Search Results (17)

With the gradual shift towards the use of electric vehicles (EV), electricity demand is expected to increase especially in energy communities. Therefore, it is important to investigate how energy is generated as the provenance of electricity supply is directly linked to climate change. There are only a few studies that investigated the internet of energy and energy provenance, but this area of research is important to prevent the rebound effect of CO₂ emission due to the lack of a transparent approach that verifies the source of electricity consumed for charging EVs. The energy system is a complex network, which results in difficulty verifying the source of electricity as related to the generation of energy. Identifying the provenance of electricity is challenging since electricity is a non-physical element. Moreover, the volatility of a Renewable Energy Source (RES), such as solar and wind power farms, in relation to the complex electricity distribution system makes tracking and tracing challenging. Disruptive technologies, such as Distributed Ledger Technologies (DLT), have been previously adopted to trace the end-to-end stages of products. Likewise, artificial intelligence (AI) can be adopted for the optimization, control, dispatching, and management of energy systems. Therefore, this study develops a decentralized intelligent framework enabled by AI-based DLT and smart contracts deployed to accelerate the development of the internet of energy towards energy provenance in energy communities. The framework supports the tracing and tracking of RES type and source consumed for charging EVs. Findings from this study will help to accelerate the production, trading, distribution, sharing, and consumption of RES in energy communities. Full article

Automation in agricultural machinery, underpinned by the integration of advanced technologies, is revolutionizing sustainable farming practices. Key enabling technologies include multi-source positioning fusion (e.g., RTK-GNSS/LiDAR), intelligent perception systems utilizing multispectral imaging and deep learning algorithms, adaptive control through modular robotic systems and bio-inspired algorithms, and AI-driven data analytics for resource optimization. These technological advancements manifest in significant applications: autonomous field machinery achieving lateral navigation errors below 6 cm, UAVs enabling targeted agrochemical application, reducing pesticide usage by 40%, and smart greenhouses regulating microclimates with ±0.1 °C precision. Collectively, these innovations enhance productivity, optimize resource utilization (water, fertilizers, energy), and mitigate critical labor shortages. However, persistent challenges include technological heterogeneity across diverse agricultural environments, high implementation costs, limitations in adaptability to dynamic field conditions, and adoption barriers, particularly in developing regions. Future progress necessitates prioritizing the development of lightweight edge computing solutions, multi-energy complementary systems (integrating solar, wind, hydropower), distributed collaborative control frameworks, and AI-optimized swarm operations. To democratize these technologies globally, this review synthesizes the evolution of technology and interdisciplinary synergies, concluding with prioritized strategies for advancing agricultural intelligence to align with the Sustainable Development Goals (SDGs) for zero hunger and responsible production. Full article

In modern electrical grids, the numbers of customer-owned distributed energy resources (DERs) have increased, and consequently, so have the numbers of points of common coupling (PCC) between the electrical grid and customer-owned DERs. The disruptive operation of and out-of-tolerance outputs from DERs, especially owned DERs, present a risk to power system operations. A common protective measure is to use relays located at the PCC to isolate poorly behaving or out-of-tolerance DERs from the grid. Ensuring the integrity of the data from these relays at the PCC is vital, and blockchain technology could enhance the security of modern electrical grids by providing an accurate means to translate operational constraints into actions/commands for relays. This study demonstrates an advanced power system application solution using distributed ledger technology (DLT) with smart contracts to manage the relay operation at the PCC. The smart contract defines the allowable total power factor (TPF) of the DER output, and the terms of the smart contract are implemented using DLT with a Cyber Grid Guard (CGG) system for a customer-owned DER (wind farm). This article presents flowcharts for the TPF smart contract implemented by the CGG using DLT. The test scenarios were implemented using a real-time simulator containing a CGG system and relay in-the-loop. The data collected from the CGG system were used to execute the TPF smart contract. The desired TPF limits on the grid-side were between +0.9 and +1.0, and the operation of the breakers in the electrical grid and DER sides was controlled by the relay consistent with the provisions of the smart contract. The events from the real-time simulator, CGG, and relay showed a successful implementation of the TPF smart contract with CGG using DLT, proving the efficacy of this approach in general for implementing electrical grid applications for utilities with connections to customer-owned DERs. Full article

