Smart Energy Systems Research Articles

A Enhancing Data Security Solutions for Smart Energy Systems in IoT-Enabled Cloud Computing Environments through Lightweight Cryptographic Techniques

A Enhancing Data Security Solutions for Smart Energy Systems in IoT-Enabled Cloud Computing Environments through Lightweight Cryptographic Techniques

Urban emissions and land use efficiency scenarios for avoiding increments of global warming

Urban areas have key roles in climate mitigation, including increasing renewable energy penetration in smart energy systems. The potential of urban areas in limiting global warming, however, is not quantified. This research work develops a new framework to analyse urban emissions and land use efficiency scenarios with coupling to the transient climate response to cumulative carbon dioxide emissions. Two new parameters that quantify contributions to and avoidance of increments of global warming from urban areas are formulated and applied to twelve scenario combinations. The results for 465 urban areas indicate that a green-growth scenario with lower ambition in reducing urban emissions can lead up to a 0.13 °C additional increment of global warming in 2050 based on the best estimate of the transient climate response to cumulative carbon dioxide emissions. Those of the most ambitious urban emissions scenario with green-growth and renewable energy are limited to 0.06 °C. When combined with the most ambitious land use efficiency scenario for 135 urban areas, it is possible to avoid more than double or 2.09 times additional increments of global warming in comparison to other integrated urban scenarios. The mean and 5–95th percentile range of the results are compared based on 10,000 Monte Carlo simulations. Informing on the urgency to ensure ambitious mitigation action in urban areas can support a climate future that remains within critical thresholds and tipping elements of the planet.

Balancing Possibilist-probabilistic risk assessment for smart energy hubs: Enabling secure peer-to-peer energy sharing with CCUS technology and cyber-security

This paper introduces the Possibilistic-Probabilistic Risk-based Smart Energy Hub (PPR-SEH) scheduling model, addressing cybersecurity challenges in the transition to advanced energy systems characterized by decarbonization, decentralization, and digitalization. The model integrates cutting-edge technologies like Carbon Capture Utilization and Storage (CCUS) and demand response programs. It addresses uncertainties from renewable energy sources, demand variability, fuel supply, and energy price fluctuations using a Z-number-based approach. Covering various energy types—electricity, heat, cooling, gas, and water—the PPR-SEH model offers a comprehensive energy management solution. Employing a mixed-integer linear programming (MILP) framework optimized with the CPLEX solver in GAMS software, it uses an epsilon constraint method and a fuzzy satisfying approach for solution selection. The model also evaluates the economic and environmental impacts of peer-to-peer energy-sharing markets linked with carbon emission trading, enhancing the efficiency and sustainability of energy distribution. The findings reveal that incorporating robust cybersecurity measures and integrating demand response and CCUS significantly influence operational efficiency and sustainability, evidenced by an increase in costs and pollution by approximately 11.43 % and 1.8 %, respectively, compared to deterministic approaches. This study underscores the importance of robust planning and the beneficial impact of a carbon system on load curve management and economic returns in smart energy systems.

Sustainable Energy Planning and Management with PV, Waste heat, positive energy districts and CO2 accounting

This 41st volume of the International Journal of Sustainable Energy Planning and Management includes three categories of papers: Ordinary submissions, submissions from the 2023 Smart Energy Systems Conference held in Copenhagen, Denmark and a submission from the 2023 Sustainable Development of Energy, Water and Environmental Systems (SDEWES) conference series. The work presented address photo voltaics (PV) in the arctic and in Sweden and electricity system scenarios of Indonesia based on, e.g. PV. Staying with PV a study investigated the interplay between PV and electric vehicles in Denmark. Moving to district heating, two papers address waste heat utilisation and positive energy districts respectively, and finally a study proves into unavoidable carbon dioxide emissions in Austria accounts for carbon capture and storage (CCS) and carbon capture and utilisation (CCUS) needs and possibilities.

