Secure Energy Research Articles

Natural hydrogen in low temperature geofluids in a Precambrian granite, South Australia. Implications for hydrogen generation and movement in the upper crust

Natural hydrogen (H2) has the potential to be a low-carbon fuel and energy source, playing a crucial role in achieving a clean, secure, and affordable energy future. However, our understanding of the generation, migration, and accumulation of H2 in the subsurface remains poorly constrained. Increasing evidence suggests that H2 is abundantly and widely present in various geological settings, making them viable targets for exploration of this emerging resource. Reports have indicated the presence of hydrogen-dominated natural gas in vintage boreholes located in the Yorke Peninsula and Kangaroo Island, South Australia. These boreholes were drilled in Cambrian sedimentary cover over Precambrian terranes that host iron ore, copper or gold ore deposits. To gain insight into these occurrences, rock samples were examined from the Roxby Downs granite, a Mesoproterozoic pluton associated with the Hiltaba Suite event (1.59 Ga), belonging to the same magmatic origin as the Yorke Peninsula basement.Our investigation revealed metasomatic fluid circulation, evidenced by alteration of feldspar and mafic grains, as well as discrete cemented fractures within the granite. In some of these fracture-fill cements, we discovered water and gas inclusions containing hydrogen. The formation of the hydrogen-bearing cements occurred at paleo-temperatures ranging from 170 °C to the present-day 55 °C. Analysing the oxygen isotope values of the quartz cements and considering their fluid inclusion temperatures, a marine water signature as the source of water in equilibrium with the quartz cements was identified.To constrain the fluid history, neon and argon isotope signatures from the fluid inclusion gases were measured from the granite and separated quartz grains. Nucleogenic neon isotopes increased with depth along specific production lines. While this is consistent with long-lived fluid within the granite and increasing fluid residence with depth, separated quartz grains show less variation with depth and suggest that younger fluids were introduced, triggering alteration of less robust minerals, visible in bulk granite. Petrographic analyses identified hydrolytic alterations of mafic minerals into magnetite, and subsequently magnetite to hematite, as sources of hydrogen and contributors to the observed increase in pore water salinity. Our findings highlight that natural hydrogen can be produced and retained in granites at low temperatures, expanding beyond the commonly reported alteration processes observed in mafic and ultramafic rocks.

Contrasting Intermediate-Temperature La0.7Sr0.3VO3.86-⸹ (LSV) Porous Catalyst Elevated Sulfur Tolerance Using Gaseous and Liquid Fuel Explored through Experimental and Modeling Characterization Over Time