This paper reviews renewable energy integration with the electrical power grid through the use of advanced solutions at the device and system level, using smart operation with better utilisation of design margins and power flow optimisation with machine learning. This paper first highlights the significance of credible temperature measurements for devices with advanced power flow management, particularly the use of advanced fibre optic sensing technology. The potential to expand renewable energy generation capacity, particularly of existing wind farms, by exploiting thermal design margins is then explored. Dynamic and adaptive optimal power flow models are subsequently reviewed for optimisation of resource utilisation and minimisation of operational risks. This paper suggests that system-level automation of these processes could improve power capacity exploitation and network stability economically and environmentally. Further research is needed to achieve these goals. Full article

Resource management in agriculture is considered a pivotal issue because greenhouse farming and agriculture-related activities generate about 10–29% of all global greenhouse gas emissions. The problem of high greenhouse gas emissions is still unresolved due to the rapid expansion of arable land to meet global food demand. The purpose of this systematic literature review was to generate new perspectives and insights regarding the development of resource management and optimized environments in greenhouses, thereby lowering energy requirements and CO₂ emissions. This review sought to answer what technologies and inventions could be used to achieve zero greenhouse gas emissions through efficient energy-saving mechanisms while considering their technical and economic viability. The synthesis of the findings led to several themes which included energy-saving techniques for greenhouses, systems that reduced unfavorable external conditions and renewable energy systems. Other themes identified regarded energy storage systems, systems for managing conditions in greenhouses, carbon capture and storage, and factors influencing the performance of different technologies to enhance resource management and ensure zero carbon emissions. The findings also revealed various technologies used in the design of energy-saving techniques in greenhouses including proportional–integral–derivatives (PID), fuzzy, artificial neural networks, and other intelligent algorithms. Additionally, technologies that were a combination of these algorithms were also examined. The systems that reduced unfavorable external conditions included the use of insulation panels and intelligent shading systems. Greenhouse covers were also optimized by smart glass systems, sensors, Internet of Things (IoT), and Artificial Intelligence (AI) systems. Renewable energy systems included PV (solar) panels, wind turbines, and geothermal electricity. Some of the thermal energy storage systems widely studied in recent research included underground thermal energy storage (UTES) (for seasonal storage), phase-change materials (PCMs), and water tanks, which are used to address short-term shortages and peak loads. The adoption of the various technologies to achieve the above purposes was constrained by the fact that there was no isolated technology that could enable agricultural producers to achieve zero energy, zero emissions, and optimal resource utilization in the short term. Future research studies should establish whether it is economical for large agricultural companies to install smart glass systems and infrastructure for slow fertilizer release and carbon capture in greenhouse structures to offset the carbon footprint. Full article

NH₃ emissions are an environmental issue that is of wide concern in livestock production. In intensive livestock farming, it is necessary to study outdoor ammonia concentrations under various conditions to maximize the protection of livestock caretakers’ health in and around the facilities. In this study, the ammonia concentrations outside smart broiler chambers in 60 scenarios, with conditions including 4 broiler chamber densities, 3 wind directions, and 5 outlet emission intensities, were simulated based on computational fluid dynamics (CFD) technology. The results show that (1) outdoor ammonia tends to accumulate near the outlet when the wind direction angle is small, while it has a wider range of influence when the angle is vertical; (2) building a smart broiler chamber cluster for intensive livestock farming is environmentally friendly; and (3) keeping the ammonia outlet perpendicular to the local dominant wind direction can effectively prevent high concentrations of ammonia around the chambers. In practical applications, the conclusions of this study can be used to arrange the layout and direction of smart broiler chamber clusters. Full article

In the next twenty years, the scarcity of food shortage and drinking water will appear in Egypt due to the growth of industries and agriculture. This paper develops a conceptual design of the new technologies in the field of water–energy–food in new cities. Border lines are the internal relationship, external influence, and linkage system evaluation for WEF nexus. The major problems of using fossil energy in desalination are emissions and non-renewability, as well as the preference for dispersed freshwater production instead of concentrated output. The design of a desalination system that is integrated with renewable energies is critical these days. This type of system can also reduce the production of environmental pollutants due to reduced energy consumption and transfer of freshwater. GIS data from the United Nations have confirmed the existence of an underground reservoir in Wadi-Dara that can cultivate 1000 acres using smart farming techniques to reach a circular economy for an integrated solution between the water–energy nexus. The possibility of cultivating a hundred acres in Wadi-Dara on the Red Sea coast exists, through which about one million people could be settled. In this comprehensive review, we conducted a deep study in order to establish a sustainable integrated lifestyle in the Dara Valley region in terms of the availability of potable water, clean energy, and agriculture. Sustainable integrated solutions were conducted for seawater desalination using beach sand filtration wells as a pretreatment for seawater using renewable energy, e.g., wind energy (18% wind turbines), and photovoltaic panels (77% PV panels). Strategic food will be cultivated using smart farming that includes an open ponds cultivation system of microalgal cells to synthesis (5.0% of bio-fuel (. Aqua agriculture and aquaponics will cultivate marine culture and integrate mangrove, a shrimp aquaculture. A municipal waste water treatment is conceived for the irrigation of shrubby forests and landscapes. Mixotrophic cultures were explored to achieve a sustained ecological balance. Food, poultry and animal waste management, as well as a cooker factory, were included in the overall design. The environmental impact assessment (EIA) study shows a low risk due to anticipated net zero emissions, a 75% green city, and optimal waste recycling. This research assists in combining research efforts to address the challenging processes in nexus research and build resilient and sustainable water, energy, and food systems. Full article

