A multi-objective optimization tool for the daily management of sustainable smart microgrids: Case Study: the savona campus SPM and SEB facilities

The transition to sustainable and intelligent energy systems has intensified the development of smart microgrids, which offer decentralized, resilient, and efficient power solutions. This review critically examines the integration of Artificial Intelligence (AI) and Deep Reinforcement Learning (DRL) into smart microgrid platforms, focusing on their role in optimizing sustainable energy management. Traditional energy management systems often struggle to adapt to the dynamic nature of modern energy demands, renewable energy intermittency, and grid complexity. AI-driven solutions, particularly DRL, provide adaptive, autonomous, and data-driven mechanisms for real-time decision-making and predictive control within microgrids. DRL, by learning optimal policies through interaction with the environment, is capable of handling multi-objective problems, including demand-response optimization, energy storage control, load forecasting, and distributed generation scheduling. This paper synthesizes recent advancements and applications of DRL algorithms such as Deep Q-Networks (DQN), Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO) in smart microgrids. It also explores hybrid models that combine DRL with other AI techniques, such as fuzzy logic and neural networks, to improve performance under uncertainty and nonlinearity. Furthermore, the review evaluates benchmark testbeds, simulation tools, and real-time platforms used to implement and validate these intelligent systems. Challenges such as high computational costs, model generalizability, real-time implementation issues, and cybersecurity vulnerabilities are discussed. The study also highlights recent research trends emphasizing decentralized control, edge computing, and federated learning to enhance scalability and privacy in DRL-based microgrid applications. Future directions suggest the need for explainable AI (XAI), robust training environments, and standardization to facilitate the wider adoption of DRL in real-world microgrid systems. The integration of DRL into smart microgrids represents a transformative shift toward resilient, efficient, and sustainable energy ecosystems. This review offers a comprehensive understanding of how AI and DRL are revolutionizing energy management, providing a foundation for future research and practical deployment in smart energy infrastructures.

Purpose This study aims to evaluates a public policy program that finances projects for the development of innovative technological solutions. This paper analyzed the influence of human and social capital on the development of the projects, under the perspective of the policy’s effectiveness and efficiency. This specific policy adopted the funding model of economic subsidy by means of grants, which shows the significant engagement of the public sector in applying nonrefundable resources more directly through loans, assuming the role of an entrepreneurial state, according to Mazzucato (2011, 2018) and Tavani and Zamparelli (2020). Design/methodology/approach This is a quantitative-descriptive study, according to Marconi and Lakatos (2017). This study is descriptive, for presenting information on innovation projects funded by FUNCAP (Ceará Foundation for Support to Scientific and Technological Development). In addition, this study is quantitative, by establishing multivariate relationships among the variables that relate to human capital and social capital, which are relevant to technological and innovative development, and by introducing variables on technological evolution, proposed as measures of the program’s effectiveness (DTRL, MkTRL) and efficiency (ETRL). Findings This paper sought to contribute on public policies for innovation, more specifically on analyzing variables that may affect the development of technological and innovative projects in knowledge-intensive companies. The authors studied capitals potentially important for these companies in the development of innovative projects. Specifically, the authors sought to understand the importance of human capital and how it reflects in technical and scientific knowledge of the project team and of social capital and how it reflects the connection and social relationship among different team members. The results presented that the degree of efficiency of the public funding program depends on how much the teams of the benefited projects have accumulated knowledge, skills and technical capacities – the so-called teams’ human capital. Research limitations/implications It is important to address the research sample as a research limitation, which had 72 responses obtained, from a submission rate of 284. Another study limitation is on the qualitative analysis of the topics addressed from the companies and policymakers perspectives, considering that the quantitative nature of the study does not allow for a deeper understanding of the qualitative perspective of the actors involved in the phenomenon studied. As recommendations for future studies, it is suggested to conduct qualitative studies on the aspects studied here. In this sense, it is possible to conduct case studies for specific companies, or policymakers, to clarify and deepen the relationships between the themes addressed here. Practical implications As for the practical implications of the research, both for managers of public funding programs and for company managers, the benefits of human capital, related to innovative project development teams, are important in programs that deal with technological development projects. In practice, this means that the greater the human capital of academic background of the members of the supported project teams, the more efficient the projects are in the process of developing their technologies by using the resources provided (Ashford, 2000; Chen et al., 2008; Lerro et al., 2014). Social implications Hence, the authors conclude that the evaluated innovation-funding program through grants achieved acceptable results in terms of promoting the technological evolution of the benefited projects and bringing the technologies closer to the market. Its efficiency was the least favorable result, showing that the program needs to focus on improving this specific aspect. Within the investigated program, the issue that needs enhancement (efficiency – ETRL) was the one that presented significant relationships with the human and social capital of the benefited projects’ teams. Thus, it is possible that, by selecting more projects that have teams with high capital, the efficiency of the public policy, in this case the development of projects with high technological and innovative potential, will be possibly reached. Originality/value The findings strengthen the need for innovation public policies designed and implemented in a systemic way in the science, technology and innovation ecosystem, to provide a technological infrastructure and human capital necessary for developing projects with high technological and innovative potential (Ergas, 1987; Audretsch and Link, 2012; Caloghirou et al., 2015; Edler and Fagerberg, 2017; Silvio et al., 2019).

