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This paper is a review of research undertaken, and subsequent policy change enacted, in the years 2018 to 2022 regarding the integration of cooking loads and needs into modern energy planning. Building on an earlier paper which described how the dominant global approaches to tackling the enduring problem of biomass-fuelled cooking was failing, and how a new UK Aid programme (Oct 2018) would be seeking to intentionally change international energy policy towards cooking and enable a significant transition in energy use, in this paper we review whether this strategy is being adopted by researchers, governments, and the private sector across the world and whether it is likely to make a significant contribution to the fulfilment of Sustainable Development Goal 7. In particular, the call is for integrated planning of modern energy inclusive of cooking loads—the potential 'Mutual Support' that both can lend to each other. The review considers the international commitments made by donors and governments to this end, the research that positions the use of modern energy as a cost-effective proposition, the urbanisation and societal changes reinforcing such planning, and positions the review in the light of climate change and the need to reach net zero carbon by 2050. [ABSTRACT FROM AUTHOR]

The ageing of coal-fired power stations in South Africa has led to regular power outages. Therefore, the country will need to urgently increase its electricity capacity to meet further energy demand from growing urbanization and population growth. This challenge has increased interest in alternative energy sources, such as renewable energy (RE). South Africa is gradually implementing appropriate renewable energy practices, reducing carbon emissions, cleansing the air, and assuring a more sustainable future. This paper summarizes the availability, current state, and future potential of renewable energy choices in South Africa. This paper also evaluates specific policy measures and government actions aimed at eliminating barriers and increasing renewable energy deployment in the future. It also considers the South African network's specialized techno-economic analysis. The findings show that South Africa is still heavily reliant on coal, with 78% of the current installed capacity coming from coal power in 2022, compared to 9.3% for solar and wind energy. [ABSTRACT FROM AUTHOR]

This paper reviews the fundamentals of the thermoeconomic diagnosis theory. Thermoeconomic diagnosis is one of the main applications of the exergy cost theory used to identify the causes of additional resource consumption of a system due to inefficiencies in its components, published in the late 1990s. Thermoeconomic diagnosis has usually been applied to diagnose power plants with high consumption of fossil fuels and fixed production. However, it does not consider the final production and waste generation variation. In this paper, Circular Thermoeconomics is applied to analyze in depth the effect of malfunctions on additional waste generation and changes in the final output of the system. This new formulation can be applied to polygeneration systems, where there is a simultaneous variation of final products, and to process integration and industrial symbiosis, where a part of the waste generated by a plant could be reused in other processes or plants. [ABSTRACT FROM AUTHOR]

This paper presents a comparative analysis of different battery charging strategies for off-grid solar PV systems. The strategies evaluated include constant voltage charging, constant current charging, PWM charging, and hybrid charging. The performance of each strategy is evaluated based on factors such as battery capacity, cycle life, DOD, and charging efficiency, as well as the impact of environmental conditions such as temperature and sunlight. The results show that each charging strategy has its advantages and limitations, and the optimal approach will depend on the specific requirements and limitations of the off-grid solar PV system. This study provides valuable insights into the performance and effectiveness of different battery charging strategies, which can be used to inform the design and operation of off-grid solar PV systems. This paper concludes that the choice of charging strategy depends on the specific requirements and limitations of the off-grid solar PV system and that a careful analysis of the factors that affect performance is necessary to identify the most appropriate approach. The main needs for off-grid solar photovoltaic systems include efficient energy storage, reliable battery charging strategies, environmental adaptability, cost-effectiveness, and user-friendly operation, while the primary limitations affecting these systems encompass intermittent energy supply, battery degradation, environmental variability, initial investment costs, fluctuations in energy demand, and maintenance challenges, emphasizing the importance of careful strategy selection and system design to address these factors. It also provides valuable insights for designing and optimizing off-grid solar PV systems, which can help to improve the efficiency, reliability, and cost-effectiveness of these systems. [ABSTRACT FROM AUTHOR]

China will strive to achieve a 'dual carbon' target: 'carbon peak' by 2030 and 'carbon-neutral' by 2060. In this context, improving the efficiency of renewable energy and reducing the use of thermal power are important ways to achieve the target. Clean, efficient and large-capacity energy-storage technology is the key to improving the utilization rate of renewable energy. First, this paper proposes to use compressed-air energy-storage technology instead of the old energy-storage technology to build an economical and environmentally friendly comprehensive energy park capacity optimization configuration model. Second, this paper uses the newly proposed improved chicken swarm optimization algorithm to solve the model, which is more accurate and faster. Finally, this paper analyzes a comprehensive energy park in north-west China. Through case analysis, it can be seen that the average utilization rate of renewable energy can reach 73.87% through the model proposed in this paper, while the average power-abandonment rate is only 9.32%. [ABSTRACT FROM AUTHOR]