The ongoing energy transition has changed the architecture of electricity networks in ways that conventional power transformers are not able to cope with the new required functionalities. For this purpose, the solid state transformer (SST), which comprises state of the art power electronics with galvanic isolation to interconnect two separate alternating current (AC) or direct current (DC) power grids, is considered to be the dominant solution. The purpose of this paper is to provide a practical, application-oriented review of the SST. In this context, the main functionalities and possible applications of the SST are presented, including smart grids (SGs), data centres, railways, offshore wind farms, etc. Furthermore, the main developed SST prototypes are analysed with special focus on the related projects, demonstrators, stakeholders and rated values, e.g., voltage, switching frequency and power. The analysis is concluded with the future trends and challenges regarding the wider implementation of SST technology in the electrical grid. Full article

With the rapid development of global offshore wind power, the demand for offshore wind power operation and maintenance is also increasing. This paper analyzes the technology of units, monitoring of deep wind field, and operation and maintenance risks and provides an innovative direction for offshore wind power operation and maintenance. In this study, the innovation of offshore wind power operation and maintenance are discussed in regard to the aspects of operation and maintenance management, the monitoring technology of units and far-reaching wind field monitoring and risks. Combined with information technology and lean management concept, this paper evaluates the development trend and difficulties of data mining and information platforms of offshore wind power operation and maintenance. A far-reaching intelligent operation and maintenance management platform for offshore wind farms is provided and a centralized and intelligent operation and maintenance management mode is explored in order to improve the efficiency and reduce the costs. Through the research on the characteristics of 5G technology, the typical application scenarios of 5G technology in the intelligent operation and maintenance of offshore wind farms are analyzed, which provide a new solution for the efficient operation and maintenance of offshore wind farms. Full article

The promising power-to-gas (P2G) technology makes it possible for wind farms to absorb carbon and trade in multiple energy markets. Considering the remoteness of wind farms equipped with P2G systems and the isolation of different energy markets, the scheduling process may suffer from inefficient coordination and unstable information. An automated scheduling approach is thus proposed. Firstly, an automated scheduling framework enabled by smart contract is established for reliable coordination between wind farms and multiple energy markets. Considering the limited logic complexity and insufficient calculation of smart contracts, an off-chain procedure as a workaround is proposed to avoid complex on-chain solutions. Next, a non-linear model of the P2G system is developed to enhance the accuracy of scheduling results. The scheduling strategy takes into account not only the revenues from multiple energy trades, but also the penalties for violating contract items in smart contracts. Then, the implementation of smart contracts under a blockchain environment is presented with multiple participants, including voting in an agreed scheduling result as the plan. Finally, the case study is conducted in a typical two-stage scheduling process—i.e., day-ahead and real-time scheduling—and the results verify the efficiency of the proposed approach. Full article

Wind-farm planning optimization is important for decision-making concerning regional energy planning in developing countries. This process is governed by restrictions on site selection based on land suitability metric variables, wind turbine technology variables, and land-use governing criteria. This study aims to create a framework for land appropriation strategies for locating optimum sites suitable for wind farms. It is using Jordan as an Area of Interest (AOI), where the scope is to illustrate how this framework will employ wind turbine energy to positively enhance the national Gross Domestic Product (GDP). The methodology employs thirteen GIS thematic layers with a 250-m spatial resolution to substantiate how site-specific criteria, turbine type, and turbine hub height variables are determining factors in the optimal solution. This method involves selecting relevant factors, database construction, data layer generation and preparation, numerical ranking and weighting of each factor, and computation of the potential wind farm locations map by overlaying all the thematic GIS layers. The results showed that the establishment of wind farms would not only meet the AOI’s growing energy needs, rather exceed them to generating income for the developing nation. The results of the feasibility study will boost the national GDP by 3.4%; where, for example, one governorate alone could produce 274.3% of the total required national consumption at a turbine hub height of 50 m. The study attests to a valuable framework that can be implemented elsewhere to establish regional power sustainability and feasibility for other nations. The results show that an added land-use layer indicating the potential value of land in terms of its suitability for establishing wind farms should be considered in future sustainable regional planning studies when considering networks for smart cities, industrial cities, smart agriculture, and new agglomerations. Full article