Environmental sustainability (ES) is critical for high‐income countries (HICs) because of their high ecological footprints. They are responsible for global environmental problems as they consume more natural resources, produce more output, and generate more greenhouse gases than other countries, which could have severe consequences for land degradation. In the context of resource conservation and land development policies, this study examined the impact of natural resource protection (i.e., land, water, and biodiversity), financial institution inclusion, financial market inclusion, and energy innovation (EI) on the enhancement of ES in 15 HICs from 1995 to 2020. The study applied Feasible GLS and Prais–Winsten regression to consider cross‐sectional dependence, autocorrelation, heteroscedasticity, and slope heterogeneity problems for unbiased and robust findings along with 2nd generation cointegration tests and the JKS Granger non‐causality test. Natural resource protection, financial institution inclusion, financial market inclusion, and EI have positive effects on ES, along with green energy and environmental regulations. It was also found that an increase in real income negatively impacts ES, as it increases the use of natural resources and energy and generates more waste and pollution which further accelerates land degradation. Cointegration and causality also exist between variables of interest. This shows that protecting natural resources, increasing financial inclusion, and EI can be successful strategies for fostering a green transition, reducing environmental impacts, and embracing more sustainable practices and laws to meet development goals and develop sustainable land use policies. This study suggests that HICs should protect land, water, and biodiversity, promote green financing, digital payments, EI, energy diversification, and environmental protection to achieve ES which is critically important to reduce land degradation.

The purpose and rationale of this project has been to develop enduring research capabilities at Utah State University (USU) and the Utah State University Research Foundation (USURF) in a number of energy efficient and renewable energy areas including primarily a) algae energy systems, b) solar lighting, c) intuitive buildings, d) electric transportation, 3) unconventional energy environmental monitoring and beneficial reuse technologies (water and CO2), f) wind energy profiling, and g) land use impacts. The long-term goal of this initiative has been to create high-wage jobs in Utah and a platform for sustained faculty and student engagement in energy research. The program’s objective has been to provide a balanced portfolio of R&D conducted by faculty, students, and permanent staff. This objective has been met. While some of the project’s tasks met with more success than others, as with any research project of this scope, overall the research has contributed valuable technical insight and broader understanding in key energy related areas. The algae energy systems research resulted in a highly productive workforce development enterprise as it graduated a large number of well prepared students entering alternative energy development fields and scholarship. Moreover, research in this area has demonstrated both the technological and economic limitations and tremendous potential of algae feedstock-based energy and co-products. Research conducted in electric transportation, specifically in both stationary and dynamic wireless inductive coupling charging technologies, has resulted in impactful advances. The project initiated the annual Conference on Electric Roads and Vehicles (http://www.cervconference.org/), which is growing and attracts more than 100 industry experts and scholars. As a direct result of the research, the USU/USURF spin-out startup, WAVE (Wireless Advanced Vehicle Electrification), continues work in wirelessly charged bus transit systems and is poised to quickly become a multi-million dollar company with clients around the globe. Moreover, USU students and researchers alike are now on the leading edge of the electrified transportation workforce. Finally, the legacy of this DOE investment in electric transportation is continuing at USU with the formation in progress of an industry sponsored research center built around the Electric Roadway and Vehicle (EVR) research facility and test track (http://evr.usu.edu). The research conducted in unconventional energy environmental monitoring and beneficial reuse technologies experienced broad success developing experimental and modeling tools and implementing those tools to better understand environmental impacts of industrial processes used in unconventional energy development in the Utah’s Uintah Basin. Before this project began the USU Uintah Basin branch campus had minimal capability to perform this regionally critical environmental research. This research investment enabled monitoring and modeling equipment and expertise to assess impacts of energy development to all aspects of environmental quality. Laboratory capability for environmental analysis has been developed and engaged along with field testing at multiple locations. Successful campaigns to measure greenhouse gas and hydrocarbon emissions from produced water surface impoundments and leakage from subsurface oil and gas infrastructure were executed. A computer model of meteorological conditions during winter inversion episodes was created, and commercialization efforts are underway for those models. Finally, in the past 24 months, nearly $2 million in non- DOE external funding from state, local, federal and private entities has been awarded to USU Uintah Basin to continue and add to work and capability established by this task. The preceding examples represent a few highlights resulting from the USU Alternative and Unconventional Energy Research and Development project. The following report provides further detail.