Transition towards Positive Energy District: a case study from Latvia

The transition from a fossil fuel-based energy system to renewable energy sources has become a crucial consideration in both national-scale planning processes and local-scale energy system planning. Research has been conducted to seek technical solutions for a specific district of a university campus located on the peninsula of Riga to implement a smart energy system with multiple energy sources, storage systems, and energy efficiency measures. The solutions for the transformation of Energy Island to an Energy Community include power generation by building integrated solar panels with different power storage alternatives, such as thermal storage, batteries, hydrogen, and fuel cells. The simulation also evaluates the potential for heat recovery and waste heat integration from the data center and cooling systems to cover the heat demand. The interlinkage with energy efficiency improvements through improved building management systems provides an opportunity to increase RES utilization rates and improve overall energy efficiency. To provide a holistic overview of the future development of the urban area, the research also compares the connection to the district heating network. Results show that the analyzed energy community can achieve up to 80% of the RES self-consumption level as cost-optimal solutions by combining off-site wind turbine, solar PV panels, water source heat pumps, waste heat recovery and adjusted power storage.

Conceptual vision of the smart energy system

In modern scientific and political circles, the smart energy system is considered as an integral component of Industry 4.0, since in a broad sense it serves the purpose of increasing production efficiency due to the introduction of artificial intelligence technologies. However, currently there is no single, established vision regarding the meaning of the term "smart energy system". As a rule, it is viewed through the prism of separate, often unrelated technological processes, which complicates the development of consistent theoretical provisions and practical recommendations for the development of Industry 4.0. The purpose of the article is the systematization of scientific views on certain aspects of the application of digital technologies in the field of energy and the development of a holistic conceptual vision of a smart energy system. The key elements of the smart energy system consist of smart energy generation, as a set of digitalization measures for the control system of energy generating facilities, aimed at increasing the specific production of electricity, as well as adjusting the load within the nodes of electricity production from renewable sources with the aim of stabilizing the energy flow; smart synchronization, which is designed to distribute the load among the energy sectors on the basis of an intelligent assessment of system needs and capabilities; smart distribution, which optimizes the operation of distribution networks based on data analysis of temporal and spatial trends in the electricity transmission system; and smart consumption, which involves the implementation of technological measures that create conditions for economical consumption of electricity. The holistic vision of the "smart energy system" concept, which provides for the comprehensive implementation of measures provided for by the micro-concepts of smart energy generation, smart synchronization, smart distribution and smart consumption, is substantiated. It is argued that the implementation of the “smart energy system” concept will ensure a synergistic effect of economical utilization of energy resources.

Smart Energy Systems Based on Next-Generation Power Electronic Devices

Power electronics plays a key role in the management and conversion of electrical energy in a variety of applications, including the use of renewable energy sources such as solar, wind and hydrogen energy, as well as in electric vehicles, industrial technologies, homes and smart grids. These technologies are essential for the successful implementation of the green transition, as they help reduce carbon emissions and promote the production and consumption of cleaner and more sustainable energy. The present work presents a new generation of power electronic devices and systems, which includes the following main aspects: advances in semiconductor technologies, such as the use of silicon carbide (SiC) and gallium nitride (GaN); nanomaterials for the realization of magnetic components; using a modular principle to construct power electronic devices; applying artificial intelligence techniques to device lifecycle design; and the environmental aspects of design. The new materials allow the devices to operate at higher voltages, temperatures and frequencies, making them ideal for high-power applications and high-frequency operation. In addition, the development of integrated and modular power electronic systems that combine energy management, diagnostics and communication capabilities contributes to the more intelligent and efficient management of energy resources. This includes integration with the Internet of Things (IoT) and artificial intelligence (AI) for automated task solving and work optimization.

Smartening Local Energy in Europe: A Comparative Analysis of Three Cases and Their Implications for Supporting Transformative Governance Practices

Achieving global sustainability goals, while maintaining or increasing access to energy services, calls for agile and many-faceted responses. The pursuit of ‘smart local energy systems’ is one such response that involves a paradigm shift, taking the concept of an energy system away from large-scale power plants and fuel stores towards more flexible configurations to harness renewable energy flows, with highly distributed physical assets, actors, skills and controls. Smart local energy requires citizens, industry, utilities and government bodies to collaborate and learn together in order to develop effective modes of governing that meet sustainability goals and provide reliable, accessible energy services. In this article, we introduce practical implications of creating more localised energy systems with the aid of digital technologies. We then analyse three emerging European energy communities in terms of their actors, activities and alliances, to build an understanding of governance practices within and beyond the communities that are capable of fostering transformative change towards sustainability. From this, we argue that maintaining progress towards smart local energy systems requires transformative governance within and beyond initiatives. It requires local governance arrangements that are agile and responsive to new actors and activities as well as to broader external circumstances.