New technologies have the potential to transform agriculture and to reduce environmental impact through a green revolution. Internet of Things (IoT)-based application development platforms have the potential to run farm management tools capable of monitoring real-time events when integrated into interactive innovation models for fertirrigation. Their capabilities must extend to flexible reconfiguration of programmed actions. IoT platforms require complex smart decision-making systems based on data-analysis and data mining of big data sets. In this paper, the advantages are demonstrated of a powerful tool that applies real-time decisions from data such as variable rate irrigation, and selected parameters from field and weather conditions. The field parameters, the index vegetation (estimated using aerial images), and the irrigation events, such as flow level, pressure level, and wind speed, are periodically sampled. Data is processed in a decision-making system based on learning prediction rules in conjunction with the Drools rule engine. The multimedia platform can be remotely controlled, and offers a smart farming open data network with shared restriction levels for information exchange oriented to farmers, the fertilizer provider, and agricultural technicians that should provide the farmer with added value in the form of better decision making or more efficient exploitation operations and management. Full article

Currently, the Direct-Current (DC) microgrid has been gaining popularity because most electronics devices require a DC power input. A DC microgrid can significantly reduce the AC to DC energy conversion loss. However, a power grid may experience a line fault situation that may damage important household devices and cause a blackout in the power system. This work proposes a new line fault protection scheme for a DC microgrid system by using a battery energy storage system (BESS). Nowadays, the BESS is one of the most cost effective energy storage technologies for power system applications. The proposed system is designed from a distributed wind farm smart grid. A total of three off-shore wind farms provide power to the grid through a high voltage DC (HVDC) transmission line. The DC microgrid was modeled by a BESS with a bi-directional DC–DC converter, various DC-loads with step down DC–DC converters, a voltage source converter, and a voltage source inverter. Details of the control strategies of the DC microgrid are described. During the line fault situation, a transient voltage was controlled by a BESS. From the simulation analyses, it is confirmed that the proposed method can supply stable power to the DC grid, which can also ensure protection of several loads of the DC microgrid. The effectiveness of the proposed system is verified by in a MATLAB/SIMULINK^® environment. Full article

In this paper, the uncertainty of wind, solar and load; smart charging and discharging of plug-in hybrid electric vehicles (PHEVs) to and from various energy sources; and the coordination of wind, solar power, PHEVs and cost-emission are considered in the smart grid unit commitment (UC). First, a multi-scenario simulation is used in which a set of valid scenarios is considered for the uncertainties of wind and solar energy sources and load. Then the UC problem for the set of scenarios is decomposed into the optimization of interactive agents by multi-agent technology. Agents’ action is represented by a genetic algorithm with adaptive crossover and mutation operators. The adaptive co-evolution of agents is reached by adaptive cooperative multipliers. Finally, simulation is implemented on an example of a power system containing thermal units, a wind farm, solar power plants and PHEVs. The results show the effectiveness of the proposed method. Thermal units, wind, solar power and PHEVs are mutually complementarily by the adaptive cooperative mechanism. The adaptive multipliers’ updating strategy can save more computational time and further improve the efficiency. Full article

The technologies related to green energy, smart cities and similar areas being dynamically developed in recent years, face frequently problems of a computational nature rather than a technological one. The example is the ability of accurately predicting the weather conditions for PV farms or wind turbines. Another group of issues is related to the complexity of the computations required to obtain an optimal setup of a solution being designed. In this article, we present the case representing the latter group of problems, namely designing large-scale power-saving lighting installations. The term “large-scale” refers to an entire city area, containing tens of thousands of luminaires. Although a simple power reduction for a single street, giving limited savings, is relatively easy, it becomes infeasible for tasks covering thousands of luminaires described by precise coordinates (instead of simplified layouts). To overcome this critical issue, we propose introducing a formal representation of a computing problem and applying a multi-agent system to perform design-related computations in parallel. The important measure introduced in the article indicating optimization progress is entropy. It also allows for terminating optimization when the solution is satisfying. The article contains the results of real-life calculations being made with the help of the presented approach. Full article