ASEAN countries are emerging economies facing substantial, sustainable energy production and consumption challenges. Power sources’ availability, sustainability, and efficiency are imperative to ensure ecological sustainability. Therefore, these countries must explore the factors that promote sustainable energy supply. The current study investigates the interlinkages between energy infrastructure, financial inclusion, and digitalization on the ecological sustainability of ASEAN region from 1980 to 2018. The study applied the continuously updated fully modified (CUP-FM) and continuously updated bias-corrected (CUP-BC) estimators to address cross-sectional dependency and slope heterogeneity issues. The study’s findings show that energy infrastructure, financial inclusion, and digitalization help to reduce ecological footprints in the long run. Moreover, digitalization complements the impact of energy-efficient infrastructure on ecological footprints. These findings recommend that ASEAN countries should improve energy infrastructure by integrating digitalization into energy supply production, management, and distribution.

This paper examines sustainable development, which employs an integrated approach to tackle environmental, social, and economic challenges. It provides a theoretical underpinning by examining sustainable development's inception, fundamental tenets, and conceptual structures. This study highlights the interdependence of social equity, economic prosperity, and environmental conservation, emphasizing the need for a comprehensive approach. Quantitative methodology is utilized in this study, and the dependent variable is sustainable development. Financial risk, green growth, technological innovation, renewable energy, financial inclusion, and soft infrastructure are all independent variables. The analysis is predicated on secondary data from the Organization for Economic Cooperation and Development and World Development Indicators databases spanning 2004 to 2019. An entropy-weighted method used for the green growth index is a metric that enhances the precision of variable indicators. Cointegration, correlation, VIF, cross-sectional dependency, and stationarity tests are among the diagnostic tests that inform the selection of methods for the panel data set. It is determined that fully modified ordinary least squares is the suitable technique. The findings suggest statistically significant positive correlations among greenhouse gases, financial inclusion, and soft infrastructure. Conversely, significant negative correlations exist between financial risk, green growth, renewable energy, and technological innovation. An estimated 55% long-run variance is present. The study's key finding is that financial risk has an adverse effect on sustainable development, while an impactful relationship where increased green growth is linked to decreased GHG emissions. This association is notably significant. Results show that renewable energy has a negative coefficient and significant negative impact on greenhouse gases, showing an active relation to enhancing sustainable development. In contrast, financial inclusion has a significant positive effect on sustainable development. The implications imply that providing incentives to institutions engaged in alternative energy, precisely renewable sources, could positively impact the environment. Government policies and funding regulations oriented toward sustainable development are indispensable for environmental sustainability. Government policies and incentives are pivotal in advancing an environmentally conscious and sustainable future. This study's contribution lies in elucidating the positive correlation between government interventions and promoting renewable energy adoption, thereby paving the way for a greener tomorrow.

This article sets out to develop the concept and the principal scheme of the formation of a risk management system for innovative economic development projects in the field of aquaculture. The research carried out by the authors helps identify the main problems and characteristics of risk management projects for the development of aquaculture in present-day Russia. The authors outline the status and features of aquaculture development projects in the Northwestern federal district and the Kaliningrad region. The article formulates and justifies the concept of «risk management projects on innovative development of aquaculture in the region» focusing on the classification of aquaculture risks in relation to innovative development projects, which expands the conceptual framework of risk management in view of the specific risks relating to economic development projects in the field of aquaculture. The authors characterize modern methods and approaches to risk management projects and organizations in the context of their application in the framework of aquaculture development projects and offer mechanisms for risk management of aquaculture development projects, which make it possible to include risk management activity in the general context of activities of parent project organization. A concept and principal scheme of formation of risk management system for aquaculture innovative development projects is developed by the authors.

Key performance indicators for Smart Campus and Microgrid

The awareness of Sustainable sources has been increased in present era and easily we can found its reflection in contemporary artwork. The illustrations, wall paintings, digital artworks are the different ways in which artists are integrating sustainable energy concepts into their creative processes with the use of computing technologies. The contemporary artists from Punjab likes, Surjit Kaur, Sadhana Sanger, Sonia Kumar, Anu Verma, Karuna Mohindra, and others are promoting to sustainable energy projects, themes, concepts, media, and forms used by Punjabi contemporary artists for creating awareness in society. These artists reflect the political, social, cultural, and technical milieu of the state at the moment. Currently, we can see the inventiveness of these artists not only in art galleries but also in their attempts to produce artworks on good educations, save nature, and social issues based on sustainable energy development. Their ideas and artworks are making the most of all the opportunities to raise public awareness on sustainable energy sources. Through their artworks, these artists often raised questions, accepted wisdom; push the envelope, and creating awareness of sustainable energy among the peoples. These modern artists could produce works that tackle problems with climate change, renewable energy sources, environmental sustainability. At present the relationship between technology and art are trying to create more sustainable future for all human being