Clean, affordable, and efficient energy sources are inevitable for a sustainable world. Energy crisis, especially the poor access and affordability, demand–supply mismatches, energy inequality, and high dependence on non-renewable energy sources, are the challenges before the attainment of clean energy goals for sustainable development. The 5-year review from the adoption of sustainable development goals (SDGs) by using bibliometric and thematic analysis was conducted in this review. This review is a synthesis of 175 scientific papers on SDG 7. Policy reforms and better funding; technology innovation and inclusion; and economic growth, rapid promotion of renewable, and alternative fuels are the recommendations for the achievement of the energy goals. Future research on energy-related goals should focus on energy justice, policy reforms, energy poverty, poor affordability, off-grid transmissions, renewable energy sources, alternative fuels, reforms in the energy supply chain, and international cooperation for better implementation of projects and for attracting foreign capital and private funds. This paper invites the attention of practitioners, academicians, funding agencies, and international agencies to collaborate in the initiatives for a clean, green, and energized world. [ABSTRACT FROM AUTHOR]

The rising global energy demand necessitates innovative solutions for harnessing renewable energy sources. Solar ponds have received attention as they present a viable means to address this challenge by absorbing and storing solar radiation. This article provides a comprehensive review of solar pond technology, including its principles, applications, heat extraction mechanisms, and approaches to optimize performance, with special attention to the salt-gradient solar pond. Additionally, the article identifies challenges that currently hinder the large-scale adoption of solar pond technology and offers recommendations for future research. By providing a detailed analysis of the current trends and future research directions, this paper seeks to contribute to the ongoing efforts to improve these systems, exploring various approaches to increase their efficiency and make them more economical and environmentally sustainable. [ABSTRACT FROM AUTHOR]

South Africa possesses extremely rich renewable energy resources, including solar energy and wind energy, in spite of this, South Africa traditionally relies on coal as its primary energy source. Recently, South Africa confronted with severe electricity shortage. With pressure of power shortage and the transition to low- carbon energy, South Africa has been actively promoting the development of renewable energy, aiming to diversify its energy structure. China, as the world's leading country in the development and utilization of renewable energy, has long been committed to helping South Africa achieve renewable energy development. This article reviews the cooperation progress between China and South Africa in renewable energy, and provides an in-depth analysis of the challenges currently faced by both sides. To address such challenges, it is suggested to strengthen the design of top-level cooperation mechanisms, create diverse collaboration platforms, prioritize the exchange and collaboration of scientific talents. This paper aims to provide a typical reference for deepening renewable energy cooperation between China and South Africa. [ABSTRACT FROM AUTHOR]

The globe is now in ecological turmoil as a result of the unrelenting increase in global warming. As a result, governments worldwide are committing to decarbonizing the environment, with the United Arab Emirates (UAE) and the Kingdom of Saudi Arabia (KSA) playing an important role in this effort. Hence, this paper evaluates the nonlinear (asymmetric) impact of natural gas consumption on renewable energy consumption and economic growth in the KSA and the UAE utilizing data stretching from 1990 to 2020. The study also considers other drivers of renewable energy consumption and economic growth, such as trade openness and CO2 emissions. The study utilizes nonlinear autoregressive distributed lag (ARDL) to evaluate these associations. The outcomes of bounds nonlinear ARDL (NARDL), affirm the long-run association between the variables in both countries. The nonlinear results show that positive and negative shocks in natural gas consumption have a negative impact on renewable energy in both UAE and KSA. In contrast, positive and negative shocks in natural gas consumption impact economic growth positively. The study proposed vital policy recommendations based on these results. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Utilizing renewable energy (RE) sources can provide a realistic answer to the problem of many nations' energy needs. This paper reviews the current status of using RE to produce electricity in the Kingdom of Saudi Arabia (KSA). The primary aim of the review is to identify and analyze the solar- and wind-energy utilization, problems, and future trends in KSA while taking into account all relevant aspects, associated development hurdles, and suggested solutions. All involved parties will receive useful results and conclusions from a thorough examination and analysis of the pertinent literature that can assist them in understanding the potential of solar and wind energy, considering all the linked issues. [ABSTRACT FROM AUTHOR]