Study on Consumers’ Perceived Benefits and Risks of Smart Energy System

This study explores consumer perceptions of smart energy systems, delving into both the perceived benefits and risks associated with their adoption and usage. This study addresses a crucial gap in understanding the consumer side of smart energy system implementation. Through ordinal logistic regression analysis, the study examines the relationship between various independent variables and an ordinal dependent variable represented on a Likert scale. The findings highlight a significant consumer emphasis on 'Safe Energy System Construction' and 'Economic Benefits,' including 'Home Energy Saving' and 'New Profit Creation.' However, the perceived benefits and risks are influenced by these factors and individual propensities, such as sensitivity to environmental destruction and acceptance of new technology. The study uncovers new areas of concern, exceptionally high energy consumption and the 'Uncertainty of Electricity Rates,' which have not been extensively addressed in previous research. The conclusions drawn from this study suggest a need for balanced policy-making that fosters technological advancement while addressing consumer apprehensions about energy consumption, rate volatility, and privacy. This study contributes to the broader discourse on technology acceptance and the sustainable implementation of smart energy solutions by providing a nuanced understanding of consumer perceptions in the evolving landscape of smart energy systems.

The Future Design of Smart Energy Systems with Energy Flexumers: A Constructive Literature Review

From powering our homes to driving our economies, energy lies at the heart of humanity’s complex challenges in the modern era. This paper reviews the evolution of smart energy systems, examining their technological advancements and societal implications while proposing a future design framework emphasizing four key pillars: holistic resource optimization, adaptive intelligence, environmental harmony, and human-centered design. While they offer numerous benefits, such as enhanced energy efficiency and reduced carbon emissions, smart energy systems also face challenges. These include cybersecurity risks, the complexity of integrating diverse energy sources seamlessly, high upfront costs, and potential compatibility issues arising from evolving technologies. Overcoming these challenges will be crucial for unleashing the full potential of smart energy systems and facilitating their global adoption. Abundant opportunities for further research and development exist in this domain, awaiting exploration and advancement.

A multi-stage interval optimization approach for operation of the smart multi-carries energy system considering energy prices uncertainty

A multi-stage interval optimization approach for operation of the smart multi-carries energy system considering energy prices uncertainty

An Integrated Smart Metering System Using LORA Technology

Precise meter readings are essential for effectively regulating residential energy systems in India's smart city context. However, due to the high number of users and the absence of daily consumption monitoring, standard meter reading methods are expensive and time-consuming, which causes consumer unhappiness. The suggested approach to address this issue is to put in place an integrated wireless smart energy system that makes use of smart metering technologies. The way utilities manage energy could be completely changed by this method. The integrated system is intended to take the place of the traditional digital energy meters, which are primarily used to record meter readings properly for payment purposes. This allows for automatic meter readings without the need for frequent travels to the location where the meters are located. Low Power Wide Area Networks (LPWAN) technology, which is renowned for its low power consumption, cost-effectiveness, long-range coverage, and efficient penetration, are used in this technology to enable the transfer of accurate and secure data on energy usage in real-time. The experiments that resulted from the trials allowed the energy to successfully communicate and documented reliable readings. By providing users with real-time usage data and guarding against overloaded scenarios, the system also benefits consumers. Additionally, the device reports electricity theft to the utility company. The shortcomings of the conventional systems and design difficulties are addressed by the suggested system.