This paper proposes a fuzzy expert system for demand-side management, management of renewable energy sources, and electrical energy storage for smart households and microgrids. The proposed fuzzy expert system is used for automatic decision making regarding energy management in smart microgrids containing renewable sources, storage systems, and controllable loads. The fuzzy expert system optimizes energy consumption and storage in order to utilize renewable energy and maximize the financial gain of a microgrid. In order to enable energy management, the fuzzy expert system uses insolation, price of electrical energy, temperature, wind speed, and power of the controllable and uncontrollable loads as input variables. These input data can be directly measured, imported from grid measurements, or predicted using any data prediction method. This paper presents fuzzification of input variables, defines a set of rules of the expert system, and presents defuzzification of outputs. The outputs of the expert system are decisions, i.e., answers to the question of how to manage energy production and consumption in a microgrid. Three outputs are defined to decide about produced energy, controllable loads, and own consumption. The first output is used to store, sell, or consume produced energy. The second output is used to manage the controllable load. The third output shows how to supply own consumption of the prosumer. The expert system is tested on hourly values of input variables in a single day in Serbia. The proposed approach is compared with other available approaches in order to validate the results.

IoT-based optimal demand side management and control scheme for smart microgrid

A ‘smart microgrid’ refers to a distribution network for electrical energy, starting from electricity generation to its transmission and storage with the ability to respond to dynamic changes in energy supply through co-generation and demand adjustments. At the scale of a small town, a microgrid is connected to the wide-area electrical grid that may be used for ‘baseline’ energy supply; or in the extreme case only as a storage system in a completely self-sufficient microgrid. Distributed generation, storage and intelligence are key components of a smart microgrid. In this paper, we examine the significant role that buildings play in energy use and its management in a smart microgrid. In particular, we discuss the relationship that IT equipment has on energy usage by buildings, and show that control of various building subsystems (such as IT and HVAC) can lead to significant energy savings. Using the UCSD as a prototypical smart microgrid, we discuss how buildings can be enhanced and interfaced with the smart microgrid, and demonstrate the benefits that this relationship can bring as well as the challenges in implementing this vision.

This article pioneers innovative strides at the crossroads of technology and inclusivity, focusing on creating supportive environments for individuals with autism. It introduces a groundbreaking approach to bolstering cybersecurity within smart microgrids (SGs) deployed in autism-friendly educational settings. It addresses integrating IoT security protocols and sustainable energy management within autism-friendly schools. It aims to ensure a reliable and efficient energy supply while safeguarding sensitive IoT systems used to support educational and sensory needs of students with autism. Through a meticulously crafted four-layered monitoring architecture tailored to SGs in educational institutions catering to autistic children, this research addresses emerging threats and evaluates the impact of advanced two-axis solar tracking systems on PV panel performance within these grids. Central to this endeavor is the integration of blockchain technology to secure data exchange among renewable resource management, smart metering, and SGs, fostering a secure and efficient energy ecosystem. The study showcases exceptional results from the implementation of SGs at the Naama solar energy center, achieving a remarkable annual production of 55374 MWh. Noteworthy metrics, particularly in June, highlight robust power generation and solar radiation under optimal conditions, with a performance rate of 0.79. The annual loss diagram reveals that ≈ 16.2% of losses stem from module inefficiencies, and 5.2% originate from converter losses. By delving into IoT security, renewable energy management, and inclusive education, this article presents a multifaceted approach that promises transformative advancements in interconnected domains. Integrating the efficient P&O MPPT technique in the solar installation at our autism-friendly school enhances system reliability and energy efficiency, while also supporting educational goals and environmental sustainability, positively impacting the specialized learning environment.

Smart microgrids (SMGs) have emerged as a key solution to enhance energy management and sustainability within decentralized energy systems. This paper presents SmartGrid AI, a platform integrating deep reinforcement learning (DRL) and neural networks to optimize energy consumption, predict demand, and facilitate peer-to-peer (P2P) energy trading. The platform dynamically adapts to real-time energy demand and supply fluctuations, achieving a 23% reduction in energy costs, a 40% decrease in grid dependency, and an 85% renewable energy utilization rate. Furthermore, AI-driven P2P trading mechanisms demonstrate that 18% of electricity consumption is handled through efficient decentralized exchanges. The integration of vehicle-to-home (V2H) technology allows electric vehicle (EV) batteries to store surplus renewable energy and supply 15% of household energy demand during peak hours. Real-time data from Saudi Arabia validated the system’s performance, highlighting its scalability and adaptability to diverse energy market conditions. The quantitative results suggest that SmartGrid AI is a revolutionary method of sustainable and cost-effective energy management in SMGs.

The Role of Good Governance in Driving and Promoting Sustainable Development in the Provision of Off-Grid Electricity Solutions in Nigeria