With the continuous increase in global energy demand and growing environmental awareness, the utilization of renewable energy has become a worldwide consensus. In order to address the challenges posed by the intermittent and unpredictable nature of renewable energy in distributed power distribution networks, as well as to improve the economic and operational stability of distribution systems, this paper proposes the establishment of an active distribution network capable of accommodating renewable energy. The objective is to enhance the efficiency of new energy utilization. This study investigates optimal scheduling models for energy storage technologies and economic-operation dispatching techniques in distributed power distribution networks. Additionally, it develops a comprehensive demand response model, with real-time pricing and incentive policies aiming to minimize load peak–valley differentials. The control mechanism incorporates time-of-use pricing and integrates a chaos particle swarm algorithm for a holistic approach to solution finding. By coordinating and optimizing the control of distributed power sources, energy storage systems, and flexible loads, the active distribution network achieves minimal operational costs while meeting demand-side power requirements, striving to smooth out load curves as much as possible. Case studies demonstrate significant enhancements during off-peak periods, with an approximately 60% increase in the load power overall elevation of load factors during regular periods, as well as a reduction in grid loads during evening peak hours, with a maximum decrease of nearly 65 kW. This approach mitigates grid operational pressures and user expense, effectively enhancing the stability and economic efficiency in distribution network operations. [ABSTRACT FROM AUTHOR]

Although the movement of people from rural to urban areas has caused the increased use of energy, the abundance of water resources can be made into a form of renewable energy known as hydroelectricity. As European countries are ranked as the first users and exporters of hydropower, the production of renewable energy in developed countries such as the Nordic region has caused great impacts on economic growth and human development. The importance of this paper is to investigate the relationship between hydroelectricity and the Human Development Index by depending on some variables such as urbanization, rule of law, corruption, trade openness, and GDP per capita from 2002 to 2021 in Nordic countries. The results were estimated depending on impulse response function after conducting the Vector autoregressive model (VAR) model and Granger causality test. Results showed a negative impact from hydro plants in the short run but a significant positive impact in the long run in Nordic countries. The long-term sustainment of Human Development Index (HDI) is due to policies limiting the immigration of labor as well as protection of energy use. Water batteries are gaining popularity across Europe and their implementation is near mandatory. [ABSTRACT FROM AUTHOR]

This paper is concerned with the impact on the global greenhouse effect issues and focus on comprehensive multi-indicator though analyze the relationship between CO2 emissions and real GDP, energy intensity, fraction of the renewable energy supply out of the total energy supply, and energy consumption from different sectors, including the agricultural, service, industrial and transport sectors. The panel data encompass all 37 Organization for Economic Co-operation and Development (OECD) member countries covering 20 years from 2000 to 2019 and divide into two subsamples, the first and second ten years, for comparison. The empirical results of all parameters track the sound progress of green growth trend in OECD countries in the second ten years (2010–2019). According to the OECD, green growth strategy had been acknowledged in OECD Ministerial Council Meeting in June 2009. Thus, the study divided into the first and second ten years with 2010 as the boundary to compare and the empirical result also indicates the green growth strategy in OECD countries have gradually matured in the last ten years. The implementation of the policy framework and measures includes pricing, removing perverse subsidies, ensuring the regulatory standards of energy efficiency, innovation, and infrastructure investments might also provide a reference and important information for energy policy makers. [ABSTRACT FROM AUTHOR]

DC power may be more efficient than AC power in certain applications, especially when it comes to local generation and storage. This is because AC power requires extra equipment to convert it to DC power, which can lead to energy losses. Using DC power, on the other hand, makes it easier for devices to use it directly, resulting in higher energy efficiency. Additionally, using DC power can reduce equipment capital costs as it eliminates the need for additional AC–DC conversion equipment. Finally, DC power systems can offer new communication capabilities, including plug-and-play for generation and storage devices, making it simpler to integrate these systems into existing infrastructure. This paper analyzes the optimal size of a photovoltaic/PEM fuel cell system to supply a certain DC commercial load in NEOM city. To identify the best size of the PV/PEMFC, minimizing the cost of energy (COE) and minimizing the net present cost (NPC) are considered. The paper studies three sizes of PEMFCs: 15 kW, 20 kW, and 25 kW. In addition, five different PV modules are selected: Axitec 450 Watt, Jinko 415 Watt, REC Solar 410 Watt, Seraphim 310 Watt, and Tongwei 415 Watt. The results of the study confirmed that the best size of the hybrid system comprises a 15 kW PEMFC, a 267 kW Tongwei PV array, a 60 kg electrolyzer, and a 20 kg hydrogen tank. Under these conditions, the COE and NPC are 0.293 USD/kWh and 498,984 USD, respectively. [ABSTRACT FROM AUTHOR]