The U.S. Army is investigating Solid Oxide Fuel Cells (SOFCs), which can produce clean, secure, and sustainable energy to replace existing power sources. Today SOFCs are known to provide high density, high efficiency power with long term stability at low cost and environmental impact, utilizing a variety of naturally sourced fuels such as hydrogen, hydrocarbons, and alcohols. This fuel flexibility makes SOFCs attractive for use with multiple applications and helps bridge the gap between current hydrogen-fueled SOFC technologies and future hydrocarbon-fueled based use. Despite this potential, many technical hurdles remain, such as thermal stress cracking and coarsening, delamination, and catalyst contamination. Catalyst contamination is of particular concern for the U.S. Army, which operates on JP-8 kerosene-based fuel via AR-70 single fuel policy, as sulfur impurities commonly found in naturally sourced hydrocarbon-based fuels, can poison the catalyst, permanently degrading SOFC system performance, even at low concentrations. As the U.S. Army begins to investigate SOFCs to enable additional capabilities like silent watch, advanced radios, and exportable power in their fleet, catalyst poisoning from sulfur presents a concerning technology gap that must be addressed, especially since it is also possible that sulfur contaminated fuel, scavenged in theater, may be used, and could contain elevated levels (>300ppm) of sulfur.While lower temperature SOFC operation is also actively being pursued to help alleviate physical material degradation issues, with the introduction of hydrocarbon-based fuels, catalyst development to reduce sulfur poisoning degradation also needs further exploration. This study continues to experimentally and theoretically investigate the response of sulfur tolerant anode catalyst La0.7Sr0.3VO3.86-⸹ (LSV) at currently targeted SOFC intermediate operating temperatures (400-600°C). We have previously investigated low and moderate hydrogen sulfide (H2S) concentrations (30ppm, 300ppm) in balance hydrogen and methane gas environments for up to 100 hours. In this work, LSV showed significant sulfur tolerance in hydrogen and methane balance gases when compared to the industry standard Ni-YSZ anode, where sulfur adsorption rates were 278-287x lower in some cases. The lowest rates occurred between 600-700°C, which is attributed to the cubic structure the material presents in this temperature range. Higher adsorption rates were observed in the monoclinic/tetragonal structure the material presents at temperatures between 400-500°C. Average adsorption rates were overall higher in methane. When compared against Ni-YSZ, which is known to accumulate sulfur from hydrogen sulfide via two-step dissociative adsorption, LSV was observed to accumulate sulfur through weak chemisorption (H2S*, 0.43 eV max) of molecular hydrogen sulfide on oxygen deficient surfaces and one-step dissociative adsorption (H2S*, 0.34 eV, max, HS*+H*, 8.34 eV, max) on oxygen sufficient surfaces. The weak chemisorption behavior on oxygen deficient surfaces is attributed to the reduced oxygen stoichiometry of the material, in which only vanadium V2+/3+ couples exist. Overall, molecular adsorption/dissociation was observed to occur near strontium defects on LaO/SrO terminations. The propensity of H2S adsorption on LSV surfaces was observed to be significantly less for oxygen deficient LSV, and significantly higher for oxygen sufficient LSV, when compared to H2S adsorption calculations on Ni (100) surfaces, which follow a two-step dissociative adsorption reaction (H2S* → HS*+H* → H*+S*), resulting in a strongly adsorbed S* species (5.96 eV, max).Under the Army’s single fuel policy, it is more likely SOFCs would be fueled using hydrogen and/or methane, which are both gases, however SOFCs in the future could also be directly fueled using liquid alcohol fuels, or as scavenged from theater. Typical small alcohol molecules (methanol or ethanol) do not contain high concentrations of sulfur; however, alcohols can be contaminated with sulfur-containing hydrocarbons. This work will investigate sulfur adsorption using methanol contaminated with 300ppm thiophene using the same operating temperature and heating duration conditions with hydrogen and methane. These results will be contrasted against the 300ppm H2S hydrogen and methane results previously reported. Figure 1

(Digital Presentation) SOFC - Enabler for Highly Efficient Power Generation

SOFC technology offers power generation with very high efficiencies > 60 %. This leads to a high future demand for decentralized power generation for a secure energy supply.Based on the current extreme load shedding in South Africa, the SOFC System industrialization between AVL and Mitochondria will be presented.In addition, SOFC in marine applications will be discussed:In April 2018, the IMO Marine Environment Protection Committee (MEPC) adopted a first strategy to reduce greenhouse gas emissions from international shipping. The first strategy defined the following targets: Reduce CO2 emissions by 40% by 2030 and by 70% by 2050 compared to 2008 levels, and reduce total greenhouse gas emissions from shipping by at least 50% by 2050.For some applications, fuel cell technologies for propulsion and auxiliary power are seen as one of the most promising solutions to achieve not only decarbonization but also other emission reduction targets in maritime transport. Fuel cell systems are considered serious competitors to internal combustion engines for several reasons: high electrical efficiency of 60% at about 25% load, low emissions, and nearly silent operation

Current Status, Future Prospects, and the Need for Geothermal Energy Exploration in Cameroon: Comprehensive Review