Environmental impacts analysis of Moroccan olive cake combustion in Stirling motor cogeneration system: Case study

Morocco is the world's 5th largest olive oil producer with 160,000 tons in 2020/2021 and the production of 1 L of olive oil generated approximately 5 kilos of waste olive cake, this type of waste is dangerous for the environment and especially for groundwater. To address this issue and take into account the thermal properties of olive waste, our project's goal is to produce power and heat by using solid olive waste in a Stirling cogeneration system. Therefore, the goal of this article is to examine by using CFD tools the environmental impacts of the Moroccan solid olive waste burning in a CHP (combined heat and power) unit. The idea is to integrate a smart renewable energy system based on olive cake and the Stirling motor to produce electricity in order to employ this electrical energy for water pumping in rural areas.The impact of the excessive air ratio on temperature profile and exhaust has been investigated and discussed. In addition, the pollutant species in air has been presented, and compared with guideline values given by some international organization for health and environment. Results show that the highest excess air ratio gives high temperatures with a homogeneous distribution around the Stirling motor hot heat exchanger, and minimum emissions of CO, CO2, NO, NO2 and NH3 that do not exceed the values set by WHO, OSHA, and NIOSH.

Pricing Game and Blockchain for Electricity Data Trading in Low-Carbon Smart Energy Systems

Pricing Game and Blockchain for Electricity Data Trading in Low-Carbon Smart Energy Systems

Optimized scheduling of smart community energy systems considering demand response and shared energy storage

Integrated energy systems within communities play a pivotal role in addressing the diverse energy requirements of the system, emerging as a central focus in contemporary research. This paper contributes to exploring optimal scheduling in a smart community featuring multiple smart buildings equipped with a substantial share of distributed photovoltaic sources, shared energy storage, and controllable loads. The study formulates a two-stage scheduling optimization model incorporating multiple stakeholders, explicitly examining the game dynamics between the smart community operator and the customer load aggregator. The weights assigned to each optimization objective are determined using an analytic hierarchy process-entropy weight method to establish a balanced and nuanced approach. The ensuing optimal scheduling encompasses unit output and energy trading considerations, focusing on enhancing the system's economic viability, safety measures, and environmental sustainability. A comprehensive evaluation is conducted to validate the proposed model by comparing its performance with alternative operational strategies. The results show that the designed strategy can reduce the operating cost by 40.22% and increase the level of PV consumption by 22.57% compared to the traditional heat-based strategy, which is effective in mitigating power fluctuations, smartly responding to dispatch peak demand, enhancing new energy integration, and ensuring the security of grid operation.

A Comparative Analysis of Machine Learning-Based Energy Baseline Models across Multiple Building Types

Building energy baseline models, particularly machine learning-based models, are a core aspect in the evaluation of building energy performance to identify inefficient energy consumption behavior. In smart city design, energy planners and decision makers require comprehensive information on energy consumption across diverse building types as well as comparisons between different types of buildings. However, there is no comprehensive study of baseline modeling across the main building types to help identify factors that influence the performance of different machine learning algorithms for baseline modeling. Therefore, the goal of this paper is to review and analyze energy consumption behavior and evaluate the prediction performance and interpretability of machine learning-based baseline modeling techniques across major building types. The results have shown that the Extreme Gradient Boosting Machine (XGBoost) model is the most accurate baseline modeling method for all building types. Time-related factors, especially the week of the year and the day of the week, have the most impact on energy consumption across all building types. This study is presented as a useful resource for smart city energy managers to help in choosing and setting up appropriate methodologies for better operational effectiveness and efficiencies when designing and planning smart energy systems.

Enhancing the performance of sustainable energy management of buildings in smart cities

Energy utilization has been the most influential parameter in recent decades, especially in the smart city model. The energy management system has been a more attractive research problem due to its utility, ability, and applications. This paper has an objective that the article discusses innovative energy management methods for sustainability and highlights the potential for integrated smart energy sources. The discussion also touches on the understanding of energy management and production, various storage systems, and their potential future applications. This paper explores challenges in sustainable smart energy management, focusing on methodologies like smart energy systems, PV calculations, electric grid models, and energy management strategies in smart cities. The passive infrared receiver (PIR) sensor has been used in real-time energy management systems to integrate these methodologies into the city's infrastructure. The energy management design aims to coordinate electrical appliances such as fans and lights to minimize energy consumption. The article proposes new energy management and security techniques based on data sources to enhance city intelligence, adaptability, and sustainability by reducing human involvement in controlling electrical appliances in residential buildings. The proposed design and development system optimizes energy utilization more efficiently and effectively than conventional systems, meeting real-time energy management objectives.