The large-scale integration of renewable energy into the grid has led to a gradual diversification of power generation trading units on the power-side, with varying operational characteristics, costs, and trading needs among diverse power generation trading units. Traditional power system clearing models face challenges. Block order is a bidding type that allows for multiple volume–price combinations. At the same time, the randomness and volatility of renewable energy poses challenges to the safe and stable operation of the system. Building a power system clearing model that meets the diverse and flexible needs of the power system has become an important consideration. Therefore, this paper considers the design of three flexible energy blocks: a sustaining block, flux block, and adjustment block to meet the differential needs of diverse trading units and establishes a flexible block order clearing model. Secondly, it establishes a joint clearing model of electrical energy and frequency modulation (FM) to ensure the stable and reliable operation of the system, and solves the model based on relevant constraints to determine the winning electrical energy price and FM price. The CPLEX and Yalmip algorithms are used to solve the model. Finally, a case study was conducted based on an improved IEEE 14-bus system. The results showed that the model proposed in this paper can satisfy the differential needs of diverse trading units, effectively improve the renewable energy consumption capacity, and reduce the prices of the energy market and frequency modulation market. Also, the standard deviation of the net load of the system is relatively low, which improves the reliability of the power system's operation. [ABSTRACT FROM AUTHOR]

Recent trends prove that energy production is shifting from traditional fossil fuel combustion technologies to renewable energy-based technologies. To estimate the economic efficiency of renewable energy technology implementation, the data for the EU-27 member states during the 2012–2021 period were collected; additionally, technological efficiency was analyzed based on a critical literature review. Breusch and Pagan Lagrangian multiplier tests were employed to select the most suitable econometric model. The results suggest that an increase in the share of renewable energy sources by one percentage point (1) decreased CO2 emissions by 0.137 metric tons per capita (technological efficiency) and (2) decreased greenhouse gases by 13 g per EUR, in terms of GDP (economic efficiency). Regarding the Kyoto Protocol implementation, it was found for EU-27 that an increase in the share of renewable energy sources by one percentage point was related to a decrease of one percentage point in the greenhouse gases index. GDP per capita appeared to be an insignificant driver for reductions in per capita CO2 emissions, while it proved to be important for economic efficiency models. Thus, increasing GDP per capita by 1000 USD reduces greenhouse gases by 7.1 g per EUR of GDP in EU-27. This paper also confirmed that a unit of electricity (1 kWh) generated by traditional energy plants is seven to nineteen times more environmentally costly than renewable energy generation. This paper thus concludes that digital transformations and additive manufacturing brought about the significant dematerialization of industrial production and the promotion of renewable energy on industrial and household levels. [ABSTRACT FROM AUTHOR]

Renewable energy sources, which use natural sources to generate energy, are currently replacing conventional energy sources to fulfil the world's expanding energy demands. However, photovoltaic and wind energy, which are among these types of energy sources, are not steady and not available for 24 hours in a day. As an alternative, it is possible to extract and use hot water from the earth all the time. Therefore, this study proposes a thermoelectric generator that uses hot water from the hot spring area to generate free electricity as a new renewable energy source in a microgrid application. In this system, the microgrid is standalone without a battery storage system because the thermoelectric generator is in operation for 24 hours in a day (day and night). In this way, the cost of the battery is eliminated by removing it from the system. In this paper, a novel generation method is proposed in microgrid applications as a renewable energy source. In addition, load management system was implemented to control three types of residence loads. The main advantage of this study is to generate electricity from renewable sources like photovoltaic and thermoelectric to demand without much wasting energy by controlled loads according to the proposed load management algorithm. In this study, the microgrid and energy management control is modeled with MATLAB/Simulink. The results showed that the essential load is always active through thermos electric generator besides the absence of battery storage system. [ABSTRACT FROM AUTHOR]

The use of base station (BS) sleep modes is one of the most studied approaches for the reduction of the energy consumption of radio access networks (RANs). Many papers have shown that the potential energy saving of sleep modes is huge, provided the future behavior of the RAN traffic load is known. This paper investigates the effectiveness of sleep modes combined with machine learning (ML) approaches for traffic forecast. A portion of an RAN is considered, comprising one macro BS and a few small cell BSs. Each BS is powered by a photovoltaic (PV) panel, equipped with energy storage units, and a connection to the power grid. The PV panel and battery provide green energy, while the power grid provides brown energy. This paper examines the impacts of different prediction models on the consumed energy mix and on QoS. Numerical results show that the considered ML algorithms succeed in achieving effective trade-offs between energy consumption and QoS. Results also show that energy savings strongly depend on traffic patterns that are typical of the considered area. This implies that a widespread implementation of these energy saving strategies without the support of ML would require a careful tuning that cannot be performed autonomously and that needs continuous updates to follow traffic pattern variations. On the contrary, ML approaches provide a versatile framework for the implementation of the desired trade-off that naturally adapts the network operation to the traffic characteristics typical of each area and to its evolution. [ABSTRACT FROM AUTHOR]