Cameroon is a country in Central Africa that relies heavily on hydropower, fossil fuels, solar, and biomass for its energy needs. However, the unstable and intermittent nature of these energy sources makes them unreliable, and there is a pressing need for a more secure and sustainable energy supply. Geothermal energy, which is abundant in Cameroon due to its favorable geological characteristics, has not been fully explored as a potential energy source. This study is aimed at providing a comprehensive review of the current status and future prospects of geothermal energy in Cameroon, based on publications related to geothermal energy in Cameroon, geological, and geophysical studies. The objectives of this study are to analyze the existing literature on geothermal energy in Cameroon, to identify the challenges and opportunities associated with geothermal energy development, and to make recommendations for future research and policy decisions. The results indicate that geothermal energy in Cameroon is still in its infancy, with limited research and development in the field. However, the country has geothermal potential, particularly in the Adamawa and Cameroon volcanic line (CVL) areas. The review highlights the challenges and barriers to geothermal energy development in Cameroon, including limited financial resources, technical expertise, and regulatory frameworks. The findings of this study suggest that Cameroon has significant potential for geothermal energy development, and that further exploration and investment in this area could contribute significantly to a more secure and sustainable energy supply in the country.

The Impact of International Relations Patterns on China’s Energy Security Supply, Demand, and Sustainable Development: An Exploration of Oil Demand and Sustainability Goals

This study explores the impact of international relations on China’s energy security and supply/demand dynamics, specifically focusing on new energy sources and technological advancements. Given China’s status as the world’s largest energy consumer, achieving a balance between energy supply, demand, and sustainable development is crucial. This study quantifies the influence of international relations on the energy market, particularly the uncertainties arising from geopolitical events and international tensions that affect energy supply and prices. The research findings indicate that, in a long-term cointegrated relationship, a 1% change in the geo-political risk (GPR) index leads to a 0.229% change in China’s crude oil imports. Additionally, the impact of China’s GDP growth, carbon emissions, and sustainable energy consumption is −2.176, 0.723, and 0.167, respectively. This study also discusses the reasons behind the differential impact of crude oil prices on the United States and China. Recognizing the interplay between China’s energy security and international relations is vital for effective policy formulation. This study provides valuable insights for policymakers and stakeholders to ensure a sustainable and secure energy future.

An optimal load curtailment method for operational risk assessment of integrated electricity, natural gas and heating systems

The rapid development of gas-fired generators and combined heat and power (CHP) units promotes the wide application of integrated electricity, natural gas and heating systems (IEGHSs). IEGHSs bring many opportunities to energy supply systems, but also produce huge challenges for ensuring secure and reliable energy supply. Therefore, it is indispensable to investigate the risk assessment for IEGHS operations, especially considering the complexity of system operations. First, a steady-state system model of IEGHSs is developed and linearized taking into account system operation characteristics, including generator operation constraints and the flexibility of CHP units. To reduce computation complexity, an optimal load curtailment method using a mixed integer linear programming algorithm is proposed, which considers both energy types and consumer importance of IEGHSs. Moreover, a contingency set based on the N-1 guideline is constructed taking into account the failures of IEGHSs with high probability. Additionally, the risk indices of IEGHSs are developed in two hierarchies: contingency level and system level. Furthermore, the operational risk of IEGHSs under the constructed contingency set is quantitatively evaluated using the proposed load curtailment method and the developed risk indices. Finally, case studies demonstrate the necessity of operational risk assessment and the effectiveness of the proposed method.

Sustainable energy transition in Bangladesh: Challenges and pathways for the future

AbstractThe industrial development of a country plays a vital role in its overall progress and is closely tied to its capacity of electricity generation. However, the scarcity of natural resources and increasing costs of fuel in global markets pose significant challenges for developing countries like Bangladesh in managing the rising expenses of electricity generation. Consequently, the government of Bangladesh is exploring alternative energy resources such as solar, wind, hydroelectricity, biomass, and biogas to supplement fossil fuels and optimize electricity generation cost. This paper aims to provide a comprehensive overview of the current status of natural resources, including gas, coal, and oil, which are conventionally used for electricity generation in Bangladesh. It highlights concerns about dwindling resource availability and their impact on the country's energy landscape. Through numerical analysis, it demonstrates the detrimental effects of relying heavily on gas‐based power plants, leading to electricity supply instability. To address the ongoing energy crisis, the paper proposes the adoption of renewable energy sources as a viable solution. Additionally, it also acknowledges the challenges associated with implementing large‐scale renewable projects in distinct areas of the country, such as limited infrastructure, technical constraints, and the need for significant investment. Overcoming these barriers is crucial for achieving widespread utilization of renewable resources. This paper concludes by offering recommendations to overcome these challenges and maximize the contributions of renewable energy in meeting future energy demands. The suggestions include developing robust infrastructure, implementing policy reforms to attract investment, emphasizing research and development, and promoting community engagement in renewable energy initiatives. It also highlights the potential of renewable energy resources in shaping a more secure and sustainable energy future for Bangladesh, emphasizing the importance of electricity generation for socio‐economic development.

