of a building energy management system (BMS). The residents of buildings with BMS enjoy secure, pleasant, and fully managed lifestyles. Although the BMS helps the building consume less energy and encourages occupant engagement in energy-saving initiatives, unwelcome interruptions and harsh instructions from the system are inconvenient for the inhabitants, which further discourages their participation in DR initiatives. Building automation control is a crucial factor for improving buildings' energy efficiency and management, as well as improving the electricity grid's reliability indices. Smart houses that use the right sizing procedure and energy-management techniques can help lower the demand on the entire grid and potentially sell clean energy to the utility. Recently, smart houses have been presented as an alternative to traditional power-system issues including thermal plant emissions and the risk of blackouts brought on by malfunctioning bulk plants or transmission lines. This paper describes the necessary technology requirements and presents the methodology and the decentralized building automation novel algorithm for efficient demand side management in a building management system. Human comfort aspects including thermal comfort and visual comfort were taken into consideration when selecting heating and lighting controls. The suggested BMS relies primarily on a load-shifting technique, which moves controllable loads to low-cost periods to avoid high loading during peak hours. The model aims to minimize the individual household electricity consumption cost while considering customers' comfort and lifestyle. All these are applied in an experimental university microgrid, and the results are presented in terms of energy saving in kWh, money in €, and working hours. The results demonstrated that the proposed approach might successfully lower energy use during the DR period and enhance occupant comfort. [ABSTRACT FROM AUTHOR]

The interest in sustainability and energy efficiency is constantly increasing, and the noticeable effects of climate change and rising energy prices are fueling this development. The residential sector is one of the most energy-intensive sectors and plays an important role in shaping future energy consumption. In this context, modeling has been extensively employed to identify relative key drivers, and to evaluate the impact of different strategies to reduce energy consumption and emissions. This article presents a detailed literature review relative to modeling approaches and techniques in residential energy use, including case studies to assess and predict the energy consumption patterns of the sector. The purpose of this article is not only to review the research to date in this field, but to also identify the possible challenges and opportunities. Mobility, electrical devices, cooling and heating systems, and energy storage and energy production technologies will be the subject of the presented research. Furthermore, the energy upgrades of buildings, their energy classification, as well as the energy labels of the electric appliances will be discussed. Previous research provided valuable insights into the application of modeling techniques to address the complexities of residential energy consumption. This paper offers a thorough resource for researchers, stakeholders, and other parties interested in promoting sustainable energy practices. The information gathered can contribute to the development of effective strategies for reducing energy use, facilitating energy-efficient renovations, and helping to promote a greener and more sustainable future in the residential domain. [ABSTRACT FROM AUTHOR]

This work, it was carried out with the design and application of a procedure for the diagnosis of energy management in the Company. The procedure is described starting from 7 steps that go from the theoretical conception of 6 variables and 21 elements of the capacity of energy management in the company; the description of the mathematical model based on compensatory diffuse logic, the design of the checkup list until the application and the valuation of the results. The application and valuation of the results in the company’s Acinox Commercial and DIVEP allowed obtaining the evaluation of the energy management capabilities. The variables are analyzed to identify the elements with the lowest performance: projection of actions of energy saving, use and/or generation of clean energy, and energy planning. [ABSTRACT FROM AUTHOR]

The increasing global consumption of energy and its negative impacts on the environment has been an issue discussed both by academics and practitioners, including in the health sector. Hospitals are major consumers of energy, which leads to increased operating costs, decreased competitiveness, and negative environmental impacts. Energy management in hospitals must be understood as a way to contribute to environmental sustainability and as a way to improve competitiveness. Therefore, the objective of this paper is to propose guidelines for efficient and sustainable energy management in hospitals, developed based on the literature review, the challenges faced and the good practices of sustainable energy management in the hospitals studied, the cross analysis of the case studies, and the authors' expertise. As a result, the eight proposed guidelines are related to culture change, energy consumption management, energy management standard, purchase of renewable energy, green technologies, sustainable hospital buildings, social responsibility programs focused on energy use, and sustainable energy public policies. These guidelines contribute in an applied/managerial way to help managers of public and private hospitals overcome the challenges of energy management and contribute to UN's SDG7 due to its potential to improve energy efficiency and environmental performance, therefore, being a movement towards clean energy. This study also theoretically/scientifically contributes to the academic debate since the empirical findings found in the hospitals studied and the proposition of guidelines deepen and expand the key elements identified in the literature on efficient energy management in hospitals, providing the basis for developing new research on the subject. Energy management in hospitals is discussed from the perspective of sustainability. Challenges need to be overcome for sustainability benefits to be achieved. This work can assist public and private hospitals in developing sustainability. Guidelines for sustainable energy management in hospitals are proposed. [ABSTRACT FROM AUTHOR]

There has been increasing interest in reducing carbon footprints globally in recent years. Hence increasing share of green energy and energy efficiency are promoted by governments. Therefore, optimizing energy consumption is becoming more critical for people, companies, industries, and the environment. Predicting energy consumption more precisely means that future energy management planning can be more effective. To date, most research papers have focused on predicting residential building energy consumption; however, a large portion of the energy is consumed by industrial machines. Prediction of energy consumption of large industrial machines in real time is challenging due to concept drift, in which prediction performance deteriorates over time. In this research, a novel data-driven method multi-regime approach (MRA) was developed to better predict the energy consumption for industrial machines. Whereas most papers have focused on finding an excellent prediction model that contradicts the no-free-lunch theorem, this study concentrated on adding potential concept drift points into the prediction process. A real-world dataset was collected from a semi-autonomous grinding (SAG) mill used as a data source, and a deep neural network was utilized as a prediction model for the MRA method. The results proved that the MRA method enables the detection of multi-regimes over time and provides a highly accurate prediction performance, thanks to the dynamic model approach. [ABSTRACT FROM AUTHOR]