Multi-objective scheduling and optimization for smart energy systems with energy hubs and microgrids

This paper introduces a novel model for optimizing microgrid systems by integrating multi-purpose renewable energy (MEM) and cutting-edge technologies, including electric vehicles (EVs). The proposed MEM demand response programs encompass various energy sources such as wind energy, multi-carrier energy storage technologies, boilers, combined heat and cooling units, EVs, P2G (power-to-gas), and demand response capabilities. The primary objective is to minimize the total operational cost of the microgrid system. A distinctive aspect of the proposed method lies in considering the prices of all energy carriers as unknown variables. Market prices are integrated into the modeling process, incorporating scenarios with reasonable probabilities and taking into account demand-side management programs. Moreover, the model allows for customizable programming of different parts of the multi-energy microgrids, with a focus on maintaining convexity principles for the operating area of each CHP (combined heat and power) unit. To tackle the unique complexity of this optimization problem, a developed blue whale optimization algorithm is proposed. This algorithm builds upon the main whale optimization algorithm (WOA), a promising population-based optimization approach. However, the effectiveness of WOA heavily relies on the careful setting of exploration and exploitation parameters, which may lead to being trapped in local optima. To address this challenge, the paper introduces a self-adaptation modification based on wavelet theory to enhance the WOA's performance. The proposed model and optimization method are thoroughly evaluated through simulation studies for different scenarios, showcasing their efficacy in achieving cost-efficient and sustainable microgrid operation. The combination of MEM and emerging technologies like EVs, along with the improved optimization algorithm, marks a significant contribution to advancing the planning and operation of microgrid systems towards low-cost, reliable, and environmentally-friendly energy solutions.

Carbon emissions of power transmission and transformation projects in the whole life cycle for smart sustainable energy systems

The study investigates the optimization of life cycle carbon emissions in smart sustainable energy systems through power transformation and transmission project power load predictions. Firstly, a multi-task learning-based short-term user load forecasting technique is developed, where the power load curves of multiple residential customers are grouped and classified using the K-means clustering method. Additionally, the Bidirectional Long Short-Term Memory (BiLSTM) technique is introduced to anticipate the power load intelligently. Secondly, a life cycle carbon emission assessment model for the power transmission and transformation project (PTTP) is constructed based on the life cycle assessment (LCA) method, which divides the project's life cycle into four stages: production, installation and construction, operation and maintenance, and demolition. Finally, an experimental evaluation of this model is conducted. The results demonstrate that compared with the baseline model Long Short-Term Memory (LSTM), this model achieves a significantly lower average Mean Absolute Error (MAE) at 3.62% while achieving significantly higher accuracy in power load forecasting at 94.34%. A comprehensive examination of carbon emissions across all four phases reveals that overall carbon emissions are highest during the operation and maintenance stage followed by the equipment production stage and installation/construction stage, with the lowest overall carbon emissions observed. Hence, this study endeavors to forecast power load demand with precision and identify the principal determinants of carbon emissions in power engineering. By discerning and managing these key factors, an optimal, energy-efficient intelligent power load scheme can be derived.

Теоретичний зміст поняття «смарт-енергосистема»

This article focuses on the analysis of the concept of smart energy systems, which are becoming a fundamental element in managing energy resources on a global scale. The research encompasses both domestic and international perspectives, comparing various approaches of scientists, governmental institutions, and industrial players in the application of smart technologies in energy. Special emphasis is placed on the diversity of definitions of smart energy systems, their approaches, and implementations, which significantly impact economic security, sustainability, and the integration of innovative technologies. The article examines how smart energy systems contribute to the stabilization of energy networks, optimization of energy production and consumption, and discusses their role in meeting contemporary environmental and economic challenges. This study provides a comprehensive overview of current technologies and strategic development directions that can be utilized to support sustainable and efficient energy systems in the future.