Blockchain-Based Microgrid for Safe and Reliable Power Generation and Distribution: A Case Study of Saudi Arabia

Energy demand is increasing rapidly due to rapid growth and industrialization. It is becoming more and more complex to manage generation and distribution due to the diversification of energy sources to minimize carbon emissions. Smart grids manage reliable power generation and distribution efficiently and cater to a large geographical area and population, but their centralized structure makes them vulnerable. Cybersecurity threats have become a significant concern with these systems’ increasing complexity and connectivity. Further transmission losses and its vulnerability to the single point of failure (SPOF) are also major concerns. Microgrids are becoming an alternative to large, centralized smart grids that can be managed locally with fewer user bases and are safe from SPOF. Microgrids cater to small geographical areas and populations that can be easily managed at the local level and utilized for different sources of energy, like renewable energy. A small group of consumers and producers are involved, but microgrids can also be connected with smart grids if required to exchange the excess energy. Still, these are also vulnerable to cybersecurity threats, as in the case of smart grids, and lack trust due to their decentralized nature without any trusted third party. Blockchain (BC) technology can address the trust and cybersecurity challenges in the energy sector. This article proposes a framework for implementing a BC-based microgrid system for managing all the aspects of a microgrid system, including peer-to-peer (P2P) energy trading, Renewable Energy Certificate (REC), and decentralized energy trading, that can be utilized in the case of Saudi Arabia. It can integrate cybersecurity standards and protocols, as well as the utilization of smart contracts, for more secure and reliable energy generation and distribution with transparency.

Blockchain based secure energy trading in V2G infrastructure

Blockchain based secure energy trading in V2G infrastructure

The role of eco-innovation, renewable energy consumption, economic risks, globalization, and economic growth in achieving sustainable environment in emerging market economies.

In the last two decades, environmental degradation has been a topic of concern. The rising level of CO2 emissions (CO2E) has adversely affected life in the E7 countries, which comprise of Brazil, China, India, Indonesia, Mexico, Russia, and Turkey. The increased in CO2E is the cause of rising sea levels in the E7 countries. Visibly, E7 nations which are considered as the largest emitters of CO2 are facing the most severe environmental challenges. This study investigates the impact of eco-innovation, economic growth (EG), renewable energy consumption (REC), economic risk (ERI), and globalization on the CO2E, using the Feasible Generalized Lease Squares (FGLS) and Panel Corrected Standard Errors (PCSE) techniques for the period 1995 to 2018. The results indicate an inverted N-shaped relationship between eco-innovation and CO2E. Also, eco-innovation, REC, and economic risk are observed to be significant factors in abating CO2 emissions. On the contrary, globalization and GDP are responsible for rising CO2E in E7 countries. According to empirical estimates, eco-innovation improves the efficiency of carbon emissions, which lowers CO2E. In addition, because they are immune to changes in the price of oil and gas and disruptions brought about by geopolitical events, renewable energy sources can offer countries a more secure energy source than fossil fuels. Alternative energy sources can reasonably cut CO2E while offering a more reliable and secure energy source. Therefore, it is crucial that policies be put in place to cut CO2E by giving priority to environmental innovative policies.