In this paper, an event-triggered distributed secondary control, along with an energy management algorithm, was developed to ensure the voltage stability and power management of a DC microgrid containing batteries and renewable energy sources, such as PV systems and wind turbines. The energy management algorithm, employing fuzzy logic control, governs power flow based on the generation status of sources and the charging rate of the battery. Consequently, the control algorithm shields the battery from overcharging and over-discharging situations, simultaneously ensuring energy quality within the microgrid. Sampled-data-based event-triggered control is integrated into the proposed distributed secondary control to alleviate communication burdens between controllers, effectively avoiding Zeno behavior. To demonstrate the efficacy of the proposed control algorithm, several experimental studies were conducted on a real DC microgrid prototype. The results obtained confirmed the controller's effectiveness. With the proposed control algorithm, autonomous control has been developed to ensure the safe and continuous operation of loads in island-mode microgrids, incorporating PV systems, wind turbines, and batteries, while also minimizing communication overhead. This control system adeptly manages power flow, safeguards the battery against overcharging and over-discharging, and optimizes the efficiency of intermittent energy sources. [ABSTRACT FROM AUTHOR]

The smart grid paradigm has ushered in an era where modern distribution systems are expected to be both robust and interconnected in topology. This paper presents a techno-economic-based sustainable planning (TESP) strategy, which can be used as a planning framework for linked distribution systems, seeking to discover a realistic solution among competing criteria of diverse genres. In this comparative analysis-based study, three voltage stability assessment indices -- VSA_A, VSA_B, and VSA_W -- and a loss minimization condition (LMC)-based framework are used in the initial stage to achieve optimal distributed generation (DG)-based asset optimization for siting, followed by sizing. The respective techniques are evaluated across two variants of multiple load growth horizons spread across 10 years. The suggested TESP technique is tested on two variants of a mesh-configured microgrid (MCMG) with varied load growth scenarios. One variant considers a 65-bus MG with a fixed load growth of 2.7% across two load growth horizons. The other variant considers a 75-bus MG with varied load growth across four load growth horizons, encapsulating an expansion-based planning perspective. The numerical results of the suggested TESP approach in a comparative study demonstrate its effectiveness, and it can be used by researchers and planning engineers as a planning framework for interconnected distribution tools across multiple planning horizons. The proposed study would contribute to enhancing the robustness and interconnectivity of smart grid distribution systems. This dual focus could lead to more cost-effective and reliable power distribution systems. [ABSTRACT FROM AUTHOR]

Recently, renewable energy has emerged as an attractive means to reduce energy consumption costs for deep learning (DL) job processing in modern GPU-based clusters. In this paper, we propose a novel Renewable-Aware Frequency Scaling (RA-FS) approach for energy-efficient DL clusters. We have developed a real-time GPU core and memory frequency scaling method that finely tunes the training performance of DL jobs while maximizing renewable energy utilization. We introduce quantitative metrics: Deep Learning Job Requirement (DJR) and Deep Learning Job Completion per Slot (DJCS) to accurately evaluate the service quality of DL job processing. Additionally, we present a log-transformation technique to convert our non-convex optimization problem into a solvable one, ensuring the rigorous optimality of the derived solution. Through experiments involving deep neural network (DNN) model training jobs such as SqueezeNet, PreActResNet, and SEResNet on NVIDIA GPU devices like RTX3060, RTX3090, and RTX4090, we validate the superiority of our RA-FS approach. The experimental results show that our approach significantly improves performance requirement satisfaction by about 71% and renewable energy utilization by about 31% on average, compared to recent competitors. [ABSTRACT FROM AUTHOR]

This research introduces an innovative analytical framework for studying the behavior of electric vehicles (EVs) in power grids. The approach primarily examines the dynamic State of Charge (SOC) and energy reserves of EV batteries. By thoroughly examining patterns of EV charging demand and operational states (charging, discharging, idling, and waiting) across various time intervals, including day and night periods, this study aims to provide a comprehensive understanding of EV dynamic behavior in power networks. The proposed model goes beyond traditional assessments by incorporating human behavioral patterns and responsiveness to economic signals, specifically investigating the impact of electricity pricing on user behavior. The core analysis centers on exploring the Vehicle-to-Grid (V2G) concept, viewing EVs not only as energy consumers but also as potential contributors to grid stability and efficiency. The study delves into how the interplay of dynamic EV behavioral characteristics and owner responses to pricing influences the overall energy consumption curve of the grid, thereby shaping the capability of EVs in providing grid support services. To quantitatively validate the effectiveness of the model, a detailed case study is conducted, offering empirical evidence of its practical utility. The research findings are quantified, highlighting the significant implications for decision-makers, grid managers, and stakeholders in the energy sector. The paper emphasizes the main outcomes, demonstrating how the proposed analytical framework can empower stakeholders in making informed decisions about policy and infrastructure development. The robust methodological approach presented in this paper serves as a valuable tool for evaluating the impacts of adopting V2G, providing strategic insights for a more sustainable and economically viable paradigm [ABSTRACT FROM AUTHOR]