Optimal management of an energy-water-carbon nexus employing carbon capturing and storing technology via downside risk constraint approach

The development of infrastructures in a sustainable manner ensures the preservation of human life. It means that societies should have constant access to clean energy and water resources. The focus on nexus planning and operation including renewable energy sources has covered the requirements for the development of sustainable integrated systems to provide secure energy and water while minimizing carbon footprint. However, the uncertainty of renewable energy resources challenges the operation of such integrated nexuses. In this regard, this paper proposes a risk-constrained operation of a sustainable energy-water nexus with the aim to reduce operational costs as well as carbon dioxide (CO2) emissions amount (t CO2). To supply the energy and water demands, a combination of renewable energy sources and desalination systems are considered. The downside risk constraint is proposed to investigate the impacts of risks of uncertainties associated with renewable energy production and electricity consumption as well as water demands. Electrical and water storage infrastructures are involved to increase the flexibility of scheduling and ensure affordability and sustainability. The problem is modeled as a mixed-integer programming problem resulting in optimal decision-making to manage the energy/water resources and storage systems to provide clean and safe energy and water with the minimum CO2 emission. For the emission sector, the carbon capturing and storing (CCS) technology is proposed to capture the CO2 defusing by the energy sector and resolve the carbon-related issues. To restrict carbon production, both CO2 taxes and cap policies are examined and the results showed that the latter has a considerable effect to incentivize the decision-maker to use CCS technology.

DESLR: Energy-efficient and secure layered routing based on channel-aware trust model for UASNs

Underwater acoustic sensor networks (UASNs) have garnered significant interest and have found widespread applications in smart ocean applications and auxiliary navigation. Nevertheless, UASNs encounter a multitude of challenges due to the constraints of the underwater environment, such as high energy consumption, secure transmission, and dynamic network topology in uncertain conditions. In this paper, we propose an energy-efficient and secure layered routing method (DESLR) for UASNs to enhance energy efficiency and improve transmission reliability. The DESLR establishes a channel-based trust model which considers factors of direct trust and indirect trust to describe the behaviors of nodes. In order to effectively identify malicious nodes, great consideration is given to the state of the acoustic channel’s reliability, as varying channel conditions can significantly impact packet transmission. An improved Ant Colony Optimization Algorithm (ACOA) is introduced to discover energy-efficient and low-latency routing paths by balancing energy consumption and routing distance. Additionally, DESLR utilizes a Layered Clustering method to group nodes into clusters and a two-layer fuzzy logic approach to select cluster heads (CH) that avoid hotspots and ensure uniform energy distribution. Simulation results demonstrate that DESLR can effectively detect defective nodes by analyzing anomalous behaviors and outperforms other related work in terms of energy consumption, average end-to-end delay, and packet loss.

Secure cross-layer routing protocol with authentication key management scheme for manets

MANET (Mobile ad-hoc networks) is typically a no-infrastructure multi-hop network where every node interacts with other network nodes either indirectly or directly via intermediate nodes. A lot of research is being undertaken to save the energy of mobile nodes at different levels. Power-relevant issues can have an effect on every layer of the stack, making the traditional layered approach ineffective. In this work, cross layered routing protocol based on PSO (Particle swarm optimization) with adapted contention window technique is proposed. To form consistent and energy efficient routing paths, PSO algorithm uses Traffic index, Average energy load, data success rate & trust value parameters that are computed from network layer. After establishing routing paths, network's contentions are measured MAC layers for communications and contention with measured contentions and average energy loads. The trust of nodes is computed using the following constraints: group trust-provided by neighbour nodes & quality trust-computed by node QoS. Dual authentications with EnDA (enhanced dual authentication) using key management strategies for enhanced data security and integrity. ECC (Elliptical curve cryptography) and Diffie-Hellman key exchanges with bilinear maps improve security of communications. The suggested protocol when measured in terms of energy usage and secure key agreements during network's transmissions, showed satisfactory performances.

Secure Energy Aware Optimal Routing using Reinforcement Learning-based Decision-Making with a Hybrid Optimization Algorithm in MANET

Mobile ad hoc networks (MANETs) are wireless networks that are perfect for applications such as special outdoor events, communications in areas without wireless infrastructure, crises and natural disasters, and military activities because they do not require any preexisting network infrastructure and can be deployed quickly. Mobile ad hoc networks can be made to last longer through the use of clustering, which is one of the most effective uses of energy. Security is a key issue in the development of ad hoc networks. Many studies have been conducted on how to reduce the energy expenditure of the nodes in this network. The majority of these approaches might conserve energy and extend the life of the nodes. The major goal of this research is to develop an energy-aware, secure mechanism for MANETs. Secure Energy Aware Reinforcement Learning based Decision Making with Hybrid Optimization Algorithm (RL-DMHOA) is proposed for detecting the malicious node in the network. With the assistance of the optimization algorithm, data can be transferred more efficiently by choosing aggregation points that allow individual nodes to conserve power The optimum path is chosen by combining the Particle Swarm Optimization (PSO) and the Bat Algorithm (BA) to create a fitness function that maximizes across-cluster distance, delay, and node energy. Three state-of-the-art methods are compared to the suggested method on a variety of metrics. Throughput of 94.8 percent, average latency of 28.1 percent, malicious detection rate of 91.4 percent, packet delivery ratio of 92.4 percent, and network lifetime of 85.2 percent are all attained with the suggested RL-DMHOA approach.

Retracted: Effects of Novel Material Field Effect Transistor for Heterogeneous Energy and Traffic-Aware Secure Applications

Retracted: Effects of Novel Material Field Effect Transistor for Heterogeneous Energy and Traffic-Aware Secure Applications

Proof of Evaluation-based energy and delay aware computation offloading for Digital Twin Edge Network

The increasing availability of Internet of Things (IoT) applications has led to the development of new technologies. Specifically, the deployment of edge servers close to IoT devices has strengthened the edge computing paradigm. With the collaboration of Mobile Edge Computing (MEC) and cloud computing, delay-sensitive and computation-intensive tasks can be offloaded to the edge/cloud servers to improve system performance in terms of the delay and energy consumption of IoT devices. However, there is a need to schedule the computation tasks for an efficient management. More importantly, the task scheduling strategy can face data tampering attacks to deliberately modify, destroy or manipulate the decisions. To solve the above problems, in this paper, we newly propose to integrate digital twin and blockchain into the edge networks. However, it is unclear (i) how energy and delay-aware computation should be combined, and (ii) which mining computations should be executed for a secure task scheduling. The state-of-the-art focuses on task scheduling and blockchain mining, separately. Therefore, we propose a novel blockchain-based digital twin-edge network architecture where our proposed algorithm solves these two challenges at the same execution. We design a three-layer system architecture, composed of physical entity layer, digital twin edge layer and blockchain layer. In the physical entity layer, we formulate an energy and delay-aware task scheduling problem. In the digital twin edge layer, we propose a novel Proof of Evaluation (PoE)-based secure energy and delay-aware task scheduling algorithm where optimization is executed by the genetic algorithm implementation of Warehouse Location Problem (WLP). In the blockchain layer, the best-found solutions are shared with the topology in a blockchain. Here, each block includes the hash of the previous block, a genetic algorithm-based solution, nonce value, and a hash of whole blocks in the blockchain. Thus, we aim to execute the computation tasks with an acceptable delay in an energy-efficient manner and prevent data tampering attacks against the optimal computation decisions. We validate the outcomes of our PoE-based secure digital twin-edge network model with extensive evaluations. Since the proposed model distributes the task not only to the local device but also to the MEC and cloud server for delay awareness, it reduces the delay but consumes more energy. Nevertheless, the additional energy consumption can be neglected against the delay reduction. The proposed scheme is also more scalable to compare with the conventional solution. The numerical results clearly show that the proposed model provides energy and delay awareness, maintaining both data integrity and trustworthiness at the same execution of algorithm.

Next-power: Next-generation framework for secure and sustainable energy trading in the metaverse

The rapid emergence of the Metaverse as a leading virtual digital technology is driving innovation in power generation. The increasing demand for sustainable energy and the rise of the Metaverse has provided an opportunity to develop a secure and sustainable energy trading system using Smart Grid (SG), Virtual Power Plants (VPP), Digital Twins (DT), and Blockchain. Integrating VPP with SG can optimize the utilization of distributed energy resources and improve the stability and reliability of the energy supply in the metaverse. Meanwhile, the use of DT can facilitate the efficient management of VPPs by simulating their behavior and performance to identify potential issues and test different scenarios for improvement. Blockchain is a rising technology that enables decentralized and trustworthy applications, making it a promising tool for creating decentralized energy trading systems in the Metaverse. In this context, we propose Next-Power, a next-generation framework for secure and sustainable energy trading in the Metaverse. Next-Power consists of: (1) an automated blockchain-based fair payment of energy traded between consumers and prosumers in the Metaverse, it uses Ethereum’s smart contracts to determine the price at which energy is traded using a cooperative game theory (i.e., reverse auction); (2) an access token-based blockchain system that ensures a secure mutual authentication between consumers and prosumers; and (3) a lightweight on-chain collaborative reputation scheme that keeps track of prosumers reputation as well as consumers credibility in the Metaverse in a fully decentralized manner. The system of Next-Power is implemented, tested, and deployed on the Ethereum official test network. Next-Power is a promising framework for the future of energy trading in the Metaverse, as demonstrated by its successful experimental results in terms of flexibility, efficiency, security, and cost-effectiveness.