In recent times, the research in sustainable energy resources was integrated with the control approaches of various hybrid renewable energy systems for balancing the electricity generation. The accelerated hybrid energy storage systems and steadily growing energy consumption make the variability and the predictable behavior occur in the renewable energy sources, which requires an energy management system. This paper aims to control hybrid renewable energy systems for power management. The systems consist of photovoltaic (PV) arrays, diesel generators, wind systems with boost converter DC-DC, and inverters. The optimum of the real-time process is less due to prediction errors of multiple renewable sources, which track the output voltage and load current. Model predictive control (MPC) is proposed for problem-solving time operation to address this issue and compensate for the prediction error. The major impact factors, such as optimal split power, stability, reliability of energy, and desired dynamic responses, have been identified by applying the MPC technique. A simulation model has been constructed using MATLAB/Simulink environment to confirm the effectiveness of the MPC technique model. [ABSTRACT FROM AUTHOR]

The maritime Internet of Things (MIoT), a maritime version of the Internet of Things (IoT), is envisioned as a promising solution that can provide ubiquitous connectivity over land and sea. Due to the rapid development of maritime activities and the maritime economy, there is a growing demand for computing-intensive and latency-sensitive maritime applications requiring various energy consumption, communication, and computation resources, posing a significant challenge to MIoT devices due to their limited computational ability and battery capacity. Mobile Edge Computing (MEC), which can handle computation tasks at the network's edge more efficiently and with less latency, is emerging as a paradigm for fulfilling the ever-increasing demands of MIoT applications. However, the exponential increase in the number of MIoT devices has increased the system's energy consumption, resulting in increased greenhouse gas emissions and a negative impact on the environment. As a result, it is vital for MIoT networks to take traditional energy usage minimization into account. The integration of renewable energy-harvesting capabilities into base stations or MIoT devices possesses the potential to reduce grid energy consumption and carbon emissions. However, making an effective decision regarding task offloading and resource allocation is crucial for maximizing the utilization of the system's potential resources and minimizing carbon emissions. In this paper, we first propose a green MEC-enabled maritime IoT network architecture to flexibly provide computing-intensive and latency-sensitive applications for MIoT users. Based on the architecture, we formulate the joint task offloading and resource allocation problem by optimizing the total system execution efficiency (including the total size of completed tasks, task execution latency, and the system's carbon emissions) and then propose a deep-deterministic-policy-gradient-based joint optimization strategy to solve the problem, eventually obtaining an effective resolution through continuous action space learning in the changing environment. Finally, simulation results confirm that our proposal can yield good performance in system execution efficiency compared to other benchmarks; that is, it can significantly reduce the system's carbon emissions and tasks' delay and improve the total size of completed tasks. [ABSTRACT FROM AUTHOR]

This paper presents the planning of the potential and feasibility of a complete solar solution for the mess at the Shri Mata Vaishno Devi University (SMVDU) campus. Since there is ample space near the mess, solar steam generating plants are proposed on the mess to reduce liquified petroleum gas (LPG) consumption substantially. Forty concentrators (sixteen square meters each) are proposed to be installed. The project's life is proposed to be twenty-five years with a capital cost of USD 19.02 thousand and additional operation and maintenance costs. The financial analysis shows that the total savings from the project are USD 172.82 thousand with a cost-benefit ratio of 6.40. The project's break-even is approximated to be attained by the fortieth month of operation. Beyond the financial benefit, the project is proposed to have multiple other benefits to the institution. The benefits are that the use of fossil fuels (LPG) for cooking can be avoided by the installation of a thermal cooking system, it shall provide a better sustainability score in various rankings done worldwide for the university, the cost of tender of mess for future can be reduced drastically, the project will be brought up as a project that shall be displayed at every level in the union territory so that we shall promote the development of renewable energy uses. [ABSTRACT FROM AUTHOR]

As the issues of global energy crisis and climate change are becoming increasingly prominent in the world, urban microgrids have received widespread attention as an effective way to improve energy utilization efficiency and reduce environmental pollution. Among them, the cogeneration of heat and power (CHP) system is considered as one of the key technologies to improve the energy efficiency of urban microgrids because it can provide both electricity and heat. However, how to optimize the energy flow scheduling for CHP systems, especially in the context of increasing renewable energy sources, has become a hot topic of current research. Existing studies usually rely on the traditional dualtime-scale scheduling strategies, namely day-ahead scheduling and real-time scheduling, but both have obvious limitations in dealing with the uncertainty and volatility of new energy sources. To address the above problems, this paper proposes a thermodynamic analysis-based scheduling method for optimizing the energy flow in the CHP system of urban microgrids. First, this paper introduces the concepts of rolling schedule and real-time schedule to improve the traditional time-scale scheduling method, so as to enhance the system's adaptability to new energy power fluctuations. Second, for the absorption CHP system, this paper proposes a thermal cycle performance optimization strategy, which significantly improves the utilization efficiency of thermal energy through the cascaded recycling of system waste heat. Through these two innovations, this study not only realizes a more accurate and efficient energy management, but also provides a new strategy for the sustainable development of urban microgrids. [ABSTRACT FROM AUTHOR]

Developing countries in hot climate regions such as Saudi Arabia have witnessed rapid population growth, which has led to greater resource consumption as a result of the increased demand for new buildings. This research proposes a multi-objective evaluation of the potential green engineering solutions to conserve energy using a building within the ROSHN housing project, which is one of the mega projects in Saudi Arabia, as a case study for this paper with the aid of simulation software, taking into consideration the context of the sustainability concept. The results showed that traditional passive architectural design, whether courtyards or Mashrabiya, had the nearly greatest influence, with percentages ranging from −4% to −5.15% for varied parameters and designs compared to the base case energy usage. Furthermore, energy efficiency solutions for the building envelope's external insulation and finish system (EIFS) enabled a drop in the U-value that lowered energy usage to −5.40%. However, the wall insulation thickness beyond 300 mm in this system has no substantial influence on energy savings. This research's most clear finding is that a P2P system for PV panels on a district scale can supply enough energy to meet its needs after implementing the optimal strategy of the other proposed solutions. [ABSTRACT FROM AUTHOR]

To promote the use of renewable energy (RE), several types of RE policies have been implemented globally. Among these, feed-in tariff (FiT) is one of the most accepted mechanisms of pricing policy. However, choosing the best policy for a market with a high RE penetration is a challenge. A case of Bhutan is considered in this paper as the source of electrical energy is predominantly hydropower. Additionally, a generous subsidy is provided by the government to keep the electricity tariff to a minimum. Recently, there has been an increase in the advocacy and motivation for other forms of RE sources (RES) to supplement hydropower and increase energy security in Bhutan. Bhutan aims to achieve a total of 20 MW of non-hydro RES by 2025 as per the RE policy of Bhutan. However, Bhutan still does not have an RE pricing policy, and therefore, there is a need to institute a suitable pricing mechanism to accommodate the penetration of the planned non-hydro RES. This paper discusses the challenges in introducing FiT for non-hydro RES in an electricity market dominated by hydropower in Bhutan. Subsequently, recommendations are made in the wake of subsidised electricity tariff, which is the lowest in the region at 0.0171 USD/kWh for low voltage customers. FiTs for solar photovoltaic based on different categories of customers have been computed and proposed. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to determine the spatial spillover effects of renewable energy on carbon emissions in China's less-developed areas. However, few studies have considered this issue from the perspective of less-developed areas. Based on panel data of 21 provinces in China from 2000 to 2017, this paper analyzes the spatial spillover effects of renewable energy on carbon emissions using Moran's I and Spatial Durbin Model (SDM). The results suggest that, first, Moran's I ranges from 0.378 to 0.519, Moran scatter plot presents that provinces are located in the high–high (HH) and low-low (LL) quadrants, indicating provincial carbon emissions in the study area have a significant spatial correlation and agglomeration. Second, under the three matrices, the direct effect coefficients of renewable energy are -0.2522, -0.2639 and -0.2601, this shows that renewable energy is beneficial to local carbon emissions reduction. In contrast, the indirect effect coefficients of renewable energy are 0.0605, 0.1012 and 0.1125, which means higher renewable energy consumption in a single area is conducive to the improvement of carbon emissions to neighbouring areas. Third, urbanization, industrialization, physical capital and other variables have different impacts on local and nearby carbon emissions. This study provides empirical evidence to achieve carbon emission reduction targets by government policymakers. [ABSTRACT FROM AUTHOR]

In this paper, an Intelligent Energy Distribution System (IEDS) has been designed by using the Supervisory Control and Data Acquisition (SCADA) system, such as LabVIEW. The main purpose of this IEDS has been to optimize, according to the needs of the laboratory, the utilization of the energy produced by renewable sources in the installation and then distribute it rationally automatically. Thus, in the recommended approach, a Multi-Input Multi-Output (MIMO) Fuzzy Logic Controller (FLC) has been joined with a Fuzzy Logic Tuning Proportional, Integral, Derivative (FLTPID) controller to give a new typology of the controller, which is named fuzzy PID smart controller FPIDSC. Therefore, this paper has aimed to design a robust power management system based on a new strategy of control, to manipulate a hybrid system management. As a comparison result between three types of controllers, the On/Off controller, the FLC controller, and the proposed controller FPIDSC, the last one has given a decrease in the use of the grid by 6,7304% compared to the FLC controller, and 18,8934% compared to the On/Off controller. Furthermore, a, decrease energy loses by solar energy of 17% compared to the FLC controller and 41,325% compared to the On/Off controller. Based on the results obtained, the proposed controller has shown its efficiency compared to the controllers used in this study. [ABSTRACT FROM AUTHOR]