Modeling the Development of Energy Network Software, Taking into Account the Detection and Elimination of Vulnerabilities

This paper solves the problem of modeling the scheme for developing software systems, which can be used in building solutions for secure energy networks. A development scheme is proposed in a set of representations through which each program of the software complex passes, namely the following representations: idea, conceptual model, architecture, algorithm, source code, graphic code, abstract syntax tree, assembler code, machine code, byte code, executed code. The main properties of each representation are indicated, such as the form (text, graphic, programming language, binary, and decoded), development (transformation) methods, as well as vulnerabilities that are detected in it. An example of each representation is given, particularly as applied to the energy networks. The scheme elements (representations, vulnerabilities, forms, etc.) and the main operations for working with their elements (representation transformation, vulnerability injection, and detection) are presented in an analytical form. An example of a development scheme for a simple software complex of energy networks is given. The classification of vulnerabilities is introduced; it divides the vulnerabilities according to the structural level, functioning disruption, and information impact. The vulnerabilities in each of the views are substantiated using the common vulnerabilities and exposures (CVE) database. An experiment was conducted to demonstrate the vulnerability spread across representations during the development of a software complex example for the energy network. The features of the applications of the obtained results for energy networks are taken into account. The advantages, disadvantages, and limitations of the study, as well as ways to eliminate them, are discussed.

Development of renewable energy system for low power underwater devices

Underwater sensor networks (UWSNs) are an emerging field in the research area as they have potential applications starting from pollution monitoring to defense and ocean exploration. Ocean monitoring is of great importance in marine scientific research. However, battery-operated devices utilized in such systems have limited power and maintenance is difficult. So, devices used underwater suffer from many research challenges and energy issues. Apart from all the problems, harvesting energy underwater is the main limiting factor. Nonrenewable energies come from sources that may not be replenished in our lifetime. Hence, it is very much essential to use renewable energy sources. Ocean has an unlimited amount of energy like wind energy, solar power, and tidal energy. Obtaining sufficient energy is sort of difficult since devices are underwater. Researchers are continuously working on it. Water energy is quite environmentally friendly, and it is a sustainable solution for a secure energy system. This paper implements a renewable energy system using piezoelectric (PZT) sensor, which generates sufficient power for lowpower underwater devices by employing two stage amplifier circuits. Experimental outcome shows the proposed energy harvesting system can generate a maximum voltage of 10.6 V and current of 10.1 mA which is sufficient to run low power underwater device.

Effect of geopolitical risk and economic uncertainty indices on renewable energy

In this study, the relationships between five renewable energy sub-sectors markets and the geopolitical risk (GPR) and economic uncertainty indices (EUI) were examined using daily data from March 30, 2012, to April 1, 2022. Convergent cross mapping results show that the renewable energy indices have definite relationships with the GPR and EUI. The renewable energy indices show differences in response directions, speed and trends for a standard information difference impulse from the GPR and the EUI. A positive dynamic conditional correlation between renewable energies and EUI was observed in the first and second waves of the COVID-19 outbreak. In contrast, there was a relatively decreased effect for two risk indices during the Russia–Ukraine conflict of February–March 2022. Our results show that renewable energy may act as a time-varying hedge against economic uncertainty and GPR owing to its safe-haven properties at various scales. Moreover, building more secure and reliable renewable energy systems can help countries to increase their energy independence, which protects them against the risks of political and economic uncertainty.