In the present energy scenario, wind energy is the fastest-growing renewable energy resource on the globe. However, wind-energy-based generation systems are also associated with increasing demands for power quality and active power control in the power network. With the advancements in power-electronics-based technology and its use in non-conventional energy conversion systems, it has witnessed tremendous growth in wind energy conversion systems (WECSs). At the same time, integrating wind farms into the grid system also results in many power quality issues in the power system that involve these renewable energy sources feeding power networks. This paper reports the effectiveness of grid-connected doubly fed induction generator (DFIG)-based WECS with a battery energy storage system (BESS) under variable wind conditions. In this study, a rotor side converter (RSC) is controlled to achieve the optimal torque for a given maximal wind power. The control scheme is simulated using MATLAB for a 2 MW-rated DFIG used in a WECS. Additionally, in this paper, a new fraction order proportional integral derivative (FOPID) controller is introduced into the system's RSC, and its performance is also observed. The BESS technique is used with a DC link to improve the overall performance of the DFIG-based WECS under different wind conditions. To control the BESS, a proportional integral (PI) controller is introduced to increase the charging and discharging rates. Two models are developed in MATLAB/Simulink: one model is a basic model, and other model is equipped with a BESS and a PI controller in the BESS. The results validate the effectiveness of the proposed PI-controller-equipped BESS at improving the overall performance of the WECS system under study. [ABSTRACT FROM AUTHOR]

Effective implementation of renewable energy sources (RES) is one of the main challenges in regard to the organization of local energy microgrids with buildings. One of the solutions is the use of dynamic building façades with photovoltaic (PV) panels, in particular the innovative perovskite solar cells (PSCs). This paper describes a case study performed on a pilot installation of perovskite PV panels located in Poland, Central-Eastern Europe. Results of preliminary measurements on this installation are provided in terms of verifying its energy efficiency and the possibility of selecting settings for the façade dynamics control system. Our experiments have considered the sun-tracking mechanism and its energy consumption as well as the impact of weather conditions at different times of the year. The energy efficiency results for the PV system, with average levels below 10%, are rather low. Therefore, even small energy savings in the operation of the PV system itself are significant. Changes in control scenarios for sun-tracking have been proposed and have obtained a reduction from 5% to 1% of energy consumption in autumn and from almost 3.2% to 0.6% in spring, in relation to overall energy produced by the PV system. The need for further experimental research from the perspective of the development and extension of the analyzed installation is pointed out as well. [ABSTRACT FROM AUTHOR]

The availability of energy is essential to support modern human activities worldwide, pushing global energy consumption to an unprecedented level within the last century. Several aspects, such as population, economy, greenhouse gas emissions (GHG) emission, gross domestic product, and labor growth, have a favorable relationship with energy consumption, which means an enlargement in energy consumption. On the other hand, distributed energy systems (DES) and renewable energy (RE) are popular alternative sources of energy production as part of the energy mix toward energy security and sustainability to tackle environmental issues. This paper aims to analyze and review the research trend of DES and RE in recent decades through bibliometric tools. Thus, the study addressed the following research questions: worldwide research’s prominent authors, relevant sources, the word associated with this research field, and thematic analysis through the Scopus database and Bibliohiny R-package. This work can help the academicians, researchers, and scientific community comprehend the study fields more rapidly. [ABSTRACT FROM AUTHOR]

One of the biggest causes of worldwide environmental pollution is conventional fossil fuel-based electricity generation. The need for cleaner and more sustainable energy sources to produce power is growing as a result of the quick depletion of fossil fuel supplies and their negative effects on the environment. Solar PV cells employ solar energy, an endless and unrestricted renewable energy source, to generate electricity directly. The optimum output, energy conversion efficiency, productivity, and lifetime of the solar PV cell are all significantly impacted by environmental factors as well as cell operation and maintenance, which have an impact on the cost-effectiveness of power generation. This article presents an analysis of recent research on the impact of operational and environmental factors on the performance of solar PV cells. It has been discovered that temperature and humidity, combined with dust allocation and soiling effect, have a significant impact on the performance of PV modules. In addition, particularly in the lonely places, the wind itself carries a lot of dust and sand particles. The situation gets worse when dust builds up in humid circumstances and produces tenacious, sticky mud on the PV cell, which lowers power output by up to 60–70%. This paper covers cutting-edge methods for reducing these elements' effects, along with their proportional benefits and difficulties. This paper also explains about the parameters which involved in the solar power production and their influence on the efficiency analysis. The efficiency and energy conversion capacity of the semi conducting materials for power production is also discussed. It is also discussed about the general benefits of the solar PV power generation. [ABSTRACT FROM AUTHOR]